ublic Disclosure Authorized
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DISTORTIONS
47769
AFRICA
TO AGRICULTURAL
INCENTIVES
IN
Editors
Kym Anderson • William A. Masters
DISTORTIONS TO
AGRICULTURAL
INCENTIVES
IN AFRICA
DISTORTIONS TO
AGRICULTURAL
INCENTIVES
IN AFRICA
Kym Anderson
and William A. Masters, Editors
Washington, D.C.
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ISBN: 978-0-8213-7652-2
eISBN: 978-0-8213-7664-5
DOI: 10.1596/978-0-8213-7652-2
Library of Congress Cataloging-in-Publication Data
Distortions to agricultural incentives in Africa / edited by Kym Anderson and William A. Masters.
p. cm.
Includes bibliographical references and index.
ISBN 978-0-8213-7652-2 — ISBN 978-0-8213-7664-5 (electronic)
1. Agriculture—Economic aspects—Africa. 2. Agriculture and state—Africa 3. Agricultural subsidies—
Africa. 4. Africa—Economic policy. I. Anderson, Kym. II. Masters, William A.
HD2118.D57 2008
338.1'86—dc22
2008037334
Dedication
To the authors of the country case studies, for their narratives and for generating the
time series of distortion estimates that underpin the studies.
CONTENTS
Foreword
xvii
Acknowledgments
xxi
Contributors
xxiii
Abbreviations
xxix
Map: The Focus Economies of Africa
xxxi
PART I
INTRODUCTION
1
1
Introduction and Summary
Kym Anderson and William A. Masters
3
PART II
NORTH AFRICA
69
2
Arab Republic of Egypt
James Cassing, Saad Nassar, Gamal Siam, and Hoda Moussa
71
PART III SOUTHERN AFRICA
99
3
Madagascar
Fenohasina Maret
101
4
Mozambique
Andrea Alfieri, Channing Arndt, and Xavier Cirera
127
5
South Africa
Johann Kirsten, Lawrence Edwards, and Nick Vink
147
6
Zambia
Peter Robinson, Jones Govereh, and Daniel Ndlela
175
7
Zimbabwe
Daniel Ndlela and Peter Robinson
205
vii
viii
Contents
PART IV EASTERN AFRICA
229
8
Ethiopia
Shahidur Rashid, Meron Assefa, and Gezahegn Ayele
231
9
Kenya
Alex Winter-Nelson and Gem Argwings-Kodhek
253
10
Sudan
Hamid Faki and Abdelmoneim Taha
283
11
Tanzania
Oliver Morrissey and Vincent Leyaro
307
12
Uganda
Alan Matthews, Pierre Claquin, and Jacob Opolot
329
PART V
WESTERN AFRICA
359
13
Cameroon
Ernest Bamou and William A. Masters
361
14
Côte d’Ivoire
Philip Abbott
385
15
Ghana
Jonathan Brooks, Andre Croppenstedt,
and Emmanuel Aggrey-Fynn
413
16
Nigeria
Peter Walkenhorst
441
17
Senegal
William A. Masters
463
18
Benin, Burkina Faso, Chad, Mali, and Togo
John Baffes
485
Appendix A: Methodology for Measuring Distortions
to Agricultural Incentives
Kym Anderson, Marianne Kurzweil, Will Martin,
Damiano Sandri, and Ernesto Valenzuela
507
Appendix B: Annual Estimates of Distortions to
Agricultural Incentives in Africa
Ernesto Valenzuela, Marian Kurzweil, Johanna Croser,
Signe Nelgen, and Kym Anderson
539
Index
607
Contents
Figures
1.1
NRAs in Agriculture, 16 African Countries, 1975–79
and 2000–04
1.2
NRAs, by Key Covered Product, 21 African Focus Countries,
1975–79 and 2000–04
1.3
NRAs for Exportable, Import-Competing, and All Farm
Products, 16 African Countries, 1955–2004
1.4
Gross Subsidy Equivalents of Assistance to Farmers,
16 African Countries, 1975–79 and 2000–04
1.5
Gross Subsidy Equivalents of Assistance to Farmers in 21 African
Focus Countries, by Product, 1975–79 and 2000–04
1.6
NRAs for Agricultural and Nonagricultural Tradables and
the RRA, 16 African Countries, 1955–2004
1.7
RRAs in Agriculture, 16 African Countries, 1975–79
and 2000–04
1.8
NRAs and RRAs, Asia, Africa, and Latin America,
1965–2004
1.9
Real GDP Per Capita, Comparative Advantage, and NRAs
and RRAs, 16 African Countries, 1955–2005
1.10
Relationship between the RRA and the Trade Bias Index for
Agriculture, 16 African Focus Countries, 1975–79 and 2000–04
2.1
Product Shares of Agricultural Output, Egypt,
1955–2005
2.2
NRAs for Exportable, Import-Competing, and All
Agricultural Products, Egypt, 1955–2005
2.3
NRAs for Nonagricultural and Agricultural Tradables and
the RRA, Egypt, 1955–2005
3.1
NRAs for Exportable, Import-Competing, and All Covered
Farm Products, Madagascar, 1955–2003
3.2
NRAs for All Agricultural and Nonagricultural Tradables
and the RRA, Madagascar, 1955–2003
4.1
Real GDP, Mozambique, 1970–2004
4.2
Shares of the Value of Primary Agricultural Production at
Distorted Prices, Covered Products, Mozambique, 1976–2003
4.3
NRAs for Exportable, Import-Competing, and All Covered
Farm Products, Mozambique, 1976–2003
4.4
NRAs for Agricultural and Nonagricultural Tradables and
the RRA, Mozambique, 1976–2003
5.1
NRAs for Exportable, Import-Competing, and All Covered
Farm Products, South Africa, 1961–2005
5.2
NRAs for Agricultural and Nonagricultural Tradables and
the RRA, South Africa, 1961–2005
ix
23
25
28
39
42
44
48
49
50
61
75
81
84
112
121
130
135
140
140
163
167
x
6.1
6.2
6.3
7.1
7.2
8.1
8.2
8.3
8.4
9.1
9.2
9.3
9.4
9.5
10.1
10.2
10.3
10.4
10.5
11.1
11.2
12.1
Contents
NRAs for Exportable, Import-Competing, and All Covered
Farm Products, Zambia, 1961–2004
NRAs for Agricultural and Nonagricultural Tradables
and the RRA, Zambia, 1961–2004
Maize and Maize Meal CTEs and Consumer Subsidy Payment,
Zambia, 1955–2004
NRAs for Exportable, Import-Competing, and All Covered
Farm Products, Zimbabwe, 1955–2004
NRAs for Agricultural and Nonagricultural Tradables
and the RRA, Zimbabwe, 1955–2004
Food Availability and Food Gap by Political Regime,
Ethiopia, 1961–2002
Farmers’ Share of Export Prices for Coffee, Oilseeds, and
Pulses, Ethiopia, 1981–2005
NRAs for Exportable and All Farm Products, Ethiopia,
1981–2005
NRAs for Agricultural and Nonagricultural Tradables and
the RRA, Ethiopia, 1981–2005
Agricultural Value Added, Marketed Production, and GDP
Per Capita, Kenya, 1965–2004
Product Shares of Agricultural Production and Consumption,
Kenya, 1960–2004
NRAs for Exportable, Import-Competing, and All Covered
Farm Products, Kenya, 1956–2004
NRAs for Agricultural and Nonagricultural Tradables and
the RRA, Kenya, 1956–2004
NRAs for Producers of Export Crops, Kenya,
1956–2004
Share of Agriculture in All Merchandise Exports, Sudan
1961–2004
Value of Agricultural Imports as a Share of Value
of Agricultural Exports, Sudan, 1961–2004
Product Shares of Agricultural Exports, Sudan,
1961–2004
NRAs for Exportable, Import-Competing, and All Farm
Products, Sudan, 1955–2004
NRAs for All Agricultural and Nonagricultural Tradables
and the RRA, Sudan, 1955–2004
NRAs for Exportable, Import-Competing, and All Farm
Products, Tanzania, 1976–2004
NRAs for All Agricultural and Nonagricultural Tradables
and the RRA, Tanzania, 1976–2004
Parallel Market Exchange Rate Premium over the Official
Exchange Rate, Uganda, 1961–2004
181
187
188
214
218
236
241
242
243
256
258
263
268
269
286
286
287
298
300
322
324
338
Contents
12.2
12.3
12.4
13.1
13.2
13.3
13.4
13.5
14.1
14.2
14.3
15.1
15.2
15.3
15.4
16.1
16.2
16.3
16.4
17.1
17.2
17.3
17.4
17.5
Coffee and Cotton NRAs, Uganda, 1961–2004
NRAs for Exportable, Import-Competing, and All Farm
Products, Uganda, 1961–2004
NRAs for Agricultural and Nonagricultural Tradables and
the RRAs, Uganda, 1961–2004
Per Capita Output of Food and Nonfood Farm Products,
Cameroon and All Sub-Saharan Africa, 1961–2005
Composition of Farm Production at Distorted Prices,
Cameroon, 1966–2003
Foreign Exchange Rates, Cameroon
NRAs for Exportable and All Covered Farm Products,
Cameroon, 1961–2005
NRAs for Agricultural and Nonagricultural Tradables and
the RRA, Cameroon, 1961–2004
Share of Agricultural Production at Undistorted Domestic
Prices, Côte d’Ivoire, 1961–2005
NRAs for Exportable, Import-Competing, and
All Farm Products, Côte d’Ivoire, 1961–2005
NRAs for Agricultural and Nonagricultural Tradables and
the RRA, Côte d’Ivoire, 1961–2005
Cocoa Production and Producer Prices, Ghana, 1964–2002
Composition of Farm Production at Distorted Domestic
Price, Covered Products, Ghana, 1966–2003
NRAs for Exportable, Import-Competing, and All Farm
Products, Ghana, 1955–2004
NRAs for Agricultural and Nonagricultural Tradables and
the RRA, Ghana, 1955–2004
Composition of Farm Production at Distorted Producer
Prices, Nigeria, 1967–2003
NRAs for Exportable, Import-Competing, and All Farm
Products, Nigeria, 1961–2004
NRAs for Agricultural and Nonagricultural Tradables
and the RRA, Nigeria, 1961–2004
Black Market Premium over Official Exchange Rate,
Nigeria, 1960–2004
Net Merchandise Trade, Senegal, 1961–2004
Foreign Exchange Rates, Senegal, 1960–2005
Wholesale and Undistorted Prices, Selected Crops,
Senegal, 1961–2004
NRAs for Exportable, Import-Competing, and All Farm
Products, Senegal, 1961–2005
NRAs for Agricultural and Nonagricultural Tradables
and the RRA, Senegal, 1961–2005
xi
342
349
353
370
371
373
376
378
391
406
408
427
430
433
435
444
451
453
454
465
476
478
478
482
xii
18.1
A.1
A.2
Contents
International Price and Grower Price for Cotton,
Burkina Faso, 1970–2005
A Distorted Domestic Market for Foreign Currency
Distorted Domestic Markets for Farm Products
Tables
1.1
Key Economic and Trade Indicators, 21 African Focus
Countries, 2000–04
1.2
Poverty in Africa, Asia, and the World, 1981–2004
1.3
Growth of Real GDP and Exports, 21 African Focus
Countries, 1980–2004
1.4
Exports as a Share of GDP, 21 African Focus Countries,
1975–2004
1.5
Sectoral Shares of GDP, 21 African Focus Countries,
1965–2004
1.6
Agriculture’s Share in Employment, 21 African Focus
Countries, 1965–2004
1.7
Sectoral Shares in Merchandise Exports, 21 African
Focus Countries, 1965–2004
1.8
Index of Revealed Comparative Advantage in
Agriculture and Processed Food, 21 African Focus
Countries, 1965–2004
1.9
Export Orientation, Import Dependence, and Self-Sufficiency
in Primary Agricultural Production, 16 African Focus
Countries, 1965–2004
1.10
NRAs in Agriculture, 16 African Focus Countries,
1955–2004
1.11
Dispersion of NRAs across Covered Agricultural Products,
16 African Focus Countries, 1955–2004
1.12
NRAs for Key Covered Farm Products, 21 African
Focus Countries, 1955–2004
1.13
NRAs in Agriculture Relative to Nonagricultural Industries,
16 African Focus Countries, 1955–2004
1.14
NRAs for Exportable and Import-Competing Farm
Products, and the Trade Bias Index, 16 African
Focus Countries, 1955–2004
1.15
NRAs for Covered Farm Products, by Policy Instrument,
21 African Focus Countries, 1955–2004
1.16
Gross Subsidy Equivalents of Assistance to Farmers,
21 African Focus Countries, 1955–2004
1.17
Gross Subsidy Equivalents of Assistance to Farmers in Africa,
Key Covered Products, 1955–2004
503
511
530
7
8
9
10
12
13
14
15
16
22
24
27
29
31
36
37
40
Contents
1.18
1.19
1.20
1.21
2.1
2.2
2.3
3.1
3.2
4.1
4.2
5.1
5.2
6.1
6.2
7.1
7.2
8.1
8.2
8.3
9.1
9.2
10.1
10.2
11.1
11.2
12.1
RRAs for Agriculture, 16 African Focus
Countries, 1955–2004
NRAs and Some of Their Determinants, 21 African Focus
Countries, 1960–2004
CTEs for Covered Farm Products, 21 African Focus
Countries, 1960–2004
Value of CTEs of Policies Assisting Producers of Covered Farm
Products, 21 African Focus Countries, 1965–2004
NRAs and CTEs for Covered Farm Products,
Egypt, 1955–2005
NRAs in Agriculture Relative to Nonagricultural
Industries, Egypt, 1955–2005
Costs of Consumer Food Subsidies, Egypt, 1990–2005
NRAs for Covered Farm Products, Madagascar, 1966–2003
NRAs in Agriculture Relative to Nonagricultural
Industries, Madagascar, 1966–2003
NRAs for Covered Farm Products, Mozambique, 1976–2003
NRAs in Agriculture Relative to Nonagricultural Industries,
Mozambique, 1976–2003
NRAs for Covered Farm Products, South Africa, 1961–2005
NRAs in Agriculture Relative to Nonagricultural
Industries, South Africa, 1961–2005
NRAs for Covered Farm Products, Zambia, 1961–2004
NRAs in Agriculture Relative to Nonagricultural Industries,
Zambia, 1961–2004
NRAs for Covered Farm Products, Zimbabwe, 1955–2004
NRAs in Agriculture Relative to Nonagricultural
Industries, Zimbabwe, 1955–2004
Economic Growth and Structural Changes, Ethiopia,
1961–2004
NRAs for Covered Farm Products, Ethiopia, 1981–2005
NRAs for Agriculture Relative to Nonagricultural
Industries, Ethiopia, 1981–2005
NRAs for Covered Farm Products, Kenya, 1956–2004
NRAs in Agriculture Relative to Nonagricultural
Industries, Kenya, 1956–2004
NRAs for Covered Farm Products, Sudan, 1955–2004
NRAs in Agriculture Relative to Nonagricultural
Industries, Sudan, 1955–2004
NRAs for Covered Farm Products, Tanzania, 1976–2004
NRAs for Agriculture Relative to Nonagricultural
Industries, Tanzania, 1976–2004
NRAs for Covered Farm Products, Uganda, 1961–2004
xiii
45
52
54
57
80
83
94
114
120
138
139
165
168
182
186
215
217
235
239
240
264
267
297
299
319
323
348
xiv
12.2
13.1
13.2
14.1
14.2
15.1
15.2
15.3
16.1
16.2
16.3
17.1
17.2
17.3
18.1
18.2
18.3
B.1
B.2
B.3
B.4
B.5
B.6
B.7
B.8
B.9
B.10
B.11
B.12
B.13
B.14
B.15
B.16
Contents
NRAs for Agriculture Relative to Nonagricultural
Industries, Uganda, 1961–2004
NRAs for Covered Farm Products, Cameroon, 1961–2004
NRAs for Agriculture Relative to Nonagricultural
Industries, Cameroon, 1961–2004
NRAs for Covered Farm Products, Côte d’Ivoire, 1961–2005
NRAs for Agriculture Relative to Nonagricultural Industries,
Côte d’Ivoire, 1961–2005
Trade and Exchange Rate Performance, Ghana, 1966–2004
NRAs for Covered Farm Products, Ghana, 1955–2004
NRAs for Agriculture Relative to Nonagricultural
Industries, Ghana, 1955–2004
NRAs for Covered Farm Products, Nigeria, 1961–2004
NRAs for Agriculture Relative to Nonagricultural
Industries, Nigeria, 1961–2004
Structure of Annual Household Expenditure by Income
Quintile, Nigeria, 2004
Food Balance Sheet Data, Senegal, 1961 and 2003
NRAs for Covered Farm Products, Senegal, 1961–2004
NRAs for Agriculture Relative to Nonagricultural
Industries, Senegal, 1961–2004
Summary Statistics for Cotton-Producing Countries of
West and Central Africa, 2001–03
Cotton Price Statistics, West and Central African
Countries, 1970–2005
NRAs for Cotton Growers, Benin, Burkina Faso, Chad,
Mali, and Togo, 1970–2005
Annual NRA Estimates, Benin, 1970–2005
Annual NRA Estimates, Burkina Faso, 1970–2005
Annual NRA Estimates, Cameroon, 1961–2004
Annual NRA Estimates, Chad, 1970–2005
Annual NRA Estimates, Côte D’Ivoire, 1961–2005
Annual NRA Estimates, Arab Republic of Egypt, 1955–2005
Annual NRA Estimates, Ethiopia, 1981–2005
Annual NRA Estimates, Ghana, 1955–2004
Annual NRA Estimates, Kenya, 1956–2004
Annual NRA Estimates, Madagascar, 1961–2003
Annual NRA Estimates, Mali, 1970–2005
Annual NRA Estimates, Mozambique, 1976–2003
Annual NRA Estimates, Nigeria, 1961–2004
Annual NRA Estimates, South Africa, 1961–2005
Annual NRA Estimates, Senegal, 1961–2004
Annual NRA Estimates, Sudan, 1955–2004
352
375
377
405
407
420
432
434
450
452
459
467
479
481
488
501
502
541
542
543
545
546
547
549
550
552
554
555
556
558
560
564
565
Contents
B.17
B.18
B.19
B.20
B.21
B.22
B.23
B.24
B.25
B.26
B.27
B.28
B.29
B.30
Annual NRA Estimates, Tanzania, 1976–2004
Annual NRA Estimates, Togo, 1970–2005
Annual NRA Estimates, Uganda, 1961–2004
Annual NRA Estimates, Zambia, 1961–2004
Annual NRA Estimates, Zimbabwe, 1955–2004
Annual NRA Estimates for Covered Farm Products,
African Focus Countries, 1955–2005
Annual NRAs for Exportable, Import-Competing,
and All Covered Farm Products, for Nonagricultural
Tradables, and for the RRAs, 16 African Focus
Countries, 1955–2005
Annual Value Shares of Agricultural Production for Farm
Products, African Focus Countries, 1955–2005
Gross Subsidy Equivalents of Assistance to Farmers, African
Focus Countries, 1955–2004
Share of the Regional Value of Agricultural Production,
16 African Focus Countries, 1955–2004
Summary of NRA Data for 21 African Focus Countries
Summary of NRA Data by Major Product, African
Focus Countries, 2000–04
Shares of the Global Volume of Consumption
and Production of Covered Agricultural Products,
African Focus Countries, 2000–04
Shares of the Global Value of Imports and Exports
of Covered Agricultural Products, 16 African Focus
Countries, 2000–03
xv
567
569
570
572
574
576
584
586
592
596
599
600
602
604
FOREWORD
One of every two people in Sub-Saharan Africa survives on less than $1.25 a day.
That proportion has changed little over the past three decades, unlike in Asia and
elsewhere, so the region’s share of global poverty has risen from one-tenth to
almost one-third since 1980. About 70 percent of today’s 400 million poor Africans
live in rural areas and depend directly or indirectly on farming for their livelihoods.
While that rural share was even higher in the past (for example, 75 percent in
1993), it means policies affecting the incentives for farmers to produce and sell
farm products remain a major influence on the extent of Africa’s poverty.
During the 1960s and 1970s, many African and other developing countries had
in place pro-urban, anti-agricultural, and anti-trade policies, while many highincome countries restricted agricultural imports and subsidized their farmers.
Both sets of policies harmed African farmers. Although progress has been made
over the past two decades to reduce those policy biases, including the antiagricultural bias in Africa, the extent of reform has not been systematically
quantified. Nor has it been clear how many trade- and welfare-reducing price
distortions remain in African agriculture, both within and between countries, and
to what extent there continues to be an anti-trade bias within agriculture.
To help fill this lacuna, the World Bank launched a major research project in
2006 aimed at quantifying the changing extent of distortions to agricultural
incentives since the 1950s. This volume is one of a series of four regional books
that summarize the findings. By including most of the large African economies as
case studies, the focus countries cover about 90 percent of the agricultural value
added, farm households, total population, and total GDP of Sub-Saharan Africa.
The Arab Republic of Egypt, the most populous and poorest country in North
Africa, is also included.
xvii
xviii
Foreword
The case studies help address questions such as the following: Where is there
still a policy bias against agricultural production? To what extent are some farmers
now being protected from import competition? What are the political economic
forces behind the more-successful reformers, and how do they compare with
those in less-successful countries where major distortions in agricultural incentives remain? How important have domestic political forces been in bringing
about reform, as compared with international forces? What explains the crosscommodity pattern of distortions within the agricultural sector of each country?
What policy lessons and trade implications can be drawn from these differing experiences with a view to ensuring better growth-enhancing and poverty-reducing
outcomes in the study’s focus countries and in the region’s other (mostly smaller
and poorer) economies?
In Africa, the anti-agricultural and anti-trade policy biases worsened during
the 1960s and 1970s, and the policy reforms since then have been less dramatic
and more sporadic than in Asia, which has contributed to Africa’s rising share of
global poverty. One of the continent’s greatest achievements has been the phasing
out of agricultural export taxes over the past quarter-century. However, alongside
that, agricultural protection from import competition has limited the decline in
anti-trade bias within the farm sector. That has added to the cost of living for net
buyers of food, who constitute the majority of the poor who survive on less than
$1.25 a day: 30 percent of the poor live in urban areas, but a sizeable share of the
other 70 percent are also net buyers of food, including farmers who grow cash
crops for export.
The new empirical indicators summarized in these case studies provide a
strong evidence-based foundation for assessing the successes and failures of policies of the past and for evaluating policy options for the years ahead. The analytical narratives reveal that the reforms to agricultural price and trade policies were
sometimes undertaken unilaterally, but in other cases they were also partly in
response to international pressures, including structural adjustment loan conditionality by international financial institutions in the 1980s.
The study is timely because the World Trade Organization (WTO) is in the
midst of the Doha round of multilateral trade negotiations, and agricultural policy reform is one of the most contentious issues in those talks. To date, the countries of Africa have taken defensive positions in those negotiations. This has
included a reluctance to reform policies that lead to high prices for staple foods,
even though those policies may be harming those urban and rural poor who are
net buyers of food. Available evidence suggests that problems of rural-urban
poverty gaps have been alleviated in parts of Africa and Asia by some of the moremobile members of farm households finding full- or part-time work off the farm
Foreword
xix
and repatriating part of their higher earnings to those remaining in farm households. Efficient ways of assisting any left-behind groups of poor (nonfarm as well
as farm) households include public investment measures that have high social
payoffs, such as in basic education and health and in rural infrastructure, as well
as in agricultural research and development. As argued in the World Bank’s World
Development Report 2008, the latter also provides more sustainable and more
equitable ways of securing domestic food supplies than artificially propping up
prices.
Justin Yifu Lin
Senior Vice President and Chief Economist
The World Bank
ACKNOWLEDGMENTS
This book provides an overview of the evolution of distortions to agricultural
incentives caused by price, trade, and exchange rate policies in a large sample of
African countries. Following the introduction and summary chapter, it includes
commissioned country studies of 16 individual African economies plus one
covering the cotton-exporting countries of West and Central Africa. The chapters
are followed by two appendixes: one provides the methodology used to measure
the nominal and relative rates of assistance to farmers and the taxes and subsidies
on food consumption; the other provides country and regional summaries of
annual estimates of these rates of assistance. In addition to including the largest
North African economy (the Arab Republic of Egypt), the studied countries
account for about 90 percent of Sub-Saharan Africa’s agricultural value added,
farm households, total population, and total gross domestic product.
To the authors of the country case studies, who are listed on the following
pages, we are extremely grateful for the dedicated way in which they delivered far
more than we could have reasonably expected. Staff of the World Bank’s Africa
Department, especially Sector Manager Karen Brooks, provided generous and
insightful advice and assistance throughout the project, including through participating in a Bank-wide seminar on the draft studies. So too did the World Bank’s
country directors of the studied countries when they cleared the working paper
versions of each chapter. We have also benefited from the feedback provided by
many participants at workshops and conferences in which drafts have been presented over the past year or so. Johanna Croser, Francesca de Nicola, Esteban Jara,
Marianne Kurzweil, Signe Nelgen, Damiano Sandri, and Ernesto Valenzuela generously assisted in compiling material for the opening overview chapter, and
Johanna Croser and Marie Damania assisted in the initial copyediting of the
country chapters.
xxi
xxii
Acknowledgments
Our thanks extend to the project’s Senior Advisory Board, whose members
have provided sage advice and much encouragement throughout the planning
and implementation stages of the project. The Board comprises Yujiro Hayami,
Bernard Hoekman, Anne Krueger, John Nash, Johan Swinnen, Stefan Tangermann, Alberto Valdés, Alan Winters, and, until his untimely death in 2008, Bruce
Gardner.
Our thanks go also to the Development Research Group of the World Bank and
to the trust funds of the governments of Ireland, the Netherlands, and the United
Kingdom for financial assistance. This support made it possible to include this set
of economies in a wider study that covers more than 20 other developing countries, 18 economies in transition from central planning, and 20 high-income
countries. Three companion volumes examine case studies of other emerging
economies in a similar way and for a similar time period (back to the mid-1950s
or early 1960s, except for the transition economies). These World Bank publications cover East and South Asia (coedited by Kym Anderson and Will Martin),
Latin America and the Caribbean (coedited by Kym Anderson and Alberto
Valdés), and Eastern Europe and Central Asia (coedited by Kym Anderson and
Johan Swinnen). A global overview volume, edited by Kym Anderson, will be
published in 2009.
Kym Anderson and William A. Masters
November 2008
CONTRIBUTORS
Philip Abbott is a professor in the Department of Agricultural Economics at
Purdue University. He earned a PhD in economics from the Massachusetts
Institute of Technology in 1976 and has been at Purdue since 1981. He conducts
research on both international trade and international agricultural development.
Emmanuel Aggrey-Fynn is the director of the Statistic Research and Information
Directorate of the Ministry of Food and Agriculture in Ghana, a post he has held
for eight years. He has written numerous reports and studies and has served on or
chaired several national committees and boards.
Andrea Alfieri is an economist at the Directorate of Studies and Policy Analysis
within the Ministry of Planning and Development in Mozambique. At the time of
writing, he was working as a trade policy advisor at the Ministry of Industry and
Trade of Mozambique. He was previously an Overseas Development Institute
fellow at the Ministry of Agriculture.
Kym Anderson is the George Gollin Professor of Economics at the University of
Adelaide and a fellow of the Center for Economic Policy Research, London. During
2004–07, he was on an extended sabbatical, serving as lead economist (trade
policy) in the Development Research Group of the World Bank in Washington, DC.
Gem Argwings-Kodhek is coordinator of the Kenyan government’s Agricultural
Sector Coordinating Unit, which coordinates reform across four agricultural
ministries and implements Kenya’s Strategy for Revitalizing Agriculture, which he
coauthored. He is an agricultural economist on secondment from Tegemeo
Institute of Egerton University.
xxiii
xxiv
Contributors
Channing Arndt is a professor of economics at the University of Copenhagen,
following a three-year period based in Maputo, Mozambique. His publications
cover poverty measurement, trade policy, macroeconomic implications of
HIV/AIDS, agricultural productivity growth, and demand-systems estimation.
Meron Assefa is a PhD candidate in agricultural economics at Virginia Polytechnic
Institute and State University. She received her master’s degree in economics from
Addis Ababa University. Before starting graduate school, she worked for the World
Bank and the International Food Policy Research Institute in Addis Ababa.
Gezahegn Ayele is a senior research fellow and the head of the agriculture and rural
development directorate at the Ethiopian Development Research Institute. He has
served as a senior scientist at the Ethiopian Agricultural Research Organization
and as country coordinator and team leader of the International Food Policy
Research Institute’s 2020 Vision Initiatives for Africa.
John Baffes is a senior economist with the Development Prospects Group of the
World Bank. His responsibilities include commodity market monitoring and
price projections for tropical commodities, as well as research on market structure
and policy reform issues. Since joining the Bank in 1993, he has worked in
Bangladesh and Mexico.
Ernest Bamou is a professor of economics at the University of Yaoundé II and
principal economist in the Economics Department of the Ministry of Economy
and Finance in Cameroon. He has held visiting positions at the International
Monetary Fund, the World Bank, and the Free University of Amsterdam.
Jonathan Brooks is a senior economist in the Trade and Agriculture Directorate of
the Organisation for Economic Co-operation and Development. His recent work
has focused on the links between agricultural and trade policy reforms and
poverty. During this project, he was seconded to the Food and Agriculture
Organization in Rome and continues to collaborate with colleagues there.
James Cassing is a professor of economics at the University of Pittsburgh. He has
held visiting positions at the International Monetary Fund, the Australian
National University, Bar-Ilan University in Tel Aviv, and the Bologna Center of
Johns Hopkins University in Italy. He has also served as senior trade analysis
advisor to the government of Indonesia.
Xavier Cirera is a research fellow at the Institute of Development Studies at the
University of Sussex. He was an advisor on trade research issues at the National
Contributors
xxv
Directorate of Studies and Policy Analysis, Ministry of Planning and Development, Mozambique. He was also an ODI fellow at the Ministry of Industry and
Trade in Mozambique.
Pierre Claquin is a graduate student and research assistant in the Economics
Department of Trinity College in Dublin, Ireland.
André Croppenstedt is an economist with the Agricultural Development Economics Division of the Food and Agriculture Organization. Before joining FAO
in 1999, he worked for the Centre for the Study of African Economies at Oxford
University and at Addis Ababa University.
Johanna Croser has been a consultant with this project and is a PhD student in the
Department of Economics of the University of British Columbia in Vancouver.
Lawrence Edwards is an associate professor in the School of Economics at the University of Cape Town. He works in the field of international trade, focusing on
economic adjustments to trade liberalization; international competitiveness; and
trade, technology, and labor.
Hamid Hussein Mohamed Faki is a research professor and the director of the Agricultural Economics and Policy Research Center, Agricultural Research Corporation
(ARC) in Sudan, where he established the Agricultural Economics Research Component at ARC. Previously he served as a coordinator of Regional Scientific
Networks with the International Center for Agricultural Research in the Dry Areas.
Jones Govereh is a research associate and in-country coordinator in Lusaka for
Michigan State University’s agricultural development economics research and
outreach program. His research work focuses on how to improve the performance of
input markets in Zambia during its transition toward private-sector-led, marketoriented systems.
Johann Kirsten is a professor and the chair of the Department of Agricultural
Economics, Extension and Rural Development at the University of Pretoria. His
research and teaching focus on agricultural policy, agricultural development, and
the application of new institutional economics on agricultural questions in
southern Africa.
Marianne Kurzweil is a young professional at the African Development Bank in
Tunis. During 2006–07, she was a consultant with this project in the Development
Research Group at the World Bank in Washington, DC.
xxvi
Contributors
Vincent Leyaro is a researcher with the Economic and Social Research Foundation
in Dar-es-Salaam, working primarily on trade policy and performance in Tanzania. He is a PhD candidate at the University of Nottingham.
Fenohasina Maret is a PhD candidate in economics at the George Washington
University. Her fields of interest are development economics and applied microeconometrics. She was living in the Democratic Republic of Congo during this
project.
Will Martin is the lead economist in the Development Research Group at the
World Bank in Washington, DC. He specializes in trade and agricultural policy
issues globally, but especially in Asia, and has written extensively on trade policies
affecting developing countries.
William A. Masters is a professor and associate head of the Department of
Agricultural Economics at Purdue University. He is the coeditor of Agricultural
Economics and coauthor of Economics of Agricultural Development, among other
publications. He was also a lecturer at the University of Zimbabwe (1988–90).
Alan Matthews is a professor of European agricultural policy at Trinity College
Dublin, Ireland. He has worked as a consultant to the Organisation for Economic
Co-operation and Development, the Food and Agriculture Organization, the
World Bank, and the European Commission; he has also been a panel member in
two World Trade Organization dispute settlement cases.
Oliver Morrissey is a professor in development economics and director of
CREDIT, School of Economics, University of Nottingham. He has published
mostly on aid policy (conditionality and effectiveness), trade policy reform, and
supply response and performance in agriculture, with a focus on Sub-Saharan
Africa.
Hoda Moussa is a researcher at the Agricultural Economics Research Institute in
Cairo. She is currently working in the Technical Office of the Agricultural
Research Center in the Arab Republic of Egypt’s Ministry of Agriculture and Land
Reclamation.
Saad Zaki Nassar is a professor of agricultural economics at Cairo University. In
1982, he was appointed to the position of dean of the faculty of agriculture, Cairo
University, Fayoum Branch. He has served as president of the Agricultural Research
Center, and in 2001 he was appointed a governor of El Fayoum Governorate.
Contributors
xxvii
Daniel Ndlela is the director of Zimconsult, economic and planning consultants
in Harare. After completing his doctorate at the University of Lund, Sweden, he
taught economics at the University of Zimbabwe and consulted widely on traderelated issues in Africa.
Signe Nelgen has been a consultant with this project and is a PhD student in the
School of Economics of the University of Adelaide in Australia.
Jacob Opolot is a senior economist with the Bank of Uganda in Kampala.
Shahidur Rashid is a senior research fellow in the market and trade division of the
International Food Policy Research Institute. He has held numerous positions at
national agricultural research centers and has collaborated with many international organizations, research institutes, and UN agencies.
Peter Robinson is the director for the African region of Economic Consulting
Associates, based in London. Before taking that post in 2007, he spent 25 years as a
consultant in Zimbabwe, working on macroeconomic modeling, forecasting trade
policy, regional integration, and infrastructural development in southern Africa.
Damiano Sandri is a PhD candidate in economics at Johns Hopkins University in
Baltimore. During 2006–07, he was a consultant with this project in the Development Research Group at the World Bank in Washington, DC.
Gamal Siam is a professor of agricultural economics and advisor to the Center for
Agricultural Economic Studies, Faculty of Agriculture at Cairo University. In
1984, he was appointed chairman of the Department of Agricultural Economics,
Cairo University. Since 1995, he has acted as advisor to the Ministry of Supply and
Home Trade.
Abdelmoneim Taha is an associate research professor in the Agricultural Economics and Policy Research Center of the Agricultural Research Corporation in
Sudan. Since completing his master’s and PhD in agricultural economics at Purdue University, he has conducted research on production, development, and agricultural policy.
Ernesto Valenzuela is a lecturer and research fellow at the School of Economics and
Centre for International Economic Studies at the University of Adelaide. During
2005–07, he was a consultant with the Development Research Group of the World
Bank in Washington, DC.
xxviii
Contributors
Nick Vink is a professor and the chair of the Department of Agricultural Economics at the University of Stellenbosch in South Africa. His work experience includes
11 years as a policy analyst and policy manager at the Development Bank of
Southern Africa. His current research is focused on agricultural trade issues and
on land reform and transformation processes in South Africa.
Peter Walkenhorst is a senior economist in the World Bank’s International Trade
Department, Washington, DC. His recent work has focused on trade policy
reform, regionalism, and export diversification. Before joining the Bank, he
worked as an economist in the Organisation for Economic Co-operation and
Development’s Departments for Economics, Trade, and Agriculture.
Alex Winter-Nelson is an associate professor in the Department of Agricultural
and Consumer Economics at the University of Illinois, Urbana-Champaign. He
conducts research on the relationship between agricultural markets and poverty
in East Africa and on the economics of animal disease control in developing
countries.
ABBREVIATIONS
ACP
BAT
CET
cif
Comecon
COMESA
CTE
ECOWAS
FAO
fob
GATT
IMF
ISIC
MFN
NGO
NPS
NRA
OECD
OLS
OPEC
OPV
PPP
PSF
RCA
REER
RER
African, Caribbean, Pacific
British American Tobacco
common external tariff
cost, insurance, and freight
Council for Mutual Economic Assistance
Common Market for Eastern and Southern Africa
consumer tax equivalent
Economic Community of West African States
Food and Agriculture Organization
free on board
General Agreement on Tariffs and Trade
International Monetary Fund
International Standard Industrial Classification
most favored nation
nongovernmental organization
non-product-specific (assistance)
nominal rate of assistance
Organisation for Economic Co-operation and Development
ordinary least squares
Organization of the Petroleum Exporting Countries
open pollinated variety
purchasing power parity
producer support estimate
revealed comparative advantage
real effective exchange rate
real exchange rate
xxix
xxx
Abbreviations
RERmis
RRA
SADC
TBI
VAT
WCA
WTO
real exchange rate misalignment
relative rate of assistance
Southern Africa Development Community
trade bias index
value added tax
western and central Africa
World Trade Organization
Note: All dollar amounts are U.S. dollars (US$) unless otherwise indicated.
The Focus Economies of Africa
ARAB
REP. OF
EGYPT
MALI
SENEGAL
CHAD
BURKINA
FASO
NIGERIA
CÔTE
D’IVOIRE
CAMEROON
GHANA
TOGO
BENIN
SUDAN
ETHIOPIA
UGANDA
KENYA
TANZANIA
ZAMBIA
MOZAMBIQUE
ZIMBABWE
MADAGASCAR
0
0
500 1000 1500 Kilometers
500
1000 Miles
This map was produced by the Map Design Unit of The World Bank.
The boundaries, colors, denominations and any other information
shown on this map do not imply, on the part of The World Bank
Group, any judgment on the legal status of any territory, or any
endorsement or acceptance of such boundaries.
SOUTH
AFRICA
IBRD 36673
DECEMBER 2008
Part I
Introduction
1
INTRODUCTION
AND SUMMARY
Kym Anderson and William A. Masters
In the 1960s and 1970s, many African governments had macroeconomic, sectoral,
and trade policies that increasingly favored urban employees at the expense of
farm households and favored the production of importable goods at the expense
of exportables (Krueger, Schiff, and Valdes 1988, 1991; Thiele 2004). Similar biases
were prevalent elsewhere but rarely to the same extent as in Africa. The magnitude
of pro-urban (antiagricultural) and also pro-self-sufficiency (antitrade) intervention matters greatly for economic development, because agriculture is the main
employer for the poor and in Africa is often a key export sector. Changes in the
magnitude of these biases could help explain Africa’s development experience,
including the continent’s slow pace of poverty alleviation and economic growth.
Indeed, since the 1980s, much progress has been made in reducing the antiagricultural and antitrade biases of policy in Africa, and these changes have been associated with faster economic growth and poverty alleviation. However, many price
distortions remain. With 60 percent of Sub-Saharan Africa’s workforce still
employed in agriculture and more than 80 percent of the region’s poorest households depending directly or indirectly on farming for their livelihoods (Chen and
Ravallion 2007; World Bank 2007), agricultural and trade policies remain key
influences on the pace and direction of change in Africa.
This volume summarizes a set of case studies measuring distortions within and
across countries over time. It is part of a global research project seeking to
improve understanding of agricultural policy interventions and reforms in Asia,
Europe’s transition economies, and Latin America and the Caribbean as well as
Africa.1 We make no attempt to summarize the voluminous literature on policy
and economic growth in Africa (the most recent major continental study being
3
4
Distortions to Agricultural Incentives in Africa
Ndulu et al. 2008), let alone the literature dealing with public investment or economic growth strategies more broadly (addressed recently by the Commission on
Growth and Development 2008). Our goals are more narrowly defined. One purpose of the project is simply to compare quantitative indicators of past and recent
agricultural price policies. A second objective is to help describe the political
economy behind these interventions in various national settings. A third purpose
is to use this evidence to explore the prospects for further policy reforms and their
potential effects.
The foundation of this project is a new set of annual time series estimates for
protection and taxation of farmers over the past half century. Comparisons over
time, across commodities, and among countries are used to help address such
questions as: Where is there still a policy bias against agricultural production? Are
some developing-country food producers that were once taxed now being protected from import competition, along the lines of such policy transitions seen
earlier in Europe and Northeast Asia?
Beyond the data themselves, what political and economic circumstances can
help explain the policies chosen by governments? What explains the pattern of
distortions within the agricultural sector of each country? What are the political
economy forces behind reform, and how do successful reformers differ from
country to country? In particular, how important are domestic political factors
relative to international forces, such as loan conditionality, multilateral trade
agreements through the General Agreement on Tariffs and Trade (GATT) and the
World Trade Organization (WTO), and regional integration agreements? How
has the balance of forces shifted over time?
Looking forward, our goal is to draw appropriate lessons from past experience,
lessons that can be used to facilitate the adoption of more growth-enhancing and
poverty-reducing policies in Africa and elsewhere. The study is timely for at least
four reasons. One immediate use for the findings is in trade negotiations. African
and other developing countries have been more engaged in the WTO’s Doha
round of multilateral trade negotiations than in any previous GATT round, and
the resulting diversity of interests has made it more difficult for WTO members to
reach consensus. More information on agricultural and trade policies in these
countries can inform dialogue between members. More information can also
assist African countries seeking to position themselves favorably in preferential
trade negotiations, notably the new Economic Partnership Agreements with the
European Union. Another immediate need is for policies to respond to changing
technologies, such as the information, communication, agricultural-biotechnology,
and supermarket revolutions. A third source of urgency is to meet the United
Nations–encouraged Millennium Development Goals by 2015, with agricultural
policy being central to the alleviation of hunger and poverty. And last but not
Introduction and Summary
5
least, the study is timely because world food prices spiked in 2007–08 at very high
levels and governments in some developing countries, in their panic to deal with
the inevitable protests from consumers, have reacted in far from optimal ways.
Such spikes have occurred in the past, most notably in 1973–74, and lessons about
what policy responses work better than others can be drawn from that set of
experiences.
Including Africa in this study is crucial for several reasons. First, the continent
is home to many of the world’s poorest people. In 2006, Sub-Saharan Africa
accounted for less than 2 percent of global gross domestic product (GDP) and
exports and just 4 percent of agricultural GDP, but it also accounted for 12 percent of the world’s farmers, 16 percent of agricultural land, and 28 percent of
those living on less than $1 a day (World Bank 2008). Second, it is the region
where agricultural growth has been slowest over the past half-century, especially
on a per capita basis. And third, it is where sectoral and macroeconomic (including exchange rate) policies have been most heavily interventionist and slowest to
reform, dampening the contribution of market incentives to economic growth.
There is thus much to be learned from examining the policy history of the region,
and there is great potential for poverty alleviation if market-friendly, growthenhancing policies were to be adopted and the recent large increase in development assistance funds were to be used wisely to complement and strengthen
market forces.
The African part of this study is based on a sample of 21 developing countries.
It includes the Arab Republic of Egypt, the largest and poorest country in North
Africa; plus five countries of eastern Africa (Ethiopia, Kenya, Sudan, Tanzania, and
Uganda); five countries in southern Africa (Madagascar, Mozambique, South
Africa, Zambia, and Zimbabwe); five large economies in western Africa
(Cameroon, Côte d’Ivoire, Ghana, Nigeria, and Senegal); and five smaller
economies of West and Central Africa for which cotton is a crucial export (Benin,
Burkina Faso, Chad, Mali, and Togo, for which we estimate price distortions only
for cotton and four nontraded food staples). In 2000–04, these economies (leaving aside Egypt) together accounted for around 90 percent of the agricultural
value added, farm households, total population, and total GDP of Sub-Saharan
Africa. Estimates of distortions are provided for as many years and products as
data permit over the past five decades (an average of 43 years), averaging nine
crop and livestock products a country and covering about 70 percent of the aggregate value of agricultural production in these countries. The time series, product,
and country coverage greatly exceed that of the earlier study by Krueger, Schiff,
and Valdes (1991), which focused on just three to five crops during the 1960–84
period in only two North African and two Sub-Saharan African countries (Egypt
and Morocco, and Ghana and Zambia).
6
Distortions to Agricultural Incentives in Africa
The 21 focus economies in Africa accounted for only 1.3 percent of worldwide
GDP but 11 percent of the world’s farmers in 2000–04. These and related shares
are detailed in table 1.1, which reveals the considerable diversity within the region
in stages of economic development, resource endowments, trade specialization,
poverty incidence, and income inequality. The countries are also very diverse in
their political and social development and thus provide a rich sample for comparative study.
The extent of poverty decline in Sub-Saharan Africa since 1981 has been disappointing relative to other developing-country regions. The number of people in
Sub-Saharan Africa living on less than $1 a day (measured in 1993 purchasing
power parity) grew from 168 million in 1981 to 252 million by 1993 and to
298 million by 2004. As a share of the population, the number of people in such
extreme poverty has declined over the past decade from a peak of 48 percent in
1996 to 41 percent by 2004—but that is only marginally below the 42 percent level
of 1981. More than two-thirds of that recent decline in poverty incidence has been
in rural areas, while most of the rest is explained by the rural poor moving to
urban centers (where many are still very poor). The African experience contrasts
strongly with that in Asia, where even in South Asia, the proportion of the population living on less than $1 a day has fallen from one-half to less than one-third
(table 1.2).
Policy choices have played an important role in the rates of economic growth,
structural change, and poverty alleviation observed in Africa. Many countries had
increasingly severe antiagricultural and antitrade biases in the 1960s and 1970s,
with subsequent reforms that varied widely in their starting dates, speed of execution, and extent of policy change. The switch to policies that are less biased against
farmers and trade began in some countries by the late 1970s but in many others
only in the 1980s or even later—and the transition is still going on, often in fits
and starts and even with the occasional reversal (the most notable recent example
being Zimbabwe). Agricultural price distortions are not the only target of policy
reform, of course, but they are a key aspect of economic policy in most African
countries.
This chapter begins with a brief summary of economic growth and structural
changes in the region since the 1950s and of agricultural and other economic
policy developments as they affected the farm sector at the time of, and in various
stages after, independence from colonial powers. It then introduces the methodology used by the authors of the individual case studies to estimate the nominal
rate of assistance (NRA), the corresponding consumer tax equivalent (CTE)
facing the buyers of agricultural products, the relative rate of assistance (RRA)
between the farm and nonfarm sectors, and the international trade bias index
(TBI). The chapter subsequently provides a synopsis of the empirical results
detailed in the country studies in this volume (and tabulated in brief in appendix
Table 1.1. Key Economic and Trade Indicators, 21 African Focus Countries, 2000–04
Share of world, %
Index, world ⴝ 100
Country or subregion
Population
Total
GDP
Agricultural
GDP
GDP
per capita
Agricultural
land per capita
RCAa
Agricultural trade
specialization indexb
Poverty
incidencec
Gini index of
per capita incomed
Benin
Burkina Faso
Cameroon
Chad
Côte d’Ivoire
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
African focus countries
All Sub-Saharan Africa
All North Africa
All Africa
0.12
0.19
0.25
0.14
0.28
1.13
1.08
0.33
0.52
0.28
0.2
0.3
1.98
0.17
0.73
0.55
0.58
0.09
0.42
0.18
0.21
9.73
9.37
2.34
11.71
0.01
0.01
0.03
0.01
0.04
0.26
0.02
0.02
0.04
0.01
0.01
0.01
0.15
0.02
0.42
0.05
0.03
0
0.02
0.01
0.04
1.21
0.98
0.70
1.67
0.09
0.09
0.38
0.07
0.21
1.11
0.23
0.2
0.29
0.1
0.1
0.08
1.09
0.09
0.39
0.5
0.33
0.05
0.15
0.07
0.14
5.74
4.93
2.81
7.74
7
5
13
5
12
23
2
6
8
5
5
4
8
10
59
8
5
5
4
7
18
13
10
30
14
55
111
74
695
139
6
58
88
103
202
353
324
73
94
275
490
166
80
60
398
200
145
164
84
148
1,034
953
445
—
722
175
958
748
636
670
624
359
3
444
134
209
800
407
938
194
602
—
—
—
—
—
—
—
—
—
—
—
—
—
0.94
—
0.03
—
—
0.52
—
0.73
—
0.8
0.35
0.83
—
0.55
0.78
0.20
31
29
15
—
18
2
12
17
12
63
39
30
71
13
9
—
56
—
83
60
62
—
41
—
32
39
40
45
—
48
34
30
41
43
47
40
47
44
41
58
—
35
—
46
51
50
—
—
—
—
7
Source: Sandri, Valenzuela, and Anderson 2007, which draws on World Development Indicators Database 2007.
Note: — no data are available.
a. The index of revealed comparative advantage (RCA) for agriculture and processed foods (this case) is the share of agriculture and processed food in national exports as a ratio
of the worldwide sectoral share of global exports.
b. The index of primary agriculture trade specialization is the ratio of net exports to the sum of the exports and imports of agricultural and processed food products (the world
average 0.0).
c. The percentage of the population living on less than $1 a day in 2004, from Chen and Ravallion 2007.
d. The Gini index is for the most recent year available between 2000 and 2004.
8
Distortions to Agricultural Incentives in Africa
Table 1.2. Poverty in Africa, Asia, and the World, 1981–2004
Region
Number of people (millions)
Sub-Saharan Africa
East Asia
South Asia
World
Percent of population
Sub-Saharan Africa
East Asia
South Asia
World
1981
1990
1996
2004
168
796
455
1,470
240
476
479
1,248
286
279
453
1,109
298
169
446
969
42
58
50
40
47
30
43
29
48
16
36
23
41
9
31
18
Source: Chen and Ravallion 2007.
B and more fully in Valenzuela et al. 2007), without attempting to survey the myriad policy changes that are discussed in more detail in the following chapters. The
final sections summarize what we have learned and draw out implications of the
findings, including those for poverty and inequality and for possible future directions of policies affecting agricultural incentives in Africa.
Growth and Structural Changes in Africa
The recent report of the Commission on Growth and Development (2008) notes
that 13 economies have had sustained growth in real per capita income of more
than 7 percent for at least 25 consecutive years since World War II. Nine of those
are East Asian and only 1 is African, namely, tiny Botswana (population: 2 million). Between 1980 and 2004, annual per capita GDP for our 21 focus countries
of Africa grew at just 0.7 percent, half the global average of 1.4 percent and a small
fraction of Asia’s 5.5 percent, so per capita incomes in Africa have been diverging
away from those of richer countries, especially those in Asia. Agricultural GDP
growth was faster in Africa than for the world as a whole (3.2 compared with
2.0 percent a year) but only marginally so when expressed on a per capita basis
(0.6 compared with 0.5 percent). In the earlier 1965–84 period, Africa’s agricultural GDP growth rate was only 1.5 percent (World Bank 1986).
Within Africa, economic growth and structural change experiences across
countries are quite diverse (table 1.3). Over time, Africa’s export volumes grew at
relatively slow rates compared with the global average of 6.1 percent (last column
of table 1.3), causing the region’s share of global exports to halve. However, as
economies have gradually opened up, the share of exports in GDP has reversed its
decline and has begun rising in several African countries (table 1.4).
Table 1.3. Growth of Real GDP and Exports, 21 African Focus Countries, 1980–2004
(at constant 2000 prices, percent per year, trend based)
Country or subregion
Agriculture
Industry
Services
Total GDP
GDP per capita
Export volume
Benin
Burkina Faso
Cameroon
Chad
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
African focus countries
All Sub-Saharan Africa
All North Africa
All Africa
5.4
3.8
3.4
3.7
3
1.8
2.6
2.3
2.1
3.3
4.2
3.7
2.1
1.4
4.9
3.6
3.9
3.6
2.5
2.3
3.2
3.6
—
—
4.3
2.5
0.4
4.3
4.7
1.3
3.6
2.5
1.6
5.6
7.7
1.6
4
0.5
4.6
5.0
1.7
9.3
0.4
0.3
2.6
1.7
—
—
2.6
4.0
0.2
3.2
5.1
4.5
6.6
3.5
1.3
2.5
6.4
5.6
2.9
2.3
3.5
4.0
1.2
6.9
1.4
2.3
3.5
2.9
—
—
3.7
3.7
1.2
3.9
4.6
2.9
4.1
3.0
1.6
3.3
4.4
3.1
2.9
1.7
4.3
3.8
2.1
5.9
1.0
1.9
3.1
2.7
3.9
3.7
0.3
0.8
1.4
0.9
2.4
0.2
1.3
0.1
1.4
0.6
2.3
0.4
0.2
0.5
1.9
1.1
1.1
2.4
1.6
0.6
0.7
0.1
1.8
—
0.6
1.2
2.5
3.5
5.0
4.7
7.0
4.1
2.1
8.1
7.7
3.0
4.5
3.7
4.3
6.2
0.3
8.9
1.1
6.0
4.4
—
—
—
9
Sources: Sandri, Valenzuela, and Anderson 2007; World Development Indicators Database 2007.
Note: — no data are available.
Table 1.4. Exports as a Share of GDP, 21 African Focus Countries, 1975–2004
10
(percent)
Country or subregion
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
Benin
Burkina Faso
Cameroon
Chad
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
African focus countries
All Sub-Saharan Africa
All North Africa
All Africa
8
6
25
11
22
—
32
28
15
12
—
35
33
31
9
—
27
—
40
22
—
—
38
—
21
7
13
14
22
9
19
23
15
15
5
37
24
23
5
9
29
7
36
23
21
21
23
22
21
7
13
14
22
9
19
23
15
15
5
37
24
23
5
9
29
7
36
23
21
21
23
22
27
6
20
13
24
7
19
31
17
18
13
46
22
22
5
14
25
7
31
26
23
23
28
25
27
—
25
—
16
14
28
24
22
24
15
42
30
23
7
17
33
11
32
—
—
—
—
—
22
9
—
—
18
18
40
24
24
29
26
42
29
27
15
17
35
13
24
—
—
—
—
—
Sources: Sandri, Valenzuela, and Anderson 2007; World Development Indicators Database 2007.
Note: — no data are available.
Introduction and Summary
11
Slow economic growth has allowed only modest restructuring of Africa’s
economies away from agriculture and toward other activities. In nearly threequarters of the focus countries, the farm sector’s share of GDP is still above
25 percent, the same share as in the later 1980s (table 1.5). The share of overall
employment accounted for by farming activities has fallen but generally remains
above 50 percent (table 1.6), much higher than the GDP shares. These data underscore the relatively low incomes of farmers and hence the continued importance
of agricultural prices for social welfare.
Agriculture’s share of merchandise exports (table 1.7) has declined at least a little in virtually all African countries. That decline is partly because of rises in other
primary exports such as petroleum in Sudan; partly because of growth in exports
of manufactured goods in, for example, Kenya, Madagascar, and Senegal; and
partly because production is increasingly consumed locally. The declining relative
importance of farm exports has been less rapid in Africa than in the rest of the
world, however, as shown by the rise in the index of revealed agricultural comparative advantage (defined as the share of agriculture and processed food in national
exports as a ratio of the share of such products in worldwide merchandise exports)
in most of the focus countries (table 1.8). The exceptions have newly exploited
mineral or energy deposits. The overall trend is a slight decline in the export
orientation of primary farm production. In the 1960s, the region was 120 percent
self-sufficient in farm products, but since then, that indicator has declined to
around 105 percent. The share of exported farm production has fallen from nearly
20 percent to just 8 percent, and the share of imports in domestic consumption of
farm products has doubled, from 2 percent to 4 percent (table 1.9).
The trends in growth and development described here are closely linked to the
agricultural policies pursued by African governments. To measure these policies
in a comparable way, a common methodology was adopted by the authors of the
country case studies in this volume (and its companion volumes; see note 1).
A summary of that methodology follows, and further details can be found in
Anderson et al. (2008), which is reproduced as appendix A in this book.
Methodology for Measuring Rates
of Assistance and Taxation
The nominal rate of assistance is defined as the percentage by which government
policies have raised gross returns to farmers above what they would have been
without the government’s intervention. Similarly, the consumer tax equivalent is
the percentage by which policies have raised prices paid by consumers of agricultural outputs. Negative values imply net taxation of farmers or subsidies to consumers. The NRA and the CTE will be identical if the sole source of government
Table 1.5. Sectoral Shares of GDP, 21 African Focus Countries, 1965–2004
12
(percent)
Country
or subregion
Agriculture
Industry
Services
1965–69 1975–79 1985–89 2000–04 1965–69 1975–79 1985–89 2000–04 1965–69 1975–79 1985–89 2000–04
Benin
Burkina Faso
Cameroon
Chad
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
African focus countries
All Sub-Saharan Africa
All North Africa
All Africa
42
34
32
38
25
—
43
33
22
59
—
49
25
9
36
—
44
46
12
20
—
—
18
—
33
29
31
37
24
—
56
32
29
55
—
29
26
6
34
—
29
71
15
16
—
—
12
—
34
28
23
33
19
47
48
27
31
42
44
36
21
5
33
—
33
53
15
15
—
—
13
—
36
32
43
40
15
41
36
26
27
34
21
25
18
3
39
41
39
31
20
14
17
18
—
—
11
21
20
13
24
—
19
17
13
10
—
12
12
36
14
—
22
12
57
28
—
—
36
—
14
23
19
13
27
—
16
17
15
10
—
33
15
40
12
—
23
6
40
31
—
—
46
—
Sources: Sandri, Valenzuela, and Anderson 2007; World Development Indicators Database 2007.
Note: — no data are available.
13
21
30
14
27
13
17
16
12
15
18
32
18
38
16
—
22
10
44
29
—
—
39
—
14
18
17
14
32
9
25
15
14
24
26
48
20
29
20
15
20
19
24
19
29
28
—
—
48
45
49
49
51
—
38
50
65
32
—
39
63
55
50
—
34
41
31
52
—
—
47
—
53
48
51
49
49
—
29
51
57
36
—
38
59
54
54
—
49
22
45
53
—
—
42
—
52
51
46
53
54
40
35
57
57
43
39
32
61
57
52
—
45
37
41
55
—
—
49
—
50
50
40
46
53
50
39
59
59
42
52
27
62
68
41
44
41
50
57
67
54
54
—
—
13
Introduction and Summary
Table 1.6. Agriculture’s Share in Employment, 21 African Focus
Countries, 1965–2004
(percent)
Country or subregion
1965–69
1975–79
1985–89
2000–04
Benin
Burkina Faso
Cameroon
Chad
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
Africa focus countries
All Sub-Saharan Africa
All North Africa
All Africa
82
92
86
93
63
—
61
86
85
93
87
72
83
33
81
91
76
91
81
78
—
—
62
—
71
92
77
89
58
—
61
83
82
90
85
59
81
21
74
87
70
88
77
74
—
—
54
—
65
92
71
85
45
—
60
80
79
87
84
46
78
15
70
85
66
85
75
69
—
—
41
—
52
92
58
74
33
82
56
75
74
80
81
32
73
9
60
80
59
79
68
62
56
61
30
56
Sources: Sandri, Valenzuela, and Anderson 2007; FAOSTAT Database 2007.
Note: — no data are available.
intervention is a trade measure and if the two are measured at the same point in
the value chain, but in general some domestic producer or consumer taxes or subsidies will differentiate them.2
The intended use of the NRAs and the CTEs influences the methodology
needed to estimate them. This project uses them for three purposes. One is simply
to compare the net effect of policies on prices and incentives across a wide range
of commodities, countries, and years. For this purpose, the methodology needs to
be both simple and flexible. Another purpose is to allow aggregation to indicate
the total extent of transfer to (or from) farmers and consumers resulting from
agricultural price policies, for which appropriate weights and denominators are
14
Table 1.7. Sectoral Shares in Merchandise Exports, 21 African Focus Countries, 1965–2004
(percent)
Agriculture and processed food
Country
Benin
Burkina Faso
Cameroon
Chad
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
Other primary
Other goods
1965–69 1975–79 1985–89 2000–04 1965–69 1975–79 1985–89 2000–04 1965–69 1975–79 1985–89 2000–04
88
95
80
96
71
—
80
—
87
97
—
60
83
—
98
—
57
—
3
—
84
92
81
83
44
—
83
65
83
91
—
6
61
26
96
83
37
97
1
—
—
—
57
—
20
—
—
71
80
99
—
3
49
—
93
91
41
—
—
51
92
85
40
—
16
86
67
57
60
55
32
0
40
12
19
71
36
84
17
53
4
1
14
2
6
—
17
—
6
1
—
37
9
—
1
—
36
—
97
—
2
0
13
9
30
—
14
20
10
0
—
94
28
20
3
4
55
3
98
—
Sources: Sandri, Valenzuela, and Anderson 2007; World Development Indicators Database 2007.
Note: — no data are available.
—
—
26
—
50
—
—
16
9
—
—
96
26
—
1
—
50
—
—
19
0
2
55
—
45
2
18
21
6
8
62
98
23
25
77
10
16
7
69
19
8
4
6
1
24
—
1
—
7
2
—
2
8
—
1
—
7
—
1
—
11
8
6
8
26
—
2
15
7
9
—
0
12
35
1
13
7
0
1
—
—
—
16
—
30
—
—
13
10
1
—
0
25
—
6
8
8
—
—
29
8
13
5
—
33
12
15
23
33
36
5
2
36
58
3
18
48
10
14
28
Introduction and Summary
15
Table 1.8. Index of Revealed Comparative Advantage in
Agriculture and Processed Food, 21 African Focus
Countries, 1965–2004
(world 1.0)
Country
Benin
Burkina Faso
Cameroon
Chad
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
1965–69
1975–79
1985–89
2000–04
3.5
3.8
3.2
3.8
2.8
—
3.2
—
3.4
3.8
—
2.3
3.3
—
3.8
—
2.2
—
0.1
—
4.5
4.7
4.2
4.1
2.3
—
4.3
3.4
4.3
4.7
—
0.3
3.1
1.3
5
4.3
1.9
4.8
0.1
—
—
—
3.9
—
1.4
—
—
4.8
5.4
6.9
—
0.2
3.3
—
6.2
6
2.8
—
—
3.3
10.3
9.5
4.5
—
1.8
9.6
7.5
6.4
6.7
6.2
3.6
0
4.4
1.3
2.1
8
4.1
9.4
1.9
6
Sources: Sandri, Valenzuela, and Anderson 2007; World Development Indicators Database 2007.
Note: See table 1.1 for a definition of the RCA. — no data are available.
needed. This function is similar in spirit to the producer and consumer support
estimates put out by the Organisation for Economic Co-operation and Development (OECD 2007) but with important differences in implementation as outlined below. And the third purpose is to enable economic modelers to use the
NRAs and CTEs in policy simulation models; to do so, modelers must be able to
allocate each distortion to a particular policy instrument such as import tariffs,
export taxes, or domestic producer or consumer taxes or subsidies.
Estimating the NRA or the CTE for an individual industry requires specialist
knowledge of that sector, particularly in countries where trade costs are high,
pass-through along the value chain is affected by imperfect competition, and markets for foreign currency have been distorted at various times and to varying
degrees in the past. Specialist knowledge is also needed to assess how policy is
Table 1.9. Export Orientation, Import Dependence, and
Self-Sufficiency in Primary Agricultural Production,
16 African Focus Countries, 1965–2004
(percent at undistorted prices)
a. Exports as a share of production
Country
1961– 1965– 1970– 1975– 1980– 1985– 1990– 1995– 2000–
64
69
74
79
84
89
94
99
04
Cameroon
11
14
16
23
29
33
20
21
17
Côte d’Ivoire
48
44
42
39
50
61
55
60
59
Egypt, Arab Rep. of
17
15
15
9
7
5
2
2
3
Ethiopia
—
—
—
—
—
—
1
3
2
Ghana
46
42
43
45
27
31
17
16
18
Kenya
35
40
44
46
43
50
44
49
45
Madagascar
—
—
—
14
7
3
13
7
30
Mozambique
8
8
10
11
8
7
6
7
8
Nigeria
10
12
7
6
2
2
1
1
1
Senegal
24
18
4
7
5
2
5
6
4
South Africa
15
14
16
27
26
20
11
6
10
Sudan
24
22
21
15
9
7
5
6
3
Tanzania
—
—
—
18
18
16
16
11
7
Uganda
29
33
29
24
21
27
8
10
3
Zambia
11
13
7
3
2
4
4
6
14
Zimbabwe
63
36
43
37
43
41
52
53
43
African focus
countries
19
18
17
17
12
11
8
8
8
b. Imports as a share of apparent consumption
Country
1961– 1965– 1970– 1975– 1980– 1985– 1990– 1995– 2000–
64
69
74
79
84
89
94
99
04
Cameroon
0
0
0
0
0
0
0
0
0
Côte d’Ivoire
3
0
0
0
0
0
1
1
1
14
Egypt, Arab Rep. of
6
6
6
14
22
20
15
16
—
—
—
—
—
—
1
1
2
Ghana
3
3
0
1
1
0
0
0
0
Kenya
13
10
11
4
6
6
10
10
12
Madagascar
—
—
—
5
6
14
35
11
28
Mozambique
1
2
1
1
1
3
4
4
3
Nigeria
0
0
0
0
1
1
0
0
1
Senegal
2
2
3
0
0
0
0
1
0
South Africa
0
0
0
0
0
0
0
1
1
Sudan
4
2
5
4
4
3
2
1
3
—
—
—
1
4
1
1
4
4
Ethiopia
Tanzania
Uganda
0
0
0
0
1
1
1
1
1
Zambia
2
2
7
2
8
5
11
9
5
Zimbabwe
2
1
1
0
2
0
12
6
9
African focus
countries
2
2
2
4
5
4
4
4
4
16
Introduction and Summary
17
c. Self-sufficiency ratio
Country
1961– 1965– 1970– 1975– 1980– 1985– 1990– 1995– 2000–
64
69
74
79
84
89
94
99
04
Cameroon
113
117
119
130
141
150
125
126
120
Côte d’Ivoire
186
178
173
166
206
268
223
251
253
Egypt, Arab Rep. of
113
110
110
94
84
85
87
86
89
—
—
—
—
100
100
101
102
100
Ghana
182
172
181
181
138
146
120
120
122
Kenya
135
153
162
182
166
192
165
178
163
Madagascar
118
117
119
137
135
125
112
106
110
Mozambique
—
—
—
114
101
89
74
95
141
Ethiopia
Nigeria
111
113
107
106
101
101
101
101
101
Senegal
129
121
100
108
105
102
105
106
104
South Africa
107
107
110
111
107
105
102
103
105
Sudan
128
125
121
114
106
105
103
104
100
Tanzania
—
—
—
121
118
119
117
108
103
Uganda
140
149
142
133
126
138
108
110
103
Zambia
110
113
101
101
94
99
92
97
113
Zimbabwe
264
161
176
160
174
170
301
204
169
African focus countries
120
119
117
116
107
108
104
105
105
Sources: Compiled using project estimates of total agricultural production valued at undistorted prices;
Food and Agriculture Organization (FAO) Agricultural Trade Database 2007.
Note: — no data are available.
actually implemented. Most distortions in markets for tradable goods come from
trade measures, such as a tariff (or occasionally a subsidy) imposed on the cif
(cost, insurance, and freight) import price or an export tax imposed on the fob
(free on board) price at the country’s border, or quantitative restrictions on trade.
These are captured in the NRA and the CTE at the point in the value chain where
the product is first traded. To estimate the NRA for a typical farmer, authors of the
country studies estimated or guessed the extent of pass-through back to the farmgate and added any domestic subsidies the farmer received for his output. To
obtain the CTE for a typical consumer, they also added any product-specific
domestic consumer taxes or subsidies to the distortion from border prices. Note
that the NRA and the CTE differ from the OECD’s producer and consumer support estimates in that the latter are expressed as a percentage of the distorted price
and hence are lower (for positive protection rates) than the former, which are
expressed as percentages of the undistorted price.3
We decided against seeking estimates of the more complex effective rate of
assistance even though it is, in principle, a better partial-equilibrium, single
18
Distortions to Agricultural Incentives in Africa
measure of distortions to producer incentives than the nominal rate. Making those
complex estimates requires knowing each product’s value added and various intermediate input shares of output. Such data are not available for most developing
countries even every few years, let alone for every year in the long time series that is
the focus of this study. And in most countries, distortions to farm inputs are very
small compared with distortions to farm output prices. But where product-specific
distortions to input costs are significant, they are captured by estimating their
equivalence in terms of a higher output price and including that in the NRA for
individual agricultural industries wherever data allow (as is also done as part of the
calculation by the OECD of its producer support estimate). Any non-productspecific distortions, including distortions to farm input prices, are also added into
the estimate for the overall sectoral NRA for agriculture as a whole.
NRA and CTE estimates were made for each of the country’s major farm products, in an attempt to cover at least 70 percent of the total gross value of farm production at undistorted prices. This target degree of coverage is similar to that for
the OECD’s producer support estimates. Unlike the OECD, however, in this project
we do not routinely assume that the nominal assistance for covered products
applies equally to noncovered farm products, because in developing countries the
agricultural policies affecting the noncovered products are often very different
from those for the chosen covered products. For example, nontradables among
noncovered farm goods (often highly perishable or low-valued products relative
to their transport cost) are often not subject to direct distortionary policies
whereas covered nontradables often are. The authors of the country case studies
were asked to provide three sets of “guesstimates” of the NRAs for noncovered
farm products, one each for the import-competing, exportable, and nontradable
subsectors. Weighted averages for all agricultural products were then generated,
using the gross values of production at unassisted prices as weights. For countries
that also provide non-product-specific agricultural subsidies or taxes (assumed to
be shared on a pro rata basis between tradables and nontradables) or assistance
decoupled from production, such net assistance is then added to product-specific
assistance to obtain an NRA for total agriculture and also for tradable agriculture
for use in generating the relative rate of assistance (defined below).
How best to present regional aggregate NRA and RRA estimates depends on
the purpose for which the averages are required. We generate a weighted average
NRA for covered products for each country by multiplying each NRA by that
product’s share of the gross value of production, valued at the farmgate equivalent
undistorted price.4 To obtain the NRA for all agriculture, we then add the NRA for
noncovered products and any non-product-specific assistance to farmers. When it
comes to averaging across countries, each polity is an observation of interest, so a
simple average is meaningful for the purpose of political economy analysis.
Introduction and Summary
19
For other purposes, however, a value-weighted average is appropriate. Finally, we
compute and use a weighted average that includes only the tradables part of
agriculture—including those industries producing products such as milk and
sugar that require only light processing before they can be traded—by assuming
that its share of non-product-specific assistance equals its weight in the total. We
denote this measure for tradable agriculture as NRAagt.
In addition to these average NRAs, it is important to provide a measure of dispersion or variability of the nominal rate of assistance across products. The welfare cost of a distortion varies exponentially with its size, so that a set of dispersed
tariffs is more costly than a uniform tariff at the same average level. The cost of
dispersion is even larger when there is a greater degree of substitution in production (Lloyd 1974). Land and labor is often specific to agriculture but highly transferable among farm activities, so we expect variation of NRAs across farm products to be quite costly. A simple indicator of this kind of dispersion is the standard
deviation of the NRA among covered products.
Each industry is classified as being import-competing, as producing exportables, or as producing a nontradable (with its status sometimes changing over the
years); this classification makes it possible to generate for each year the weighted
average NRAs for the two different groups of tradables. Those NRAs are used to
generate a trade bias index, TBI, defined as:
TBI (1 NRAagx兾100)兾(1 NRAagm兾100) 1
(1.1)
where NRAagm and NRAagx are the average percentage NRAs for the importcompeting and exportables parts of the agricultural sector. The TBI indicates in a
single number the extent to which the typically antitrade bias (negative TBI) in
agricultural policies changes over time.
Farmers are affected not just by prices of their own outputs but also, albeit
indirectly through changes to factor market prices and the exchange rate, by the
incentives nonagricultural producers face. That is, it is relative prices and hence
relative rates of government assistance that affect producer incentives. More than
70 years ago, Lerner (1936) proved his symmetry theorem, which holds that in a
two-sector economy, an import tax has the same effect as an export tax. This result
carries over to a model that also includes a third sector producing nontradables, to
a model with imperfect competition, regardless of the economy’s size (Vousden
1990, pp. 46–7). If one assumes that there are no distortions in the markets for
nontradables and that the value shares of agricultural and nonagricultural nontradable products remain constant, then the economy-wide effect of distortions to
agricultural incentives can be captured by the extent to which the tradable parts of
agricultural production are assisted or taxed relative to producers of other tradables. By generating estimates of the average NRA for nonagricultural tradables, it
20
Distortions to Agricultural Incentives in Africa
is then possible to calculate a relative rate of assistance, defined in percentage
terms as:
RRA 100[(1 NRAagt兾100)兾(1 NRAnonagt兾100) 1]
(1.2)
where NRAagt and NRAnonagt are the weighted average percentage NRAs for the
tradable parts of the agricultural and nonagricultural sectors, respectively. Since
the NRA cannot be less than 100 percent if producers are to earn anything, neither can the RRA (assuming NRAnonagt is positive). And if both of those sectors
are equally assisted, the RRA is zero. This measure is useful in that if it is below
(above) zero, it provides an internationally comparable indication of the extent to
which a country’s policy regime has an anti- (pro-) agricultural bias.
Exchange rate distortions generated by dual or multiple exchange rate regimes
are considered when calculating the NRAs and CTEs, following the methodology
outlined in appendix A. These types of distortions have been important in many
African countries, particularly during the 1970s and 1980s, making their estimated, (typically) positive NRAs for importables and (typically) negative NRAs
for exportables larger than they otherwise would have been.
Dollar values of farmer assistance and consumer taxation are determined by
multiplying the NRA estimates by the gross value of production at undistorted
prices to obtain an estimate in current U.S. dollars of the direct gross subsidy
equivalent of assistance to farmers. This estimate is then added up across products for a country and across countries for any or all products to get regional
aggregate transfer estimates for the studied economies. These gross subsidy
equivalent values are calculated in constant dollars and are also expressed on a
per-farm-worker basis.
To obtain comparable dollar value estimates of the consumer transfer, the CTE
estimate at the point at which a product is first traded is multiplied by consumption (obtained from the Food and Agriculture Organization’s supply and utilization database) valued at undistorted prices to obtain an estimate in constant U.S.
dollars of the tax equivalent to consumers of primary farm products. This too is
added up across products for a country, and across countries for any or all products, to get regional aggregate transfer estimates for the covered farm products of
the focus countries.
Estimates of Policy-Induced Distortions
in Africa
We begin with the nominal rates of assistance to agriculture, then compare them
with the nominal rates for nonagricultural tradables by calculating the relative
rates of assistance. Dollar equivalents of assistance or taxation to farmers are also
Introduction and Summary
21
presented, as are the consumer tax equivalents of policies that affect buyers of
farm products in each country (which includes domestic processors).
Nominal rates of assistance to agriculture
Agricultural price, trade, and exchange rate policies have reduced the earnings of
African farmers quite substantially.5 The average rate of taxation as measured by
our weighted average NRA was less than 10 percent at the time many Africa countries achieved independence in the early 1960s, but it then rose sharply during the
1960s and 1970s as interventions became more severe. Reforms have since
reduced the average extent of taxation to below its level of the early 1960s; there
was even a brief period in the late 1980s when a combination of policy reforms
and low international commodity prices brought the weighted average NRA to
near zero (table 1.10). Such averages hide considerable diversity within the region,
however. A visual impression of the variation across countries and the extent of
reforms between 1975–79 and 2000–04 is provided in figure 1.1, showing clearly
the major reduction in taxing of farmers in such countries as Ghana, Uganda,
Tanzania, Cameroon, Senegal, and Madagascar. That figure also shows the transition from taxation to support of farmers in Mozambique and Kenya, as well as the
transition from slight support to slight taxation in Nigeria, and the continuing
heavy degree of taxation still in Côte d’Ivoire, Zambia, and Zimbabwe.
One important type of variation in distortions is the within-country dispersion of product NRAs, as measured in table 1.11 by their standard deviation
around the weighted mean NRA for covered agricultural products in each
period. This dispersion was highest in the middle of our 50-year period, when
the NRAs were most distorting, but even after the recent reforms, dispersion is
no lower than it was at the beginning of the period. The dispersion of NRAs
within African countries is an important target for reform, whatever the level of
average NRA.
Variation among products has a somewhat similar pattern across countries.
Figure 1.2 shows the pattern of dispersion in the regionwide average NRA among
the key farm commodities in the late 1970s and a quarter century later, both
unweighted and weighted by value of production. As in other regions of the
world, the rice pudding ingredients of sugar, rice, and milk are among the products receiving the highest assistance, while assistance is most negative for tropical
cash crops such as coffee, cotton, cocoa, and tobacco. The dispersion over a wider
range of products and for the full time period is summarized in table 1.12.
A third type of variation is cross-country diversity of national average NRAs.
This diversity is evident from the bottom of table 1.10: NRA averages for the agricultural sector became more similar between the latter 1950s and the early 1970s,
22
Table 1.10. NRAs in Agriculture, 16 African Focus Countries, 1955–2004
(percent)
Country
Region 1955–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
a
Cameroon
Côte d'Ivoirea
Egypt, Arab Rep. of
Ethiopiaa
Ghana
Kenya
Madagascar
Mozambique
Nigeriaa
Senegala
South Africa
Sudan
Tanzaniaa
Ugandaa
Zambiaa
Zimbabwe
Unweighted averageb
Weighted average
Dispersion of country NRAsc
W
W
N
E
W
E
S
S
W
W
S
E
E
E
S
S
—
—
23.2
—
4.4
26.6
0.2
—
—
—
—
11.7
—
—
—
16.9
0.3
13.6
20.8
2.9
23.5
33.9
—
9.0
23.0
5.9
—
20.7
9.3
4.1
20.4
—
1.8
—
27.2
7.8
7.7
13.4
6.0
29.3
37.7
—
19.8
9.7
11.1
—
11.9
7.2
9.4
31.8
—
3.1
22.4
25.5
12.5
11.3
15.1
7.4
28.1
37.5
—
14.9
11.8
13.5
—
6.7
22.4
0.7
43.4
—
7.8
15.8
26.0
12.9
14.7
14.3
14.4
30.8
15.9
—
25.6
1.7
27.1
34.5
6.3
22.7
3.8
24.3
41.8
17.6
37.3
28.6
15.5
12.7
17.1
11.2
32.2
9.2
17.5
21.2
18.6
38.8
25.2
9.4
20.5
22.9
29.3
56.3
6.2
2.7
24.0
13.7
7.9
21.2
2.4
24.3
56.6
22.3
6.3
10.5
18.2
32.0
8.2
4.7
11.7
35.4
45.3
6.8
58.9
24.1
8.9
1.0
29.5
1.1
19.5
6.1
24.4
1.7
5.8
5.4
2.7
3.9
5.6
10.8
47.8
25.2
0.6
30.8
24.9
8.7
8.9
16.1
1.3
20.0
4.0
17.8
3.0
2.4
2.9
3.9
0.4
6.1
5.7
24.5
23.2
0.5
28.6
20.8
6.6
5.7
12.3
0.1
24.5
6.1
11.2
1.4
9.3
1.0
12.4
5.4
7.5
0.1
11.9
12.4
0.4
28.5
38.7
6.0
7.3
13.5
Sources: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–17 of this book.
Note: The table shows the weighted average for each country, including product-specific output and input distortions and non-product-specific assistance as well as authors’
guesstimates for noncovered farm products, with weights based on gross value of agricultural production at undistorted prices. — no data are available.
a. For Cameroon, Côte D’Ivoire, Nigeria, Senegal, Uganda, and Zambia: 1960–64 1961–64. For Tanzania: 1975–79 1976–79. For Ethiopia: 1980–84 1981–84.
b. The unweighted average is the simple average of the national NRA (weighted) across the 16 countries.
c. Dispersion is a simple five-year average of the annual standard deviation around a weighted mean of the national agricultural sector NRAs each year.
Introduction and Summary
23
Figure 1.1. NRAs in Agriculture, 16 African Countries, 1975–79
and 2000–04
20
percent
0
⫺20
⫺40
N
ig
er
ia
na
G
ha
a
ut
h
m
Af
er
o
ric
on
da
ca
ag
as
Ca
So
M
M
oz
ad
Ug
an
r
a
Ke
ny
am
bi
qu
e
⫺60
countries
20
percent
0
⫺20
⫺40
e
a
ba
bw
bi
Zi
m
te
Cô
Za
m
oi
Iv
d’
nz
Ta
,A
yp
t
Eg
re
an
ia
n
Su
da
a
op
i
Et
hi
l
ga
ne
Se
ra
b
Re
p.
of
⫺60
countries
1975–79
2000–04
Sources: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–17.
Note: Data for Ethiopia for the first period refer to 1981–84 because data for 1975–79 are unavailable.
24
Table 1.11. Dispersion of NRAs across Covered Agricultural Products, 16 African Focus Countries, 1955–2004
(percent)
Country
1955–59
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
Cameroon
Côte d’Ivoirea
Egypt, Arab Rep. of
Ethiopiaa
Ghana
Kenya
Madagascar
Mozambique
Nigeriaa
Senegala
South Africa
Sudan
Tanzaniaa
Ugandaa
Zambiaa
Zimbabwe
—
—
21.9
—
9.8
33.2
—
—
—
—
25.7
34.2
—
—
—
74.6
13.5
25.1
14.7
—
17.2
26.0
31.3
—
112.9
20.3
17.9
34.9
—
7.8
14.5
71.0
18.0
28.0
17.1
—
29.9
30.7
24.7
—
95.4
16.1
19.1
34.1
—
11.6
29.6
47.3
21.8
33.1
21.3
—
29.0
20.5
24.6
—
94.2
33.5
25.3
36.2
—
28.5
26.6
36.9
29.0
46.2
32.2
—
47.9
26.5
37.5
34.8
89.9
44.5
31.6
40.0
38.6
47.0
36.1
27.7
20.6
33.3
31.9
26.4
69.6
22.3
39.2
36.0
92.0
38.2
42.7
31.7
39.1
39.3
34.8
28.1
17.2
33.1
89.6
28.2
56.3
23.6
42.0
40.3
94.4
58.8
35.0
54.4
41.3
40.5
35.4
24.4
16.1
26.2
33.0
28.0
26.2
23.4
39.1
28.6
83.2
67.1
31.8
75.3
46.5
7.8
39.2
25.2
13.0
23.4
28.7
29.1
17.2
24.7
30.3
33.4
72.7
14.3
20.3
41.2
47.3
6.6
36.1
25.3
7.5
33.1
22.1
23.6
25.5
25.6
22.5
37.9
53.2
18.6
20.3
63.2
51.9
6.9
38.1
33.9
African focus countries:
Unweighted averageb
Product coveragec
33.2
68
31.3
73
30.9
72
33.2
72
40.6
70
39.1
67
44.7
66
37.3
66
29.0
66
30.2
68
a
Sources: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–17 of this book.
Note: The dispersion for each country is a simple five-year average of the annual standard deviation around a weighted mean of NRAs across covered products each
year. — no data are available.
a. For Cameroon, Côte D’Ivoire, Nigeria, Senegal, Uganda, and Zambia: 1960–64 1961–64. For Tanzania: 1975–79 1976–79. For Ethiopia: 1980–84 1981–84.
b. The unweighted average is the simple average across the 16 countries of their five-year simple average dispersion measures.
c. Share of gross value of total agricultural production, valued at undistorted prices, accounted for by covered products.
Introduction and Summary
25
then less similar through the later 1980s, and then more similar again, so that by
2000–04, this type of dispersion was back to what it had been in the early 1960s.
The fourth important type of variation is differential treatment of importcompeting and exportable products in a way that often favors self-sufficiency. The
extent of antitrade bias is shown in figure 1.3 as the gap between the average NRAs
Figure 1.2. NRAs, by Key Covered Product, 21 African Focus
Countries, 1975–79 and 2000–04
a. Unweighted average across 21 countries
sugar
wheat
rice
milk
maize
poultry
banana
plantain
millet
cassava
yam
product
sunflower
bean
sorghum
sheep meat
palm oil
vanilla
coffee
beef
cotton
cocoa
groundnut
tea
sesame
soybean
tobacco
100
50
0
percent
50
100
(Figure continues on the following page.)
26
Distortions to Agricultural Incentives in Africa
Figure 1.2. (continued)
product
b. Weighted average across 21 countries
sugar
sorghum
milk
poultry
banana
plantain
wheat
millet
cassava
yam
sunflower
maize
rice
coffee
palm oil
vanilla
tea
sheep meat
bean
beef
cocoa
sesame
groundnut
cotton
soybean
tobacco
100 80
60
40
20
0
percent
1975–79
20
40
60
80
2000–04
Sources: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–18 of this book.
Note: The weights in figure b are based on the gross value of agricultural production at undistorted prices.
Thus, each NRA (by country, by product) is weighted by the value of production of that commodity in each
country in a given year.
for import-competing and exportable products. This gap grew from the 1950s
to the 1980s. It has since narrowed, mainly because of changes in taxation of
exportables, but the gap is still sizable. This variation is summarized in the trade
bias index reported for Africa as a whole in the middle row of table 1.13, and for
individual countries in table 1.14.
Table 1.12. NRAs for Key Covered Farm Products, 21 African Focus Countries, 1955–2004
(percent)
Product
27
Banana
Bean
Beef
Cassava
Cocoa
Coffee
Cotton
Groundnut
Maize
Milk
Millet
Palm oil
Plantain
Poultry
Rice
Sesame
Sheep meat
Sorghum
Soybean
Sugar
Sunflower
Tea
Tobacco
Vanilla
Wheat
Yam
All covered products
1955–59
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
—
—
13
0
14
11
16
29
4
35
77
—
0
—
62
40
12
35
—
22
—
3
—
—
13
0
19.9
2
6
21
0
27
27
41
27
12
22
19
25
0
13
38
53
14
62
—
6
15
9
42
62
27
0
13
4
2
29
0
54
36
53
38
3
32
6
31
0
13
39
64
18
87
14
11
17
7
38
53
13
0
17.8
0
3
37
0
48
44
54
51
7
42
4
44
0
16
22
65
22
49
30
24
6
20
45
39
6
0
22.1
2
39
4
1
60
62
49
46
12
1
1
17
0
24
14
68
21
28
43
11
7
30
54
57
12
1
20.3
1
53
11
2
52
53
43
44
1
22
1
25
0
18
14
60
20
17
43
1
16
34
47
76
5
1
12.1
1
66
23
1
36
42
31
17
38
67
0
12
0
3
29
48
37
41
40
42
7
29
48
85
19
0
0.9
3
25
38
1
35
37
54
30
8
27
1
108
0
6
0
48
49
37
53
2
6
40
38
78
4
1
12.4
5
24
1
3
32
21
38
36
2
8
3
41
0
13
8
50
45
23
50
7
6
28
34
28
1
4
6.6
Sources: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–18 of this book.
Note: — no data are available.
2000–04
1
25
26
3
36
12
46
40
5
15
2
13
0
3
5
38
21
21
54
44
4
16
63
13
1
3
8.9
28
Distortions to Agricultural Incentives in Africa
Figure 1.3. NRAs for Exportable, Import-Competing, and All
Farm Products, 16 African Countries, 1955–2004
a. Unweighted averages across 16 countries
40
percent
20
0
20
40
4
00
–0
9
20
95
–9
4
19
90
–9
9
19
85
–8
4
19
80
–8
9
19
75
–7
4
19
70
–7
9
19
19
65
–6
4
–6
60
19
19
55
–5
9
60
years
b. Weighted averages across 16 countries
80
60
percent
40
20
0
20
40
4
20
00
–0
9
19
95
–9
4
19
90
–9
9
19
85
–8
4
19
80
–8
9
19
75
–7
4
19
70
–7
9
19
65
–6
4
–6
60
19
19
55
–5
9
60
years
exportables
import-competing
total
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–17 of this book.
Note: The total NRA can be above or below the exportable and importable averages because assistance to
nontradables and non-product-specific assistance are also included.
Table 1.13. NRAs in Agriculture Relative to Nonagricultural Industries, 16 African Focus Countries, 1955–2004
(percent)
a. Unweighted averages across 16 countries
Indicator
1955–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
NRA, covered products
NRA, noncovered products
NRA, all agricultural products
Total agricultural NRAa
Trade bias indexb
NRA, all agricultural tradablesa
NRA, all nonagricultural tradables
RRAc
Memo item, ignoring exchange
rate distortions
Total agricultural NRA
Trade bias index
RRAc
0.0
0.6
1.8
0.3
0.11
3.1
18.8
13.2
14.5
1.0
10.0
7.8
0.35
10.9
13.1
21.2
19.3
0.4
14.2
12.5
0.40
19.7
12.6
28.7
20.2
0.8
14.7
12.9
0.33
20.6
23.5
35.5
24.8
1.3
17.0
15.5
0.41
26.2
27.0
41.8
20.5
1.5
15.4
13.7
0.34
21.5
27.3
38.2
11.6
3.8
10.1
8.9
0.41
13.9
23.0
29.7
13.3
3.5
10.7
8.7
0.24
13.9
18.8
27.5
9.1
3.0
7.1
6.6
0.19
9.3
15.2
21.2
8.9
2.9
6.5
6.0
0.21
9.4
14.5
20.9
7.0
0.00
8.3
6.1
0.16
17.1
8.4
0.13
21.5
13.0
0.03
27.8
13.6
0.11
31.3
13.1
0.29
28.7
7.6
0.45
18.8
9.8
0.03
23.8
8.5
0.03
20.7
8.6
1.31
19.6
(Table continues on the following page.)
29
30
Table 1.13. NRAs in Agriculture Relative to Nonagricultural Industries, 16 African Focus Countries, 1955–2004
(continued)
b. Weighted averages across 16 countries
Indicator
1955–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
NRA, covered products
NRA, noncovered products
NRA, all agricultural products
Total agricultural NRAa
Trade bias indexb
NRA, all agricultural tradablesa
NRA, all nonagricultural tradables
RRAc
Memo item, ignoring exchange
rate distortions
Total agricultural NRA
Trade bias index
RRAa
19.9
0.5
14.0
13.6
0.00
24.1
19.5
36.5
13.0
3.6
8.4
7.7
0.41
13.3
3.7
15.2
17.8
1.8
12.2
11.3
0.45
19.6
2.7
21.4
22.1
0.2
15.6
14.7
0.44
25.0
1.5
26.0
20.3
0.3
13.8
12.7
0.50
22.1
5.7
25.9
12.1
3.3
9.5
7.9
0.43
13.5
1.6
13.1
0.9
7.6
2.0
1.0
0.60
0.3
9.2
8.3
12.4
4.8
10.0
8.9
0.39
15.4
2.7
17.1
6.6
5.1
6.1
5.7
0.33
8.7
2.0
10.4
8.9
5.2
7.7
7.3
0.26
12.0
7.3
18.0
10.3
0.03
26.7
5.2
0.14
9.7
7.3
0.17
13.4
11.6
0.16
17.7
8.9
0.29
17.0
3.7
0.05
2.7
5.6
0.26
5.9
6.7
0.01
12.7
5.6
0.30
11.8
6.2
0.20
16.1
Source: Anderson and Valenzuela (2008, based on estimates reported in chapters 2–17 of this book.
a. NRAs including non-product-specific assistance, that is, the assistance to all primary factors and intermediate inputs as a percentage of the total primary agricultural
production valued at undistorted prices.
b. The trade bias index is TBI (1 NRAagx兾100)兾(1 NRAagm兾100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and
exportable parts of the agricultural sector. The regional average TBI is calculated from the regional averages of the NRAs for exportable and import-competing parts of the
agricultural sector.
c. The RRA is defined as 100*[(100 NRAagt )兾(100 NRAnonagt) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural and
nonagricultural sectors, respectively.
Table 1.14. NRAs for Exportable and Import-Competing Farm Products, and the Trade Bias Index,
16 African Focus Countries, 1955–2004
(percent)
Country, agricultural sector
1955–59
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
—
—
—
—
16.4
—
—
100
26.0
—
—
100
28.9
—
—
100
38.5
—
—
100
28.5
—
—
100
7.4
—
—
100
4.7
—
—
100
4.7
—
—
100
1.1
—
—
100
—
—
—
—
47.2
13.7
0.5
77
50.3
0.1
0.50
76
48.7
15.7
0.55
78
57.3
42.6
0.70
82
57.9
18.9
0.64
81
44.2
22.6
0.54
84
47.9
15.2
0.55
76
41.8
14.8
0.49
75
46.3
16.6
0.54
78
31.5
34.3
0.05
48
52.4
44.0
0.15
49
62.4
44.6
0.32
51
62.2
44.4
0.31
47
43.4
5.5
0.39
46
34.0
2.5
0.28
35
5.0
138.2
0.55
38
30.9
2.4
0.31
34
17.8
16.9
0.29
32
29.7
0.8
0.28
28
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
33.8
—
—
100
44.9
—
—
100
48.0
—
—
100
40.0
—
—
100
20.4
—
—
100
a
Cameroon
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
Côte d’Ivoirea
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
Egypt, Arab Rep. of
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
Ethiopiaa
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
31
(Table continues on the following page.)
32
Table 1.14. NRAs for Exportable and Import-Competing Farm Products, and the Trade Bias Index,
16 African Focus Countries, 1955–2004 (continued)
Country, agricultural sector
Ghana
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
Kenya
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
Madagascar
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
Mozambique
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
Nigeriaa
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
1955–59
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
14.9
9.8
0.22
77
23.9
15.4
0.34
81
54.5
10.8
0.59
76
46.6
11.7
0.53
69
74.4
27.2
0.79
76
76.3
44.6
0.84
72
53.3
53.4
0.69
66
33.1
26.7
0.47
53
19.4
17.5
0.31
73
19.6
28.3
0.37
68
25.5
12.3
0.1
88
16.8
2.4
0.2
75
3.3
4.2
0.09
72
16.3
46.0
0.64
77
2.3
25.3
0.48
88
13.0
40.5
0.57
76
14.0
16.1
0.24
87
26.1
35.4
0.31
54
10.1
2.9
0.12
57
0.5
9.3
0.09
55
0.0
17.7
0.15
92
16.7
20.4
0.31
98
22.5
13.0
0.27
63
16.9
18.3
0.14
34
60.1
19.6
0.47
49
73.0
41.2
0.53
48
62.2
3.1
0.62
48
32.5
3.6
0.34
36
18.0
4.5
0.21
28
20.7
8.3
0.27
26
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
73.3
67.7
0.05
69
68.6
63.6
0.08
60
76.4
72.2
0.38
47
25.5
5.2
0.20
50
3.1
29.5
0.25
40
3.9
57.7
0.39
49
—
—
—
—
34.3
216.4
0.8
65
49.3
176.8
0.82
65
57.2
152.4
0.81
58
51.5
87.8
0.74
54
43.0
67.2
0.66
41
53.4
92.8
0.70
42
24.3
39.7
0.45
28
19.5
28.9
0.36
31
18.5
9.1
0.04
24
Senegala
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
South Africa
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
Sudan
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
Tanzaniaa
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
Ugandaa
NRA, exportables
NRA, import competitors
Trade bias index
Exportables share
—
—
—
—
18.7
19.9
0.3
84
16.6
15.0
0.27
80
39.5
14.1
0.47
84
42.5
24.4
0.54
84
39.7
14.1
0.47
79
9.1
56.3
0.42
73
6.7
61.1
0.42
76
13.5
8.5
0.20
75
19.5
15.3
0.30
76
39.9
10.1
0.6
34
2.7
2.7
0.01
51
8.2
8.6
0.00
42
10.0
5.1
0.14
56
2.5
7.7
0.03
55
34.6
26.3
0.07
42
40.5
1.1
0.40
35
32.9
0.1
0.33
30
16.0
2.8
0.13
31
5.3
2.8
0.10
35
21.9
19.6
0.3
83
35.0
19.6
0.45
81
43.1
10.5
0.36
79
50.9
34.6
0.24
81
37.5
23.8
0.46
84
38.3
8.6
0.26
81
57.8
65.0
0.74
85
64.7
20.4
0.48
75
41.4
6.5
0.35
63
33.8
35.5
0.50
71
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
68.8
40.2
0.43
64
77.4
50.4
0.55
66
75.4
12.0
0.71
68
57.0
5.7
0.58
61
43.8
12.2
0.29
58
36.4
2.4
0.35
56
—
—
—
—
8.4
15.2
0.20
84
15.1
20.6
0.30
82
43.4
42.2
0.58
78
89.7
79.9
0.94
90
66.2
54.8
0.77
69
64.8
58.2
0.77
67
9.4
15.1
0.21
78
1.2
13.9
0.13
66
0.2
14.8
0.13
76
33
(Table continues on the following page.)
34
Table 1.14. NRAs for Exportable and Import-Competing Farm Products, and the Trade Bias Index,
16 African Focus Countries, 1955–2004 (continued)
Country, agricultural sector
1955–59
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
23.4
2.3
0.21
49
29.8
21.6
0.08
55
46.4
41.8
0.06
54
58.2
55.0
0.08
71
47.7
23.0
0.30
18
77.0
67.8
0.28
22
57.7
53.7
0.08
26
45.9
27.0
0.22
37
51.4
10.1
0.46
68
39.4
1.6
0.37
98
36.8
26.2
0.50
99
45.4
1.9
0.44
97
55.8
24.6
0.40
95
50.0
25.2
0.33
85
44.2
17.0
0.31
95
44.3
48.5
0.13
83
34.8
52.5
0.45
82
66.7
78.2
0.83
69
22.7
19.7
0.35
30.4
16.5
0.40
30.5
3.4
0.33
39.0
4.1
0.41
35.2
2.1
0.34
31.0
17.8
0.41
24.1
0.3
0.24
17.5
2.2
0.19
17.6
4.6
0.21
30.1
18.6
0.41
66
38.4
11.8
0.45
64
42.6
1.9
0.44
63
42.6
14.5
0.50
67
35.0
13.2
0.43
61
36.7
58.3
0.60
63
35.8
5.2
0.39
54
26.1
9.8
0.33
54
24.6
1.6
0.26
54
a
Zambia
NRA, exportables
—
NRA, import competitors
—
Trade bias index
—
Exportables share
—
Zimbabwe
NRA, exportables
23.9
NRA, import competitors
26.8
Trade bias index
0.01
Exportables share
100
All studied Africa, unweighted
averagesb
NRA, exportables
3.1
NRA, import competitors
8.5
Trade bias index
0.11
All studied Africa, weighted
averagesb
NRA, exportables
20.6
NRA, import competitors
20.6
Trade bias index
0.00
Exportables share
61
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–17 of this book.
Note: For a definition of the trade bias index, see table 1.13, note b. The exportables share is the share of the gross value of production of tradables at undistorted prices that is
attributable to the exportable subsector of agriculture. — no data are available.
a. For Cameroon, Côte D’Ivoire, Nigeria, Senegal, Uganda, and Zambia: 1960–64 1961–64. For Tanzania: 1975–79 1976–79. For Ethiopia: 1980–84 1981–84.
b. The regional averages of the trade bias index are calculated from the regional averages of the NRAs for exportable and import-competing parts of the agricultural sector.
Introduction and Summary
35
Decomposing the NRA into components reveals a subtle but important influence on the aggregate average. The final “exportables share” row of table 1.14
shows that since the late 1970s, the share of tradable farm products that are
exportable has fallen from two-thirds to just over one-half (from 67 percent to
54 percent). Many governments tax trade in both directions, with negative NRAs
for exportables and positive NRAs for importables, so the changing composition
of African agriculture from exportable to importable helps drive the aggregate
NRA toward zero. This compositional effect adds to the changes within the
exportable and import-competing subsectors illustrated in figure 1.3.
Another important decomposition of the average NRA is provided in
table 1.15, showing the contribution of domestic input subsidies, output taxes or
subsidies, and border measures. In the African context, price distortions for
product-specific inputs contributed so little to the sectoral NRA estimates that in
many cases the case-study authors reported no values at all. Interventions in
domestic markets also contributed relatively little. Most of the region’s measured
NRA is attributable to border measures—largely trade taxes, quantitative trade
restrictions, and the operations of parastatal trading companies.
In aggregate, the total value of taxes on farming has been substantial.
Africa’s antiagricultural bias in NRA terms peaked in the late 1970s, but the
sector has grown, and so the total value of annual transfers from farmers has
risen from around $2 billion in constant 2000 U.S. dollars in the early 1960s
(note that NRAs were available for only four-fifths as much agricultural production then as after 1980) to $10 billion in the 1970s, and back to around
$6 billion in the 1980s (ignoring the mid-1980s period when international
prices were at record lows), 1990s, and 2000–04 (see bottom row of table
1.16a). The distribution across countries is shown in figure 1.4, where it is clear
that the major transfers in recent years have been from farmers in Ethiopia and
Sudan in the east, Zimbabwe in the south, and Côte d’Ivoire and Nigeria in the
west. What is also clear from that figure is how much decline there has been in
such transfers since the late 1970s, particularly in Egypt and Tanzania but also
in many smaller African economies. For Africa as a whole, the latest estimate is
equivalent to a gross annual tax of $40 for each person engaged in agriculture,
down from more than three times that amount in the 1970s (bottom row of
table 1.16b), but still larger than government investment or foreign aid targeted to agriculture (Masters forthcoming, figure 9). As shown in table 1.17
and figure 1.5, the burden of taxation was imposed mainly through the three
major export cash crops (cocoa, coffee, and cotton) plus groundnuts, beef, rice,
and sugar in the 1970s. Three decades later those cash crops are still the main
source of transfer from agriculture, whereas sugar and milk have become positively assisted.
36
Table 1.15. NRAs for Covered Farm Products, by Policy Instrument, 21 African Focus Countries, 1955–2004
(percent)
Policy instrument
Unweighted averages
NRA, inputs
NRA, domestic market support
NRA, border market support
NRA, total
Weighted averagesa
NRA, inputs
NRA, domestic market support
NRA, border market support
NRA, total
1955–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
0.0
1.3
1.3
0.0
0.0
0.6
13.9
14.5
0.0
0.7
18.7
19.3
0.0
0.7
19.5
20.2
0.1
1.1
23.8
24.8
0.1
1.4
19.2
20.5
0.0
0.8
10.8
11.6
0.0
1.1
12.2
13.3
0.0
1.2
7.9
9.1
0.0
1.2
7.7
8.9
0.0
2.1
17.8
19.9
0.1
0.9
12.2
13.0
0.1
0.7
17.2
17.8
0.1
1.0
21.3
22.1
0.3
1.6
19.0
20.3
0.6
1.9
10.9
12.1
0.2
2.1
2.8
0.9
0.1
1.6
10.8
12.4
0.1
2.8
3.9
6.6
0.2
3.0
6.0
8.9
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–18 of this book.
Note: For Cameroon, Côte D'Ivoire, Nigeria, Senegal, Uganda, and Zambia: 1960–64 1961–64. For Tanzania: 1975–79 1976–79. For Ethiopia: 1980–84 1981–84.
a. Weights are based on gross value of agricultural production at undistorted prices.
Table 1.16. Gross Subsidy Equivalents of Assistance to Farmers, 21 African Focus Countries, 1955–2004
(constant 2000 US$ millions)
a. Total
37
Country
1955–59
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995-99
2000–04
Benin
Burkina Faso
Cameroon
Chad
Côte d'Ivoire
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
African focus countries
—
—
—
—
—
1,561
—
103
137
2
—
—
—
—
—
344
—
—
—
—
39
1,829
—
—
83
—
406
2,472
—
188
162
84
—
—
2,193
76
186
686
—
—
36
—
347
1,838
—
—
174
—
603
3,348
—
350
75
185
—
—
1,176
54
500
1,200
—
—
64
149
305
4,682
8
5
263
20
742
4,153
—
334
134
358
12
—
867
234
300
2,547
—
1
199
112
475
9,030
4
11
636
25
2,223
2,046
—
727
157
555
28
280
986
377
330
1,861
1,525
2
462
388
779
10,770
5
12
274
15
1,535
1,204
1,863
404
408
579
22
198
2,198
220
2,067
2,373
1,062
6
144
31
602
6,691
3
5
48
2
1,047
5,348
2,392
91
168
239
11
120
1,402
45
853
2,984
665
4
111
396
533
834
13
10
33
7
752
582
2,188
28
77
73
18
20
794
37
841
3,633
322
7
12
178
536
6,817
17
13
39
8
878
354
2,096
78
35
39
31
51
96
31
456
1,848
576
7
18
197
467
5,314
4
0
4
1
911
571
1,113
34
140
10
2
55
1,034
42
14
1,210
330
3
14
158
851
6,031
(Table continues on the following page.)
38
Table 1.16. Gross Subsidy Equivalents of Assistance to Farmers, 21 African Focus Countries, 1955–2004 (continued)
(constant 2000 US$)
b. Per person engaged in agriculture
Country
Benin
Burkina Faso
Cameroon
Chad
Côte d'Ivoire
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
African focus countries
1961–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
—
—
35
—
275
363
—
86
41
34
—
—
174
55
75
176
—
—
10
—
225
29
—
—
71
—
368
459
—
149
17
67
—
—
86
35
197
292
—
—
15
106
180
68
8
2
102
12
402
535
—
130
27
116
4
—
60
137
122
574
—
2
42
71
249
120
4
3
241
14
1,072
250
—
248
27
162
9
53
69
196
156
381
196
3
88
215
363
134
4
3
99
7
644
144
—
120
—
151
6
34
153
103
1,097
432
121
7
24
15
244
77
2
1
16
1
382
672
—
23
—
56
3
21
96
19
442
482
65
4
16
164
182
9
9
2
10
3
250
75
107
6
8
15
5
3
54
14
440
539
27
7
2
65
161
55
11
3
11
3
280
43
94
15
3
7
7
7
6
11
250
255
43
7
2
67
132
39
3
0
1
0
292
67
45
6
11
2
0
7
68
13
8
156
22
2
2
52
237
41
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–18 of this book.
Note: For Cameroon, Côte D’Ivoire, Nigeria, Senegal, Uganda, and Zambia: 1960–64 1961–64. For Tanzania: 1975–79 1976–79. For Ethiopia: 1980–84 1981–84.
— no data are available.
39
Introduction and Summary
Figure 1.4. Gross Subsidy Equivalents of Assistance
to Farmers, 16 African Countries,
1975–79 and 2000–04
constant 2000 US$ billions
1.5
1.0
0.5
0
⫺0.5
⫺1.0
⫺1.5
⫺2.0
na
n
M
ha
Ca
ad
m
G
er
as
ag
Af
h
ut
So
M
oo
ca
r
a
ric
da
an
oz
am
Ug
bi
Ke
ny
qu
a
e
⫺2.5
countries
constant 2000 US$ billions
1.5
1.0
0.5
0
⫺0.5
⫺1.0
⫺1.5
⫺2.0
n
Su
da
a
pi
io
ig
N
lv
d’
te
Cô
Et
h
ia
er
re
oi
bw
ba
Zi
Re
b
Eg
yp
t
,A
ra
m
p.
an
nz
Ta
e
of
ia
a
bi
m
Za
Se
n
eg
al
⫺2.5
countries
1975–79
2000–04
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–17 of this book.
Note: Data for Tanzania for 1975–79 are for 1976–79.
40
Table 1.17. Gross Subsidy Equivalents of Assistance to Farmers in Africa, Key Covered Products, 1955–2004
(constant 2000 $US millions)
a. By product
Product
Banana
Bean
Beef
Cassava
Cocoa
Coffee
Cotton
Groundnut
Maize
Milk
Millet
Palm oil
Plantain
Poultry
Rice
Sesame
Sheep meat
Sorghum
Soybean
Sugar
Sunflower
Tea
Tobacco
Vanilla
Wheat
Yam
1955–59
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
—
—
152
—
110
12
364
27
28
337
106
—
—
—
327
63
75
136
—
30
—
2
—
—
80
—
1
1
422
4
421
290
1,203
271
306
218
89
117
—
21
379
98
94
1,113
—
31
8
8
306
13
236
2
1
1
813
5
882
496
1,767
501
65
350
95
132
—
35
652
112
148
1,186
1
70
6
10
148
13
91
4
0
3
1,512
10
1,033
837
2,254
979
500
609
81
154
—
87
884
243
279
1,008
2
480
1
37
143
12
160
14
1
258
26
49
2,419
3,139
2,362
1,176
723
10
25
132
—
267
460
298
323
685
14
356
11
154
271
17
117
37
0
232
425
182
1,257
1,574
1,424
881
49
451
17
96
0
190
333
210
338
409
22
254
23
160
215
49
132
79
1
217
1,236
43
833
1,053
947
204
1,913
1,019
3
80
0
19
549
109
490
704
20
403
6
134
219
80
632
13
7
58
2,235
35
532
452
1,569
385
498
522
12
373
2
77
0
80
647
613
20
6
8
212
223
43
166
32
10
137
43
307
731
346
850
545
171
254
66
182
4
185
236
145
595
496
23
70
11
179
211
9
49
262
1
134
1,549
209
890
82
858
640
417
374
40
89
2
52
133
73
319
330
19
429
5
92
315
17
60
182
Introduction and Summary
41
b. By subsector
Years
1955–95
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
Total GSE, all direct
GSE for
assistance to farmers
GSE for
noncovered
covered farm
farm
ImportNonproducts
products
Total Exportables competing tradables
1.9
2.9
5.2
9.5
11.8
6.9
0.4
6.4
4.1
5.0
0.0
0.4
0.2
0.0
0.0
0.8
1.8
1.2
1.6
1.4
1.9
2.2
4.7
9.0
10.5
6.3
0.7
6.8
5.3
6.0
1.1
4.0
6.1
9.6
13.9
9.5
9.5
7.7
6.3
5.7
0.7
1.5
1.0
0.1
2.3
2.1
8.6
0.8
2.0
0.3
0.0
0.0
0.0
0.0
0.2
0.3
0.6
0.7
1.3
1.0
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–18 of this book.
Note: Gross subsidy equivalents (GSEs) include assistance to nontradables and non-product-specific
assistance.
In summary, the level and dispersion of agricultural NRAs confirm that there
has been substantial reform toward less distortion of incentives. However, these
NRAs also suggest that there are still many opportunities for policy changes that
would be both pro-poor and progrowth, raising income for low-income farmers
and improving resource allocation within and between countries.
Assistance to nonfarm sectors and relative rates of assistance
The antifarm policy biases of the past stemmed not only from agricultural policies
but also from policies affecting mobile resources engaged in other sectors. For
example, to the extent that protection to manufacturing also has declined over
time, the relative burden on agriculture has diminished even more than the agricultural NRA suggests.
The results of this study aim to capture intersectoral effects through using the
NRA for nonagricultural products to generate the relative rate of assistance
between farm and nonfarm activities. The case studies were far more focused on
agricultural policy, and their NRAs for the nonfarm sector typically were measured using data on applied trade taxes rather than price comparisons. As a result,
unlike for farm NRAs, the estimated nonfarm NRAs usually do not include the
42
Distortions to Agricultural Incentives in Africa
Figure 1.5. Gross Subsidy Equivalents of Assistance to Farmers
in 21 African Focus Countries, by Product,
1975–79 and 2000–04
sugar
milk
maize
sorghum
poultry
millet
wheat
coffee
product
palm oil
tea
rice
bean
yam
cassava
tobacco
sheep meat
groundnut
cotton
cocoa
beef
3000
2000
1000
0
1000
constant 2000 US$ billions
1975–79
2000–04
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–18 of this book.
effects of quantitative trade restrictions, which were important in earlier decades
but have been relaxed in recent times. The nonfarm NRAs also do not capture
distortions in the services sectors, some of which now produce tradables or
use resources that are mobile between sectors. We can therefore be confident that
the estimated NRAs for nonfarm activities are smaller and decline less rapidly
than in fact was the case, and that our RRA estimates understate the past level of
antifarm bias.
Introduction and Summary
43
Even though the estimates of the NRA for nonfarm tradables should be considered lower-bound estimates, they turn out to be nonetheless quite large. Their
unweighted average among the African focus countries rose from around 12 percent in the 1960s to 27 percent during 1975–84 before declining to around 15 percent during the most recent decade or so. As a result, the unweighted RRA is lower
and dips even more (to 42 percent) in the middle of the studied period than
does the NRA for agriculture, before returning at the end of the period to around
the 20 percent it was in the early 1960s (figure 1.6a).
The 10 five-year RRAs and their two component NRAs for each country are
summarized in table 1.18. A visual picture of RRA changes in the focus countries since the latter 1970s is provided by figure 1.7. Even after the reforms since
the 1980s, only three of these countries had a set of incentives in 2000–04 that
was neutral between agriculture and other tradable sectors, namely, Kenya,
Mozambique, and South Africa. But other than Zimbabwe, none has a worse
set of intersectoral distortions now than it had in the 1970s.
Comparisons across regions and countries
Trends in agricultural NRAs and in intersectoral RRAs for Africa, Asia, and Latin
America are summarized in figure 1.8, which shows that other regions have had
similar—but even steeper—trends over most of the past four decades. These
similarities suggest that common political economy forces might be at work.
Indeed, agricultural NRAs and RRAs tend to be positively correlated with per
capita income and revealed comparative advantage in trade (see Anderson 1995),
even in Africa (but less so than in Asia and Latin America; see chapter 1 of
Anderson and Martin 2008 and Anderson and Valdés 2008). This tendency is
confirmed statistically in the simple regressions with country-fixed effects shown
in figure 1.9, and with the multiple regressions with country- and time-fixed
effects shown in table 1.19.
Looking across countries, one can ask whether policy changes have helped
make the international location of production more or less efficient over
the past five decades. To answer that question well, these NRA data should be
analyzed using a global computable general equilibrium model. Until that can
be done, a crude approach is to examine the standard deviation of RRAs across
the economies of the region over time. That indicator suggests that distortions
were more dispersed across African countries up to the 1980s but less so
thereafter; that measure averaged around 30 percent during 1955–79, nearly
45 percent during the 1980s, but only 20 percent during 2000–04 (final row of
table 1.18).
44
Distortions to Agricultural Incentives in Africa
Figure 1.6. NRAs for Agricultural and Nonagricultural Tradables
and the RRA, 16 African Countries, 1955–2004
a. Unweighted averages across 16 countries
40
30
20
percent
10
0
10
20
30
40
4
00
–0
9
20
95
–9
4
19
90
–9
9
19
85
–8
4
19
80
–8
9
19
75
–7
4
19
70
–7
9
19
19
65
–6
4
–6
60
19
19
55
–5
9
50
years
b. Weighted averages across 16 countries
30
20
percent
10
0
10
20
30
4
20
00
–0
9
19
95
–9
4
19
90
–9
9
19
85
–8
4
19
80
–8
9
19
75
–7
4
19
70
–7
9
19
65
–6
4
–6
60
19
19
55
–5
9
40
years
NRA agriculture
NRA nonagriculture
RRA
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–17 of this book.
Note: For a definition of the RRA, see table 1.13, note c.
Table 1.18. RRAs for Agriculture, 16 African Focus Countries, 1955–2004
(percent)
Country
45
Cameroon
NRA, agricultural
NRA, nonagricultural
RRA
Côte d'Ivoire
NRA, agricultural
NRA, nonagricultural
RRA
Egypt, Arab Rep. of
NRA, agricultural
NRA, nonagricultural
RRA
Ethiopia
NRA, agricultural
NRA, nonagricultural
RRA
Ghana
NRA, agricultural
NRA, nonagricultural
RRA
Kenya
NRA, agricultural
NRA, nonagricultural
RRA
1955–59
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
—
—
—
14.2
18.4
27.6
24.7
22.8
38.5
27.0
25.9
41.9
36.9
29.8
51.0
27.3
29.4
43.6
5.2
24.7
23.1
3.7
19.1
18.8
4.2
18.3
19.0
0.5
14.9
13.4
—
—
—
32.9
15.9
42.1
38.1
11.7
44.6
35.0
9.6
40.7
38.6
20.2
48.7
42.9
14.7
50.2
33.3
17.2
43.1
32.7
11.2
39.5
27.5
7.5
32.6
32.5
4.4
35.4
33.1
31.2
49.0
48.1
42.3
63.4
53.6
44.2
67.8
53.0
40.3
66.5
23.2
23.5
37.8
13.3
17.4
26.3
87.3
20.9
55.6
9.1
25.5
27.3
5.9
25.2
15.5
9.2
24.5
27.0
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
33.8
40.2
52.6
44.9
51.3
63.4
48.0
44.5
63.8
40.0
20.8
49.8
20.4
10.5
27.9
9.3
3.7
12.5
16.6
1.5
18.0
38.8
0.3
38.4
28.9
2.7
30.8
50.2
5.5
47.5
39.9
0.1
39.3
17.3
1.0
18.7
5.7
3.8
9.2
8.8
3.4
11.7
3.3
5.2
8.0
41.5
20.0
17.9
37.7
21.9
12.7
15.7
29.2
10.4
13.3
24.5
30.2
11.8
20.0
6.9
6.5
33.2
29.9
20.3
28.3
6.1
4.3
18.0
18.7
3.1
13.8
9.3
12.3
10.3
1.9
(Table continues on the following page.)
Table 1.18. RRAs for Agriculture, 16 African Focus Countries, 1955–2004 (continued)
46
Country
Madagascar
NRA, agricultural
NRA, nonagricultural
RRA
Mozambique
NRA, agricultural
NRA, nonagricultural
RRA
Nigeria
NRA, agricultural
NRA, nonagricultural
RRA
Senegal
NRA, agricultural
NRA, nonagricultural
RRA
South Africa
NRA, agricultural
NRA, nonagricultural
RRA
Sudan
NRA, agricultural
NRA, nonagricultural
RRA
Tanzania
NRA, agricultural
NRA, nonagricultural
RRA
1955–59
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
15.8
11.3
26.0
24.4
12.4
32.8
21.3
8.7
27.6
41.6
13.3
48.2
57.5
20.0
64.2
38.1
12.7
44.8
16.8
11.5
25.4
8.3
10.2
16.7
1.5
14.4
11.3
—
—
—
—
—
—
—
—
—
—
—
—
70.1
28.0
76.7
67.3
28.0
74.4
75.1
28.0
80.6
15.4
28.0
33.9
16.3
28.2
9.4
26.0
23.1
2.4
—
—
—
54.4
1.4
52.3
30.5
1.1
29.0
18.7
1.7
20.8
19.2
2.9
22.6
41.8
2.9
45.6
24.8
2.2
27.4
20.7
6.2
28.8
14.9
9.0
26.2
7.5
0.5
7.0
12.7
11.1
21.4
10.5
11.6
19.8
30.9
10.3
37.4
31.1
11.1
37.9
28.0
9.1
34.1
8.2
12.4
3.6
9.7
10.9
1.0
8.1
9.8
16.3
10.9
11.4
20.1
5.2
3.6
1.5
11.9
3.2
8.4
0.7
2.5
3.1
5.2
2.6
2.4
31.7
5.8
24.4
17.5
5.5
11.3
14.6
7.0
7.2
7.9
4.0
3.7
0.4
2.6
2.2
25.8
2.4
23.4
36.4
5.6
32.7
48.1
4.7
45.6
28.0
6.7
22.7
32.6
1.5
33.5
38.5
8.5
32.9
53.6
7.1
55.4
28.8
8.8
34.7
14.2
4.2
17.5
—
—
—
—
—
—
—
—
—
59.6
35.5
70.3
68.2
69.9
81.3
55.4
39.8
68.1
32.3
16.6
41.3
31.7
11.9
38.9
20.1
10.3
27.6
1.4
—
—
—
8.4
—
—
—
—
—
0.9
—
—
—
—
Uganda
NRA, agricultural
NRA, nonagricultural
RRA
Zambia
NRA, agricultural
NRA, nonagricultural
RRA
Zimbabwe
NRA, agricultural
NRA, nonagricultural
RRA
African countries,
unweighted averagesa
NRA, agricultural
NRA, nonagricultural
RRA
African countries,
weighted averagesb
NRA, agricultural
NRA, nonagricultural
RRA
Dispersion of RRAc
—
—
—
4.6
9.6
13.0
8.6
19.4
23.1
24.3
34.9
43.1
70.6
68.1
82.1
22.8
53.6
49.5
25.1
52.9
50.6
1.3
21.6
18.8
4.0
31.0
20.6
3.6
26.1
18.0
—
13.8
—
22.4
16.1
33.2
33.3
20.0
43.8
44.4
27.6
56.2
58.4
34.5
68.8
27.6
24.1
41.4
69.7
24.2
75.2
55.2
21.2
62.6
36.2
13.5
43.8
36.7
6.4
40.5
23.9
26.0
1.7
38.5
29.1
52.3
45.6
30.8
58.3
44.2
37.8
59.5
54.5
48.1
69.1
46.7
46.9
63.4
42.9
42.2
59.8
45.2
35.9
59.5
40.0
20.9
50.6
72.9
20.2
77.3
3.1
18.8
13.2
10.9
13.1
21.2
19.7
12.6
28.7
20.6
23.5
35.5
26.2
27.0
41.8
21.5
27.3
38.2
13.9
23.0
29.7
13.9
18.8
27.5
9.3
15.2
21.2
9.4
14.5
20.9
24.1
19.9
36.8
40.7
13.3
3.2
14.8
24.0
19.5
2.3
21.1
24.3
24.9
0.9
25.6
22.7
22.0
4.8
25.2
35.6
13.5
0.8
12.5
42.4
0.1
8.6
7.5
45.2
15.3
2.2
16.6
28.6
8.7
1.6
10.1
23.3
11.9
6.6
17.4
20.0
Source: Anderson and Valenzuela (2008) based on estimates reported in chapters 2–17 of this book.
Note: For a definition of the RRA, see table 1.13, note c. For Cameroon, Côte D’Ivoire, Nigeria, Senegal, Uganda, and Zambia: 1960–64 1961–64. For Tanzania:
1975–79 1976–79. For Ethiopia: 1980–84 1981–84. — no data are available.
47
a. Simple averages of the above (weighted) national averages.
b. Weighted averages of the above national averages, using weights based on gross value of national agricultural production at undistorted prices.
c. Dispersion is a simple five-year average of the standard deviation around a weighted mean of the national RRAs each year.
48
Distortions to Agricultural Incentives in Africa
Figure 1.7. RRAs in Agriculture, 16 African Countries, 1975–79
and 2000–04
30
10
percent
⫺10
⫺30
⫺50
⫺70
Su
er
o
Ca
m
ag
as
ad
da
n
on
r
ca
na
ha
ric
Af
G
M
M
So
oz
ut
h
N
ig
er
ia
a
a
Ke
ny
am
bi
qu
e
⫺90
countries
30
10
percent
⫺10
⫺30
⫺50
⫺70
e
a
Zi
m
ba
bw
bi
lv
oi
d’
te
Cô
Za
m
re
ia
op
Et
hi
e
av igh
er ted
ag
Eg
e
yp
t,
Re
p.
of
Ta
nz
an
ia
al
eg
Se
n
Af
ri
ca
,u
nw
Ug
an
da
⫺90
countries
1975–79
2000–04
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–17 of this book.
Note: For a definition of the RRA, see table 1.13, note c. Data for Ethiopia for the first period are for years
1981–84.
49
Introduction and Summary
Figure 1.8. NRAs and RRAs, Asia, Africa, and Latin America,
1965–2004
20
percent
10
0
10
20
–0
4
20
00
–9
9
19
95
–9
4
19
90
–8
9
19
85
–8
4
19
80
–7
9
19
75
–7
4
70
19
19
65
–6
9
30
years
Africa
Asia
Latin America and the Caribbean
10
0
percent
10
30
50
4
20
00
–0
9
19
95
–9
4
19
90
–9
9
19
85
–8
4
19
80
–8
9
19
75
–7
4
–7
70
19
19
65
–6
9
70
years
Africa
Asia
Latin America and the Caribbean
Source: Anderson and Valenzuela 2008.
Note: The NRAs and RRAs are five-year averages weighted by the value of production at undistorted prices
as weights. For China, the NRAs and RRAs for 1965–81 have been extrapolated back based on the
assumption that they were the same as the average for 1981–84.
50
Distortions to Agricultural Incentives in Africa
Figure 1.9. Real GDP Per Capita, Comparative Advantage, and
NRAs and RRAs, 16 African Countries, 1955–2005
a. Regression of NRA on log real GDP per capita, with country fixed effects
0.6
NRA
0.3
0
0.3
0.6
1
0.5
0
0.5
1
natural log of real GDP per capita (US$ 10,000s)
Africa NRA observations
Africa fitted values
Coefficient: 0.13. Standard error: 0.04. R2: 0.03.
b. Regression of RRA on log real GDP per capita, with country fixed effects
1.5
1
RRA
0.5
0
0.5
1
1
0.5
0
0.5
natural log of real GDP per capita (US$ 10,000s)
Africa RRA observations
Africa fitted values
Coefficient: 0.18. Standard error: 0.05. R 2: 0.04.
1
Figure 1.9. (continued)
c. Regression of NRA on revealed comparative advantage, with country fixed effects
1.8
NRA
1.2
0.6
0
0.6
0
2
4
6
8
10
real comparative advantage
Africa NRA observations
Africa fitted values
Coefficient: 0.01. Standard error: 0.01. R2: 0.03.
d. Regression of RRA on revealed comparative advantage, with country fixed effects
2.1
1.5
RRA
0.9
0.3
0
0.3
0.9
0
2
4
6
real comparative advantage
Africa RRA observations
8
10
Africa fitted values
Coefficient: 0.03. Standard error: 0.01. R2: 0.07.
Source: Based on data in Anderson and Valenzuela 2008, which draws on estimates reported in
chapters 2–17 of this book, and in Sandri, Valenzuela, and Anderson 2007.
Note: The dependent variable for the regressions is the sector’s NRA or RRA by country and year, expressed
as a fraction. The results are ordinary least squares estimates. The revealed comparative advantage is the
share of agriculture and processed food in national exports as a ratio of that sector’s share of global exports.
52
Table 1.19. NRAs and Some of Their Determinants, 21 African Focus Countries, 1960–2004
Explanatory variable
(1)
Ln GDP per capita
0.14*
(0.02)
0.15*
(0.04)
Ln GDP per capita
squared
Importables
Exportables
Revealed comparative
advantagea
Trade specialization
indexb
Constant
R2
Number of observations
Country-fixed effects
Time-fixed effects
0.16*
(0.01)
0.02
5372
No
No
(2)
(3)
(4)
0.10*
(0.02)
0.09*
(0.03)
0.04*
(0.02)
0.35*
(0.01)
0.15*
(0.02)
0.01
(0.04)
0.09*
(0.02)
0.35*
(0.02)
0.20*
(0.02)
0.04
(0.04)
0.09*
(0.02)
0.35*
(0.02)
0.01
(0.00)
0.01
(0.01)
0.18
5372
No
No
0.05
(0.02)
0.02
(0.02)
0.20
3788
No
No
0.03
(0.02)
0.19
3838
No
No
(5)
0.02
(0.04)
0.57*
(0.05)
0.22*
(0.01)
0.03
5372
Yes
No
(6)
(7)
(8)
0.02
(0.04)
0.57*
(0.05)
0.08*
(0.02)
0.31*
(0.01)
0.04
(0.05)
0.69*
(0.07)
0.15*
(0.02)
0.30*
(0.02)
0.15*
(0.05)
0.62*
(0.07)
0.12*
(0.02)
0.31*
(0.02)
0.03*
(0.01)
0.10*
(0.01)
0.18
5372
Yes
No
0.01
(0.03)
0.12*
(0.02)
0.18
3788
Yes
No
0.24*
(0.03)
0.18
3838
Yes
No
(9)
0.13*
(0.04)
0.49*
(0.06)
0.14*
(0.04)
0.13
5372
Yes
Yes
(10)
(11)
(12)
0.14*
(0.04)
0.51*
(0.05)
0.08*
(0.02)
0.33*
(0.01)
0.18*
(0.06)
0.50*
(0.08)
0.15*
(0.02)
0.30*
(0.02)
0.17*
(0.06)
0.54*
(0.08)
0.13*
(0.02)
0.31*
(0.02)
0.02*
(0.01)
0.38*
(0.04)
0.27
5372
Yes
Yes
0.09*
(0.04)
0.42*
(0.05)
0.28
3788
Yes
Yes
Source: Authors’ estimates.
Note: The dependent variable for regressions is the NRA by commodity, country, and year. Results are ordinary least squares estimates. The main explanatory variable
is ln GDP per capita in US$10,000s.
a. For a definition of revealed comparative advantage, see table 11.1, note a.
b. For a definition of the trade specialization index, see table 1.1, note b.
* Significance at the 99 percent level. Standard errors are shown in parentheses.
0.40*
(0.08)
0.28
3838
Yes
Yes
Introduction and Summary
53
Consumer tax equivalents of agricultural policies
The extent to which farm policies alter the retail prices of food, livestock feed, or
inputs into processing industries depends on various intervening factors, including
the extent of competition along the value chain. For simplicity, like the OECD
(2007), we ask only how policies affect buyers at the point on the value chain where
the farm product is first traded internationally. That is the point where the most
direct comparisons can be made between domestic and international prices (such
as the price for milled rice or raw sugar). Then, to sum up the CTEs across commodities and countries, we use consumption values from national sources or from
the FAO food balance sheets. In the case of minor products, we proceed indirectly
by using FAO value-of-trade data and assuming the undistorted value of consumption is production valued at undistorted prices plus imports minus exports.
If there were no farm input distortions and no domestic output price distortions so
that the NRA was entirely the result of border measures such as an import or export tax
or restriction, and if there were no domestic consumption taxes or subsidies in place,
then the CTE would equal the NRA for each covered product. But such domestic distortions are present in several African countries. In addition, the value of consumption
weights used in obtaining the CTEs are quite different from the value of production
weights used for obtaining weighted average NRAs (both measured at undistorted
prices). Hence, the average CTEs are quite different from the average NRAs for numerous countries, particularly those exporting cash crops in order to import staple foods.
This difference can be seen by comparing the country and product CTEs in table 1.20
with the corresponding NRAs in tables 1.10 and 1.12. Nonetheless, the weighted average CTE for the region has moved much like the NRA: starting at around 10 percent
at the time of independence, falling to 17 percent (that is, a 17 percent consumer
subsidy equivalent) by the early 1970s, and then gradually lessening and eventually
nearing zero (with a blip in the latter 1980s, when Egypt overshot in its reform efforts
to reduce the suppression of domestic food prices just when the international price of
food fell to record low levels).The variance both in national CTEs within countries and
in product CTEs across countries also rose before the reforms and fell after the late
1980s (see table 1.20a and 1.20b, including the bottom row of each).
In dollar terms, the subsidies to consumers of farm products in Africa are
largest in Ethiopia and Sudan, while the tax on consumers historically has been
largest in Nigeria and South Africa. Egypt before its reforms in the 1980s was also
a huge subsidizer of food consumers. For the region in 2000–04, the transfer on
average from producers to consumers amounted to around $1.7 billion a year,
which is only one-third (when expressed in 2000 U.S. dollars) the average annual
transfer in the 1970s (table 1.21a). Among the covered products, the diversity in
measures across the continent means that no products stand out as having
extreme NRAs (table 1.21b), unlike in other regions, where the biggest transfers
are from consumers to producers of milk, rice, and sugar.
54
Table 1.20. CTEs for Covered Farm Products, 21 African Focus Countries, 1960–2004
(percent, at primary product level )
a. Aggregate CTEs, by country
Country
Benin
Burkina Faso
Cameroon
Chad
Côte d’Ivoire
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
Unweighted average
Weighted averagea
Dispersion of national CTEsb
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
—
—
0.4
—
9.4
47.1
—
2.1
26.1
15.9
—
—
31.2
10.8
4.0
15.2
—
—
1.0
26.7
28.7
7.4
7.8
21.3
—
—
0.7
—
20.1
49.5
—
4.4
21.3
22.1
—
—
23.1
10.3
10.2
28.9
—
—
1.8
38.5
35.4
12.1
11.8
22.8
0.0
0.0
1.3
0.0
8.4
49.6
—
2.5
12.8
19.2
0.0
—
14.0
30.2
0.2
41.8
—
0.0
1.1
46.3
40.1
13.3
16.6
19.8
0.0
0.0
3.7
0.0
3.8
20.8
—
4.6
20.7
26.2
0.0
50.5
9.0
25.2
6.7
16.8
42.0
0.0
1.3
54.3
53.7
12.7
8.7
22.7
0.0
0.0
3.7
0.0
10.8
12.3
15.2
1.7
26.0
42.4
0.0
39.6
4.3
18.3
29.8
24.2
53.7
0.0
1.0
20.8
39.4
10.4
6.1
21.6
0.0
0.0
1.1
0.0
3.9
109.5
17.6
10.2
14.8
13.4
0.0
53.4
15.2
32.0
14.7
30.1
41.3
0.0
0.9
68.0
37.1
3.3
15.5
40.6
0.0
0.0
0.4
0.0
4.6
2.7
20.3
4.0
14.6
1.2
0.0
3.6
5.6
31.9
8.6
47.7
17.5
0.0
0.3
54.4
42.4
7.6
8.2
19.9
0.0
0.0
0.2
0.0
4.3
13.9
12.1
0.8
12.0
1.9
0.0
5.5
7.4
6.0
6.6
21.2
23.1
0.0
1.7
30.5
36.6
4.2
0.5
13.9
0.0
0.0
0.0
0.0
3.8
2.8
10.0
2.8
18.7
4.0
0.0
31.1
0.9
7.0
0.6
5.2
8.8
0.0
1.3
31.3
63.7
3.6
3.2
17.9
b. Aggregate CTEs, by product
Product
Banana
Bean
Beef
Cassava
Cocoa
Coffee
Cotton
Groundnut
Maize
Milk
Millet
Palm oil
Plantain
Poultry
Rice
Sesame
Sheep meat
Sorghum
Soybean
Sugar
Sunflower
Tea
1961–64
2
6
21
0
31
35
46
22
15
23
3
25
0
11
27
45
7
102
—
2
19
10
1965–69
4
2
28
0
46
41
54
36
3
32
4
31
0
11
33
56
13
94
14
11
17
6
1970–74
0
3
36
0
43
43
55
47
3
42
2
45
0
12
16
58
17
73
32
16
6
22
1975–79
2
37
7
1
60
59
50
41
1
1
0
19
0
24
10
61
14
56
43
10
8
46
1980–84
1
48
18
3
48
50
43
39
10
22
2
29
0
18
9
51
12
34
43
6
19
32
1985–89
1
64
48
1
34
46
31
12
48
67
3
13
0
3
41
38
32
69
41
54
13
27
1990–94
3
25
32
1
20
47
55
26
10
27
4
107
0
6
9
38
47
68
53
2
13
41
1995-99
5
24
6
3
22
37
40
32
4
8
6
41
0
13
2
40
36
38
51
6
0
40
2000–04
2
19
21
3
34
14
58
36
2
19
6
17
0
2
10
38
18
40
56
45
1
36
55
(Table continues on the following page.)
56
Table 1.20. CTEs for Covered Farm Products, 21 African Focus Countries, 1960–2004 (continued)
b. Aggregate CTEs, by product (continued)
Product
Tobacco
Vanilla
Wheat
Yam
Weighted averagea
Dispersion of region’s
product CTEsc
1961–64
39
—
36
0
8
30.3
1965–69
38
—
22
0
12
30.4
1970–74
49
—
19
0
17
28.0
1975–79
57
—
2
1
9
30.3
1980–84
50
—
14
1
6
27.9
1985–89
50
—
34
0
16
41.9
1990–94
34
—
8
1
8
36.9
1995-99
37
—
3
3
0
26.4
2000–04
46
—
1
3
3
27.4
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–18 of this book.
Note: The table reflects the assumption that the CTE is the same as the NRA derived from trade measures (that is, not including any input taxes, input subsidies, or domestic
producer price subsidies or taxes). For Cameroon, Côte D'Ivoire, Nigeria, Senegal, Uganda, and Zambia: 1960–64 1961–64. For Tanzania: 1975–79 1976–79. For Ethiopia:
1980–84 1981–84. — no data are available.
a. Weights are consumption valued at undistorted prices, where consumption (from the FAOSTAT Database) is the sum of production plus imports net of exports plus change in
stocks of the covered products.
b. Simple five-year average of the annual standard deviation around a weighted mean of the national average CTEs.
c. Simple five-year average of the annual standard deviation around a weighted mean of the regional average CTE for the covered products shown above.
Table 1.21. Value of CTEs of Policies Assisting Producers of Covered Farm Products, 21 African Focus Countries,
1965–2004
(constant 2000 US$ millions, at the primary product level)
a. Aggregate CTEs, by country
57
Country
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
Benin
Burkina Faso
Cameroon
Chad
Côte d’Ivoire
Egypt, Arab
Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
Senegal
South Africa
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
African focus
countriesa
—
—
12
—
139
2,950
0
0
24
0
65
3,891
0
0
57
0
39
2,196
0
0
30
0
151
1,631
0
0
8
0
54
9,315
0
0
5
0
76
224
0
0
3
0
63
1,087
0
0
0
0
42
221
—
31
19
137
—
—
1,338
51
310
792
—
—
24
160
125
2,754
—
33
71
321
0
—
1,011
226
145
1,874
—
0
20
188
216
6,063
—
44
282
282
0
206
947
334
323
898
993
0
25
310
482
4,038
1,014
78
241
386
0
183
769
177
1,534
1,557
730
0
46
128
321
3,450
1,435
116
75
93
0
152
1,495
253
627
2,136
393
0
17
214
239
7,138
1,427
59
143
9
0
19
755
190
440
3,073
139
0
7
191
270
4126
944
18
91
16
0
58
1,209
32
346
1,265
397
0
49
136
217
215
759
61
134
34
0
164
111
38
14
442
165
0
37
180
408
1,729
(Table continues on the following page.)
58
Table 1.21. Value of CTEs of Policies Assisting Producers of Covered Farm Products, 21 African Focus Countries,
1965–2004 (continued)
b. Aggregate CTEs, by product
Product
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
Banana
Bean
Beef
Cassava
Cocoa
Coffee
Cotton
Groundnut
Maize
Milk
Millet
Palm oil
Plantain
Poultry
Rice
Sesame
Sheep meat
Sorghum
1
1
787
5
15
68
1,170
360
67
350
53
116
0
30
506
45
105
1,223
0
3
1,415
10
24
83
1,658
759
262
609
33
156
0
70
756
119
232
1,138
1
231
176
50
118
111
2,126
889
76
10
6
148
0
259
347
155
212
940
0
211
908
189
47
175
1,212
698
576
451
26
146
0
185
352
110
187
599
1
189
2,861
43
38
223
742
135
2,497
1,019
40
95
0
17
955
47
424
864
6
54
2,087
33
44
151
1,401
345
627
522
58
387
2
83
219
35
662
706
8
132
264
293
82
146
654
486
306
258
89
185
4
206
45
42
499
615
0
127
1,247
200
138
30
756
595
246
375
80
112
2
61
206
22
106
430
Soybean
Sugar
Sunflower
Tea
Tobacco
Vanilla
Wheat
Yam
All covered productsa,b
0
52
6
1
65
—
341
4
2,754
1
355
1
4
27
0
528
14
6,063
10
345
12
24
74
5
96
37
4,038
24
392
26
24
35
8
837
81
3,450
19
571
12
16
39
38
2,120
13
7,138
22
32
16
20
38
9
463
30
4,126
26
60
0
18
14
2
209
249
215
23
521
6
15
41
17
49
179
1,729
Source: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–18 of this book.
Note: For Cameroon, Côte D’Ivoire, Nigeria, Senegal, Uganda, and Zambia: 1960–64 1961–64. For Tanzania: 1975–79 1976–79. For Ethiopia: 1980–84 1981–84.
Because of this, the totals in tables a and b in these three time periods might not match exactly. — no data are available.
a. These dollar amounts do not include noncovered farm products, which amount to almost one-third of agricultural output (see last row of table 1.11) nor any markup that
might be applied along the value chain.
b. These data include also all the minor covered products not shown above.
59
60
Distortions to Agricultural Incentives in Africa
The link between antifarm and antitrade policies
A visual picture of the overall finding—that distortions have been reduced substantially since the 1970s—is provided in figure 1.10. That figure shows values of
agriculture’s trade bias index on the horizontal axis and the relative rate of assistance on the vertical axis. An economy with no antiagricultural bias (RRA 0)
and no antitrade bias within the farm sector (TBI 0) would be located at the
intersection of the two axes in the upper right-hand corner. In 1975–79, South
Africa was the only economy anywhere near that point, and most other SubSaharan African economies were far to the southwest of it. In 2000–04, by
contrast, Kenya and Nigeria were also close to that neutrality point, and all the
other countries shown were far closer than they were in the 1970s. This is not to
say that few distortions are left within the agricultural sector, however, because
RRA and TBI values in the ranges of 20 to 40 and 0.2 to 0.4, respectively,
are not small, and because within most countries’ agricultural sector, product
NRAs are still widely dispersed. Note also from figure 1.10 that the 2000–04 values
fit roughly along a 45-degree line, because the tax burden on agriculture in these
countries consists primarily of taxes on trade.
International spillovers and multilateral agreements
The distortion estimates take each country’s border prices as given, but in reality
each country’s policies do have some small effect on other country’s prices. An
import restriction that raises domestic prices will lower prices elsewhere, and an
export tax that lowers domestic prices will raise them elsewhere. In addition,
attempts by one country to stabilize its domestic prices over time will reduce the
stability of international prices. As a result, each country’s openness to trade contributes to an international public good, offering other countries more favorable
and often more stable border prices. This is a classic collective-action problem,
calling for a multilateral agreement to lock in freer trade policies.
Collective action to stabilize world prices is precisely what was sought during
the GATT’s Uruguay Round Agreement on Agriculture, through tariff bindings
and disciplines on administered domestic prices. Tariff bindings can reduce the
extent of spillovers by restricting the range over which tariffs can increase in
response to low prices. But WTO bindings are now so far above applied import
tariffs that this discipline on food-importing members in years of low international prices is very weak. The most recent stage of the Doha round of WTOsponsored multilateral trade negotiations broke down in mid-2008 because many
developing countries were calling for policy space in the form of a special safeguard mechanism that would have allowed even more scope for limiting
imports—something richer members including the United States were not willing
61
Introduction and Summary
Figure 1.10. Relationship between the RRA and the Trade Bias
Index for Agriculture, 16 African Focus Countries,
1975–79 and 2000–04
a. 1975–79
Nigeria
20
10
South Africa
0
RRA (%)
10
20
Sudan
30
Senegal
Egypt, Arab Rep. of
40
Ghana
50
Madagascar
Côte d’Ivoire
60
Tanzania
70
Zimbabwe
Zambia
Mozambique
80
Uganda
1
0.8
0.6
0.4
0
0.2
0.2
trade bias index
b. 2000–04
20
10
RRA (%)
Kenya
Mozambique
0
10
Ghana
20
Sudan
30
Tanzania
South Africa
Nigeria
Madagascar
Senegal Uganda
Egypt, Arab Rep. of
Côte d’Ivoire
40
Zambia
50
60
70
80
1
0.8
0.6
0.4
0.2
0
0.2
trade bias index
Sources: Anderson and Valenzuela 2008, based on estimates reported in chapters 2–17 of this book.
62
Distortions to Agricultural Incentives in Africa
to sanction in a new agreement. Moreover, there is no corresponding GATT/WTO
discipline on food export restrictions, which, as 2008 has starkly revealed, can be a
problem in years of high international prices.
Africa’s share of world trade is so small that its policies contribute relatively
little to the collective-action problem described above, except to the extent that
African governments have sided with such countries as Indonesia and India in
demanding special safeguards, thereby delaying or preventing the emergence of a
new WTO agreement. As the victim rather than the perpetrator of international
agricultural-policy spillovers, however, Africa could benefit greatly from a more
effective system of multilateral trade rules. International agreements may also
help African governments undertake reforms that would not otherwise be possible, allowing them to make commitments and assemble coalitions that cannot
otherwise be sustained. The details of WTO and other international agreements
are outside the scope of this book, but generally our results regarding national
policies suggest that multilateral agreements can help each government deliver
more favorable market conditions for agricultural development at the very least
by limiting the rise of import restrictions in other countries. In addition, following the imposition by numerous food-exporting developing countries in 2008 of
export restrictions that harmed food importers, perhaps WTO members may
eventually agree to limit export restrictions as well.
Summary: What have we learned?
Each of the case studies presented in this volume provides detailed insights into
Africa’s wide variety of country experiences. Aggregating their results to characterize all of Africa necessarily obscures as much as it reveals. Making generalizations is sometimes useful, however, if only to allow comparison with other regions
and to detect common trends that cannot be seen in individual cases. Averaging
over the 21 African countries considered in this study, our principal findings are
the following.
African governments have removed much of their earlier antifarm and antitrade
policy biases. Government policy biases against agriculture had worsened in the
late 1960s and 1970s, primarily through increased taxation of exportable products. Reforms of the 1980s and 1990s reversed that trend, and average rates of
agricultural taxation are now back to or below the levels of the early 1960s.
Substantial distortions remain and still impose a large tax burden on Africa’s poor.
Measured in constant (2000) U.S. dollars, the transfers paid by farmers in the 21
focus countries peaked in the late 1970s, at over $10 billion a year, or $134 for each
farm worker. In 2000–04, the burden of taxation averaged $6 billion a year, or $41
for each person working in agriculture. However, even this lower amount is
Introduction and Summary
63
appreciably larger than public investment in or foreign aid to the sector. This
continuing taxation in Africa contrasts with both Asia and Latin America, where
the average agricultural NRAs and RRAs had risen all the way to zero by the early
21st century from lower levels than in Africa (although, like Africa, those other
regions still have a wide dispersion of NRAs across products and countries within
their regions).
African farmers have become less taxed in part because of the changing trade orientation of African agriculture. Reduced taxation of farmers has occurred in part
because of a decline in the share of output that is exportable and a corresponding
rise in the share from import-competing agricultural industries. That subsector’s
rate of protection from imports has fluctuated but remains positive.
Trade restrictions continue to be Africa’s most important instruments of agricultural intervention. Other interventions such as domestic taxes and subsidies on
farm inputs and outputs and non-product-specific assistance are a small share of
total distortions to farmer incentives in Africa. As a result, policy incidence on
consumers tends to mirror the incidence on producers, with fiscal expenditures
playing a much smaller role than in more-affluent regions.
Differences in NRAs and RRAs across commodities and countries are still substantial. Dispersion rates, as measured by the standard deviation in NRAs and RRAs
across commodies and countries, rose and then fell with the average degree of
intervention in the decades on either side of the 1970s. Looking forward, whatever
the overall level of taxation or assistance, moving toward more uniform rates
within the farm sector and between countries within the region could still yield
substantial increases in efficiency of resource use.
Implications for the Future
Readers of this volume will draw their own conclusions as to what these findings
imply about the future of agricultural policy in Africa, and wide variations in
NRAs among countries will no doubt continue. We hope that, despite difficult
conditions, many African governments will continue to reduce taxation of agricultural exports, improve market institutions, and invest in rural public goods,
and that producers will respond in ways that generate faster economic growth and
sustained poverty alleviation. That has been the pattern in other regions, and
African countries have shown their willingness and ability to begin these changes.
Our hopes are tempered by experience, however, including particularly the
experience of agricultural policy transition in other regions. A fundamental
concern in agricultural policy over time as economies join the middle-income
group is “overshooting.” In response to rural poverty and inequality, many countries start protecting agriculture soon after they stop taxing it.6 This protection
64
Distortions to Agricultural Incentives in Africa
imposes large costs on consumers and slows national economic growth. Countries
that lock in relatively efficient and equitable policies as soon as they are attained
can therefore enjoy a high payoff relative to those that allow farm support policies
to become increasingly costly over time. In particular, policies that raise the prices
of staple foods impose serious costs on the urban poor and on rural net buyers of
these products, as has been demonstrated by recent increases in their prices for
other reasons (Ivanic and Martin 2008).
Rural-urban poverty gaps can be addressed in far more efficient ways than by
subsidizing production or raising food prices. For example, rural poverty can and
has been alleviated in parts of Africa and Asia by the mobility of some members of
farm households who work full- or part-time off the farm and repatriate part of
their higher earnings to those remaining on the farm (Otsuka and Yamano 2006;
World Bank 2007). Concerted government interventions through targeted social
policy measures can also be an efficient and effective way to reduce gaps between
rural and urban incomes and raise national incomes overall (Winters, McCulloch,
and McKay 2004). Efficient ways of assisting the left-behind groups of poor (nonfarm as well as farm) households include public investment measures that have
high social payoffs such as basic education and health care, rural infrastructure,
and agricultural research and extension.
The rest of this volume contains a collection of analytical narratives of the policy experiences of 21 African countries over the past half century, each illustrated
by detailed quantitative estimates of the extent of distortions to farmer incentives.
While they bring new empirical evidence to bear on many common concerns,
they inevitably also raise new questions. Among the most important are: What
impact have past and recent policies had on economic welfare, agricultural prices,
income inequality, and poverty? Why did governments intervene in the ways they
did, especially when some of those means were grossly inefficient and inequitable?
More in-depth empirical analysis is now possible, thanks to the provision of the
distortion estimates reported here and in the three companion volumes cited in
note 1. Some early findings from such analyses will appear in the project’s forthcoming books. For example, Anderson, Valenzuela, and van der Mensbrugghe
(forthcoming) provide results from a global economy-wide model of the impacts
on agricultural markets, national economic welfare, and net farm incomes of distortions to the world’s goods markets as of 2004. How those distortions, both
own-country and rest-of world’s, affect the extent of poverty and inequality are
explored in a series of country case studies in Anderson, Cockburn, and Martin
(forthcoming), using global and national economy-wide models that are
enhanced with detailed earning and spending information of numerous types of
urban and rural households. And in Anderson (forthcoming b), a broad range of
theoretical and econometric analyses are brought together in an attempt to shed
Introduction and Summary
65
more light on the political economy forces that generated the evolving pattern of
inter- and intrasectoral distortions to farmer and food consumer incentives over
the past half century. Our hope is that the results from these studies will spawn
many more such analyses in the years to come. We hope too that these comparative analyses will help African governments to adopt more successful policies,
allowing African countries to achieve faster economic growth, poverty alleviation
and improved living conditions for all.
Notes
1. The other three regional studies are Anderson and Martin (2008), Anderson and Swinnen
(2008), and Anderson and Valdés (2008). Together with the present volume and comparable studies of high-income countries, they form the basis for a global overview volume (Anderson forthcoming a).
2. Our definition of a policy-induced price distortion follows Bhagwati (1971) and Corden (1997)
and includes any policy measure at a country’s border (such as a trade tax or subsidy, a quantitative
restriction on trade, or a dual or multiple foreign exchange rate system, assuming the country is small
enough to have no monopoly power in international markets). It also includes any domestic producer
or consumer tax; subsidy; or restraint on output, intermediate inputs, or primary factors of production (except where it is needed to directly overcome an externality, or where it is set optimally across all
products or factors, for example as a value added tax to raise government revenue). For more on this
project’s methodology, see Anderson, et al. (2008).
3. Some analytics and empirical evidence regarding the appropriate choice of denominator are
provided in Masters (1993).
4. Corden (1971) proposed that free-trade volumes be used as weights, but because they are not
observable (and an economy-wide model is needed to estimate them), the common practice is to compromise by using actual distorted volumes but undistorted unit values or, equivalently, distorted values
divided by (1 NRA). If estimates of own-and cross-price elasticities of demand and supply are available, a partial equilibrium estimate of the quantity at undistorted prices could be generated, but if those
estimated elasticities are unreliable, this estimate may introduce more error than it seeks to correct.
5. Recall that our sample covers around 90 percent of Sub-Saharan Africa’s economy. For North
Africa, the sample includes only Egypt, which accounts for almost half the population of North Africa
but only 37 percent of its GDP.
6. Details on this and other patterns in agricultural distortions data are provided in Anderson
(forthcoming b).
References
Anderson, K. 1995. “Lobbying Incentives and the Pattern of Protection in Rich and Poor Countries.”
Economic Development and Cultural Change 43 (January): 401–23.
———, ed. Forthcoming a. Distortions to Agricultural Incentives: A Global Perspective, 1955 to 2007.
———, ed. Forthcoming b. Political Economy of Distortions to Agricultural Incentives.
Anderson, K., J. Cockburn, and W. Martin, eds. Forthcoming. Agricultural Price Distortions, Inequality
and Poverty.
Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675–704.
Anderson, K., and W. Martin, eds. 2008. Distortions to Agricultural Incentives in Asia. Washington, DC:
World Bank.
66
Distortions to Agricultural Incentives in Africa
Anderson, K., and J. Swinnen, eds. 2008. Distortions to Agricultural Incentives in Europe’s Transition
Economics. Washington, DC: World Bank.
Anderson, K., and A. Valdés, eds. 2008. Distortions to Agricultural Incentives in Latin America. Washington,
DC: World Bank.
Anderson, K., and E. Valenzuela. 2008. Global Estimates of Distortions to Agricultural Incentives, 1955 to
2007. Database spreadsheet available at http://www.worldbank.org/agdistortions.
Anderson, K., E. Valenzuela, and D. van der Mensbrugghe. Forthcoming. “Effects of Distortions on
Global Welfare, Farm Incomes, and Agricultural Markets.” In K. Anderson, Forthcoming a,
chapter 12.
Bhagwati, J. N. 1971. “The Generalized Theory of Distortions and Welfare.” In Trade, Balance of
Payments and Growth, ed. J. N. Bhagwati, R. W. Jones, R. A. Mundell, and J. Vanek. Amsterdam:
North-Holland.
Chen, S., and M. Ravallion. 2007. “Absolute Poverty Measures for the Developing World, 1981–2004.”
Policy Research Working Paper 4211. World Bank, Washington, DC.
Commission on Growth and Development, chaired by M. Spence. 2008. The Growth Report: Strategies
For Sustained Growth and Inclusive Development. Washington, DC: Commission on Growth and
Development.
Corden, W. M. 1971. The Theory of Protection. Oxford, U.K.: Clarendon Press.
———. 1997. Trade Policy and Economic Welfare, 2d ed. Oxford, U.K.: Clarendon Press.
Ivanic, M., and W. Martin. 2008. “Implications of Higher Global Food Prices for Poverty in LowIncome Countries.” Agricultural Economics (39) 35: 405–16.
Krueger, A. O., M. Schiff, and A. Valdés. 1988. “Agricultural Incentives in Developing Countries: Measuring the Effect of Sectoral and Economy-wide Policies.” World Bank Economic Review 2 (3):
255–72.
———. 1991. The Political Economy of Agricultural Pricing Policy, vol 3: Africa and the Mediterranean.
Baltimore: Johns Hopkins University Press for the World Bank.
Lerner, A. 1936. “The Symmetry between Import and Export Taxes.” Economica 3 (August): 306–13.
Lloyd, P. J. 1974. “A More General Theory of Price Distortions in an Open Economy.” Journal of International Economics 4 (November): 365–86.
Masters, W. A. 1993. “Measuring Protection in Agriculture: The Producer Subsidy Equivalent Revisited.” Oxford Development Studies 21 (2): 133–42.
———. Forthcoming. “Beyond the Food Crisis: Trade, Aid and Innovation in African Agriculture.”
African Technology Development Forum 5 (1).
Ndulu, B., S. A. O’Connell, R. H. Bates, P. Collier, C. C. Soludo, J.-P. Azam, A. K. Fosu, J. W. Gunning,
and D. Njinkeu. 2008. The Political Economy of Economic Growth in Africa, 1960–2000, vol. 1 and 2.
New York: Cambridge University Press.
OECD (Organisation for Economic Co-operation and Development). 2007. Agricultural Policies in
OECD Countries: Monitoring and Evaluation 2007. Paris: OECD.
Otsuka, K., and T. Yamano. 2006. “Introduction to the Special Issue on the Role of Nonfarm Income in
Poverty Reduction: Evidence from Asia and East Africa.” Agricultural Economics 35 (November,
supplement): 373–97.
Sandri, D., E. Valenzuela, and K. Anderson. 2007. “Economic and Trade Indicators for Africa.” Agricultural Distortions Working Paper 21. World Bank, Washington, DC.
Thiele, R. 2004. “The Bias against Agriculture in Sub-Saharan Africa: Has It Survived 20 Years
of Structural Adjustment Programs?” Quarterly Journal of International Agriculture 42 (1):
5–20.
Valenzuela, E., J. Croser, M. Kurzweil, S. Nelgen, and K. Anderson. 2007. “Annual Estimates of African
Distortions to Agricutural Incentives.” Agricultural Distortions Working Paper 55. World Bank,
Washington, DC.
Vousden, N. 1990. The Economics of Trade Protection. Cambridge, U.K.: Cambridge University
Press.
Introduction and Summary
67
Winters, L. A., N. McCulloch, and A. McKay. 2004. “Trade Liberalization and Poverty: The Empirical
Evidence.” Journal of Economic Literature 62 (March): 72–115.
World Bank. 1986. World Development Report 1986: Trade and Pricing Policies in World Agriculture.
New York: Oxford University Press.
———. 2007. World Development Report 2008: Agriculture for Development. Washington, DC: World
Bank.
———. 2008. World Development Indicators. Washington, DC: World Bank.
Part II
NORTH AFRICA
2
Arab Republic
of Egypt
James Cassing, Saad Nassar,
Gamal Siam, and Hoda Moussa*
Egypt is an ancient civilization but with a certain geopolitical regularity where
agriculture and incomes are concerned. Foremost, for over 50 centuries there has
been an inexorable pressure of a growing population against fixed resources—
land and water. Additionally, for a very long time, local central rulers and an
assortment of foreign powers have used control over limited agricultural land as a
source of political patronage and taxation aimed to achieve particular ends.
Historically, this situation has disadvantaged the rural peasantry despite periodic
infrastructure investments and the introduction of lucrative new crops such as
Egyptian cotton in 1820.
This study focuses on the period 1955–2005. In the early part of that era,
despite an articulation of concern for the rural population, a policy emphasis on
industrialization and import substitution met with mixed success as promotion of
industry, tempered especially by the 1952 revolution and ultimately Nasser socialism,
reduced incentives to both the basic agricultural sector and to international trade.
This antiagricultural and antitrade policy bias, in turn, has held important implications for the prosperity of the population generally and especially for rural
incomes in a country where even today one-third of the population is in the agricultural sector and more than one-half might be characterized as rural. The
period since the mid-1980s has been characterized by a policy reorientation away
* The authors are grateful for helpful comments from Steven Husted, Daniel Brent, and workshop
participants. Detailed data and estimates of distortions reported in this chapter can be found in
Cassing et al. (2007).
71
72
Distortions to Agricultural Incentives in Africa
from state planning and toward reinvigorating the private sector, including
agriculture.
Even though the current policy tendency leans clearly toward embracing markets and free enterprise, it is confronted with some burdensome legacies of the past.
On the one hand, the government of Egypt is openly committed to the goal of
increased incomes and employment for all Egyptians. To that end, it has actively
pursued sensible policies of macroeconomic stability, along with a strong commitment to private sector development, privatization of state-owned firms, and legal
reforms that affect investment. The government has also pursued a series of trade
barrier reductions, including abolition of most quantitative restrictions and significant reductions in tariffs, especially for certain key capital goods, and entered a
number of regional and global free trade commitments. Although there was some
hesitation in policy reform and relative economic stagnation from 2000 to 2003,
bold reform once again seems to be well on track (Srinivasan 2005; IMF 2006).
However, the legacy of the past is daunting for even well-intentioned policy
reformers. Historically, by the middle of the 20th century, a long period of widely
unpopular European influence had left wealth concentrated in the hands of foreigners and a domestic elite.1 Following the revolution of 1952 that brought Gamal
Abdel Nasser to power, and particularly after the sanctions following the Suez crisis
of 1956, the economy was realigned structurally. The state assumed ownership of
the means of production, and it regulated prices. The public sector soon accounted
for 75 percent of gross domestic product (GDP), and with increased centralized
planning came such things as directives about what a certain product should look
like and how it should perform. At the same time, foreign companies were nationalized, which virtually shut off inflows of foreign investment.
In the 1970s, in response to slower growth, the government began an open-door
policy with a more outward-looking orientation. Since the 1980s, the pace of economic reform has increased, with an emphasis on reliance on markets, increased
foreign trade and investment, and, beginning in the 1990s, privatization. But the
history of socialism and Egypt’s trade orientation toward Comecon (Council for
Mutual Economic Assistance) countries has left many Egyptians with a distrust of
markets and of foreign trade. Add to this a stifling bureaucracy, and one can appreciate the difficulty in advancing deeply needed economic policy reforms.
Egyptian farmers grow a wide variety of crops—grains, cotton, sugar, berseem
(clover), legumes, fruits, and vegetables—and also produce meats and dairy products. Over the years the agricultural and related sectors have been subject to significant policy interventions and large structural changes. For about 10 years after the
1952 revolution, agriculture continued to dominate output and employment, and
cotton was the main export. The sector was driven by close-to-free-market incentives. Since about 1960, however, owing somewhat to both direct and indirect policy
Arab Republic of Egypt
73
interventions, agriculture has diminished in relative economic importance. Today it
contributes only one-seventh of GDP, although agricultural employment remains
disproportionately higher, at around one-third of national employment. Meanwhile, agricultural exports have declined substantially in importance and
agricultural imports of the staples wheat and flour have increased dramatically.
Combined with the politically sensitive policy of substantial bread subsidies to
consumers, Egypt’s food policy today represents a large and growing drain on
government finances that is difficult to sustain.
As livestock production has become more important, maize has increased in
both domestic cropping and in imports. Berseem production has expanded as
well, while rice production, perhaps subsidized more than any other crop by a
policy of free irrigation water, remains important for domestic consumption and
has some importance as an export.
Although food security has always been and remains a priority, agricultural
policies other than those pertaining to water are largely oriented toward institutionalizing market incentives in production and, except for bread and to some
extent edible oil and sugar, in consumption. This is the reverse of policies of the
1960s and 1970s. In that earlier period, policy emphasized the mobilization of
agricultural savings in order to subsidize the urban consumer and promote industrialization. During the Nasser era, the government also sought to alter the
traditional biennial crop rotation, which was believed to be harsh on the land.
Market distrust meant virtually all farmers became members of cooperatives. The
cooperatives, in turn, were run by government bureaucracies solely entrusted to
provide inputs to and buy outputs from farmers at artificially low administered
prices.
The Principal Bank for Development and Agricultural Credit, originally established in 1931, became the instrument of allocation for agricultural trade and
finance. At the same time, some land reforms and rent controls were implemented, along with government-dictated cropping patterns. Most social histories
recount that the system was highly inefficient and somewhat corrupt, probably
exploiting the rural peasantry to the benefit of a controlling class of “rural notables” at the village level. Certainly the agricultural sector was extremely repressed.
Even relatively freely traded agricultural products—livestock, certain animal
feeds, and some horticulture—suffered from high industrial trade protection and
an overvalued currency.
Important market-oriented reforms began in 1986, the terminal year in the case
study by Dethier in Krueger, Schiff, and Valdez (1991), and by 1994 the private sector was substantially enfranchised once again. Egypt by 2006 had engineered a
remarkable, almost unprecedented, reversal of its agricultural policies. Nonetheless,
as reported here, some indirect disincentives to the agricultural sector remain, and
74
Distortions to Agricultural Incentives in Africa
the government continues to control the sugar sector. In addition, food consumer
policy, particularly untargeted bread subsidies, remains problematic.
The remainder of this study attempts to amplify the policy discussion and to
quantify its impacts on incentives. The study first provides a brief history of
growth and structural changes in the Egyptian economy over the past 50 years. It
then recounts the evolution of agricultural policy since 1955 before providing
measures of the extent of distortions to incentives. An analytical narrative of
policy evolution is followed by some conclusions concerning food policy, rural
incomes, and the prospects for future national policy reform.
Growth and Structural Change in the Egyptian
Economy, 1955 to 2005
Egypt’s economy has grown unevenly over the past 50 years, driven by population
growth as much as by investment, and structurally affected by significant policy
swings. The period is marked first by the rapid nationalization of industry and the
move toward import substitution and central planning and then by the equally
rapid reorientation of the economy toward reliance on markets, private property,
and integration into the world economy. These policy swings have applied to both
the agricultural and nonagricultural sectors, although the emphasis on heavier
industry in the early years clearly penalized agriculture indirectly. Also, in the
reform period, which began in the 1970s, other reforms have been implemented
more quickly than has the dismantling of import substitution policies and tariff
escalation, so some bias against agriculture continues.
Demographically, the population grew from about 25 million to around
75 million over the past 50 years. The bulk of that growth was in the nonagricultural population, which rose from 30 percent to over 60 percent, although the rural
population actually stayed proportionately constant at more than one-half the
total population.
The population trend is reflected in the labor market, where the labor force
grew from 6 million to 20 million, but the share employed in agriculture fell from
over half to just one-third. With such rapid population growth, the population is
demographically quite young, posing a challenge for the economy to absorb the
burgeoning cohort of new entrants into the labor force.
Overall, GDP and especially GDP per capita have grown somewhat haltingly.
Meanwhile, agriculture has fallen from 30 percent of GDP to about 14 percent, and
manufacturing has grown to more than the size of the agricultural sector. Oil and
gas, plus government and other services, account for the remaining share of GDP.
The composition of primary agriculture by product over time for the 70 percent of
products covered in this study (at current distorted prices) is shown in figure 2.1,
Arab Republic of Egypt
75
Figure 2.1. Product Shares of Agricultural Output, Egypt, 1955–2005
percent, at current distorted prices
100
90
80
70
60
50
40
30
20
10
0
55 958 961 964 967 970 973 976 979 982 985 988 991 994 997 000 003
1
2
1
1
1
1 1
1
2
1
1
1
1
1
1
1
year
19
noncovered products
maize
sugar
rice
milk
wheat
cotton
meat
Source: Data compiled by the authors.
where the contraction of the cotton sector is evident and the growing importance
of meat and horticulture are implicit as key parts of the noncovered products.
Exports and imports have been in secular decline. Except for a few
commodities—cotton in the early period; gas and oil, Suez Canal services, garments, and tourism in the later years—Egypt has essentially disengaged from
international commerce. As a share of GDP, merchandise exports have fallen from
an average of over 10 percent before the 1990s to about 5 percent since the early
1990s. For imports, the comparable shares are 27 percent and 16 percent (World
Bank 2006). Egypt’s share of world trade was substantially larger in 1975 than it is
today. Imports remain few, and the sum of exports plus imports as a share of GDP
has fallen, raising the specter that economic reform has been somewhat biased
against trade in that dismantling the import-substitution policy of yesteryear has
received lower priority. Repatriated wages by Egyptians working abroad and foreign aid still make up a significant share of foreign exchange earnings. Foreign
investment, which was all but frozen in the early years, remains fairly low relative
to other developing countries, and some of it is driven by “tariff jumping” into
heavily protected industrial sectors of the economy (Nathan Associates 2002).
The commodity composition of trade has changed considerably over the
period. Agricultural products, mostly cotton, no longer dominate exports, while
76
Distortions to Agricultural Incentives in Africa
gas and oil (“other primary exports”) have increased substantially since the return
of the Sinai oil fields to Egyptian control after the 1973 Arab-Israeli war. Imports
continue to be mostly manufactures, primarily capital goods and especially oilindustry-related, but food imports—especially wheat and flour—still represent
20 percent of merchandise imports despite a concerted effort to decontrol farmgate prices and achieve self-sufficiency in flour for bread production.
The substantial antitrade bias in the foreign trade sector stems from a host of
direct and indirect policy interventions, most notably significant tariff and nontariff trade barriers escalating in favor of industry and from an overvalued
exchange rate from the 1950s until about 1997. In the late 1990s, agricultural
production was penalized by much higher levels of tariff protection for manufacturing, which were amplified by nontariff barriers such as “red-tape” costs of
importing and a restrictive system of standards and quality controls (Nathan
Associates 1996, 1998).
In the past decade, tariff and trade reform appears to have had little impact on
the extent of tariff escalation between primary agriculture and processed food,
and the tariff decline for primary agriculture—from 4.6 percent in 1995 to
1.9 percent in 2005—has widened the gap between it and tariff protection for
nonagricultural primary sectors, which has remained steady at over 10 percent on
average (UNCTAD-TRAINS 2006).
The exchange rate appeared to be overvalued in the 1960s and 1970s, since it
was well below the black market rate, but devaluations in the late 1970s, the
late 1980s, and the early 2000s have periodically corrected its misalignment
(Cassing, et al. 2007, appendix figure 3). The inflation rate has varied, exceeding
10–15 percent for much of the 1970s and 1980s before falling substantially in the
1990s.
Policy Evolution
Economic performance is tied to events and to policy. From 1950 to 1952, the
annual rate of GDP growth in Egypt was 7–8 percent (Al-Sayyid 2003). After the
1952 revolution, however, the growth rate declined sharply before beginning a
slow recovery in 1955–56 (Mabro 1974). This was also a period of political instability and, despite some effort to attract foreign capital, low foreign investment.
Income and wealth were highly skewed: 1 percent of the farm population received
39 percent of total agricultural income, while only 29 percent of the total farm
income went to landless and poor peasants who accounted for 80 percent of the
farm population (Abdel-Fadil 1975, 1981). In the urban areas, the poorest 60 percent of the population received 18 percent of total personal income, while the top
1 percent received 11 percent.
Arab Republic of Egypt
77
From 1956 until about 1966, the economy was marked by a rapid swing toward
state socialism. While the Organization of Free Officers that took power in 1953
had no strong, unanimously held views on economic policy other than to support
“social justice” and land reform, the genesis of the policy shift resided in the political events that shifted Egypt’s trade orientation from West to East (Nutting 1972;
Hansen and Nashashibi 1975).2 The public sector expanded, and with a large
number of public enterprises it increasingly dominated the economy. A period of
agrarian reform reduced the maximum landholding to 100 acres per family and
saw the beginning of state planning and procurement policies for most major
crops. GDP growth was fairly high in this period, about 8–12 percent a year
(Al-Sayyid 2003), but central planning was beginning to show strains.
The period between 1967 and 1973 began and ended with wars. Economic
growth slowed to 3.1 percent following Egypt’s defeat in the June War of 1967.
Emphasis was put on industrialization, and the maximum farm landholding was
lowered in 1969 to 50 acres per family. From 1975 until the early 1980s, the Egyptian
economy grew at about 6 percent per year. But much of this performance was
attributable to one-time factors such as the return of oil fields after the 1973 war,
the rise in oil prices in 1973 and 1979, increased use of the Suez Canal, inflows of
remittances from expatriate workers, and the rapid infusion of external assistance.
Savings were low, non-oil manufactured exports were almost nonexistent, public
firms dominated the industrial sector, and low investment resulted in crumbling
infrastructure (Ikram 2006).
A sharp fall in oil prices in 1982 made the weaknesses apparent, and by 1991
the situation was untenable: the budget deficit was 20 percent of GDP, inflation
was almost 15 percent and rising, real interest rates were negative, and external
debt was rising as foreign exchange reserves dwindled. At this point, the Egyptian
government began to develop a fairly sound macroeconomic environment, and by
1998 inflation had fallen to 3.8 percent, real interest rates were positive, external
reserves were much higher, and external debt was manageable.
In addition, the government began to institute significant structural reforms,
beginning with the privatization of some public firms, a trend that accelerated
after 1996. The financial sector was liberalized a little, with passage of a law that
allowed private firm ownership. Some trade reforms were also implemented,
although tariff and nontariff barriers remained relatively high and tariff escalation increased. Some attention also was paid to widespread human resource
development needs in the hopes of alleviating poverty. The results of the reforms
have been mixed but, from a historical perspective, substantial progress has been
made toward developing a market-oriented, outward-looking economy.
From the early 1960s until the mid-1980s, agriculture’s share of GDP and
employment declined significantly, but because absolute employment and
78
Distortions to Agricultural Incentives in Africa
population numbers in rural areas remained high, the proportions were still
34 percent and 50 percent, respectively. The relative stagnation of the sector was
attributable mainly to government intervention in agricultural production, marketing, and pricing (Siam 2005). Administered prices were far below border
prices, representing a heavy tax on the sector, as the central government sought to
transfer the agricultural surplus to finance the development of the nonagricultural sectors. Confronted with low profitability in agriculture, land productivity
declined and labor began to migrate out of agriculture to nonagricultural job
opportunities both in Egypt and in Iraq, the Gulf countries, Libya, and elsewhere.
These interventionist farm policies began to be reversed in 1986, when the government took action to transform the economy gradually by reducing its role and
increasing the role of the private sector, with the objective of increasing the efficiency of the use of agricultural resources in particular and economic resources
generally. More efficient use of agricultural resources was achieved through two
stages. The first period (1986–90) focused on direct distortions in agriculture. The
prices of 10 main crops were completely or partially liberalized, obligatory deliveries of the strategic crops were reduced or eliminated, subsidies on farm inputs
were cut, the government monopoly on major farm inputs and strategic crops was
eliminated, and the market for private investment was expanded.
The second stage (1990–97) addressed indirect distortions affecting agriculture
by implementing the general macroeconomic reforms discussed above, including
an exchange rate determined by the free market and some liberalization of foreign
trade.
All of these actions affected agricultural output and trade. Historically, cotton
lint dominated Egyptian exports, representing nearly 80 percent of all commodity
exports in the early 1960s. Rice has been the other significant agricultural export.
However, both items have fallen in importance relative to total commodity
exports—now dominated by oil and gas—and relative to other agricultural exports,
notably horticulture (Cassing, et al. 2007, appendix figure 2a).
Agricultural imports also were affected. Together, imports of maize, sugar, and
especially wheat have represented nearly half of all commodity imports throughout the study period. Maize has grown in importance, reflecting the expansion of
domestic livestock industries. Wheat and flour remain substantial imports despite
considerable recent policy efforts to encourage domestic wheat production and a
publicly articulated, if somewhat unrealistic, goal of wheat self-sufficiency.
These imports are in turn integrally related to the long-standing and politically
sensitive policy of substantial bread (baladi) subsidies to all consumers. Throughout most of the study period, bread has been sold on the street at 20–30 percent
of its border price. Since a government procurement subsidy accounts for the
difference, and since bread is a staple in the Egyptian diet with consumption of
Arab Republic of Egypt
79
almost half a kilo per capita per day, the food policy has become a significant
drain on government revenues representing nearly 2 percent of GDP annually.
Some sugar and cooking oil is also substantially subsidized in consumption, but
these commodities are subject to rationing.
Measures of Distortions to Agricultural
Incentives, 1955–2005
Using the methodology for this project, explained in appendix A and Anderson
et al. (2008), we quantify the extent of direct and indirect distortions affecting the
agricultural sector in Egypt. The main focus is on government-imposed distortions that create a gap between domestic prices as they are and what they would be
under free market conditions. Since the characteristics of agricultural development cannot be understood with a sectoral view alone, the project’s methodology
not only estimates the effects of direct agricultural policy measures (including
distortions in the foreign exchange market) but also generates estimates of distortions in nonagricultural sectors for comparative evaluation.
More specifically, this study computes a nominal rate of assistance (NRA) for
farmers that includes an adjustment for direct interventions on inputs. It also generates an NRA for nonagricultural tradables, for comparison with that for agricultural tradables, through the calculation of a relative rate of assistance (RRA; see
appendix A).
The analysis considers five import-competing products (maize, sugar, wheat,
meat, and milk) and two exported crops (cotton and rice). These products constitute around 70 percent of primary agricultural output. For sugar, rice, and cotton,
we also report on the primary commodity (cane sugar, paddy rice, and seed cotton)
as well as on the lightly processed derivatives. We have not focused specifically on
berseem, which is an important feed input for livestock but is rarely traded, nor on
horticulture, which consists of essentially undistorted commodities.
Nominal rates of assistance and consumer tax equivalents
As noted, the NRA measures can include policy-induced input price changes.
While some inputs have been subsidized in Egypt—notably, water, fertilizer, and
pest control—we have mostly ignored this channel of assistance. Thus our NRA
estimates are mostly NRAs on output.
Table 2.1 summarizes the NRA for all seven commodities, while figure 2.2
shows the NRA by trade status. Trends were roughly similar for all of the commodities. In particular, all of the crops were penalized substantially in the early
part of the study period, but those penalties were reversed in the mid-1980s. This
80
Table 2.1. NRAs and CTEs for Covered Farm Products, Egypt, 1955–2005
(percent)
Product
1955–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–05
a
NRA, exportables
Rice
Cotton
NRA, import-competing
productsa
Wheat
Maize
Sugar
Meat
Milk
NRA, total of covered productsa
Dispersion of covered
product NRAsb
Percent coverage
(at undistorted prices)
CTE, total of covered productsc
of which wheat flour
⫺31.5
⫺64.4
⫺21.6
⫺34.3
⫺52.4
⫺62.4
⫺50.0
⫺44.0
⫺62.4
⫺57.4
⫺64.0
⫺44.6
⫺62.2
⫺48.5
⫺64.9
⫺44.4
⫺43.4
⫺22.6
⫺49.9
⫺5.5
⫺34.0
⫺19.6
⫺38.7
⫺2.5
5.0
52.4
⫺13.6
138.2
⫺30.9
⫺11.9
⫺40.2
2.4
⫺17.8
⫺18.2
⫺14.5
16.9
⫺28.1
⫺23.8
⫺34.1
0.0
⫺40.8
⫺32.1
⫺26.9
⫺13.4
⫺68.1
⫺33.1
21.9
⫺48.5
⫺35.5
⫺52.8
⫺32.6
⫺57.1
⫺48.1
14.7
⫺34.2
⫺31.8
⫺34.7
⫺49.9
⫺50.6
⫺53.6
17.1
⫺30.0
⫺22.4
⫺59.3
⫺48.0
⫺43.1
⫺53.0
21.3
⫺12.7
23.6
⫺26.6
12.3
⫺28.8
⫺23.2
32.2
⫺31.5
13.2
⫺8.9
26.5
⫺43.9
⫺13.3
31.9
129.2
237.4
81.6
156.2
57.4
87.3
89.6
47.5
31.1
⫺24.4
⫺11.2
⫺15.6
⫺9.1
33.0
29.6
23.1
⫺5.4
34.5
⫺19.5
5.9
28.7
6.0
17.8
7.2
1.6
⫺19.3
⫺8.3
23.0
70
71
70
71
69
68
65
67
67
67
—
⫺76
⫺51
⫺79
⫺49
⫺73
⫺50
⫺72
⫺21
⫺65
⫺13
⫺72
108
⫺4
⫺3
⫺36
13
⫺44
⫺2
⫺56
Source: Data compiled by the authors.
Note: — ⫽ data are not available.
a. Weighted averages, with weights based on the unassisted value of production.
b. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
c. Weighted averages, with weights based on the unassisted value of consumption.
Arab Republic of Egypt
81
Figure 2.2. NRAs for Exportable, Import-Competing, and All
Agricultural Products, Egypt, 1955–2005
240
200
percent
160
120
80
40
0
⫺40
19
55
19
58
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
⫺80
year
import-competing products
exportables
total
Source: Data compiled by the authors.
is consistent with the earlier study by Dethier (1991), who recorded negative rates
of direct and exchange rate assistance on the order of ⫺30 percent to ⫺40 percent
for wheat and maize from 1964 to 1985, and ⫺60 percent or more for rice and
cotton. Dethier reports only modestly negative or no assistance for sugarcane
when the calculation is relevant using his methodology.
The NRAs turned positive by about 1986 and then suddenly spiked over the next
couple of years. This reflected not only the government’s attempt to reinvigorate
agriculture but also an overshooting, because administered prices were adjusted
substantially upward and tied to a lagging moving average just as world prices fell
dramatically in 1986. Indeed, 1986 was the last year of area restrictions, quotas, and
low fixed procurement prices for wheat and maize. Private sector imports were
allowed in 1991–92. Cotton procurement prices were gradually increased from 1986
to 1991 to more closely reflect border prices and were deregulated after that.
Furthermore, the exchange rate regime was liberalized substantially in this period,
and the black market premium disappeared as rates were market determined.
Rice and sugar exhibit similar trends, including the spike in the 1985–89
period, although neither product was deregulated until later. Sugar production
was never fully deregulated and remains a government enterprise at the milling
level, while rice was not really liberalized until 1991.
82
Distortions to Agricultural Incentives in Africa
Table 2.1 also reports NRAs for milk and beef, neither of which is much traded
although we still categorize them as importable. Livestock was largely unregulated, but beef production was protected with a 100 percent import tariff; in addition, very restrictive health standards applied to beef imports for some years. Our
calculations suggest that milk and beef products followed the NRA patterns of the
five crops, although beef in particular seems to have experienced few disincentives
in the 1970s and 1980s as livestock expanded fairly steadily until feed—maize and
berseem—became an input constraint. Note that while the mean NRA has
approached zero, the standard deviation of NRAs has increased over time (near
the bottom of table 2.1). Consequently the welfare cost of agricultural programs
may have remained high, and possibly even have risen, because of the intrasectoral variance in covered NRAs.
Since it is mostly trade measures that generate the NRAs, the distortions of the
consumer side of the market are similar. This can be seen from the estimates of
the average consumer tax equivalent (CTE) across covered products, shown at the
bottom of table 2.1. Wheat flour receives a very heavy consumer subsidy, with its
price being as low as one-fifth the border price in the 1960s (final row of table 2.1).
We assume noncovered farm products face no distortions to their prices,
because they are mostly horticultural products that are not subjected to government policy interventions. Including them therefore reduces the overall average
NRA for the agricultural sector, as shown in the top rows of table 2.2. We have no
estimates of assistance that is not product specific.
Relative rate of assistance
The relative rate of assistance (RRA) seeks to take into account the effects on
farmer incentives of policy-induced price changes in nonagricultural sectors. It
does so by comparing the NRAs for only the tradable parts of agricultural and
nonagricultural sectors. The NRA for the nonagricultural sector is assumed to be
the average import tariff equivalent throughout the period (so ignoring nontariff
barriers for which we have no estimated NRAs). All manufactures are assumed to
be import competing, and “other primary exports” are assumed to represent
nonfarm exportables. For early missing data years, we simply assume that nothing
had changed from the closest available year, which was 1960. These calculations
suggest that nominal nonagricultural (weighted) assistance averaged in the
30–45 percent range up to the mid-1970s and then remained close to 25 percent
except for a couple of outlier years. Consequently, since the nonagricultural sector
was favored by import protection and an overvalued exchange rate over the
study period, the RRA estimates were considerably below the NRA estimates for
agricultural tradables (table 2.2). And they were positive only in the latter 1980s
(figure 2.3). For the latest period, 2000–05, the estimates suggest that producer
Table 2.2. NRAs in Agriculture Relative to Nonagricultural Industries, Egypt, 1955–2005
(percent)
Category
1955–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–05
NRA, covered products
NRA, noncovered products
NRA, all agricultural products
Trade bias indexa
NRA, all agricultural tradables
NRA, all nonagricultural
tradables
RRAb
Memo item, ignoring
exchange rate distortions:
NRA, all agricultural products
RRAa
⫺33.1
0.0
⫺23.2
0.05
⫺33.1
31.2
⫺48.1
0.0
⫺33.9
⫺0.15
⫺48.1
42.3
⫺53.6
0.0
⫺37.7
⫺0.32
⫺53.6
44.2
⫺53.0
0.0
⫺37.5
⫺0.31
⫺53.0
40.3
⫺23.2
0.0
⫺15.9
⫺0.39
⫺23.2
23.5
⫺13.3
0.0
⫺9.2
⫺0.28
⫺13.3
17.4
87.3
0.0
56.6
⫺0.55
87.3
20.9
⫺49.0
⫺63.4
⫺67.8
⫺66.5
⫺37.8
⫺26.3
55.6
⫺27.3
⫺15.5
⫺26.1
⫺21.7
⫺45.8
⫺29.2
⫺53.9
⫺32.3
⫺57.5
⫺34.4
⫺59.5
⫺15.7
⫺37.4
⫺9.1
⫺26.2
57.1
55.9
⫺5.3
⫺24.9
4.0
⫺15.3
⫺5.5
⫺26.1
⫺9.1
0.0
⫺6.1
⫺0.32
⫺9.1
25.5
5.9
0.0
4.0
⫺0.29
5.9
25.2
⫺8.3
0.0
⫺5.5
⫺0.27
⫺8.3
24.1
Source: Data compiled by the authors.
a. The trade bias index ⫽ (1 ⫹ NRAagx /100)/(1 ⫹ NRAagm /100) ⫺ 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and
exportable parts of the agricultural sector.
b. The RRA is defined as 100*[(100 ⫹ NRAagt )/(100 ⫹ NRAnonagt ) ⫺ 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural
and nonagricultural sectors, respectively.
83
84
Distortions to Agricultural Incentives in Africa
Figure 2.3. NRAs for Nonagricultural and Agricultural Tradables
and the RRA, Egypt, 1955–2005
160
120
percent
80
40
0
⫺40
19
55
19
58
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
⫺80
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the authors.
Note: For definition of the RRA, see table 2.2.
prices for farmers relative to prices received by producers of nonagricultural tradables were about one-quarter below what they would have been under free market
conditions. The bottom two rows of table 2.2 show what those indicators would
be if the exchange rate distortions had not been included in our analysis. In that
case both the NRA for the agricultural sector and the RRA would have been
slightly less negative before the 1980s.
While agriculture was repressed until about the mid-1980s, the degree of negative bias appears to have lightened or even reversed since then. Typically, importcompeting industries fared better than exportables. This picture is consistent with
studies by Fletcher (1996), Bautista et al. (1998), and Ender and Holtzman (2003),
who find that any biases against primary agriculture that existed earlier seem to
have largely disappeared after the mid-1980s. The similarities in the NRA and
RRA calculations suggest that the trends owe more to reversal of low procurement
prices and exchange rate misalignment than to the import-substitution policies
favoring nonprimary agriculture and manufacturing.
In calculating the experience of each product, we have assumed that one-half
of foreign exchange was converted at the parallel rate when the official rate
seemed overvalued. This assumption is consistent with Al-Sayyid (2003), who
reports a flourishing gray market during the period of the 1960s and 1970s when
Arab Republic of Egypt
85
the exchange rate premiums were most pronounced. We use the black market
premiums as reported in Cowitt (various years) to calculate the parallel exchange
rates. The impact those exchange rate distortions have on the NRA and RRA estimates is relatively minor except in the 1960s, as shown at the bottom of table 2.2.
Evolution of Specific Policy Choices
and Their Impacts
In this section, we focus on the policy choices of the Egyptian government, especially with respect to agriculture and food policy, but we are mindful that certain
industrial and exchange rate policies had profound indirect effects on agriculture.
The main indirect policy effects were engendered by trade protection and direct
subsidies to nonagricultural industries, especially heavier manufacturing industries, and by an overvalued exchange rate. By the 1990s, high and escalating tariffs
along with some nontariff barriers (such as “standards”) for manufacturing were
the main remaining indirect disincentives to agriculture.
As recounted earlier, widespread planning characterized much of the economy
from about 1956 until the mid-1980s, but the retreat from markets was operationally less pronounced in agriculture until the 1960s. By 1964, however, central
planning, mandatory membership in agricultural cooperatives, and administered
prices for major crops were in place. Consequently, we briefly review developments during a period of regulation, 1964–1986, which are surveyed extensively in
Dethier (1991), and the subsequent period of deregulation, 1987–2005, characterized by a turn back toward market incentives. We begin with an overview and then
turn to some product-specific issues, food subsidies, and rural income. We relate
our narrative to the measures of distortions presented in tables 2.1 and 2.2 and
figures 2.2 and 2.3.
Overview: 1964–1986
This period was characterized by “Arab socialism” and a widespread distrust of
markets, rooted in the 1952 revolution and Suez Crisis of 1956. The policy objectives of the period were aimed at promoting the equitable distribution of food and
income in Egypt and financing industrial growth through the provision of inexpensive food to urban consumers. The context was a vision of a grand coalition
between the factory worker and the rural peasantry.
To achieve these objectives, the government mandated crop rotation schedules
and crop area allocations, a compulsory delivery quota for crops at fixed prices
that were substantially lower than international prices, and subsidized consumer
prices for basic food commodities. As reported below, while administered prices
and quantity quotas (acreages) need not necessarily be inconsistent with one
another, in this case they were.
86
Distortions to Agricultural Incentives in Africa
Institutionally, agricultural cooperatives were created in each village to control
production and marketing of major crops. Cooperatives, in turn, provided agricultural inputs to farmers, imposed crop rotation schedules, procured the crop
quotas, and ultimately marketed the major crops. The Principal Bank for Development and Agricultural Credit was reconstituted to work with the cooperatives
in providing credit to farmers and receiving their output quotas.
In effect, and mixed with substantial planning in the nonagricultural sector
along with an overvalued exchange rate aimed at conserving foreign exchange
resources, the policy performed poorly. The government intervention in production and marketing created many inefficiencies and distorted choices among competing crops.3 The overvalued exchange rate and artificially low producer prices
eventually suppressed agricultural production and led to stagnation of the agricultural sector. The extent of the disincentives to agriculture is clear in table 2.1:
for the five crops studied and milk, the NRA is almost uniformly and substantially
negative throughout the period. Beef and maize appear to have been mildly
favored toward the end of this era.
These disincentives to farm production ultimately frustrated the original policy objectives. Yields fell, cropping patterns were distorted, and cotton exports
declined. The food gap, which had narrowed somewhat initially, widened by the
mid-1980s, and self-sufficiency in wheat declined to its lowest level as imports
rose. The food subsidy system imposed a heavy burden on the government’s
budget and foreign exchange reserves, thus frustrating plans to support industrialization and conserve foreign currency. Furthermore, instead of achieving “a
more equitable distribution of income,” the urban-rural income gap initially grew
as the heavy implicit taxation reflected in artificially low producer prices caused
farm incomes to decline. That decline increased the political hostility of the rural
classes toward the government, which responded not by reducing government
intervention but by increasing subsidies to farm inputs and extending food subsidies to rural areas in the late 1970s (Dethier 1991). In addition, land reform laws
arguably redistributed land ownership more equitably.
Overview: 1987–2005
Except for seeking to redress the budgetary and foreign exchange pressures its
initial policies created, the government’s overall policy objectives after 1986
remained ostensibly unchanged. Specifically, the agricultural reform program of
this era aimed to provide an adequate supply of food to all income groups, to
promote greater self-sufficiency in crop production, to increase farm income,
to conserve foreign exchange, and to bring the budget deficit under control
(Kherallah 2000).
Arab Republic of Egypt
87
In fact, the policy pursued was essentially one of dismantling central planning
and restoring market incentives. The policy measures implemented under the
agricultural reform program consisted of two phases. In the first phase, prices,
quotas, some crop restrictions, and marketing controls were partially liberalized
for 10 crops. The compulsory delivery program was eliminated for all crops and
replaced with an optional program for 3 of them, namely, wheat, maize, and rice.
Moreover, procurement prices were replaced by floor prices, often tied to a moving average of lagging prices. It is this last feature that accounts for the positive
NRA spikes in 1986–87, shown in figure 2.2, when generous floor prices were set
just as world prices were falling. The volatility in the NRA caused by anchoring
domestic prices to an average of lagging prices is consistent with the finding by
Baffes and Gardner (2003) that world price fluctuations over time were transmitted only incompletely to domestic markets in Egypt.4
The second phase of the reform coincided with the launching of the Economic
Reform and Structural Adjustment Program in 1991. With the assistance of the
International Monetary Fund (IMF) and the World Bank, this program sought
to shift Egypt from a state-controlled economy toward a more efficient, marketoriented economy. In this phase, cotton marketing was liberalized, all remaining
input subsidies were eliminated, and the private sector was encouraged to play a
greater role in agricultural trading. By 1997, the land rental relationship was liberalized as well.
Our measures of the NRA and RRA indicate that these policy shifts had an
impact, appearing to reduce or eliminate the direct disincentives to agriculture
(although, as noted earlier, the increased variance of the NRA has made the welfare implications of the policy shift less clear). Protection for nonagricultural
industry and processed foods remains but is not large when weighted by production. Agricultural yields have generally increased and cropping patterns have
been rationalized (Saad et al. 1996; Ender and Holtzman 2003). On the other
hand, although farmgate prices have risen, the enactment of a market-oriented
land policy has left landless some tenants who previously benefited from controlled, artificially low, land values.
Crop-specific and other farm policies
Because the measures adopted by the government vary by product, we consider
them in turn.
Cotton
For more than a century, cotton has been an important traditional crop in Egypt,
dominating area planted, value of production, importance to downstream industry,
88
Distortions to Agricultural Incentives in Africa
and exports. The sector was nationalized in the 1960s, and low administered procurement prices, along with many other interventions, were used to divert revenues to the government. This policy is clearly reflected in the large negative NRA
estimates for cotton (see table 2.1), particularly before 1987, although the cotton
sector was again taxed heavily in the early 1990s (Saad et al. 1996).
In consequence, total area planted in cotton declined by about half from 1980
to 2000. This contraction resulted from low profitability and was exacerbated by
rising wages in the 1970s and 1980s (cotton is one of the most labor intensive of
the major crops).5 The land was instead planted with cereals, especially wheat and
rice, a fact consistent with our NRA estimates for wheat and rice, which turned
from substantially negative to mildly positive after the mid-1980s (see table 2.1).
Horticulture also expanded somewhat, and berseem became quite profitable as
the livestock sector flourished (see figure 2.1).
Confronted with the demise of a profitable industry, the government reversed
course in the 1990s. In 1992, procurement prices were increased to 66 percent of a
five-year moving average of world prices. This policy accounts for both the
upward trend and the sharp swings in our NRA estimates after 1991 as world
prices fluctuated yearly. In 1994, administered prices were changed to floor prices,
although the government did limit exports in 1995 to satisfy the needs of local
mills, and in 1996, the floor prices actually exceeded the border prices.
In 1997, prices became market determined and the sector was essentially completely liberalized. Nonetheless, the NRA for cotton remained negative and, until
quite recently, substantially so. The negative NRA reflects domestic prices, which,
although rising, still lagged border prices as the Egyptian pound depreciated
sharply against the U.S. dollar, falling from 2.16 in 1991 to 3.41 in 1997 and to 6.15
in 2004. Apparently the exchange rate changes are reflected more slowly in prices
closer to the farm, or possibly they are captured somewhere in shipping and processing along the value chain between farm and port.
Rice
Rice is Egypt’s other export crop. Since the 1960s, the government has intervened
actively in the rice supply chain with low administered prices, government procurement, an export monopoly, and extensive public sector mills. In the 1960s and
1970s, both processed rice and primary production confronted disincentives, but
paddy rice was penalized even more, which allowed the mills, and traders, to garner profits somewhat at the expense of the farmer. Our calculations show that this
relative disadvantage disappeared in the 1980s. In any case, the relative price
advantage of rice over cotton, which was still penalized, aided perhaps by the
relatively higher subsidy value of the free water policy to a water-intensive crop,
resulted in continued expansion of rice acreage as cotton contracted. Rice
Arab Republic of Egypt
89
expansion was further encouraged by incentives to wheat—the two crops are
complementary in the crop rotation.
In the 1990s, rice production was substantially liberalized, and crop area, yield,
and production grew by 4–5 percent. Nominal prices to farmers doubled, and
assistance to paddy rice was actually positive or only mildly negative. Farmgate
prices for rice rose so much at one point that milling and exporting became
unprofitable and the government enacted export subsidies of 100–200 Egyptian
pounds (LE) per ton to aid the (mostly government-owned) milling sector. As
with cotton, the negative NRAs since the early 1990s reflect rising domestic prices
that nonetheless lag behind border prices, which were rising rapidly in domestic
currency terms because of the sharp currency depreciation.
A number of commentators have noted that government rice policy is often in
conflict with itself. Crop choice has been liberalized, yet the rice growing area is
still restricted. Similarly, while the area is restricted to conserve on water usage,
exports are periodically subsidized.
Maize
Maize, an import-competing industry, competes for growing area with rice and
cotton, as well as with some other summer crops. Since the 1960s, maize has been
regulated through mandatory cropping, delivery quotas, and administered prices.
This control resulted in very negative NRAs throughout the 1960s and much of
the 1970s. Low prices for yellow maize were passed on as feed subsidies until 1987,
when the sector was liberalized and procurement prices were raised to encourage
production, consistent with the government’s renewed interest in food selfsufficiency and the growth of the livestock industry.6 The production area has
expanded largely by displacing cotton; in the current decade maize accounts for
about 15 percent of the cropping area.
Politically, maize policy has become more entwined with food policy. Foremost, yellow maize is an important input into the expanding livestock sector,
which in turn is stimulated by the growing Egyptian demand for red meat. Also, in
an effort to reduce wheat imports, which have risen to produce subsidized baladi
bread, the government has experimented with substituting maize flour for wheat
flour. Because maize flour is cheaper, the cost of producing bread is thereby
reduced and, along with it, the government cost of the bread subsidy.
Sugar
Sugar processing is directed by a government-owned company, the Egyptian
Sugar and Refining Company. Prices are administered, and procurement is handled through contracts between producers and the government company. Sugar
consumption, which for a long time has been a part of the food subsidy policy, is
90
Distortions to Agricultural Incentives in Africa
still partially subsidized through price-discounted ration cards distributed to
nearly two-thirds of the population. Because of the consumer subsidies, providing
higher prices to growers has a negative impact on the government budget. Moreover, inefficiencies in milling, which inflate processing costs, make it difficult for
the government to raise the farmgate prices of sugarcane and sugar beet (the latter
of which represents about one-quarter of sugar production). Nonetheless, we calculate that after the late 1970s, the NRA for sugar turned positive, corroborating
the estimates in Dethier (1991).
Wheat
Wheat is the primary input into the most important staple food in Egypt, bread,
which is consumed in enormous quantities, heavily subsidized, and at the heart of a
politically charged food subsidy policy. Before 1955, the government slowly began
to tighten its control over the production and trading of wheat. The explicit objective was equitable distribution of food and income, and the provision of inexpensive food for urban consumers aimed to finance industrial growth (Kherallah et al.
2004). In 1955, the government reduced the area allocation requirement for wheat
production to 33 percent of agricultural land holdings and at the same time initiated a compulsory delivery policy whereby each farmer had to sell a specific quota
of wheat—between 1 and 3 ardeb per feddan—at a fixed price that was lower than
the international price. By the 1960s, wheat, along with the other cereals, was subjected to mandatory delivery quotas, low administered prices, and other marketing
regulations. As table 2.1 shows, the NRA for wheat was substantially negative until
about 1987, although it increased in the late 1970s, reflecting the replacement of the
compulsory delivery requirement with an optional delivery program in 1976.7 In
1960, Egypt began to import wheat for the first time in its history and has imported
it ever since. Before 1965, imports were further encouraged by U.S. PL-480, which
made available credit subsidies for wheat imports from the United States.
After 1987, the government offered floor prices, announced at planting time
and set to approximate or exceed international prices. For example, in 2005, the
procurement price for wheat from Egyptian farmers, at LE 1,165 per ton, was
about 11 percent higher than the price of French wheat adjusted for shipping
costs. Since the government procured 2 million tons locally at this price, support
payments amounted to about LE 220 million, or about 3 percent of the total value
of wheat production. As with the other cereals, there was some overshooting in
the late 1980s when floor prices exceeded international prices, but the NRA generally turned neutral or positive after that. Wheat production expanded and yields
rose as well. Nonetheless, since the early 1980s, Egypt has never produced more
than 55 percent of its total wheat consumption, making it one of the top four
wheat importers in the world.
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91
Livestock
Egypt has a significant stock of animals yielding meat and milk. (Buffalo are also a
source of power on the farm.) Since there is little permanent pastureland, animals
feed on berseem, corn, barley, and wheat, and thus compete with human consumption. The livestock population grew steadily after 1952, stimulated by an
NRA of 100 percent and rising demand, and stabilized during the 1980s as feed
became less available. Milk from water buffalo is consumed primarily on farms,
while milk consumed in urban areas is supplied by commercial dairy herds of
mainly Holstein cattle. In addition to buffalo and cattle, farmers raise poultry,
sheep, and, in diminishing quantities, camels. Pigs are less important because
pork is not widely consumed for religious reasons.
Input policies
Before the reform era of the mid-1980s, the government, through the Principal
Bank for Development and Agricultural Credit monopolized farm inputs and distributed, at subsidized prices, many inputs from seed to fertilizer administratively,
using technical information from the Ministry of Agriculture and Land Reclamation to ration inputs. The subsidies fell mainly on chemical fertilizers, pesticides,
seeds, and animal feed. Under the Economic Reform and Structural Adjustment
Program, the monopoly was eliminated and private investment was allowed to
compete with the Principal Bank for Development and Agricultural Credit,
although there was a two-year reversion to the old system for fertilizer during the
1995 “fertilizer crisis.” Today, private firms dominate the fertilizer industry,
accounting for 75 percent of nitrogen fertilizer and for all phosphorus chemical
fertilizer (Saad 2003). The private sector was also allowed to import, export, and
distribute farm inputs. The government still controls cotton pesticides, however.
Between 1990 and 1997, virtually all input subsidies were eliminated and input
prices now approximate international prices. Import taxes on fertilizer, prominent
in the 1970s to protect some domestic producers, do not exceed 2 percent now.8
The Nile River almost defines Egypt, and water policy is viewed as critical.
Many elements of Egypt’s water policy are centuries old, did not change over the
study period, and are commonly viewed as the purview of government. These
include minimizing water loss (modern irrigation methods, improved navigational paths, new approaches to canal maintenance and weed control, efficient use
of groundwater, water recovery, and the like) and various programs for cost sharing (currently through water users’ associations, which are locally based). In addition, the Aswan High Dam came on line during the study period. In effect, the
marginal cost of water to farmers is zero. This situation has resulted in the expansion of water-intensive crops—rice, bananas, and sugar cane—relative to what
otherwise might have been. This water subsidy might help explain how rice can
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Distortions to Agricultural Incentives in Africa
remain a viable farm industry despite the negative NRA estimate shown in
table 2.1. Note, however, that any water subsidy encourages farmers to choose rice
over cotton (Hansen and Nashashibi 1975).
Land policy has evolved from an initially highly political issue that is integrally
related to rural incomes. In 1952 the government announced that land reform
would be a centerpiece of rural income equity policy. Over the ensuing years, land
ownership was limited to 50 feddans (about 48 acres), and about 12 percent of the
cultivated area was distributed to 341,000 families who had previously been tenants. Over the years the number of small-holders owning 5 feddans or fewer has
increased substantially, suggesting continued land fragmentation. By the end of
the 1990s, the average size of a holding was less than 2 feddans. In 1990, about
two-thirds of the total land area was owned and cultivated by landlords (with
family or hired workers) and only about 10 percent was rented for cash or sharecropped (Siam 2005).
Food consumer policy
It is impossible to divorce agricultural reform in Egypt from food policy, or food
policy from real incomes. Historically food consumer subsidies and food security
have been pursued in Egypt for more than 10 centuries, and state granaries have
existed since Pharaonic times (Scobie 1981a, 1981b). There is a very deeply
ingrained mindset in the general population that government is mandated to ensure
affordable food and, since the Nasser era, the state has explicitly pursued that mandate (Khouri-Dager 1996). Indeed, Singerman (1995) argues that the government
policy of political exclusion has paralleled its commitment to provide the basic
needs of the population, thereby maintaining its legitimacy. Thus, food consumer
subsidies, especially for baladi bread and flour, are viewed as central to political stability, and the food riots of 1977, triggered by increases in the prices of staples, still
serve as a reminder for caution in policy reform. However, as the government recognizes, a policy aimed to subsidize food consumption and raise farmgate prices to
encourage production and reduce imports, while still maintaining a credible budget
balance to pursue other development goals, is inherently inconsistent.
Specifically, while rationing and subsidies for sugar, edible oil, sometimes
wheat, and some other products were in place before 1952, the government
expanded the program greatly after the revolution—and especially in the 1960s
and 1970s—extending it to 18 foods, including beans, lentils, frozen fish, red
meat, chicken, rice, and yellow maize. There was some rationing, but baladi bread
in particular was not rationed and was heavily subsidized to the general public
through the mechanism of subsidizing the wheat input to the bakeries. As selfsufficiency in wheat became elusive, and after 1960 as imports grew, this subsidy,
along with the others, became a substantial drain on the budget.
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After the 1976 attempt to cut subsidies met with violent public resistance, a
more gradual approach was invoked. The number of subsidized foods was
reduced, subsidy levels were decreased, and distribution of ration cards became
stricter. Currently, sugar, edible oil, and baladi bread and flour continue to be subsidized. Sugar and oil are rationed and arguably manageable. Bread, however, is
still not rationed, and it has been estimated that as much as 8 percent of the total
available is used as livestock or poultry feed.
Since the 1980s, the subsidy benefits have been about equally distributed across
the population. In this sense the food subsidy is not well targeted even though it
may be perceived as one of the most effective means of alleviating poverty in
Egypt. The bread subsidy has been cited as particularly effective in rural areas
where it has helped 11 percent of the poor out of poverty; bread is a basic source
of nutrition for this group, accounting for 27 percent of the rural poor’s total
caloric needs.9 Nonetheless, the system remains blunt in its targeting and expensive to operate. Leakages from the system into the black market are significant—
28 percent for flour, 20 percent for sugar, and 15 percent for cooking oil—and the
costs of transferring LE 1 of income to the needy often costs the government more
than three times that amount (Ahmed et al. 2001).
Bread policy presents a political economy dilemma for the Egyptian government. Currently, for example, the government provides 6 million tons of wheat
for bread made available on the street at 5 piastres a loaf, which is just 30 percent
of the true cost of the wheat input. One-third of the wheat is procured from local
production by the Ministry of Supply and Home Trade, and the rest is imported
by the General Authority for Supply Commodities. Given the recent depreciation
of the pound, the purchase of imported wheat at international prices, along with
price supports, generates a subsidy cost on the order of LE 9 billion a year, or
almost 2 percent of GDP.
The cost of the other food subsidies is less severe. Access to subsidized sugar
and edible oil is rationed monthly, at 0.5 kilogram and 1 kilogram, respectively.
While some receive a full subsidy (green cards), others receive only a partial subsidy (red cards) or no subsidy at all. The coverage of ration cards has been reduced
modestly from 79 percent of the population in 1994 to 63 percent in 2004, when
about 40 million individuals were covered by the green cards and about 6 million
by the red cards. Table 2.3 reports on total food subsidies in recent years, where
the dominance of the bread subsidy is clear.
Impact on Rural Incomes
The agricultural reforms undertaken in Egypt over the last two decades have been
broad and deep. Essentially, the agricultural sector has been converted from
an almost totally centrally planned economy to a fairly wide-open free market
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Distortions to Agricultural Incentives in Africa
Table 2.3. Costs of Consumer Food Subsidies, Egypt, 1990–2005
(LE millions)
Fiscal year
Sugar
Oil
Baladi bread
Total
1990/91
1991/92
1992/93
1993/94
1994/95
1995/96
1996/97
1997/98
1998/99
1999/2000
2000/01
2001/02
2002/03
2003/04
2004/05
2005/06
500
675
597
464
464
466
635
511
530
449
523
577
546
609
634
609
368
586
500
471
473
479
520
497
400
657
798
719
614
854
1,283
1,570
1,255
1,057
1,308
1,424
1,486
2,185
2,307
2,380
2,460
2,561
2,744
2,950
3,009
3,201
7,123
8,442
2,123
2,318
2,405
2,359
2,423
3,130
3,462
3,388
3,390
3,667
6,465
4,246
4,169
4,664
8,051
10,622
Source: Ministry of Supply and Home Trade.
economy. Because the earlier administration model entailed using agriculture as a
source of forced savings to subsidize the urban consumer and industrialization,
this reform should have resulted in increased rural prosperity as farmgate prices
were allowed to rise.
However, the link between rural incomes and reform is not straightforward.
Rural income is generated from owner-worked farms, hired labor, tenant farmers,
and nonfarm wages. Currently in rural Egypt, wage employment makes up the
largest part of household income, about 43 percent, and explicit agricultural income
constitutes about 29 percent. Of the remainder, transfers are the most important, at
17 percent. The value added in primary agriculture depends both on output prices
for primary goods and on input prices, especially prices for land, water, fertilizer,
and pest control. The cost of food is also a very large component of real income.
Rady, Omran, and Sands (1996) calculate that the agricultural resource income
available to labor and other inputs from eleven crops, including the five crops of
focus here, rose by 22 percent in the reform era of 1987–94, compared with the
1980–86 period immediately before reform. While the reduction of input subsidies hurt somewhat (income fell in 1991), the increases in efficiency, higher prices,
and improved incentives allowed the same resources to generate over 20 percent
more income. Rady, Omran, and Sands observe that “these are precisely the kinds
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95
of gains that justify the political risks that policy decision makers confronted
when formulating the reforms.”
The impact of reform on income distribution and poverty is more complicated. A number of studies have attempted to assess the issues using householdexpenditure survey data obtained from the country’s Central Agency for Public
Mobilization and Statistics and other data assembled by the International Food
Policy Research Institute. Food items, especially grains and high-carbohydrate
items, dominate household expenditures in both rural and urban areas of Egypt,
representing about 50 percent of expenditures on average and 70 percent for the
poor. So the impact of more expensive food resulting from either higher farmgate
prices or reduced food subsidies is potentially enormous. Datt and Olmstead
(1998) infer that real wages declined substantially in response to food price
increases and imply that the increases in the prices of food crops in the context of
the Economic Reform and Structural Adjustment Program most probably led to a
decline in rural real incomes.
Siam (2005) reports a similar finding, noting that a significant increase in the
agricultural wage in money terms in the 1990s was not reflected in living standards in the rural sector because the cost of living increased by more than the
wage. According to El Helepy (2004), the index of the real agricultural wage
(relative to the rural cost of living) fell by about 35 percent between 1974–91
(straddling reform) and 1992–2002. This may be explained substantially by the
effect of the structural adjustment program, under which farm prices increased
by more than agricultural wages. Moreover, labor wages contribute a significant
part of farm incomes, particularly for the majority of small farmers where it is as
much as 70 percent. The ratio between the agricultural wage and nonagricultural
wage narrowed to 0.18 in 1992–2002, from 0.26 in 1982–1991 and 0.29 in
1974–81 (El-Halaby 2004). This may account for some of the labor migration out
of agriculture. Land reform also pushed some poor households out of crop agriculture and into informal wage employment and the livestock-rearing sector.
Comparing 1981/82, before reform, with 1990/91 after reform, IFPRI (1994)
concludes that poverty increased slightly in urban areas and may have increased in
rural areas, depending on the particular income level used to measure poverty. If
all food subsidies were to have been removed in 1990/91, the poor would have
required income increases of 17 percent just to maintain the same welfare level.
Since poverty is generally higher in some politically sensitive areas of the rural
Nile Delta, it is understandable that policy reform has been marked by cautious
gradualism. Lofgren and El-Said (1999) estimate that the benefits of eliminating
the sugar and edible oil subsidies would be small while the negative impact would
be quite regressive. Gutner (1999) has proposed more politically palatable targeted food subsidy reforms that would reduce access of the wealthy.
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Distortions to Agricultural Incentives in Africa
What about Future Policies?
From 2000 to 2003, real incomes in Egypt stagnated, unemployment rose, and
inflation approached 16 percent. In 2004, a proreform cabinet led by Prime
Minister Ahmed Nazif was appointed, and reappointed in 2005, with a mandate
to bolster private sector activity through policy reforms. Recently, import tariffs
and income taxes have been reduced, and plans are in place to privatize most state
enterprises and to restructure the financial sector. Feedback is positive as real GDP
growth has increased, inflation has fallen, real interest rates are now positive, and
investors have reappeared. Moreover, foreign exchange earnings are strong, led by
the energy sector, tourism, Suez Canal revenues, and worker remittances.
These recent reforms and the programs announced, particularly the import
tariff reductions and commitment to a flexible exchange rate, should work to
reduce the remaining indirect disincentives to primary agricultural production.
According to our NRA calculations, the remaining direct disincentives in farming
are not large after the substantial reforms of the last decade. However, milk and
the exportables, cotton and rice, continue to suffer negative assistance. And food
subsidies, especially for bread and flour and their links to the fiscal budget deficit
and poverty reduction, remain a policy dilemma.
Notes
1. Specifically, following Mohammed Ali’s failed attempts to develop a protected industrial economy in the early 1800s, the period from 1840 to 1930 was marked by agreements between the European powers and the Sublime Porte, which underwrote 90 years of almost perfectly free trade. This
ended in the period 1930-50 as Egypt gained tariff autonomy and embraced protectionist policies.
Additionally, during World War II, a system of direct controls for distributing food and raw materials
and for regulating prices was created and never fully dismantled after the war. See Hansen and
Nashashibi 1975 and historical references therein.
2. These events included the Egyptian-Czechoslovak arms deal of 1955; relations with the United
States concerning the World Bank Aswan High Dam loan; the Suez Canal nationalization; the BritishFrench-Israeli aggression and the Suez War; and the subsequent foreign exchange and trade blockade
by the United States, Britain, and France.
3. Hansen and Nashashibi (1975) observe that planning per se need not distort acreage choices of
farmers nor necessarily lead to suboptimal cropping patterns, but it did, according to their methodology.
4. There is also an aberration in our exchange rate series owing to a black market rate outlier in
1985. We have experimented with smoothing out this aberration and found that it is of little consequence to the NRA spike observed around this time. Price trends are the drivers.
5. In an earlier period, the cotton production area had been restricted to reduce the supply of
Egyptian long-staple cotton on world markets, which were dominated by Egypt’s exports at that time
(but this was not the case in the more recent times discussed above).
6. Also, until 1965 prices and regulations were undoubtedly influenced by the U.S. PL-480
program, which offered subsidized corn and wheat import credits to Egypt.
7. Compulsory delivery was reinstated for two years in 1985 and 1986.
8. www.customs.gov.eg/customs_tariff/customtable_tariff.html.
9. For the urban poor of Cairo, the comparable number is 39 percent (Ahmed and Bouis 1998).
Arab Republic of Egypt
97
References
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(1952–1970): A Study in the Political Economy of Agrarian Transition. Cambridge, U.K.: Cambridge
University Press.
———. 1981. The Political Economy of Nasserism: A Study in Employment and Income Distribution
Policies in Urban Egypt, 1952–1972. Cambridge, U.K.: Cambridge University Press.
Ahmed, A. U., and H. E. Bouis. 1998. A Review of International Experience on Food Subsidy Programs:
Lessons Learned for Egypt. Washington, DC: International Food Policy Research Institute.
Ahmed, A. U., H. E. Bouis, T. Gutner, and H. Lofgren. 2001. The Egyptian Food Subsidy System: Structure, Performance, and Options for Reform. Washington, DC: International Food Policy Research
Institute.
Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675-704.
Al-Sayyid, M. K. 2003. “Politics and Economic Growth in Egypt (1950–2000).” Cairo University,
Cairo.
Baffes, J., and B. Gardner. 2003. “The Transmission of World Commodity Prices to Domestic Markets
under Policy Reforms in Developing Countries.” Journal of Policy Reform 6 (3): 159–80.
Bautista, R., S. Robinson, F. Tarp, and P. Wobst. 1998. “Policy Bias and Agriculture: Partial and General
Equilibrium Measures.” TMD Discussion Paper 25. International Food Policy Research Institute,
Washington, DC.
Cassing, J., S. Nassar, G. Siam, and H. Moussa. 2007. “Distortions to Agricultural Incentives in Egypt.”
Agricultural Distortions Working Paper 36. World Bank, Washington, DC.
Cowitt, P. P., ed. Various years. World Currency Yearbook. Brooklyn: Currency Data and Intelligence, Inc.
Datt, G., and J. Olmstead. 1998. “Agricultural Wages and Food Prices in Egypt: A Governorate-Level
Analysis for 1976–1993.” FCND Discussion Paper 53. International Food Policy Research Institute,
Washington, DC.
Dethier, J.-J. 1991. “Egypt.” In The Political Economy of Agricultural Pricing Policy, vol. 3: Africa and the
Mediterranean, ed. A. O. Krueger, M. Schiff, and A. Valdez. Baltimore: Johns Hopkins University
Press.
El-Halaby, D. 2004. “The Impact of Macroeconomic Policies on Agriculture Development in Egypt.”
PhD thesis, Faculty of Agriculture, Cairo University.
Ender, G., and J. S. Holtzman, eds. 2003. Does Agricultural Policy Reform Work?: The Impact on Egypt’s
Agriculture, 1996–2002. Cairo: Abt Associates.
Fletcher, L. B., ed. 1996. Egypt’s Agriculture in a Reform Era. Ames, IA: Iowa State University Press.
Gutner, T. 1999. The Political Economy of Food Subsidy Reform in Egypt. Washington, DC: International
Food Policy Research Institute.
Hansen, B., and K. Nashashibi. 1974. “Protection and Competitiveness in Egyptian Agriculture and
Industry.” Working Paper 48. National Bureau of Economic Research, New York.
———. 1975. Foreign Trade Regimes and Economic Development: Egypt. New York: National Bureau of
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IFPRI (International Food Policy Research Institute). 1994. Maintaining Food Security in Egypt During
and After Agricultural and Food Policy Reforms. Washington, DC: IFPRI.
Ikram, K. 2006. The Egyptian Economy, 1952–2000: Performance, Policies, and Issues. London: Routledge.
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Kherallah, M., C. Delgado, E. Gabre-Madhin, N. Minot, and M. Johnson. 2004. Reforming Agricultural
Markets in Africa. Baltimore: Johns Hopkins University Press.
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Khouri-Dager, N. 1996. “The State, Urban Households, and Management of Daily Life: Food
and Social Order in Cairo.” In Development, Change, and Gender in Cairo, ed. D. Singerman and
H. Hoodfar. Bloomington: Indiana University Press.
Lofgren, H., and M. El-Said. 1999. “A General Equilibrium Analysis of Alternative Scenarios for Food
Subsidy Reform in Egypt.” TMD Discussion Paper 48. International Food Policy Research
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Mabro, R. 1974. The Egyptian Economy 1952–1974. Oxford: Clarendon Press.
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Impediment to Trade. Cairo: DEPRA.
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———. 2002. “The Egyptian Economy and Structural Reforms.” Technical report, DEPRA, Cairo.
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Rady, A. M., M. A. Omran, and F. B. Sands. 1996. “Impacts of the Policy Reforms on Agricultural
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Part iii
Southern
Africa
3
Madagascar
Fenohasina Maret*
Agriculture is a key economic sector in Madagascar, but its performance since the
1950s has been insufficient to cope with demographic pressures or to contribute to
a significant reduction of poverty. Madagascar’s agricultural sector accounts for
nearly 30 percent of gross domestic product (GDP) and 40 percent of merchandise
export earnings, while providing livelihood to 73 percent of the total population.1
The incidence of poverty is very high in the rural areas, where it reaches 77 percent. The sector remains vulnerable to external shocks. According to 60 percent of
focus groups convened in a 2001 commune census (Trine 2004), variations in
producer prices are the main cause of deteriorating living standards. Population
growth from 4.2 million in 1950 to 18 million in 2004 (INSTAT 2005) also plays a
key role, having put intense pressure on the agricultural sector.
Food insecurity remains a severe problem. Despite the need to increase production, agriculture continues to have low productivity and high vulnerability to
climatic conditions as well as to world price fluctuations. In addition, several periods of civil unrest and political uncertainties have disrupted the rural economy
and discouraged investment. Natural conditions for farming are relatively favorable, however, and Malagasy agriculture is quite diversified relative to other
African countries.
Economic and financial policies have not provided much support to the agricultural sector, reflecting in part the very low political weight of the rural and
farming population. Key agricultural exports and inputs have been taxed, and
* The author is grateful for help, either with data or with comments, to Dera Andriambololona, Xavier
Maret, Bart Minten, Jean Nirison, Tojo Rakotoniriana, Jean Marie Rakotovao, François Rasolo, Henri
Abel Ratovo, and Roland Razafindraibe, and for helpful comments from workshop participants.
Detailed data and estimates of distortions reported in this chapter can be found in Maret (2007).
101
102
Distortions to Agricultural Incentives in Africa
marketing chains have been heavily regulated. The weakness of the industrial sector makes exports of agricultural products a key source of foreign currency,
despite the volatility of world prices of primary commodities. Imports, mainly
composed by manufactured products, have been subject to licensing and tariffs,
imposing a further distortion against agriculture.
Ensuring the full potential of the agricultural sector and increasing rural standards of living remain key challenges for Madagascar. After gaining its independence from France in 1960, the country went through three different economic
regimes: the postindependence period, when the economy was still closely linked
to France (1955–71); the socialist economy period (1972–88); and gradual liberalization (1988 to date). Through all three periods agricultural output per capita
declined steadily.
This chapter analyzes government policies and reforms as they affected the
agricultural sector from 1955 to 2004, with a view to ascertaining current policy
challenges and choices that could be useful for policy makers molding the future
of the sector. Direct and indirect distortions are computed for cassava, cloves,
cocoa, coffee, maize, pepper, rice, sugar, vanilla, and yam. These commodities represent nearly 70 percent of the country’s value added in agriculture, excluding
fishery and forestry.
A general finding of the analysis is that producers’ incentives were increasingly
distorted in favor of urban consumers during the state intervention period of the
1970s. Those distortions were then significantly reduced for most of the covered
commodities as a result of the liberalization policies that were initiated beginning
in the late 1980s; the exceptions are sugar and vanilla, where domestic market
inefficiencies still isolate producers from developments on world markets.
The chapter begins with a summary of the historical background and the evolution of policy conducted in Madagascar before independence. Then the chapter
looks at the history of economic growth and structural changes since the 1960s.
The main part then describes the estimates of distortions. Some prospects for
reform conclude the analysis.
Policy Evolutions before the 1960s
In the early 1950s, as in most other French colonies and overseas territories, Madagascar implemented a development plan that strengthened its economy and contributed to its diversification. Madagascar’s performance in the 1950s relied heavily
on its agricultural sector, and some progress was achieved in extending the value
added chain to food and other agricultural processing. The country benefited from
its membership in the CFA franc zone, which facilitated trade access and limited
exchange rate exposure, as well as from having relatively good infrastructure and
Madagascar
103
institutions. Outside of cloves, coffee, and vanilla, most agricultural production
remained centered on staple food items such as rice. As a result, competitiveness
with foreign food products limited increases in most agricultural producer prices,
and exports of cash crops (mainly cloves, coffee, and vanilla) remained vulnerable
to external shocks as well as to weather.
The satisfactory economic performance over the 1950–60 period was accompanied by a 26 percent increase in population. This population boom, to 5.3 million inhabitants in 1960, reflected an average annual growth rate of 2.3 percent, in
contrast to an estimated annual average of 1 percent over the previous three
decades. Demographic change involved a rising share of youth as well as geographical and rural-urban disparities that started to exacerbate poverty issues. On
the one hand, school enrollment increased substantially (by 80 percent), and the
schooling rate reached 45 percent, exceeding the performance of most developing
countries at the time. On the other hand, nonagricultural employment remained
broadly stagnant over the 1950s, except for an increase in civil servants, and nothing had been done to improve agricultural employment (no professional training
was provided, and most agricultural school graduates joined the civil service).
Moreover, the deficiency of animal protein and fats in human diets was not
addressed, even though the caloric intake increased by 7 percent over the period.
Annual, per capita agricultural income remained very low, at about $202, including the estimated value of food produced and consumed at home. Agriculture was
the dominant economic and export activity in the 1950s. Crop production grew
by nearly 4 percent per year on average, despite the negative impact of a cyclone in
1959 that reduced output by 8 percent in that year. Cattle herding had a much less
satisfactory performance, growing by only 7 percent over the period.2 At the end
of the 1950s, agricultural production was quite diversified and relatively resilient
to external shocks. Rice, the staple food product for the Malagasy population,
accounted for 43 percent of total production value, followed by coffee (14 percent), sugarcane (6 percent), cassava (5 percent), potato, vanilla, and cloves (3 percent each), and various less-important products.
Economic activities in the mining, energy, and industry sectors grew faster
than agricultural production in the 1950s, but they remained relatively small as a
share of the economy, equivalent to less than 15 percent of agricultural value
added in 1960. Most of the growth in the industrial sector, moreover, resulted
from food processing activities, including rice milling, sugar refining, and soft
drink production, as well as cotton, sisal, and tobacco processing.
Imports in the 1950s grew at a similar rate as exports, and the ratio of exports
to imports remained stable at around 70 percent. However, imports of capital
goods and production inputs were fairly constant over the period, while imports
of food products and other consumption goods increased by 45 percent. This
104
Distortions to Agricultural Incentives in Africa
increase reflected a rise in nonagricultural wages of nearly 150 percent over the
period, and because import prices increased by much less, urban workers favored
imported products, which maintained downward pressure on domestic food
prices. Rural producer prices increased by only 30 percent over the decade.
In 1960, 93 percent of Madagascar exports were agricultural products. These
exports accounted for 20 percent of agricultural production valued at producer
prices. The share of these exports going to the CFA zone, where some products
benefited from preferential treatment, fell from nearly 90 percent in 1950 to about
75 percent in 1960. Although export volume growth was greater than production
growth until 1958, it was also more sensitive to external shocks.
Growth and Structural Changes since the 1960s
Madagascar’s economic development and policy making since the 1960s has been
strongly influenced by succeeding schools of economic development thought
(from colonialism to socialism to liberalism) and a succession of political shocks.3
The economic takeoff of the Malagasy economy that was initiated in the 1950s
continued in the 1960s after independence from France in 1960. Increasing state
intervention after 1972 resulted in the implementation of a socialist model and a
decline of productive activities. The departure from the CFA zone in 1974 also
contributed to economic underperformance, as the new Malagasy franc was overvalued and protected by foreign exchange restrictions until 1994, when the currency was allowed to float freely and was devalued by more than 60 percent.
In the 1980s, stabilization and structural adjustment programs were implemented to reduce economic distortions and restore macroeconomic equilibrium,
following the failure of the economic development policies of the 1970s. The
turnaround of economic activities was modest, however, highlighting the partial
and gradual character of the reforms. The reforms focused on exchange rate and
international trade liberalization, price deregulation, and state withdrawal from
economic and commercial activities. Quantitative restrictions and tariffs
remained high, nevertheless, with an important negative impact on external trade,
illustrating the country’s inward-looking development strategies inherited from
the 1970s and 1980s (Pryor 1990). Progress was interrupted by a political crisis in
1991 and the withdrawal of the donor community until 1996. During this period,
real GDP per capita declined by 2.7 percent per year, on average, reaching its lowest level in 1996 at about US$200.
A renewed track record of broadly satisfactory economic performance under
new adjustment programs instituted since 1997 was temporarily set back by a new
political crisis in 2002. This experience highlights the persistent lack of resilience
of the political system and the need for further reforms, including establishment
Madagascar
105
of a secure and reliable institutional environment and the pursuit of progress
toward a market-oriented economy.
The agricultural sector has performed poorly since the 1960s. Productivity of
staples has stagnated at low levels. While the availability of agricultural infrastructure and services has improved marginally, it is still at a low level. Recent improvements in access to output and input markets and in transportation have not
proven sufficient to drive a significant turnaround of agricultural activities. The
structural adjustment policies since the mid-1980s have improved the market
framework by removing most of the market distortions through a devaluation of
the Malagasy franc, a reduction in import barriers, market liberalization, and privatization of public enterprises. These changes have not been enough to stimulate
rapid output growth in rural areas; a reduction in overall public investments and
possible declining efficiency of these funds, the lack of an emerging private sector,
the degradation of the natural resources base, and relatively large risks in agriculture have led to little supply response (Minten 2006). As a result, adoption of
modern agricultural technologies has been low, leading to an agricultural system
with low land and labor productivity.
There is little doubt that agriculture can contribute to poverty reduction
through multiplier and participation effects (Christiaensen, Demery, and Kühl
2005), but the design of a proper policy mix to ensure sustainable development and
higher productivity of the sector has remained unsatisfactory. The problems to be
addressed, from macroeconomic issues to microeconomic and institutional ones,
are complex and include lack of infrastructure, poor institutional capacity, lack of
proper economic incentives, and market failures in input and output markets—
together these factors have compounded the difficulty of designing effective
poverty reduction strategies rooted in rural sector development. Removing distortions to agricultural incentives will have to be accompanied by the implementation
of strong sectoral policies and the emergence of frameworks conducive to private
sector development, including institutional reforms to provide training and education, build trust and transparency, and improve credit access; provision of research
and extension services for staple foods, decreasing overreliance on rice; and security and development of road and irrigation infrastructures (Minten 2006).
The transition period of the 1960s and the socialist
experiments of the 1970s
The influence of the French remained strong in economic and financial activities
after Madagascar gained its independence in 1960. Agricultural production
and marketing, as well as policies, remained broadly unchanged. Small traders
organized the marketing of rice with the parastatal Office of Rice Marketing and
106
Distortions to Agricultural Incentives in Africa
Stabilization (Bureau de Commercialisation et de Stabilisation du Riz) during the
First Republic (1960–72). This agency fixed minimum and maximum prices, provided credit to farmers, and organized rural associations. Agricultural policies
aimed at increasing land under cultivation through large irrigation schemes (such
as Lake Alaotra, Marovoay, and the Mangoky Delta), and agricultural extension
activities complemented these irrigation efforts by promoting the use of modern
inputs and technology, as well as by introducing improved equipment for rice
cultivation.
The focus of economic policy turned in the early 1970s to an increasing intervention by the state in productive and commercial activities. The government of
General Gabriel Ramanantsoa initiated this process in 1972 by nationalizing several large companies, starting to regulate and control numerous prices, and
imposing state monopoly on various products, including rice. Madagascar
departed from the CFA zone in 1974, in favor of exchange controls at an overvalued exchange rate. The government of Didier Ratsiraka, who assumed power in
1975, pushed these socialist trends further. Convinced that a lack of investment
was at the root of the lack of economic performance, the government initiated a
large and unsustainable investment program in the late 1970s that relied on foreign financing and money creation (Pryor 1990).
Increasing intervention by the state, which implemented rural development
policies rooted in socialism, led to a significant reorganization of Madagascar’s
agricultural sector in the 1970s. The new socialist government that came to power
in 1972 got rid of the private marketing sector that was perceived as predatory.
Agricultural policies were then anchored around state control of prices and marketing, taxation of export crops, and protection of the industrial sector and urban
consumers. Shortly after assuming power in 1975, Ratsiraka’s government decreed
that holdings in excess of 500 hectares would be turned over to landless families,
and it is reported that 500,000 hectares of land had already been processed under
the program by the end of that year (Library of Congress 1994).
This redistribution of land, which aimed at creating collective forms of farm
management (cooperatives and state farms), was accompanied by state intervention in all activities of the agricultural sector. The Ministry of Agricultural Production oversaw the activities of more than 70 parastatal agencies in the areas of
land development, agricultural extension, and research activities. Moreover, the
collection, transformation, and marketing (domestic and external) of key agricultural products were put under state control. Domestic agricultural prices were
subsidized and kept low to favor urban consumers, which resulted in declines in
domestic production and higher imports for such commodities as rice. Taxes and
economic barriers were put in place to allow each village or neighborhood
government (fokontany) to benefit from agricultural production and to control
product movements.
Madagascar
107
While an objective of the interventions was to stabilize the prices of export
crops (cloves, coffee, and vanilla), the interventions ended up penalizing producers of these crops. Producers received only 40 percent of world prices for coffee
and only 25 percent of world prices for cloves and vanilla. Yet, from 1974 to 1987,
more than half of Madagascar exports were concentrated on coffee and vanilla
(around 30 percent were from coffee). Because of its potential and through the
levying of export taxes, the agricultural sector was contributing a large fraction of
the government budget, including the public investment program aimed at developing industrial activities.
The inefficient system of agricultural supply and marketing that resulted from
state intervention in the 1970s became a major factor inhibiting agricultural
development. From 1973 to 1977, one major parastatal agency, the Association for
the National Interest in Agricultural Products (Société d’Intérêt National des Produits Agricoles, or SINPA) had a monopoly in collecting, importing, processing,
and distributing a number of commodities, most notably rice. Corruption leading
to shortages of rice in several areas resulted in social unrest in 1977, and the government was forced to take over direct responsibility for rice marketing. In 1982,
SINPA continued to control a large share of all distribution for many agricultural
commodities, and it subcontracted many smaller parastatal agencies to handle
distribution in certain areas. In the cash crop and export sector, the state took over
marketing of the main crops through stabilization boards for cloves, coffee,
vanilla, and pepper. Public enterprises were put in charge of collecting and marketing the crops, fixing prices at each stage of the marketing chain, and leaving the
actual farmgate price as a residual.
The economic policies of the 1970s led to recession and higher inflation, as well
as to a severe decline in per capita agricultural output. These outcomes were exacerbated by high volatility and a declining trend in world agricultural prices.
Madagascar’s GDP per capita declined by an annual average of 1.6 percent in the
1970s. The FAO index of agricultural production per capita started to decline in
1975 and by 2005 was only one-third of its 1975 level, and the large investment
program resulted in a balance of payments crisis. Given the policy biases against
agriculture, peasants started to focus on food security and household selfsufficiency: they developed staple food crops and increasingly ignored cash crops,
leading to the development of a system of nonmonetary and highly vulnerable
autarky in the rural sector.
The gradual adoption of liberalization since the 1980s
The failure of the socialist development policies and the increasing inability of the
government to subsidize prices led the Ratsiraka regime to enact a series of
structural adjustment reforms during the 1980s. These included the removal of
108
Distortions to Agricultural Incentives in Africa
government subsidies on the consumer price of rice in 1984 and the disbanding of
the state marketing monopoly controlled by SINPA in 1985. The Malagasy government also liberalized agricultural exports gradually. The elimination of export
taxes on nontraditional products in 1985 was extended to all exports, with the
exceptions of coffee, cloves, and vanilla, in 1987. Export taxes were removed from
coffee and cloves in 1988 and from vanilla in 1997. The currency was devalued by
55 percent in real terms in 1987, and a liberalized import system was implemented
a year later, ending the intervention of the state in the allocation of foreign
exchange. Currency devaluation in 1994 was accompanied by the official liberalization of the foreign exchange market.
The commercialization of rice and other commodities continued to decrease
in the second half of the 1980s, as gradual implementation of structural reforms
and the persistence of bottlenecks, such as inappropriate transportation infrastructures, undermined the new policy stance. Rice growers responded by moderately expanding production by 9 percent during the latter half of the 1980s,
whereas rice imports dropped dramatically, falling by 70 percent between 1985
and 1989. However, the Ratsiraka regime failed to restore self-sufficiency in rice
production, and rice imports rose again in 1990. In 1992, rice production occupied about two-thirds of the cultivated area and produced 40 percent of total agricultural income, including livestock, fishing, and forestry.
Other food crops witnessed small increases in production from 1985 to 1992.
Cassava, the second major food crop as measured by area planted (almost everywhere on the island) and probably by quantity consumed, increased in production from 2.14 million tons in 1985 to 2.32 million tons in 1992. During this same
period, corn production increased from 140,000 tons to 165,000 tons, yam production increased from 450,000 tons to 487,000 tons, and banana production
dropped slightly from 255,000 tons to 220,000 tons.
Among the exports, coffee prices witnessed a boom during the first part of the
1980s, making coffee the leading export crop of the decade. Prices within the coffee market gradually declined during the remainder of the 1980s, although they
rebounded in 1992. Cotton traditionally has been the second major export crop,
but most output during the early 1980s was absorbed by the local textile industry.
Although cotton output rose from 27,000 tons in 1987 to 46,000 tons in 1988,
once again raising the possibility of significant export earnings, the combination
of drought and a faltering agricultural extension service in the southwest contributed to a gradual decline in output to only 20,000 tons in 1992.
Two other export crops—cloves and vanilla—also declined in importance
from the 1980s to the 1990s. Indonesia, the primary importer of Malagasy cloves,
temporarily halted purchases in 1983 as a result of sufficient domestic production, leaving Madagascar with a huge surplus. A collapse in international prices
Madagascar
109
for cloves in 1987, compounded by uncertain future markets and the normal
cyclical nature of the crop, led to a decline in production from a high of 14,600
tons in 1991 to 7,500 tons in 1993. Similarly, the still state-regulated vanilla industry (state-regulated prices for coffee and cloves were abolished in 1988–89) found
itself under considerable financial pressure after 1987 because Indonesia reentered the international market as a major producer; in addition, synthetic competitors emerged in the two major markets of the United States and France. As a
result, vanilla production declined from a high of 1,500 tons in 1988 and 1989 to
only 700 tons in 1993.
Agriculture and livestock are closely linked within the farming system.4 More
than half the farms raise cattle. Livestock production was limited in part, however,
because of traditional patterns of livestock ownership that hampered commercialization. Its rate of growth was around 1 percent yearly. Beef exports in the early
1990s decreased because of poor government marketing practices, rundown
slaughtering facilities, and inadequate veterinary services. All but 1 percent of
cattle are zebu. The Food and Agriculture Organization estimates that in 1991
Madagascar had 10.3 million cattle, 1.7 million sheep and goats, and 21 million
chickens.
Trade policy
Madagascar participates actively in the multilateral trading system. It became a
member of the World Trade Organization in November 1995. The country also is
involved in regional trade agreements with the Indian Ocean Commission (created in 1984), the Regional Integration Facilitation Forum (launched in 1992), the
Common Market for Eastern and Southern Africa (from 1995), the African
Growth and Opportunity Act (from January 2001), and the Southern Africa
Development Community (only in 2005). Many of Madagascar’s exports to the
European Union enjoy nonreciprocal preferential treatment in the form of
exemption from import duties. Madagascar also benefits from preferential tariff
treatment granted by Australia, Canada, the European Union, Japan, New
Zealand, and the United States under the Generalized System of Preferences
(WTO 2001).
Since Madagascar liberalized its trade regime in the early 1990s, its trade policy
framework has been based on tariffs (WTO 2001). Extraregional tariffs are still
restrictive. The simple average of applied most favored nation (MFN) import
duties is 16.2 percent in 2001. Tariffs on the agricultural sector alone are 17.7 percent on average. Import duties and taxes continue to constitute a significant
source of government revenue. An import tax of 2 percent and a custom stamp
duty of 1 percent also apply to imports. An excise duty ranging to over 100 percent
110
Distortions to Agricultural Incentives in Africa
is levied on petroleum, alcoholic and nonalcoholic beverages, and tobacco
products. A value added tax of 18 percent is also collected on sales of goods and
services except for pharmaceuticals, medical equipment, news print books, and
brochures.
Madagascar has bound customs tariffs at 30 percent. MFN customs tariff rates
have been reorganized from 13 bands to 4 bands ranging from zero to 30 percent.
The government wishes to simplify the tariff structure to one rate, but an impact
study is yet to be undertaken to examine the need to smooth adjustment for
sensitive products and sectors. To secure custom duties revenue, the Malagasy
authorities have contracted with a preshipment inspection company for all
imports worth $1,000 or more. All quantitative restrictions on imports have been
eliminated, except for prohibitions or prior authorization requirements maintained under international conventions for health, phytosanitary, or security reasons or on products deemed strategic by the government—including vanilla and
precious stones in Madagascar’s case (WTO 2001).
With its difficulties in balancing its budget, the country cannot afford to provide farm price support programs or match the developed countries’ export subsidies (FAO 2003). Elimination of export taxes, liquidation of marketing boards,
and abolition of monopolies held or exclusive rights exercised by state-owned
companies were a good step forward, although agricultural incentives have shown
only very moderate improvement. That is because, among other reasons, the vacuum left by the elimination of the boards has not been filled, and the country’s
capacity to respond to new opportunities has been very limited (WTO 2001).
Nonetheless, with the move to a more open trade policy, Madagascar has
increased its trade volume in recent years, with textile and tourism the most rapidly expanding exports.
Evolution of rural poverty since the 1960s
Unsatisfactory economic and financial performance since the 1960s has contributed to a lack of overall progress in poverty reduction. The 1984–85 agricultural census estimates that at that time, 8.7 million people lived in rural areas
and that 65 percent of the economically active population within these areas lived
at the subsistence level. Based on the 2001 household survey by Madagascar’s
National Statistics Institute (INSTAT), almost 70 percent of the population in
Madagascar was poor, with about 90 percent of the poorest quintile living in rural
areas and engaged in farming. The data also point to wide variations among
provinces.
Significant correlates of poverty are household residence in rural areas (which is
associated with 30 percent lower consumption) and the occupation of the head of
Madagascar
111
the household as a small-scale farmer. The first national household survey was done
in 1993, and over time rural areas have consistently been shown to be worse off than
urban areas. Poverty in the primary sector worsened between 1993 and 2001 by
almost 9 percent, while falling in the secondary and tertiary sectors. Poverty levels
have remained very high over the years and were still estimated in 2004 at about
77 percent in rural areas, compared with 54 percent in urban areas. Poverty reduction in urban areas was mainly driven by export processing zones and tertiary sector
developments (Minten, Randrianarisoa, and Randrianarison 2003).
Direct and Indirect Distortions to Agricultural
Incentives
In this section, the effect of the three different phases of policy reform on farmers’
incentives is quantified. The main focus of this study’s methodology (see appendix A and Anderson et al. 2008) is on government-imposed distortions that create
a gap between domestic prices as they are and what they would be under free market conditions. Since the characteristics of agricultural development cannot be
understood from a sectoral view alone, the project’s methodology not only estimates the effects of direct agricultural policy measures (including distortions in
the foreign exchange market) but also generates estimates of distortions in nonagricultural sectors for comparative evaluation. More specifically, I compute
nominal rates of assistance (NRAs) for farmers and an NRA for nonagricultural
tradables for comparison with that for agricultural tradables through the calculation of a relative rate of assistance (RRA).
As mentioned earlier, the immediate period after independence was recorded
as the most favorable time for Madagascar’s farmers in the last half century. Government policy toward primary agriculture was relatively neutral. Data for estimating NRAs are available for only four farm products (cassava, rice, sugar, and
yam) for the period before 1966, but their weighted average was 1 percent in
1955–59 and 20 percent in 1960–65 (figure 3.1). The country was then a net
exporter of rice and sugar.
The socialist structure of the early 1970s allowed the government to extract
rents by indirect taxation, so even though agricultural producers were exempt
from income taxes, use of various forms of government “hand-on” policies, such
as export taxes, licensing, and marketing boards, eroded farmers’ revenues and
favored corruption and rent-seeking for political elites.5 Export duties were one of
the principal sources of government revenue in the early 1980s, providing 30 percent of total revenue in 1983.
The impact of those policies on farmer incentives is clear from figure 3.1. Producer prices were not allowed to rise with international prices in 1973–74, causing
112
Distortions to Agricultural Incentives in Africa
Figure 3.1. NRAs for Exportable, Import-Competing, and All
Covered Farm Products, Madagascar, 1955–2003
30
percent
10
0
10
30
50
70
58
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
19
19
55
90
year
import-competing products
exportables
total
Source: Data compiled by the author.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
the NRA to fall from close to zero in the early 1970s to 50 percent. As international prices returned to normal, the prices of importables rose again but those of
exportables fell even further, and their NRA averaged between 60 and 75 percent in the late 1970s and 1980s. Even when the reforms begun in the mid-1980s
started to have an effect, they continued to favor import-competing farmers over
those producing exported goods.
By the late-1980s, when international food prices were exceptionally low, the
degree of taxing of farmers had returned to the level of the late 1960s (around
25 percent), and thereafter it came even closer to zero. By the turn of the century
it was virtually zero, although the antitrade bias within the sector remained—the
NRA for exportables in 2000–03 was still 30 percent, while the NRA for importcompeting farm products was 7 percent. Even within each of those two subsectors, there is still considerable variance in the NRAs, so the chapter examines the
situation for individual crops before comparing the overall agricultural situation
with that of producers in nonfarm activities.
Madagascar
113
Food crops
The main food crops covered in our study are rice, cassava, maize, and yams; each
is addressed here in turn.
Rice
Rice is the staple food in Madagascar, and paddy rice is the country’s most important food crop. It is grown by about 70 percent of the population and covers about
3 million acres, or 50 percent of the total area under cultivation. Small-holders
dominate production, and farms consume an estimated 80 percent of production.
The Malagasy consumption of rice per capita is about 120–140 kilograms per
year. Rice productivity has been low and stagnant for the last 40 years with yields
of around 2 tons a hectare, while other countries like Indonesia and Vietnam have
managed to increase their rice yield three- or fourfold. Annual rice production grew by less than 1 percent during the 1970s, when cultivated paddy area
expanded by more than 3 percent per year.6 Land tenure problems, poor control
of water, and lack of agricultural inputs are still obstacles affecting rice cultivation.
The share of rice available for marketing in the rapidly growing urban areas
declined from more than 15 percent of the total crop in the early 1970s to nearly
10 percent during the latter part of the decade (Dorosh and Minten 2005). As a
result, Madagascar became a net importer of rice beginning in 1972. By 1982, it
was importing nearly 200,000 tons annually, equal to about 10 percent of the total
domestic crop and roughly equal to the demand from urban customers. Even
within the rural areas, many people are net buyers of rice, because only a minority
of farmers produce enough to be net sellers.
Government policies have contributed to the poor performance of the rice sector. Even though low labor costs and little use of inputs mean that Malagasy rice
has low production costs, its competitiveness at the international level is lost in
the value chain because of the large marketing costs caused by remoteness, transport costs, and the multiple actors involved in that chain. The lack of maintenance
of the fragile transportation infrastructure in the late 1970s and early 1980s was a
major contributing factor to the decline in Madagascar’s marketed agricultural
production. Government support of farm credit and agricultural inputs was small
or absent in many areas, and credit flows were skewed toward the estates and
wealthier small-holders (Pryor 1990).
The trends in the NRA for rice can be seen in table 3.1. The minimum pricing
scheme established by the government through the parastatal agency SINPA basically subsidized imports at the expense of export crops. The resulting low producer
price and government neglect in providing inputs discouraged production. The discrepancy between the world price and the official domestic price was exacerbated by
114
Table 3.1. NRAs for Covered Farm Products, Madagascar, 1966–2003
(percent)
Product, indicator
a,b
Exportables
Vanillac
Cocoa
Pepperc
Clovesc
Coffee
Import-competing productsa,b
Nontradablesa
Yam
Cassava
Mixed trade statusa
Rice
Maize
Sugar
Total of covered productsa
Dispersion of covered productsd
Percent coverage (at undistorted prices)
1966–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–03
26.6
52.3
31.6
33.9
44.7
26.6
—
0.0
0.0
0.0
18.1
39.0
30.3
4.1
18.1
15.3
28.0
0.0
0.0
0.0
60.9
56.9
71.0
39.1
80.6
63.0
20.1
0.0
0.0
0.0
73.9
76.4
68.4
46.7
91.7
73.5
42.2
0.0
0.0
0.0
63.6
85.2
60.5
80.0
84.9
58.5
3.0
0.2
0.0
0.0
33.4
77.8
25.6
30.2
62.7
28.9
1.7
0.2
0.0
0.0
17.7
28.5
22.8
62.0
27.4
12.7
0.7
0.2
0.0
0.0
29.3
12.8
18.5
10.2
18.7
37.6
7.4
0.0
0.0
0.0
22.6
27.6
1.9
24.0
23.3
44
21.5
2.7
1.0
20.0
23.3
54
20.1
17.7
2.5
37.8
35.6
71
42.2
4.1
1.1
51.4
37.2
75
2.7
6.6
0.4
26.2
39.8
68
1.9
28.7
0.2
7.5
37.1
71
0.9
14.1
0.8
3.7
28.7
72
7.4
29.5
0.7
0.5
23.8
66
Source: Data compiled by the author.
Note: — no data are available.
a. Weighted averages, with weights based on the unassisted value of production.
b. Mixed trade status products included in exportable or import-competing groups depending upon their trade status in the particular year.
c. Data for vanilla, pepper, and cloves are missing for 2002 and 2004.
d. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
Madagascar
115
the way the government controlled the quantity of rice imports and regulated rice
domestic marketing, particularly during the late 1970s and early 1980s. Domestic
producer prices for paddy were set without reference to border prices and were kept
substantially below import parity levels (Dorosh, Bernier, and Sarris 1990). This
continued to be the case into the current decade, according to Minten, Randrianarisoa, and Randrianarison (2003), because the factors determining the pricing of
rice in Madagascar are the time of harvest, storage costs, the distance to urban centers, access to roads, the availability of imported rice, the level of wealth of each
locality, and the climatic condition and incidence of natural disasters.
Domestic marketing of rice was liberalized after 1988, which reduced the distortions to farmers. Since 2000, the tariffs and domestic taxes applied to rice
imports have resulted in a slightly positive NRA for rice (7 percent in 2000–03).
Rice continues to be a political crop and the government continues to intervene,
particularly by making unpredictable changes in the import tariff and in the
allowed volume of imports by private actors (notwithstanding the formal removal
of government controls along the value chain). This fact seems to have favored
corruption and rent seeking. Dorosh and Minten (2005), in their study on the rice
crisis that occurred in 2004, note that transparent and preannounced tariff reductions could mitigate the effects of increases in the price of imported rice on poor
consumers, even if they resulted in small losses of tariff revenues.
Cassava
Cassava leaves and tubers are edibles. Annual production is about 2.5 millions tons,
of which a very small quantity of about 15,000 tons are used industrially for making tapioca and candy at four locations, in Anjiro, Marovitsika, Vodiala, and Moramanga. Cassava is mainly used for animal feed and is also very important for food
consumption as a buffer crop during lean seasons. In the southern part of the
country, the crop is often dried before consumption. Because of a lack of detailed
data on the dried product, however, this study looks only at green (fresh) cassava.
The southern part of Madagascar used to export cassava to neighboring islands
but increasing freight and shipping costs have made such exports unprofitable,
and the volume of cassava exports has been falling since the mid-1970s. In addition, port infrastructures are poor, and storage capacity is insufficient near the
harbor. Competition from French subsidized cassava further reduced incentives.
Hence in this study, cassava is classified as nontradable, and the NRA on output is
assumed to be zero.
Maize and yams (sweet potatoes)
Similar to cassava, sweet potatoes are classified as nontradable, and their NRAs
and consumer tax equivalent (CTE) are assumed to be zero. The trade status of
116
Distortions to Agricultural Incentives in Africa
maize has changed over time. It was an exportable commodity from 1955 to 1972
and then switched regularly between being exportable and nontradable. Imports
have increased since 2000. In most of the years in which maize has been imported,
the NRA for maize has been positive.
Export crops
Madagascar’s main export crop is vanilla, a strategic product that has been an
important source of foreign exchange and accounts for more than 30 percent of
agricultural exports in recent years. 7 Good climatic condition, low labor costs,
and very high quality make Malagasy vanilla highly competitive and give the
country a strong comparative advantage in its production.
A vanilla stabilization fund was created in 1962, and a cartel was formed with
Comoros and Réunion to exploit the region’s collective market power. The fund,
known as CAVAGI, stabilized the price received by producers and financed stockholding costs, with contributions taken from export proceeds after payment of
an export tax. The intervention in the 1960s sought to bring stability and equity
in the distribution of gains from the vanilla trade (Cadot, Dutoit, and de Melo
2006), accumulating stocks of vanilla in an attempt to raise international prices
and to exploit monopoly rents. During the 1970s, intervention grew and rents
were appropriated by government and by a limited number of traders. Production was regulated, with farmers required to have a license (valid for three years)
to grow vanilla. In addition, the Ministry of Trade required vanilla preparers
(processors and stockers) to obtain an annual license. Export taxation became
massive, with some farmers receiving less than 8 percent of vanilla’s free on board
price (Cadot, Dutoit, and de Melo 2006). A specific export tax of $35 per kilogram was supplemented with an export duty of 15 percent and an export surcharge of 11 percent.
In their study, de Melo, Olarreaga, and Takacs (2001) conclude that in addition
to distortions stemming from taxes and marketing controls, the cartel overestimated the country’s degree of market power in international vanilla markets and
thus opened the door for competition from Indonesia. The international price of
Malagasy vanilla initially rose, but the cartel’s high prices discouraged consumption so much that revenue was reduced. In addition, the cost of stockpiling the
accumulating inventories escalated beyond the amount CAVAGI could finance
out of its revenue. In the end, three-quarters of the stock of inventories, which by
1990 exceeded four years’ volume of exports in good times, was destroyed by
burning. This was an extraordinary waste given the high unit value of vanilla and
the extreme poverty of the farmers whose output was thus destroyed (Cadot,
Dutoit, and de Melo 2006).
Madagascar
117
Since independence, the NRA for vanilla has fluctuated between 40 percent
and 60 percent, which implies heavy direct taxation of producers. Misalignment
of the foreign exchange market made the situation worse, as did the explicit introduction of an export tax in the mid-1970s. The NRA on output averaged about
70 percent then and about 80 percent in the 1980s (see table 3.1). The vanilla
export tax and most other forms of government intervention were completely
removed in 1997, and the NRA has since moved much closer to zero, but the sector has still not recovered.8 Sharp price fluctuations during 2000–03, which
resulted partially from speculation from large wholesalers and exporters in Madagascar, did not help. The price of a kilogram of vanilla was $50 in 1999, soared to
$475 in 2004, but then dropped to $35 in 2005–06, when after deducting marketing costs farmgate prices reached as low as $15 per kilogram. A possible explanation for the sinking prices for growers is the continuing control of the sector by a
small number of traders and processors, who have amassed most of the benefits of
the reform. Cadot, Dutoit, and de Melo (2006) tried to determine how much the
reforms achieved by themselves by looking at a model that recreated the old policy environment under current market conditions. They found meager improvement in farmers’ projected income and concluded that the sources of the remaining distortions stem from the malfunctioning of the market and imperfect
information among farmers and traders. Moreover, substitutes for natural vanilla
are now more widely used, which means there is more competition among suppliers in international markets and oligopsony among buyers (Rakotoarisoa and
Shapouri 2001).
Madagascar’s other main export crops are coffee, cloves, pepper, and cocoa,
which represented, respectively, 20 percent, 14 percent, 6 percent, and 5 percent of
agricultural exports during 1995–2005. Annual production growth has been relatively sluggish, partially because of climatic conditions, while the value of exports
has fluctuated sharply as a result of changes in world commodity prices. Green coffee represented around 40 percent of Madagascar’s agricultural export earnings
during 1995–99, when favorable international prices accompanied liberalization.
Like vanilla, coffee and cloves were regulated and subject to licensing. The marketing board purchased a large part of the crop, which it marketed directly, and it
fixed the price for all export transactions. Coffee and cloves were also subject to
export taxes and export duties starting in the early 1970s. As shown in table 3.1,
NRAs on output for these four export crops followed almost the same patterns as
for vanilla and have been negative since independence. This suggests that Madagascar’s pricing and exchange rate policies discriminated against these export
crops. The NRA on coffee, for example, averaged around 65 percent from the
mid-1970s to 1987. But after the deregulation of trade in 1988, those NRAs were
reduced and became much closer to zero.
118
Distortions to Agricultural Incentives in Africa
Industrial crops: sugarcane
The sugar industry has been one of the most important food processing activities
in Madagascar, accounting for 60 percent of the value of food processing output
in the late 1980s. Developing agroindustry was one of the goals of the government
after independence, so sugarcane farmers were not discriminated against as other
farmers were. The NRA for sugar, even though it has fluctuating with movements
in international prices, has averaged approximately zero since the 1960s (see
table 3.1). Sugarcane growers do often face long delays in receiving payment for
their crop after it is delivered to the state processing factory, however.9
The two sugar companies, Siramamy Malagasy and Sucrerie de Nosy Be et de la
Cote Est, were nationalized in 1976, extensively rehabilitated in 1985, and combined into a single entity in 1987. The Ministry of Trade fixed prices for sugar put
into the domestic market until liberalization in 1989, after which wholesalers and
retailers were free to fix their own margins.
Madagascar has been a net importer of processed sugar since 1991, although
exports expanded in 1999. The export quota of 7,258 tons to the United States and
10,760 metric tons to the European Community (as of 2001) until recently was
generally filled. The sugar company has encountered various difficulties, however,
resulting in a production shortfall. The country has stopped exporting to the
United States altogether and can barely fill its quota to the European Union. And
with the recent reductions in the favored export price under preferential access
given by the European Union to ACP (African, Caribbean, Pacific) countries,
which is scheduled to expire in 2009, even that trade is vulnerable.
Privatization of the state sugar monopoly was supposed to occur by 2001 as
part of market-led reforms, but it is still under debate. Instead, technical assistance
for management has been sought. Even though sugar imports are subject to an
import tax (35 percent) and a value added tax (20 percent), inefficiencies associated with low capacity utilization and low sugarcane yields continue to keep the
industry uncompetitive internationally. Domestic distribution of sugar also is
inefficient, with only five firms licensed to serve the domestic wholesale market.
The nonagricultural sector
Madagascar’s manufacturing sector is dominated by food processing and beverages, agribusiness, light manufacturing, construction, soaps and detergents, packaging, textiles, and footwear. After independence, the government adopted an
import-substituting trade regime and public investment strategy. Then toward the
mid-1990s, Madagascar eliminated all types of currency rationing in trade as well
as quantitative restrictions on imports apart from those arising from the application of international conventions and those maintained for health and security
Madagascar
119
reasons. Export restrictions in almost all areas have also been eliminated, as have
foreign exchange controls. By the end of the 1990s, the average MFN tariff for the
manufacturing sector, defined as Major Division 3 under ISIC (International Standard Industrial Classification) Revision 2, was 16.2 percent (WTO 2001).
Since the start of the reform process, the government has progressively encouraged the emergence of a private sector. Manufacturing activities are increasingly
concentrated in the export processing zones, where textiles and clothing constitute a major subsector.10 According to a World Bank report (2005) assessing
Madagascar’s investment climate, even though firms rank corruption and tax
rates lower than they are ranked in other African countries, a poor business environment affects the whole private sector, and price controls and inflation are
major constraints. Firms that are not in export processing zones suffer from low
productivity relative to the firms in the zones, which are devoted solely to exports.
The mining sector was nationalized in 1975 and then opened to foreign investment for prospecting in 1985; private investment and exploitation has been
encouraged since 1990. The sector is still underdeveloped, however, despite its
potential.
The services sector contributed about 57 percent to the country’s GDP in 2004,
with tourism the largest component. Financial and telecommunication services
underwent liberalization and privatization, and some satisfactory performance
and progress is now occurring. Improvements in the transportation system
remain on the government’s list of goals for its economic reform program.
To compare the rates of assistance to nonagricultural sectors with those for
agriculture, I first assume there are no distortions to noncovered farm products
except those operating through the exchange rate system, so the weighted average
NRA for covered and noncovered farm products is somewhat less negative than
for covered products alone (top rows of table 3.2). But because nontradable farm
products are assumed to have zero NRAs, the weighted average NRAs for just the
tradable parts of agriculture—because of the dominance of exportables—are very
negative. The NRAs for nonagricultural tradables, by contrast, are positive. They
are calculated using mainly import tariffs for import-competing sectors and
export subsidies and taxes for exportables, in addition to the exchange rate distortions. Because of a lack of available data, nontariff barriers, which were very common during the 1970s, are not taken into account, but the NRAs still suggest
heavy assistance to nonfarm tradables throughout the period. Hence the relative
rate of assistance is even more negative than the NRA for agriculture (figure 3.2
and middle rows of table 3.2).
The bottom rows of table 3.2 show what the key distortion indicators would be
had the analysis not taken into account the distortions in the market for foreign
currencies. The differences are not very great, suggesting they alone were not a
120
Table 3.2 NRAs in Agriculture Relative to Nonagricultural Industries, Madagascar, 1966–2003
(percent)
Indicator
1966–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–03
Covered products
Noncovered products
All agricultural products
Trade bias indexa
NRAs, all agricultural tradables
NRAs, all nonagricultural tradables
RRAb
Memo item, ignoring exchange
rate distortions:
NRA, all agricultural products
Trade bias indexc
RRAd
24.0
1.4
11.9
0.40
25.6
12.4
33.8
20.0
0.3
13.5
0.14
21.3
8.7
27.6
37.8
1.0
27.1
0.47
41.6
13.3
48.2
51.4
1.1
38.8
0.53
57.5
20.0
64.2
26.2
1.6
18.2
0.62
38.1
12.7
44.8
7.5
0.6
5.4
0.34
16.8
11.5
25.4
3.7
0.9
2.9
0.21
8.3
10.2
16.7
0.5
0.3
0.5
0.31
0.9
13.7
12.9
10.1
0.34
29.1
13.6
0.17
27.6
26.9
0.38
46.4
37.7
0.31
60.4
17.6
0.58
42.6
4.9
0.30
22.2
2.5
0.18
14.1
0.5
0.31
12.9
Source: Data compiled by the author.
a. Trade bias index is TBI (1 NRAagx兾100)/(1 NRAagm兾100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and exportable
parts of the agricultural sector.
b. The RRA is defined as 100*[(100 NRAagt)兾(100 NRAnonagt ) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradable parts of the agricultural and
nonagricultural sectors, respectively.
Madagascar
121
Figure 3.2. NRAs for All Agricultural and Nonagricultural
Tradables and the RRA, Madagascar, 1955–2003
40
20
percent
0
20
40
60
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
67
19
64
19
61
19
58
19
19
19
55
80
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the author.
Note: For the definition of RRA, see table 3.2.
very significant contributor to the strong antiagricultural bias that has prevailed
in Madagascar until recently.11
Conclusions and Prospects for Further Policy
Reform
The pattern of distortions to agricultural incentives clearly has depended very
much on the government in power and on its policies. The first president after
independence, Philibert Tsiranana, managed to maintain the traditional market
structures as well as an acceptable balance between agriculture and the rest of the
economy. Agricultural production rose at a modest rate, and the RRA was no
worse than 30 percent in those years. The functioning production and transport
infrastructure from early independence also contributed to the relative well-being
of farmers during this period of the First Republic.
After taking power in 1972, President Ratsiraka turned the intersectoral terms
of trade much more against agricultural producers and caused the market to disintegrate. Agriculture faced strong production disincentives, as indicated by the
plunge of the RRA to 60 percent by the early 1980s. The government established
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Distortions to Agricultural Incentives in Africa
a state-owned marketing system to purchase crops and supply farmers with agricultural inputs and consumer goods, but that system did not function adequately
either. The resulting shortage of foodstuffs led to the creation of a parallel market
that benefited the estates and richer small-holders who had better access to transportation and therefore widened income differentials within the rural area. Heavy
taxation, a cumbersome foreign exchange allocation system, and overvalued
exchange rates also affected exports negatively. Agricultural production stagnated
and imports of staple food became a necessity. In the meantime, Malagasy farmers
remained reticent in expressing their discontent with government policies, which
continued to be urban oriented.
Distortions were gradually reduced, but not fully eliminated, as part of the
market liberalization drive in the late 1980s. Rural areas still have the highest incidence of poverty, however, and the policy reversal did not have much of a positive
impact on production, nor has it ensured sustainable growth and development.
Yet despite the persistence of distortions, producers seem now to receive a higher
proportion of international prices, at least in periods of low international prices.
Progress toward a more market-oriented agricultural sector has not completely
reversed the past’s disincentives for farmers for three main reasons. First, the
reforms have been gradual, partial, and incomplete. Second, political crises and
civil unrest have led to “stop-go” reforms. And third, assistance has not been used
effectively. As well, rural development projects have been poorly conceived and
implemented, and mistrust between public actors and private actors remains
(Bene and Beyries 2002).
The phasing out of trade policy biases to agricultural incentives needs to be
combined with domestic policies aimed at improving farmers’ incentives and
income. Indeed, international prices are still far from being the main determining
factor in returns to farmers. Baffes and Gardner (2003), in their multicountry
analysis, note that world price transmission to average producer prices in Madagascar has been low or nonexistent and that only a moderate improvement in
market integration took place following the reforms.
The current evidence shows that the rural sector is still fragmented and badly
organized. The essential bonds between production, transformation, and marketing are weak. The Malagasy rural economy remains a mainly subsistence
economy. Market failures caused by huge transportation costs and intermediation margins are still present. Downstream operators (collectors, wholesalers,
retailers, and importers) are using their monopsonist power and speculating with
key primary products. In addition, a minority has important political weight and
uses it in rent seeking from the government. There is thus a vicious cycle, where
producer prices are low, leaving farmers with little purchasing power to acquire
a good standard of living (education, drinking water, electricity, energy, health
Madagascar
123
services). Their low living standard in turn reduces farmers’ human capital and
productivity, which are key factors for increasing production and farmers’
incomes.
Current domestic policy objectives outlined in the National Program for Agriculture, Farming, Fishing and Agricultural Processing Industries, promise good
prospects for Malagasy agriculture (Repoblikan’I Madagasikara 2005). Also, President Marc Ravalomanana’s plan, “Madagascar Naturally,” envisions, by 2020, a
country devoted to its agriculture, with market-oriented production, and a diversified agroindustry satisfying domestic food needs and exports, closely linked to
service sectors providing agricultural credit and research and extension as well as
tourism and other services.12 Under that plan, a policy bias against agriculture
through price distortions should no longer be a major dampener to producer
incentives. Most of the nonprice interventions needed are well laid out in the
Madagascar Action Plan for Rural Development, even if their implementation
and feasibility remain a challenge. These measures include greater land security,
rural credit access, and irrigation infrastructure plus the promotion of marketoriented activities.
Madagascar’s future is firmly intertwined with agriculture and agroindustry.
Increasing consumer demand in developed economies for organic food may
provide an export opportunity for the country. Minten, Randrianarison, and
Swinnen (2005) show that farmers’ participation in contract farming with global
retailers also promises the development of niche markets abroad, which will help
contribute to poverty reduction at home.
Notes
1. Madagascar was ranked 143rd among 177 countries in 2007 on the UN’s Human Development
Index (UNDP 2007), and its GDP per capita was only $280 in 2006, equivalent to 77 cents a day
(World Bank 2008).
2. Beef accounted for nearly 50 percent of livestock sector revenue, followed by poultry (25 percent), pork (15 percent), and fishing and others (10 percent). Poultry and fresh water fishing contributed the most to growth of the sector in the 1950s.
3. As Minten (2006) points out, it is striking that the three periods of growth (late 1960s, late
1980s, and late 1990s) were each interrupted by social and political crisis.
4. Livestock represents about 35 percent of agricultural GDP. Over 40 percent of total land is used
for pasture. Cattle raising is at the heart of the rural economy in much of western and southern
Madagascar.
5. The majority of agricultural activities were being run on a small-scale basis as part of the informal sector. As such they were not taxed on the basis of revenue, nor did they receive any form of social
security from the government.
6. In the early 2000s, rice accounted for about 50 percent of the value added in agriculture and
45 percent of the calories consumed by an average Malagasy person (Dorosh and Minton 2005).
7. Vanilla is an orchidaceous plant that has a 15-year life span. Harvesting takes place 4 years after
planting. Five kilograms of green vanilla are required to produce one kilogram of dry vanilla. The
process involves curing, drying, and packing.
124
Distortions to Agricultural Incentives in Africa
8. The state role now is confined to sanitary and quality inspection and to setting the date and
place of vanilla marketing each year. Certification attesting to the vanilla’s quality and wholesomeness
is necessary before it can be exported, to prevent excessive amounts of immature vanilla beans being
offered for sale (WTO 2001). The European Union’s Stabex fund (export stabilization fund) continues
to finance efforts aimed at quality improvements.
9. Payment to growers is basically done in three parts. The first 25 percent is based on a preannounced price and is paid at the time of delivery to the factory gate. The remaining 75 percent is paid
in two payments at revised postharvest prices. Prices are fixed by a joint commission representing the
company and the growers, together with the Centre Malgache de la Cane et du Sucre (CMCS), an
entity responsible for the supervision and regulation of the sugar industry value chain.
10. Because of low domestic demand and low savings, the government adopted a growth strategy
based on exports in 1989. Export processing zones (EPZs) were then established, offering various tax
benefits and exemptions to attract foreign investors and multinationals. The benefits include a waiver
of corporate income taxes, zero import duties and taxes, and free access and movement in foreign
exchange (Razafindrakoto and Roubaud 1997). In addition, EPZ firms enjoy preferential market access
provided by the United States and the European Union.
11. This is also true in other Africa countries that were using the CFA currency, such as Cameroon
and Senegal. See chapters 13 and 17 in this volume.
12. The results sought by the Malagasy authorities are to increase exports by increasing agricultural production (such as rice, maize, and cassava) by 100 percent in 5 years and 200 percent in 10
years, by increasing agricultural exports (such as vanilla, clove, and shrimp) by 100 percent in 5 years
and 150 percent in 10 years, by increasing processed exports (such as canned fruits, sugar and sweeteners, and rum) of 50 percent in 5 years and 150 percent in 10 years, and by developing nonfood
agroindustrial production (such as essential oils and textiles) by 50 percent in 5 years and 200 percent
in 10 years. At the same time, products where the country has a comparative advantage will be identified in order to take advantage of regional market agreement. See Repoblikan’I Madagasikara (2005).
References
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Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675–704.
Baffes, J., and B. Gardner. 2003. “The Transmission of World Commodity Prices to Domestic Markets
under Policy Reforms in Developing Countries.” Journal of Policy Reform 6 (3): 159–80.
Bene, S., and P. Beyries. 2002. “ Note sur Madagascar.” Réseau Thématique, Institutions Publiques
Agricoles. Ministry of Foreign Affairs, Office of Agricultural Policies and Food Security
(DCT/EPS). Paris, France.
Cadot, O., L. Dutoit, and J. de Melo. 2006. “The Elimination of Madagascar’s Vanilla Marketing Board,
Ten Years On.” CEPR Discussion Paper Series. 5548. Centre for Economic Policy Research, London.
Christiaensen, L., L. Demery, and J. Kühl. 2005. “Agricultural Growth, Nonagricultural Growth and
Poverty Reduction: Evidence from an African Perspective.” World Bank, Washington, DC.
de Melo, J., M. Olarreaga, and W. Takacs. 2001. “Pricing Policy under Double Market Power: Madagascar and the International Vanilla Market.” Review of Development Economics 4: 120.
Dorosh, P., R. Bernier, and A. Sarris. 1990. “Macroeconomic Adjustment and the Poor: The Case of
Madagascar.” Cornell Food and Nutrition Policy Program Monograph 9. Cornell University,
Ithaca, NY.
Dorosh, P., and B. Minten. 2005. “Rice Price Stabilization in Madagascar: Price and Welfare Implications of Variable Tariffs.” World Bank, Washington, DC.
FAO (Food and Agriculture Organization). 2003. “Trade Reforms and Food Security: Conceptualizing
the Linkages.” Commodities and Trade Division, FAO, Rome.
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Antananarivo.
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Library of Congress (U.S.). 1994. “Madagascar, Section on Agricultural Production.” Library of
Congress Country Studies, Washington, DC, August.
Maret, F. 2007. “Distortions to Agricultural Incentives in Madagascar.” Agricultural Distortions
Working Paper 53. World Bank, Washington, DC.
Minten, B. 2006. “The Role of Agriculture in Poverty Alleviation Revisited: The Case of Madagascar.”
World Bank, Washington, DC.
Minten, B., J. C. Randrianarisoa, and L. Randrianarison. 2003. “Agriculture, pauvreté rurale et
politiques économiques à Madagascar.” Cornell University, Ithaca, NY. www.ilo.cornell.edu.
Minten, B., L. Randrianarison, and J. Swinnen. 2005. “Supermarkets, International Trade and Farmers
in Developing Countries: Evidence from Madagascar.” SAGA Working Paper. Cornell University,
Ithaca, NY. www.saga.cornell.edu.
Pryor, F. L. 1990. The Political Economy of Poverty, Equity, and Growth: Malawi and Madagascar.
London: Oxford University Press.
Rakotoarisoa, M. A., and S. Shapouri. 2001. “Market Power and the Pricing of Commodities Imported
from Developing Countries: The Case of US Vanilla Bean Imports.” Agricultural Economics 25:
285–94.
Razafindrakoto M., and F. Roubaud. 1997. “Les entreprises franches à Madagascar : économie
d’enclave ou promesse d’une nouvelle prospérité?” Economie de Madagascar 2: 217–48.
Repoblikan’I Madagasikara. 2005. “Programme National de développement rural. “Office of the Prime
Minister, Antananarivo, June.
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July. www.fivims.org.
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WTO (World Trade Organization). 2001. Trade Policy Review: Madagascar. Geneva: WTO.
4
Mozambique
Andrea Alfieri, Channing Arndt,
and Xavier Cirera*
In recent decades, Mozambique has undergone enormous political and economic
transformations. Once a colony of Portugal, the country moved to a phase of
socialism after gaining independence in 1975, and then from 1986 the government initiated a program of economic reform aimed at establishing a market
economy. Mozambique suffered from more than a decade of armed conflict, however, which together with other socioeconomic changes caused production to
continue declining during much of the period to the end of civil war in 1992.
Since then, a combination of peace, political stability, economic reform, and large
aid flows has helped the country move from being the poorest nation in the world
to achieving the highest growth rates in the region. Poverty rates have been significantly reduced and agricultural incomes have increased.
Roughly 75 percent of Mozambicans depend on agriculture for their livelihood
(Bias and Donovan 2003). For this reason, government interventions in the agricultural sector have potentially large impacts on many people’s welfare. The purpose of this chapter is to analyze and measure the effects of such interventions for
a group of agricultural products during the past three decades of economic transformation. We focus on whether interventions effectively tax or subsidize producers and processors of selected agricultural products. We do so by computing different measures of assistance, most notably the nominal rate of assistance (NRA)
to farmers for the period 1975–2004. The products analyzed are the main cash
* The authors are grateful to Carla Lopes for research assistance and to Danilo Abdula, Rafael Uaiene,
Jorge Tinga and all the staff at GPSCA-MINAG, Norberto Mahalambe, Juan Farfan, Dr. Raimundo
Matule, and Finn Tarp for suggestions and for providing data. We also appreciate the helpful
comments from workshop participants. Detailed data and estimates of distortions reported in this
chapter can be found in Alfieri, Arndt, and Cirera (2007).
127
128
Distortions to Agricultural Incentives in Africa
and food crops: beans, cashew, cassava, cotton, groundnuts, maize, rice, sugar, and
tobacco. These products represent about two-thirds of the value of primary agriculture production in the country.
Despite a lack of data availability for some years for prices, margins, and transport costs, the estimated coefficients suggest the existence of three clear periods
regarding government intervention in the agriculture sector. In the first period,
when the central government imposed fixed or minimum prices, producers were
clearly taxed and consumers were subsidized. This period was followed by price
liberalization in the 1990s, when producer assistance levels became neutral or positive, mainly because of market reforms and the rationalization of import duties
and taxes. In the third period (from the late 1990s), we observe an average reduction of assistance rates and an increase in their volatility, associated with large
exchange rate depreciations in the presence of slow price adjustment.
The chapter begins with a brief description of the agricultural sector in Mozambique and then summarizes the main policy interventions in the sector during the
three-decade study period. The chapter discusses the main distortion measures
used and the estimated rates of assistance and explores the evolution of policies in
Mozambique. It concludes with a discussion of prospects for further policy reform.
The Agricultural Sector in Mozambique’s Economy
Mozambique’s recent history can be divided into four different periods based on
the economic and political environments of the time (Wuyts 1978, 1984): a highly
regulated and dependent colonial economy before independence; a central planning period following independence in 1975; a high-intensity war period involving economic collapse; and a postwar period characterized by policy reform, large
aid flows, and high rates of economic growth after implementation of the peace
agreements. These periods can be clearly identified when analyzing agricultural
development in Mozambique.
Before independence
During this period, the monetized economy was equally divided into output from
plantations, settlers, and peasants. Production was highly specialized across
provinces. For instance, Zambezia, a central province, specialized in plantation
crops such as tea, copra, and sugarcane. Nampula, in the north, was the center of
cashew and cotton production, the two most important peasant cash crops, and it
also produced most of Mozambique’s sisal and tobacco.
Agriculture was highly regulated. Production of cash crops was structured
around geographical concessions, where only specific crops could be cultivated,
Mozambique
129
and there was a system of forced labor. Prices of production were fixed by negotiation between the colonial government, concession firms, and farmers.1 Agricultural commerce was carried out by a parastatal marketing board.
1975–1986
Immediately before and continuing after independence, a massive emigration of
the settler population and capital flight generated large falls in production and
marketed outputs. In 1976 the export value of agricultural crops was 40 percent
lower than it had been in 1973. The ruling Front for the Liberation of Mozambique nationalized several firms, but, surprisingly, the emigration of former
colonists did not lead to land reform. In fact, instead of distributing freed land to
peasants, the government itself took over abandoned land, which laid the foundation for the creation of large state farms in the years to come. State-controlled
agricultural operations, mainly organized in large-scale farms, rose to 52 percent
of total production by 1982 (Hanlon 1984; Wuyts 1984).
The marginalization of the peasantry and the lack of structured state assistance
contributed to a fall in production of both cash and food crops. Large investments
to overturn the situation could not be financed from internal savings, and
between 1975 and 1982, the monetary value of agricultural output fell by almost
30 percent.2
Agricultural policy during this period therefore can be characterized by an
intensification of regulation in what was already a highly regulated sector, a suppression of private initiative, and a policy bias toward larger farms. Prices were
fixed at all stages of the supply chain, and producer prices were set low to subsidize
consumers. The setting of mandatory producer prices below market-clearing levels encouraged the emergence of parallel black markets from the early 1980s.
1987–1994
In 1987, the Economic Rehabilitation Program began, marking a clean break from
past policies. Many fixed prices for agricultural goods were liberalized and others
became just indicative prices. Private traders entered the market. This caused a
sharp increase in consumer prices in formal markets (by 182 percent in 1987
alone) to align with prices previously registered in parallel markets. State farms
and other small and medium parastatal enterprises went through a vast program
of privatization, which concluded only at the end of the 1990s.
Despite the destabilizing effects of the ongoing civil war, which isolated farmers
from markets, especially in the center-north of the country, production increased
for key food and cash crops such as beans, cassava, cotton, groundnuts, and maize.
130
Distortions to Agricultural Incentives in Africa
Figure 4.1. Real GDP, Mozambique, 1970–2004
350
1986: Start of economic
rehabilitation program
billions of Mozambican meticais
at 1980 constant prices
300
1981: Intensification
of civil war
250
200
150
100
1975: Independence from Portugal
50
0
1970
1992: End of civil war
1974
1978
1982
1986
year
1990
1994
1998
2002
Source: Arndt, Jones, and Tarp (2006).
1994–today
With the signing of the peace agreement in 1992 and democratic elections in 1994,
Mozambique entered into a new phase of high economic growth—an average of
7.8 percent annually from 1993 to 2004 (figure 4.1).3 Agriculture probably benefited more than other sectors from the end of the war, because farmers could get
back to their land and because commercialization became easier, even though the
destruction of major transport infrastructure contributed to the segmentation of
the internal market into three distinct geographic regions: south, center, and north.
On average, real agricultural output grew 6.2 percent annually between 1992
and 2004. This was slightly slower than the economy as a whole, so the importance
of the agricultural sector as a share of GDP gradually declined, to 23 percent by
2004, but agriculture still remains the key sector in terms of employment.
Basic food crops include cassava and maize grown mainly by small-holders (69
percent and 63 percent of total production, respectively; TIA 2002). Cassava is the
more important of the two and is used mostly for subsistence consumption by
producing households, with very little marketed. Other major crops include
beans, groundnuts, and rice. Cash crops for small-holders include traditional
ones, such as cotton, cashew, and sugarcane, as well as “new” crops such as oilseeds
Mozambique
131
(sesame, soybean, sunflower), spices (ginger, paprika), and tobacco. The percentage of farmers growing these new crops, although small, increased in the first part
of the 1990s, signaling a possible diversification pattern that has been confirmed
by more-recent agricultural household surveys (TIA 2002).
With the end of the armed conflict, the relative stabilization of the macroeconomic framework, and large inflows of foreign aid, the country has had a propitious opportunity for the design of a long-term strategy for agricultural development. Unfortunately, Mozambique’s agricultural policy is still extremely
fragmented and without a clear prioritization of objectives. Remaining interventions seem to be more the heritage of past policies than the result of a new
forward-looking strategy.
Policy Interventions in Agriculture
In this section we describe the different policy instruments of intervention used
by the government, both general and product specific (for a more extensive
overview, see Bias and Donovan 2003).
General policies
Over time, Mozambique has used several types of intervention, from setting fixed
prices to imposing strict marketing regulations, production taxes, and trade tariffs.
Fixed and minimum prices
Before independence, the colonial government regulated farmgate prices. These
prices were established by a monopsonistic marketing board through which all
commercial production had to be sold. This system continued after independence
and throughout most of the war period. After independence, the National Commission of Wages and Prices set fixed producer prices, and all production had to
be sold at the set price to AGRICOM, a parastatal marketing board, which then
took care of distribution.
Prices began to be liberalized in the late 1980s, moving first from fixed to minimum prices, before being fully liberalized. Even though some minimum prices
were still present in the late 1990s, from 1996 they were only indicative. Currently,
only cotton is regulated, with an established minimum price for producers.
Commercialization
Commercialization of agricultural products was carried out by a state monopsony
during the colonial regime. After independence, this same system continued, and
the commercialization of all crops, except cotton and cashew, was controlled by
AGRICOM, which had a wholesale monopoly and regulated marketing margins.
132
Distortions to Agricultural Incentives in Africa
In the early 1990s, trading in agriculture was liberalized, and private traders
started entering agriculture markets. Restrictions regarding product movements
across districts and provinces were removed in the early 1990s, as was the colonial
system of official geographic monopolies for traders.
Trade taxes
During the colonial period, the agricultural sector was extremely protected, and
this high protection remained after independence and during the period of
central planning.
Mozambique started applying a most-favored-nation tariff structure in 1989.
The country became a signatory of the General Agreement on Tariffs and Trade
in 1992 and a founding member of the World Trade Organization in 1995. Since
then, import duties have been reduced and simplified. Agricultural products
were subject to a 20 percent tariff as of 2006, except for those products considered inputs or basic food products. Maize and rice paid just 2.5 percent and sugar
paid 7.5 percent. Tobacco and cottonseeds also paid 2.5 percent. Other products
such as beans, cashew, cassava, groundnuts, and tea paid 20 percent. Preferential
trade to other members of the Southern Africa Development Community did
not start for agricultural products in Mozambique until 2007. One agricultural
product, sugar, is also subject to a variable tariff surcharge that depends on
the international price of sugar; the surcharge is on top of the normal duty of
7.5 percent.4
To supply cheap inputs to the local cashew-processing industry, exports of raw
cashew were banned from 1976 to 1992. In early 1992, an export tax, still in place,
replaced the ban. The cotton sector has an export tax too, of 2–3 percent, aimed at
financing the crop improvement services of the National Cotton Institute (Instituto de Algodão de Mocambique, IAM).5
Taxes on and subsidies to production
Production subsidies have not been an instrument of intervention in Mozambique, and there are no records of any direct subsidies to production. The main
tax is a value added tax (VAT) of 17 percent, which was introduced in 1998 to
replace a consumption tax (5 percent). There are significant exemptions to VAT
that affect agricultural products, including a total exemption for seeds. Sugar
imports are also exempted from the tax. Nevertheless, the relevance of VAT for
domestic production and sales is questionable. The tax is always levied on
imports, except for sugar; however, most domestic production and retail sales of
farm products do not pay any VAT. As a result, the VAT acts de facto as a 17 percent
import duty for agricultural products.
Mozambique
133
Extension services
Most farmers do not receive any extension services. These are mainly concentrated in a few crops, such as cashew, cotton, maize, and tobacco. In the case of
cotton, these services are provided by the concessionary cotton company.6
Input policies
Small-scale agriculture in Mozambique typically does not use purchased inputs—
less than 10 percent of small-holder producers use any kind of purchased inputs.
The main sectors that make use of them are cotton and sugar, which do so
through private cotton and sugar concessions. Input markets in Mozambique are
more or less nonexistent, and only very recently have some private importers
established operations in Mozambique. Two donor-funded programs financed
most imports of inputs for agriculture during the 1980s and 1990s: the Mozambique Nordic Agriculture Program during 1977–90; and most important, the
Japanese program for Grant Aid for Increase in Food Production (KRII) during
1987–97. These two programs provided finance for the purchase of machinery,
fertilizers, and pesticides. But input interventions are concentrated on very specific crops and producers and have had very little impact on total agricultural production, in part because they are carried out in a fragmented way by nongovernmental organizations (NGOs) and donor-funded programs.
Product-specific interventions
The different products analyzed in this study can be grouped according to their
degree of intervention.7
One group of food crops, composed of beans, cassava, groundnuts, maize, and
rice, has received hardly any government support or intervention. For this group,
the main types of government intervention have been fixed and minimum pricing
during the 1970s and 1980s, and duties and a value added tax on imports. Maize,
rice, and groundnuts (to a lesser degree) had some support from donor-funded
programs and NGOs regarding extension services and improved seed varieties;
this aid, however, obtained mixed results.
A second set of products includes tea and tobacco, which are export cash crops
that have been developed through government-awarded concessions to private
firms. Apart from designing and implementing the regulation relative to concessions, since the removal of minimum prices and the privatization of the tea plantations, no substantial government intervention could be identified in either sector.
The last group of products consists of three cash crops subject to heavy intervention: cashew, cotton, and sugar. The sugar sector, since the privatization of the
sugar plantations and mills, has been granted high protection and has received
134
Distortions to Agricultural Incentives in Africa
investment incentives such as duty and VAT exemptions for importing capital
goods. The cotton sector is structured in a closed geographical concession system
where farmers are forced to sell to the concessionary Ginning Company, and in
exchange, they receive inputs and extension services on credit.8 Exports of raw
cashew had been banned until 1992, with fixed domestic producer and factorygate prices. In 1992, following World Bank suggestions, the sector was liberalized
and raw cashew exports were allowed through an export quota and subject to an
export tax of 30 percent. In the following years, the quota was removed and the
export tax was progressively reduced to 14 percent.
Summary of main interventions
Government interventions in agriculture can be clustered in three different periods. The first period, from 1975 to 1987, involved central planning, where large
plantations, commercialization, and processing firms were state owned. During
this period, the main instruments of government intervention were fixed and
minimum prices designed to subsidize consumer prices.
The second period, from 1987 to 1998, was characterized by progressive price
liberalization and privatization. In this period, prices and commercialization were
gradually liberalized and a new tax structure started being introduced.
In the current period, which began in 1999, government intervention has been
largely restricted to import duties and a VAT, while some specific sectors are more
highly controlled: sugar, through an import surcharge; cashew, through an export
tax; tobacco, through geographical concessions, and cotton, through minimum
prices and closed geographical concessions.9
Measuring Agricultural Policy Distortions
The main purpose of this chapter is to measure the level of distortions induced by
government policy interventions in the agricultural sector in Mozambique. The
focus is on government-imposed distortions that create a gap between domestic
prices and what they would be under free market conditions (appendix A and
Anderson et al. 2008). Since the characteristics of agricultural development cannot be understood from a sectoral view alone, the project’s methodology not only
estimates the effects of direct agricultural policy measures (including distortions
in the foreign exchange market) but also generates estimates of distortions in
nonagricultural sectors for comparative evaluation.
More specifically, this study computes the NRA for farmers, including an
adjustment for direct interventions on tradable inputs (such as border protection
on fertilizers) and on nontradable inputs (such as credit subsidies to farmers). It
135
Mozambique
also generates an NRA for nonagricultural tradables, for comparison with that for
agricultural tradables through the calculation of a relative rate of assistance (RRA,
see appendix A and Anderson et al. 2008).
Products selected
The products selected for the analysis for Mozambique are beans (nhemba and
butter beans), cashew, cotton, groundnuts, maize, rice, sugar, and tobacco, plus
the nontraded staples led by cassava and including millet, potato, sorghum, and
yam. The main criterion for selecting these products was their importance for
agricultural production in Mozambique—the products covered in the analysis
account for about 70 percent of the value of production in primary agriculture
(figure 4.2), but data availability also was a constraint. The traded products are the
main agricultural products in terms of exports, rural incomes, and focus of
government intervention.
Figure 4.2. Shares of the Value of Primary Agricultural
Production at Distorted Prices, Covered Products,
Mozambique, 1976–2003
100
90
80
percent
70
60
50
40
02
00
20
20
98
19
96
94
19
92
19
19
90
19
88
86
19
84
19
82
19
19
80
19
78
19
19
76
30
year
residual
cashew
bean
rice
millet
cotton
tobacco
sorghum
yam
groundnut
Source: Data compiled by authors using FAO price and quantity data.
sugar
maize
potato
cassava
136
Distortions to Agricultural Incentives in Africa
Cassava is a nontradable and complementary product to maize. It is grown by
subsistence farmers, and while a low share of production is marketed, it makes up
close to half the value of farm production and is very important in the consumption of food by poor rural households (Tarp et al. 2002). Beans and groundnuts
are mainly produced in the center and north and traded in southern markets,
where they compete with imports from South Africa. Most maize production also
takes place in the center and north, which registers some exports to Malawi, while
in the south, Mozambican maize competes with imported maize mainly from
South Africa. Rice is not extensively produced in Mozambique, and there is only
one rice mill in the south, which competes with Asian imported rice. In the center
and north, paddy rice is milled and commercialized in small quantities by smallscale processors.
Cotton and tobacco are export crops organized around concession systems.
Sugar is grown in large plantations that control production and milling; only
recently have outgrower schemes for small-holder production been introduced.
Finally, cashew is mainly a food crop produced by small-scale farmers. Part of the
production, however, is commercialized for processing factories or export.
Data issues
The main challenge in estimating any measure of assistance to agriculture in
Mozambique is the lack of data. Data are scarce, and sometimes there are significant discrepancies among different sources.
The Agricultural Market Information System (SIMA) within the Ministry of
Agriculture began to collect producer, wholesale, and retail prices in 1991 or 1994,
depending on the crop. SIMA collects information in all the provinces of the
country for several products. In the context of our sample, SIMA covers producer,
wholesale, and retail prices for beans (different types), cassava, groundnuts (different types), maize, and rice.10 In the case of sugar, data are available only since
1998 from the National Institute of Sugar. Cotton and cashew have long historical
series of prices from the National Cotton Institute and the National Cashew Institute. Prices for cashew are also reported in McMillan, Horn, and Rodrik (2003).
The main problem for most products, with the exception of cashew and cotton, is the lack of price data for the 1970s and 1980s. However, this period is characterized by regulated prices, and therefore we use government-established fixed
and minimum prices based on Tarp (1990) and MINAG (1993). These prices tend
to reflect accurate producer and retail prices until the early or mid-1980s. From
the mid-1980s to the years of price liberalization, however, black markets became
more and more important. As a result, producers and retailers received higher
prices, and we may be underestimating domestic prices and overestimating the
degree of taxation as expressed by the NRA estimates for this period.11
Mozambique
137
For cotton, this estimation problem is present during the whole study period.
There is evidence that some cotton companies pay prices different from the
agreed price to farmers, reflecting production incentives and transport costs. Nevertheless, these price differentials are not very substantial.
For international reference prices we use cost, insurance, and freight (cif)
import unit values, if the product is importable, or free on board (fob) export unit
values, when exportable. When cif import unit values from the rest of the world
are not available, we use South African export unit values and apply a cif adjustment, because most imports in Mozambique come from South Africa anyway.
To make prices comparable, we need to adjust them for margins. In the case of
import-competing products, we assume that commercialization margins are equal
for imported and domestic products, and we then adjust both prices with transport
costs. To do this, we inflate both prices using data on domestic transport costs for
maize available from SIMA from 2001 to 2005. We take as the point of comparison
the city of Maputo, the largest market in the country. Thus, we compute the average
transport costs from all the provinces of the country to Maputo and from the border
with South Africa and Swaziland to Maputo, for the period 2001–05. We then add
this transport cost coefficient as a percentage of producer price and as a percentage of
cif unit values to inflate the prices when we calculate the NRA. We apply this kind of
adjustment to beans, groundnuts, and maize.12 For rice and sugar, we apply transport
cost adjustments available specifically for these products (also from SIMA).
In the case of export products, we need to calculate the margin and transport
cost adjustment to the border. For cotton it is not required, because cotton lint is
exported by cotton processors directly so no intermediary is involved. For cashew,
we use the margins for traders suggested in McMillan, Horn, and Rodrik (2003)—
50 percent on the producer price and 40 percent on the processor price. For
maize, we use the average of transport costs from the center-north region to
Malawi as a percentage of price from 2001 and 2005 plus a 30 percent trader margin, as suggested by the Ministry of Industry and Commerce (MIC 2001).
For nontradable staple foods, we take prices and quantities from the database
of the Food and Agriculture Organization and assume their NRAs are zero.
The exchange rate was liberalized very gradually in the early 1990s, and some
capital controls still remain. Following Anderson et al. (2008), we use a weighted
average between the official and the parallel exchange rate, as the equilibrium
exchange rate that would prevail in the absence of any distortions.
Results
The NRA five-year average estimates are tabulated in tables 4.1 and 4.2, and
shown in figures 4.3 and 4.4. To compute the NRA measures, we use, whenever
data are available, a measure based on averages taken during commercialization
138
Distortions to Agricultural Incentives in Africa
Table 4.1. NRAs for Covered Farm Products, Mozambique,
1976–2003
(percent)
Product indicator
NRA, import-competing
productsa,b
Rice
Maize South
Bean
Groundnut
NRA, exportablesa,b
Maize Center
Maize North
Cashew
Cotton
Tobacco
NRA, mixed trade statusa
Sugar
NRA, nontradables
Cassava
Millet
Potato
Sorghum
Yam
NRA, total of covered productsa
Dispersion of covered productsc
Percent coverage (at undistorted
prices)
1976–
79
1985–
89
1990–
94
67.7 63.6 72.2
5.2
67.3
63.4
—
67.9
70.0
55.6
55.6
85.6
64.0
64.5
59.8
1980–
84
52.0
54.9
—
67.9
68.6
56.2
56.2
90.1
63.8
58.0
65.7
75.6
66.2
—
65.4
76.4
61.8
61.8
90.3
65.0
54.8
65.8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
48.5 41.6 51.4
36.9
33.9
38.1
70
61
60
1995– 2000–
99
03
29.5
55.4
49.6
7.5
7.6
10.1
26.0
43.9
5.0
18.5
25.5
3.1
0.0
0.0
0.0
0.0
72.9 13.8
1.4
2.7
31.6 19.0
18.9
90.5
25.8
19.9
50.6
46.3
1.0
0.0
0.0
5.5
2.4
0.0
101.8
0
0
0
0
0
0
3.9
26.6
73
0
0
0
0
0
0
4.9
30.3
80
0
0
0
0
0
0
7.2
30.1
71
Source: Data compiled by the authors.
Note: — no data are available.
a. Weighted averages, with weights based on the unassisted value of production.
b. Mixed trade status products included in exportable or import-competing groups depending upon
their trade status in the particular year.
c. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean
of NRAs of covered products.
(postharvest) periods, and when data are not available, we use yearly average
producer prices.13
In the case of import-competing products, the results show a very clear
common pattern in NRA values for all products (see figure 4.3), with periods similar to those described earlier. In the first period, NRA coefficients are highly
negative from 1976 through 1990, reflecting the government goal of subsidizing
Mozambique
139
Table 4.2. NRAs in Agriculture Relative to Nonagricultural
Industries, Mozambique, 1976–2003
(percent)
Indicator
NRA, covered products
NRA, noncovered products
NRA, all agricultural products
Trade bias indexa
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAb
Memo item, ignoring exchange
rate distortions:
NRA, all agricultural products
RRAb
1976–
79
1980–
84
1985–
89
1990– 1995– 2000–
94
99
03
48.5
0.0
42.8
0.05
70.1
28.0
76.7
41.6
0.0
19.0
0.08
67.3
28.0
74.4
51.4
3.9
0.0
0.0
38.3
5.0
0.38 0.20
75.1 15.4
28.0
28.0
80.6 33.9
4.9
7.2
0.0
0.0
2.2
5.1
0.25 0.36
16.3 26.0
28.2 23.1
9.4
2.4
24.3
60.1
12.7
66.4
36.3
75.8
2.2
9.4
3.6
33.1
5.1
2.3
Source: Data compiled by the authors.
a. Trade bias index is TBI (1 NRAagx兾100)兾(1 NRAagm兾100) 1, where NRAagm and NRAagx are
the average percentage NRAs for the exportable and import-competing parts of the agricultural
sector.
b. The RRA is defined as 100*[(100 NRAagt )兾(100 NRAnonagt ) 1], where NRAagt and NRAnonagt
are the percentage NRAs for the tradables parts of the agricultural and nonagricultural sectors,
respectively.
consumer prices through low fixed producer prices and fixed margins. These negative NRA values continue until the early 1990s, but we are overestimating the
degree of taxation expressed by the NRA by the end of this period: the lack of
market producer prices required us to use government-established minimum
prices, which are likely to be below actual prices received by producers.
In the second period, from 1991 through 1997, price liberalization is captured
in our estimations by the shift from using minimum prices to collected producer
prices from SIMA. For the reasons underlined earlier, it is likely that the rise in the
NRA that we record as having begun in 1990 actually began a couple of years earlier. During this period, domestic prices rose in order to achieve market-clearing
conditions. Furthermore, NRA coefficients started to become positive as a result
of the introduction of taxes on imports and exports.
The third period shows a peak for the NRA in 1998 and fluctuates around positive values that mainly reflect import duties. Note that volatility increases in this
period. Such an increase, when using observed producer prices, is consistent with
the experiences of other countries in the Africa region.
NRAs seem to oscillate during the period 1995–2000 around the value of the
import tariff, plus the VAT in some cases.14 Nevertheless, the average NRA
Figure 4.3. NRAs for Exportable, Import-Competing, and All
Covered Farm Products, Mozambique, 1976–2003
75
50
25
percent
0
25
50
75
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
100
year
import-competing products
exportables
total
Source: Data compiled by the authors.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
Figure 4.4. NRAs for Agricultural and Nonagricultural
Tradables and the RRA, Mozambique, 1976–2003
50
25
percent
0
25
50
75
02
20
00
20
98
19
96
94
19
92
19
90
19
88
19
19
86
19
84
19
82
19
80
78
19
19
19
76
100
year
NRA, agricultural tradables
NRA, nonagricultural tradables
Source: Data compiled by the authors.
Note: For definition of the RRA, see table 4.2, note b.
140
RRA
Mozambique
141
estimates for 2001–03 decrease significantly. The lack of government intervention
in the sector implies that the actual NRA values should theoretically converge to
import tariffs and VAT rates. Thus, the differences observed may well correspond
to measurement errors.
The case of exportable goods seems to be slightly different from importcompeting products. Despite the shift from a negative NRA toward zero with the
process of price liberalization, the trend after the 1990s is different across products. In the case of exportable maize in central and northern regions, the absence
of intervention causes the trend to converge to the expected zero NRA, while for
cotton lint, the trend converges to the export tax. For cashew and tobacco, NRA
estimates remain negative longer.
Evolution of NRAs by product
The NRAs for each product evolved somewhat differently, reflecting policy interventions specific to each market.
Maize
Maize is imported in the southern region and exported from the center and north
of the country. High transport costs make trading maize from north to south
unprofitable, and maize surplus is therefore exported to Malawi, while the deficit
in the south is largely covered by maize from South Africa. For this reason, we
compute the NRA for maize at these regional levels.
In the south, the NRA follows the trend described in the previous section for
import-competing products. In the first period, the NRA is negative because of
fixed and minimum pricing with the objective of subsidizing consumer prices in
urban areas. In the second phase, prices are liberalized and the NRA becomes positive, tending to converge to the import tariff. In the final period, the NRA is characterized by high volatility. However, in the absence of other policy interventions,
the actual NRA should lie around the import tariff plus the VAT rate.
In the center and north, where maize is exportable, the picture is quite different. Our estimates, accounting for fixed transport costs and trading margins of
about 41 percent, indicate a negative NRA during most of the period before 1990
of between 55 and 60 percent. For the period since then, we assume a zero
NRA in the absence of government intervention after price liberalization.
Beans
Two main types of beans are produced in Mozambique, nhemba and butter. Beans
are mainly produced in the center and north of the country, and the quantities
commercialized are mainly consumed in the south. The fact that nhemba beans
142
Distortions to Agricultural Incentives in Africa
are a domestic variety simplifies the calculations. There are no possible reference
prices for this type of bean, since it is produced only in Mozambique, and therefore, in the absence of intervention, the NRA can be assumed to be zero. Butter
beans, however, compete with beans imported from South Africa. For the period
for which we have data, the NRA following price liberalization is close to the tariff
and VAT rate of 46 percent.
Rice
Rice in Mozambique is mainly produced by small-scale farmers. More than 75
percent of production is concentrated in the center and north of the country. Rice
produced in the south is milled in the only existing industrial mill in the country,
while the rice produced in the center and north is milled directly by farmers and
then sold. In this case, producer and processor prices coincide. The trend of the
NRA for this product is similar to the rest of import-competing crops—highly
negative in the early period and then shifting toward positive rates similar to the
import tariff plus VAT.
Tobacco
Tobacco is an export crop organized in a system of geographical concessions, first
state-owned and then private. The NRA was more than 50 percent before liberalization and thereafter converged to zero.
Cotton
Cotton is very important in rural areas and is highly regulated. Table 4.2 shows a
highly negative NRA for cotton producers, but it has a highly positive trend
following the privatization of the ginning sector, when ginners were allowed to
export directly to the international market. The lack of quality adjustment may
explain some of the price differential, but the result seems to be consistent with
the findings by Boughton et al. (2003) of low quality and also very low producer
prices in Mozambique compared with other African countries.
Cashew
The cashew sector has been the subject of intense debate in the last two decades.
This is one of the main crops in the northern provinces, and the processing industry was traditionally one of the main sources of industrial employment. After the
reform many of the processing unions were forced to close down, unable to compete with prices offered by traders that export raw cashew for processing in India.
These reforms can be easily identified in the NRA evolution. For cashew producers after independence and with the export ban, NRAs are negative and very
high, indicating a large tax on producers to subsidize the processing industry with
Mozambique
143
cheap raw cashews. After the replacement of the export ban with an export tax,
the NRA became less negative. The gap between the producer price and the border
price, once controlled for the traders’ margin, narrowed considerably over the
1990s, and the NRA tended to converge on average to the export tax.
Sugar
Sugar is a very important focus of government support in terms of agroindustrial
policy. The structure of the sector, where processors control production, implies
that the relevant support measure for sugar is the processor NRA.15 This product
is considered to have been exportable from 1975 to 1982 and importable afterward.16 During the 1970s the sector was nationalized, and it operated with stateowned plantations that were privatized in the 1990s. This is reflected by a negative
NRA during the period until prices were liberalized and farms privatized. Then
import tariffs became the main influence on the NRA.
Aggregate NRAs and the RRA
The NRAs for covered agricultural products as a whole move from about 50
percent before 1990 to an average of zero in the 1990s and to just above zero in the
current decade. If we assume noncovered products are not distorted (because
many of them are nontraded horticultural and livestock products), the overall
NRAs for the farm sector are somewhat closer to zero. The NRA for tradable farm
products alone, however, is very negative before the 1990s’ liberalization. When
that NRA is compared with the positive NRA for tradable nonagricultural products, the relative rate of assistance is highly negative until the reforms begin to
make their mark in the 1990s; it then converges to zero and even becomes slightly
positive after 2000 (see table 4.2 and figure 4.3).
The final set of rows in table 4.2 shows what the distortion indicators would
have been had the distortions to exchange rates not been taken into account.
These calculations suggest that less than one-eighth of the RRA in the 1980s was
attributable just to exchange rate distortions, and that influence has since
disappeared.
Conclusions and Prospects for Further Policy Reform
The agricultural sector in Mozambique has undergone a process of progressive
liberalization and elimination of government intervention. The country shifted
from central planning, concession systems, and the use of fixed and minimum
pricing during the 10 years after independence toward a market economy. Since
the early 1990s, when those economic reforms began, government intervention
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Distortions to Agricultural Incentives in Africa
has been minimal and based mainly on the use of import tariffs, with the exception of cotton, cashew, and sugar where more complex policies have been implemented. Sugar now has a large positive NRA based on a very high import surcharge. While this situation is not unlike many other countries, the government
nonetheless could explore other, less distortionary forms of assistance.
Notes
1. The colonial government set producer and consumer prices as well as marketing margins at all
stages of production (Tarp 1990). These were negotiated with settlers’ farm associations. Prices varied
according to province of origin and quality.
2. Data in this section are drawn from a National Planning Commission report of 1994, cited in
Tarp and Lau (1996).
3. The average real growth rate during this period, excluding large project investments in natural
resources and aluminum, was 6.5 percent; the poverty headcount index moved from 69 percent in
1996/67 to 54 percent in 2002/03, and agricultural incomes increased on average about 27 percent in
the same period (Arndt, Jones, and Tarp 2006).
4. In 2004, for instance, this surcharge was close to 60 percent, although in 2006, when international prices were higher, the surcharge was zero and only the standard duty applied.
5. The export tax is intended to finance extension services, crop research, pest control, and other
activities, but the IAM’s provision of such services has been quite minimal because of the lack of
human and financial resources.
6. Some analysts suggest that these services tend to be of poor quality (see, for example, Wandschneider and Garrido-Mirapeix 1999). Boughton et al. (2003), and Walker et al. (2004) found these
services had a very limited impact on agricultural production and rural incomes. Some NGOs, such as
World Vision and CARE, and some donor agencies, offer some extension services under specific programs for cashews, cotton, maize, and tobacco in northern Mozambique.
7. The main product-specific interventions, and lists of the official interventions recorded in the
official government (Boletím da República), are described in the appendix to Alfieri, Arndt, and Cirera
(2007).
8. The geographical concession system was opened in the late 1990s, but some ginning companies
soon experienced financial difficulties and the reforms were abandoned.
9. In 1999, a donor-funded sectorwide program for agriculture (PROAGRI) of about US$200 million was introduced. Although it included support measures to extension and marketing, the program
has been criticized for not having a significant impact on agriculture. The main objectives of PROAGRI
are to improve the productive capacity and productivity of agriculture, the family sector, and the
private sector using labor-intensive technologies and sustainable management of natural resources; to
guarantee access to land and reduce associated bureaucracy; to promote and facilitate the marketing of
agricultural and livestock products, and also the access to markets (for factors of production as well as
credit); and to reduce the vulnerability of households facing chronic food insecurity (Bias and
Donovan 2003).
10. SIMA price data are collected in at least two or three markets for each province. Average prices
thus appear to be representative in geographical coverage, although they have not been weighted with
provincial consumption shares.
11. In addition, some observations are missing for some products in the early 1990s.
12. Three issues have to be taken into account when doing this. First, not all production is sold in
Maputo; a significant amount is commercialized in central and northern provincial markets. Second,
transport costs for maize do not necessarily reflect costs of transport for other products. Third, we
assume a constant transport cost ratio between border-Maputo and rest-of-the-country–Maputo
Mozambique
145
through time. Nevertheless, and despite these strong assumptions, what is relevant when using this
approach is the accuracy of the ratio between the two price-adjustment coefficients. This ratio should
also approximate the ratio of transporting another product from a remote farm to a central provincial
market relative to the transport costs from the nearest port to the same market.
13. For most products, higher producer prices experienced during the off season mean that NRA
values are higher when yearly averages are calculated. This may be misleading because in the absence of
storage infrastructure, prices that most producers receive are likely to be the prices recorded during
postharvest periods.
14. The value added tax is not paid along the value chain of agricultural products, from the farm to
the market, because small businesses are not required to charge the tax. Nevertheless, unless the product
is exempted, VAT is always paid at the border and therefore acts de facto as an import tariff.
15. For the NRA aggregation, we assume full pass-through of the distortion to sugarcane
farmers.
16. With the rehabilitation program in the 1990s and the protection granted to the domestic market, production has increased but is oriented toward the (relatively profitable) national market, where
Mozambique’s sugar competes mainly with sugar from South Africa or Swaziland. Exports are growing
but are limited to the quota-limited preferential access to markets in the European Union and the
United States.
References
Alfieri, A., C. Arndt, and X. Cirera. 2007. “Distortions to Agricultural Incentives in Mozambique.”
Agricultural Distortions Working Paper 54. World Bank, Washington, DC.
Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675–704.
Arndt, C., S. Jones, and F. Tarp. 2006. “The Impact of Aid Flows in Mozambique.” Ministry of Planning
and Development, Maputo.
Bias, C., and C. Donovan. 2003. “Gaps and Opportunities for Agricultural Sector Development in
Mozambique.” MINAG Research Report 54E. Ministry of Agriculture, Maputo.
Boughton, D., D. Tschirley, H. de Marrule, A. Osorio, and B. Zulu. 2003. “Cotton Sector Policies and
Performance in Sub-Saharan Africa: Lessons behind the Numbers in Mozambique and Zambia.”
Flash 34E. Directorate of Economics, Department of Policy Analysis, Ministério da Agricultura e
Desenvolvimento Rural. Maputo.
Hanlon, J. 1984. Mozambique: The Revolution Under Fire. London: Zed.
McMillan, M., K. Horn, and D. Rodrik. 2003. “When Economic Reform Goes Wrong: Cashews
in Mozambique.” NBER Working Paper 9117. National Bureau of Economic Research,
Cambridge, MA.
MIC (Ministerio da Industria e Comercio). 2001. “Analise dos custos de transporte na comercializacao
agricola em Moçambique—Estudo de casos dos transportes de milho das zonas norte e centro
para a zona sul de Mocambique.” DNCI 18. MIC, Maputo.
MINAG (Ministry of Agriculture). 1993. Estadisticas Agricolas 1975—1993. Maputo: MINAG.
Tarp, F. 1990. “Prices in Mozambican Agriculture.” Journal of International Development 2 (2):
172–208.
Tarp, F., C. Arndt, H. Jensen, S. Robinson, and R. Heltberg. 2002. “Facing the Development Challenge
in Mozambique: An Economywide Perspective.” Research Report 126. International Food Policy
Research Institute, Washington, DC.
Tarp, F., and I. M. Lau. 1996. Mozambique: Macroeconomic Performance and Critical Issues. Copenhagen: Institute of Economics, University of Copenhagen.
TIA. 2002. Trabalho de Inquérito Agrícola. Ministério da Agricultura e Desenvolvimento Rural,
Maputo.
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Distortions to Agricultural Incentives in Africa
Walker, T., D. Tschirley, J. Low, M. Pequenino Tanque, D. Boughton, E. Payongayong, and M. Weber.
2004. “Determinants of Rural Income in Mozambique in 2001–2002.” Research paper RP57E.
Michigan State University, East Lansing, MI.
Wandschneider, T. S. and J. Garrido-Mirapeix. 1999. “Cash Cropping in Mozambique: Evolution and
Prospects.” FSU Technical Paper 2. Food Security Unit, European Commission, Maputo.
Wuyts, M. 1978. “Peasants and Rural Economy in Mozambique.” Centro de Estudos Africanos,
Maputo.
———. 1984. “Money, Planning and Rural Transformation in Mozambique.” Journal of Development
Studies 22 (1): 180–207.
5
South Africa
Johann Kirsten, Lawrence Edwards,
and Nick Vink*
The Union of South Africa was formed in 1910 by combining two British colonies
(the Cape and Natal) with the defeated Boer republics (Transvaal and the Orange
Free State). In the ensuing years, the South African Parliament set about consolidating legislation from the four component territories and introducing new legislation (Vink and van Zyl 1998). In agriculture, for example, a Land Bank was
established under its own legislation in 1912, made up of elements of similar institutions that had existed in the four territories. Just a year later the first of the notorious land acts was promulgated, not only to proscribe land ownership by blacks
but also to outlaw labor tenancy and sharecropping. These laws set the scene for
an approach to agricultural policy that was to dominate the sector for at least the
next seven decades, namely, increasing support to white commercial farmers and
decreasing opportunities for black farmers.1 The structural dualism that resulted
still exists today after more than a decade of democracy.
Between 1910 and 1935, 87 acts were passed that allowed the government to assist
farmers (Minnaar 1990). For example in 1912, the year the Land Bank was established, the Land Settlement Act was also promulgated. Its purpose was to regulate the
settlement of white farmers on state-owned land and to enable the state to purchase
further land for such settlement (Grobler 1988), a process that was to last until after
World War II. This legislation was followed in 1922 by the Cooperative Societies Act,
aimed at securing input supply and marketing services for farmers through legislation that favored cooperatives by limiting their tax liability and introducing the concept of “forced cooperation” to enable them to manage free riding. It is estimated that
* The authors are grateful for helpful comments from workshop participants. Detailed data and
estimates of distortions reported in this chapter can be found in Kirsten, Edwards, and Vink (2007).
147
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Distortions to Agricultural Incentives in Africa
the government spent £112 million on agriculture between 1910 and 1936, and a further £11 million on export subsidies between 1931 and 1937 (De Kiewiet 1942).
The year 1937 saw the advent of a marketing law, under which more than
70 percent of total agricultural output was controlled until 1996, when the new
Marketing of Agricultural Products Act was promulgated by the democratic government. The Marketing Act of 1937, amended in 1968, sanctioned different types
of marketing schemes for different agricultural commodities. The powers available under these plans included monopoly buying, single channel exports, control
over agroprocessing, and quantitative controls over imports. Of the commodities
included in the current study, only poultry meat escaped this form of control,
while the sugar industry was regulated under separate legislation.
The main impetus for this agricultural policy was aptly summarized in a white
paper published by the government (Union of South Africa 1946):
Farming has been our traditional occupation and it still sustains three-fifths
of the population. The industry is therefore of great economic importance.
It is of similar importance nutritionally. Great distances separate us from
the food exporting regions of the world. . . . A large and healthy farming
industry is a key factor in national security. In these circumstances the people of the Union have a vital interest in the farming industry—in its efficiency and prosperity. . . . [T]he farming industry is in large part unable to
stand up to overseas competition, the real test of efficiency in normal market conditions. The production of wheat, sugar, maize, dairy, wine, [and]
tobacco has expanded chiefly under the stimulus of heavy protection. Even
so in bad seasons total production falls short of the effective demand. Nor
does the industry in its present state provide reasonable living conditions
for the bulk of farmers and farmworkers. . . .
After 1955, the story of agricultural policy toward commercial farmers
involved widespread support, regulation, and control in a climate of increasing
isolation from the rest of the world, especially in the 1980s, followed by rapid
deregulation and trade liberalization during the course of the 1990s with the
advent of democratization and implementation of the terms of the Marrakech
Agreement that brought agriculture into the World Trade Organization. It is this
period since 1955 that is the focus of the rest of this chapter.
Economic Performance of South African
Agriculture since 1955
The growth performance of South African agriculture is characterized by distinct
periods that correspond to the policy periods described in the next section.
During the 1950s and 1960s, as the South African government invested in
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149
agricultural research, extension services, rural infrastructure, and settlement of
farmers, agricultural output gradually started to grow. Guaranteed markets and
guaranteed prices for most farm commodities assisted the growth in the sector.
The 1970s was also a period of rapid growth in the economy, assisted by high gold
prices and high agricultural growth, but the oil crisis in the mid-1970s negatively
affected economic growth in the late 1970s and early 1980s. Direct government
transfers to farmers plus highly supported farm prices stimulated agricultural
growth in the late 1980s, pushing it up to the level of the early 1970s. A massive
drought in the early 1990s, market liberalization, and the instability before and
immediately after the 1994 elections all negatively affected growth opportunities
in the sector. Agricultural growth has increased marginally since the end of
apartheid, but only after confidence in the democratic change was restored, and
then only with a weakening exchange rate and thus higher commodity prices and
export earnings.
Relative to the rest of the economy, however, the share of agriculture, forestry,
and fisheries in the country’s gross domestic product (GDP) has declined steadily
since 1955 to its current level of less than 4 percent. The mining sector has also
experienced a decline in its relative share of GDP, but so has manufacturing. Services account for a steadily increasing share of GDP, as the South African economy
has reached a relatively advanced stage of maturity.
Within agriculture, there has been a shift in the relative shares of livestock, field
crop, and horticultural production. The livestock sector has maintained an overall
share of about 45 percent of total agricultural output, moving between 35 and
50 percent with the typical livestock cycle (Department of Agriculture 2006).
However, the composition of livestock production has changed considerably. Beef
and veal production increased from 450,000 tons to 700,000 tons between 1970
and 2005, but cattle’s share of total meat production nevertheless declined from
52 percent to 39 percent over this period. Likewise, pork production has
increased, but its share of the total has declined from 9 percent to 7 percent, while
sheep and goat meat has declined in absolute terms (from 214,000 tons to 112,000
tons) and relatively (from 25 percent to 6 percent). The big shift has been to poultry meat, with production increasing from 121,000 tons to 862,000 tons and its
share increasing from 14 percent to 48 percent of the total.
The composition of field crop production has not changed much over the past
three decades: sugarcane and maize made up 59 percent of the value of production in 1970, and maintained that share in 2005. Production of some specialty
cash crops such as cowpeas, lentils, and chicory root has virtually come to a halt,
while cotton production has also declined considerably.
Within the horticultural sector, fruit has increased its share of physical
production from 55 percent to 60 percent, while within that sector, the share of
deciduous fruit declined by 6 percentage points (from 60 percent to 54 percent of
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Distortions to Agricultural Incentives in Africa
the total between 1976 and 2004) while the share of citrus increased to 31 percent.
Subtropical fruit, berries, and summer fruit maintained their relative shares of
total output.
Exports of primary agricultural products and food products have also grown
rapidly, although their share of total merchandise exports declined from approximately 18 percent in 1975 to around 7 percent in 2004, as would be expected during the process of development of the economy. Exports of processed agricultural
products have increased faster than exports of unprocessed agricultural products:
the share of processed goods in total agricultural exports has increased from
around half to around 60 percent.
Agricultural imports have also risen and at a faster rate than other imports or
agricultural exports. Agricultural imports have more than doubled their share of
total imports into the country over the past two decades, from 2.6 percent to
5.4 percent. During this period, imports increased from 6.2 percent of total agricultural output to more than a fifth (22.6 percent) of output. As a result, import
cover (the ratio of agricultural exports to agricultural imports, a measure of the
ability of the agricultural sector to pay for its own imports) has declined drastically from 5.6 to 1 to 1.35 to 1. The main reason for the rapid increase in imports
is the emergence of animal feeds, especially poultry feed, as South Africa’s main
agricultural import item. Along with this has been the emergence of Argentina as
the single largest source of agricultural imports.
The export composition and export orientation of agriculture has also shifted
over this period. South Africa is generally a net importer of meat and is an
exporter of field crops in some years. Maize exports have remained relatively
stable, but as production has risen, the share of maize output that is exported
has declined from 30–40 percent of the total harvest in the 1970s and 1980s to
10–20 percent over the first five years of the current decade. In the case of horticulture, there has been a considerable shift in export orientation: the share of
production exported has increased from around 24 percent to 32 percent over the
past three decades. Within deciduous fruit, exports have shifted away from apples
toward apricots, table grapes, pears, peaches, and plums, while within citrus the
relative shift has been away from grapefruit and lemons toward oranges. The only
subtropical fruit that South Africa has traditionally exported is avocados, and the
proportion of the total crop that is exported has increased from some 40 percent
in the early 1980s to just over 60 percent.
Nevertheless, the country’s export portfolio has not changed much for more
than a century. Traditionally, wine, fruit, sugar, maize, wool, and hides and skins
were exported, mainly to the United Kingdom and other parts of Europe. These
items made up 72 percent of total agricultural exports on average between 2002
and 2004 (up from around 45 percent in 1972), while the European Union
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151
remains the largest export destination, taking more than 40 percent of exports.
South Africa’s second largest agricultural export market is to other countries
within the South African Development Community, accounting for almost
20 percent of total agricultural exports.
Total farm employment increased until the early 1970s, after which it started a
long decline. In 1955, agricultural employment still represented more than 25 percent of total formal sector employment in the country (Vink and Kirsten 1999),
but it was less than 10 percent at the time of the last census in 2002. However,
these data hide the relative shares of permanent and seasonal labor. The trend
toward horticultural production is expected to result in a swing to more seasonal
workers, because harvesting in this sector is still largely done by hand.
Agricultural Policy
State support to commercial farmers increased until around 1980, with the
deployment of a host of legal and other policy instruments that affected the prices
of and access to natural resources, finance, capital inputs, and labor, as well as
access to local and foreign markets.
Policies to 1980
The main features of the commercial agricultural sector after World War II were
the mechanization of commercial farming, the consolidation of marketing plans,
and increased pressure on food production in the homelands. Regarding mechanization, the experience in the maize farming areas tells the story of capital and
labor substitution in agriculture (De Klerk 1983).
The total number of farm employees in South African agriculture grew until
1970. Although this trend corresponded with increased mechanization following
the large-scale introduction of tractors, an increase in the area planted led to
increased demand for labor to harvest the bigger crop. Employment then fell
between 1970 and 1980, although farm employment was still higher in 1980 than
it had been in 1950. The turning point around 1970 coincides with the introduction in the late 1960s of combine harvesters, stimulated by preferential tax treatment. De Klerk (1983) shows that the share of the maize crop that was harvested
with combine harvesters grew from 16 percent in 1968 to 81 percent by 1977. This
period simultaneously saw the highest rates of forced removal of permanent labor
from farms and an increasing use of temporary or seasonal labor, most of whom
were women and children (Marcus 1989).
Other features of the commercial farm sector in the postwar period include the
tightening of control over prices and over the movement of produce under terms
of the Marketing Act, and an increase in subsidies to white farmers. The subsidies
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Distortions to Agricultural Incentives in Africa
came partly from direct budgetary transfers for disaster relief, irrigation infrastructure, water subsidies, research, and the like and partly through price policy
and interest rate subsidies.
South Africa used a full range of policy instruments to support commercial
farmers, including not only direct subsidies but also many regulatory instruments
aimed at health, safety, and the protection of natural agricultural resources. Yet the
most important instrument used was marketing intervention, mainly through the
Marketing Act. This enabling legislation set out the conditions under which farmers or the minister of agriculture could set up a marketing plan that would be
administered by a control board. The powers of the board were selected from
among those allowed under the act, and farmers were guaranteed a majority of
the seats on the board. By the 1970s, more than 20 boards were in operation, covering some 80 percent of total agricultural production.
The maize, red meat, and deciduous fruit export schemes are discussed below
to illustrate the working of the specific control measures pertaining to each, as
well as the economic consequences of these schemes.2
The maize scheme
Until the late 19th century, sorghum was the most prevalent starchy staple consumed in southern Africa. However, white maize superseded sorghum as traditional economies became monetized, largely because maize production and
preparation placed fewer demands on available household time (Low 1986).
The result is that the demand for maize in southern Africa differs from that in
the rest of the world because of the relatively large human consumption of
white maize. That also made it easier for South Africa’s Maize Board to justify a
control regime that precluded imports as far as possible, in the name of food
self-sufficiency.
Maize marketing was controlled under a single-channel, fixed-price regime.
The Maize Board was the sole buyer and seller of maize at a price fixed annually by
the Parliament’s cabinet. Annual surveys of average production costs by the
Department of Agriculture were used as the basis for the price. Farmers’ selling
price to the Maize Board was set at average production cost plus a profit margin,
while the board’s selling price to millers was its buying price plus a margin that
covered handling, storage, and transport. The board appointed agents to purchase
maize from farmers on its behalf and to store and distribute the produce to
millers. The board usually appointed a cooperative to act as its agent, with the
result that the cooperatives gained regional monopoly powers.
The buying and selling prices of maize were panterritorial and panseasonal,
fixed regardless of when and where maize was delivered. The board also controlled imports and exports. A stabilization fund was set up to defray expenses in
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153
times when surpluses had to be exported at a lower world price and to deposit
profits in times of shortage when the board could import at a lower world price.
In practice, the board set buying and selling prices in such a way that the stabilization fund was perpetually in arrears. During the late 1970s and the 1980s, the
board exported some maize every year, and the weighted average of maize domestic prices remained above the export realization price. The panterritorial pricing
regime meant that transport costs of those farmers who delivered maize from distant areas were subsidized by farmers closer to the market. The transport system
was expected to transport raw commodities rather than processed foods, thereby
increasing the cost structure of the system as a whole. Millers paid the same price
regardless of the location of their plant. Over time, therefore, the agribusiness sector gravitated toward the main urban areas, thereby depriving the rural areas of an
important source of economic activity. Panseasonal pricing had a similar effect on
storage, preventing the emergence of private sector stockholding.
The red meat marketing scheme
The per capita consumption of beef and veal in South Africa decreased from
36 kilograms in fiscal 1948/49 to 22 kilograms in fiscal1980/81, while that of poultry increased from 2.2 kilograms to 12 kilograms over the same period (Nieuwoudt 1985). Thus, any policy intervention that resulted in an artificial increase in
the price of red meat would favor the poultry industry. The red meat marketing
plan did precisely that: by restricting sales of red meat, it contributed to the rise in
popularity of its greatest competitor.
Formally, the red meat scheme was classified as a “surplus removal scheme,”
because the main instrument used was a minimum price set by the Meat Board to
stabilize the price by removing short-term surpluses and adding supply to the
market in times of shortages. Again, the board frequently could not resist the
temptation to set the minimum price above the market-clearing level, with the
result that additional intervention was required to manage the resultant oversupply on the market. To this end, the board divided the country into controlled and
noncontrolled areas, where the former covered the areas of greatest demand, that
is, the main metropolitan markets. At the same time, the requirements for the
erection of abattoirs were tightened, with the result that most of the smaller facilities in the country were closed down. Permits or quotas were required of any producer who wished to sell red meat into the controlled market.
The economic consequences of the scheme are clear. Because large producers
(mostly feedlots) were more likely to gain access to quotas or permits, they were able
to capture the economic rents arising from the difference in price in the controlled
and uncontrolled areas by buying stock in the countryside and selling it in the towns
and cities. Thus, the largest effect of the intervention lies in the redistribution of
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Distortions to Agricultural Incentives in Africa
wealth toward larger producers (and speculators) and away from smaller producers.
Since larger producers were more likely to have their interests represented on
the board, these economic consequences become something of a self-fulfilling
prophecy. Transportation rules were not fully enforced, however, and unrecorded,
informal sales of red meat into the poorer urban areas had become almost the norm
rather than the exception by the 1980s (Karaan and Myburgh 1993).
The deciduous fruit scheme
South African fruit exports started in the early 1890s, and annual apple exports
had reached 170,000 tons by 1975, compared with 50,000 tons from a country
such as Chile. However, Chilean apple exports grew by some 800 percent from
1975 to 1995, compared with the approximately 66 percent growth in South
African exports.
One of the main differences in the marketing regime between South Africa and
Chile was the extent of state intervention in South Africa. There, deciduous fruit
and citrus were marketed under a single-channel pool scheme, where the respective boards or their agents were the sole buyers of fruit for the export market and
therefore the sole sellers in the export market. The produce of farmers was pooled,
and the proceeds divided on the basis of the quantity delivered to the pool. As a
result, farmers who delivered produce that was below average in quality were
favored, while those that delivered high-quality fruit were penalized.
These monopolistic arrangements probably inhibited growth in the volume of
exports in any number of ways.
• The South African deciduous fruit industry traditionally focused on selling
only the best quality under the “Cape” trademark, with the result that price
premiums of up to 30 percent were regularly achieved. However, this quality
came at the expense of volume.
• South African exporters had to finance the facilities required to move their produce from the farm to the respective boards themselves. The considerable
investment in packing houses, combined with relatively high interest rates, limited the amount of investment funds available for the expansion of production.
• South Africa was relatively unsuccessful at exploiting new markets, with only a
small proportion of exports going to nontraditional markets such as in Asia and
the Middle East, compared with Chile, which sold about a third of its export
crop in these markets. Again, it could be argued that a monopoly exporter
would not be sufficiently flexible to be able to exploit such niche markets.
• A further result of the concentration of exports to a few traditional markets,
and South Africa’s isolation from the world market, was the relative lack of
effort given to the development of new cultivars in the period before 1990.
South Africa
155
Hence the country’s fruit growers have since been at a competitive disadvantage with respect to changing tastes abroad.
A broadening of the policy focus
Four events between 1973 and 1976 created a security crisis in South Africa (Vink
and Schirmer 2002). These included labor unrest and “unlawful” strikes by black
trade unions in the Durban region in 1973; the OPEC (Organization of Petroleum
Exporting Countries) oil crisis of 1973; the coup d’état in Lisbon in April 1974 that
led to the abortive invasion of Angola by South Africa in 1975; and the Soweto
unrest of June 1976. Despite attempts by the ruling elite to maintain the existing
order, it lasted for fewer than 20 years after these events and was doomed to failure.
By 1976, the economy had moved into recession, which turned into a period of
prolonged stagflation that lasted until 1994. Terreblanche (1998) shows that over
time the ruling National Party shifted from an exclusive focus on the interests of
Afrikaners to a broader focus on the interests of whites. Vink (1993) summarized
the impact of agricultural policy in the period leading up to 1980 as follows:
This combination of segregation of land ownership and a two-track
approach to access to support services had a number of major effects on the
farming sector. First, it resulted in extraordinary institutional duplication
with attendant high fiscal cost. . . South Africa ended up with 11 Departments of Agriculture by 1980 (14 by 1984). . . Second, it created “two agricultures” . . . which differed in access to land and support services, productivity, etc. . . Third, it created the anomaly of a country that regularly
exported food “surpluses” while most of the population lived well below
minimum levels of living. In addition, the food self-sufficiency index
showed exports of field crops and imports of red meat while the country
has a poor arable resource base. . . . Fourth, for much of this period farm
input prices were rising faster than product prices despite attempts to keep
domestic prices above parity with imports. Fifth, there was much evidence
of severe environmental damage to fragile land resources in both the commercial farming areas and the homelands. . . . Sixth, the combination of
subsidies and distortionary price policies led to high rates of growth in
farmland prices. By the beginning of the 1980s the farm sector had become
inflexible and it has been argued that these farm policies made the sector
particularly vulnerable to the disastrous drought that struck the
subcontinent in the early 1980s. . . . Seventh, the processes of forced
removals and homeland consolidation created a high level of uncertainty
among individual farmers, both black and white, as to the protection of
existing property rights, with predictable economic consequences in some
of the ecologically most vulnerable parts of the country.
156
Distortions to Agricultural Incentives in Africa
Policies during the 1980s
Financing and assistance formed one of the three pillars for the Ministry of Agriculture’s policy of “optimum agricultural development,” as defined in a 1984
white paper (RSA 1984). The other two pillars on which this policy was based
were optimum agricultural resource use and orderly marketing and price stabilization. Agricultural financing was considered an important third pillar in view
of the risks inherent to agriculture in South Africa’s relatively unsuitable climate.
This, according to the government of the day, necessitated special financing facilities to create confidence in the industry and to give it needed stability.
Agricultural financing programs were provided through the Land Bank, commercial banks, other private financiers including the agricultural co-operatives,
and finally the funds supplied under the Agricultural Credit Act of 1966. Funds
were made available under this act to help poorer farmers acquire land and to provide production loans. These programs are summarized in Kirsten, Edwards, and
Vink (2007, appendix table 3).
During this period, marketing policy started to shift quite radically, although
within the framework of the Marketing Act and the control boards that constituted its institutional infrastructure. Vink (1993) argues that these changes came
about as a result of macroeconomic pressures. South Africa’s macroeconomic policy changed in the late 1970s and early 1980s from a focus on nonmarket controls
over monetary policy toward market-oriented controls (Strydom 2002). Monetary policy reforms were led by the submission of the report of the De Kock Commission (1985), which, through its interim reports, had already stimulated a shift
away from interest rate controls, liquid asset requirements, and cash reserve
requirements as the main instruments of monetary policy.
The example of the Land Bank is relevant here, because it was allowed to sell
scrip of up to three years’ duration under the definition of “liquid assets,” enabling
the Land Bank to pass on these lower borrowing costs to its clients, the commercial farmers, without requiring a direct subsidy from the taxpayer.
Financial sector liberalization preceded the deregulation of the real sector of
the economy. One of the results was to stimulate exports by allowing the free
floating exchange rate to depreciate while import substitution policies were still in
place in the manufacturing sector. Fiscal policy was no more successful. Its main
feature was the rising cost of maintaining the apartheid system (Strydom 2002),
which was reflected in an increase in current expenditure as a proportion of GDP,
the growing cost of homeland governments, increased spending on security (military and police), and a high tax burden. One important consequence was that the
budget deficit reached a peak of 7.3 percent of GDP in 1993 (Strydom 2002),
necessitating high real interest rates.
South Africa
157
The most immediate effect on agriculture came from changes in the external
value of the currency and in the interest cost of farm borrowing. As the South
African rand started a decade-long decline in value, farm input prices, which have
a relatively large import component, rose faster than farm output prices. At the
same time, interest rapidly became the single largest cost of production in agriculture. During this period, many of the existing controls over the movement of
labor in South Africa were also lifted, setting in motion a vast population movement from the farms and the homelands to the towns and cities (Urban Foundation 1991). This was accompanied by migration of people from most parts of
Southern Africa to the rural and urban areas of South Africa (see Simkins 1993,
for example). Finally, considerable microeconomic deregulation took place, also
starting in the late 1970s and early 1980s, leading to a significant increase in activity in the informal economy (Kirsten 1988; May and Schacter 1991; Moll 1993).
One of the most visible effects was the increase in informal marketing of farm
products in the urban areas (Karaan and Myburgh 1993).
Beginning in the 1980s, the agricultural authorities undertook a process of
deregulation and policy change in the farm sector.3 The most prominent examples
include the following:
• Deregulation of marketing by loosening the terms of the Marketing Act and
other legislation. This included the elimination of restrictive registration of
processors in the red meat industry, the abolition of most controls on domestic
marketing of deciduous and citrus fruit, the abolition of production quotas in
the wine industry, deregulation of single channels for sorghum and leaf tobacco;
and eventual deregulation of the mohair and maize schemes as well as abolition
of control schemes in the banana, wool, egg, and chicory industries. The report
of the Kassier Committee (1992) can be regarded as a milestone in this process.
• Liberalization of price controls in large parts of the farm sector, again mainly
by relaxing the terms of the Marketing Act. Price setting in the grain industries
was changed from a cost-plus basis to market-based systems (Brand Report
1988), leading to substantial declines in real farm output prices. The most
important liberalization was the restriction on the ability of control boards to
carry losses and profits on stabilization funds into a following year. Additional
examples include the eventual abolition of price controls on dairy products
and later on flour, meal, and bread; and the termination of consumer price
subsidies on maize meal and bread.
• A change in tax treatment of agriculture, which, among other things, reduced
the implicit subsidy represented by income tax concessions to farmers, which
in 1981–84 amounted to 70 percent of their theoretical tax bill (Lamont 1990).
Changes in tax policy also resulted in an extension, from one to three years, of
158
Distortions to Agricultural Incentives in Africa
the period over which capital purchases could be written off; restrictions were
also placed on the extent to which farming could be used as a tax shelter for
other income sources.
• A change in direct budgetary expenditure on agriculture, including a proportionate increase in budgetary transfers to the Departments of Agriculture in
the homelands and a proportionate decrease to commercial agriculture (Vink
and Kassier 1991). In addition, real spending on commercial farming was
reduced during the 1980s (Brand et al. 1992).
• Scrapping, in 1991, of the Land Acts and related legislation that enforced the
racially based segregation of access to land. This was the most visible of the
policy changes in agriculture following the breaking of the political logjam in
February 1990.
• Tariffication of farm commodities, mainly because of the pressures arising from
the Uruguay Round of the General Agreement on Tariffs and Trade (GATT).
Policies since the 1990s
Deregulation and liberalization were a fact of life in the agricultural sector of
South Africa during the 1980s.4 Yet isolation from the world market, accompanied
by the increased isolation of the country in the social, cultural, political, and intellectual spheres, meant that the deregulation steps that did take place were aimed at
the domestic market. Foreign trade still consisted primarily of managing imports
and exports in order to manipulate domestic prices (for commodities such as
maize and wheat) or to protect monopoly export schemes (for fruit, for example).
The steps that were taken were characterized by change within an existing institutional structure, because the main players remained in place despite the general
relaxation in state intervention. The leadership structure itself then changed with
the election of the Government of National Unity in 1994, although in agriculture
some changes had to wait until 1996 after the withdrawal of the National Party
from the Government of National Unity and the appointment of a minister of
agriculture from the African National Congress party.
The most important policy initiatives taken after the advent of majority rule in
1990s included land reform, institutional restructuring in the public sector, the
promulgation of new legislation including the Marketing of Agricultural Products
Act and the Water Act, and trade policy and labor market policy reform, all within
the framework of wider macroeconomic policy reform.
Marketing policy
The Marketing of Agricultural Products Act of 1996 changed the way in which
agricultural marketing policy was managed in South Africa, not least by opening
the sector to world market influences in a manner that could hardly have been
South Africa
159
anticipated a decade earlier. The act, promulgated on January 1, 1997, set up the
National Agricultural Marketing Council (NAMC), whose immediate task was to
dismantle the existing control boards by January 6, 1998, after which it would
manage and monitor state intervention in the sector. 5
Land reform
Land reform was initiated in 1994, but the process of designing the actual land
reform policy was not completed until 1997, when the Department of Land
Affairs published its white paper (RSA 1997). Under this plan, land reform was to
consist of land restitution, redistribution, and tenure reform programs, but the
actual shape of the programs remained subject to much debate. A large proportion of the analytical work that supported the policy positions taken during these
debates was subsequently published in Van Zyl, Kirsten, and Binswanger (1996).
The program was designed more or less in accordance with the market-assisted
approach recommended by the World Bank (1993). In practice, however, beneficiary households usually had to pool their meager (means-tested) grants to afford
land from a willing seller. The reason was at least partly attributable to a 1970 law
governing subdivision. Its repeal was provided for by Parliament in the Subdivision of Agricultural Land Act Repeal Act of 1998. Repeal has not yet been brought
into operation by the president, however, and until subdivision is facilitated farm
boundaries can rarely be redrawn into affordable pieces of land. Instead of subdivision, at the end of the 1990s a new approach, termed the Land Reform for Agricultural Development program, was adopted, which provided for an extended
scale of grants, the size of which depended on the amount each farmer contributed
(LRAD 2000). At the same time, the Comprehensive Agricultural Support Program
was launched. Its purpose was to implement farmer support services such as
research, extension, finance, information, and infrastructure.
Overall, the net effect of the land reform program has been limited. After
12 years of state-sponsored land reform, less than 4 percent of the land has been
transferred.
Institutional restructuring in the public sector
One of the main features of South African agricultural policy in the 1990s was the
extent of institutional restructuring that took place. Some institutions (such as
the Development Bank, the Land Bank, the Agricultural Research Council, the
Department of Regional and Land Affairs, and the Development Corporations in
the former homelands) were believed to be too closely aligned with apartheid
policies aimed at “development” of the former homeland areas or favoring commercial farmers (Callear and Mthethwa 1996; DBSA & LAPC 1997). Such institutions were subjected to restructuring programs intended to realign them in support of the development priorities of the new government.
160
Distortions to Agricultural Incentives in Africa
Also, public sector agencies supporting the agricultural sector were subjected
to the processes of “provincialization” established under the interim and then the
final constitution. In the case of agriculture, the formerly race-specific “own
affairs” and “general affairs” departments were amalgamated to form the core of
the new national Department of Agriculture, new provincial departments were
created, and the functions and staff from the former homeland departments of
agriculture were redeployed to the new national or provincial departments as
appropriate. All agricultural institutions in the public sector were reoriented to fit
in with new policy directions. The most radical of these changes occurred in the
agricultural marketing institutions.
Water law reform
Changes resulting from the new Water Act of 1996 were expected to have a severe
effect on agriculture. These changes included the priority afforded to water uses
that were more highly valued, including preferential access for small farmers and
the environment, the termination of the riparian principle of water rights, the
implementation of an integrated catchment management system, the termination
of subsidized water prices, and greater cross-border cooperation between Southern African countries. Slow progress in the implementation of the act has, however, minimized its impact to date.
Labor market policy
Until the 1980s, farmworkers in South Africa had little legal protection of their
rights to organize and of basic conditions of employment. The Agricultural Labor
Act of 1993, addressed this shortcoming to some extent, but it was only after 1994
that farmworker rights were brought into line with rights of workers elsewhere in
the economy. The four major labor laws in South Africa—the Labor Relations Act
(1995), the Basic Conditions of Employment Act (1997), the Skills Development
Act (1998), and the Employment Equity Act (1998)—all applied to the agricultural sector. One consequence has been the adoption of a minimum wage, differentiated by region, for farmworkers.
Trade policy
Quantitative restrictions; a multitude of tariff lines; a wide dispersion of tariff
rates; and formula, specific, and ad valorem duties and surcharges characterized
South Africa’s trade regime before 1994 (Lewis 2001; Edwards 2005). In agriculture,
quantitative restrictions, specific duties, price controls, import and export permits,
and other regulations were replaced by tariffs after 1994, when South Africa was
among the original signatories to the Marrakech Agreement establishing the World
Trade Organization following the GATT’s Uruguay Round negotiations. Surcharges
South Africa
161
implemented in response to the balance of payments crisis in the late 1980s were
also reduced and eliminated by 1995. The one exception to this process of liberalization was the sugar industry, where a price pooling system remained and the
South African Sugar Association continued to be the only sugar exporter (OECD
2006).
South Africa also engaged in a number of bilateral and regional trade agreements. The three most important trade agreements in the southern African region
are the Southern Africa Customs Union, which exhibits the deepest level of
integration, the Southern Africa Development Community, and the South
Africa–Zimbabwe bilateral agreement. Of the extraregional influences, the Lomé
(and then Cotonou) preferences, the Africa Growth and Opportunity Act of the
United States, and South Africa’s separate bilateral agreement with the European
Union are most influential.
Initial progress in rationalizing the tariff regime and lowering nominal and
effective protection was fast. Between 1990 and 1999, the number of tariff lines
was reduced from 12,500 in 200 tariff bands to 7,743 in 47 tariff bands or fewer
than 2,500 in 45 bands if the zero tariffs are ignored. The maximum existing tariff
was also reduced from almost 1,400 percent to 55 percent, and the average
economy-wide tariff fell from 28 percent to 7.1 percent, although a number of tariff peaks remain. For example, tariffs in excess of 25 percent (and up to 45 percent) can be found on various meat products, tobacco, refined sugar, and beverages. Nevertheless, virtually all tariffs in agriculture are now below the bound rates
of the Marrakech Agreement.
The structure of protection also affects agriculture. Tariffs on primary agriculture and other primary products are relatively low compared with tariffs on
processed foods and other manufacturing. This tariff escalation, which is a typical
aspect of trade policy in many countries, creates more dispersion in effective rates
of protection than in the nominal rates for each product.
State support to agriculture
State spending on the farm sector, measured as the budgeted amounts for the
national Department of Agriculture plus the agricultural budgets of the nine
provinces, amounted to R2.8 billion in 1998. In real terms, this was 46 percent of
the budget that the national former homeland agriculture departments had
10 years earlier, in 1988. The decline in state spending is also illustrated by the
rapid decline of government funding of agricultural research. Baseline funding
for agricultural research provided by government through the parliamentary
grant system dropped from a high of R337 million in 1997 to R 262 million in
2001—equivalent to only 55 percent in real terms of the parliamentary grant it
received nine years earlier, in 1992.
162
Distortions to Agricultural Incentives in Africa
Direct and Indirect Distortions Facing
Producers and Consumers
This section describes the evolution of direct distortions faced by producers and
consumers in South Africa since the mid-1950s. The main focus of this study’s
methodology (see appendix A and Anderson et al. 2008) is on governmentimposed distortions that create a gap between domestic prices and what they
would be under free market conditions. Because the characteristics of agricultural
development cannot be understood from a sectoral view alone, the project’s
methodology not only estimates the effects of direct agricultural policy measures
(including distortions in the foreign exchange market), it also generates estimates
of distortions in nonagricultural sectors for comparative evaluation.
More specifically, this study computes a nominal rate of assistance (NRA) for
farmers, including an adjustment for direct interventions on inputs. It also
generates an NRA for nonagricultural tradables, for comparison with that for
agricultural tradables through the calculation of a relative rate of assistance
(RRA).
Distortion estimates are calculated for approximately 80 percent of field crops
and animal products (excluding fresh milk and eggs) and 65 percent of horticultural products (excluding vegetables). Distortion estimates are also calculated for
related lightly processed products (wheat and maize flour, refined sugar, and sunflower oil).6
Some caution is required in interpreting the results presented below. Our
distortion estimates are very volatile, reflecting volatile exchange rates and
imperfect pass-through to domestic prices. Further, identifying appropriate
international prices and transport and marketing margins proved difficult. For
example, at times we find sudden switches from positive to negative nominal
rates of assistance on import-competing products, without a concomitant
change in agricultural policy.7 While such switches could be affected by adjustments to margins, the quality coefficient, or international reference prices, we
have chosen not to do so, because these adjustments might induce further ad hoc
misrepresentations to the existing data. In addition, not all data series were
available from 1955, and a consistent database could be constructed only from
1965.
The analytical narrative of the changes in distortions presented below should
be read in the context of the main policy shifters presented in the earlier sections
of the chapter. As a reminder, the major structural changes were initiated sequentially, first by the initial voting power of white farmers, then by the impact of the
sanctions era (especially on exports), then by the effect of democratization, and
most recently by the impact of multilateral trade liberalization.
163
South Africa
Nominal rates of assistance to agriculture
The estimates of the total NRA for farmers include the direct transfers that are
summarized in Kirsten, Edwards, and Vink (2007, appendix table 2).8 All these
support programs were suspended more or less at the time of the democratic
transition in 1994–95. The extent of direct subsidization to commercial farmers
was at its height during the 1970s, 1980s, and early 1990s. On average, estimates of
the NRA in agriculture reflect a change in policy from one that was antitrade in
the 1970s and 1980s to more-liberal markets in the 1990s, following reductions in
both import protection and export taxation. The five-year average NRA for primary agriculture rose to a peak of 31 percent between 1980 and 1984, but then fell
to less than 10 percent in the 1990s and remained close to zero after that. This is
consistent with the abolition of the control boards and trade liberalization under
the Marrakech Agreement on Agriculture.
There is substantial variation within these five-year averages. As shown in the
annual data presented in figure 5.1, the average NRA for agriculture moved from
Figure 5.1. NRAs for Exportable, Import-Competing, and All
Covered Farm Products, South Africa, 1961–2005
120
100
80
percent
60
40
20
0
20
40
03
00
20
97
20
94
19
91
19
88
19
85
19
82
19
79
19
76
19
73
19
70
19
67
19
64
19
19
19
61
60
year
import-competing products
exportables
total
Source: Data compiled by the authors.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
164
Distortions to Agricultural Incentives in Africa
slightly negative to slightly positive in the period 2000–04. The rise reflects to a
large extent a relatively slow pass-through of currency shocks to producer prices
during this period. The post-2000 period in South Africa is characterized by a
substantial and rapid depreciation of the rand, from R6.9 per U.S. dollar in 2000
to R10 per U.S. dollar in 2002, and a subsequent appreciation to R6.5 per U.S. dollar in 2004. Domestic prices of some agricultural products, particularly processed
products such as bread and maize flour, appear to be sticky downward during
periods of declining agricultural input prices (Cutts and Kirsten 2006), resulting
in relatively large increases in measured NRA.
Some variations in the trend level of distortions are also evident across
importable and exportable products. With quantitative import controls in place
for most of the period between 1960 and 1994, the positive NRAs on importables
shown in figure 5.1 are not unexpected. These drop from an average of 10–21 percent in the 1980s to close to zero percent in the period 1995–2005, reflecting the
demise of the control boards and the liberalization phase as South Africa complied with the requirements of the Marrakech Agreement on Agriculture. In all
cases, except for poultry, the average NRA in the period 2000–04 was lower than
the average during the 1980s. The trend in NRA is, however, volatile during the
1990s and early 2000s, reflecting an imperfect pass-through of the exchange rate
to domestic prices as well as changes in the composition of exportables and
importable products.9
Sugar products (sugarcane and refined sugar) have NRA values in excess of
40 percent for many periods, caused by high tariff protection as well as a pricing
mechanism enabling import parity pricing despite sugar’s being an export product. More generally, NRAs are volatile over time, especially during the 1970s and
1980s when the government attempted to smooth domestic farmgate prices. With
smoothed domestic prices, international price and exchange rate volatility leads to
volatility in the distortion estimates. The dispersion of NRAs among covered
products has, however, declined since the early 1980s, consistent with the shift to a
more market-oriented agricultural policy (see row near the bottom of table 5.1).
The picture for exportables could be confusing, given the high levels of average
support of over 35 percent in the 1980s and 1990s. In this regard, it is important to
recall the dominance of yellow maize and fresh fruit in South Africa’s export portfolio up to 1995. After 1995, as deregulation and liberalization measures were
introduced, the export portfolio shifted, and all measures to support exports and
export losses were abolished. The peak of the NRA series for exportables in
1985–89 can be explained by the export of large quantities of maize at a huge loss.
Much of the loss can be attributed to the decline in the world price (a 33 percent
decline from 1985 to 1987) but a rise in the domestic price (44 percent from 1985
to 1987).
Table 5.1. NRAs for Covered Farm Products, South Africa, 1961–2005
(percent)
Product indicator
a
Exportables
Sugar
Apple
Orange
Grape
Import-competing productsa
Beef
Sheep meat
Poultry
Nontradablesa
Apple
Orange
Grape
Mixed trade statusa,b
Wheat
Maize (yellow)
Maize (white)
Sunflower
Total of covered productsa
Dispersion of covered productsc
Percent coverage (at undistorted
prices)
1961–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–05
3.3
32.5
6.1
7.3
20.6
4.9
7.3
19.5
12.9
0.0
0.0
0.0
0.0
9.6
43.3
4.1
17.9
20.6
10.5
16.4
13.6
12.9
0.0
0.0
0.0
0.0
9.4
15.3
2.3
40.3
2.8
6.4
4.2
40.1
15.7
0.0
0.0
0.0
0.0
3.7
3.4
10.6
28.3
0.2
9.3
34.6
39.0
23.8
0.9
0.6
1.0
0.6
38.2
49.5
17.3
15.5
33.1
28.3
52.2
28.3
18.4
3.1
2.8
3.5
2.8
48.5
39.0
12.9
18.2
23.6
1.5
0.9
32.4
2.9
6.1
6.0
6.2
6.0
35.3
78.9
9.0
4.4
5.5
0.1
12.5
33.1
6.5
1.6
2.3
1.0
2.3
18.1
35.9
7.3
2.9
8.8
3.7
0.6
23.4
12.9
0.0
0.0
0.0
0.0
9.5
44.4
0.7
13.0
6.7
0.6
5.7
4.1
6.0
0.0
0.0
0.0
0.0
2.0
4.9
10.3
18.9
3.3
15.3
11.6
19.0
0.9
17.7
9.5
18.8
25.7
4.6
20.0
6.2
3.2
25.0
61.1
13.7
15.8
7.2
3.9
31.1
67.4
39.2
20.0
19.9
31.1
42.7
65.8
86.3
35.8
7.4
15.5
38.3
13.4
56.0
32.6
6.9
9.3
34.5
0.1
12.7
5.0
6.9
6.8
20.4
7.6
19.7
7.8
2.9
3.6
21.7
69
68
64
66
68
68
69
68
67
Source: Data compiled by the authors.
165
a. Weighted averages, with weights based on the unassisted value of production.
b. Mixed trade status applies to products that are included in exportable or import-competing groups depending upon their trade status in the particular year.
c. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
166
Distortions to Agricultural Incentives in Africa
The large losses recorded in the exports of surplus yellow maize resulted in
large shortfalls in the Maize Board’s stabilization fund. The government bailed out
the Maize Board with a payment of R400 million to cover the shortfall but indicated that the bailout would not be repeated. As a result the Maize Board changed
its price policies to a single-channel pool marketing scheme (from a singlechannel fixed price scheme) to ensure that shortfalls in the stabilization fund did
not recur. Given the size of this sector, this shift in price policy caused a substantial increase in the aggregate NRA for exported agricultural products in this
period. The relatively high NRA for exported products in the early 1990s is largely
attributable to the sugar sector, where stagnant world prices for sugarcane and a
sharp increase in domestic cane prices (the domestic price more than doubled
between 1988 and 1992) led to high rates of assistance. The decline in the five-year
average NRA after 2000 arose from relatively large declines in the NRA for white
maize exports.10
The average NRA for lightly processed food products tends to follow about
the same trend as shown for primary agriculture for most of the study period.
Because we do not include dairy products, which have relatively high tariffs and a
high producer support estimate (OECD 2006), our NRA for lightly processed
products may be biased downward. NRAs for lightly processed products are generally higher in the 1980s and 1990s than the rates for primary agriculture. However, a decline in distortions is evident during the 1990s, although this decline has
been offset by a rise from 2003. The recent increase reflects the appreciation of the
rand (which rapidly lowered border prices), the relatively slow downward adjustment in domestic prices, and the rise in the NRA for refined sugar and processed
meat products. These increases are not associated with changes in the policy environment, hence they are not expected to signify the start of a long-run upward
trend in distortions.
Relative rates of assistance
A comparison of the NRA for agriculture with that for nonagricultural tradable
industries (manufacturing, mining, and highly processed agricultural products) is
presented in figure 5.2. The relative rate of assistance to agriculture (RRA), also
presented there, reflects the incentive to produce agricultural relative to nonagricultural tradable products. Both the RRA and the NRA measures are likely to
underestimate the actual level of distortions in the nonagricultural industries
because collection rates (import duties over merchandise import value) are used
as the distortion measure for manufacturing.11 As is shown in Edwards (2005),
collection rates underestimate protection in manufacturing, but unfortunately
alternative measures are not available over the entire period.
167
South Africa
Figure 5.2. NRAs for Agricultural and Nonagricultural Tradables
and the RRA, South Africa, 1961–2005
50
40
30
percent
20
10
0
⫺10
⫺20
03
00
20
20
97
94
19
91
19
88
19
19
85
82
19
79
19
76
19
73
19
70
19
67
19
64
19
19
19
61
⫺30
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the authors.
Note: The RRA is defined as 100*[(100 ⫹ NRAagt)兾(100 ⫹ NRAnonagt) ⫺ 1], where NRAagt and
NRAnonagt are the percentage NRAs for the tradables parts of the agricultural and nonagricultural
sectors, respectively.
The results suggest that distortions in the agricultural tradable sector were high
relative to nonagricultural tradables during the 1960s, the late 1970s, and the
1980s. During the 1990s, distortions declined in both sectors but fell more rapidly
in agriculture. The net effect was that by 2000–04, the incentive for resource allocation had shifted, albeit slightly, against agriculture and toward nonagricultural
industries.
The results of the RRA estimates in table 5.2 and depicted in figure 5.2 clearly
reflect the impact of deregulation. The trend in RRA follows that of primary agriculture closely, reflecting the relatively low distortions estimated in the nonagricultural sectors. The low levels of distortion in agriculture from the mid-1990s
suggest that economic policies have a relatively neutral impact on aggregate agricultural production on average. However, the significant variation of NRAs within
the farm sector, with some industries being taxed and others being protected, suggests there is still ample scope for efficiency gains within the farm sector were
those differences in NRAs to be phased out.
168
Table 5.2. NRAs in Agriculture Relative to Nonagricultural Industries, South Africa, 1961–2005
(percent)
Indicator
1961–64 1965–69 1970–74 1975–79 1980–84 1985–89
a
NRA, covered products
NRA, noncovered products
NRA, all agricultural productsa
Non-product-specific (NPS) assistance
Total agricultural NRA (including NPS)b
Trade bias indexc
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAd
3.3
1.5
1.7
2.4
4.1
0.01
5.2
2.8
1.5
9.5
0.1
6.4
3.0
9.4
0.00
11.9
3.3
8.4
3.2
2.9
3.3
2.5
0.7
0.14
0.7
2.6
3.1
3.9
1.4
2.1
1.7
3.8
0.03
5.2
2.7
2.4
31.1
4.0
21.2
1.7
22.9
0.07
31.7
5.0
24.4
15.5
2.5
9.0
2.7
11.7
0.40
17.5
5.3
11.3
1990–94
9.3
2.4
7.0
3.8
10.8
0.33
14.6
7.3
7.2
1995–99 2000–05
6.8
0.3
4.4
1.3
5.7
0.13
7.9
4.6
3.7
3.6
0.9
2.0
0.1
2.1
0.11
3.2
2.7
0.1
Source: Data compiled by the authors.
a. NRAs including product-specific input subsidies.
b. NRAs including product-specific input subsidies and non-product-specific (NPS) assistance. Total of assistance to primary factors and intermediate inputs divided to
total value of primary agriculture production at undistorted prices (percent).
c. Trade bias index is TBI ⫽ (1 ⫹ NRAagx兾100)兾(1 ⫹ NRAagm兾100) ⫺ 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and
exportable parts of the agricultural sector.
d. For the definition of the RRA, see figure 5.2 note.
South Africa
169
Comparison with OECD’s estimates
Our estimates differ somewhat from the estimates of distortions in South African
agriculture provided by the Organisation for Economic Co-operation and Development (OECD 2006). Looking first at the average distortion in primary agriculture, we find a decline in our NRA from 1994 to 2003 that is consistent with the
decline found by the OECD in its price support estimates. The turning points are
also largely consistent, except for 2000 and 2003 when our estimates of NRA rose
sharply, while the OECD-derived NRA fell. As argued above, we attribute much of
the difference in 2003 to imperfect pass-through of the appreciation in the currency to domestic wholesale prices. We also estimate a sharper decline in distortions than the OECD did for the period 1994–2002.
The distortion measures differ between the studies for a number of reasons.
First, the studies use different international reference prices for some of our products, in particular beef and maize. These differences are discussed in more detail
in the product-specific analysis that follows. Second, the coverage of the two studies differs. The OECD study includes pork, groundnuts, eggs, and dairy products,
all of which we omit. The OECD study shows dairy products to have relatively
high levels of distortions from 1994 to 1997, which may account for the relatively
larger decline in our estimates of protection during this period but not afterward.
Third, our study, but not the OECD study, splits apples, oranges, and grapes into
traded and nontraded products because these products are not perfectly substitutable and have very different prices. Finally, there are important methodological
differences in how distortions are measured. In the OECD study, when the producer price is lower than the international reference price (at the farmgate), a zero
producer distortion is imposed. In our estimates if the producer price is less than
the international reference price, we estimate a negative NRA. In the case of
imports, this approach reflects the fact that the producer price is less than the
import parity price. The lower domestic price may reflect quality differences, seasonal variation in international and domestic prices, or unmeasured margins and
distortions in the domestic market. Rather than simply imposing a zero NRA, we
have left our estimates as negative in these cases.
Policy Reform Needed to Deal with Existing
Distortions
The results of this analysis confirm the general perception that since the mid1990s South African agriculture on average has been operating in a nondistorted
environment, where the net effect of price-distorting policies on aggregate
resource use in agriculture seems to be neutral. The NRA and RRA results confirm
that the sector on the whole is receiving virtually no policy support.
170
Distortions to Agricultural Incentives in Africa
As stressed by Anderson et al. (2007), however, this conclusion does not mean
that no further policy reforms need to be addressed. There is still considerable dispersion in NRAs within the farm sector, and in particular the sugar industry is still
highly protected (as are the dairy and pig meat industries, according to OECD
2006). High NRAs are also found in the processing sector and reflect relatively
high import tariffs on processed products and a potential lack of competition in
the processing and retail sectors. It appears, for example, that the exchange rate
appreciation of 2002 was only imperfectly passed through to domestic prices of
processed agricultural products, a situation that led to significant increases in the
NRA and the consumer tax equivalent (CTE) for processed products. The implication is that the policy reforms that have concentrated on primary agriculture
may not have adequately filtered through to consumers. This is also shown in the
high CTE relative to the NRA in primary agriculture. These conclusions are
indicative and not conclusive, because the current study does not cover the full
range of processed products. Nevertheless, the results suggest that the policy
reform agenda should shift to the processing and retail sector.
For primary agriculture, the issue is to identify the policies—usually outside
the ambit of the agricultural portfolio, such as labor legislation, land taxes, water
tariffs, electricity rates, and road and fuel taxes—that reduce incentives for agricultural production. When the general deterioration of infrastructure, inefficiencies in government service delivery, poor facilitation in trade-related matters, and
generally high costs of business operations are added, it is clear that South African
agriculture faces rather difficult prospects.
Conclusions
South African agriculture has been subjected to major reform over the past
25 years: from internal market deregulation (from the 1980s within the thenexisting institutional framework), to liberalization of trade (after the Uruguay
Round Agreement on Agriculture in 1994), and then to further fast-tracking of
deregulation under the new Marketing of Agricultural Products Act in 1997
(resulting in the abolition of the elaborate structure of commodity control
boards). These events coincided with the last decade of the apartheid regime (the
1980s), the lengthy transition to democracy (1990 to 1994), and the first years
under the new democratic constitution, respectively.
The first phase of internal market deregulation resulted from perceptions about
the high fiscal burden of controlled agricultural marketing and about the efficiency
costs of overregulation. Nevertheless, the institutions and mechanisms of control
were kept in place. Trade liberalization, on the other hand, resulted directly from
the new government’s drive to create conditions of macroeconomic stability in the
South Africa
171
country: the impact on agriculture was, therefore, a side effect of a larger policy
objective. The comprehensive deregulation after 1996 reflects the urge to complete
the process of deregulation, as well as the declining lobbying power of the commercial farming sector. In the process, however, the mechanisms through which
small and emerging farmers can be supported have disappeared, even though there
is increasing pressure on the government to provide such support.
In the light of the policy imperative for successful black economic empowerment and land reform, an important case can be made for the reintroduction of
some of the programs implemented by the apartheid government in the 1950s
and 1960s to empower Afrikaner farmers. There is also a powerful imperative not
to repeat the mistakes of the past: overreliance on the state, direct intervention in
markets that creates distortions, and an inability to foresee the high fiscal costs of
intervention. To this end, future policies will have to accommodate a larger role
for the private sector (commercial farmers and agribusiness), will have to be more
market friendly, and will have to account for the country’s obligations under the
World Trade Organization (by using targeted “green box” assistance measures to
support this important political imperative). Examples include an expansion of
the Comprehensive Agricultural Support Program, improved access to financial
services, the revitalization of extension services at the provincial level, and development of irrigation infrastructure. Such support services would need to be targeted at emerging farmers. It is likely that current political economy forces favor
such initiatives, but whether this will hold true in the future is uncertain.
Notes
1. Because this chapter focuses on the commercial farming sector, the focus in the discussion falls
on those policies that affected the sector directly, that is, on those policies that favored white commercial farming. For a more exhaustive discussion of the interplay of policy effects between commercial
and subsistence farming, see Vink and Van Zyl (1998).
2. These sections borrow heavily from Vink (1999).
3. This discussion draws from Vink (1993).
4. This section draws on Vink and Schirmer (2002).
5. For a more detailed discussion on marketing policy, see Kirsten and Van Zyl (1996); Vink and
Kassier (1991); and Vink (1993, 2000a, 2000b). See also the Kassier Committee Report (1992) on the
details of the deregulation proposals.
6. To estimate the average distortion for all lightly processed products, we use the NRAs of products directly calculated in this study to estimate distortions for similar processed products not covered
in this project. The products covered in this manner are as follows: slaughtering and preserved meat
(weighted average NRA of poultry, beef, mutton), vegetable and animal oils (sunflower oil), sugar
products (refined sugar), sugar confectionary (refined sugar), prepared animal feed, grain mill products. and bakery products (weighted average wheat and maize flour). Production values (at distorted
prices) based on input-output tables are used as weights. Distortions in the highly processed beverages
and tobacco products are not accounted for.
7. A domestic subsidy is consistent with negative direct rates of assistance on import competing
products.
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Distortions to Agricultural Incentives in Africa
8. The lack of product-specific distortions in input costs implies that the NRA to farm production
is equal to the NRA to farm output.
9. For example, yellow maize was an importable product with a negative NRA for the period
2002–04, but became an exportable with a high positive NRA in 2005. This raises the average NRA for
importables in 2004.
10. White maize is not widely traded internationally. South Africa is one of the dominant producers of white maize, hence domestic prices are to some extent affected by domestic supply and demand
conditions. The international maize price is based on yellow maize (U.S. No. 2 Yellow, free on board,
Gulf of Mexico) and may not adequately proxy regional price fluctuations of white maize.
11. A zero tariff on services was assumed. Production values (at distorted prices), derived from various input-output tables were used to calculate the weighted average NRA for nonagricultural sectors.
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6
Zambia
Peter Robinson, Jones Govereh,
and Daniel Ndlela*
Zambia is a landlocked country in central Africa with a population of 12 million
people. The country has abundant land resources, favorable soils, relatively good
rainfall and low population density.1 A study of regional integration potential in
southern Africa concluded that Zambia has the natural resources to be a major
food and agricultural producer for the region (African Development Bank 1993),
but this potential has never been realized. One important reason has been the
dominance of copper in the economy: despite providing a livelihood to the majority of the population, agriculture as an export sector has always been subsidiary to
mining.
During the colonial period, agriculture was developed primarily to serve the
mining sector. Development was limited to the areas close to the line of rail
running through the copper belt and the capital city, Lusaka, to Livingstone (near
Victoria Falls on the Zambezi River). After independence, a more widespread
form of development was intended, but squandering of the copper wealth in the
first decade of independence (1964–74), when copper prices were high, was followed by a long period of economic turmoil and decline after the price of copper
collapsed in 1975. A change of government at the end of 1991 resulted in the
interventionist policies of the past being replaced by an orientation toward an
open, more liberalized economy.
Changes in agricultural policies started earlier, and agricultural growth has
been relatively high since the mid-1980s. By early in the 21st century, the share of
agriculture in Zambia’s gross domestic product (GDP) had risen to 20 percent.
* The authors are grateful for helpful comments from workshop participants, including Marianne
Kurzweil and Ernesto Valenzuela. Detailed data and estimates of distortions reported in this chapter
can be found in Robinson, Govereh, and Ndlela (2007).
175
176
Distortions to Agricultural Incentives in Africa
From the viewpoint of diversifying away from dependence on copper, a more significant change was the growth of agricultural exports, from $10 million in 1987
to $222 million in 2004.2 Despite recent progress, however, agriculture is still far
from attaining its full potential as a contributor to the economy and to the wellbeing of the majority of the population whose livelihoods depend directly on
farming.
In the first decade after independence, GDP grew at an annual average of
5.6 percent. From 1975, when the price of copper collapsed, to 1999, average GDP
growth was only 0.6 percent. Since 2000, the growth rate of real GDP has accelerated to 6.2 and 6.3 percent, respectively, in 2006 and 2007 (IMF 2008).
Agricultural GDP growth rates have followed a different pattern from overall
GDP. From 1971 to 1984, the average annual growth of agricultural GDP was
2 percent. Then came two five-year periods of much stronger growth (5.3 percent
in 1985–89 and 7.7 percent in 1995–99), interrupted by the 1990–1994 period,
when average growth was only 2.5 percent, pushed down by a devastating drought
in 1992 (when agricultural GDP declined by one-third) and a severe drought in
1994 (when agricultural GDP declined by one-fifth). Despite these and other less
significant drought episodes, agriculture’s contribution to GDP grew between
1985 and 2000 in real terms and as a share of total GDP (from 15 to 20 percent).
That increased agricultural output came principally from crops other than maize.
The share of maize in the value of production of key crops fell from nearly 80 percent in the early 1980s to barely 50 percent by 2005 (even though the share of
maize in household consumption remained much more stable (see, for example,
Robinson, Govereh, and Ndlela 2007, appendix figures 4 and 5).3
The growth of the agricultural sector is attributable not only to the changes
in agricultural incentives discussed in this chapter. The calculations show that agricultural incentives have been depressed over the entire study period (1955–2005).
Negative assistance to agriculture was particularly evident in the 1970s and 1980s,
but even after the opening up of the economy in the 1990s, agricultural producers
have generally continued to receive prices well below border equivalents. There are
three main reasons for this: the direct influence of agricultural policies, the monopsonistic structure of agricultural markets, and the indirect but significant influence
of macroeconomic mismanagement, which has led to an overvaluation of the
currency for most of the five decades covered by the study.
As is discussed in detail later, currency misalignment was significant from the
mid-1960s to the mid-1990s, accounting for half or more of the magnitude of the
distortions in the 1970s and 1980s. Even after the official exchange and the parallel market rates converged in the late 1990s (thereby eliminating currency overvaluation from the calculated distortion measures using the project’s chosen
methodology), there is still reason to suppose that the kwacha remained overvalued,
Zambia
177
depressing agricultural incentives more than has been estimated using the available data.
While the calculations indicate that farmers were most heavily taxed in the
1970s and 1980s, the common perception among the farming community, especially small-holder farmers, was that these were the glory decades for farming.
Land was even more abundant than it is now, and trading costs were low because
the parastatal agricultural marketing agency, NAMBOARD, maintained a wide
network of depots from which it delivered fertilizer, seed, and other inputs and
purchased the crop at the farmgate, not at the depot. NAMBOARD, with its
deficits met by taxpayers, absorbed the transport costs and did not seek to make a
margin on transactions.
The terms of trade for farmers therefore were perceived to be relatively favorable in the 1970s and 1980s, whereas since then farmers have been of the view that
they have to deal with “unscrupulous” businessmen, many of whom are not
involved in the agricultural sector on a long-term basis. Contrary to what might
have been predicted, private marketing costs may have increased after liberalization, and certainly a much higher level of risk has been passed on to farmers.
Over the five decades covered by the study, changes in agricultural and food
policies have at no stage brought unambiguous improvements in the lot of the
small-scale farmer. The extent to which agriculture and food policies have been
conducive to the achievement of national socioeconomic goals has been the subject of a number of in-depth studies.4 The broad-brush picture is that the failure
to achieve anything like the potential of Zambia’s agricultural sector, coupled with
largely perverse effects of subsidies and other interventions in food markets, have
imposed immense costs on the economy and account to a significant extent for
the widespread persistence of poverty.
This is not to say that some policies and actions did not aim to promote agriculture and to alleviate poverty. However, the pattern of public expenditure
reflected misplaced priorities, focusing on subsidies requiring large recurrent
expenditures and delivering restricted benefits instead of productive investments
with more widespread developmental consequences. Channeling resources into
long-term investments in infrastructure, extension services, and market development would have had a larger payoff. The recurrent expenditures also invariably
exacerbated differentials, further entrenching dualism. Before independence,
almost all benefits went to European farmers, while after 1964, those subsidies and
policies that did benefit producers also disproportionately favored farmers located
close to the rail line, who have better access to inputs, transport, and marketing
services.5
In recent years, rapid decreases in poverty have been measured in some rural
areas resulting from rapid growth in output, but that growth has been very
178
Distortions to Agricultural Incentives in Africa
unevenly distributed.6 The liberalization of the maize market and the emergence
of hammer mills able to compete favorably with industrial mills on price and
nutritional quality have benefited those rural households that are net food purchasers as well as urban households. However, the removal in the early 1990s of
the maize meal subsidies, which had proved unsustainable in the late 1980s, coincided with the loss of employment associated with public sector reform and closure of manufacturing firms that were unable to compete with rapidly liberalized
imports. Urban poverty thus rose rapidly in the early 1990s (McCullogh, Baulch,
and Cherel-Robson 2001).
Agricultural Policy in the Colonial Period
Commercial agriculture was started in the early years of the 20th century to provide food to the copper mines and the capital city. European settler farmers were
settled along the rail line and provided with various forms of assistance to encourage production of maize and other crops to the copper belt and other urban areas.
Small-scale African farmers were deliberately disadvantaged, not least by being
given significantly lower prices for their crops. This dualistic agriculture, which
constitutes a structural distortion in the agricultural sector that persists to this
day, was the result of deliberate policies initiated a century ago.
The settler farmer production system was well established by the 1920s. The
international depression of the 1930s sharply reduced demand for copper. In the
face of falling demand for agricultural goods, European and African farmers suffered extreme hardship during that period (McPherson 2004). In 1936, the government promulgated the Maize Control Ordinance, which resulted in the formation of the Maize Control Board. Its mandate was to stimulate production of
maize while protecting European farmers from competition from African farmers. These objectives were achieved by raising the producer price of maize above
world market levels for sales to the “internal pool,” three-quarters of which was
reserved for European farmers. Additional maize was directed to the “external
pool,” which involved sales at lower export parity prices (Jansen 1991). Urban
consumer prices were set very low, with the control board’s losses being made up
by substantial government subsidies.
World War II raised the demand for copper and hence for maize to such an
extent that imports became necessary. Producer prices for maize for both African
and European farmers were kept below import parity levels. While African farmers consistently received lower prices than European farmers, small-scale African
farmers in remote areas had to contend with even lower net returns than their
counterparts who were based within the Maize Control Board’s restricted area of
operations (eight districts along the rail line).
Zambia
179
After World War II, maize production began to exceed internal demand, and
exports of maize were resumed. This trend continued during the Federal period
(1953–1963), with the Federal Grain Marketing Board keeping producer prices
above export parity levels. A discriminatory element was still evident, however. “Not
all producers were subsidized, nor were they subsidized equally,” wrote one economist; “the African producer price was still considerably less than the European producer price because the government diverted part of the proceeds from sales of
domestic maize to an African farming improvement fund.” (Jansen 1991, p. 278).
Measurement of Agricultural Distortions,
1955–2004
The main focus of the current study’s methodology (see appendix A in this volume and Anderson et al. 2008) is to measure the extent to which governmentimposed distortionary policies create a gap between domestic prices and what
they would be under free markets. The objective is to have simple measures of
policy-induced distortions to agricultural prices that are uniform and comparable
across time periods and between countries. Because the characteristics of agricultural development cannot be understood from a sectoral view alone, the project’s
methodology not only estimates the effects of direct agricultural policy measures
(including distortions in the foreign exchange market), but it also generates estimates of distortions in nonagricultural sectors for comparative evaluation.
More specifically, this study computes a nominal rate of assistance (NRA) for
farmers that includes an adjustment for direct interventions on inputs. It also generates an NRA for nonagricultural tradables, for comparison with that for agricultural tradables through the calculation of a relative rate of assistance (RRA).
The basis of the approach is a comparison between the prices actually received
by producers (or paid by consumers) and the prices that would have prevailed had
there been no policy distortions. This approach reflects the assumption that the
relevant opportunity costs are reflected in the international border prices for the
commodities adjusted for nonpolicy price wedges such as transport costs, marketing margins, and quality differences. Where available, actual import and export
prices are used in preference to the alternative of constructing synthetic border
prices from international reference prices, adjusted for transport and related costs.
Details of the data sources and assumptions made to generate the NRAs are laid
out in the appendix of Robinson, Govereh, and Ndlela (2007).
In interpreting the NRA results presented below, the reader should bear in
mind five points that arise from the way the domestic-to-border calculations have
been made (as well as the limitations stemming from the poor quality of some of
the data).
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Distortions to Agricultural Incentives in Africa
First, the wholesale level has been chosen as the point in the value chain where
the ratios are calculated. Before economic liberalization, the wholesale level was
composed of the state marketing boards, notably NAMBOARD for the crops
covered by this study. The calculated NRA measures thus apply to farmers close
to the depots and would be lower, meaning more negative in almost all years, for
farmers living further away from the depots. After independence, the network of
marketing board depots was extended into the rural areas beyond the rail line to
improve the position of small farmers in remote areas, and panterritorial pricing
was introduced.
Second, from 1961 to 1994, the wholesale prices used in the calculations are the
minimum guaranteed prices to farmers. Those farmers able to market their products locally, or to engage in informal cross-border trade with neighboring countries (notably the Democratic Republic of Congo and Malawi), would have
received higher prices and hence have been subject to higher (less negative) NRAs
than have been calculated. Even in the case of tobacco, which was sold at auction,
the prices available for and used in this study are the floor prices that the government set to protect farmers.
Third, farmers who received inputs from NAMBOARD were required to sell
their crops through official channels, with a “stop order” system ensuring that the
loans due on the inputs were repaid. While this system often may have involved
low selling prices, the inputs themselves were typically subsidized, and the farmers
nonetheless may have tried to enhance their incomes by selling at least part of
their crops at higher prices.
Fourth, farmers able to store their crops until later in the season usually did
much better than farmers who were forced to sell immediately after harvest at the
minimum guaranteed prices. Studies have shown that even small farmers are well
aware of the changing prices over the season and try to delay sales but typically
have to sell a portion of their crops immediately after the harvest at the lowest
prices to raise cash (Coulter et al. 1996; Mundia 1999). Even where monthly producer price data are available, there are no corresponding volume data, and so no
basis to calculate a proper weighted average price for the year. Data from a 2003
survey on the month when the household had the largest sales, however, suggest
that most crops are sold in the early part of the marketing season. Averaging the
prices alone is obviously unsatisfactory when there is a large range of selling prices
over a particular cropping season.7
And fifth, the prices used in the calculations for maize, sorghum, wheat, and
sunflower after 1994 relate to trades conducted through Zambia’s Agricultural
Commodity Exchange. Where possible, these are prices from actual sales, but in
some months data for bid or offer prices are available. Here too there is the problem of annual average prices having to be calculated without weighting by sales
181
Zambia
volumes. For these crops, any apparent improvement in NRAs is partly attributable to the change from a low minimum price reference point to actual market
prices received by farmers. The commodity exchange prices are Lusaka wholesale
prices, which are the highest a farmer can get. All prices outside of Lusaka and the
main copper towns will be lower.
The Patterns of Distortions, 1955–2005
The annual NRA estimates for import-competing products and exportables are
illustrated in figure 6.1, while five-year averages for individual products are shown
in table 6.1.8 On a five-year average basis, the overall NRA results are within 2 to
4 percentage points of those calculated by Jansen (1991), the Zambia case study in
the Krueger, Schiff, and Valdes (1991) project.9
Positive assistance for a decade or so after the Second World War was followed
by a sustained half-century period of negative assistance to farmers. Policies
encouraging import substitution of rice and wheat did result in positive NRAs for
these crops for short periods (1979–84 and 1995–96 for rice; 1981–83, 1994–96,
Figure 6.1. NRAs for Exportable, Import-Competing, and All
Covered Farm Products, Zambia, 1961–2004
20
percent
0
20
40
60
80
03
97
94
91
00
20
20
19
19
85
88
19
19
82
19
19
76
79
19
70
67
73
19
19
19
19
64
19
19
61
100
year
import-competing products
exportables
total
Source: Data compiled by the authors.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
182
Table 6.1. NRAs for Covered Farm Products, Zambia, 1961–2004
(percent)
Product, indicator
Exportablesa,b
Groundnut
Cotton
Tobacco (Virginia)
Tobacco (burley)
Import-competing productsa,b
Rice
Wheat
Nontradables
Millet
Sunflower
Mixed trade statusb
Maize
Sorghum
Soybean
Total of covered productsa
Dispersion of covered productsc
Percent coverage (at undistorted prices)
1961–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
23.4
—
—
9.1
12.0
9.4
—
—
30.3
41.5
31.6
18.4
47.7
21.6
14.6
76.7
46.4
59.4
36.6
30.6
37.1
41.8
52.9
60.0
58.2
68.7
38.9
57.2
50.1
55.0
13.9
28.2
47.7
66.4
37.7
26.9
37.6
23.0
29.8
12.4
77.0
78.2
76.6
77.1
80.0
67.8
50.5
69.3
57.7
77.2
34.9
30.9
23.4
53.7
27.2
60.2
45.9
66.7
27.5
5.2
23.9
27.0
9.5
11.8
52.6
69.2
51.4
29.3
58.1
10.1
23.8
23.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
27.0
—
—
24.3
21.8
78
33.7
15.4
77.6
32.8
32.6
77
41.6
34.4
71.3
42.2
26.8
76
57.1
64.1
39.8
57.3
36.2
75
23.1
57.1
33.4
25.5
35.1
74
67.6
73.7
60.7
68.2
33.8
72
52.4
53.8
54.7
53.4
39.4
71
28.3
50.9
31.0
33.6
35.7
69
29.8
25.0
15.7
34.2
33.2
67
Source: Data compiled by the authors.
Note: — no data are available.
a. Weighted averages, with weights based on the unassisted value of production.
b. Mixed trade status products included in exportable or import-competing groups depending upon their trade status in the particular year.
c. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
Zambia
183
and 2000–04 for wheat; and a few other separate years for both commodities).
Otherwise, occasional positive rates for maize, sorghum, soybeans, cotton, and
tobacco result from coincidental upward movements in domestic prices, currency
devaluation, or reductions in the reference border prices (and vice versa for negative spikes). These coincidental factors are absorbed in the five-year averages presented in table 6.1, where the only positive rates are for rice (1980–84 and
1995–99) and wheat (1980–84, 1995–99, and 2000–04).
The patterns of assistance or taxation are the result of the interplay of a number of different influences. The direct influences arise from agricultural sector
policies, which are discussed in detail in the next two sections. In explaining the
changes in NRAs, it is not just the stated policies that matter, but also the way they
are implemented as reflected in the institutional structures, price regulations, and
financial flows to the agricultural sector (such as subsidies and public sector
investments). Particularly in the period since liberalization, the impact of these
policies has been tempered by the nature and structure of agricultural markets.
These structural issues are important in explaining the pattern of assistance to
Zambian farmers.
Another key part of the explanation for the NRA pattern lies in the indirect
effects of the macroeconomic and trade policies pursued. Detailed aspects of these
are discussed below, but it is relevant at the outset to stress that the main macroeconomic influence occurs through overvaluation of the exchange rate. Using the
crude measure of the parallel market premium, the Zambian kwacha appears
overvalued from the early 1960s to the end of the 1990s. In years where the parallel rate is way out of line with the official rate (such as 1977 or 1988), the world
parity price in kwacha (which appears in the denominator of the NRA formula) is
much higher than the value calculated with the official exchange rate. The NRA
values for years such as 1977 and 1988 are thus suddenly much more negative.
This results in a mirror-image downward swing in the NRA curves, reflecting the
upward swing in the exchange rate premium. Except for import-competing products in the 1980–84 period, the growing exchange rate overvaluation during the
1970s and 1980s amplifies what would be (at the official exchange rate) far more
modest levels of negative assistance. The progressive reduction in overvaluation
since the 1980s brings the calculated NRAs increasingly closer to what they would
be had official exchange rates been used in the calculation.
For the entire period of this study, the overall patterns that emerge are of
increasingly negative assistance to agriculture during the periods of dirigiste control over the economy, which were also years of significant overvaluation of the
exchange rate. Economic liberalization is the hallmark of the Third Republic,
which started in 1992. During the 1990s, macroeconomic stability was progressively restored and many of the former controls over the economy, including those
184
Distortions to Agricultural Incentives in Africa
pertaining to agriculture, were unwound. As is clear from figure 6.1, these measures are less negative than in the 1980s, but they did not lead to positive NRAs for
agriculture, in part because the government in fact adopted a half-hearted
approach to liberalizing agricultural markets.
Fertilizer and maize markets provide two key examples of areas where the government did not completely give up control and where full liberalization has yet
to occur. However, consumers did benefit from increased competition in the more
liberalized market environment, which resulted in lower processing and marketing margins. Data from the Ministry of Agriculture show that real maize meal
prices had a downward trend, while real maize grain prices remained virtually stable between 1990 and 2005.
NRAs by commodity
Maize constitutes on average two-thirds of the total value of the commodities
being studied, and hence the maize NRA to a large degree determines the average
NRA for agriculture as a whole. The NRA for maize suggests producer prices have
been between one-fifth and two-thirds below what they would have been in an
open-economy environment, peaking at 68 percent in 1985–89. The other
traded cereal crops (sorghum, wheat, and rice) generally have very large negative
five-year average NRAs, but in some periods they reverse to low negative or even
positive values. In the most recent 10 years, the government had a 15 percent
import duty on wheat, to compensate those farmers who had invested in wheat
production but faced high costs of fuel and electricity compared with competitor
wheat producers.
Among the traded oilseeds, the NRA for groundnuts is severely and consistently negative, with soybeans also always negative but less severely so between
1995 and 2004. The NRAs for the export cash crops, cotton and tobacco, tend also
to be large and negative up to 1990, the worst period being 1985–89. Even in the
most recent period, 2000–04, tobacco NRAs are still very negative (burley
58 percent, Virginia 29 percent), as is the NRA for cotton (51 percent).
Assistance patterns for tradable products and for
agriculture as a whole
The patterns for import-competing products and exportables both follow the
overall pattern of exchange rate misalignment. As a result, the largest negative
NRA values for both were in 1985–89, followed by 1975–79, with a continuous
improvement for import-competing products since 1990. For any particular commodity, a change in status from import-competing to exportable would tend to
Zambia
185
make its NRA less negative because the cost, insurance, freight (cif) import price
is almost always higher than the free on board (fob) export price. All else being
equal, the average NRA for import-competing products might be expected to be
more negative than the average NRA for exportables, but that is not the case for
Zambia. The reason is that in the weighted average across all import-competing
products there is a preponderance of import-competing foodstuffs that (through
relatively higher producer prices) are taxed less than exportable cash crops. By
2000–04, the NRA for import-competing products improved to 10 percent,
while the exportables’ NRA became even more negative than in the 1995–99
period (53 percent, compared with 46 percent).
The third-to-last row of table 6.1 gives the weighted average rates of assistance
for all of the commodities covered in this study. This is the same as the first row in
table 6.2. When the guesstimated NRAs for noncovered products (which account
for between one-sixth and one-quarter of the gross value of farm production) and
for non-product-specific agricultural subsidies are included, the sector’s negative
NRA is considerably reduced. The tradables part of agriculture faces more discrimination than the nontradables part, however. By contrast, the tradables part
of nonagricultural industries has a positive weighted average NRA, with trade
taxes and distortions to the exchange rate assisting import-competing producers
more than they are hurting exporters (mainly, the mining sector). Thus the relative rate of assistance is more negative than the NRA for agricultural tradables
(table 6.2 and figure 6.2 ).10
The growth in agriculture’s contribution to GDP and exports took off with a
lag following the changing levels of disincentives to agriculture, that is, not until
the early 1990s. The most significant development was the growth of floriculture
and horticulture, whose exports contributed significantly to the impressive rise in
overall agricultural exports, from under $20 million a year in the late 1980s to
over $150 million in the new millennium. That represents an annual growth rate
of more than 30 percent. But note that floriculture and horticulture—whose
NRAs have not been estimated—enjoyed special assistance through duty drawback arrangements on imported equipment and a zero rating value added tax
(VAT) status (claiming VAT on inputs without being charged VAT on output sold
in the domestic market). This rapid export growth occurred alongside negative
NRAs for the export crops covered in this study. Had these new industries been
included, the estimated NRA for agriculture as a whole would have been somewhat less negative.
Had the exchange rate not been distorted, the agricultural NRAs and RRA
would have been only slightly less negative (bottom rows of table 6.2), suggesting
that exchange rate distortions are not the major reason for the antiagricultural
and antitrade bias.
186
Table 6.2. NRAs in Agriculture Relative to Nonagricultural Industries, Zambia, 1961–2004
(percent)
Indicator
NRAs, covered products
NRAs, noncovered products
NRAs, all agricultural products
Non-product-specific (NPS) assistance
Total agricultural NRAa
Trade bias indexb
NRAs, all agricultural tradables
NRAs, all nonagricultural tradables
RRAc
Memo item, ignoring exchange
rate distortions:
NRA, all agricultural products
Trade bias indexb
RRAc
1961–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
24.3
4.0
19.7
—
19.7
0.21
22.6
16.1
33.4
32.8
15.2
28.0
5.8
22.6
0.10
33.1
20.0
43.6
42.2
23.9
36.8
22.4
15.8
0.06
44.3
27.6
56.2
57.3
34.7
49.5
13.7
37.3
0.08
57.9
34.5
68.5
25.5
16.5
22.6
20.9
2.7
0.30
27.7
24.1
41.5
68.2
51.6
60.8
2.7
58.9
0.28
70.0
24.2
75.4
53.4
36.3
46.5
18.1
30.8
0.08
55.3
21.2
62.7
33.6
26.5
31.3
2.7
28.6
0.00
36.7
13.5
44.2
34.2
23.0
31.3
2.8
28.5
0.41
36.5
6.4
40.3
19.1
0.16
30.8
18.3
0.45
36.3
11.3
0.63
48.4
17.9
1.17
49.0
9.2
0.10
41.8
63.1
1.63
74.2
31.4
0.64
61.6
25.3
0.12
38.9
24.8
0.41
36.1
Source: Data compiled by the authors.
Note: — no data are available.
a. NRAs include product-specific input subsidies and non-product-specific (NPS) assistance. Total of assistance to primary factors and intermediate inputs divided to
total value of primary agriculture production at undistorted prices (percent).
b. Trade bias index is TBI (1 NRAagx兾100)兾(1 NRAagm兾100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and
exportable parts of the agricultural sector.
c. The RRA is defined as 100*[(100 NRAagt )兾(100 NRAnonagt ) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the
agricultural and nonagricultural sectors, respectively.
187
Zambia
Figure 6.2. NRAs for Agricultural and Nonagricultural
Tradables and the RRA, Zambia, 1961–2004
60
40
20
percent
0
20
40
60
80
03
00
20
97
20
94
19
91
19
19
88
85
19
82
19
79
19
76
19
19
73
70
19
67
19
64
19
19
19
61
100
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the authors.
Note: For the definition of the RRA, see table 6.2, note c.
Consumer tax equivalent patterns
In this study, the NRAs and consumer tax equivalents (CTEs) are calculated at the
wholesale level. Consequently, it is only when farmers or consumers receive direct
subsidies on product prices that the calculated primary producer NRA will differ
from the CTE. In the case of Zambia, there are no such subsidies (only farm input
subsidies) and thus the primary product CTE is always numerically identical to
the corresponding NRA. The negative assistance to the primary producer is mirrored by an implicit subsidy of the same magnitude for the consumer. In a country where the power base of the ruling party is drawn from the urban areas, it is
not surprising that agricultural pricing policies should have produced this result.
The only processed product for which the data exist to do a separate CTE calculation at the retail level is maize meal. The most common grade for popular
consumption is roller meal, so results presented in figure 6.3 refer to that as the
benchmark form of maize meal. The basic data used for the CTE maize calculation are the wholesale producer price and the cif import price of maize. For the
roller meal CTE calculation, the numerator is the maize price plus processing and
188
Distortions to Agricultural Incentives in Africa
Figure 6.3. Maize and Maize Meal CTEs and Consumer Subsidy
Payment, Zambia, 1955–2004
consumer subsidy or CTE as a percent of price
0.8
0.6
0.4
0.2
0
0.2
0.4
0.6
0.8
1
1.2
1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
year
maize meal consumer subsidy
CTE for maize
CTE for maize meal
Source: Data compiled by the authors. Maize meal prices are for roller meal.
wholesale margins, while the denominator is the cif price of maize meal. The subsidy is calculated as the theoretical price of roller meal (the wholesale price of
maize adjusted for the extraction rate, processing, wholesale, and retail margins)
compared with the actual retail price given by Central Statistics Office data for
roller meal. The wholesale and retail margins are assumed to be fixed at 12 percent
and 8 percent, respectively, while the processing margin is assumed to be 24 percent before liberalization and to adjust from 1993, so the retail price reflects the
fact that consumer subsidies were no longer provided by government.
Given these assumptions, figure 6.3 suggests that in the 1970s and 1980s the CTE
for maize meal was even more favorable to consumers than the CTE for maize grain.
From 1991, however, the results suggest that the implicit consumer subsidy for
maize meal has been less than that available for maize grain, with the graph moving
into the positive range (an implicit consumer tax) in 1994, 1998, and 2003. The consumer subsidy graph shows how hazardous calculations of this sort are. This estimation approach produces plausible results in most years (cumulated margins
Zambia
189
dropping from 50 percent to 33 percent as a result of liberalization) but also some
aberrant years (1989 and 1992). There are also implausible processing margins (in
1996, 1999, and 2001) that occurred because these calculations are made for the
industrial millers, whereas many consumers switched to buying maize grain and
having it milled by small hammer mills at a more modest cost (see below).
Policies behind the Distortions: 1964–1991
At independence in 1964, there were high hopes for Zambia. Per capita incomes
then averaged three times those in the Republic of Korea, copper prices were high,
and the new government was committed to using copper wealth to raise education and living standards and diversify the economy. By the end of the Second
Republic in 1991, the economy was in crisis, with zero growth in GDP, savings and
investment at low levels (8.4 percent and 11 percent of GDP, respectively), shortages of basic goods, inflation in triple digits, the budget deficit (excluding grants)
at 16.2 percent of GDP, and debt service the equivalent of 66 percent of export
revenues (Robinson 2004). Poverty was widespread, with 58 percent of the population deemed to be living in extreme poverty.
Background
After independence in 1964, it was expected that policies would be put in place
that would significantly enhance the position of African farmers. President
Kenneth Kaunda responded to calls to boost small-scale agriculture by announcing a “fair price” policy for agriculture. But as McPherson (2004, p. 306) put it,
“Though originally intended to raise the prices received by African producers, the
initiative quickly became a ‘low price’ policy designed to reduce the cost of staple
food for urban workers.” This pro-urban bias, reflecting the base of political support for the ruling party, set the tone for pricing in the Kaunda era, which lasted
until the end of 1991. However, to keep farmers from becoming politically agitated, low producer prices were offset somewhat by government provision of subsidized farm inputs.
In the first year of independence, the world price of copper rose by 50 percent,
and copper prices remained high throughout the so-called First Republic
(1964–73). Despite the problems associated with the imposition of international
sanctions on the illegal regime in Rhodesia after 1965, economic conditions in
independent Zambia were buoyant initially. Output of agricultural commodities
increased, though rather modestly. The five-year moving average of total cereal
production increased from 740,000 metric tons in 1964 to 850,000 metric tons in
1969 and over 1 million metric tons by 1974, according to data from the Food and
190
Distortions to Agricultural Incentives in Africa
Agriculture Organization. This increase is equivalent to annual growth of only
3.1 percent, whereas the average annual population growth rate over the decade
was 3.4 percent.
One of the main strategies the government adopted in pursuit of its agenda of
diversifying away from copper and creating greater social equity was to take
greater direct control over the economy. After 1968, a vigorous program of
nationalization was launched, through which the government acquired a majority
stake in many large private enterprises and also created a number of new parastatals. This nationalization shifted the locus of economic decision making decisively to the public sector, while at the same time the government became progressively more interventionist in its approach to economic policy making. In the
agricultural sector, the setting of producer and consumer prices for agricultural
commodities became the norm, while trade policy came to be characterized by
import licensing, foreign exchange allocation, and quantitative import controls.
The start of the Second Republic in 1973 was marked by the formal introduction of a one-party state. In the aftermath of the 1973 global oil crisis, commodity markets collapsed. The copper price fell sharply (by 40 percent in 1975), while
at the same time the price of fuel and other key imports rose sharply. Copper
prices in real terms have never returned to the high levels of the first decade of
Zambia’s independence (although they are coming close in the 2007–08 boom
period). In the mid-1970s, the government assumed that low copper prices
would be a temporary phenomenon and did not therefore seek to make fundamental changes in the patterns of consumption and production in the economy.
In the short term, however, levels of imports had to be sharply reduced, GDP
growth turned negative, government revenues fell sharply, and inflation and
domestic debt rose. Moreover, Zambia began to accumulate significant levels of
external debt which henceforth became a major restraining factor in macroeconomic policy making.
The introduction of the one-party state in 1973 heralded an intensification of
the dirigiste tendencies in economic management that had been evident in the
early years of independence. As macroeconomic and balance of payments problems grew, the government increasingly turned to international donors for assistance. The government’s orientation ran counter to donor policy prescriptions,
particularly those of the World Bank and the International Monetary Fund. This
resulted in a succession of half-hearted reform attempts in the 1980s, interspersed
by populist measures intended to head off growing political discontent.
The clearest example of such populism is provided by the heavy commitment
to consumer subsidies of maize meal. The budgetary requirements for these subsidies grew to proportions that by the mid-1980s destabilized the national budget.
When reforms in December 1986 doubled the price of breakfast meal, which is a
Zambia
191
slightly higher grade of maize than roller meal, there were riots in the copper
region and the increases were hastily withdrawn. In May 1987, President Kaunda
announced a break with the Bretton Woods institutions and the introduction of a
homegrown recovery program, but this too did not last. By 1989, the country had
negotiated a policy framework paper with the World Bank and the International
Monetary Fund. Devaluation, removal of price controls, and institutional reform
followed.
In the food sector, these economic reforms involved a tripling of the maize
price, offset by the introduction of a coupon system to provide a targeted subsidy,
and the scrapping of the parastatal marketing organization, NAMBOARD. The
increased prices led to more maize meal riots in June 1990, when 19 people died,
and also to a coup attempt on June 30, 1990. An opposition party emerged soon
after, and it was legalized in time to contest the October 1991 elections. The maize
meal subsidy was increased again before the election, but that did not prevent the
defeat of President Kaunda’s party.
Agricultural and food policies
At independence in 1964, the new government’s agriculture and food policies
were shaped by concerns about equity and food self-sufficiency. Equity required
increasing the involvement of small-scale farmers in the market economy, while
the food concerns revolved around feeding the rapidly growing urban population.
These objectives had immediate built-in tensions for food prices, which were
always biased toward urban workers who constituted the bedrock of the ruling
party’s power base. The agricultural measures the government adopted to offset
low producer prices included a broader range of agricultural services provided at
subsidized rates, such as credit, fertilizer, tractor plowing, and marketing. These
services were extended throughout the country, most visibly through expanding
the network of the Agricultural Rural Marketing Board depots, which did have
some positive equity impacts, increasing the participation of households in
remote areas in producing for the market.
Uniform panterritorial pricing, introduced in the 1974–75 crop season, gave
further assistance to farmers in surplus-producing provinces away from the rail
line who had hitherto had to meet the high cost of transport to urban markets.
But the uniform pricing penalized farmers in maize-deficit areas where prices
would otherwise have been higher. Under the old system, farmers in these areas
received prices above the national average to cover the cost of transport from elsewhere, but they now had to sell at the same panterritorial price as the source
regions. Uniform pricing was billed as being synonymous with equity, but analysis
of the consequences indicates that the opposite was the case. “Uniform pricing
192
Distortions to Agricultural Incentives in Africa
depressed the price received by the poorest segment of the population, i.e., farmers in the distant (non border) deficit areas and has inflated the price received by
better-off (and more politically vocal) farmers in surplus regions, particularly the
Eastern province,” Jansen and Rukovo (1992) wrote. Panterritorial and panseasonal pricing encouraged the production of maize in areas not suited to the crop
and also greatly increased the transport costs that had to be covered by subsidies
to NAMBOARD, which had taken over the marketing depot network.11 Combined with consumer subsidies on maize meal, fertilizer subsidies, and smaller
subsidies for other crops, the fiscal requirements of agricultural subsidies grew to
be a significant drain on national resources, reaching a peak of 6.7 percent of GDP
in 1980 (McPherson 2004).
In addition to maize, minimum producer prices were set for the other major
crops, and it is these prices that have been used for the NRA calculations. Jansen
(1991) notes that these prices were based on costs of production and were always
well below border-equivalent levels, with partially compensating direct assistance
being given to farmers in the form of subsidies on inputs and transport. The producer prices were adjusted to influence crop choice through maize—the prices of
other crops were held down when the government decided greater maize production was necessary, and vice versa. Parastatal procurement agencies had a mix of
legal and de facto monopsonistic control over primary agricultural markets.
These agencies were either inefficient (in the case of groundnuts, for example) or
enjoyed high rents from the low farmgate prices (in the case of cotton).12 Tobacco
was marketed through an auction, but the government provided a floor price to
encourage farmers to produce tobacco without the risk of prices falling below
costs of production in poor years.
Macroeconomic and exchange rate policy
As these agriculture and food policies were becoming entrenched, poor macroeconomic policies following the crisis induced by the dramatic fall in the world
copper price in 1975 plunged the country into persistent internal and external
imbalance. These macroeconomic problems were induced when Zambia failed to
adjust its exchange rate in the face of high inflation; the consequence was falling
export receipts. More and more reliance was then placed on quantitative restrictions and tariffs to restrain imports, and increasing levels of foreign borrowing
were needed to sustain even that restricted level of imports. When new lending
from international private banks dried up, the government was forced to
approach the Bretton Woods institutions for assistance.
Over the next decade, economic reform promises were made but were never
fully supported politically, and the result was a series of failed reform programs
Zambia
193
funded by short-term surges of foreign aid. The first of these was an Extended
Fund Facility granted by the International Monetary Fund in 1981 and discontinued in 1982. The Memorandum of Development Objectives and Policies that
Zambia and the World Bank signed in early 1983 included increased prices for
maize meal and fertilizer and flexibility in setting other prices (subject to ex post
review) as well as significant macroeconomic and trade policy reforms, but the
Bank suspended disbursements in October 1983 when the government fell into
arrears after unilaterally suspending debt payments.
After the 1983 elections, President Kaunda promulgated an intensified version
of the economic reforms, but the policy improvements had to contend with a further slide in copper prices, drought, and a dip in aid. Popular dissatisfaction with
economic conditions led to student riots in February 1984 and industrial unrest
in the first half of 1985. In response, financial policies were relaxed, thereby aggravating Zambia’s fiscal and external debt problems and leading to a fresh appraisal
of the government’s policy stance.
In October 1985, a comprehensive structural adjustment program was launched.
This included a foreign currency auction that resulted in rapid depreciation of the
kwacha. Food prices rose dramatically as a result of the depreciation and reduction
in subsidies, leading to the food riots in December 1986 that were mentioned earlier.
This incident led to policy reversals, including the suspension of the foreign
exchange auction in early 1987 and full-scale repudiation of the structural adjustment program on May Day 1987, when a homegrown program was announced. By
October 1987, however, the government had reopened discussions with the World
Bank and there was a gradual return to structural adjustment measures over the
period 1988–1990. Exchange rate policy remained central: the kwacha was devalued
and a new foreign exchange auction system was introduced (intended more to
allocate foreign currency than to set the rate). Exporter retention schemes and
(from 1989) a formal multiple exchange rate system became operational.13
In 1989, all consumer prices except maize were decontrolled and NAMBOARD
was abolished. The fiscal burden of maize subsidies was reduced by tripling the
maize price and introducing a coupon system to allow for targeting of the remaining maize subsidy. The country was still cut off from assistance from the multilateral institutions, but the positive measures taken regarding exchange rates and
subsidy reductions paved the way for a Policy Framework Paper to be agreed on in
1989 and relations to be restored in early 1990. In the run-up to the elections,
however, the Kaunda government abandoned adjustment one last time. Expansionary fiscal measures included increases in wages and in maize and other subsidies. President Kaunda’s United Independence Party was nonetheless defeated in
the October 1991 elections, ushering in a fresh epoch under a new party, the
Movement for Multiparty Democracy.
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Distortions to Agricultural Incentives in Africa
Policies behind the Distortions:
The Period since 1992
The new government of President Frederick Chiluba committed itself to the program that its predecessor had negotiated and then abandoned. Donors pledged
extensive support, including substantial food aid to counter the effects of the
1991–92 drought, which was of a once-in-a-century severity. The government
acted swiftly on several economic policy fronts, particularly the exchange rate and
trade liberalization. The foreign exchange auction was broadened, and bureaux de
change, introduced in September 1992, led to the unification of the exchange rate
by December 1992. Export bans (except on ivory, oil, maize, and fertilizers) were
removed and all imports, bar a small negative list, were liberalized by September
1992. Import tariff rates were reduced to six levels in the 1991 budget, with the
new minimum and maximum rates being set at 15 percent and 50 percent respectively, and the number of duty-exempt goods was reduced. These changes resulted
in a dramatic opening up of the economy to imports, not least from neighboring
countries, which enjoyed 70 percent preferences (rising to 100 percent in later
years) under the Common Market for Eastern and Southern Africa and bilateral
agreements.
These steps greatly improved the availability of basic goods but also resulted in
large-scale closures of businesses and loss of jobs, particularly in the manufacturing sector. The social impact of the loss of employment could have been mitigated
by adopting a more gradual approach. The pace and sequencing of trade and
other economic reforms have also been criticized (for example, by Botchwey et al.
1998) as being a major cause of the persistent instability of the macroeconomy
throughout the 1990s. The period was characterized by high inflation, a volatile
and generally overvalued exchange rate, high real interest rates, and a banking
system oriented to financing the government deficit rather than to servicing the
credit needs of productive enterprises. The long delay in the privatization of the
copper mines was extremely costly both within the copper sector itself and in
undermining the progrowth orientation the Chiluba government supposedly
supported.
Overall, the economic environment in the 1990s was not conducive to fulfilling
one of the basic intentions of the new government, namely, that private investment would spearhead economic growth. The fact that nontraditional exports,
including agricultural exports, grew significantly over the period, is claimed as
contrary evidence. A more pertinent question arises from the counterfactual—by
how much more would the nontraditional exports have grown if the environment
had been truly conducive to private sector growth?14
The pattern of growth of agricultural exports provides interesting perspectives
on this question. The removal of exchange controls, improvement in input
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195
supplies, opening of markets, and improvement in transport services did encourage an expansion of agricultural exports in the 1990s, but the persistence of negative NRAs for the main agricultural commodities, particularly exportables, can be
interpreted as prima facie evidence that agricultural exports could have grown
even faster than they did. The agricultural subsectors exhibiting the most dramatic growth—floriculture and horticulture—involved very few farmers who,
having gained access to European markets, exploited them by insulating their
operations from domestic policy changes by establishing offshore arrangements
for inputs and spare parts (McPherson 2004). In particular, they benefited from
duty drawback arrangements and VAT zero ratings and can be said to have grown
to a significant extent because of the policy environment.15
Growth in exports of traditional agricultural products, on the other hand,
together with growth in processed food exports (notably maize meal exports to
the Democratic Republic of Congo), were rather more “in spite of ” than “because
of ” the policy environment.16 Much the same can be said of other changes in the
agricultural sector. At first gloss, a good deal was achieved very soon after the new
government came to power in fulfilling its stated commitment to withdrawing
government from direct intervention in the agriculture sector. In the midst of the
drought and large imports of food that the drought required, maize meal and
fertilizer subsidies were removed. Various agricultural reform programs were
launched in 1992–93, notably those targeted at liberalization of maize, agricultural input markets, and agricultural credit schemes. In 1995, the milling industry
was privatized, and the World Bank-led Agricultural Sector Investment Program
was initiated.
However, these reform programs were not carried through with the vigor that
was needed to produce the required results. The government commissioned a
maize marketing study that recommended that the government should fully withdraw from maize and fertilizer marketing and retain only a small role in establishing an agency to hold modest stocks for food security purposes. The Food Reserve
Agency was duly established in 1996 but soon was required to take on additional
roles. The government justified extending the agency’s mandate by saying that the
private sector response to the government’s withdrawal from input and product
had been inadequate. This is ironic, because the supposedly poor response is
clearly a result of continued intervention by the public sector and the associated
unpredictability and risks that the intervention involves for private entities.17
The resources associated with agricultural credit schemes initiated by the new
government were used inefficiently or misappropriated (or both), so the objectives of the schemes were thwarted. The fate of the marketing and fertilizer credits
made available to lending institutions in 1992/93 and 1993/94 were subject to a
special investigation commissioned by the minister of finance. The Agricultural
196
Distortions to Agricultural Incentives in Africa
Credit Management Program launched in 1994 was also poorly implemented,
giving rise to high administrative costs, low credit recovery, and corruption.
McPherson (2004) concludes that the principal function of agricultural credit in
Zambia has been to redistribute wealth to relatively well-off farmers, rather than
to expand agricultural output.
The Agricultural Sector Investment Program, which was supposed to be a landmark example of a coordinated multidonor, sectorwide approach, unifying 180
separate donor-funded projects, has also largely been deemed to be a failure. The
World Bank itself, through its Operations Evaluation Department, rates the outcome as unsatisfactory, sustainability unlikely, and institutional development modest (World Bank 2003). These ratings pertain to the original objectives—improve
household food security, make better use of natural resources, generate employment, raise incomes, and increase exports—objectives that “were not achieved,”
according to the evaluation. The project was later restructured, but even the scaleddown project failed at the time to achieve most of its revised targets.
In the light of recent developments in the sector, however, the project may have
been more successful than it appeared earlier. First, the agriculture sector has
experienced impressive export growth, and the sector itself has shown reasonably
good average growth rates throughout 2000s despite drought during the 2001–02
season, suggesting that the investment program perhaps had some positive lag
effects. Second, on sustainability, the investment program created the Agricultural
Consultative Forum, (which is still active and is one of the leading think tanks
facilitating policy dialogue between the Ministry of Agriculture and sectoral
stakeholders. Third, the Rural Investment Fund, the largest component of the
investment program, is still active and continues to facilitate investments into
rural infrastructure. Recent field visits by World Bank staff have reportedly shown
that many infrastructure facilities (such as small dams and storage facilities) built
under the fund but dormant during the early 2000s are coming back to productive
use and some, such as small-scale irrigation plans, are being further developed by
local communities. Finally, the Agriculture Sector Investment Program managed
to scale down the Ministry of Agriculture and focus it on core functions, although
the fertilizer subsidy programs and maize market interventions have recently
crowded out the agriculture budget for core functions.
After serving two terms, President Chiluba was not eligible to stand for reelection in 2001, and he was succeeded by Levy Mwanawasa. Both were from the same
political party and there have not been any dramatic shifts in policy in recent
years. The macroeconomy has continued to improve, and real GDP growth
remained above 5 percent per year over the last five years, from 2003 through
2007. In 2006 and 2007, real GDP growth was 6.2 and 6.3 percent, respectively
(IMF 2008).
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197
The Mwanawasa government has made a few positive steps to address criticisms of the weaknesses and inconsistencies of the agricultural liberalization to
date and has also taken some backward steps. On the positive side, it has acceded
to the arguments opposing the formation of a Crop Marketing Authority (see, for
example, Nijhoff et al. 2003) and has accepted that intervention should be limited
to the more restricted roles established for the Food Reserve Agency. On the negative side, the government used a tariff review in 2005 to raise border tariffs on
agricultural goods18 and continues to hold down private sector involvement in
maize marketing by continuing panterritorial pricing and procurement and by
injecting uncertainty about the whether export bans, tariff waivers, public sector
import levels, and subsidies will be imposed when there is a maize shortfall.19
The main policy change has been to increase the level of maize and fertilizer
subsidies. Producers have also benefited from a more certain policy environment.
Despite the inherent policy inadequacies, the so-called “new deal” government has
not made varied pronouncements during its tenure. Participants in the agricultural sector have thus learned how to deal with the inadequacies in a relatively
stable environment largely free of the uncertainties associated with policy shifts.
Although the agricultural policy environment since 1992 has not been as open
and growth oriented as had initially been expected, some notable positive changes
have benefited small-scale farmers and poor consumers. Two sectors illustrate this
point. First, removal of subsidies and other aspects of maize liberalization undermined the monopolistic position of the large milling companies, making it profitable for small hammer mills to produce maize meal. These are widely dispersed
and often operate on a service milling basis, charging a fee for grinding maize
grain that is brought to them by producers or households who were able to buy
that grain or obtain it through food aid sources. Not only is the cost of the maize
meal from hammer mills significantly cheaper than the commercial product—
Jayne et al. (1999) estimate 20–30 percent cheaper—it is also (in its straight-run,
or mugaiwa, form) more nutritious (Mwiinga et al. 2002). A 1997 study estimates
that there were at least 5,000 hammer mills in the country, by that time providing
a significantly cheaper source of maize meal while also employing 10,000 people.
In addition, “the presence of the hammer mill has been reported to have stimulated increased crop production” (Temba 1997).
Second, in the case of cotton, the dissolution of the Lint Company of Zambia
and its replacement by a variety of purchasers of seed cotton has been associated
with a dramatic rise in the production of seed cotton (from 48,000 metric tons in
1993 to 144,000 in 2004, according to the Central Statistics Office). Unlike other
export crops that grew rapidly in the 1990s (fresh flowers and sugar), cotton is primarily a small-holder crop. “Its potential role in poverty alleviation and food security is thus very large,” according to Tschirley, Zulu, and Shaffer (2004, page 1).
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Distortions to Agricultural Incentives in Africa
Neither of these positive developments is reflected in our NRA calculations. In
the case of maize and maize meal, the data used is for commercial operations,
while in the case of cotton the calculated NRAs are simply not consistent with
developments in the sector. This may well be due to the monopsonistic structure
of the industry.20 After liberalization, the Lint Company of Zambia gave way to
several cotton companies, but they operate in restricted areas and in effect are
local monopsonists. This allows the Zambian cotton companies to sell inputs to
farmers at cost, since they will receive any output and are assured of a profitable
margin on the product side. The companies wanted to create order and predictability, which has paid off in increased production. Cotton and tobacco production also expanded because they were profitable relative to other crops. Maize
production was adversely affected by the dissolution of NAMBOARD, and many
small-scale producers reduced their maize areas and started growing cotton and
tobacco (Tschirley, Zulu, and Shaffer 2004).
The unexpectedly negative NRA results since 1991 for most of the commodities studied (especially exportables) may also stem in part from the monopsonistic buying that is also evident in the cereal and oilseed sectors. Although there are
many buyers of these crops, and not just a small number of big companies, the
buyers nonetheless operate in specific localities, where competition is limited.
Furthermore, the buyers are aware of the cash needs of farmers and therefore offer
the lowest prices just after the harvest, accepting that somewhat higher prices will
have to be paid later in the season, but knowing that the average for the year will
be very low relative to border prices.
Market adjustment lags between domestic and border prices appear not only
for small-holders but also in trades involving large-scale producers, even those
using the Agricultural Commodities Exchange. In theory with perfect competition producer prices would rise to match border prices, providing strong incentives for increased production of the affected crops and hence rapid growth of the
agricultural sector. This has not happened. To the extent that market imperfections affect prices, the difference could be labeled as a “market imperfection margin.” Assuming the most recent five-year period (2001–05) to be the most liberal,
for Zambia the results suggest that this margin may have averaged, across all
crops, as much as 30 percent gross or 25 percent net of input subsidies, even
including a positive NRA for a major import-competing product (wheat). The
market imperfection margin for exportables alone is estimated to be 39 percent. 21
Prospects for Further Reform
In the last five-year period covered, all the NRA estimates for our covered products remain stubbornly negative, with the sole exception of wheat (see table 6.1).
If the levels of distortion are to be reduced in the future, attention will have to be
Zambia
199
given to both microeconomic and macroeconomic factors. The government needs
to shift expenditure priorities in agriculture from short-term recurrent subsidies
to long-term investments, to promote the development of competitive, private
sector involvement in input supply and marketing, and to ensure a competitive
exchange rate to enhance the profitability of traded agricultural commodities.
Government expenditure on agriculture is currently biased toward short-term,
high-visibility expenditures that have obvious political payoffs but do nothing to
overcome structural weaknesses in the agricultural sector. Thus of the K650 billion allocated to agriculture in 2006, over 30 percent (K199 billion) was for fertilizer subsidies. The current expenditure pattern varies greatly over time, and offers
relatively low payoffs that depend heavily on rainfall. Other interventions would
have lower and more stable returns. As concluded in a recent study on the
poverty-reducing potential of small-holder agriculture, what is required is a comprehensive and holistic long-term approach to rural development, “not just an
agricultural or commodity-specific strategy” (Siegel and Alwang 2005). Government expenditure should thus be directed to higher investment in agricultural
infrastructure with a higher social impact such as roads, energy, water, telecommunications, and agricultural research and extension.22
With regard to building the capacity of the private sector, the government
needs to recognize that its own activities often undermine the private sector. In
areas close to the rail line it should be profitable for the private sector to supply
inputs and market production, but in practice private operators often find their
efforts undercut by public sector provision of cheaper inputs or higher prices for
crops. Parallel, subsidized delivery systems in the districts along the line of rail are
suppressing commercial investments.
The government would do better to revert to targeting subsidies to areas that
are difficult for the private sector to serve because of underdeveloped infrastructure and sparse populations. A recent study for the Food Security Research Project
found that districts in which at least 25 percent of sampled households purchased
fertilizer from commercial outlets were near the rail line. Subsidies could be provided to households in more remote districts by adopting incentive-based subsidy
mechanisms, similar to those now commonly used in infrastructure sectors to
leverage private sector capital and skills into serving remote areas. Under such
output-based aid approaches, or “smart subsidies,” potential private operators bid
to provide specified services, and the bidder requiring the lowest level of subsidy is
given the tender. Mechanisms for monitoring implementation and penalizing
nonperformance would be needed, however.
Finally, despite the liberalizations of the past 15 years and the consequent
diversification that has occurred, copper still remains the lead sector in Zambia’s
economy, particularly in terms of foreign currency generation. Currently, the key
macroeconomic issues are the level and variability of the exchange rate. With the
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Distortions to Agricultural Incentives in Africa
reduction of Zambia’s external debt; a resumption in confidence, as exemplified
by foreign purchases of government securities; and a steep increase in the copper
price (from $1,560 a metric ton in 2002 to over $8,000 in 2006), the nominal
exchange rate appreciated 60 percent between June 2005 and June 2006—and the
real appreciation was even larger. The exchange rate keeps moving, however, from
K2,900 in mid-June, for example, to K4,000 to the U.S. dollar in mid-August of
2006. Appreciation of the kwacha and variability of the exchange rate pose significant threats to the sustainability of the recent achievements in increasing agricultural and other nontraditional exports.
As highlighted above, the government, with the support of the International
Monetary Fund, is treating the appreciated exchange rate as a valid measure of the
opportunity cost of foreign currency. In contrast, other major copper exporters,
such as Chile, are attempting to limit the Dutch disease effects by building up offshore reserves, thereby sterilizing the impact in the local economy.23 Sterilizing
resource rents in boom periods to maintain a competitive exchange rate and promote alternative exports is one of the main recommendations that emerges from
the literature on why so few resource-rich countries have performed better than
resource-scarce ones.24 As long as Zambia continues with a policy whereby the real
exchange rate is effectively held hostage to the vagaries of the copper market, there
will be continuous underachievement in the goal of economic diversification.25
After the firm Anglo American withdrew from Zambia, the operators who took
over the copper mines were given extraordinarily generous terms. At this juncture,
the government is receiving virtually no taxes and no mining royalties. The main
benefits of production to the economy are through employment and multiplier
effects, both of which are limited in the mining sector. Without abrogating agreements, the government must investigate ways to increase its share in copper revenues.26 Any additional resources from the copper sector should be used to build
up infrastructure, human capital, and productive capacity in other sectors. Of
these, the key sector is agriculture, where there is so much untapped potential and
where the equity and poverty reduction benefits would be substantial.
Notes
1. The total land area of the country is 74 million hectares, of which 47 percent is suitable for
agriculture; rainfall averages over 1,000 millimeters a year. Population density is only one person per
6.4 hectares (World Bank 2006; FAO 2006).
2. Values and growth rates that are not cited are from World Bank (2006).
3. Detailed analysis of changes in cropping mix among small-scale farmers is available in Zulu
et al. (2000).
4. See papers produced by the Food Security Research Project (FSRP), a collaboration between the
Agricultural Consultative Forum, the Ministry of Agriculture and Cooperatives, Michigan State
Zambia
201
University, and the U.S. Agency for International Development in Lusaka. http://www.aec.msu.edu/
agecon/fs2/zambia/index.htm.
5. This conclusion applies even to the effects of panterritorial prices. See later discussion in this
chapter and Jansen and Rukovo (1992).
6. McCullogh, Baulch, and Cherel-Robson (2001); Balat and Porto (2006); Siegel and Alwang (2005).
7. There are reasons to suspect that the price variations in Kabwe were particularly large in the
1998–99 season; a main reason was that Food Reserve Agency imports were largely channeled to
industrial millers and did not reach local markets. Much of the locally produced grain was probably
sold early in the season because of farmers’ cash needs. So with restricted supply and increased
demand (to take to hammer mills), prices rose dramatically in the later months.
8. Year-by-year data are in appendix B of this volume, with further details in the appendix to
Robinson, Govereh, and Ndlela (2007).
9. Jansen’s full set of estimated nominal rates of protection for 1966-84 are given in table 7-7 in
Jansen (1991) and are extended for maize, cotton, and tobacco to 1990 in table 7 of Jansen and Rukovo
(1992).
10. Given the many assumptions behind the RRA calculations, weight needs to be given to the
direction of change from the NRA numbers rather than to the absolute magnitudes. In particular, the
data on subsidies are not complete or consistent over the whole period. After 1990, subsidies throughout the economy were sharply reduced but in agriculture some subsidies were continued, particularly
in 1992 and 1993, to counter the effects of the extreme drought. There was also significant support to
the agricultural sector through the large Agriculture Sector Investment Project over the period 1994 to
2001. In the new millennium, subsidies to agriculture have been increased again, notably on fertilizers
and other inputs.
11. Jansen (1991) cites a linear programming transport model exercise showing that transport
costs increased 20 percent as a result of panterritorial pricing.
12. For details, see Jansen (1988).
13. For most of the time this was in operation, the surrender requirement on exporters was
50 percent of their export proceeds; the other 50 percent was sold at parallel market rates. These are
the values used in the spreadsheet. The multiple exchange rate system was unwound in 1992 with full
unification of the exchange rate by early 1993.
14. These issues are discussed in more detail in Robinson (2004).
15. More recently, floriculture and horticulture have experienced declines. Sugar, cotton, and
tobacco have exhibited more sustained growth.
16. Between 1987 and 2003, the bulk of nontraditional exports were primary agricultural products (33 percent), floriculture and horticulture (23 percent), processed food (20 percent), and textiles
(20 percent).
17. Specific examples of the government’s stop-go approach and the resulting increasing intrusion
of the public sector, have been documented in, for example, Jayne et al. (1999), Govereh et al. (2002),
IMCS (2003), Mwanaumo et al. (2005), Siegel and Alwang (2005).
18. Using the Global Trade Analysis Project (GTAP) product classifications, between 2003 and
2005 the applied Zambian import tariffs have gone up as follows: paddy rice, from 4.6 percent to
15 percent; wheat, from 5 percent to 10 percent; cereal grains, from 4.8 percent to 12.4 percent;
and oilseeds, from 4.5 percent to 5.6 percent (World Bank 2008).
19. Mwanaumo et al. (2005) document the significant direct costs involved in public sector delays
in response to the 2005 maize shortfall (such as fourth-quarter imports costing $256 and $320 per
metric ton, compared with $210, and lower transport costs had the maize been purchased in June).
That report also notes the indirect, long-term costs of intervention in preventing the emergence and
expansion of a competitive private sector capable of reducing marketing costs over time.
20. This would not be unique to Zambia. See “Why Liberalization Did Not Lead to Price
Competition in Zimbabwe,” in Goreux (2003, Section 2.6).
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Distortions to Agricultural Incentives in Africa
21. The conundrum of negative NRAs after liberalization is even more difficult to explain to the
extent that the kwacha arguably remained overvalued after the liberalization of the foreign exchange
market, yet our NRA estimates assume it has been in equilibrium since 1992. The possibility that the
kwacha is overvalued when it is “market determined” is denied by the IMF and the Bank of Zambia.
However, when monetary and international reserve policies are taken into account, one estimate, for
the period 1996-2000 suggests that the kwacha was 60 percent overvalued (Robinson 2004).
22. Similarly, Balat and Porto (2006) conclude that while expanded trade opportunities in crops
such as cotton, tobacco, and hybrid maize offer the prospect of significantly higher rural incomes,
these gains will not materialize without “complementary policies, like the provision of infrastructure,
credit, and extension services.”
23. “Coping with the Copper Boom,” The Economist, May 25, 2006.
24. See, for example, Reinhardt (2000); Auty (2001, 2004); and Esanov, Raiser, and Buiter (2004).
25. Kayizzi-Mugerwa (1991) uses a multisector general equilibrium model to show the complexity of the links in an economy subject to Dutch disease shocks caused by the dominance of copper. He
also argues for a more competitive exchange rate but observes that “in practical terms, the size of the
devaluation of the nominal exchange rate necessary to realize a favorable change in the real exchange
rate might be politically unacceptable. Success thus depends . . . on the political work put into selling
the adjustment package” (p. 862).
26. Certain tax concession periods for have now expired.
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Ministry of Agriculture and Cooperatives and Agricultural Consultative Forum, Michigan State
University, East Lansing, MI.
Reinhardt, N. 2000. “Back to Basics in Malaysia and Thailand: The Role of Resource-Based Exports in
their Export-Led Growth.” World Development 28 (1): 57–77.
Robinson, P. B. 2004. “Evaluation of World Bank Trade Assistance to Zambia (1987–2002).” Operations
Evaluation Department, World Bank, Washington, DC.
Robinson, P., J. Govereh, and D. Ndlela. 2007. “Distortions to Agricultural Incentives in Zambia.”
Agricultural Distortions Working Paper 40. World Bank, Washington, DC.
Siegel, P. B., and J. Alwang. 2005. “Poverty Reducing Potential of Smallholder Agriculture in
Zambia: Opportunities and Constraints.” Africa Region Working Paper Series 85. World Bank,
Washington, DC.
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Distortions to Agricultural Incentives in Africa
Temba, J. 1997. “The Hammermill Industry in Zambia.” The Study Fund, Social Recovery Project,
Report 36. World Bank, Washington, DC.
Tschirley, D., B. Zulu, and J. Shaffer. 2004. “Cotton in Zambia: An Assessment of Its Organisation,
Performance, Current Policy Initiatives, and Challenges for the Future.” FSRP Working Paper 10.
Food Security Research Project, Ministry of Agriculture and Cooperatives and Agricultural Consultative Forum, Michigan State University, East Lansing, MI.
World Bank. 2003. “Project Performance Assessment Report, Zambia: Agricultural sector Investment
Program (Credit 2698-ZA).” Sector and Thematic Evaluation Group, Operations Evaluation
Department, Report 26086. World Bank, Washington, DC.
———. 2006. World Development Indicators. Washington, DC: World Bank.
———. 2008. World Integrated Trade Solution (WITS) database. Washington, DC: World Bank.
http://wits.worldbank.org.
Zulu, B., J. J. Nijhoff, T. S. Jayne, and A. Negassa. 2000. “Is the Glass Half Empty or Half Full? An
Analysis of Agricultural Production Trends in Zambia.” FSRP 2. Food Security Research Project,
Ministry of Agriculture and Cooperatives and Agricultural Consultative Forum, Michigan State
University, East Lansing, MI.
7
Zimbabwe
Daniel Ndlela
and Peter Robinson*
Zimbabwe’s agricultural history can be traced to the period dating from the 13th
to the 15th century, when the country was known as the Great Zimbabwe under
the Mhunumutapa Empire. In precolonial times, people relied on barter trade for
goods and services offered by the trading communities, and production patterns
were based on comparative advantage. Then, with the arrival of the first European
settlers in the late 19th century, acquisition and control over land became the central factor underpinning the growth, maturation, and decline of agriculture in
Zimbabwe. This colonial and postcolonial era can be divided into seven subperiods defined by major political and economic developments.1
In colonial times, the country was initially ruled by the British South Africa
Company, under a British charter (1890–1923), and subsequently by a white
minority, to which Britain granted “self-government” in what was then called
Southern Rhodesia (1923–53). These settler regimes deliberately created a dualistic system of agriculture, in which the European farmers were given exclusive
rights to the best farmland, together with various forms of support and assistance,
while the majority African producers were confined to areas much less suitable for
agriculture and were subject to discriminatory policy measures designed to subordinate African agriculture. The areas in which Africans were required to remain
were initially known as Native Reserves, but were subsequently referred to as
Tribal Trust Lands (during the 1960s and 1970s) and as Communal Lands (after
independence). In these areas, traditional communal land tenure prevails.2
* The authors are grateful for helpful comments from workshop participants, including Marianne
Kurzweil and Ernesto Valenzuela. Detailed data and estimates of distortions reported in this chapter
can be found in Ndlela and Robinson (2007).
205
206
Distortions to Agricultural Incentives in Africa
As early as the 1930s, a small provision was made for African farmers to acquire
land on a freehold basis, but the available land never amounted to more than
8 percent of the total land area. Almost all small-holders were confined to what are
now communal areas. This fundamental structure, dividing agriculture between
small-scale communal farmers and large-scale commercial farmers, remained
intact and determined production patterns throughout the 20th century.
During 1953–63, the country was part of the Federation of Rhodesia and
Nyasaland (now Zambia, Zimbabwe, and Malawi). With the federal government
situated in Salisbury (now Harare), the Southern Rhodesian government had a
dominating influence over the federation. When Zambia and Malawi achieved independence, the federation dissolved. The Rhodesian government tried to avoid pressures for majority rule through a unilateral declaration of independence (UDI) from
the nominal colonial ruler, Britain, in November 1965. The international response to
this illegal action was the imposition of trade and investment sanctions, which led to
a “closed economy” environment that in turn stimulated a period of intense import
substitution. The agricultural sector grew rapidly, diversifying away from the main
export crop, tobacco, which was particularly hard-hit by the sanctions.
During the UDI period, nationalist forces intensified their struggle into a war
of liberation that eventually sapped the resources of the UDI regime. The main
focus of the struggle was the restoration of land to the African majority. Yet after
independence was achieved in 1980, land reform proceeded slowly. Various resettlement “models” were tried in the early 1980s, but still few Africans were able to
acquire land, even after the restrictive terms of the transitional Lancaster House
Constitution expired in 1990. Pressure from various quarters for resolution of the
land question resulted in the convening of a major international land conference
in 1998. The proposals made at that time seemed to have the support of a wide
cross-section of stakeholders but were rejected by President Robert Mugabe.
Had the 1998 proposals been implemented, an orderly land reform program
probably could have been undertaken with relatively little disruption to agricultural production. That did not occur, however. Two years later, when the government lost a constitutional referendum in February 2000, a precipitous “fast-track”
land reform program was implemented in a manner that has effectively decimated
the agricultural sector. At the same time, perverse macroeconomic policies were
imposed, with an acceleration of inflation to above 1,000 percent per year in 2006
and above 10,000 percent in 2007 (IMF 2008). The combined effect of adverse
structural change and inflationary macroeconomic policies has been eight consecutive years of declining gross domestic product (GDP) since 1999, with the
cumulative decline totaling about one-third of national output.
The decline in the agricultural sector since 2000 has been even steeper than the
decline in the overall economy. Between introduction of the land reform program
Zimbabwe
207
in 2000 and 2002, the large-scale commercial sector shrank from 39 percent of the
land area to 8 percent. White-owned commercial farms continued to be expropriated and reallocated to new owners in a discriminatory way, in a highly politicized
environment. As a result, much of the land is now occupied by people unable to
use it productively. Moreover, the perception of injustice in land access continues.
Thus, despite the destruction of the agricultural base and much of the institutional structure that supported a highly productive agricultural sector, the “land
question” in Zimbabwe still remains to be settled.
It is against this background that the agricultural distortion measures in this
study are to be assessed. The data presented here are calculated for the period
1955–2004 and attempt to measure the divergence between prices actually paid
and prices that would have prevailed in the absence of policy distortions. Those
undistorted prices are estimated using trade parity prices, based on external
border prices plus or minus the marketing margins that would prevail in a competitive market. With the exception of wheat before 1973, and to a lesser extent
maize and cotton for some years in the early part of the study period, plus a very
few other single-year values elsewhere in the time series, the nominal rates
of assistance (NRA) for all the crops studied are found to have large negative
values.
The high taxation of agriculture can be explained by three main factors: agricultural policies that have driven down producer prices, offset at various times to
some extent by direct subsidies to agriculture; market imperfections, particularly
monopsonistic buying practices, which deprive farmers of the returns they should
be receiving; and macroeconomic mismanagement, notably a persistently overvalued exchange rate.
The highest rates of growth in the agricultural sector as whole came in the late
1960s and early 1970s. However, after independence the support given to the previously neglected small-scale farmers, coupled with subsidy policies that encouraged the marketing of maize and repurchase of maize meal, resulted in significant
improvement in performance, with the communal sector becoming the dominant
supplier of both maize and cotton. A particular focus of attention is whether the
liberalization of agricultural markets, which occurred as part of a broad structural
adjustment program in the 1990s, had a positive effect on the agricultural sector.
It turns out that the calculated NRAs and the growth of agricultural GDP are
hardly different from the rates registered before liberalization, although it should
be noted that the averages for the 1990s include the adverse effects of the once-ina-century drought that occurred in the 1991–92 agricultural season.
Before 1990, the taxation of agriculture can be largely attributed to direct interventions. After liberalization, indirect interventions explain the persistence of low
prices for producers, including particularly monopsonistic buying of agricultural
208
Distortions to Agricultural Incentives in Africa
outputs and credit market restrictions that prevent farmers from borrowing to
pay for storage of crops to take advantage of higher prices later in the season.
In response to the steep decline in agricultural output following the 2000 land
reform program, the government (mainly through quasi-fiscal payments by the
Reserve Bank of Zimbabwe) provided huge levels of subsidies to farmers (equivalent, in 2004, to 19 percent of GDP). However, distortions in the overall economy
mean that items such as subsidized fuel and credit are likely to have been used for
highly profitable arbitrage purposes rather than for agricultural production.3
The crisis in the agricultural sector and the economy as a whole is politically
induced, and until there is a political realignment, implementation of the comprehensive economic and social program that is so desperately needed will not be
possible.
Agricultural Policy and Distortions before 1955
Zimbabwe’s modern economy was built upon the land alienation policies that
followed the country’s colonization by white settlers organized by the British
South Africa (BSA) Company in 1890. The primary motive of the colonization by
the BSA Company was the pursuit of rich gold deposits, but failure to realize this
original dream turned the company toward exploitation of the land and related
agricultural resources. Already by the early 20th century, agriculture was being
vigorously organized to provide food for commercial settlements, namely, mines
and urban centers. By the beginning of 1900, three types of land categories were in
existence: reserves set aside for the exclusive use by Africans; land alienated to
mines and farms, sometimes occupied, sometimes in the hands of absentee land
owners or companies; and unalienated land, which the BSA Company regarded as
its own until the British Privy Council decision of 1918 conferred it to the Crown.
Between 1908 and 1914, the BSA Company pursued a so-called “white agricultural policy” to limit the African reserves with the intention of recovering the best
land and making it available for European settlement (Palmer 1977, p. 80). The
BSA Company’s management of land rights was even more racially discriminatory than its charter specified, actively preventing Africans from acquiring land
that by law should have been open for purchase by members of all races.4
The dual structure of land ownership was reinforced through the provision of
government services. In 1908, the Department of Agriculture was reorganized to
give technical support to white farmers. A land bank was set up in 1912 with a
share capital of £250,000 (Palmer 1977, p. 89). Bank loans of up to £2,000 for the
purchase of farms, livestock, and other agricultural equipment were made available to white farmers only. No loans at all were available to black farmers until
1945, when the land bank initiated a scheme of advancing credit to farmers in the
Zimbabwe
209
African Purchase Areas where freehold ownership had been allowed. These areas
accounted for a very small proportion of farmland in the country, occupying a
maximum of 8 percent of the total land area. Loans were not available to other
African farmers, because of their alleged lack of collateral security.
The transition in 1923 from BSA Company rule to self-rule by the white settlers only reinforced dualism and ushered in further land alienations. The 1898
British order that “a Native may acquire, hold, encumber and dispose of land on
the same conditions as a person who is not a Native,” which had not been enforced
by the BSA Company, was formally rescinded by the new government of Southern
Rhodesia at the recommendation of its 1925 Land Commission. The commission
recommended that native Africans be allowed freehold ownership only in newly
demarcated Native Purchase Areas. Selected African farmers were allowed to buy
those plots, whose scale was much larger than could be farmed by a typical household. Those operations later became known as small-scale commercial farms.
The actions taken following the 1925 Land Commission prepared the stage for
the Land Apportionment Act of 1930 and consequently also laid the foundations
for the permanent division of the country into African and European areas. The
Land Apportionment Act provided a legal foundation to confirm BSA Company
practice and provide separate areas reserved for whites and blacks. In creating
African reserves, the Land Apportionment Act not only prevented Africans farmers from becoming competitors to the white settler farmers, it also impoverished
Africans to such an extent that the majority of adults would be compelled to work
for white farmers in mines or farms (Ndlela 1981, p. 72).
African agricultural production was severely curtailed. At the beginning of the
century, African sales of farm produce accounted for 70 percent of their total cash
earnings; by 1932 the figure had fallen to 20 percent (Arrighi 1970, p. 216). A stagnant peasant agriculture within the framework of dualism in the economy had
emerged as increasing numbers of black peasant farmers were evicted from the
more-fertile lands and from the areas within easy reach of markets. This discriminatory and dualistic political and economic framework, especially with regard to
land policy, was further entrenched under the Native Land Husbandry Act of
1951. And when the Land Apportionment Act of 1930 was superseded by the
Land Tenure Act of 1969, all the main provisions of the former were confirmed.
Government interventions in marketing and prices came after dualism was
established, and were triggered by a deep slump in Rhodesian cattle and maize
prices that occurred in 1921–23. This slump had far more devastating effects than
previous economic depressions. In 1920, African grain sales to “white” traders
were estimated at 19,800 metric tons at 10 shillings per bag.5 In 1921, the average
price had fallen to approximately 5 shillings per bag, at which prices sales of grain
became uneconomic in many districts. There was a bumper harvest that year, but
210
Distortions to Agricultural Incentives in Africa
only 43,000 bags (4,300 metric tons) were purchased from African peasant farmers, a drop of 78 percent in sales. A similar reduction was reported in sales of
African cattle. From an estimate of at least 20,000 head of cattle sold in 1919 at
prices on the order of £7 to £8, by 1921 the demand for African cattle had practically ceased to exist.
The collapse in prices and purchases from African farmers was not only a cyclical phenomenon but also a structural change driven in part by surpluses from
areas reserved for white settler farmers. African farmers had been moved out of
those areas to the more remote reserves, cut off from the rail line or other transport systems. Only 30 percent of the land assigned to Africans, but 75 percent of
that allocated to Europeans, was within 25 miles of the railway line and therefore
within reach of markets for agricultural goods in the towns and mines. From the
early years of colonial administration, the policy was to locate the European farms
close to the railway line so white farmers had easy access to the country’s transport
system. Peasant farmers located more than 40 miles or so from the rail line, by
contrast, were cut off from markets. When railway costs were added, grain crops
could not bear the costs of more than 15 miles of ox-wagon transport. Furthermore, what little could be produced and transported from African areas was
worth little when it arrived in town, because those markets were now being served
by produce from the more productive and conveniently located areas now being
used by white settlers (Arrighi 1970).
Explicit price discrimination in product markets was introduced in 1931.
White farmers had been calling for the establishment of statutory marketing
agencies to stabilize and guarantee their producer prices during the 1920s. The
sudden decline in world maize prices at the onset of the Great Depression added
urgency to their demands, which were met with creation of the Maize Marketing
Board under the Maize Control Act of 1931. Under the law all maize destined to
be marketed in urban areas had to be sold through the board, except for sales
between Africans in the same administrative area. The board’s initial mandate was
to operate a dual price system, keeping domestic consumer prices 30–50 percent
above export values. A quota system allocated white producers preferential access
to the local pool, in an amount just sufficient to meet local demand (Ndlela 1981,
p. 164), with the remaining maize sold to the export pool at whatever prices could
be realized in the world market.
A further step toward price discrimination came with the Maize Control
Amendment Act of 1940, which introduced a fixed price to producers based on
the estimated costs of production plus some profit (Yudelman 1964, p. 273). Procurement occurred preferentially in white-controlled areas. White farmers were
further privileged through a bonus paid for all maize delivered to the maize board
that had been grown under certain conditions of “sound” farming practices,
Zimbabwe
211
defined in a way that excluded almost all African farmers. Price discrimination
worsened in the 1950s, when the few African farmers who did deliver grain were
made to pay special marketing levies nominally intended to cover the cost of handling their crops.
The system of monopoly marketing and price discrimination developed for
maize was extended to other crops after 1950, when the Maize Marketing Board
was renamed the Grain Marketing Board (GMB). The GMB’s mandate included
controlling the purchase and sale of various products including sorghum (from
1950), groundnuts (from 1951), soybeans (from 1969), wheat (from 1970), and
coffee (from 1971).6 Many of these functions were eventually scrapped during the
opening up of the economy in the 1990s, but then reintroduced beginning in 2001.
Measuring the Extent of Price Distortions,
1955–2004
The main focus of this study’s methodology (see appendix A of this volume and
Anderson et al. 2008) is on government-imposed distortions that create a gap
between domestic prices of farm products and what they would be under free
market conditions. Because the characteristics of agricultural development cannot be understood from a sectoral view alone, the project’s methodology not only
estimates the effects of direct agricultural policy measures (including distortions
in the foreign exchange market), but it also generates estimates of distortions in
nonagricultural sectors for comparative evaluation.
More specifically, this study computes a nominal rate of assistance for farmers
including an adjustment for direct interventions on inputs. It also generates an
NRA for nonagricultural tradables, for comparison with that for agricultural
tradables through the calculation of a relative rate of assistance (RRA).
The basis of the approach is a comparison between the prices actually received
by producers (or paid by consumers) and the prices they would have received (or
paid) had there been no policy distortions. This approach reflects the assumption
that in small countries the relevant opportunity costs are reflected in the international border prices for the commodities, adjusted for nonpolicy price wedges
such as transport costs, marketing margins, quality differences, and the like.
Where actual import and export prices are available, these are used in preference
to the alternative of constructing a synthetic border price from international commodity reference prices, adjusted for transport and related costs.
The import and export parity prices are converted to local currency terms at an
equilibrium exchange rate estimated from the official rate and the proportion of
export receipts traded on the parallel or sanctioned secondary market (when
there were retention schemes for exporters) or the illegal (black) secondary
212
Distortions to Agricultural Incentives in Africa
market for foreign currency. Almost all import and export transactions in
Zimbabwe involving the main crops have taken place at the official exchange rate
throughout the five decades covered by this study.7
The longest series of border prices is obtained from the trade volume and value
data from the Food and Agriculture Organization’s FAOSTAT database. Dividing
value by volume produces aberrant unit values in years when volumes are small,
so for those years we used either national trade data (when that was available) or
the international commodity reference price approach—bearing in mind that
much of Zimbabwe’s agricultural trade is within the southern African region
rather than to and from international ports.
The producer price and production data for maize, cotton, groundnuts,
sorghum, tobacco, and wheat are available over the entire time period, mainly
from the official Central Statistical Office (2005) and from individual researchers,
notably Muir (1981b) and Masters (1994a, 1994b). Producer price and data are
available for sunflower only from 1960 and for soybeans only from 1968, because
these are relatively new crops. As many primary and secondary data sources as
possible were consulted to build up the data series needed for the calculations, and
it should be noted the figures available for any particular commodity and year are
sometimes quite divergent.
Interpretation of the NRA and consumer tax equivalent (CTE) results presented here needs also to take account of several other issues that arise from the
way the calculations have been made. First, the wholesale level was chosen as the
point in the value chain where the ratios were calculated. We assumed that from
1955 to 1990, the wholesale level was constituted by the state marketing boards,
namely, the GMB for maize and other grains covered in this study (groundnuts,
soybeans, sorghum, sunflower, and wheat) and the Cotton Marketing Board for
cotton. Tobacco’s point of sale is calculated as the price prevailing at the tobacco
auctions in Harare. The calculated NRA measures thus apply to farmers close to
the depots and would be lower (which in almost all years means more negative)
for farmers living away from the depots. This remained true even after independence, when the government did try to improve the position of small farmers in
remote areas by extending the network of marketing board rural depots beyond
the line of rail and introducing panterritorial pricing.
Second, attempts were made during the 1990–94 period to deregulate domestic markets for major crops, but less progress was made in the liberalization and
demonopolization of imports and exports by the marketing boards. Although the
GMB was completely deregulated by April 1994, it continued to maintain its
monopoly on international trade and to provide the reference wholesale level
prices. Then in 2000, the government reintroduced domestic controls, including
the compulsory purchase of grain and tight control over transport of maize and
other crops. Thus, except for the period 1994–2000, the GMB has consistently
Zimbabwe
213
exercised a statutory monopoly and monopsony over both domestic and international marketing of maize and other major grains.
Third, even during the 1994–2000 period, the GMB continued to set minimum
guaranteed prices for farmers, and it is this minimum price that has been used in
the NRA calculations. Farmers who were able to market their products on the free
market would have received higher prices and hence have been subject to higher
(less negative) NRAs than have been calculated.
Fourth, in the case of seed cotton, those farmers who had received inputs from
the Cotton Marketing Board were required to sell their crop through official channels, with a “stop order” system ensuring that any loan due from the input credit
scheme was repaid. Initially following liberalization, some farmers tried to market
their crop to freelance agents and ginners without repaying their loans; those farmers thus received higher prices than those used in the NRA calculations. Subsequently, since the inputs were typically subsidized and the interest rates were below
the prevailing bank rates, most farmers preferred to market though the main
cotton companies and thereby have access to inputs for the following season.
And fifth, for the CTE calculations, the GMB selling price to the millers has
been used as the applicable wholesale price. Such prices are available only for
maize, sorghum, soybeans, and wheat. The subsidies have been given through the
marketing boards: the difference between the board purchase price from the
farmer and the selling price to the processors, less the board’s operating cost
margin. This difference indicates whether there is a subsidy to producers (positive
difference) or to consumers (negative difference).8
Overall NRA pattern
The annual NRA estimates for import-competing products and exportables are
illustrated in figure 7.1, while five-year averages for individual products are shown
in table 7.1.9 Except for sunflower, which is assumed be a nontradable and whose
NRA is estimated to be zero, the NRAs are generally negative. Some commodities
enjoyed brief periods of positive assistance: maize in the late 1950s; cotton in the
early 1960s; and wheat from 1955 to 1974. The overall pattern, however, is one of
negative assistance to agriculture after the 1950s. During the 1960s, the NRA for
products covered in this study averaged 42 percent, then it worsened in the
1970s, 1980s, and the first half of the 1990s to an average of 47 percent (peaking
at around 54 percent in the late 1970s). The negative NRA dropped back slightly
to 40 percent in the late 1990s, before relapsing severely (to around 70 percent) in the 2000–04 period. In other words, farmers were taxed most heavily after
the fast-track land reform program was implemented in 1998.
This overall negative pattern is the result of the interplay of a number of different influences. The direct influences arise from agricultural sector policies and the
214
Distortions to Agricultural Incentives in Africa
Figure 7.1. NRAs for Exportable, Import-Competing, and All
Covered Farm Products, Zimbabwe, 1955–2004
60
40
20
percent
0
20
40
60
80
03
00
20
97
20
94
19
91
19
88
19
85
19
82
19
79
19
76
19
73
19
70
19
67
19
64
19
61
19
58
19
19
19
55
100
year
import-competing products
exportables
total
Source: Data compiled by the authors.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
nature and characteristics of agricultural markets, which are discussed in detail
below. In explaining the changes in NRAs, it is not just the articulated policies that
matter but also their implementation as reflected in the institutional structures,
regulations, and financial flows (such as subsidies and public sector investments)
to the agricultural sector.
The other main strand explaining the NRA pattern lies in the indirect effects of
the macroeconomic and trade policies pursued by the government. Various
aspects of these are discussed later, but it is relevant at the outset to stress that the
main macroeconomic influence is through overvaluation of the exchange rate.
Using the parallel market premium, the Zimbabwean dollar appears overvalued
during most of the period under review, with heavy spikes immediately after the
unilateral declaration of independence in 1965, and in 1976, 1983, 2001, and 2003
(Ndlela and Robinson 2007, appendix figure 3). The peaks for 1965 and 1976 do
not include the full black market premiums, discounting the exchange rate movement that resulted from extreme capital account activity so as to leave only the
rates applicable to current account transactions. The NRA values for years such as
Table 7.1 NRAs for Covered Farm Products, Zimbabwe, 1955–2004
(percent)
Product indicator
Exportablesa,b
Groundnut
Cottonc
Tobacco
Import-competing productsa,b
Wheat
Nontradables
Sunflower
Mixed trade statusb
Maize
Sorghum
Soybean
Total of covered productsa
Dispersion of covered productsd
Percent coverage (at undistorted
prices)
1955–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
23.9
38.5
86.9
—
26.8
26.8
0.0
0.0
39.4
50.1
84.1
42.7
1.6
33.7
0.0
0.0
46.3
79.3
27.5
39.1
26.2
56.6
0.0
0.0
45.4
74.8
43.6
45.7
1.9
15.0
0.0
0.0
55.8
73.2
56.6
53.0
24.6
23.7
0.0
0.0
50.0
68.7
52.5
45.7
25.2
11.7
0.0
0.0
44.2
41.9
47.8
45.9
17.0
8.6
0.0
0.0
44.3
49.5
57.4
37.2
48.5
47.3
0.0
0.0
36.4
46.0
36.3
35.0
52.5
43.8
0.0
0.0
66.7
80.9
63.5
66.0
78.2
76.6
0.0
0.0
39.0
—
—
23.9
78.4
5.1
9.8
—
38.5
73.1
21.9
16.5
14.1
45.5
56.2
22.3
57.1
28.5
44.2
36.9
45.6
38.6
42.0
54.4
27.7
30.8
30.9
42.2
46.7
28.1
36.0
36.8
33.6
42.7
24.4
49.0
63.6
48.5
44.8
25.2
32.9
74.3
54.3
39.9
27.3
62.9
77.1
68.4
72.9
33.9
71
66
59
52
52
56
55
53
53
71
Source: Data compiled by the authors.
Note: — no data are available.
215
a. Weighted averages, with weights based on the unassisted value of production.
b. Mixed trade status products included in exportable or import-competing groups depending upon their trade status in the particular year.
c. The NRA for cotton for 1975–79 excludes 1977.
d. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
216
Distortions to Agricultural Incentives in Africa
1965, 1976, and 1983 are more negative than surrounding years, because of a
mirror image upward swing in the exchange rate premium.10
NRAs by commodity
The NRA for maize was 46 percent during 1975–79 (the height of the liberation
war), 36 percent in 1985–89, and 49 percent in 1990–94 (see table 7.1). The
NRA further worsened to 63 percent in 2000–04 (the height of the land reform
program), notwithstanding unprecedented subsidies to the sector amounting to
19 percent of GDP in 2004). The other traded cereal crops (sorghum and wheat)
have very large negative NRAs too, particularly in the 1990–2004 period. Among
the traded oilseeds, the NRA for groundnuts is severely and consistently negative
at around 75 percent during the UDI period (1965–79) and peaks again at
81 percent in 2000–04. Soybeans also are always negative and peak at 68 percent in 2000–04. The NRAs for the export cash crops, cotton and tobacco, tend to
be negative, though less so than food crops, with cotton at 57 percent, 36 percent and 64 percent in the 1990–94, 1995–99, and 2000–04 periods, respectively.
The tobacco NRAs have remained negative throughout the period under study
and in certain years are even more negative than those for cotton (39 percent
in 1965–69 and 66 percent in 2000–04).
NRA for tradables and for agriculture as a whole
The NRAs for import-competing products were generally less negative than those
for exportable farm products before the 1990s, and their average was actually positive at the start of the UDI regime under extreme import-substitution measures.
During the late 1990s, the NRA for import-competing crops was even more negative than the NRA for exportables, which is unusual. In Zimbabwe’s case the
import-competing farm subsector is relatively small, and those food grains are
considered essential for political stability, hence the provision of scarce foreign
exchange at a low price to bring in what are effectively subsidized cereal imports.
The weighted average NRA for the commodities covered in table 7.1 (which
account for between 55 and 70 percent of agricultural output over the 50-year
period) is reproduced in row 1 of table 7.2. To that, we add our guesstimate of the
NRA for the residual noncovered products. The elements of agriculture that grew
most rapidly under the liberalized conditions of the 1990s—horticulture and
export-oriented floriculture—did so in a relatively neutral policy environment.
Most fruit and vegetables traditionally are for domestic consumption and are
not traded internationally. We therefore assume the average NRA for all noncovered products is zero, and assume they are nontradables, which is true for most
of the period studied. Then the weighted average NRA for all agriculture and
for the tradable component can be estimated. These are shown in table 7.2 and
Table 7.2. NRAs in Agriculture Relative to Nonagricultural Industries, Zimbabwe, 1955–2004
(percent)
Indicator
NRA, covered products
NRA, noncovered products
NRA, all agricultural products
Trade bias indexa
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAb
Memo item, ignoring exchange
rate distortions:
NRA, all agricultural products
Trade bias indexa
RRAb
1955–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
23.9
0.0
16.9
0.01
23.9
26.0
1.7
38.5
0.0
27.2
0.37
38.5
29.1
52.3
45.5
0.0
30.8
0.58
45.6
30.8
58.3
44.2
0.0
26.0
0.44
44.2
37.8
59.5
54.4
0.0
28.6
0.40
54.5
48.1
69.1
46.7
0.0
24.0
0.33
46.7
46.9
63.4
42.7
0.0
24.1
0.31
42.9
42.2
59.8
44.8
0.0
24.9
0.13
45.2
35.9
59.5
39.9
0.0
21.2
0.42
40.0
20.9
50.6
72.9
0.0
38.7
0.83
72.9
20.2
77.3
37.3
0.10
9.4
32.9
0.31
47.8
24.5
0.40
41.3
27.7
0.21
44.6
31.3
0.13
48.4
23.9
0.36
42.3
21.4
0.13
40.5
31.6
0.59
50.8
30.8
0.71
47.0
46.2
—
63.1
Source: Data compiled by the authors.
Note: — no data are available.
a. Trade bias index is TBI (1 NRAagx兾100)兾(1 NRAagm兾100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and exportable
parts of the agricultural sector.
b. The RRA is defined as 100*[(100 NRAagt )兾(100 NRAnonagt ) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural and
nonagricultural sectors, respectively.
217
218
Distortions to Agricultural Incentives in Africa
Figure 7.2. NRAs for Agricultural and Nonagricultural
Tradables and the RRA, Zimbabwe, 1955–2004
80
60
40
percent
20
0
20
40
60
80
03
00
20
97
20
94
19
91
19
88
19
85
19
82
19
79
19
76
19
73
19
70
19
67
19
64
19
61
19
58
19
19
19
55
100
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by authors.
Note: For the definition of the RRA, see table 7.2, note b.
figure 7.2. Also shown there are the NRAs for nonagricultural tradables, based on
import tariff protection rates and assumptions about the shares of import-competing production in the total value of nonagricultural tradables production. That
NRA is positive, averaging between 20 and 50 percent, and so further dampened
agricultural incentives, as indicated by the relative rate of assistance, which is even
more negative than the NRA for agriculture.11
Had the exchange rate not been distorted, the agricultural NRAs and RRA
would have been considerably less negative (bottom rows of table 7.2), suggesting
that exchange rate distortions have made a nontrivial contribution to the antiagricultural and antitrade bias.
Policies behind the Distortions
To trace the evolution of distortionary policies in Zimbabwe, it is helpful to divide
the period since 1955 into subperiods, with structural breaks after 1979, 1990,
and 1999.
Zimbabwe
219
1955–1979
The Federation of Rhodesia and Nyasaland maintained the dualistic economy
through land alienation and continued discrimination in labor and factor markets
as well as grain marketing. By 1961, the proportion of land occupied by the
African reserves (22 percent of the total land area) was the same as it had been in
1911. Forcible removal of Africans from elsewhere into these areas had started
under BSA Company rule, and by the 1960s the reserves formed a vast patch of
farms with irregular plots, a high degree of land degradation through soil erosion,
sparse grazing, and depleted trees. Agricultural production in white controlled
areas increased significantly during this period, however, and Zimbabwe (then
Southern Rhodesia) was a significant exporter of maize (Muir 1981a). Domestic
prices were kept above export parity through quotas on domestic sales, hence the
positive NRAs for maize from 1955 to 1960.
Following the unilateral declaration of independence in 1965, the Rhodesian
regime responded to international sanctions with extreme import-substitution
policies and with even more intense discrimination between white and African
farmers. Agricultural output increased strongly in the first decade of this period,
by 13 percent per year in 1965–69 and by 22 percent per year in 1970–74. The
real value of white farmers’ agricultural output increased by 45 percent between
1965 and 1979 (Nziramasanga 1980, p. 39). Livestock production grew faster
than crop production, with most of the increases after 1969 consisting of
increases in the size of white-owned herds. The real value of African agricultural
output, however, did not change significantly over this period, increasing by just
12 percent between 1965 and 1972 and thereafter declining to less than the 1967
level.
A key feature of agricultural policy after the universal declaration of independence was for white farmers to replace tobacco exports with even more maize production, further displacing African growers. The country’s flue-cured tobacco
exports had accounted for 22 percent of total world tobacco exports in the decade
before UDI, during 1954–64, but fell sharply during the UDI period and represented only approximately 11 percent of total world exports by 1979.12 Meanwhile, white farmers’ production of maize increased markedly after 1966, spurred
by government investment in new seed varieties, irrigation, and other services as
well as by price policies.
In addition to the major crops that were controlled by parastatal organizations,
a variety of noncontrolled products were regulated by producers’ associations that
had the power to levy fees on growers, set minimum quality standards, and regulate prices. The most notable of these were the Rhodesian Oilseeds Producers’
Association, the Rhodesian Deciduous Fruit Growers’ Association, and the
Rhodesian Tea Growers’ Association. An umbrella body for the farmers, the
220
Distortions to Agricultural Incentives in Africa
Rhodesian National Farmers’ Union, worked with the producer associations to
improve the producer prices of products, especially those products produced by
white farmers.13
In 1967, the government set up the Agricultural Marketing Authority to
administer four statutory marketing boards, some of which were already in existence. The four boards were the GMB; the Cotton Marketing Board; the Cold
Storage Commission (now the Cold Storage Company), responsible for livestock
and meat products; and the Dairy Marketing Board, now completely liberalized as
Dairibord Zimbabwe Limited for milk and milk products. The marketing authority conducted marketing research for different products, studied marketing channels, and advised the government on marketing policies.
Like the producers’ associations, the monopolistic marketing agencies had the
legal authority to levy fees on growers each year, to set producer prices, and to
control imports. In addition, the Minister of Agriculture had the power to set the
minimum auction floor price of tobacco as well as the production quota. In general, the crops in which Africans did not have a share of the market experienced
rising prices, an indication of the success of the white-controlled producer associations and the national farmers’ union.14 However, the large negative NRAs for
all commodities during the UDI period (other than for wheat up to 1973) show
that these institutions failed to raise producer prices above import or export
parity levels.
In addition to the fundamental injustice of discriminatory land policies, many
other measures continued to penalize African producers during the 1960s and
1970s. For example, special levies were charged on sales to the GMB by black
farmers, which could be as high as 15 percent of the selling price. The money
raised through these levies was paid to the Ministry of Internal Affairs’ African
Development Fund for use in the general development of the communal
(African) areas. Quite like the GMB’s procurement policies, the levy was a form of
discrimination that worsened dualism in the produce market.
One mechanism by which white farmers enjoyed lower marketing costs was by
delivering their produce directly to the marketing boards’ depots, along the railway line. An initial payment was made to those farmers at the beginning of the
harvest period, and the board paid out an adjustment at the end of the season
based on market conditions. Most African farmers were ineligible to sell their produce directly to the marketing boards in this way. They sold their produce through
approved buyers (agents), who in turn delivered it to the marketing boards.
The calculated NRAs are based on white farmers’ prices and apply to producers
close to the rail line. Our data should be seen as an upper bound on the actual
NRA facing an average farmer and seen as clearly understating the negative incentives facing African farmers.
Zimbabwe
221
1980–1990
In the first 10 years after winning independence in 1980, Zimbabwe was characterized by a controlled economy and, in the sphere of land, by some piloting of
land reform models. In 1982, the resettlement areas were introduced. These consisted of land originally purchased from large-scale commercial areas by the
Mugabe government for resettlement of selected black farmers. Tenure in the
resettlement areas was broadly similar to that of the communal areas, with openaccess grazing areas and individually held cropping areas. By 1985, however, the
resettlement program had run out of steam and concern rose over the government’s neglect of land reform.
To stimulate agricultural production in the communal areas, extension services
were greatly expanded in the early 1980s, and marketing services were extended
into remote areas. Thus marketing operations before 1980 were mostly commercial and geared to marketing farm products produced mainly by large-scale commercial farmers; during the 1980s marketing operations were expanded to communal areas in response to government social and strategic goals. The GMB had
both commercial and noncommercial roles. Its commercial roles related to the
purchase, storage, and subsequent sale of agricultural produce to meet profitable
market opportunities. Its noncommercial activities related to price support and
stabilization activities, reserve food stock holdings, and provision of uneconomic
depots as marketing channels for small-holder farmers and consumers in rural
areas. The distortions behind almost all agricultural crops in the 1980s, where all
NRAs were well below zero, arose from government’s desire to maintain the multiple objectives of national food self-sufficiency, food security, low-priced food for
consumers, and access to marketing channels for all farmers wherever they were
located. This led to a set of policies combining higher domestic producer prices
than prevailed in neighboring countries (but still well below border prices), subsidized consumer prices, accumulation and maintenance of strategic stocks, and an
expansion of the depot network.
Subsidies were generally administered at two levels. One was through the trading accounts of the agricultural parastatals, mainly the marketing boards; the
other was through direct payments to millers and processors. Most subsidies went
to the marketing boards, and payments to millers peaked in fiscal 1982/83 (Chelliah 1986). Since colonial days, the government has been nominally committed to
a cheap food policy for urban dwellers and the nonfarm workforce. The payment
of explicit subsidies has mainly benefited urban consumers, who represent a relatively small share of the population (Ndlela, Kanyenze, and Munemo 1999). On
balance, price policy operated at the expense of the poor majority in rural areas
who are dependent directly or indirectly on agriculture for their livelihood.
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Distortions to Agricultural Incentives in Africa
1991–1999
Under the economic structural adjustment program launched in 1990, the government liberalized the previously tightly controlled economy. Price and interest
rate controls were unwound, trade was liberalized, and some of the public enterprises, including the dairy and cotton marketing boards, were privatized and commercialized. The liberalization of the cotton sector led to wider geographical distribution of production, more provision of training and extension, and an
increase in input credit, all of which had a positive impact on cotton production.
In addition, a well-organized and efficient private seed company took over the
production of cotton planting seed.15
After being controlled for more than 60 years, maize was decontrolled in 1994,
allowing farmers to sell to whomever they chose. However, the GMB was not privatized like other parastatals and retained its monopoly over maize imports and
exports. The decontrol period was short-lived; in 2000–01, the government
reasserted control by passing a statute that criminalized the sale of most grains to
any entity other than the GMB—even sales to a starving neighbor.
The shift in policy from the strict controls of the 1980s to the liberalized regime
of the 1990s is not reflected in a change in the NRAs. That is largely explained by
the pace and structure of the domestic liberalization in the marketing of grains,
which left the GMB with a continued monopoly over international trade. During
the brief period that domestic marketing of maize was liberalized, however, the
structure of maize and maize meal markets changed significantly. The previously
single-channel marketing system became a dual market, consisting of private and
official segments.
After liberalization, the private sector consisted of farmers, traders, and hammer
mills. These operated legally in noncommercial or communal farming areas starting in the 1992 marketing season and in commercial areas and industrial mills
starting with the 1994 marketing season. The private segment of the market flourished in this partially deregulated environment, capturing an increasing share of
maize and maize meal markets at the expense of the official market (represented by
the GMB and industrial millers), which witnessed an erosion of its market share.
During the liberalization period, the GMB still operated under a political mandate to honor a fixed producer price for all farmers during the entire marketing
season. Such panterritorial and panseasonal pricing relied on cross-subsidization
and could not be maintained in a liberalized market, because private traders could
always undercut the GMB in the most accessible markets and force the GMB to
incur ever-larger transport and storage costs. Liberalization also made it harder
for the GMB to defend preannounced prices, because volumes were highest in
years when the GMB was most likely to lose money.16
Zimbabwe
223
The reform measures effectively reduced the GMB to a residual buyer or seller
of maize (and other crops), depending on the relationship between the preset producer price and the price that emerged in the private sector. The GMB found itself
in the unenviable position of having to purchase large maize surpluses even in
normal years but able to sell maize domestically under exceptional circumstances
such as drought. In the 1993–94 marketing season, which followed a good harvest,
the GMB losses were estimated at Z$1.4 billion, or roughly 4.6 percent of GDP,
which was normally absorbed by the state treasury at taxpayers’ expense.17
The massive fiscal cost of GMB losses in the early 1990s had a major impact on
the government’s ability to meet its other objectives. In particular, the objective of
poverty alleviation was not achieved, because the bulk of GMB’s purchases continued to come from large-scale commercial farmers rather than smallholders. In
the 1990s, an average of 74 percent of the GMB’s purchases originated from only
5 percent of all farms in Zimbabwe (Chipika 1994). In the 1993–94 marketing
season, the major beneficiaries of GMB support prices were 1,360 large-scale
commercial farmers and 4,470 small-scale commercial farmers (for more detailed
information, see Collier and Foroutan 1996). In effect, access to the GMB limited
the cost to these producers of the government’s other policies. Even so, except for
the years 1995 and 2000, the calculated NRAs that apply to farmers located close
to GMB depots remained strongly negative.
When the domestic maize milling market was liberalized in 1993, consumers
gained access to cheaper “straight-run” maize meal from local hammer mills,
which quickly gained market share at the expense of the more processed products
from larger-scale roller mills.18 Whereas 70 percent of urban households consumed roller meal in March 1993, only 23 percent did so by December 1993, with
a commensurate rise in consumption of the straight-run meal. However, this shift
depended on a supply of maize gain from the liberalized market outside the GMB.
During the 1990s, most small-scale millers were eventually forced to close down
because of the high costs associated with inadequate supplies of maize (Ndlela,
Kanyenze, and Munemo 1999, p. 41).19
Low production of maize and other crops during the liberalization period was
caused in part by price policy, but also by inadequate infrastructure and farm
technology, particularly for communal areas. For example, the GMB had no maize
input scheme similar to that provided for cotton, so it was very difficult for farmers to obtain fertilizer and seeds. Furthermore the liberalization coincided with a
reduction of public resources for crop improvement research and extension. Negative NRAs for output were to some extent offset by subsidies to inputs, although
in Zimbabwe there have never been generalized input subsidies. In particular, fertilizers were not explicitly subsidized, although there were fertilizer price controls
that led to rationing and misallocation of fertilizer to areas other than the most
224
Distortions to Agricultural Incentives in Africa
profitable ones (WTO 1995, p. 55). In-kind grants of both seed and fertilizer were
periodically made to farmers, especially small-holders, as part of drought relief
programs.
The most successful input supply program was the Cotton Inputs Scheme,
which began in 1992 with the assistance of the World Bank. Under the scheme, the
Cotton Marketing Board supplied cotton inputs on credit to growers, most of
whom were small-holders, and the loan was repaid when the cotton was marketed. After the cotton industry liberalization in 1995, the cotton board’s successor, Cottco (Cotton Company of Zimbabwe), was the only company that offered
an input credit scheme. Farmers who had received Cottco inputs were then able to
sell their output to other traders, who offered higher prices in part because they
were not providing input credits, and in part because they accepted low-quality
cotton without imposing Cottco’s grading standards. Quality suffered, which in
turn threatened to erode the high premium Zimbabwe cotton enjoyed in the
international market (Goreux 2003, p. 16). This has not been solved, but a larger
number of cotton ginning companies are participating in the input credit scheme
to expand supply.
The monopsony position of cotton companies in purchasing from farmers
goes a long way to explaining why large negative NRAs persist for cotton after liberalization (Goreux 2003). What is more difficult to explain is why high rates of
negative assistance persist for other liberalized crops. One plausible explanation is
that the monopsonistic buying that is evident in the cotton sector is also present
in the cereal and oilseed crops sectors, where the buyers operate in specific localities in which competition is relatively limited. For the entire 1995–99 period, this
“market imperfection margin” may have been as large as 36 percent across all
crops, ranging from a low of 24 percent for maize to a high of 74 percent for
sorghum. The kinds of policy change that would be needed to eliminate this tax
on farmers involve greater competition among more diverse firms, and so would
take longer to implement than most “stroke of the pen” reforms.
After 2000
After 2000, a dramatic deterioration in agricultural productivity occurred as a
result of the fast-track land reform program, coupled with the effects of macroeconomic mismanagement which led to shortages of imported inputs such as
fuel, seed, and fertilizer as well as the disruption of research and extension services, input supplies, and marketing systems. While the need for land reform was
long overdue, the manner in which it was done was clearly never intended to solve
the land question. As shown by the government’s own land audits (Government
of Zimbabwe 2003), ruling party stalwarts were given multiple farms while
Zimbabwe
225
millions of hectares lie fallow and farmers in all tenure systems have had to go
without inputs year after year.20 The fast-track land reform program involved
wanton destruction of agricultural infrastructure, which subsequent massive subsidies have failed to address. The collapse of the agricultural sector, which had
strong forward and backward links with other productive activities and commercial services, was a major contributor to the precipitous decline in the performance of the entire economy.
The fundamental agricultural policy change in the new millennium was the
reversal of the 1994 decontrol of the maize market. In 2001, the government
reclaimed controlled of maize and wheat marketing and criminalized any selling
of maize by farmers even to their neighbors, let alone to independent market players. In an environment of accelerating inflation, the prices the government offered
to farmers failed to take account of rapidly rising prices elsewhere in the economy.
It is not surprising that by 2003 the NRAs of the major crops had fallen to all-time
lows, on the order of 90 percent. Maize producer prices were relatively higher
than those for other crops, though, with the maize NRA in 2003 at 44 percent.
Prospects for Reform
To say that the policies of the Mugabe government fall short of what is needed
to address the deteriorating economic situation in Zimbabwe would be a gross
understatement. The measures that are needed to stabilize the economy, such as
strong fiscal adjustment, full liberalization of the exchange rate regime, and
strengthening reforms for the agricultural sector, are a distant prospect.
The crisis in the agricultural sector and the economy as a whole is politically
induced, and until such time as there is a political realignment that allows a bold
change in policy direction, the economic outlook will remain bleak, with particularly detrimental effects on the poorest segments of the population. It is only
political change that will allow the basic conditions for economic recovery to be
restored. These include the reestablishment of the rule of law, including respect
for private property rights, and the formulation and implementation of a comprehensive program to address the crisis in a systematic and internally consistent
manner.
Political change is also a prerequisite for addressing the land question in an
equitable and balanced fashion. A satisfactory solution to this issue is vital for the
resolution of Zimbabwe’s deep socioeconomic crisis. Once there is a regime
change, the challenge will be for the authorities to implement a comprehensive
package of macroeconomic policies and structural reforms to lay the basis for sustained growth, low inflation, and external viability. Overarching policies for the
restoration of the agricultural sector will be needed—policies that are aimed at
226
Distortions to Agricultural Incentives in Africa
restoring and enhancing the productivity of the sector as a whole, integrating different modes of production to overcome dualism, and reducing the historically
entrenched distortions to agricultural incentives.
Notes
1. See Ndlela and Robinson (2007, appendix table 1 and, for the apportionment of land, appendix
table 2).
2. From the beginning of colonial administration, native reserves (now communal lands) were set
aside for exclusive use by Africans. These reserves were administered directly by the central government, albeit remaining “traditional” in that traditional leaders retained rights to allocate arable plots
among local households, while grazing was open for those households. Methods of cultivation were
similar to those used before colonialism, but with much higher population densities and therefore
lower levels of production per person. See Riddell (1978, pp 6–11).
3. Gideon Gono, governor of the Reserve Bank of Zimbabwe, bemoaned this fact while increasing
the levels of support to agriculture in a monetary policy statement issued in October 2005.
4. The BSA Company refused to sell land to leading Ndebele households, even though they could
afford to buy it. The company also refused to sell land to the Fingo Community, migrants from South
Africa who had been invited by Cecil Rhodes to settle in Rhodesia (Loney 1975).
5. This is equivalent to 198,000 bags, and each bag weighed 200 pounds.
6. Some other products were initially controlled and later removed from the controls list: beans in
1959, bulrush millet in 1962, and finger millet (rapoko) in 1965.
7. Over the study period (1955–2004), the average proportion of foreign exchange sold on the parallel market was 0.122. This figure rose sharply in 2002–03 (to 65 percent) and in 2004–05 (to 75 percent). During the five decades, official transactions for the main agricultural commodities took place
at official exchange rates. Trading was the preserve of the GMB (for coarse grains including maize) and
the Cotton Marketing Board/Cottco (for cotton seed and lint).
8. The largest recorded subsidy before hyperinflation set in was in early 2006, when the GMB
purchased a metric ton of maize from farmers for $31,200 and sold it to millers for just $6,500. The
potential profit of $24,700 for each metric tone provided a huge incentive for the maize to be resold by
the millers back to the GMB, a practice known as “round tripping.”
9. Year-by-year data are given in Ndlela and Robinson (2007, appendix table 8). The production
shares of the crops covered by this study are shown in Ndlela and Robinson (2007, appendix figure 1),
together with their tradability status (exportable, import-competing, or nontradable), while household consumption shares of the food crops covered are given in appendix table 2.
10. The exchange rate influence is evident in Ndlela and Robinson (2007, appendix figure 3). When
calculated at the official exchange rate, the NRAs are less negative for most time periods and, for the
2000–2004 period, turn from negative to positive. See the bottom rows of table 7.2 in this chapter.
11. From 2004, large direct subsidies to agricultural inputs have been provided. Ostensibly, these
subsidies are in recognition of the need to restore agricultural production following the chaotic land
reform program. However, distortions elsewhere in the economy are such that many farmers divert the
subsidies into direct profits (by selling subsidized fuel on the parallel market, for example) or into
other channels (such as investing low-interest loans in financial markets). As a result, agriculture is not
being revived by those direct subsidies.
12. Virginia flue-cured tobacco, which was grown almost exclusively by European farmers in the
1965–79 period, was a “controlled crop.” Its marketing was regulated by and controlled by the Tobacco
Marketing Board, which in turn was under the umbrella of the Agricultural Marketing Authority.
13. After independence in 1980, the Rhodesia National Farmers’ Union became the Commercial
Farmers’ Union and continues to represent the commercial farmers, while the majority of small and
indigenous farmers are represented by the Zimbabwe Farmers’ Union.
Zimbabwe
227
14. For example, the Tobacco Association, which carried out tobacco surveys to document production costs and had a say in the minimum price, assisted the minister in setting minimum prices. Thus
tobacco remained a profitable crop despite the economic sanctions.
15. The Cotton Company of Zimbabwe has interests in two seed producers, holding a 100 percent
interest in Quton Seed Company, which produces cotton planting seed, and a 40.5 percent share in
Seed Co Limited (listed separately on Zimbabwe Stock Exchange). It produces and markets maize seed
and other crop seeds.
16. The GMB had no way of knowing whether farmers would deliver maize to its depots or to the
private market after deregulation. If the producer price is not consistent with the private sector’s valuation of maize, the GMB cannot compete effectively in a deregulated environment. By definition, the
producer price announced before the start of the planting season could not be adjusted later to reflect
market conditions. It is more than likely that the announced price would be at variance with the private sector’s valuation of maize.
17. The GMB loss includes all handling, storage, transport, administrative, and financial losses
associated with maize marketing.
18. Straight-run maize meal is referred to as mugaiwa in Zambia, and although not officially
referred to by that name in Zimbabwe, mugaiwa is commonly used in Zimbabwe.
19. With the reintroduction of maize marketing controls and the demise of the small-scale hammer millers after 2000, Zimbabwean consumers are now back to consuming roller meal.
20. President Mugabe is on record as having said “It’s clear we . . . have serious bottlenecks in the
system of procuring and supplying inputs to our people now on the land. . . . The farmer prepares for
the season diligently, only to be failed by the various arms of government.” Closing remarks at his 2005
Party Congress at Esigodini, as reported by Sunday Mail, December 11, 2005.
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Ndlela, D. B., G. Kanyenze, and J. Munemo. 1999. “A Review of Pricing Policy in a Liberalized Environment in Zimbabwe: The Case of Basic Commodities.” Paper prepared for the National Economic
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Ndlela, D., and P. Robinson. 2007. “Distortions to Agricultural Incentives in Zimbabwe.” Agricultural
Distortions Working Paper 39. World Bank, Washington, DC.
Nziramasanga, M. 1980. “Agricultural Sector in Zimbabwe: Prospects for Change and Development.”
In Zimbabwe Towards the New Order, An Economic and Social Survey. Working papers, vol. 1,
UNCTAD/MFD/19, UNDP PAF/78/010. Geneva: United Nations.
Palmer, R. 1977. Land and Land Discrimination in Rhodesia. London: Heinemann.
Riddell, R. C. 1978. The Land Problem in Rhodesia: Alternatives for the Future. Gweru, Rhodesia:
Mambo Press; London: Catholic Institute of International Relations.
WTO (World Trade Organization). 1995. Trade Policy Review: Zimbabwe 1995. Geneva: WTO.
Yudelman, M. 1964. Africans on the Land: Economic Problems of African Agricultural Development in
Southern, Central and East Africa, with Special Reference to Southern Rhodesia. Cambridge, MA:
Harvard University Press.
Part IV
EASTERN AFRICA
8
Ethiopia
Shahidur Rashid, Meron Assefa,
and Gezahegn Ayele*
Over the past half century, Ethiopia has gone through three ideologically distinct
political regimes: the monarchy, from 1950 to 1974; central planning (by the
Dergue, meaning committee), from1974 to1991; and the regime that has been in
power since the collapse of Dergue in May 1991.1 Each shift in political regime has
been marked by dramatic change in economic policies with direct implications
for the agricultural sector both in access to factors of production and in marketing
of inputs and outputs.
During the monarchy, the land tenure system was complex, private transfer of
land was practically nonexistent, and ownership was skewed, with the state and
the church maintaining control over large shares of agricultural land.2 In fact,
opposition to the land tenure system mobilized rural peasants and urban intelligentsia with the popular slogan “land to the tiller” and was one of the central
forces that eventually brought down the monarchy in 1974.
After the 1974 revolution, the Dergue government introduced all aspects of a
centrally planned economy. It nationalized rural land, abolished tenancy, ordered
all commercial farms to remain under state control, redistributed lands, and maintained a highly overvalued currency.3 The most direct interventions fixed panterritorial grain prices, restricted private grain movements across regions, and set
quotas for grain production (Lirenso 1987; Franzel, Colburn, and Degu 1989).
* The authors are thankful to Taddasse Kumu for sharing his data on the coffee and hides and skins
markets, to Kassu Wamisho for providing various macroeconomic data, to Abera Birhanu for providing information on the chat markets, and to Alemayehu Seyoum for insightful discussions. The
authors are also grateful for helpful comments from workshop participants. Detailed data and
estimates of distortions reported in this chapter can be found in Rashid, Assefa, and Ayele (2007).
231
232
Distortions to Agricultural Incentives in Africa
The outcomes of these policies are well known: economic growth was thwarted,
farmers smuggled cash crops to neighboring countries (to circumvent highly overvalued exchange rates), and civil strife gained momentum. To make matters worse,
a devastating famine hit the country in 1984. The problems became even more
acute in the late 1980s, when Soviet assistance decreased and armed insurgencies in
the north escalated. The Dergue eventually collapsed on May 28, 1991.
Following the fall of the Dergue regime, a transitional government embraced
market-oriented economic polices. It adopted structural adjustment programs,
abolished agricultural price controls, established macroeconomic stability, and
emphasized agriculture as the priority sector in a strategy document called
“Agricultural Development Led Industrialization.” According to many studies, the
reforms paid off, but the country is still struggling to transform its agriculture.4
While the agricultural sector has registered an average annual growth rate of
1.7 percent since 1992, both production and prices continue to be more volatile
than they are in most other developing countries, and the government has occasionally used public enterprises to intervene in agricultural markets to ensure
price stability and an adequate distribution of inputs.5
This chapter traces the broad policies under the three different political
regimes and examines how each affected agricultural incentives, economic
growth, structural changes, and poverty over time. The chapter examines the
trends in growth and structural changes across sectors and within agriculture; catalogs changes in agricultural pricing, taxation, and investment policies; and estimates the extent of distortions to agricultural incentives for selected commodities.
The analysis itself covers the period 1981 to 2005 and generates estimates of distortions for eight commodities, which together account for about 80 percent of
Ethiopia’s export value and about 60 percent of agricultural value added.6
Historical Overview of Politics
and Economic Policies
The Ethiopian state originated in the Aksumite kingdom.7 It emerged as a trading
state around the first century, with trading relations with the Byzantine Empire,
Egypt, and the Arabic peninsula. Since then, Ethiopia has traveled a very long and
troubled path in history which, in many respects, is unique in Africa. This chapter
takes up the story starting in the mid-1950s when the monarchy, led by Haile
Selassie, formulated the first five-year plan (1957–61) in the country’s history.
Three key messages emerge from the major political events and economic policies of the past half century. First, throughout its modern history, Ethiopia has
suffered from political instability. Among other problems, the monarchy survived
a coup attempt in the early 1960s and encountered strong insurgencies from the
Ethiopia
233
Eritrean Peoples’ Liberation Front and from the increasing discontent of tenant
farmers and the urban intelligentsia. The first few years of the Dergue regime were
filled with internal conflicts, violence, and bloodshed until Mengistu Haile
Meriam came to power in 1977. Even then, however, the regime was constantly
challenged by regional rebel groups, most notably the Eritrean People’s Liberation
Front and the Tigray Peoples’ Liberation Front, which eventually forced Mengistu
into exile in Zimbabwe in 1991. While the country has enjoyed relative stability in
recent years, the current government has faced difficulties in the past and continues to face occasional civil strife. After Eritrea gained its independence in 1993,
the tensions between the two countries continued. In May 1998, a dispute over the
undemarcated border with Eritrea led to a war between the two countries that
lasted until June 2000. More recently, following a disputed general election, political violence erupted in several places in June and November 2005.
Second, Ethiopia has embraced all dominant ideologies and associated economic policies since the mid-1950s. As part of its five-year plan, the monarchy
adopted an export promotion strategy with an elaborate incentive package to
attract foreign direct investment. When the economic outcome did not meet
expectations, the government adopted a strategy along the lines of PrebischSinger import substitution, which the regime continued until its fall in 1974. The
Dergue clearly embraced a socialist view of the world, imitating almost all aspects
of economic management that the Soviet Union had developed. The current government adopted a more liberal approach, implementing many aspects of the
World Bank–International Monetary Fund structural adjustment program, which
included devaluing its currency and taking measures to establish macroeconomic
stability. The reforms in the agricultural sector included removal of all restrictions
on private trade, elimination of officially fixed prices, removal of compulsory
delivery quotas, and abolition of grain rationing to urban consumers.
Finally, albeit with varying degrees, each regime has exerted some form of control over agricultural markets. The monarchy used two control mechanisms: large
state ownership of land with very limited property rights; and control of international trade through state enterprises.8 The Dergue regime controlled almost all
aspects of the agricultural markets: it outlawed private ownership of land holdings over 10 hectares, abolished rural wage labor, set production quotas and agricultural prices, and empowered state enterprises to control practically all aspects
of agricultural markets (EEA 2000; Zewde 2002). The most pervasive distortion in
Ethiopian agriculture during this regime was control over farmgate prices
through the Agricultural Marketing Corporation, which imposed fixed prices and
sales quotas that ranged from 50 to100 percent of traders’ turnover and from 10 to
50 percent of the farmers’ harvest at prices consistently lower than market prices
(Dercon and Lulseged 1995; McCann 1995).
234
Distortions to Agricultural Incentives in Africa
After the fall of Dergue, the new government gradually eliminated many of the
government controls. However, it supported 24 public enterprises in 2001, which
incurred a net loss of Ethiopia Birr (Br) 51.5 million (equivalent to about
US$6.5 million) and reported a net retained earnings of Br 1.65 billion (or
$19.1 million). In 2005, the number of public enterprises was reduced to 19, and
the net loss declined to about Br 24.8 million (about $2.8 million). However, the
agricultural input marketing parastatals continued to dominate the markets. In
2005, the Agricultural Input Supplies Corporation controlled more than 80 percent of the market in improved seeds, chemical fertilizers, and pesticides.9
Over time, shifting economic philosophies and government control of farm
production and prices have severely affected agricultural development in the
country. The most direct consequence was perhaps the reduction of public spending on agriculture when public resources were diverted to finance wars and subsidize public enterprises.10 During the Dergue regime, expenditure on agricultural
research, as well as on other social development, remained flat. Agriculture
received more public funding than other social sectors, however, because agricultural expenditure included subsidies to public enterprises, which were a large part
of total expenditure on agriculture. According to one study, between 1977 and
1990, state farms nearly quadrupled their holdings, from 550,000 hectares to
2.1 million hectares, absorbing 64 percent of all public expenditure on agriculture
and accumulating a net loss of approximately $300 million (Rahmato 1990;
McCann 1995).11
Economic Growth, Structural Changes,
and Poverty
Since 1960, economic growth rates have varied significantly both across and within
each of the three political regimes. Table 8.1 shows that during the monarchy, the
economy fared relatively well compared with the other two regimes. Although per
capita rates were negative in a few years, the overall growth rates in all three sectors
were positive between 1961 and the monarchy’s collapse in 1974. On average, GDP
(gross domestic product) grew at 3.7 percent, agriculture at 2.1 percent, and both
industry and the service sector at more than 7 percent during 1961–73.12 The
structure of the economy also changed. The share of agriculture in GDP declined
from 76 percent in 1961 to 62 percent in 1973, and the shares of both industry and
services grew by 3 percent and 11 percent, respectively.
The Dergue regime did more harm to agricultural production than the other
two regimes. On average, the agricultural sector registered a little more than half a
percentage point growth, and both total GDP and sectoral GDP suffered negative
growth rates in a number of years. Overall GDP growth rates were negative in
Ethiopia
235
Table 8.1. Economic Growth and Structural Changes, Ethiopia,
1961–2004
(percent)
Monarchy (1961–73)
Sector
Total GDP
Agriculture
Industry
Services
Dergue (1974–90)
Current (1991–2004)
Growth
ratesa
Shares
in total
GDP
Growth
ratesa
Shares
in total
GDP
Growth
ratesa
Shares
in total
GDP
3.7
2.0
7.0
7.3
100
68
9
23
2.0
0.6
3.6
3.8
100
56
11
33
4.6
2.3
5.3
6.9
100
47
11
42
Source: Computed by the authors from various publications of the National Bank of Ethiopia.
a. Growth rates are calculated by fitting a log-linear trend.
9 years of the Dergue’s 17-year rule, agricultural growth rates were negative in
11 years, and industrial growth in 7 years. Declines in growth rates of GDP and
in the agricultural sector were as much as 12 percent and 15 percent in the
mid-1980s.
The withdrawal of the government from agricultural markets in the early
1990s provided a much-needed boost to agricultural production and, given its
large share of GDP, to the overall economy. Between 1992 and 2004, the country
achieved an overall GDP growth of 4.6 percent per year, agricultural growth of
2.3 percent, industrial growth of 5.3 percent, and services growth of about 7 percent. The share of agriculture in the total economy declined from 56 percent in
fiscal 1991/92 to about 42 percent in fiscal 2003/04.13 The most significant growth
in agriculture took place in the early 1990s, mostly driven by expansion of crop
area in response to liberalization, the strong emphasis on extension, and a creditled push toward agricultural intensification. The growth slowed in the later part of
the 1990s, however, and the country experienced large fluctuations in both production and prices. As a result, per capita agricultural GDP and per capita grain
production continued their long-term decline, at 1.8 and 0.6 percent, respectively (Byerlee et al. 2006).
Economic growth and structural changes affect poverty and food security in
complex ways, and assessment is hampered also by the unavailability of historical
data on poverty. The World Development Indicators published by the World Bank
have only two estimates of headcount poverty for Ethiopia, one for 1996 (46 percent) and the other for 2000 (44 percent). Similarly, the State of Food Insecurity put
out by the UN’s Food and Agriculture Organization (FAO) has information only
for a few years. As an alternative, we use two crude measures, namely, food availability and the food gap, to assess changes in poverty and food security. (The food
236
Distortions to Agricultural Incentives in Africa
monarchy
Dergue
current
8
7
6
5
4
3
2
1
0
19
6
19 1
6
19 3
65
19
6
19 7
6
19 9
7
19 1
73
19
7
19 5
7
19 7
7
19 9
8
19 1
83
19
8
19 5
8
19 7
8
19 9
9
19 1
93
19
9
19 5
9
19 7
99
20
01
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0
food gap (millions of metric tons)
per capita food availability (quintal)
Figure 8.1. Food Availability and Food Gap by Political Regime,
Ethiopia, 1961–2002
year
food gap
per capita food availability
Source: FAOSTAT, Ethiopian Ministry of Agriculture, and the National Bank of Ethiopia.
gap is defined as the population’s basic food requirement of 220 kilograms of
cereal per capita per year less net cereal production domestically.) These data are
presented in figure 8.1.14 They indicate that the food gap has increased since the
early 1980s but that per capita food availability has remained relatively stable over
the years; that food availability was high and stable during the monarchy, and that
despite relative stability and higher economic growth, food security has not
improved under the current regime.
The generous inflow of food aid starting in the 1970s helped keep food availability relatively stable. Food aid averaged 388,230 tons a year during the Dergue
and 715,345 tons a year during 1991–2002.15 The higher and more stable per
capita food availability during the monarchy is consistent with the relatively stable
economic growth observed during the period.
Why has food security not improved under the current regime, despite significant liberalization and relatively robust growth? A possible explanation may be
that most of the cereals grown in Ethiopia are nontradable, and their production is
largely weather dependent. Only about 10 percent of the total cereal cropland is
irrigated, and yield variability at the regional level is one of the highest in the
developing world (World Bank 2006; Rashid, Cummings, and Gulati 2005). Therefore, while liberalization resulted in positive supply responses for most cash crops,
the cereal sector lagged behind. Without technological innovation and reduction
in transactions costs, relative stagnation in cereals production is unlikely to change
Ethiopia
237
in the near future. This is a reason for concern, as the cereals subsector is the largest
employer in agriculture and accounts for about 50 percent of agricultural value
added (GOE 1998). Indeed, a recent study concludes that growth in staple crops
has the highest potential to reduce poverty in Ethiopia (Diao et al. 2005). Specifically, this study predicts that, between 2003 and 2015, annual growth of 2.1 percent in cereal yield combined with 1.3 percent annual expansion of the growing
area would result in poverty reduction of 10 percent a year, with 3.9 percent
annual growth in GDP and 3.5 percent annual growth in agricultural GDP.
To summarize, while each regime change is marked by heroic efforts of
Ethiopians to embrace new ideas and policies, their livelihoods and well-being
have changed little. The Human Development Index worsened between 1987 and
1996, the food gap increased from 0.75 million tons in 1979 to 6 million tons in
the 1990s and early 2000s, and the country has become increasingly dependent on
food aid to feed its populations (EEA 2004).
Measuring Distortions to Agricultural Incentives
The main focus of the current study’s methodology (Anderson et al. 2008) is on
government-imposed distortions that create a gap between domestic prices and
what they would be under free markets. Because the characteristics of agricultural
development cannot be understood from a sectoral view alone, the project’s
methodology not only estimates the effects of direct agricultural policy measures
(including distortions in the foreign exchange market) but also generates estimates of distortions in nonagricultural sectors for comparative evaluation.
More specifically, this study computes a nominal rate of assistance (NRA) for
farmers that includes an adjustment for direct interventions in input markets. It
also generates an NRA for nonagricultural tradables, for comparison with that for
agricultural tradables, through the calculation of a relative rate of assistance (RRA).
A large share of Ethiopian agricultural products is nontradable. This subgroup,
which includes almost all cereals and tubers, accounts for about half of all agricultural value added. There are no subsidies (or taxes) on these products except for
emergency food assistance and food distribution under social safety net programs.
However, the country has consistently received large volumes of food aid that
influence the markets for these products. 16 Given the significance of food aid in
Ethiopia, we need to incorporate the effects on agricultural incentives of the government’s decision to accept food aid.17 If the food aid depresses prices, it implicitly serves as both a consumer subsidy and a producer tax. We calculate the rate of
that distortion as the product of the percentage change in cereal availability attributable to food aid and the inverse of the price elasticity of demand. Since food aid
comes mostly in the form of wheat, we calculate the change in the wheat price by
238
Distortions to Agricultural Incentives in Africa
using its own-price elasticity and the cross-price elasticity (with respect to wheat)
for the other two key cereals, teff and maize. With this qualification, the formula
in Anderson et al. (2008) for the NRA and the CTE (consumer tax equivalent) for
nontradables becomes
NRA ⫽ CTE ⫽
bi ⫻ h⫺1
i
(1 ⫹ e/h)
,
(8.1)
where bi is the percentage change in total cereal availability and h and e are the
own-price elasticities of supply and demand, respectively.
Data and product coverage
Price and quantity data were collected from various local and international
sources. Local sources include the National Bank of Ethiopia (NBE), the Central
Statistical Authority (CSA) of Ethiopia, the Ministry of Agriculture, the Ministry of
Finance and Economic Development, and the Ethiopian Economic Association.
Although data for some variables were available from multiple sources, reconciling
them was a difficult task. For instance, free on board (fob) prices for exports are
available from a number of local sources as well as from the FAO, but the differences in any given year are as high as 100 percent. In general, we found NBE data
on macroeconomic variables, CSA data on prices, FAO data on production, and the
transaction costs data from the finance ministry to be more consistent across years.
In years when differences were large, data from the most authoritative available
source was used in the analysis. The policy review did not pose any significant
problem, because most of the information was available from a government publication called Negarit Gazeta, which is often synthesized by the Ethiopian Economic
Association.
The NRAs are calculated for five exportable commodities and three nontradable commodities that dominate Ethiopian agriculture. Although the country is a
large recipient of food aid, commercial import (or export) of cereals is limited
because of a large gap between the fob export price and the cost, insurance,
freight, or cif, import price. According to various NBE publications, agricultural
imports as a percentage of agricultural exports have ranged from 14.6 percent
during 1986–90 to only 5.5 percent during 1993–2000. There is very little importing of commodities except food aid. On the export side, the analysis includes all
five exportable commodities, which have historically accounted for more than
80 percent of total agricultural export values. Furthermore, the analysis includes
the three major cereals, which are commonly regarded as nontradable and whose
domestic prices have been depressed by the government’s policy of accepting food
aid from abroad, as explained using equation 8.1.
239
Ethiopia
NRA results for agriculture
A summary of commodity-specific NRA estimates is presented in table 8.2. For
the main products, the NRAs became more negative through the 1980s and early
1990s but have since turned less negative as a consequence of recent reforms. The
exceptions that still have high negative NRAs are chat (a minor stimulant leaf
from an evergreen shrub) and hides and skins, but they account for only about
1 percent of the value of agricultural production. The decline is most pronounced
in the cases of coffee and pulses, which have received more policy attention since
the late 1990s. The weighted average NRA of all commodities, both tradable and
nontradable, also declined, and in 1995–2005, it was only two-thirds of the average for 1990–94 (13 instead of 22 percent). This trend is consistent with the
country’s liberalization program, which withdrew price controls and reduced
export taxes in the mid-1990s and eliminated them by 2002. The trend for chat is
different, mainly because it has always remained outside of parastatal control, and
its export continues to be taxed at 29 percent.18 The lack of any change in the NRA
for hides and skins may be rather surprising, particularly because a number of
government initiatives have been designed to improve the sector.19
Table 8.2. NRAs for Covered Farm Products, Ethiopia, 1981–2005
(percent)
Product indicator
a
Exportables
Pulses
Chat
Hides and skins
Oilseeds
Coffee
Nontradablesa
Wheat
Maize
Teff
Total of covered productsa
Dispersion of covered
productsb
Percent coverage
(at undistorted prices)
1981–84
1985–89
1990–94
1995–99
2000–05
33.8
32.6
52.4
46.9
43.3
28.5
5.6
6.9
4.3
4.9
11.9
26.4
44.9
56.3
45.3
49.8
48.2
32.7
8.4
10.6
6.6
7.6
15.0
28.2
48.0
52.0
45.1
51.6
57.2
38.5
9.3
11.8
7.4
8.5
17.1
28.0
40.0
35.1
43.0
49.0
52.5
36.4
4.8
6.1
3.8
4.3
9.7
29.1
17.5
17.7
39.5
48.4
40.1
6.2
5.5
4.4
6.1
7.0
6.8
20.6
61
60
60
59
61
Source: Data compiled by the authors.
a. Weighted averages, with weights based on the unassisted value of production.
b. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean
of NRAs of covered products.
240
Distortions to Agricultural Incentives in Africa
Table 8.3. NRAs for Agriculture Relative to Nonagricultural
Industries, Ethiopia, 1981–2005
(percent)
Indicator
1981–84
1985–89
1990–94
1995–99
2000–05
11.9
26.1
17.5
15.0
33.4
22.3
17.1
35.3
24.4
9.7
29.5
17.8
6.8
14.6
9.9
33.8
44.9
48.0
40.0
17.5
40.2
51.3
44.5
20.8
11.1
52.6
63.4
63.8
49.8
25.8
10.2
12.0
13.5
15.9
9.9
27.3
28.4
29.6
42.1
25.3
NRA, covered products
NRA, noncovered products
NRA, all agricultural
products
NRA, all agricultural
tradables
NRA, all nonagricultural
tradables
RRAa
Memo item, ignoring
exchange rate distortions:
NRA, all agricultural
products
RRAa
Source: Data compiled by the authors.
a. The RRA is defined as 100*[(100 NRAagt )/(100 NRAnonagt ) 1], where NRAagt and NRAnonagt
are the percentage NRAs for the tradables parts of the agricultural and nonagricultural sectors,
respectively.
To the NRA for covered products we need to add our guesstimate of the NRA
for noncovered products. This is shown on the top of table 8.3. Non-productspecific assistance also could be included, but, as shown in table 8.3, we assume that
to be zero. During the central planning regime, the government did provide farmers with inputs through parastatals. However, detailed data could not be obtained
from official sources. In recent years, the government has been distributing fertilizers through cooperatives and extension offices, which enjoy some preferential
treatment such as cheap credit and public warehousing facilities. Arguably, these
are some forms of, albeit implicit, non-product-specific subsidies. However, one
could also argue that these are essential interventions to address market failures, in
which case they should not be included in the NRA calculations.
Although the overall trends of the NRA estimates are consistent with the
country’s policy changes, the magnitudes of the estimates need to be interpreted
cautiously. First, the NRA estimates underestimate changes stemming from liberalization, because the parastatals’ overhead costs during the Dergue regime are
not factored in due to unavailability of data. Byerlee et al. (2006) report that seed
parastatals’ overhead for maize seed is as high as 65 percent of the sale price. If
such costs were factored in for the 1980s, it would be clear that farmers were even
worse off at that time than the NRA estimates for the 1980s suggest.
Ethiopia
241
Figure 8.2. Farmers’ Share of Export Prices for Coffee,
Oilseeds, and Pulses, Ethiopia, 1981–2005
0.90
farmgate price/fob price
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
19
8
19 1
82
19
8
19 3
8
19 4
8
19 5
86
19
8
19 7
8
19 8
89
19
9
19 0
9
19 1
92
19
9
19 3
9
19 4
9
19 5
96
19
9
19 7
9
19 8
9
20 9
0
20 0
0
20 1
02
20
0
20 3
0
20 4
05
0
year
coffee
oilseeds
pulses
Source: Data compiled by the authors.
Second, because the government has almost completely withdrawn from the
market, and because the NRAs account for all the costs (including traders’ opportunity costs) from farmgate to the border, one might argue that the NRAs after
liberalization should have been zero. Our data on transactions costs are less than
perfect, however. For example, transportation costs in Ethiopia are notoriously
unpredictable. Our interviews with traders indicate that transporting a ton of coffee from Sidamo (the main coffee-growing region) can vary from Br 400 to Br 750
within a period of 15 days. Furthermore, the trade margins that we obtained from
official sources may be much smaller than those the traders and exporter actually
incur.
Finally, although farmers’ shares in the final sales price improved in the 1990s,
they continued to remain low. Figure 8.2 shows the farmgate price as a percentage
of the fob price for three products: the farmgate price of coffee in the 1980s averaged about 40 percent of the fob prices—and only 20 percent in 1985—whereas
after liberalization, that share increased to an average of 53 percent, with a high of
80 percent in 2002. Similar patterns are shown for oilseeds and pulses. However,
these numbers are still low relative to other countries. For example, Kenyan coffee
farmers received about 87 percent of the fob prices (Winter-Nelson and ArgwingsKodhek 2007). The numbers for Ethiopia reflect the continuing weakness of the
242
Distortions to Agricultural Incentives in Africa
Figure 8.3. NRAs for Exportable and All Farm Products,
Ethiopia, 1981–2005
10
0
percent
10
20
30
40
50
60
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005
year
exportables
total
Source: Data compiled by the authors.
infrastructure and relatively high transaction costs—factors that the liberalization
program has not changed.
Available calculations suggest that the wholesale prices of all three major
cereals—wheat, maize, and teff—lie within the export and import parity bound
(Rashid, Assefa, and Ayele 2007, appendix figures 3–5), which is why we consider
them nontradable. According to our calculations, these products are much less
heavily taxed than exportables, ensuring that the NRA for all covered products is
far less negative than for exportables alone (table 8.2 and figure 8.3). However,
these calculations do not consider the depressing effects of food aid on domestic
cereal prices. Because food aid has accounted for roughly 25 percent of human
cereal consumption, accounting for food aid affects would significantly change
the figures. Our crude estimates suggest that food aid flows have depressed
domestic prices within the ranges of 2–26 percent for wheat, 3–13 percent for
maize, and 2–11 percent for teff.20 These are conservative estimates, but they are
large enough to change the tradability status of the cereals: all three cereals would
become importable had these negative effects of food aid not depressed the Addis
Ababa wholesale prices. This implies that food aid can distort incentives both for
farmers (through depressing farm prices) and for traders (by distorting their
Ethiopia
243
arbitrage opportunities in domestic and international markets). Thus if one took
food aid as well as price and trade policies into account, one would conclude
that farming has been discouraged even more in Ethiopia than our NRA estimates
suggest.
RRA results
The estimates of relative rates of assistance (RRAs), which also account for
distortions to other sectors producing tradables, are presented in table 8.3 and
figure 8.4. Nonagricultural importables are subject to sizable tariffs, according to
the World Integrated Trade Solution (WITS) database compiled by the UN Conference on Trade and Development (UNCTAD 2006). Using the ad valorem
equivalent of those tariffs as a measure of the NRA for the import-competing part
of nonfarm goods sectors, and assuming exportables are not distorted and that all
services are nontradable, we obtain an NRA for all nonagricultural tradables and
thus can calculate the RRA, as shown in the middle rows of table 8.3.
The broad picture that emerges is that the NRA for nonagricultural tradables
rose in the 1980s as the NRA for agricultural tradables became more negative, so
Figure 8.4. NRAs for Agricultural and Nonagricultural Tradables
and the RRA, Ethiopia, 1981–2005
80
60
40
percent
20
0
20
40
60
80
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005
year
NRA, agricultural tradables
NRA, nonagricultural tradables
Source: Data compiled by the authors.
Note: For a definition of the RRA, see table 8.3, note a.
RRA
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Distortions to Agricultural Incentives in Africa
the RRA shows an even more accentuated fall than the NRAs for agricultural
products in the 1980s and early 1990s. The RRA declined to below 60 percent,
before growing gradually less negative after 1992; the RRA averaged around
25 percent in 2000–05 and just 15 percent in 2005. In other words, policyinduced distortions to farmer incentives in Ethiopia have declined significantly
from their levels before the mid-1990s. The remaining challenges for the country,
apart from bringing those NRAs and hence the RRA closer to zero, are to minimize distortions related to food aid and to reduce the still-high transaction costs
of trade.
Policies behind Agricultural Disincentives
As in many other developing countries, exchange rate controls, prohibitive trade
taxes, and agricultural price policies in Ethiopia have historically been the main
sources of distortions to agricultural incentives. All of these have changed significantly since the early 1990s. This section summarizes the broad changes, relates
them to the measures of distortions presented above, and identifies the areas that
continue to dampen production and trade incentives.
Exchange rate policies
Until the introduction of the auction system in May 1993, Ethiopia had followed a
pegged exchange rate regime, which was one of the most significant sources of
distortion to agricultural incentives. Because the currency was highly overvalued,
a parallel market for foreign exchange flourished. Between 1975 and 1992, the
black market premium for foreign currency averaged 117 percent; at its highest in
1988, it reached 226 percent. One documented consequence was the smuggling of
cash crops to neighboring countries, which reduced official export and foreign
currency earnings.21
After the fall of the Dergue in 1991, the transitional government undertook a
series of measures to realign the exchange rates, including devaluing currency by
more than 100 percent (from 2.5 to 5.5 Ethiopian birr per US dollar), eliminating
foreign exchange rationing, inaugurating foreign exchange auction markets in
1993, allowing commercial banks to open foreign exchange bureaus in 1996, and
permitting foreign exchange trading between banks (GOE 2004). Under the current system, the National Bank of Ethiopia is the sole provider of foreign
exchange, and only authorized banks and investors able to bid for at least
$500,000 are allowed to participate in the auctions, which occur weekly. The marginal rate determined at each auction serves as the official rate until a new rate is
determined during the next auction.
Ethiopia
245
The impact of the reduction in currency misalignment on agricultural incentives is nontrivial compared with the devaluation of 1993. The two bottom rows
of table 8.3 show what the NRAs for agriculture and the RRAs would have been if
exchange rate distortions had been ignored in our analysis; a comparison of these
rows with the corresponding rows above them indicates that the distortions to the
market for foreign exchange accounts for around one-third of the NRA for agriculture as a whole and for about half of the RRA. This contribution is larger than
in many other countries, but that is partly because there are no large importcompeting sectors in Ethiopian agriculture that were benefiting from an overvalued
exchange rate.
Agricultural taxation policies
Heavy agricultural taxation in Ethiopia dates back to 1943, when an elaborate customs and export duties proclamation was issued (Cohen 1987; GOE 1999; Zewde
2002). The complex tax system was applied on the basis of quantity exported or
imported. Taxation on coffee is a good illustration of the nature of the tax system,
which was instituted in the mid-1950s and continued, with minor changes, until
1993. For each ton of coffee exported, an exporter had to pay Br 200 as custom
duty, Br 400 as surtax, Br 15 as a cess tax, and a 2 percent (deducting other taxes)
transaction tax. When added, all these taxes amounted to 11–27 percent of the farmgate price in the 1980s. In addition to these taxes, the government also collected
progressive taxes based on the international price of coffee. Converted to ad valorem rates at the official exchange rate, this tax ranged from about 1 percent
when the international price was $820 a ton to about 15 percent when the international price reached $1,000 a ton.
Since 1993, the tariff structure has undergone extensive reforms. The government has issued a number of proclamations and regulations to revise and streamline the old tax system. These initiatives have brought about five distinct changes
in policy. First, the former system of specific duties and taxes (weight-based) has
almost completely been converted to ad valorem taxes, making tax administration
much more efficient. Second, the maximum tariff has declined from a high
230 percent to 50 percent, and the difference between the maximum and minimum tariff has declined from 225 percent to 45 percent. Third, the proportion of
duty free imports has declined from 60 percent to 3 percent. Fourth, the sales tax
on both imported and exported goods has been reduced to 5 percent on essential
commodities and to a uniform 12 percent on all other commodities (GOE 1999).
Fifth, since 2002, the country’s tax structure has been harmonized with those
of fellow members of the Common Market for Eastern and Southern Africa
(GOE 2003).
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Distortions to Agricultural Incentives in Africa
A 1993 proclamation replaced the complex tax structure for coffee exports
imposed by the Dergue regime by introducing a flat 6.5 percent tax on coffee
exports. That tax was then completely eliminated in 1998 following declining coffee prices in the international market. In 2002 the current government followed
up by eliminating taxes for other exportable commodities. With these reforms,
most exports are now free of tax. Of the commodities covered in this analysis, only
chat remains subject to an export tax (29 percent). The elimination of export taxes
has further boosted exports, particularly of oilseeds and pulses. Total export of
oilseeds and pulses jumped from about 100,000 tons in fiscal 2003 to 184,000 tons
in fiscal 2005. During the first half of 2006, total export earnings from oilseeds
and pulses exceeded that from coffee, which has historically been the number one
export crop in the country.
Agricultural policies on output prices
Ethiopia has experimented with a whole spectrum of agricultural pricing policies,
ranging from parastatal-centric control through production quotas and trade
control during the Dergue regime, to a dual-pricing approach during 1992–99, to
total liberalization (except security reserve and safety nets) with ad hoc interventions since 1999. As a first step toward liberalization, the transitional government
undertook substantial reforms in agricultural marketing in 1992, which included
elimination of wheat subsidies, closure of all eight regional Agricultural Marketing Corporation offices, and a reduction in the number of branch offices from 27
to 11; the number of grain procurement centers was reduced from 2,013 to only
80 (Gabre-Madhin and Mezgebou 2006). Since then there have been five important government proclamations that highlight the shifts in policy objectives over
time, three points about which are worth noting.
First, the Ethiopian Grain Trading Enterprise (EGTE), a downsized version
of the former marketing corporation, was mandated to stabilize prices, maintain food security reserves, and export agricultural commodities to generate
foreign currency. These are clearly conflicting mandates. While the involvement
of a government agency in food price stabilization and the maintaining of food
security stocks may be justified if there are market failures, it is not clear why the
EGTE was mandated to also export in liberalized markets. Furthermore, nontradable cereals can be exported only with subsidies. The policy turned counterproductive in 1997, when the EGTE exported 48,000 tons of grain at a subsidized price only to face the daunting challenge of managing domestic price
hikes a few months later. The export transaction turned out to be unprofitable
for the EGTE, because the export price was 15 percent lower than the domestic
sales price (Bekele 2002).
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247
Second, despite the 1997 export experience, the policy of export promotion
continued as a central mandate of EGTE. In 1999, the EGTE was merged with
another public enterprise, Ethiopian Oilseeds and Pulse Export Corporation, to
consolidate public export functions into one agency. Although the private sector
dominates exports of oilseeds and pulses, the EGTE continues to have a large
export share, despite having much larger marketing costs than the private sector.
Third, there are indications that the absence of food price stabilization and the
ad hoc pricing policy are sending mixed signals to the producers. Two recent examples can substantiate this statement. Two consecutive years of bumper harvests of
maize and other crops resulted in a precipitous 80 percent decline in producer
prices of maize in early 2002. As the ratio of input prices to maize prices increased
from 1.7 in 2000 to 9.0 in 2002, maize production became a highly unprofitable
business. This led farmers to abandon their maize crop in the field and reduce their
fertilizer use by up to 20 percent. Low rainfall the following year led to a dramatic
drop in maize production and skyrocketing prices. The second example is more
recent. In January 2006, at the time of Ethiopian Christmas and other religious festivals, cereal prices rose more than 20 percent above their levels in the previous
months, and the government announced a temporary ban on exports.
To summarize, while extensive reforms have been introduced to dismantle the
policies of the central planning regime, a large public agency continues to operate
with conflicting mandates. Export promotion, in most cases of nontradables,
continues to be an important mandate for the EGTE even in the most recent government proclamations. This is very different from the rural and agricultural
development policies adopted elsewhere in developing countries, where food selfsufficiency came before export promotion and the policies focused, among other
things, on ensuring price stability and giving proper incentives to farmers to adopt
best-practice technology (Rashid, Cummings, and Gulati 2005; World Bank 2006;
Byerlee et al. 2006).
Farm input market policies
Modern use of farm inputs is limited in Ethiopia. Available estimates suggest that
Ethiopian farmers apply about 16 kilograms of nutrients per hectare of cultivated
land (EEA 2005), and only 3 to 5 percent of farmers use modern seeds (Byerlee
et al. 2006). A host of factors—such as limited irrigation facilities, weak dissemination, and suitability of these inputs—is responsible for low adoption of modern
seed and fertilizer technology. However, government policies toward input markets,
which are heavily controlled by the public sector, might also be a contributing factor.
The following reviews the public policies toward the two most commonly used
modern inputs in the country, fertilizer and improved seeds.
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Distortions to Agricultural Incentives in Africa
Between 1984 and 1993, government parastatals had monopoly control over
fertilizer importation, distribution, and pricing. In 1993, the government issued
its National Fertilizer Policy, which allowed the private sector to participate in fertilizer imports and distribution. A few importers and several wholesalers and
retailers entered the market, but two years later the government decided to create
regional holding companies with strong ties to regional governments (GOE
2001). This policy created disincentives for the private sector, because the government provided the parastatal holding companies preferential access to foreign
currency to import and distribute fertilizers under the New Extension Intervention Program. By 1996, this program accounted for 67 percent of the country’s
fertilizer distribution, with the holding companies being awarded virtually all of
the fertilizer supply contracts (Stepanek 1999). This preferential treatment, along
with subsidized storage and transportation to the holding companies, discouraged the private sector and forced many companies to exit the market. As of 2001,
two regional holding companies and the parastatal Agricultural Input Supplies
Corporation accounted for all fertilizer imports and local distribution (Jayne et al.
2003). Since 2004, though, farmers’ cooperatives and unions, which enjoy preferential access to credit, have emerged as buyers and distributors of fertilizers.
The modern seed sector in Ethiopia is dominated by the Ethiopian Seed Enterprise (ESE), especially for hybrid maize and wheat. The only major competitor is
Pioneer Hi-Bred, an international company that is involved in the production and
marketing mainly of maize seed, including both hybrid and open pollinated varieties (OPVs). According to a recent government report, ESEs produced 82 percent
of all hybrid maize seed used in the country and 70 percent of the OPV seed. Furthermore, although some private firms and farmers multiply seeds under contract
arrangements, only ESE and Pioneer carry out the marketing and distribution
(Alemu and Spielman 2006). The dominance of ESE in an arguably liberalized
market is not clear, particularly because available data suggest that the marketing
of improved seed production can be lucrative. The failure of private sector firms
to emerge in the country’s seed industry can perhaps be explained by the preferential treatment that ESE is granted for its operation.
Summary and Implications
With three ideologically distinct political regimes, Ethiopia has embraced all
major waves of economic policy thinking over the past 50 years. It pursued export
promotion in the 1950s, Prebisch-Singer import substitution in the 1960s, central
planning during 1974–1991, and primarily market-oriented policies since the
early 1990s. This chapter has provided a critical review of the country’s broad
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249
economic policies since the 1950s as well as time series estimates of rates of distortion to agricultural incentives since 1981. The review suggests that policies of
all political and policy regimes distorted agricultural incentives, albeit to varying
degrees. The monarchy controlled land and exports of cash crops; the central
planning regime controlled almost all aspects of agricultural markets; and the
current regime, which has implemented substantial reforms, continues to intervene in output markets through ad hoc policies and input markets through marketing parastatals.
The estimates of assistance and taxation are in line with the broad environment under each political regime. High taxation and an overvalued currency
resulted in high nominal and relative rates of assistance in the 1980s compared
with the 1990s. The estimates also suggest that even though farmers were heavily
taxed in the 1980s, the government did not generate revenues in real terms
because of the parastatals’ high overhead costs and an overvalued currency.
Currency devaluation, abolition of price controls, and the streamlining of tax
systems have resulted in significant declines in the rates of distortion since the
mid-1990s. The improvement in agriculture’s NRAs and RRAs has contributed to
an increase in the volume of exports of all major exportable farm commodities.
However, although farmers’ share of the fob prices increased in the 1990s, those
shares remain low compared with those in neighboring countries. Our analysis
also suggests that three forms of distortions in agriculture still persist: control over
input markets; ad hoc government interventions in output (mainly cereal) markets; and disincentives through depressed prices, caused by the continued inflow
of food aid.
Is the current situation likely to improve in the future? There are reasons to be
optimistic. Ethiopia is now in the process of accession to the World Trade Organization, and may therefore have to withdraw from the farm input markets and
stop intervening in the farm output markets. The government of Ethiopia has also
placed more emphasis on developing infrastructure and market institutions
(commodity exchanges are in the making) and on designing more effective social
safety net programs. If these initiatives are successful, and political stability is
maintained, agricultural incentives may well improve further in the future.
Notes
1. The monarchy started earlier, but the country adopted its first five-year plan in 1956; following
the revolution in 1991, a transitional government held power until 1995.
2. For example, in the southern part of the country, agricultural lands were equally distributed
among the state, churches, and the local people. Tenancy rates ranged between 65 and 80 percent of
landholdings, and the tenants’ payments to landowners reached as high as three-fourths of total
production (Zewde 2002; Cohen 1987).
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Distortions to Agricultural Incentives in Africa
3. For further details on the policy actions and their consequences, see Zewde (2002) and
McCann (1995).
4. Many studies have documented the impacts of policy reforms, notably Negassa and Jayne
(1997); Dessalegn, Jayne, and Shaffer (1998); and Gabre-Madhin (2001).
5. One recent intervention was an export ban on cereals in the wake of increasing prices in February 2006.
6. The numbers are based on a new social accounting matrix developed at the International Food
Policy Research Institute in Addis Ababa.
7. This section draws from Zewde (2002) and McCann (1995).
8. In the southern part, the state and the church owned two-thirds of the land. The northern part
had nontransferable communal kinship ownership, which it wanted to protect and so waged a defensive struggle against the government’s land privatization policy. Furthermore, the government made
extensive land grants to its supporters—the military and public officials—in order to broaden its
power base (Cohen 1987; U.S. Library of Congress 2004). Zewde (2002) reports that the first public
enterprise in Ethiopia, called the Ethiopian National Corporation, was established in early 1942 by the
Ministry of Commerce and Agriculture to control exports; this public corporation was succeeded by
the Coffee Board, the Livestock and Meat Board, and the Grain Corporation, designed to control the
three most important agricultural commodities.
9. Preliminary calculations based on data from the Ethiopian Seed Enterprise and the Agricultural Input Supplies Enterprise.
10. Rashid, Assefa, and Ayele (2007, appendix figure 1) present public expenditures, as a percentage of GDP, for various sectors during 1981–2003. The upward trend in defense expenditure clearly
corresponds with the years of civil strife. In the 1980s, defense expenditures accounted for 7–11 percent of GDP. Defense spending came down to about 2 percent after the fall of the Dergue but picked up
again during the war with Eritrea.
11. Unfortunately, continuous time series data on public subsidies are not available.
12. Detailed time series data are presented in Rashid, Assefa, and Ayele (2007, appendix table 2).
13. Calculated from Rashid, Assefa, and Ayele (2007, appendix table 2).
14. Detailed data are presented in Rashid, Assefa, and Ayele (2007, appendix table 3).
15. Food aid figures are calculated from World Food Programme data reported in FAOSTAT. No
data are available for the monarchy period, but food imports averaged only 28,068 tons a year from
1960 to 1973.
16. It amounts to about 13 percent of cereal utilization, which is equivalent to about 25 percent of
total human consumption (where in addition to human consumption, cereal utilization includes seed,
feed, and waste).
17. A number of studies have analyzed the disincentive effects of food aid flow and come up
with very different conclusions. While Abdulai, Barrett, and Hoddinot (2005) argue that food aid
had no adverse impact on agricultural incentives, Demeke, Guta, and Ferede (2004) find significant
negative effects, both indirect (through depressed producers price) and direct (through reduced
production).
18. In fact, because of its addictive effects, governments in the region (Ethiopia, Somalia, and
Djibouti) have tried to prohibit chat cultivation at various points in time, but without much
success.
19. The government of Ethiopia, with financial support from the U.S. Agency for International
Development, is currently implementing a large multiyear, multi-million-dollar project to improve the
sector’s performance
20. These estimates are sensitive to the price elasticities used in the calculations. However, food
aid seems to depress price under a wide range of elasticities. For our calculations, we have used an
estimate of 0.50 for own-price elasticity of wheat and 0.8 and 0.7 for cross-price elasticities of
maize and teff, respectively. These are based on estimates provided by Alemayehu Seyoum of Addis
Ababa University.
21. On coffee smuggling and supply responses, see Dercon and Lulseged (1995).
Ethiopia
251
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Demeke, M., F. Guta, and T. Ferede. 2004.“Agricultural Development in Ethiopia: Are There Alternatives
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Dercon, S., and A. Lulseged. 1995. “Smuggling and Supply Response: Coffee in Ethiopia.” World Development 23 (10): 1795–1813.
Dessalegn, G., T. S. Jayne, and J. D. Shaffer. 1998. “Market Structure, Conduct, and Performance: Constraints on Performance of Ethiopian Grain Markets.” Working Paper 20. Grain Market Research
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Diao, X., A. N. Pratt, M. Gautam, J. Koeough, J. Chamberlin, L. You, D. Puetz, D. Resnick, and B. Yu.
2005. “Growth Options and Poverty Reduction in Ethiopia.” DSGD Discussion Paper 20. International Food Policy Research Institute, Washington, DC.
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———. 2001. Annual Report on the Ethiopian Economy, 2000/2001, ed. B. Degefe, B. Nega, and
G. Taffesse. Addis Ababa: EEA.
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Ethiopia. Addis Ababa: EEA.
———. 2005. Report on the Ethiopian Economy, 2004/2005: Transformation of the Ethiopian
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Jayne T. S., J. Govereh, M. Wanzala, and M. Demeke. 2003. “Fertilizer Market Development: A Comparative Analysis of Ethiopia, Kenya, and Zambia.” Food Policy l (28): 293–316.
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9
Kenya
Alex Winter-Nelson
and Gem Argwings-Kodhek*
At independence in 1963, Kenya inherited a relatively open and export-oriented
economy with a policy environment that was favorable to the agricultural sector.
Unlike many other developing countries, the ruling elite in Kenya had strong links
to agriculture and implemented policies that supported both small-holder and
large-scale producers. For most of the next 20 years the agricultural sector thrived,
the economy in general grew, and the country enjoyed political stability. In contrast, the second 20 years of independence were marked by agricultural and economic stagnation and persistent struggles with corruption and other forms of
poor governance. In recent years, both agriculture and the economy generally
have shown signs of recovery and growth.
This chapter first reviews major developments in the structure of the Kenyan
economy and summarizes economic policies up to independence. It then presents
measures of policy-induced price distortions over the 1963–2004 period. Distortions are measured using estimated rates of assistance based on comparisons of
domestic commodity prices with undistorted world market prices. Finally, the
paper links changes in rates of protection to the evolution of various policies over
the same period.
From 1965 to 1981, Kenya’s real GDP (gross domestic product) per capita rose
at an average rate of 2.5 percent a year while agricultural value added grew at an
annual rate of almost 5 percent.1 During this period, the state presence in the economy expanded: the prices for most agricultural commodities were administered by
* The authors are grateful for helpful comments from workshop participants. Detailed data and estimates of distortions reported in this chapter can be found in Winter-Nelson and Argwings-Kodhek
(2007).
253
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Distortions to Agricultural Incentives in Africa
marketing boards, and trade was restricted through import licensing regulations.
Nonetheless, for the first 20 years of independence the agricultural sector was
spared high direct or indirect taxation as measured in the nominal rates of assistance (NRAs), except during a few periods of exchange rate distortion.
After this promising start, growth in agricultural production and in per capita
income faltered in the early 1980s and stagnated until after 2004, when performance improved markedly. Slow growth in income was paralleled with rising rates
of poverty. In 1982, the rural head-count poverty rate in the country was 48 percent, ranging from 26 percent in the agriculturally rich Central Province to
58 percent in Nyanza Province. Ten years later, the average rural poverty rate was
unchanged, but the rate in Central Province had risen to 36 percent. In 1997 the
rural poverty rate was 53 percent, according to Kenya’s Central Bureau of Statistics
(Government of Kenya 2000). Aggregate rural and urban poverty rates were estimated to be 55 percent in 2001 and 56 percent in 2003 (IMF 2005).
Policy initiatives starting in the late 1980s often centered on liberalizing the agricultural economy in an effort to reduce transactions costs and ensure that producer
prices reflected global scarcity values. However, the process of liberalization suffered various policy reversals (World Bank 1998; WTO 2000) and was complicated
by increasing macroeconomic instability in the early 1990s. Nonetheless, domestic
market liberalization has made considerable progress in recent years. While many
marketing boards still exist, their roles are greatly diminished. Meanwhile, trade
policy reforms have replaced licensing schemes with tariffs, and the tariffs have
been steadily reduced. Finally, a shift to a floating exchange rate system in 1993 has
eliminated currency overvaluation as a source of price distortion.
Despite the recent policy reforms, performance in the agricultural sector has
been disappointing, except for the dramatic expansion in the production of horticultural products and the recovery of cereals production in 2004–06. Slow growth
in the marketed supply of cereal crops is partly a result of rural population growth
and increased consumption on farms. External shocks, including sharp swings in
coffee prices, have also been partly to blame for poor performance. Probably more
important for this analysis is the problem of excessively high domestic marketing
margins. As a result of the poor state of the rural infrastructure, producers face
costs of delivering output and securing inputs that are sometimes prohibitively
high (Omamo 1998; Obare, Omamo, and Williams 2003). For certain commodities, regulations continue to protect high-cost public enterprises and parastatals,
further raising transactions costs. Moreover, continued regulation and red tape
raises the costs of doing business while introducing avenues for corruption
(World Bank 2006). All these costs tax the agricultural sector in ways that are not
fully reflected in the price distortions calculated here.
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255
Two important developments in the agricultural sector have influenced trends
in the measured rates of assistance apart from any changes in policy. First, because
of growth in population and demand, wheat and maize have shifted from being
exportable commodities to being importable. Administered prices were generally
set within the fob-cif band, between the free-on-board (fob) prices that would
have been received for exports and the cost-insurance-freight (cif) prices that
would have been paid for imports in the major production areas, so this shift
implied a change from subsidizing to taxing production relative to free trade. Second, the share of coffee in the sector has fallen relative to those for tea and horticultural production, shifting the commodity mix in the aggregate NRA. And
third, the largely undistorted market for fruits and vegetables has muted the
weighted average rate of distortion for the agricultural economy as a whole.
Kenya has rarely experienced egregious price distortions in the agricultural
sector, but the degree of government support for agricultural development has
been uneven over time. Currently, growth in the sector seems to be more inhibited
by limited public investment and excessive red tape than by distorting policy
interventions. The success in exports of fruits, vegetables, and cut flowers was
facilitated by targeted public investment in extension, rural roads, and improvements at the Nairobi airport (Schapiro and Wainaina 1991; Minot and Ngigi
2004). The revitalization of much of the agricultural sector may require investments in physical infrastructure to reduce transactions costs as well as administrative reforms to allow more creative marketing arrangements and macroeconomic
stability to encourage private investment. Public investments should be targeted
to commodities that have some potential comparative advantage. This analysis
suggests which commodities those may be. Unfortunately, the current analysis
cannot reveal the precise degree to which current marketing margins are inflated
by regulations.
Growth and Structural Changes since 1955
Kenya’s strong economic performance up to 1980 was rooted in the growth of the
agricultural sector, which has consistently accounted for a large share of employment, value added, and exports. The expansion of agricultural output between
1955 and 1980 was based on increases in cropped area and the opening of commercial production opportunities to small-holder African producers. From 1960
to 1969, cereals output rose by 69 percent, with cropped area growing by 61 percent (FAO 2006). Investment in agricultural research also produced improvements in yields for maize (the primary staple) and the export crops coffee and tea.
Price booms for those exports in the 1970s further boosted performance.
256
Distortions to Agricultural Incentives in Africa
The Kenyan economy has yet to experience a structural transformation into
industrial production. Indeed the manufacturing sector has seen no growth in its
share of the economy, and agriculture continues to account for almost 30 percent
of national income. The significance of agriculture in the economy is larger than
official data suggest because it has a disproportionately large share of employment, accounts for more than 50 percent of export revenues, and directly contributes to about 50 percent of manufacturing production. In the last 10 years,
growth in services, including exportable services (tourism) has eroded somewhat
the centrality of agriculture. Value added data suggest that the declining share of
the agricultural sector in GDP is attributable to more rapid expansion in services,
not to a decline in agricultural output. Data on marketed agricultural production
from the government’s Statistical Abstract of Kenya give a somewhat different
impression, indicating agricultural stagnation since 1990 (figure 9.1).
Not surprisingly, trends in GDP per capita have mirrored growth in the agricultural sector. Figure 9.1 juxtaposes data on per capita GDP with agricultural
Figure 9.1. Agricultural Value Added, Marketed Production,
and GDP Per Capita, Kenya, 1965–2004
index of constant LCU value
1.40
1.20
1.00
0.80
0.60
0.40
0.20
9
20 9
01
20
03
97
19
95
19
93
19
91
19
89
19
87
19
85
19
83
19
81
19
79
19
77
19
75
19
73
19
71
19
69
19
67
19
19
19
65
0
year
agricultural value added (constant LCU)
GDP per capita (constant LCU)
agriculture marketed production
Source: World Bank (2007) and Government of Kenya, Statistical Abstract of Kenya (various years).
Note: LCU ⫽ local currency unit.
Kenya
257
value added and with the value of marketed agricultural production. Both series
show a close correspondence between strong agricultural performance and strong
per capita income growth up to 1982. From that point on, the agricultural value
added figures continue to grow while per capita incomes and marketed production stagnate. This pattern probably reflects the strain that population growth has
placed on the agricultural sector. Kenya’s total population grew at an average rate
of over 3 percent annually from 1980 through 2004, with the rural population
increasing from 13.6 million to 20 million during that period. With this population growth, agricultural land per agricultural worker halved, falling from about
4.4 hectares in 1980 to 2.2 hectares in 2004. Meanwhile, agricultural workers faced
a high dependency ratio, with about 50 percent of the population under age 15
throughout the period. While agricultural value added continued to grow through
the 1990s, the increases in production did not match population growth and were
in large part consumed on the farm.
While the Kenyan economy has seen little in the way of structural transformation, the structure of the agricultural sector itself has evolved considerably since
1955. In the first instance, small-holder production expanded relative to estate
production for the two main export crops (coffee and tea) and for maize. Through
the 1960s, the share of marketed production from small-holders increased rapidly,
as did total production. For example, tea production rose from 13,000 metric
tons, with 1 percent grown by small-holders in 1960, to 20,000 metric tons with
5 percent grown by small-holders in 1965, and to 40,000 metric tons, with 20 percent
grown by small-holders in 1970. Small-holders now produce about 60 percent of
Kenya’s tea. The small-holder share of coffee production rose from 20 percent in
1960 to 50 percent in 1965, where it remains today.
Expansion of small-holder production did not initially affect the crop mix in
production or exports, but over time the crop mix has changed (figure 9.2). First,
coffee production has declined in significance, the result of both declining world
market prices for the commodity and low growth in output since the late 1980s.
Meanwhile tea production has expanded, with tea replacing coffee as the single
largest export commodity by value in about 1990 and remaining in that position
ever since. Growth in both tea and sugar production was facilitated by institutional innovations and investments to support small-holder production and to
formalize the marketing chains that serve small-holders.
More dramatic than the expansion of tea production has been the growth in
exports of horticultural products, as exemplified by green beans. Before 1985,
Kenya recorded no exports of green beans. By 2000, exports of green beans
exceeded coffee exports. Altogether, fruits and vegetables have accounted for
about 20 percent of the value of Kenya’s agricultural exports since 2000, about
one-quarter of which has been from green beans. Canned pineapples and other
Figure 9.2. Product Shares of Agricultural Production
and Consumption, Kenya, 1960–2004
a. Primary agricultural production shares
100
90
80
percent
70
60
50
40
30
20
10
0
1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
five-year average
other agriculture
tradable fruit and vegetables
tea
wheat
domestic fruit and vegetables
sugar
coffee
maize
b. Final household food consumption shares
100
90
80
percent
70
60
50
40
30
20
10
0
1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
five-year average
other agriculture
coffee
domestic fruit and vegetables
wheat
Source: FAOSTAT; Statistical Abstract of Kenya (various years).
sugar
maize
tea
Kenya
259
fresh vegetables represent most of the remaining exports in this class. Exports of
cut flowers have grown on a similar path to fruits and vegetables and account for
an even larger share of export revenue, according to the government’s Economic
Survey of Kenya for 2005.
The data on production shares in figure 9.2a are compiled from government
sources, the Food and Agriculture Organization’s FAOSTAT database (FAO 2006),
and scholarly research. Because a large share of maize production is not marketed
and much of the marketed maize is sold in informal markets, total maize production is estimated at about four times the marketed output (Pearson and Monke
1995; Jayne et al. 2001). Inflating marketed production figures taken from the
Statistical Abstract of Kenya by this factor results in production estimates close to
those reported in FAOSTAT and Hassan and Karanja (1997). As for horticulture,
government sources report only sales of specific crops and do not cover the same
crops in all years. Export data are therefore used to estimate production of tradable fruits and vegetables. Moreover, Muendo, Tschirley, and Weber (2004) suggest that the domestic market for fruit and vegetables may have much larger value
than the export market. The domestic market for fruits and vegetables is dominated by tomatoes, cabbages, and kale (sukuma wiki), with substantial production
of cooking bananas and potatoes. Argwings-Kodhek (2005) estimates the value
added from domestic horticulture to be similar in scale to export horticulture
(including floriculture). Despite the limitations of the data, it is clear that maize
has been and remains the core of agricultural production in Kenya, and that the
output of tea, fruits, and vegetables has expanded rapidly while coffee output has
been in decline.
In addition to changes in crop mix and export concentration, Kenya has experienced a change in market position. As figure 9.2b shows, domestic consumption
patterns have been fairly stable, with maize accounting for 40–50 percent of food
expenditures and wheat drawing an additional 10 percent. The country, however,
has shifted from being a net exporter of wheat and maize in the 1950s and 1960s
to becoming a net importer of both of these cereals since the 1990s. The transition
from exporter to importer occurred fairly abruptly in the 1970s for wheat, but was
more prolonged for maize. Kenya was a net exporter of maize for most of the
1960s and 1970s, while during the 1980s it oscillated between maize surplus and
deficit. Since the 1990s, however, it has been a fairly consistent importer, despite
the government’s policy of targeting maize self-sufficiency. This transition has
also come despite successful research efforts to develop improved varieties of
maize that have been widely adopted. Indeed, maize yields rose by 1.5 percent
annually from 1975 to 1984 and continued to rise through the 1990s (Hassan and
Karanja 1997).
260
Distortions to Agricultural Incentives in Africa
Agricultural Policy in the Colonial Period,
1895–1963
Agricultural policy during the colonial period in Kenya (1895–63) was largely
motivated by a need to make the East African railroad system profitable. Toward
that end, European settlers were encouraged to enter the high-potential agricultural areas of the colony (the so-called White Highlands) and produce commercial crops to be shipped by rail to Mombasa on the coast. Coffee was the initial
focus of export production, but colonial authorities promoted experimentation
with a range of commodities including wheat, tea, cotton, and pyrethrum. The
colonial administration favored settler agriculture, and policies were biased
strongly against indigenous, small-holder producers (Mosley 1983).
Colonial agricultural policies included alienation of land from local populations to create an estate sector of European-owned farms. Labor markets were also
restricted, with “hut” taxes on small-holder households used as an explicit device
for channeling African labor to the estate sector. Access to export markets was
restricted to European producers, further encouraging labor supply to the estate
sector and protecting European producers from domestic competition. Finally,
starting in the mid-1930s, agricultural finance was made available to estate producers at subsidized rates (Winter-Nelson 1995). According to Smith (1976), the
bulk of tax revenue before the Second World War was collected from native populations, while public investment in infrastructure and agricultural research concentrated on the estate sector.
Agricultural commodity markets came under administered pricing systems
during the colonial period (Mosley 1983; Winter-Nelson 1995). Export-crop marketing boards were established in the 1930s to reduce costs of marketing and
enforce quality control. These boards passed world market prices to producers
and also enforced exclusion of African farmers from markets. The boards invested
in processing capacity and agricultural research and extension in addition to
performing marketing services.
Under the Sale of Wheat Ordinance of 1933, the Kenya Farmers Association
became the sole legal marketer of wheat. It used this position to maintain an artificially high domestic price, while exporting surpluses at a lower free-market
price. To maintain this system, a high import tariff was introduced to keep
cheaper foreign wheat out of the colony. The maize market came to be regulated
in a similar manner, with the farmers association as the sole legal maize buyer outside of small local markets. Because coffee growers forcefully opposed regulations
that could increase the domestic price of maize, thus raising their labor costs, the
association administered maize markets in such a way as to stabilize local prices
and provide services to growers without imposing a high tax on consumers.
Annually, the association announced a price to ensure a “guaranteed minimum
Kenya
261
return” to producers and used its market position to deliver (subsidized) cropsecured loans in cash or inputs. The maize purchase price was typically set
between import and export parity. It thus shielded consumers from high import
prices but ensured profitable production for European settler farmers given the
prices charged for inputs.
Starting in 1955, the colonial government began an effort to develop a class of
African commercial farmers. The government’s Swynnerton Plan initiated a partial liberalization of the agricultural sector by allowing Africans to produce crops
for export. The Swynnerton Plan also introduced a system of land registration and
titling for Africans, while continuing to exclude them from owning farms in the
White Highlands. In addition to removing cropping restrictions, policy at this
point included substantial investment in infrastructure and extension to serve the
nascent small-holder commercial farm sector as well as the estate sector. While
allowing broader access to markets, the state continued to administer prices for
major commodities through marketing boards.
At independence, the Kenyan government maintained a supportive stance
toward export agriculture and expanded efforts to commercialize small-holder
production. At the same time, an indigenous Kenyan elite entered into large-scale
agricultural production. In contrast to many other African countries, Kenya
refrained from imposing high implicit or explicit taxes on the agricultural sector
in the 1960s. While government control of markets expanded in the postcolonial
period, prices were typically administered to pass through world prices to largescale farmers growing export crops or to the cooperative societies representing
small-holder producers. Similarly, the administered prices for maize and wheat
were held above export parity but below the cif price in the main growing regions.
This pricing was consistent with the colonial price administration (Jabara 1985).
However, because commercial maize production became more geographically
dispersed as the market came to serve surplus producers throughout the country,
the panterritorial pricing scheme introduced larger distortions in some regions
than in others.
Direct and Indirect Distortions
to Agricultural Incentives
The main focus of the current study’s methodology (see appendix A in this volume and Anderson et al. 2008) is on government-imposed distortions that create
a gap between actual domestic prices and what they would be under free market
conditions. Because the characteristics of agricultural development cannot be
understood from a sectoral view alone, the project’s methodology not only estimates the effects of direct agricultural policy measures (including distortions in
262
Distortions to Agricultural Incentives in Africa
the foreign exchange market) but also generates estimates of distortions in nonagricultural sectors for comparative evaluation. This involves computing an NRA
for nonagricultural tradables for comparison with that for agricultural tradables
through the calculation of a relative rate of assistance (RRA).
This study calculates NRAs for maize, wheat, coffee, tea, sugar, export fruits
and vegetables, and domestic fruits and vegetables. These commodities account
for about 75 percent of the value of agricultural production and value added. The
remaining 25 percent comes primarily from nontradable beef for slaughter and
raw milk, exportable cut flowers, and importable dairy products. In calculating
the overall NRA for agriculture, prices for the nontradable residual commodities
are assumed to be undistorted, while prices for exportables are influenced by
exchange rate distortions, and the prices of importable dairy are affected by both
trade protection and exchange rate distortions. Trade protection is measured
through the trade weighted ad valorem tariff rates on milk and dairy reported in
Sandri, Valenzuela, and Anderson (2006) or by the average applied tariff for agriculture taken from from the Statistical Abstract of Kenya.
Data on world prices, domestic prices, and volumes of production and trade
came from government sources (primarily the Statistical Abstract of Kenya and the
Economic Survey), FAOSTAT, and the UN’s Comtrade database. The application
was particularly constrained by the availability of reliable data on the appropriate
margins to apply for processing and marketing commodities. Sources for data on
these costs included Nyoro, Kiiru, and Jayne (1999); Nyoro, Kirimi, and Jayne
(2004); Jayne, Myers, and Nyoro (2005); World Bank (2005); and Pearson and
Monke (1994). (Additional sources are noted in the discussion of specific commodities; see also the appendix in Winter-Nelson and Argwings-Kodhek (2007).
For many crops, actual marketing costs are not documented for long periods of
time. Consequently, documented costs for specific years were discounted by the
consumer price index and applied to a range of up to 20 years to estimate the
actual costs incurred. Even if these estimates of the actual costs are accurate, they
include implicit taxation introduced by inefficiencies in the management of public and parastatal intermediaries. Because mismanagement of parastatal marketing boards has been an important issue in Kenya, especially in the 1980s and
1990s, an alternative “best-practices” margin was also calculated and applied to
estimate the commodity-specific rates of assistance to farmers. These best practices are typically based on costs incurred in the sector after parastatal reforms
were adopted. Rates of assistance to farmers (the NRAs on output for farmers) are
adjusted downward from the NRA for the commodity whenever the estimated
margin charged exceeded the estimated best-practices margin. This approach creates a wedge between the NRA at the farmgate and the NRA in wholesale markets
for many crops, notably maize and wheat, in the 1970s and 1980s. Given the
Kenya
263
likelihood of technical change since the late 1950s, the best-practices margins for
the 1950s and 1960s have been raised, bringing them closer to estimated actual
margins in that period.
Other areas in which data are problematic include the estimates of the appropriate world price (or shadow price) for agricultural outputs and the parameters
for estimating support to the nonagricultural sectors that are used to calculate the
RRA. Where world prices were particularly difficult to establish (such as those for
sugar), upper and lower bounds were explored. Uncertainty in the RRA calculation
emerges from limited information on the tradability of output from nonagricultural sectors and from lack of precise data on applied tariffs, taxes, and subsidies as
well as on nontariff barriers. However, direct distortions tend to be small in most
nonagricultural sectors. Finally, the amount of non-product-specific support that
agriculture has received is difficult to estimate. In calculating the aggregate rates of
support, this analysis presents indicators that exclude all such support and separate
indicators that treat the entire agricultural budget as assistance to the sector.
The NRA estimates shown in figure 9.3 and table 9.1 reveal modest to moderate rates of taxation to the sector overall for most of the postcolonial period.
Figure 9.3. NRAs for Exportable, Import-Competing, and All
Covered Farm Products, Kenya, 1956–2004
150
100
percent
50
0
⫺50
19
56
19
59
19
62
19
65
19
68
19
71
19
74
19
77
19
80
19
83
19
86
19
89
19
92
19
95
19
98
20
01
20
04
⫺100
year
import-competing products
exportables
total
Source: Data compiled by the authors.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
264
Table 9.1. NRAs for Covered Farm Products, Kenya, 1956–2004
(percent)
Product indicator
Exportablesa,b
Coffee
Tea
Vegetables and fruits
Import-competing productsa,b
Nontradablesa
Vegetables and fruits
Mixed trade statusa
Wheat
Maize
Vegetables and fruits, tradable
Sugar
Total of covered productsa
Dispersion of covered products
Percent coverage (at undistorted
prices)
1956–59 1960–64
1965–69
1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
25.5
⫺10.7
2.6
—
12.3
0.0
0.0
16.8
⫺0.4
11.5
⫺1.3
⫺16.6
8.0
0.0
3.3
⫺12.7
⫺6.7
⫺12.5
4.2
0.0
0.0
⫺16.3
⫺19.4
⫺15.6
⫺21.5
⫺46.0
⫺5.5
0.0
⫺2.3
⫺4.3
⫺1.0
⫺6.7
⫺25.3
⫺19.1
0.0
⫺13.0
⫺15.2
⫺10.2
⫺14.8
⫺40.5
⫺44.2
0.0
⫺14.1
⫺14.8
⫺13.0
⫺7.4
16.1
⫺1.3
0.0
⫺26.6
⫺21.9
⫺29.5
⫺12.8
⫺35.4
⫺6.0
0.0
⫺10.5
⫺5.0
⫺14.9
⫺3.2
2.9
0.0
0.0
⫺0.6
⫺3.3
0.2
0.0
9.3
0.0
0.0
12.3
59.4
—
—
23.7
30.5
64
5.1
44.3
⫺1.0
⫺29.1
15.8
25.8
66
10.1
13.1
⫺9.9
42.7
⫺2.3
32.7
70
⫺26.8
⫺24.1
⫺17.4
⫺47.9
⫺24.1
20.2
79
⫺7.7
⫺17.2
⫺5.3
⫺24.6
⫺14.7
25.7
82
⫺20.5
⫺46.4
⫺11.8
⫺47.9
⫺29.9
23.9
85
18.6
⫺1.3
⫺5.8
21.1
⫺8.0
20.4
81
⫺10.7
⫺34.5
⫺10.5
⫺27.1
⫺30.0
21.7
85
36.8
⫺5.3
⫺2.5
30.6
⫺4.5
18.7
80
46.2
0.5
0.0
36.5
3.7
19.1
78
Source: Data compiled by the authors.
Note: — ⫽ no data are available.
a. Weighted averages, with weights based on the unassisted value of production.
b. Mixed trade status products included in exportable or import-competing groups depending upon their trade status in the particular year.
c. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
Kenya
265
Positive rates of assistance to agricultural producers (and commensurate taxation
on food consumers) in the late 1950s and early 1960s are driven largely by high
domestic prices for wheat and maize, which are exportables for much of this
period. The general shift toward taxation of agricultural production in the 1970s
and through the 1980s is followed by a reduction in distortions from the mid1990s, and, in the last years covered here (2000–04), the NRA for covered farm
products is slightly positive.
Considerably more variability occurs in rates of assistance for importables
than for other classes of commodities. The negative rates of assistance for
importables in the early 1960s arise because maize and wheat were importable in
some years during this period and were priced below import parity (but above
export parity). Maintenance of a domestic price within the fob-cif band in Kenya
implied that maize production was supported on average in the 1960s, but when
maize was an importable, its production was taxed (see table 9.1). Because cereals
account for a large share of production, importables as a group were subject to
negative rates of assistance when maize and wheat were importable. The pronounced spike in assistance to importables in the late 1960s (see figure 9.3)
reflects protection of the nascent sugar industry and the exportable status of
maize and wheat at that time. Sugar prices often have been held above the international free market price and the Kenyan cif price. Because sugar was the only
commodity designated as an importable in 1967–69, importable agriculture
appears to have received high protection in that period. In the mid-1980s, the
NRA on sugar output increased above its level in the late 1960s, coinciding with
another spike in assistance to importables. In later years, the support to sugar continued, but by the 1990s, maize had become an importable commodity, so the
overall NRA for that class of goods was lower.
There are three periods during which tradable agriculture and the sector in
general had distinctly negative rates of assistance (the early years of the 1970s, of
the 1980s, and of the 1990s). In each of these periods, the cause of the taxation on
agriculture is an overvaluation of the Kenya shilling. The severe drop in the NRA
on output in the early 1990s reflects the additional effect of unusually high world
prices for maize and tea that were not matched with increases in farmgate prices.
Excessive charges by parastatal marketing boards also contributed to negative
NRAs in the 1980s and early 1990s. Only during the late 1970s and early 1980s do
prices for nontradables appear highly distorted, a result of maize being treated as
a nontradable during this time, when the equilibrium price fell within the fob-cif
band. Because the fob-cif band is wide in Kenya, the shadow price is difficult to
estimate precisely. Consequently, the NRA on output for maize during this period
has a large margin of error. Prices for other nontradable commodities (fruits and
vegetables) were undistorted throughout the period.
266
Distortions to Agricultural Incentives in Africa
In contrast to the negative rates of assistance in the 1980s and early 1990s, the
years since then have seen little price distortion outside of sugar and wheat, which
are importable commodities and receive protection. The decline in aggregate
price distortions reflects in part the rapid expansion of horticulture. Both tradable
and nontradable horticulture have become substantial shares in total agricultural
production, and neither of these commodity groups is subject to direct intervention. The only distortions that are recorded in the tradable fruits and vegetables
sector are those that enter through currency overvaluation. The nontradable fruits
and vegetable sector is assumed to be undistorted. While the growth in fruits and
vegetables as a share of the sector mutes the level of distortion in aggregate, policy
reforms (including exchange rate liberalization) have also brought the NRAs for
coffee, tea, and maize closer to zero in the last decade under study.
Considering support only for tradable agriculture, the pattern is of assistance in
the 1950s and 1960s followed by taxation through the early 1990s and relatively
undistorted prices since the mid-1990s. Treatment of non-product-specific public
spending influences the measured level of support but does not alter this general
impression. As table 9.2 suggests, total agricultural spending (treated as nonproduct-specific support here) has been between 6 and 20 percent of the value of
agricultural production, averaging about 10 percent. The total NRA for agriculture
including this support was 9 percent in the 2000–04 period. Excluding this spending, the NRA for agriculture was only 3 percent. In either treatment, the agricultural sector has negative rates of assistance through most of the 1970–94 period.
Meanwhile, nonagricultural sectors are estimated to have had trade protection
that implies nominal rates of assistance of over 20 percent from 1960 through
1990, gradually declining to less than 10 percent afterward (figure 9.4). Given
these estimates, and treating the agricultural budget as support for tradable agriculture, the five-year averages of the RRA were negative from the late 1960s
through the late 1990s and turned slightly positive after 2000. Excluding nonproduct-specific spending, the RRA remains negative through the 2000–04
period.
The final three rows of table 9.2 report values for three indicators assuming
exchange rate distortions are not taken into account. They suggest that distortions
in the local market for foreign currencies accounted for up to 10 percentage points
of the negative NRAs and RRAs from independence until the end of the 1980s.
Distortions by commodity
The following section describes the evolution of NRAs by commodity, in rough
order of importance starting with coffee and tea, then wheat and maize, sugar, and
fruits and vegetables.
Table 9.2. NRAs in Agriculture Relative to Nonagricultural Industries, Kenya, 1956–2004
(percent)
Indicator
NRA, covered products
NRA, noncovered products
NRA, all agricultural products
Non-product-specific assistance
Total agricultural NRA (including
NPS)a
Trade bias indexb
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAc
Memo item, ignoring exchange
rate distortions:
NRA, all agricultural products
Trade bias indexc
RRAc
1956–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
23.7
0.0
15.2
11.4
26.6
15.8
0.0
10.1
12.8
23.0
⫺2.3
0.0
⫺2.2
11.9
9.7
⫺24.1
0.0
⫺19.2
7.5
⫺11.8
0.12
41.5
20.0
17.9
0.18
37.7
21.9
12.7
0.09
15.7
29.2
⫺10.4
0.64
⫺13.3
24.5
⫺30.2
26.9
0.13
18.4
23.4
0.20
13.7
15.6
0.28
0.4
⫺3.4
1.19
⫺16.3
⫺29.9
⫺0.1
⫺25.7
7.1
⫺18.6
⫺8.0
⫺0.2
⫺6.6
17.2
10.5
⫺30.0
⫺1.2
⫺26.8
21.0
⫺5.8
⫺4.5
⫺0.3
⫺3.7
6.1
2.4
3.7
0.0
2.9
6.4
9.3
0.48
11.8
20.0
⫺6.9
0.57
⫺6.5
33.2
⫺29.9
⫺0.24
20.3
28.3
⫺6.1
0.31
⫺4.3
18.0
⫺18.7
⫺0.12
3.1
13.8
⫺9.3
⫺0.09
12.3
10.3
1.9
1.2
0.62
⫺1.4
⫺15.3
0.92
⫺21.4
13.5
⫺0.16
0.2
⫺4.6
0.64
⫺15.5
3.0
⫺0.08
⫺8.1
9.3
⫺0.09
1.9
⫺14.7
0.0
⫺12.3
10.7
⫺1.7
Source: Data compiled by the authors.
267
a. NRAs including product-specific input subsidies and non-product-specific (NPS) assistance. Total of assistance to primary factors and intermediate inputs divided to total value
of primary agriculture production at undistorted prices (percent).
b. Trade bias index is TBI ⫽ (1 ⫹ NRAagx兾100)兾(1 ⫹ NRAagm兾100) ⫺ 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and exportable
parts of the agricultural sector.
c. The RRA is defined as 100*[(100 ⫹ NRAagt )兾(100 ⫹ NRAnonagt ) ⫺ 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural and
nonagricultural sectors, respectively.
268
Distortions to Agricultural Incentives in Africa
Figure 9.4. NRAs for Agricultural and Nonagricultural
Tradables and the RRA, Kenya, 1956–2004
80
60
40
percent
20
0
⫺20
⫺40
⫺60
04
01
20
98
20
95
19
92
19
89
19
86
19
83
19
80
19
77
19
74
19
71
19
68
19
65
19
62
19
59
19
19
19
56
⫺80
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the authors.
Note: For a definition of the RRA, see table 9.2, note c.
Coffee and tea
The data for NRAs for coffee and tea reveal very little impact directly from agricultural policy. Official records of producer prices indicate that growers consistently
received close to the export parity price converted at the official exchange rate. As
figure 9.5 indicates, deviations from export parity occurred primarily when the
Kenya shilling became overvalued in the early 1970s, early 1980s, and early 1990s.
When the exchange rate is undistorted, the NRA is usually near zero. Negative
NRAs that are not explained by exchange rate distortion can be attributed to
charges by the parastatal intermediary in excess of the best-practices cost estimate.
The impression of generally modest price distortions in tea and coffee is subject to at least two important caveats. First, considerable public investment was
made in both these sectors in the 1960s and 1970s. Moreover, both sectors
received subsidized credit through the central government at that time. While neither of these effects is quantified in the analysis, their impact would be to increase
the rate of assistance, bringing the NRAs closer to zero.
A second feature of the analysis may be more misleading. The producer prices
used are the prices paid out by the central marketing authority. These prices were
Kenya
269
Figure 9.5. NRAs for Producers of Export Crops, Kenya,
1956–2004
80
60
40
percent
20
0
⫺20
⫺40
⫺60
19
5
19 6
5
19 8
6
19 0
6
19 2
6
19 4
66
19
6
19 8
7
19 0
7
19 2
7
19 4
76
19
7
19 8
8
19 0
8
19 2
8
19 4
86
19
8
19 8
9
19 0
9
19 2
9
19 4
96
19
9
20 8
0
20 0
0
20 2
04
⫺80
year
coffee
tradable fruits and vegetables
tea
exchange rate premium
Source: Data compiled by the authors.
paid directly to estate producers but channeled through cooperatives for smallholders. After the coffee and tea booms of the 1970s, small-holder growers complained repeatedly of delayed payments, with delays of more than a year often
reported. Discounting the value of farmer prices for these delays would make the
NRAs more substantially negative in many instances. However, the extent and
duration of actual delays are unknown.
The deviation between the NRA for estate producers and that for small-holders
may be more pronounced for coffee than for tea. Small-holder producers are
required to use cooperative societies for the initial (wet) processing of arabica coffee. Cooperatives charge about twice the costs reported by estate growers for this
service (World Bank 2005). These costs are deducted from the grower price. (The
NRA falls by about 7 percentage points if the full cost differential is treated as a
tax.) Given payment delays, small-holders may have faced some taxation even
when the NRAs are positive, and intermediaries, including cooperative unions
and parastatal agencies, could have captured positive rates of assistance when the
NRA is negative.
270
Distortions to Agricultural Incentives in Africa
Wheat and maize
Based on shares of production and consumption, maize is the single most important commodity in the agricultural sector. As a result, price distortions in maize
tend to drive the overall degree of distortion in the sector. An exception to this
tendency arose during the coffee boom in the 1970s, when the value of coffee production briefly exceeded that of maize.
Distortions to incentives for cereals production have probably been somewhat
greater than those in coffee and tea but are still generally modest. Until the mid1990s, prices for maize and wheat were administered by the National Cereals and
Produce Board or its predecessor institutions. In the case of wheat, this system
implied a price that was above both import parity and export parity for much of
the period. Following the colonial administration’s lead of setting the maize price
to balance a positive return to farmers with affordability for consumers, the
administered maize prices tended to fall between export and import parity, at least
for producers in Kitale District, a major supplier of maize for the country.
During the past 50 years, population growth and some income growth have
caused cereals demand to rise more rapidly than supply. As a result, cereal crops
have gradually shifted from being exportable to being importable. Based on trade
patterns, both maize and wheat were exportable products through most of the
1960s, but since the mid-1970s, wheat has been an importable. In the case of
maize, production growth was more robust, but by the 1980s the commodity
could reasonably be classified as a nontradable, with a domestic equilibrium price
falling somewhere within the rather wide fob-cif band. Since 1990, Kenya’s average position in maize has been one of a significant importer, despite occasional
surpluses. In this analysis, wheat is treated as exportable from 1960 to 1971, save
for 1962, and as importable from 1956 to 1959 and from 1972 onward. Maize is
treated as exportable from 1956 to 1976 except for 1961, and during 1964–66 and
1970–71. It is taken as a nontradable from 1977 to 1991 and as an importable
from 1992 onward.
This transition from exportable crop to importable crop occurred while prices
were administered to fall within the fob-cif band. The effect of agricultural policy
then was to subsidize maize and wheat while they were export crops. In both cases
these subsidies were defended from international trade through import restrictions. The cereals board was the sole entity with the legal right to import maize
and wheat. Tariffs were also in place, but these tariffs were suspended when large
imports were deemed necessary. They were redundant when the cereals board
simply declined to import. The shift to importability for wheat implied a rise in
the reference price for measuring distortions from the fob to the cif price. This,
plus exchange rate distortions, resulted in implicit taxation of the commodity in
the 1970s, but wheat appears to be subsidized in the late 1980s and 1990s. The
Kenya
271
measured protection to wheat is consistent with high applied import tariffs in the
1990s and after 2000.
In contrast to wheat, the rates of assistance to maize are negative for most of
the 1970s, 1980s, and 1990s. The shift to referencing against the higher cif price
implied a major reduction in the NRA for maize in the 1980s. This downward
pressure on the NRA was exacerbated by marketing costs in excess of the bestpractices estimate. In the 1990s, the market for maize was liberalized and marketing margins fell, encouraging a recovery in the NRA. The market has been largely
undistorted since 2000. While a duty on imported maize exists, this duty was
repeatedly suspended when the country faced substantial maize deficits. Undocumented trade in maize from neighboring countries has also muted the effect of
the tariff. The combination of these factors has led to an NRA for maize that is
now quite modest.2
As with coffee and tea, exchange rate distortions overwhelmed direct interventions in the early 1970s and early 1990s. In each of these periods, the NRA for
cereals was negative. In other periods, the negative NRA is associated with intermediation charges in excess of the best-practices margin and with the administration of the price.
At least two caveats should be made concerning the calculated NRAs for maize
and wheat. First, panterritorial pricing coupled with high transportation costs
implied very different experiences across the country. The NRAs were calculated
based on transport costs from Kitale District, a region with a large cereals surplus
(Nyoro, Kirimi, and Jayne 2004). However, other parts of the country would have
somewhat different NRAs. Second, the reference price for maize in the 1980s,
when the crop is classified as nontradable, is taken as the average of the fob and cif
prices, weighted 3 to 1 in favor of the cif price. (A simple mean was applied for
1978–80.) Revisions of this crude proxy to other levels within the fob-cif band
could change the sign on the NRA. Despite these concerns, the results presented
here are consistent with other analyses of rates of assistance to cereals in Kenya.
Shapouri, Missiaen, and Rosen (1992) report producer subsidy equivalents for
maize and wheat in Kenya in the 1980s that are similar in levels and in patterns
over time to our NRAs. Consistent with this study, the distortions they identify in
the early 1980s result from exchange rate misalignment, while later distortions
result from administered pricing of the commodities.
Sugar
In this analysis sugar has been treated as an import substitute product throughout
the period. Although Kenya has occasionally exported large volumes of sugar, our
decision to classify it as an import substitute is based on the high cost of domestic
production compared with the international free market price. The NRAs for
272
Distortions to Agricultural Incentives in Africa
sugar production have varied widely through time but are now large and positive.
These direct rates actually understate the full support this sector receives, because
the government has made and continues to make significant investments in the
sector while repeatedly writing off debts and providing subsidized credit.
Estimating the NRA for sugar is complicated by distortions both within and
outside Kenya. Kenya has occasionally had preferential access to markets in
Europe and exported sugar at well above the free market price. Meanwhile the
country has imported sugar at a relatively high cost from sources in the region
(primarily South Africa, Malawi, and Egypt). Imports from these and other countries of the Common Market for Eastern and Southern Africa (COMESA) are not
subject to the 100 percent tariff applied to other sugar exporters. Use of import
and export unit values from customs data would suggest that Kenyan producers
often face an import price that is less than the export parity for the same-quality
product along with export and import parity prices that are above any free market
level. The use of these data could suggest that Kenyan producers cannot compete
with imports but can compete in the export market. Rather than using Kenyan cif
prices, one could apply a “free market” reference world price adjusted for shipping
costs. This approximation, however, is subject to error stemming from quality differentials, variation in transportation costs, and other factors.
Using the free market prices from the Global Economic Monitor Database of
the World Bank, the NRA data indicate rates of protection in excess of 100 percent
in many years. When the cif price is taken as the reference, the NRA figures are
more modest, but still exceed 50 percent. The two series present a reasonable set of
bounds for the assistance estimate. In calculating the weighted average NRA and
other aggregate measures of assistance for agriculture, the lower bound is used.3
The NRA estimates for sugar are comparable in size and volatility to estimates
made by other analysts. Earley and Westfall (1996) report producer subsidy equivalents for Kenyan sugar as follows:
1982
1983
1984
1985
1986
1987
1988
1989
⫺262
15
⫺8
97
96
63
63
⫺9
These calculations confirm the impression of a pronounced increase in assistance
in the mid-1980s, as well as periods of taxation in the early 1980s and again at the
end of the decade. High measured rates of assistance to sugar are consistent with
import restrictions in the 1970s and 1980s and with high import duties since the
1990s. The consumer tax equivalent on sugar is even greater than the NRA
because the commodity has been subject to exceptionally high excise taxes in
addition to the interventions already mentioned.
In addition to uncertainty regarding the appropriate reference price, there is
considerable question about the best-practices and actual processing costs for
Kenya
273
sugar. Estimates of postfarm costs range from $100 to $300 a metric ton, varying
by year, factory, and source of cane. The average cost in African, Caribbean, and
Pacific countries reported in Odek, Kegode, and Ochola (2003) is $105 a metric
ton. Given the low sucrose content of Kenyan cane sugar, a slightly higher than
average value of $150 is used in the analysis from 1980 onward, with a higher cost
of $200 applied before 1980 to reflect lower processing capacity (Jackson 2004).
Use of a higher cost would increase the NRA. Overall, it is clear that the total costs
of sugar production are high in Kenya relative to other eastern and southern
African producers. Jackson (2004) places production costs for raw sugar in Kenya,
Tanzania, and Uganda at about $290 a metric ton compared with $210 for other
countries exporting sugar in eastern and southern Africa. The Kenya Wetlands
Forum (2005) reported costs in Kenya to be 40 percent above costs in other
COMESA countries.
Fruits and vegetables
Growth in horticultural production and export has been a bright spot in Kenya’s
recent economic performance (Minot and Ngigi 2004; Voor Den Dag 2003). As
mentioned, exports of fruits and vegetables have recently grown from a small
share of total exports to become a major component. Because of the significance
of horticulture in the agricultural economy, an NRA has been calculated for the
composite category of export fruits and vegetables (see table 9.1).
The NRAs reported in table 9.1 are based on the volumes and revenues from
fruits and vegetables exports reported by the FAO and on the internal marketing
margins associated with green beans. Green beans are the largest single fresh vegetable export (this category having previously been dominated by processed
pineapples).
The constructed NRA for tradable fruits and vegetables represents an estimate
of the NRA for green beans that is scaled up to the volume of total fruits and vegetable exports. While this approach implies aggregation of such distinct products
as apricots and zucchinis, it allows for inclusion of this important sector in calculation of the NRA. To ignore it completely would imply a measure of price distortions that failed to reflect the conditions in a highly dynamic part of the country’s
agricultural economy. The biases implied by treating this diverse set of crops as
one constituent part (green beans) may be small because the major components
of the fruits and vegetables group appear to be uniformly unaffected by policy.
The exportable fruits and vegetables sector has emerged with little policy intervention, but it has benefited from public investment in rural infrastructure,
increased airfreight capacity, and agricultural extension as well as a supportive
macroeconomic policy environment. While trade restrictions do prohibit the
import of certain horticultural crops, the bulk of fruit and vegetable exports has
274
Distortions to Agricultural Incentives in Africa
not been subsidized or protected directly. For all of these commodities, the main
distortions to producer incentives have been indirect, through occasional currency overvaluation. Fruits and vegetables do face a 1 percent cess for services
from the Horticulture Development Authority.
The great majority of fruits and vegetables grown in Kenya are destined for
domestic markets and either do not meet the standards of or lack access to international markets (Muendo, Tschirley, and Weber 2004). Data from FAOSTAT suggest that by weight, only about 5 percent of Kenyan vegetable production and
about 7.5 percent of fruit production is exported. The nonexport production sells
at a much lower price in largely unregulated (and undistorted) markets. Although
import duties are placed on horticultural products from Uganda and Tanzania,
these duties are unlikely to be relevant, given the porous nature of the borders and
the high costs to long-distance transportation of the commodities. Because production of nontradable fruits and vegetables has expanded rapidly and now
accounts for a large share of the agricultural sector, the RRA calculation for this
study includes an estimate of the NRA for nontradable fruits and vegetables.
Tomatoes, onions, kale, and cooking bananas constitute about half of the value
of domestically consumed vegetables and fruits (Ayieko, Tschirley, and Mathenge
2005). Evidence in Muendo, Tschirley, and Weber (2004) suggests the total value
of domestically traded fruits and vegetables is about three times the value of the
exported counterparts. Argwings-Kodhek (2005) estimates the agricultural value
added from the domestic horticulture sector to be similar in level to that of export
fruits and vegetables plus floriculture. Further, based on Muendo, Tschirley, and
Weber (2004), we set the price of the domestic products to be about half of the
price of the export version of the same product. Because the nontraded crops tend
to be bulky, lower-priced goods (potatoes rather than green beans), the price per
kilogram of the nontraded vegetables and fruits group is set at 15 percent of the
price in the exportable sector. At this price, the value of the nontradable fruits and
vegetables is about one-and-a-half to two times that of their export counterparts.
These prices are assumed to be completely undistorted by policy. Their inclusion
in the analysis therefore tends to bring the calculated total NRA for covered farm
products toward zero, but has no effect on the calculated rates of assistance in the
importable and exportable subgroups.
Policies behind the Distortions since 1960
Kenyan agriculture benefited from a supportive policy environment during the
first 20 years of independence. Unlike their counterparts in other African countries, the Kenyan political elite had strong agricultural interests at independence.
Government interventions supported both the estate sector and small-holder
Kenya
275
production. Through the Kenya Tea Development Authority and other institutions, significant investments were made to facilitate small-holder production of
export agriculture. Pressure for efficient operation of these public enterprises in
agriculture can probably be explained by the coincidence of interests of the
numerous small-holders and the politically important estate producers (Jabara
1985; Bates 1989).
The policy stance toward cereals has been somewhat more complicated
because the country has historically tried to balance demands for low-cost maize
with support for producers. Until 1996, maize and wheat prices were administered
by the parastatal National Cereal and Produce Board and enforced by the state.
The cereals board also controlled all import and export of maize and all longdistance trade within the country. In general, prices were held within the fob-cif
band for the major cereals-producing region. However, the combination of high
transportation costs and panterritorial pricing meant that some producers
received prices outside of their local fob-cif band. In some instances, when the
cereals board found itself unable to cover the costs of serving specific regions,
it failed to open buying centers or to deliver maize for consumers (Bates 1989;
Pearson and Monke 1994).
Price administration allowed the cereals board to deduct its intermediation
costs from the wholesale prices and provided little incentive to control those costs.
Since liberalization of the maize market in 1996, marketing margins appear to
have fallen considerably for maize. Based on Nyoro, Kirimi, and Jayne (2004),
costs of moving maize from Kitale District to Nairobi have dropped from about
$400 a metric ton to $200. The main beneficiaries of this decline have probably
been the consumers (Argwings-Kodhek, Mukumbu, and Monke 1993; Nyoro,
Kiiru and Jayne 1999; Nyoro, Kirimi and Jayne 2004). The current analysis uses
marketing margins from the postreform period to estimate best-practices margins. Thus, excess charges by the National Cereal and Produce Board are treated as
a tax amounting to 50 percent of the margin that was charged, and lowering the
farmer NRA. The liberalization of maize markets seems fairly thorough now,
although the cereals board does influence prices through maintenance of stabilization stocks. Moreover, the route to liberalization was slow. In 1988, limited
unlicensed maize trade was allowed. In 1992, the liberalization process was practically halted; it was not until 1996 that the cereal board was significantly downsized. Despite increased competition from private traders, the board remains a
major player in the Kenyan maize market. Jayne, Myers, and Nyoro (2005) present
analysis suggesting that maize purchasing by the board supported domestic producer prices in 2002, when they otherwise might have fallen significantly. Their
analysis suggests that the cereals board may be serving to maintain a price floor,
in contrast to its earlier tendency to impose a producer tax.
276
Distortions to Agricultural Incentives in Africa
In contrast to maize, the NRA on wheat has been increasing recently and suggests significant price distortion. Like maize, the domestic wheat market has been
liberalized, but imports of both cereals have been subject to tariffs of 35 percent.
The maize tariff has been suspended repeatedly when large imports are required,
and Jayne et al. (2001) suggest that maize smuggling has diminished the impact of
the tariff. Tariffs on wheat, in contrast, have not been suspended, and informal
trade flows are unlikely to be large. From a political economy perspective, the difference in treatment of two cereals could be explained by the fact that maize
is grown primarily by small-holders and is consumed as a staple, while wheat is
grown primarily on estates and is consumed less widely.
Like cereals, coffee and tea markets have been administered by parastatal bodies. The Kenya Tea Development Authority and the Coffee Board of Kenya with
the Kenya (coffee) Planters Cooperative Union have had a policy of passing
through to farmers the world price minus processing and marketing costs. In
general, producer prices appear to be close to export parity calculated at the official exchange rate. However, both coffee and tea producers have complained of
long delays in payments. The delays, which imply a reduction in the real price
received, may be attributable to the local cooperative societies through which
small-holder production was channeled in addition to the national organizations. The NRA data reported here are based on payments by the tea authority
and the coffee board and so do not reflect local deductions made by cooperative
societies.
The system of pass-through pricing implies little incentive to hold intermediation costs down. Payment delays may have been partly a mechanism for covering
rising costs of intermediation by reducing the real prices paid to farmers (Pearson
and Monke 1994). Liberalization and privatization have progressed to a degree for
Kenyan tea and coffee. The tea authority has been replaced with a private body, the
Kenya Tea Development Agency. The estimated NRA for tea takes the costs
incurred by the private agency as an estimate of best practice for calculating the
marketing margins. Using this estimate, tea is subject to slight taxation on average
over the period and is currently undistorted. If a larger margin were to be
assumed, set at the average costs incurred in the late 1980s, tea would appear to be
undistorted on average over the last 40 years and to be subsidized currently. Given
the absence of any policy to explain such a subsidy and the likelihood of some
inefficiency in the earlier administration of the parastatal tea authority, the NRA
based on best practices seems preferable.
For coffee, the implicit taxation through the deviations from best practices
appears to be larger than it is for tea. The best-practice cost figures we use suggest
$100 per metric ton for final processing and marketing of arabica coffee. Costs
Kenya
277
charged over time have ranged from $25 to $800, with an average well over the
best-practices figure. Coffee marketing has also been liberalized, with the coffee
board playing a reduced role. However, liberalization of the coffee system is a continuing process. Through 2006, coffee growers were critical of requirements that
all Kenyan coffee pass through the coffee board auction, because they felt that the
system precluded access to higher prices available through direct contracting. This
problem may have been particularly serious for the highest-quality and specialty
coffees. Further criticisms suggested that coffee producers are being forced to
work through the coffee board when more innovative and lower-cost intermediation may be possible. In a sign of government responsiveness, starting in January
2007 coffee cooperatives were allowed to market coffee directly to international
dealers, avoiding the coffee board auction for the first time.
In contrast to coffee and tea, sugar policy in Kenya has been highly distortionary. Sugar prices have been administered at a level well above the free market
price, imports of sugar have been taxed heavily and subjected to quotas, and consumers of sugar have faced high excise taxes. While liberalization is fairly well
advanced in cereals, tea, and coffee markets, the sugar market remains tightly controlled by the state. Because farm-level production costs are high in many of the
sugar-growing areas, some of the assistance to the sector is passed onto farmers to
support production. However, sugar factories are well positioned to capture a
large share of the subsidy to the sector. Currently Kenya demands about 200,000
metric tons of sugar in excess of domestic production. Imports from outside the
COMESA region are subject to a 120 percent tariff. A quota of approximately
100,000 metric tons of table sugar and 100,000 metric tons of refined sugar limits
duty-free imports from COMESA countries. The quota on imports from
COMESA is allowed under a protective provision that was scheduled to expire in
February 2008, but the government of Kenya was seeking to extend this protective
quota provision to 2011. After that time, Kenyan sugar industry may be subject to
competition from lower-cost sources in the COMESA region (FAO 2007; Export
Processing Zones Authority 2005).
The liberalization of Kenya’s agricultural sector was a priority of the international financial institutions (World Bank 1998). Kenya agreed to numerous
adjustment lending programs in the 1980s and 1990s that stressed liberalization
and privatization. The country’s compliance with those programs was often poor.
Nonetheless, once the national leadership was convinced of the need for reform
(or its inevitability) and found politically acceptable mechanisms for introducing
it, the liberalization program gathered speed. The success of liberalization of
maize markets and of markets for agricultural inputs attests to the potential for
further gains in areas that remain controlled.
278
Distortions to Agricultural Incentives in Africa
Fiscal and trade policy
Historically, the government of Kenya has relied on excise taxes, income taxes, and
import duties for revenues. The mix has been complicated, but trade taxes are
becoming decreasingly important as a source of revenue. Export duties were
largely eliminated in the 1970s, and tariffs have played a decreasing role since the
introduction of a value added tax (VAT) system in 1989 (Karingi and Wanjala
2005; Muriithi and Moyi 2003). Import duties accounted for almost 40 percent
of tax revenue in the 1960s, falling to about 25 percent in the 1970s and to about
16 percent since the VAT was introduced. Excise duties continue to account for
about 16 percent of government revenue, as they did in the 1960s, while income
taxes have consistently accounted for about one-third of revenue.
The VAT now accounts for 25–30 percent of government revenue. It was initially differentiated into 15 categories, with rates ranging from zero to 150 percent.
It was soon simplified to a system of 4 (and later 3) categories, ranging from zero
to 16 percent with a standard rate of 16 percent. In addition, a few goods, including sugar, remain subject to excise taxes. Both imported and domestically produced goods are subject to the same VAT rates. Imports, however, are subject to
separate import duties. Thus the tax on imported sugar from non-COMESA
sources includes both an import duty of 120 percent and a development duty of
7 percent in addition to the 16 percent VAT charged on all noncereal agricultural
products.
Average import tariffs have been falling in Kenya. This reflects efforts to comply with the World Trade Organization as well as a strategy since the mid-1970s of
reducing import tariffs on industrial inputs as a way to increase effective protection of the manufacturing sector. Average tariffs have been falling, but tariffs on
agricultural products have risen over the past 15 years. Average tariff rates on food
and livestock are now about 35 percent, with much higher rates on sugar and a
few other specific agricultural products.
While the trend in increased applied import duties in agriculture appears pronounced, it is not clear how great the practical implications are. Because trade in
most agricultural products was controlled by parastatal organizations for most of
the period 1955–90, nontariff barriers to imports were the more relevant source
of distortion. Partly in response to pressures from the WTO and international
financial institutions, the nontariff barriers have been replaced with tariffs. The
trend toward zero in the calculated NRA would suggest that the current applied
tariffs in agriculture have less impact than the nontariff barriers of the past. Be
that as it may, the applied tariffs are distorting for specific crops (such as wheat),
and uncertainty about the application of tariffs may negatively affect potential
importers of maize.
Kenya
279
Regulation, red tape, and rent seeking
Over the last 20 years, Kenya has preserved a large state presence in much of the
economy and has also developed a reputation for corruption. Allegations and evidence of fraud and corruption have at times been particularly strong in the area of
customs and international trade. The abundance of red tape and the possibility of
corruption among those administering paperwork raise transactions costs and
create inefficiencies in the economy that are not captured in this analysis. According to the World Bank’s Doing Business survey for 2005, importing into Kenya
required 13 documents, 20 signatures, and 62 days compared with 9 signatures
and 34 days in South Africa and 10 signatures and 25 days in Thailand. Exporting
from Kenya required 15 official signatures and 45 days, compared with 7 signatures and 31 days in South Africa and 10 signatures and 23 days in Thailand.
Many of the regulations in the Kenyan economy are perceived to foster corruption and rent seeking, further raising transactions costs. The “corruption perception index” published by Transparency International ranked Kenya 144th out of
158 countries in 2005, placing Kenya in a tie with Somalia, Sudan, and the Democratic Republic of Congo. Apparent improprieties in the 2007 presidential election
reinforced the impression of corruption in the country. Even if corrupt practices
were controlled in Kenya, the relatively onerous paperwork requirements constitute an impediment to trade and economic growth. Initiatives are now in progress
in Kenya to create a fast track that would remove license requirements in the
absence of environmental, health, and safety considerations. Moreover, the Doing
Business survey for 2007 (World Bank 2006) indicated a marked reduction in red
tape since 2005.
Prospects
The Kenyan economy has historically benefited from good performance in agriculture, while the agricultural sector has benefited from a political elite that had
strong rural links, largely through the estate sector. In the recent past, agricultural
production has faltered, the economy in general has suffered, and poverty has
spread. Although direct taxation of the agricultural sector does not seem to have
been a substantial factor in this decline, indirect taxation through currency overvaluation played a role. Other policy factors that probably contributed to the
decline in the sector include growing domestic marking margins, which stem
from poor infrastructure services and high costs in the parastatal marketing
enterprises. One explanation for the government’s tolerance of these rising costs
in the agricultural sector could be that the political elite found it increasingly
attractive to use agricultural marketing institutions and monetary policy to serve
280
Distortions to Agricultural Incentives in Africa
short-term political goals including redistribution, employment, and patronage
rather than long-term economic development (Bates 1981).
Sound public investment in developing the horticulture sector indicates that
the Kenyan government is willing to make strategic moves to enhance agricultural
output. Meanwhile, heavy investment in sugar and continued protection of the
sector suggests that agricultural policy will continue to be used to affect politically
important distributional objectives.
Policy reforms to liberalize the agricultural markets were made in the hopes of
reducing marketing margins and increasing agricultural output. In the case of
maize markets, in which the parastatal cereals board now plays a much-reduced
role, this goal was achieved. Marketing margins have fallen by half compared with
the prereform period, and consumer prices have fallen as a result. There is less evidence of such reductions in marketing margins or a shift toward competitive and
open markets in the case of coffee, tea, and sugar. However, the loosening of
administrative regulations restricting trade and marketing systems is encouraging.
Further expansion of the agricultural sector probably requires public investments in areas of potential comparative advantage (such as horticulture), continued policy reforms to reduce the costs of doing business, and maintenance of a
stable macroeconomic environment to encourage private investment. Whether
policy makers in Kenya will find such policies in their interests remains to be seen,
but the current political debate and recent administrative reforms suggest the possibility of further progress.
Notes
1. Unless otherwise noted, data in this paper are from the World Bank’s World Development
Indicators online (www.worldbank.org/data).
2. The low rates of assistance shown in this analysis are consistent with Jayne, Myers, and Nyoro
(2005), who indicate that maize prices have averaged only 2–3 percent above import parity over the
last 15 years, despite the de jure 20–30 percent tariff.
3. Winter-Nelson and Argwings-Kodhek (2007, appendix figure 4) present NRA estimates using
both the cif price and the free market reference price for sugar adjusted for shipping costs. Only when
the Kenya shilling was significantly overvalued did the NRAs become negative. While the cif data can
be expected to understate the degree of protection, the rates indicated from use of the reference price
cannot be defended based on actual policies. Because sugar’s share of agricultural production is small,
the choice of sugar price has little impact on the weighted average NRA, but it has considerable effect
on the estimated assistance to importables when maize is treated as an exportable or nontradable.
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10
Sudan
Hamid Faki
and Abdelmoneim Taha*
Agriculture is the most important sector in Sudan’s economy. It accounts for close
to 40 percent of the country’s gross domestic product (GDP), provides a livelihood for more than 80 percent of the population, and employs about 70 percent
of the active labor force. This study is by no means the first examination of price
and trade policies in Sudan, but it is the most comprehensive in terms of its commodity and temporal coverage.1 In this chapter, we examine the evolution of policies since 1955 and provide new estimates of the effects of distortions on agricultural incentives for 12 of Sudan’s agricultural products. Together, these products
account for around three-fourths of agricultural output value.
Since independence in 1956, Sudan’s agricultural policies have provided government hegemony over production, marketing, and trade of farm products
through a series of public-sector-led development plans, production and marketing parastatals, and close control of foreign exchange transactions with an overvalued currency. Many attempts were made to reduce overvaluation, particularly
during the 1980s with interventions from the World Bank and the International
Monetary Fund, but it persisted into the late 1990s. Trade flows were for a long
time subjected to quantitative controls and licensing, and the tariff structure
continued to tax trade until recently. Agricultural import tariffs averaged about
30 percent in recent years.2
Market interventions have been accompanied by significant public investment
in agriculture, most of which has been directed to the irrigated sector, with
notable neglect of the economically more important traditional, rainfed sector.
* The authors are grateful for helpful comments from workshop participants. Detailed data and estimates of distortions reported in this chapter can be found in Faki and Taha (2007).
283
284
Distortions to Agricultural Incentives in Africa
Other important policies since independence include land acquisition, production controls, and land and crop taxes (especially indirect ones) that have provided the bulk of government budget revenue.
This chapter begins with a summary of the country’s economic growth and
structural changes since independence. It then provides empirical estimates of the
changing extent of distortions to agricultural incentives over the past 50 years.
The reasons behind the government’s policy choices are analyzed, and the chapter
concludes with a discussion of prospects for further policy reform.
Growth and Structural Changes since 1955
With a total land area of about 2.4 million square kilometers, Sudan is the largest
country in Africa in geographic terms. Demographically, its population of around
36 million is growing at a rate of about 2.6 percent a year. Economically, even by
the most conservative estimates, more than 50 percent of the population is living
on less than $1 a day. Poverty in Sudan is mainly a rural phenomenon, and the
level of poverty is closely linked to the strength of agricultural productivity. The
economy is based predominantly on agriculture, which in turn is based on three
major farming systems: irrigated; rainfed, semimechanized; and rainfed traditional agriculture, accounting for around 30 percent, 10 percent, and 60 percent of
agricultural production, respectively. Crop production accounts for 53 percent of
agricultural output, livestock for 38 percent, and forestry and fisheries (not considered in this study) for 9 percent. About 60 percent of all crop production comes
from the irrigated sector, 7 percent comes from mechanized dryland farming, and
the remaining 33 percent from the traditional rainfed sector.
Ever since a period of food shortages in the 1980s, the government has given
attention to the production of food crops, resulting in large expansions in the
amounts of sorghum and wheat planted and harvested, often at the expense of
the main cash crop, cotton, the production of which has declined by more than
40 percent since the mid-1980s. Livestock production is most prevalent in the traditional rainfed farming systems but is increasing in irrigated areas.
Although endowed with rich natural resources, Sudan remains underdeveloped, primarily as a result of protracted civil strife and poor economic management. During the three decades from 1960 to 1990, the Sudanese economy experienced low and sometimes negative rates of growth and deteriorating real per
capita income. The poor economic performance was reflected in other economic
indicators such as deficits in government accounts, accelerating rates of inflation,
deterioration in national savings and in the value of the national currency, and
frequent food shortages.
Sudan
285
Economic development in Sudan has largely been influenced by the country’s
colonial history (D’Silva and Elbadawi 1988). Agriculture has always been the
main sector shaping development patterns and growth throughout the economy,
and the government has tended to take a paternal attitude over the whole economy, especially the production sectors through excessive regulations (FAO 1997).
A major feature of Sudan’s agricultural development has been its focus on expansion of irrigated agriculture and mechanized rainfed farming, a situation that
started early in the colonial era and continued after independence. The vast traditional rainfed sector, which accommodates the majority of the population and
contributes significantly to foreign exchange earnings, has been neglected (D’Silva
and Elbadawi 1988). For example, in 2004, the traditional crop and livestock sectors received only 25 percent of total public expenditure on agriculture, which
itself amounted to less than 1.9 percent of GDP (Abdalla et al. undated).
The contribution of agriculture to the country’s GDP has ranged from 29 percent to 46 percent during the last half century, averaging 38 percent and surpassing in many years that of the services sector (which itself is highly dependent on
agricultural activities). The share of industry was relatively low but has increased
during the current decade. Growth of agricultural output has been variable and,
in many years, negative. Because agriculture is the main source of economic
growth in the country, overall GDP growth had been variable and low, with an
annual growth rate of 0.3 percent for the entire 50-year study period.
Agriculture was also the major source of foreign exchange before the discovery
of oil, contributing close to 100 percent of the total value of merchandize exports
until oil exports began in 1999. Since then its share of exports has averaged
around 25 percent (figure 10.1). Meanwhile, agricultural imports have been
steadily increasing in value relative to exports. In the 1960s, farm imports averaged about 20 percent more than farm exports; today they average more than 100
percent (figure 10.2).
Traditionally, the export structure has been dominated by five commodities:
cotton lint, sesame, groundnuts, live animals, and gum arabic. Since 1961 these
five commodities have contributed between 50 and 90 percent (on average,
77 percent) of all agricultural exports (figure 10.3). Cotton led those exports—
although with substantial annual fluctuations—until the early 1990s, when live
animals and sesame became more important. Gum arabic has retained its importance relative to groundnuts, whose exports declined in the early 1980s, in part
because of increases in processing for domestic consumption of groundnut oil.
Except for some processing of oilseeds and cotton, agricultural raw material processing has been weak, hampered by poor transport and other infrastructure and
shortages of essential inputs such as electricity and fuel (Ministry of Finance and
National Planning 2006a, 2006b).
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Distortions to Agricultural Incentives in Africa
Figure 10.1. Share of Agriculture in All Merchandise Exports,
Sudan 1961–2004
100
80
percent
60
40
20
19
6
19 1
6
19 3
6
19 5
6
19 7
6
19 9
7
19 1
7
19 3
7
19 5
7
19 7
7
19 9
8
19 1
8
19 3
8
19 5
8
19 7
8
19 9
9
19 1
9
19 3
9
19 5
9
19 7
9
20 9
0
20 1
03
0
year
Source: Compiled by the authors using FAOSTAT data.
Figure 10.2. Value of Agricultural Imports as a Share of Value
of Agricultural Exports, Sudan, 1961–2004
180
160
140
percent
120
100
y = 2.1204x + 6.3174
80
60
40
20
19
6
19 1
6
19 3
6
19 5
6
19 7
6
19 9
7
19 1
7
19 3
7
19 5
7
19 7
7
19 9
8
19 1
8
19 3
8
19 5
8
19 7
8
19 9
9
19 1
9
19 3
9
19 5
9
19 7
9
20 9
0
20 1
03
0
year
Source: Compiled by the authors using FAOSTAT data.
Note: Equation shows ordinary least squares estimate of a linear time trend, with an average annual
increase in the ratio of agricultural imports to exports of 2.1204 percent per year.
Sudan
287
Figure 10.3. Product Shares of Agricultural Exports, Sudan,
1961–2004
100
90
80
percent
70
60
50
40
30
20
10
0
61 964 967 970 973 976 979 982 985 988 991 994 997 000 003
2
2
1
1
1
1
1
1
1
1
1
1
1
1
year
19
residual
groundnuts
gum arabic
live animals
sesame
cotton lint
Source: Compiled by the authors using FAOSTAT data.
Policy Evolution and the Economy
This section summarizes the history of growth and economic policies in the
Sudanese economy, delineating the periods by changes in political systems or specific
economic policies and programs. This is not the place to discuss macroeconomic
policies in detail; but they are crucial, and exchange rate policy in particular has been
a major factor in directing the pace and path of change in Sudan’s economy.
The colonial period
From 1899 to1956, Sudan was under British colonial administration, whose policies laid the foundation of the modern economy (Abdelgadir and Elbadawi 2002).
The centerpiece of this economy was long-staple cotton grown under irrigation.
British colonial rule early in the 20th century involved state control over agricultural patterns of land use that largely remain in place today. A law enacted in
1903 enabled the government to acquire land by expropriating all rights, which
was followed by the Land Acquisition Ordinance of 1930 that authorized the
British governor general to acquire land for public purposes against payment of
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Distortions to Agricultural Incentives in Africa
compensation (Tothill 1948). Privately owned farmland remained in some areas,
mostly along the Nile in the northern part of the country where land is particularly valuable, and agriculture was based on irrigation using the traditional sagia
waterwheel.
Land acquisition allowed the colonial government to charge rent and tax private
investment in pump enterprises along the main Nile north of Khartoum and in the
Khartoum area, where land use was allotted to tenants using yearly leases. In northern Sudan, in response to problems of land fractionation that built up on account
of Islamic inheritance rules, policy was directed to the development of government
pump schemes behind sagia land strips. This involved attracting freeholders to sell
land to the government to be reallotted on a government tenancy basis.
During and immediately after the First World War, the government opened
seven major irrigation and agricultural development projects in the north, basically to feed British regiments then stationed in Egypt. These projects continue to
function today, albeit with different and varying objectives and management over
time. The single most far-reaching undertaking was and remains the Gezira irrigation system, which currently covers nearly 1 million hectares of land. Early steps
toward establishment of the project took place in 1911, with the main objective
being to produce cotton for British industry. Initially, tenants on cotton land were
required to pay a fixed charge for water. Eventually a cost and profit-sharing
arrangement was established between the government, the Sudan Plantation
Syndicate that was then in charge of the business, and the Gezira tenants, with
respective shares of 35 percent, 25 percent, and 40 percent. Those shares underwent many changes before and after independence, but the basic structure has
largely remained. Crops other than cotton, once exempted from irrigation-water
charges, are currently subject to such payment. The Gezira scheme served as a
model for the establishment of many other government irrigation schemes, bringing the total area under irrigation to some 2 million hectares. The government,
which practiced close control over the areas and the types of crops to be grown,
provided most of the inputs or the financing for them. The most important crops
grown under irrigation are cotton, groundnuts, sorghum, and wheat. The government still controls cotton ginning and cotton exports and has controlled wheat
delivery and distribution for extended periods of time.
Agriculture formed the main source of government revenue through direct
and indirect land and crop taxation and other avenues. Important types of direct
taxes were levies on land, date trees, and rainfed crops. Land taxes included a tax
on the estimated value of land itself and one on the gross value of crops produced. Taxes on date palms were levied exclusively in northern Sudan. Taxes
known as ushur were levied on the produce of rainfed areas at 10 percent ad valorem, consistent with the Islamic zakat. However, the administration aimed at
Sudan
289
keeping direct taxes at low levels. Over a seven-year period in the 1940s, the three
types of taxes contributed only 1.4 percent to Sudan’s total budgetary revenue
(Tothill 1948).
Indirect taxation included two main items: royalties on gum arabic and other
natural products, and customs charges. Royalties were levied ad valorem on
tobacco and per unit weight on export in the case of exportables such as gum arabic. Customs duties were charged on all of Sudan’s exported produce at a rate
of 1 percent. Agricultural producers also contributed to government revenue
through the prices paid to government monopolies, for cotton transport on
inland railways, and for the import and sale of sugar. Taken together, the sum of
all agricultural taxes is estimated to have accounted for about 40 percent of government budget revenue (Tothill 1948).
The 1956–70 period
At independence in 1956, agriculture dominated the Sudanese economy, contributing about 61 percent of GDP (Abdelgadir and Elbadawi 2002). The industrial sector was rudimentary, with a share of just 1.1 percent of GDP, while the
services sector accounted for the remaining 38 percent of GDP. The economy
was clearly dualistic in nature, with a vast traditional sector and a small modern
sector—a situation that continues today.
Following independence in 1956, Sudan adopt the first in a series of development plans. The Ten-Year Plan of Economic and Social Development,
1961/62–1970/71, placed considerable emphasis on the development of agriculture, allocating about 27 percent of total public investment to the sector. This
investment was driven by a campaign to combat hunger and malnutrition and to
provide food and nutritional security through an import substitution program to
increase production of wheat and sugar and through improvement of livestock
and horticultural products. The modern irrigated subsector received the lion’s
share of the projects in the investment plan. The Roseires dam, 620 kilometers
south of Khartoum, was the key project in a plan to enhance the water supply
and thus diversify and intensify irrigated cropping. The plan also sought to
expand sugar production by 25 percent. The economy in general was stable
compared with that of the 1970s and beyond, but imports started to expand in
quantity and value, resulting in trade deficits.
The 1970s and 1980s
In the early 1970s, the Sudanese government and the governments of some Persian Gulf states saw Sudan as a potential food basket for the Arab world. Sudan’s
290
Distortions to Agricultural Incentives in Africa
agricultural strategy thus shifted its emphasis from production of cotton and
other nonfood crops toward food production and export, using Arab funds
and western technology to produce wheat, sugar, livestock, and textiles for export
and to promote sugar and wheat as import substitutes. This was planned within
the framework of the Five-Year Plan of 1970/71–1974/75, which later was
extended to 1976/77. Key objectives of the plan were to adopt a socialist development path to achieve average annual GDP growth of 8 percent, raise agricultural
production by 61 percent, increase livestock production by 75 percent, increase
industrial production by 57 percent, and satisfy national demands for food.
Implementation did not follow the plan, however; investment was diverted
from agriculture to the transport and communications sectors, and the majority
of the projects were not completed. Overall GDP growth for the period was only
4 percent. Not only did Sudan miss its planned targets on food import substitution, but discrimination in Sudanese policy against export crops, particularly cotton, caused real exports to decline by 13 percent between 1970 and 1977. In 1974,
a sharp increase in the price of fuel and capital goods increased the cost of imports
by more than 100 percent, leading to mounting deficits in the current account of
the balance of payments.
During the late 1970s, Sudan’s economy began to experience severe, interdependent structural problems that inhibited economic growth. The internal sector
had long suffered from excess aggregate demand resulting in inflationary pressures
in the economy. The situation was further aggravated by the devastating effects of
a civil war in the south and frequent incidence of drought. The external sector
experienced a continuous deficit in the balance of payments, and foreign debt
mounted. Exacerbating these problems was the government’s approach to the
economy, which included confiscation and nationalization of industrial and agricultural firms and banks and a diminished role in economic activities for the private sector. During this period the government set prices for production, exports,
imports, and consumption goods in addition to putting controls and restrictions
on import and export quantities. Furthermore, the government expanded the public sector, which was often criticized for its inefficiency and poor performance.
To address these issues, the government launched a series of development
plans and programs, the most important of which was an economic recovery program. Its major targets were the adoption of a more realistic exchange rate, reduction of quantitative restrictions on exports, and removal of export taxes. The
Sudanese pound was devalued, and attempts were made to adopt tighter demandmanagement policies. The potential effects of these policies were undermined,
however, by rising inflationary pressures. Between fiscal 1978 and fiscal 1984, the
official exchange rate was devalued by 14.5 percent a year on average, whereas
domestic inflation averaged 27 percent a year (Hag Elamin and El Mak 1997).
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291
A number of sector-specific policies were implemented in agriculture, the
most important being the introduction of the individual account system of production relations in the Gezira scheme in 1981,3 general rehabilitation of the
major public agricultural schemes, reduction of agricultural export taxes, and the
dismantling of the parastatal Oilseeds Company’s monopoly on oilseeds exports.
Despite these policy reforms, a host of other policy variables were left
untouched (Hag Elamin and El Mak 1997). The government, through its agricultural public corporations, continued to control the irrigated sector. These public
corporations dictated crop rotations, varieties to be grown, and input quantities,
and set farmgate prices for cotton, wheat, and gum arabic. The corporations also
continued to recover their land and water costs for all crops through their control
of cotton marketing, which made cotton relatively less profitable than other crops.
The state also continued its marketing monopoly for principal export commodities such as cotton, gum arabic, and oilseeds but failed to achieve its major objective of stabilizing producer prices. At the same time, the export monopoly dampened incentives for producers by paying them low prices compared with
international levels.
The Agricultural Bank of Sudan (ABS) was the principal supplier of formal
credit to agriculture, while informal lenders dominated rural financial markets in
Sudan. The bank’s credit was channeled mainly to a limited number of large-scale
farmers who could provide collateral. But the bank was nonetheless unable to
recover on many of its loans. It also experienced high administrative costs, interest
rates fixed at negative real values, capital erosion, poor coordination, and inadequate supplies of loanable funds. The other source of formal credit to agriculture
was the Bank of Sudan, which provided loans to farmers through the public corporations. In most cases, farmers receiving the loans treated them as a subsidy
from government that did not need to be repaid, and so the public corporations
accumulated debt, a factor that contributed significantly to their inefficiency. All
other banks’ credit to agriculture was negligible, however, because they concentrated on financing industry and foreign trade.
The economy in general, and agriculture in particular, was crippled by a series
of cumbersome bureaucratic procedures such as import licensing, registration of
exporters, reporting of stocks, and restrictions on crop movements, all of which
greatly discouraged production and exports. Moreover, domestic policies were
unstable; for example the government monopoly over oilseeds was abolished and
then reinstated. Further, a host of exogenous negative shocks, including civil war,
drought, and famine, and an influx of refugees from neighboring countries, coincided with the implementation of the adjustment policies in 1978–85. The performance of the economy was poor under the economic recovery program—GDP
growth declined to 2.2 percent, the government budget deficit tripled, the rate of
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Distortions to Agricultural Incentives in Africa
inflation rose to an annual average rate of over 27 percent, and the balance of
payments continued to deteriorate (Hag Elamin and El Mak 1997).
The 1986–89 period
The economic recovery program ended in April 1985, when a civil uprising,
mainly driven by poor economic conditions for the majority of the population,
led to a political change in the government. In 1987, the newly elected government, together with the World Bank and the International Monetary Fund, prepared an action program. Under the program, the exchange rate was unified and
devalued by 44 percent, and a compensatory rate (in lieu of interest rates, which
are forbidden under Islamic law) was introduced within the Islamic banking
system, with effective lending rates pegged at 3 percentage points above the
annualized quarterly rate of inflation. To encourage production, the preseason
announcement of prices was expanded to include additional commodities.
There were also substantial increases in the consumer prices for fuel (25 percent), sugar (66 percent), cement (33 percent), and other basic commodities previously provided with indirect subsidies (through the multiple exchange rate
system) or direct subsidies (through the central government’s budget and
pricing policies).
These policy measures led to trade union strikes and street demonstrations,
which forced the government to declare the action program inoperative. Partial
adjustments made before 1989 were associated with increased inflation, underuse
of capacity, stagnant economic growth, and a heavy dependence on food aid and
external foreign assistance. A change in the political regime in 1989 led to another
new formulation of economic programs.
National Economic Salvation Program policies, 1990–93
In response to the woes of the late 1980s, the government embarked on a threeyear (1990–93) National Economic Salvation Program that aimed to reallocate
available resources in favor of the production sectors, particularly agriculture.
Objectives included food self-sufficiency, food security and social equity, liberalization and deregulation, removal of administrative and legal barriers to agricultural exports, private sector enhancement, and financial and social stability (Hag
Elamin and El Mak 1997). Vulnerable segments of the society would be targeted
for social welfare programs to alleviate adverse effects of adjustment. General economic reforms were directed at foreign exchange, trade, fiscal, and monetary policies. The nominal exchange rate was devalued (Abdelgadir and Elbadawi 2002),
but recognizing the adverse effects of foreign exchange liberalization on prices of
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293
imported inputs, the government adopted a preferential exchange rate (between
the official and market exchange rates) for the import of essential inputs.
The program also sought several specific agricultural objectives, including:
• The removal of subsidies on goods and services provided by the production
corporations, mainly fertilizers, insecticides, land, and water.4 Significant
reductions in subsidies on food products were also planned.
• The lifting of government price controls and regulations on agricultural commodities. The government would continue to set a minimum procurement
price for wheat.
• An end to the monopolies held by the public marketing parastatals, namely, the
Oil Seeds Company, the Livestock Marketing Corporation, and the Cotton
Company.
• A freeze on the role of the Ministry of Commerce in setting product prices;
ministerial committees were to be formed to oversee a set of flexible signal
prices.
• A reduction of export taxes to 5 percent for all exports except cotton and gum
arabic, for which export taxes were reduced to 10 percent.
• A shift in financing from the agricultural public corporations to a consortium
of commercial banks, with higher credit ceilings and expanded services for
agriculture, including the establishment of new specialized banks and adoption of Islamic forms of lending.
• Revision of the 1990 Investment Encouragement Act to include more concessions and privileges to attract national and foreign investment.
• Reform of government administrative structures to cope with liberalization
policies and to enhance the role of the private sector.
Reform policies since 1993
Under the 1992 liberalization policy, previous controls that negatively affected the
private sector role were abandoned. The most significant of those was the yielding of
export earnings to Sudan’s central bank at overvalued official rates, while domestic
prices and access to foreign exchange were subject to black market conditions. The
reform policy after 1992 seemed to be implemented consistently and rapidly and
reflected a continuing relaxation of restrictions on foreign exchange, credit, and
product prices; a high rate of privatization of state-owned enterprises; attraction of
foreign direct investment; wide abolition of subsidies; reduction of direct agriculture taxation; and introduction of a value added tax to replace production taxes.
Following the reforms of 1992, GDP growth improved significantly, rising
from 1.2 percent during the 1980s to a high of more than 10 percent in the early
294
Distortions to Agricultural Incentives in Africa
1990s. Favorable natural conditions contributed to improved agricultural production, but rapid growth was accompanied by high rates of inflation, deterioration
in the value of the local currency, and rising costs of production, associated with a
significant increase in the money supply and high government borrowing from
the banking system. This macroeconomic situation offset the benefits from potential positive production; by 1996, GDP growth had fallen back to 4.7 percent, and
features of former economic crises started to recur. According to Sheikh Musa
(2001), the deterioration in the economy in 1996 could be attributed to the previous structural problems that had not been corrected along with poor implementation of financial and monetary reforms. Efforts were made to ease structural
problems but insufficient account was taken of interrelationships between sectoral policies, macroeconomic policy, and economic growth.
In 1997, the government undertook a more comprehensive economic and structural reform program monitored by the International Monetary Fund. The objectives of this program were the removal of exchange rate distortions along with the
formulation of financial and monetary policies to remove negative performance of
the current account and the increased rate of inflation; the normalization of relations with regional and international financial organizations as steps to improve the
flow of external financial resources needed to rehabilitate the basic infrastructures of
the production sectors; and the abolition of the speculative marginal activities in
foreign exchange, automobile, crop markets, and other strategic commodities. The
program was implemented in three stages: a short-term (second half of 1996) fiscal
shock program to remove the distortions in the financial and monetary sectors and
ease the pressure on aggregate demand and demand on foreign exchange; a one-year
(1997) program of financial and monetary reform with a component of social support to mitigate the negative effect of liberalization; and a subsequent one-year
(1998) program aimed at increasing aggregate supply to narrow the gap with aggregate demand, in addition to expansion of social programs.
By the end of 1996, the economy started to respond positively to the reform
program, and by the end of 1998, economic indicators were showing clear gains.
Real economic growth averaged 6 percent for the year, the annual rate of inflation
fell to 17 percent, the current account deficit declined to 4 percent of GDP, the
budget deficit dropped to 0.5 percent of GDP, annual growth in the money supply
declined to 19 percent, and export volumes increased.
Building on the positive results of these reform programs, and to maintain and
consolidate the economic gains achieved, a follow-on program for 1999–2002 was
designed and implemented with the support of the International Monetary Fund.
The main features and agenda of that program were comprehensiveness in targeting all aspects of economic liberalization, capacity strengthening of human
resources and infrastructure, development of social services, and normalization of
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295
external relations to attract foreign support. Considerable gains were realized in
overall economic stability through recapturing the balance between aggregate
demand and supply, lowering the rate of inflation, converting the foreign
exchange rate system into a more realistic, single free-market rate, and increasing
overall growth, which reached 8 percent in 2000.5
It can be argued that, after more than a decade of liberalization, Sudan has still
not managed to put in place adequate practical policy measures and institutionbuilding mechanisms to promote outward-looking and proactive private sector
strategies. For instance, it has not moved to privatize noncore activities or to free
up markets (particularly for key export commodities such as cotton and gum arabic) so as to enable the private sector to procure all its needed inputs at competitive world market prices. As a result, despite the macroeconomic and sectoral
reforms described above, the outlook for future growth remains uncertain.
Estimates of the Changing Extent of Distortions
With this policy history as background, the rest of this study focuses on estimating
the extent to which prices facing farmers have been distorted over the past
50 years, generating an antiagricultural bias and, within the sector, an antitrade
bias. The methodology adopted is the standard one for this project (see appendix
A and Anderson et al. 2008), which seeks to measure the government-imposed
distortions that create a gap between domestic prices and what they would have
been under free markets. Because the characteristics of agricultural development
cannot be understood from a sectoral view alone, the project’s methodology not
only estimates the effects of direct agricultural policy measures (including distortions in the foreign exchange market) but also generates estimates of distortions
in nonagricultural sectors for comparative evaluation.
More specifically, this study computes a nominal rate of assistance (NRA) for
farmers by calculating the difference between the prices actually paid to domestic
producers and what those prices would have been under free market conditions.
No adjustment is made for interventions on input markets, because of a lack of
data. The study also provides an NRA for nonagricultural tradables, for comparison with the NRA for agricultural tradables through the calculation of a relative
rate of assistance (RRA).
Twelve commodities have been identified based on their contribution to
the country’s value added. Grouped into relevant categories, these are importcompeting products (wheat, sugar, and milk), exportable cereals (sorghum and
millet), exportable oilseeds and oils (sesame and groundnuts), exportable livestock (live sheep, cattle, camels, and goats), and lightly processed exportables (cotton lint, cleaned gum arabic, and cheese). Together these commodities have
296
Distortions to Agricultural Incentives in Africa
contributed 80–90 percent of the value of agricultural output, with most of the
rest being shared by a wide range of vegetables and fruits. Data for the analysis
were collated from various secondary sources for the period 1955 to 2004, as
detailed in the appendix to Faki and Taha (2007). Throughout the five decades,
milk and beef cattle made the biggest contributions to the value of production,
followed by sheep and goats and (before the1990s) cotton. Sorghum has been the
most valuable grain, followed by millet, while groundnuts and sesame have been
equally valuable contributors to oilseed production. Gum arabic, while important
in exports, has contributed only 1 or 2 percent to the value of production. The
consumption shares are similar, making animal products unusually high for such
a low-income country.
Nominal rates of assistance
Our estimates of commodity assistance rates are summarized by five-year time
periods in table 10.1, and annually in aggregate form in figure 10.4. In most periods, the importable commodities (wheat, sugar, and milk, making up about onefifth of the value of farm production) enjoyed positive direct assistance. Not surprisingly, when international food prices spiked in 1973–74, their domestic prices
did not respond fully, and so the NRA for this subgroup became as negative as for
exportables. But its average NRA was much higher than that for exportables,
implying a strong antitrade bias within the sector throughout the past half century. Among the exportables, the cash crops such as gum arabic and sesame,
together with live animals, have been the most heavily taxed, and the staple foods
(sorghum, millet, and groundnuts) the least heavily taxed. The NRA estimates for
the various covered products, including those for the exportable and importcompeting sectors, fluctuate a great deal over time (see figure 10.4). But in terms
of trends, the 10-year average NRAs for covered exportables became ever more
negative until the mid-1990s. Since then, however, the extent of implicit taxation
has fallen, from 65 percent in 1990–94 to 34 percent in 2000–04.
The noncovered products (mostly fruits and vegetables, whose markets are not
subject to government intervention except through exchange rate distortions),
account for between 10 and 20 percent of the value of agricultural production.
Taking these noncovered products into account makes the estimated total NRA
for the agricultural sector somewhat less negative (top of table 10.2).
The middle rows of table 10.2 show the estimated NRAs for tradable agriculture and the nonagricultural sectors, from which the relative rate of assistance is
calculated. That RRA is an indicator of the percentage by which the prices of farm
relative to nonfarm outputs have been distorted from their free market levels. The
RRA has been quite negative, moving from around 15 percent in the 1950s to
45 percent by the early 1970s, before becoming less negative through to the end
Table 10.1. NRAs for Covered Farm Products, Sudan, 1955–2004
(percent)
Product indicator
Exportables
Sorghum
Millet
Groundnuts
Sesame
Cotton
Gum arabic
Livestock
Sheep
Cattle
Camels
Goats
Import-competing productsa
Wheat
Sugar
Milk
Total of covered productsa
Dispersion of covered productsb
Percent coverage (at undistorted
prices)
1955–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
22.3
35.3
76.8
41.2
40.3
7.8
33.3
10.5
33.9
2.4
5.3
20.0
19.1
10.1
—
19.4
15.9
33.6
75
35.4
48.8
73.2
55.3
52.5
4.9
33.4
40.1
53.2
36.2
38.8
8.4
19.2
4.9
42.4
19.0
25.4
34.2
80
43.4
39.9
71.9
51.7
63.6
11.8
42.0
51.1
55.8
44.8
61.7
38.1
11.4
0.6
41.2
16.2
36.8
32.9
86
51.1
54.3
41.2
59.8
65.3
10.2
58.5
59.5
66.7
59.8
34.4
60.2
35.7
35.6
45.2
41.1
48.5
35.0
90
37.7
39.7
18.6
59.0
67.8
7.4
47.4
34.2
51.0
31.9
29.6
43.1
23.4
10.6
26.5
26.5
28.3
38.8
86
38.5
48.6
6.2
55.4
59.5
2.1
61.1
34.1
43.9
32.6
0.7
32.6
9.3
6.5
35.7
3.5
32.9
31.1
89
58.1
23.8
7.9
33.3
48.4
1.0
66.7
67.1
61.7
61.9
69.3
59.4
65.3
31.5
16.5
79.2
38.9
52.5
91
Source: Data compiled by the authors.
297
Note: — no data are available.
a. Weighted averages, with weights based on the unassisted value of production.
b. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
64.8
75.5
76.2
36.1
48.1
31.9
57.3
76.7
76.7
74.5
85.3
53.7
21.2
58.8
20.1
33.1
53.9
72.3
87
41.8
20.9
8.7
52.2
49.9
10.3
59.8
47.5
61.4
42.9
23.6
50.6
6.8
19.8
24.4
1.9
29.2
40.5
85
34.2
10.9
0.4
28.9
38.1
17.0
67.1
30.0
37.4
45.1
87.7
13.3
35.8
22.2
120.5
29.3
14.6
60.9
83
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Distortions to Agricultural Incentives in Africa
Figure 10.4. NRAs for Exportable, Import-Competing, and All
Farm Products, Sudan, 1955–2004
120
80
percent
40
0
40
80
19
55
19
58
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
120
year
import-competing products
exportables
total
Source: Data compiled by the authors.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
of the 1980s as international food prices fell after their spike in 1973–74. Then the
RRA repeated that cycle, becoming more negative in the first half of the 1990s
before the policy reforms began to take hold in 1993. After that, the RRA moved
much closer to zero at 18 percent in 2000–04 (and just 9 percent in 2004),
compared with 56 percent a decade earlier. While the negative RRA means an
antiagricultural bias is still present, the reforms have driven that intersectoral
distortions indicator to its lowest level in the 50 years (figure 10.5).
The bottom rows of table 10.2 show what three of these indicators would have
been if distortions in the market for foreign exchange had been ignored in our calculations. They reveal that before 1993, up to one-third of the NRA for the overall
agricultural sector was attributable to exchange rate distortions, and even more to
the antiagricultural trade bias. Only a small fraction of the RRA stems from that
distortion though, reflecting that the exchange rate impacts on all tradable sectors
and that the sizes of those impacts depend on the shares of the import-competing
and exportable subsectors in each sector.
Table 10.2. NRAs in Agriculture Relative to Nonagricultural Industries, Sudan, 1955–2004
(percent)
Indicator
1955–59 1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
NRA, covered products
NRA, noncovered products
NRA, total, all agricultural products
Trade bias indexa
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAb
Memo item, ignoring exchange
rate distortions:
NRA total, all agricultural products
Trade bias indexa
RRAb
15.9
0.8
11.7
0.30
15.4
0.9
16.1
25.4
0.6
20.3
0.45
24.9
2.4
23.2
36.8
0.5
31.8
0.36
36.4
5.6
32.7
48.5
0.3
43.4
0.24
48.1
4.7
45.6
28.3
0.4
24.3
0.46
28.0
6.7
22.7
32.9
0.5
29.3
0.26
32.6
1.5
33.5
38.9
0.2
35.4
0.74
38.5
8.5
32.9
53.9
0.4
47.7
0.48
53.6
7.1
55.4
29.2
0.8
24.5
0.35
28.8
8.8
34.7
14.6
0.9
11.9
0.50
14.2
4.2
17.5
7.9
0.17
16.1
14.5
0.26
23.1
24.8
0.05
33.7
34.9
0.21
44.8
13.4
0.14
18.8
18.1
0.11
28.6
15.8
0.51
23.3
38.2
0.03
56.4
23.2
0.30
33.7
11.9
0.50
17.6
Source: Data compiled by the authors.
a. Trade bias index is TBI (1 NRAagx兾100)兾(1 NRAagm兾100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and exportable
parts of the agricultural sector.
b. The RRA is defined as 100*[(100 NRAagt )兾(100 NRAnonagt ) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural and
nonagricultural sectors respectively.
299
300
Distortions to Agricultural Incentives in Africa
Figure 10.5. NRAs for All Agricultural and Nonagricultural
Tradables and the RRA, Sudan, 1955–2004
80
60
40
percent
20
0
20
40
60
80
19
55
19
58
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
100
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the authors.
Note: For a definition of the RRA, see table 10.2, note b.
The Evolution of Policy Choices
The analysis of the NRAs and RRAs reveals a legacy of highly discriminatory distortions to Sudanese agricultural production and trade, but no consistent longterm policy trend up to 1993. The variability in the NRAs was influenced by ad hoc
agricultural policies, with the movement toward freer markets (less antiagricultural bias and, within agriculture, less of an antitrade bias) often being short-lived.
The increasing antiagricultural bias (increasingly negative RRAs) from the late
1950s up to the early 1970s was associated with ambitious but unsuccessfully
implemented development plans that focused on an import substitution agenda.
The notable improvement from the mid-1970s to the late 1980s is attributable to
the attention and support to agriculture from the socialist regime, when government control of the economy sought to boost food production. Nevertheless,
these policies were more favorable to import-competing farm products than to
exportables, discriminating in particular against cash crops. Distortions were
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301
affected by exchange rate volatility and fluctuating policies toward public marketing parastatals, engendering low and unstable producer prices. The trend toward
less discrimination against agriculture, noticeable since 1993, was mostly governed by progressive implementation of macroeconomic reforms. Throughout
the whole 50-year period, few covered products had NRAs close to zero; the main
exception was cotton.
Import-competing products
The pattern of the NRA for wheat was influenced by slow responses of the government to changes in international prices, and by import-substitution policies
especially from the mid-1970s through the 1980s (UNDP 2005). Among importcompeting crops, there were periods of high NRAs in the late 1970s, the 1980s,
and again in the late 1990s through 2004. These high rates of assistance were influenced by the exchange rate regime and price controls on some goods, while others
experienced high inflation (UNDP 2005).
The data shown in table 10.1 refer to primary agricultural production but are
influenced by policies to encourage domestic wheat flour milling and other processing activities. For example, milling and importing of sugar are undertaken by
a government monopoly that accounts for a substantial share in government
budget revenue. The discrepancy in price levels between factory and consumer
prices includes an implicit tax on production and consumption.
Milk is exclusively consumed in the domestic market and its prices respond
sluggishly to changes in the international market. Other variations in the NRA for
milk, including the peaks during the second half of the 1970s and the second half
of the 1980s, can be traced to natural conditions that influence milk production
and trigger high domestic prices. Another factor that affects the estimated levels of
distortions is the nature of price comparisons between fresh and dry milk on the
one hand, and local and imported cheese on the other hand. Although these were
substitutes, the calculation of their relative prices might be subject to errors.
Exportable cereals
Trade in sorghum was once subject to a strict discipline on the ground that the
crop is the major staple food in the country. Control of sorghum trade is now
relaxed, but the government still limits sorghum exports from time to time. The
situation is intermingled with food aid, which often includes sorghum.
Millet is not a very important export commodity, and its local consumption is
concentrated in certain areas, mainly western Sudan; as a result, government
intervention seems to be quite limited. The trend in the rate of assistance is
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Distortions to Agricultural Incentives in Africa
upward, although one needs to keep in mind that domestic prices during 1955–65
and export prices in the 1990–2004 period were based on extrapolated estimates.
The high rates of assistance around 1990 were again a result of exchange rate
movements interacting with lags in local market adjustments. By and large, the
pattern of assistance appears to be influenced by exchange rate movements and
domestic market constraints, especially transport-related infrastructure.
In general, and despite the differences in the rates of assistance between the two
cereals, their overall patterns have been similar. While some substitutability in
consumption exists between the two products, it seems that they are influenced
also by similar policy measures.
Exportable oilseeds and oils
For oilseeds (sesame and groundnut), distortions became more negative until
about 1980 as a result of exchange rate distortions. But trade in oilseeds was highly
affected during this period by the nationalization of oilseed exports in 1970 and
the transfer of trading functions to the parastatal Sudan Oilseeds Company (FAO
2004). Their monopoly was later abolished in 1980, reintroduced in 1986, and
finally removed in 1991, but the company continued to compete with the private
sector during periods of demonopolization. When the monopoly was in operation, minimum producer prices were set to encourage production, but financial
resources often ran short, and the company could not always meet the payments
needed to maintain those prices.
Exportable cotton
Rates of assistance to cotton, although variable, reflect a reasonable alignment of
domestic and export prices. The pattern of the NRAs for cotton is dictated by the
setting of producer prices by the government. The periods of negative NRAs were
influenced by a change in the cotton export-market policy from the fixed-price
system to a system of tenders (Bank of Sudan 1975). A drastic reduction in the
area planted to cotton in the first half of the 1990s may have been driven by the
declining NRA at that time, but it also coincided with the government’s objective
of increasing food crops in the irrigated sector to boost food security. The increase
in assistance since the early 1990s is associated with the liberalization policy under
which the official exchange market and foreign exchange retention policies were
abandoned (Bank of Sudan 1992).
Exportable gum arabic
Gum arabic is clearly and consistently taxed. A private monopoly controlled trade
in the commodity until 1969, when the government took over. Floor prices are
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303
announced and are usually far below export border prices. Until the later 1990s,
the commodity was subject to relatively high direct export taxes as well. For both
reasons the estimated NRA is highly negative. A recent report on the Gum Arabic
Company (Khalid 2006) indicates that inland en-route fees and charges reached
40 percent in recent years. If trader costs are increased to this level, the farm NRA
will still be negative, but with an overall average of about 42 percent instead of
about 53 percent for the whole period. That difference is attributable to market
failure more than to government policy distortions. This situation is unfortunate
for farmers but less so for the nation as a whole, given that Sudan is the world’s
main gum arabic producer and so has some influence on the international price.
Exportable livestock
The level of producer assistance to livestock production reflects government intervention through export licensing. The implied level of taxation was reduced from
1992, when export earnings became a more important government objective.
Other state intervention in prices and marketing activities has been quite limited
(Hussein 2004).
Modalities for the promotion of livestock marketing and exports include the
establishment of a parastatal Livestock and Meat Marketing Corporation in the
mid-1970s that provided various marketing services. It was dissolved in 1992, and
most of its functions were transferred to the Animal Resources Services Company.
Estimated NRAs also capture market failure relating to monopolistic competition
among traders. The NRAs also are responsive to exchange rate regulations: up to
the early 1980s when exchange rate distortions were low, so were the negative levels of the assistance rate, but during the 1980s and the beginning of the 1990s,
exchange rate distortions reflected more negatively on producers. The rate of
assistance during 2002 and 2004 might have been affected by a monopoly situation of livestock exports granted to the Gulf Livestock Company owned by a Saudi
prince through an exclusive export agency agreement, under which export prices
were fixed. The agreement faced local resistance and was dissolved in 2004
(Hussein 2004).
Prospects for National Policy Reform
For many years the Sudanese government has targeted the development of the
agricultural sector, with limited success. While many investments were undertaken, it is evident that malfunctioning markets have limited agricultural performance. This is partly attributable to government intervention in markets
through the fixing or influencing of prices, control over production and product
delivery and disposal, and excessive internal taxation of products. There are also
304
Distortions to Agricultural Incentives in Africa
indications of monopolistic behavior, which is partly government induced. However, many exchange rate controls that had long been in place have recently been
removed. It remains for the other distortions to agricultural incentives to be
reduced. Some potential policy actions to help achieve that are canvassed in this
final section.
One potential action is to continue the ongoing foreign exchange rate policy
reform with the aim of allowing the real exchange rate to reach its natural equilibrium. This will not be easy while trade measures that restrict exports are still in
place. More generally, the risk of appreciation in the exchange rate (such as in
2006 when it appreciated by about 20 percent) will always raise concerns among
exporters about the sustainability of their competitiveness when selling on world
markets.
A second useful action would be to deregulate state and state-induced market
monopolies, especially in gum arabic and cotton, to open up more export opportunities for the private sector. The government is now moving in this direction:
the gum arabic monopoly is in the process of being abolished, and the private sector can now engage in cotton exports from irrigated areas in addition to the previously permitted private exports of rainfed cotton. Wide involvement of the private
sector in trade is, however, limited by the availability of finance and trade information, both of which need relevant policy action. Another requirement is quality
assurance of some export products for which Sudan has a big share in the international market, especially gum arabic, sesame and, to some extent, sheep. Regulations setting quality standards as well as a strong institutional arm for implementation will be conducive to competitive export promotion. These are being
prepared within the context of Sudan’s accession to the World Trade Organization
(WTO).
Third, domestic monopoly-like practices should be removed via policy interventions to promote finance from public and private sources, and training should
be encouraged to empower newcomers in commerce.
Fourth, the recent trade reform process should be encouraged to continue. It
has involved the removal of export taxes, as well as a review of the import tariff
structure in the context of negotiating Sudan’s accession to the WTO. Such
reforms should be aimed at raising efficiency by lowering the average tariff and its
variance across industries, but with reasonable implementation periods to allow
improvements in productivity to be reached.6
And fifth, given the high dominance of primary products in Sudan’s export
portfolio, investments in infrastructure and agricultural research, and the efficient
provision of complementary services, are essential if enough quantities and quality of raw materials are to be forthcoming to stimulate an expansion in processing
activities.
Sudan
305
Of great importance to all of these policy recommendations is the adoption of a
stable strategy of policy reforms that is nevertheless flexible enough to respond to
internal and external changes. Such stability is needed in view of the past frequent
policy shifts that have not only depressed agricultural incentives but also added to
the natural uncertainty that is inevitably associated with agricultural production.
Notes
1. Studies of macroeconomic policy issues affecting Sudanese agriculture include Hag Elamin and
El Mak (1997), Abdelgadir and Elbadawi (2002), and Amal (2006). Analyses of the comparative advantage of some farm products and related policy issues include Hassan and Faki (1993); Hassan, Faki,
and Byerlee (2000); and Faki, Gumaa, and Ismail (1995).
2. Sudan’s initial offer during its World Trade Organization accession negotiations on agricultural
tariffs averaged 45 percent.
3. Before 1981, the cotton accounts system entailed placing cotton proceeds in a joint account
from which cotton production costs were deducted and the balance divided between the three partners: the government, the scheme administration, and the farmers. Because it was believed that such a
system did not provide adequate incentives for farmers to produce, an individual account system was
set up, whereby individual accounts were provided for each farmer to accommodate his/her costs and
revenue (Suliman 2002).
4. It might be argued that such subsidies were a result of the overvalued exchange rate, the progressive amendments of which have led to the rise in their prices. There were no explicit subsidies on inputs.
5. An analytical overview of the main macroeconomic indicators in the period 1960–98 is given by
Abdelgadir and Elbadawi (2002). Despite a relatively favorable policy situation in the period 1960–73,
growth was negative, while positive growth with a fairly high average per capita growth rate was
recorded for the following period, even though that period’s associated policy indicators were deteriorating. According to the authors, one possible explanation was that, except for the overvaluation index,
the other two policy indicators were on the safe margins: the two-digit inflation rate was low compared
to the threshold 40 percent inflation rate considered detrimental to growth, and the budget deficit was
slightly above the 5 percent threshold. Further deterioration of the policy indicators, except for the
budget deficit, was associated with negative growth during the period 1984–94. This was the period
when the country was very unstable both in terms of politics and economics. The noticeable improvement in the policy indicators since 1994 was also reflected by positive growth in real per capita GDP.
6. The current structure of Sudan’s tariff on agriculture can be found in the applied tariff and the
bound tariff offer prepared by Sudan’s Commission for WTO affairs in connection with Sudan’s WTO
accession process. The 2006 average applied agricultural tariff is 31 percent, with all tariff lines in the
0–45 percent tariff range. A modified bound tariff offer averages 44.9 percent in which 64 percent are
within the 0–40 percent tariff range and 93 percent of the tariff lines in the 0–60 percent tariff range.
This would provide more opportunities for protecting domestic producers if prices were to fall
internationally.
References
Abdalla A. A., A. Dingle, A. Ijaimi, E. A. Hassan, and A. O. El Gasim. Undated. “Food Security and
Agricultural Development in the Sudan: Poverty Reduction and Programs in Agriculture.” Study
prepared for the FAO as a contribution to the Interim Poverty Reduction Strategy Paper (2004–06)
for Sudan, Khartoum.
Abdelgadir, A., and I. A. Elbadawi. 2002. “Explaining Sudan’s Economic Growth Performance.” Paper
for AERC (African Economic Research Consortium) Collaborative Research Project on Explaining
Africa’s Growth Performance. Arab Planning Institute, Kuwait.
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Distortions to Agricultural Incentives in Africa
Amal, M. M. 2006. “Response of the Irrigated Gezira Scheme to Macroeconomic and Structural
Reform Policies in Sudan.” PhD thesis, University of Khartoum, Khartoum.
Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675-704.
Bank of Sudan. 1975. Annual Report 1974. Khartoum: Bank of Sudan Publications.
———. 1982. Annual Report 1981. London: Burrup Mathieson & Co. Ltd.
———. 1992. Annual Report 1991. Khartoum: Bank of Sudan Publications.
D’Silva, B., and I. A. Elbadawi. 1988. “Indirect and Direct Taxation of Agriculture in Sudan: The Role of
the Government in Agriculture Surplus Extraction.” Core Historical Literature of Agriculture.
http://chla.library.cornell.edu.
Faki, H., Y. T. Gumaa, and M. A. Ismail. 1995. “Potential of the Sudan’s Irrigated Sector in Cereal Grains
Production: Analysis of Various Policy Options.” Agricultural Systems 48: 457–83.
Faki, H., and A. Taha. 2007. “Distortions to Agricultural Incentives in Sudan.” Agricultural Distortions
Working Paper 44. World Bank, Washington, DC.
FAO (Food and Agriculture Organization). 1997. “National Program for the Development of Agriculture, Livestock and Irrigation Sectors in the Republic of Sudan; A Mission Report (Part II).” Policy
Assistance Branch, Regional Office for the Near East, FAO, Cairo.
———. 2004. Strengthening National Capacity in Agricultural Trade Negotiations of the Sudan: An
Analysis of Sudan’s Export Potential of Oil Crops. Rome: FAO.
Hag Elamin, N. A., and E. M. El Mak. 1997. “Adjustment Programs and Agricultural Incentives in
Sudan: A Comparative Study.” AERC Research Paper 63. African Economic Research Consortium,
Nairobi.
Hassan, R., and H. Faki. 1993. “Economic Policy and Technology Determinants of the Comparative
Advantage of Wheat Production in Sudan.” CIMMYT Economics Paper 6. International Maize and
Wheat Improvement Center, Bangkok.
Hassan, R., H. Faki, and D. Byerlee. 2000. “The Trade-Off between Economic Efficiency and Food
Self-Sufficiency in Using Sudan’s Irrigated Land Resources.” Food Policy 25: 35–54.
Hussein, Abubakr Ibrahim. 2004. “Sudanese Livestock Marketing and Competitiveness.” TCP 2409
(A), FAO, Rome, and Ministry of Agriculture and Forestry, WTO Accession Unit, Khartoum.
Khalid, M. 2006. “Crisis of Gum Arabic and its Company: Rescue and Reform.” A report by the Chair
of the Board of Directors, Gum Arabic Company, Khartoum.
Ministry of Finance and National Planning. 2006a. The Sudanese Economy in Figures 2000–2005. 1st
and 2nd Editions, Macroeconomic Policies and Programs Directorate (MEPP) of MFNP, Sudan.
———. 2006b. “Addressing Issues of Declining Productivity in the Agricultural and Industrial
Sectors” (Arabic). Ministerial Committee Report, Ministry of Planning and National Economy,
Khartoum, Sudan.
Sheikh Musa, A .O. 2001. Procedure for Economic Reform in the Sudan. Sudan: Currency Printing Press.
Suliman, S. A. 2002. The Gezira Scheme, The Living Legend: A Preliminary Study (in Arabic). Sudan:
Currency Printing Press Ltd.
Tothill, D. J., ed. 1948. Agriculture in the Sudan. London: Oxford University Press.
UNDP (United Nations Development Programme). 2005. Macroeconomic Policies for Poverty Reduction: The Case of Sudan. New York: UNDP.
11
Tanzania
Oliver Morrissey
and Vincent Leyaro*
Following independence in 1961 (as Tanganyika, which united with Zanzibar to
form Tanzania in 1964), Tanzania experienced a relatively brief period when the
share of agriculture in gross domestic product (GDP) declined as resources were
shifted into other sectors with potentially higher value added. Between the early
1960s and the early 1970s, agriculture’s share of GDP fell from about 60 percent to
just below 40 percent. It then grew slowly to just over 40 percent of GDP by the
late 1970s and rose steadily back up to about 60 percent of GDP by the late 1980s
and early 1990s before once again dropping back to around 45 percent (World
Bank 1994). In this sense, Tanzania has yet to achieve or complete the traditional
“structural transformation.” Balanced growth is said to have been achieved if agriculture becomes increasingly commercialized while the manufacturing sector
grows. Initially manufacturing may be based on agriculture, through processing
and agribusiness, but ultimately manufacturing and the economy will become
diversified (Thirlwall 1986). This diversification has not happened in Tanzania,
and the economy remains essentially based on agriculture.
Given the major importance of agriculture to the country, this chapter provides
an analysis of the combined effect of various government policies (in particular
taxes and exchange rates) and features of the agricultural sector (notably inefficiencies in the input supply and product marketing chains) on incentives to production
in agriculture. The next two sections provide an overview of agricultural performance and relevant policies since independence. Then the methodology applied to
* The authors are grateful for helpful comments from Kym Anderson, Henry Gordon, and, specifically
on cotton, Colin Poulton, as well as from workshop participants. Detailed data and estimates of
distortions reported in this chapter can be found in Morrissey and Leyaro (2007).
307
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Distortions to Agricultural Incentives in Africa
measure distortions faced by agricultural producers and consumers is described,
after which the results are discussed.
The analysis reveals that while some reforms have significantly reduced distortions for some crops, many others still face high distortions, including, most worryingly, the two major food crops, maize and rice, which together account for
more than 40 percent of agricultural output. Although exchange rate liberalization and privatization of marketing has removed many distortions, marketing
inefficiencies and limited competition persist for many products, so the level of
distortion against agriculture remains reasonably high for all tradables on most of
the measures used. For exportables overall, part of the remaining high distortion
is attributable to high distribution and marketing costs, stemming, for example,
from inefficient marketing structures and high transport costs faced by exporters.
For food crops (import-competing products), persistent distortions are attributable to inefficiencies in the domestic marketing chain or monopoly power in processing and purchasing, or both. Although reductions in distortions to many
crops have to some extent been offset by persistent high distortions facing others,
especially certain exports, the overall bias against agriculture has been reduced.
Brief conclusions are offered in the final section. Reforms—especially liberalization of the exchange rate regime and reductions in trade taxes—have been
moving in the right direction, but much remains to be done to improve the efficiency of marketing (including transport) and thus eliminate the net distortions
against agriculture. The core problem is that effective real producer prices remain
low, especially given high costs of inputs and inefficiencies in marketing. For coffee, government policy distortions have been largely eliminated, so the major traditional export crop now faces a neutral policy regime, but domestic prices appear
insufficient for profitable trading margins, given the decline in the world price
(and there is evidence of declining production).
Growth and Structural Changes
Tanzania experienced fairly steady economic growth from the mid-1960s to the
mid-1970s, with real GDP increasing by almost 4 percent, although real agricultural GDP grew at only just over 2 percent. Performance weakened in the latter half
of the 1970s, partly in response to external shocks and partly to increasing state
intervention in the economy, including widespread nationalization. Between 1976
and 1980, real GDP rose by just over 2 percent, but real agricultural GDP grew by
less than 1 percent. The combination of the 1979 oil price shock and the war with
Uganda precipitated an economic crisis, with negative real growth over 1981–83
(although agriculture grew by over 2 percent). Recovery began in 1986 with the
implementation of a World Bank–sponsored economic recovery program that
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steadily introduced liberalization policies. Over the period 1986–92, both real GDP
and agricultural GDP grew by more than 4 percent (World Bank 1994).
Agriculture has remained the dominant production part of the economy, and
its share of GDP has actually increased. Agriculture accounted for about 40 percent of GDP in the 1970s and early 1980s, rising to 48 percent in the early 1980s
(when the services share fell), before falling back to 45 percent in the early 2000s.
The services sector has varied around 45 percent of GDP, whereas manufacturing
has declined steadily from 12 percent in the 1970s to just over 7 percent in the
early 2000s. The mining share has been less than 2 percent. Within agriculture, the
best performance was in food crops, notably pulses, starches, oilseeds, and nontraditional exports (fruit and vegetables) throughout 1976–91, but with good
growth in cereals during 1976–85. Traditional export crops performed poorly,
with negative growth through 1976–85 and modest growth over 1986–91, reflecting the effect of unfavorable terms of trade on Tanzania: real export prices for coffee, cotton, and tea in 1990 were less than half their value in 1984.
The econometric results in McKay, Morrissey, and Vaillant (1999), based on
data up to the early 1990s, suggest that the agricultural sector is quite responsive
to relative prices and so can be expected to expand in response to market liberalization. Short-term responses can be expected to be greater for annual crops than
for perennials. This kind of supply response has indeed been observed following
adjustment policies in Tanzania in the mid-1980s. Liberalization of agricultural
markets increased prices paid to farmers and was associated with improved
performance following the reforms of the 1980s. Complementary interventions
to improve infrastructure, marketing, access to inputs and credit, and improved
production technology can be expected to make producers even more
responsive.
The role of public investment is especially important if the objective is to
expand total agricultural output. Evidence from Tanzania is consistent with the
view that much supply response comes from substitution between crops. Total
production will respond if incentives are improved, but response is greater if
structural constraints are also relaxed. Production data support this argument:
although there was a dip in the early 1990s, production of import-competing food
crops has grown dramatically in volume terms since the 1970s; production of staple nontradable foods has also grown, but the volume of export crop production
declined in the 1980s and recovered only in the late 1990s and 2000s. Considering
production shares in total agriculture, however, it is the nontraditional crops that
have increased, especially vegetables such as green beans and fruits. Cash crops
(for export) have declined as a share of production since 1985, and importcompeting products such as maize and rice (and nontraded staples) have maintained their production shares.
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The growth of food crop production from the mid-1980s probably contributed
to poverty reduction. In 1990, about 85 percent of the Tanzanian population was
defined as rural, and agriculture was the primary source of income for the vast
majority of these rural people. Almost 60 percent were below the poverty line,
some 77 percent of total expenditure was on food, and over 40 percent of total
food consumption came from home production (World Bank 1994). Growth in
agriculture, especially food production, makes a major contribution to the
income and welfare of rural households and hence is central to any poverty reduction strategy.
The growth of agriculture following the economic recovery program was not
sustained beyond the early 1990s. In particular, the removal of all subsidies for
agriculture in 1994 heralded stagnation if not decline in production, especially as
the large increase in fertilizer prices discouraged its use and reduced yields. Production levels of the major crops, maize and paddy, are also very susceptible to
fluctuating levels of rainfall and especially drought, which can reduce paddy production by up to half (Isinika, Ashimogo, and Mlangwa 2005).
Skarstein (2005) argues that the reforms led to failure in food crop production
during the 1990s, with declines in labor productivity and in maize and wheat
yields. The combination of successive devaluations, the removal of the fertilizer
subsidy, and privatization of input markets led to a dramatic increase in input
prices. Price deregulation in July 1990 was initially associated with significant real
producer price increases in the early 1990s (more than doubling for maize, rice,
wheat, and millet), but then it induced a decline in real producer prices of maize,
rice, and beans (all to less than half their levels of the early 1990s and below the
levels of the early 1980s by 1999), wheat (relative to the early 1990s but not the
1980s), and millet in the late 1990s (Skarstein 2005). Although maize and rice production did increase during the 1990s, low real prices and limited marketing
opportunities meant that much of the additional production was absorbed as
household own-consumption.
Tanzania’s strong economic performance over 2000–04, with average annual
real GDP growth of almost 6 percent, has been helped by farmers, in particular
through an increase in the area under cultivation. Although agriculture had lower
growth rates than industry or services, it made a larger contribution to GDP
growth than either of the other two sectors (World Bank 2006). There appears to
have been a slight reduction in poverty in Tanzania, from an overall headcount of
almost 39 percent in 1991 to just over 35 percent in 2000. Although the major
reduction was in Dar-es-Salaam (from 28 percent to 18 percent), rural poverty
declined slightly, from 41 percent to 39 percent (World Bank 2006). However, sustained growth requires improved manufacturing performance, and to date, Tanzania has not achieved any manufacturing growth.
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The structure of exports changed notably in the early 2000s, with a decline in
the share of traditional cash crops and an increase in other exports especially
from the mining sector. The structure of traditional exports has also changed as
coffee and cotton declined, largely because of falling world prices, and there has
been a renewal of the cashew nut industry. With the exception of tea, most cash
crops experienced a significant fall in export volume over 1994–2003, with a
notable dip after 1998 resulting from a decline in international prices, especially
for cotton (Kweka 2006). By 2000, the real prices for all major export crops had
declined significantly, including the prices of cotton, coffee, and tea, which had
declined by some 50 percent since 1994. Although traditional cash crop production has not been a source of increasing (or even stable) farm incomes, there has
been a substantial shift toward other products. By 2003, nontraditional exports
accounted for almost 80 percent of total exports, of which half was from the
mining sector.
A Brief History of Agricultural Policy
After independence, the institutional structure of agriculture was characterized by
cooperatives. This mode was not particularly successful, and parastatals dominated marketing starting in the mid-1970s. But these parastatals were not efficient
or successful either, and the liberalization policies in agriculture from the mid1980s have seen a shift back toward cooperatives, with a viable private sector
emerging starting in the 1990s.
1960–75: The cooperative system
Following independence, small-holder agriculture was market oriented and supported by an organized system of state-supported cooperatives. The National
Agricultural Products Board, established in 1962, held a monopoly over the marketing of grain, purchased from cooperative unions which in turn sourced from
the primary cooperatives. The board became the National Milling Corporation
(NMC) in 1973, which had the additional responsibility of maintaining the strategic grain reserve (Isinika, Ashimogo, and Mlangwa 2005). Cooperatives were
owned and controlled by members on a democratic basis, sales were restricted to
the official market, and the marketing board’s purchasing price was fixed. The
actual producer price was the board’s price minus unit marketing costs. Consequently, producer prices varied across the country according to variations in
agreed unit costs (an important source of variation was transport costs). Corruption and weak administrative capacity in the cooperative societies and unions
were major problems, but the marketing board did help to involve farmers and
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limit marketing costs. The system was relatively successful, and through the 1960s
Tanzania was self-sufficient in food.
The Arusha Declaration in 1967 heralded the government’s “villagization” policy (ujamaa), which moved rural populations into new villages with a more
socialist-oriented mode of production. The area under cultivation and extension
services expanded, and use of chemical fertilizer increased to expand food production. The policy was not successful, and in the early 1970s, a combination of
drought and increased prices of imported inputs led to a decline in production
(Isinika, Ashimogo, and Mlangwa 2005).
1976–80: The parastatal marketing system
In 1976, the cooperative system based on the membership of individual farmers
was abolished and replaced by parastatal crop authorities. Ten parastatal crop
authorities were established to cover 27 main and about 15 minor crops. This system was highly centralized, with parastatals responsible for production, research
and development, project financing, procurement, processing, and marketing of
crops. Each parastatal had a countrywide procurement capability and operated
with government-fixed uniform buying and selling prices. A major problem was
the lack of effective controls on marketing costs, the burden of which fell primarily on producers of export crops. For food crops, government sought to contain
marketing costs in order to maintain relatively low food prices for consumers, and
the sector also benefited from input subsidies. For both export and food crops,
however, the policy of panterritorial pricing discriminated against producers
located close to markets while providing price incentives for remote areas, and
thereby expanded total spending on transport and marketing.
Distortions associated with the parastatal system were extensive and costly.
Their inefficiencies effectively bankrupted the parastatal organizations, which
began to fail in basic functions such as crop collection and payments to farmers.
By 1980, the problems had become so alarming that the government decided to
reestablish the cooperative movement. This was achieved through the 1982 Cooperative Act, but the new marketing system was hastily formed. For example, every
“primary society” was based on only one village, even if that village was too small
or too isolated to provide marketing services cost-effectively or was too large for
management to be held accountable to its members. In addition, the parastatal
companies were converted into marketing boards, limiting their responsibility to
processing and final sale but maintaining the marketing chain in the hands of
government officials.
Although the parastatal and cooperative marketing system maintained the previously high level of state intervention, significant changes occurred in the 1980s.
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For example, export taxes were almost completely eliminated by 1985. In addition, the system allowed for regional price differences thorough a dual price
regime, offering premium prices for regions with high marketed output. This did
not take into account differences in transport costs, however, and therefore
subsidized regions with high production and high transport costs (such as the
Southern Highlands) while taxing regions with low production and low transport
cost (such as the Coast). The prices used also had the effect of paying premium
prices for less-preferred foods, such as sorghum and cassava from drought-prone
areas. These foods were then accumulated in the NMC reserve, leading to heavy
financial losses (Isinika, Ashimogo, and Mlangwa 2005).
Price controls imposed high implicit taxation on most producers, encouraging
them to switch from cash crops to foods that could be sold at higher prices on parallel markets. The overvalued exchange rate added to these distortions because it
“taxed exports and subsidized imports to the extent that it sometimes became
cheaper for the NMC to import maize than buy locally” (Isinika, Ashimogo, and
Mlangwa 2005, p. 202).
1985–2000: Market transition
The limitations of previous policies led the government to implement reforms
towards a more market-oriented, liberalized agricultural sector. In 1984, the government started to decontrol prices, initially for food crops, and to reduce the role
of the NMC. By 1990, the marketing of food was largely run by the private sector.
Between 1985 and 1992, for example, the share of maize marketed by the private
sector in Dar-es-Salaam rose from about 50 percent to 80–90 percent (Isinika,
Ashimogo, and Mlangwa 2005, p. 205).
With the growth of private trade in parallel markets, official prices became
minimum floor prices. Retail prices were determined by market forces, and actual
farmgate prices were those prices minus the farm-to-market marketing and transport costs. Thus, producer prices in the regions with the highest transport costs
were closest to the official (minimum) prices (and most likely to become the
major sources for government procurement), whereas market prices in other
regions were much higher than the official premium price.
As liberalization continued throughout the 1990s, the private sector became
more efficient in food marketing. Marketing costs and margins were reduced, private sector trade became more competitive, and grain markets became more spatially integrated, with narrower margins and more effective price transmission.
Nevertheless, limited access to information about market opportunities remained
a problem for small farmers, and increases in input prices reduced farm profits
and discouraged production (Isinika, Ashimogo, and Mlangwa 2005). Concerns
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about input costs motivated the government to reintroduce fertilizer subsidies
from 2003, albeit on a limited basis. In any case, fertilizer use was not widespread,
with no more than 15 percent of farmers using it in the late 1980s; its use was concentrated on maize in the Southern Highlands, coffee in Kilimanjaro, and tobacco
in Tabora (Cooksey 2003). During the period of no fertilizer subsidies in the
1990s, maize yields remained stable and production increased in all except
drought years.
Liberalization also had significant effects on export crops, especially the two
most important: cotton and coffee. In 1994, the monopoly of the Cotton Board was
eliminated, cooperatives were allowed to engage in marketing and ginning, and
private companies entered the market. By the 1996/97 season, private firms were
purchasing about half of production, offering higher prices than the cooperatives.
As a result, marketing improved and ginning capacity increased. The producer’s
share of the cotton export price was about 40 percent during 1989–94 and rose to
about 50 percent in 1995–2000 (Baffes 2004). In the late 1990s, taxes on cotton
were high, at 13–14 percent of the producer price, but often these were not paid in
full (Baffes 2004). And although cotton is very responsive to prices in general, there
is no evidence of significant supply response in Tanzania, perhaps because of constraints on the availability of credit and input use, as well as variation in quality.
There are some similarities between cotton and cashew nuts, a crop that was also
liberalized in the 1990s: although marketing efficiency increased and production
grew steadily, limited access to credit to finance purchases of inputs, especially sulfur, was a major constraint, particularly for poorer cashew growers (Poulton 1998).
For coffee, although almost all of Tanzania’s production is from small-holders,
the Tanzania Coffee Board had a monopoly over marketing, processing, and
exporting until the mid-1990s. After 1995, private agents were allowed to enter
marketing and processing, although exports were still required to go through the
coffee board’s auction. According to Temu, Winter-Nelson, and Garcia (2001), by
1997 five fully vertically integrated exporters, all subsidiaries of multinational coffee companies, were engaged in domestic trade in Tanzania. They processing factories and accounted for 45 percent of deliveries to the export auction. Other private buyers accounted for 22 percent of deliveries to auction, and from a zero
share before 1994, private agents accounted for almost 70 percent of marketed
coffee by fiscal 1997. During this period, marketing margins were reduced dramatically, and the producer price as a share of the export price rose from 50 percent to over 90 percent (Temu, Winter-Nelson, and Garcia 2001). Although there
was concern that the five vertically integrated exporters could gain a detrimental
dominant position in the market, that had not happened by the late 1990s.
In the early 2000s, some of the gains from liberalization in coffee and other
crops were being reversed, in part because the declining world coffee price was
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squeezing the margins of traders, and cooperatives were gaining political support
in a rearguard action to preserve their position relative to private traders (Cooksey
2003). In 2001, laws were presented to reestablish the Tanzania Coffee Board and
Tanzania Tobacco Board, under which producers needed the permission of the
boards to grow the crops. Similar measures were proposed for sugar (Cooksey
2003). The 2001 Cotton Industry Act increased the intervention powers of the
Cotton Board (Baffes 2004). In sum, while liberalization appeared to have had
limited successes for food crops (but see Skarstein 2005), the evidence for traditional exports was mixed, because liberalization policies were either not implemented or not sustained.
Post-2000 policy issues
Recognizing that agriculture accounts for some 50 percent of GDP, 80 percent of
rural employment, and over 50 percent of the foreign exchange earnings, Tanzania’s Development Vision 2025 places considerable emphasis on the sector. An
annual real growth rate of at least 8 percent in agriculture would be needed to
provide the basis for economic growth and poverty reduction. A number of policy
documents have aimed to achieve this growth: the Agricultural Sector Development Strategy and Agricultural Sector Development Program in 2001, and the
Cooperative Development Policy of 2002, complemented by a variety of sector
policies, which are fully reviewed in ESRF (2005). We summarize these efforts in
terms of three core issues:
First, the policy statements of the early 2000s identified the issues and proposed a strategy. The development strategy statement emphasized the need to
improve the efficiency of input markets and product marketing, increase access to
credit, enhance the provision of extension services, and increase investment in
rural areas (especially for irrigation and transport). The development program
was in principle the plan for implementing these aims, but it had limited impact.
Thus, the culmination of these initiatives was the formulation of a widespread
belief in Tanzania in the need to “reintroduce selective subsidies, particularly for
agricultural inputs, machinery and livestock development inputs and services”
(ESRF 2005).
Second, the initiatives of the 2000s recognize that, despite the Cooperative
Development Policy, the cooperative sector failed to respond to the challenge of
liberalization. The sector continued to suffer from weak managerial (and advocacy) skills, a lack of financial resources (in particular undercapitalization of
cooperative banks, so credit constraints remained), and a weak institutional
structure (especially in the cooperatives’ lack of accountability to members).
Thus although the cooperative sector remained significant, it was not viewed as
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successful, either in supporting development and growth or in representing the
interests of members, giving added impetus to reform.
Third, the reform efforts recognize agriculture as integral to the country’s
poverty reduction strategy, and growth in the agricultural sector is essential if
Tanzania is to achieve sustained economic development. While this may seem
somewhat obvious, it marks a change in emphasis—the whole sector (not only
export crops) has attained a higher status on the political agenda, and a wider
range of political actors have expressed the need for positive support to the
sector.
Trade policy reforms
Although elements of trade policy reform were introduced as part of adjustment
programs beginning in the early 1980s, the major reductions and rationalization
of both import duties and domestic sales taxes were announced in 1988 and 1989.
The range and levels of tariffs were reduced, and most specific sales taxes were
converted to ad valorem taxes. The average effective tariff (defined as tariff revenue relative to value of imports) rose from 2.9 percent in 1986 to 4.5 percent in
1988, which was a period of roughly 100 percent currency devaluation. The average effective tariff then fell slightly to 4.4 percent by 1990, a period of tariff rationalization along with another currency devaluation of about 100 percent
(Lyakurwa 1992).
In 1991, the Tax Commission placed a heavy emphasis on further reform of
tariffs and sales taxes, recommending that customs duties be simplified to three
rates. The 1992 budget actually reduced the number of tariff rates to five. Considerable emphasis was placed on the need to limit the scope of exemptions, because
too many importers—in particular government bodies and parastatals—were
exempted from tariffs and sales tax. In 1989, actual import tax revenue represented only 44 percent of the yield that would have resulted had no importers
been exempt (Tax Commission 1991). Licenses for virtually all imports and
exports were abolished in 1993, and by the end of that year, the foreign exchange
market was significantly liberalized. The number of tariff rates and the maximum
tariff were reduced a number of times; by 1997, there were only four rates, the
maximum being 30 percent (with a different and lower schedule of rates applying
to members of regional trade agreements). The average tariff fell from about 28
percent in the early 1990s to 16 percent in the early 2000s.
The reforms appear to have had a beneficial effect. The ratio of imports
to GDP declined by almost 30 percent (from 37 percent to 26 percent), while
the ratio of exports to GDP increased by almost 50 percent (from 14 percent to
18 percent) between the early 1990s and the late 1990s. As of 2005, however,
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further harmonization of the tariff structure was still needed, along with improvements to marketing and input supply for agricultural exports. The National Trade
Policy of 2003 had sought to address export promotion, but that reform agenda is
incomplete and the National Trade Policy was also weak on policies to enhance
agriculture. One of its key features was an emphasis on regional integration and
commitment to multilateral trade agreements. Agricultural exports featured
prominently in the policy, and yet much remains to be done to integrate trade,
agriculture, and poverty reduction strategies.
Measuring Distortions to Agricultural
Incentives
The main focus of the current study’s methodology (see appendix A in this volume and Anderson et al. 2008) is on government-imposed distortions that create
a gap between domestic prices and what they would be under free markets.
Because the characteristics of agricultural development cannot be understood
from a sectoral view alone, the project’s methodology not only estimates the
effects of direct agricultural policy measures (including distortions in the foreign
exchange market) but also generates estimates of distortions in nonagricultural
sectors for comparative evaluation. More specifically, this study computes a nominal rate of assistance (NRA) for farmers. It also generates an NRA for nonagricultural tradables, for comparison with that for agricultural tradables through the
calculation of a relative rate of assistance (RRA).
The quantitative analysis is applied to the most important crops in Tanzania
over the period 1976–2004. Almost 80 percent of agricultural crop production is
covered. The analysis excludes livestock products, however. Livestock, dairy, and
chickens have been important contributors to overall agricultural growth since
the mid-1990s, but we did not have adequate data to include them. The 18 products analyzed are classified as cash crops (coffee, cotton, tea, sisal, tobacco, cashew
nuts, pyrethrum, and beans); import-competing food crops (maize, rice, wheat,
and sugar);1 and nontraded crops (cassava, sorghum, millet, Irish potato, yam,
and plantain).
The basic principle underlying the measures we estimate is that the price
received by producers (farmers or processors), adjusted to allow for taxes (subsidies), margins (marketing and transport), and exchange rate distortions, is then
compared with some reference price (an undistorted or international price
intended to measure the true opportunity cost). In principle, the result is an estimate of the difference between the domestic and competitive world price for a
product at a comparable point in the supply chain, with a nonzero wedge implying distortions. For nontraded goods, there is no reference international price, but
318
Distortions to Agricultural Incentives in Africa
the market could be distorted between domestic producers and consumers. We
lack information on distortions to input markets and have no evidence to assume
any taxes or subsidies to producers of staples (either because there is no tax or the
crops are mostly sold by small traders in local markets where sales taxes are not
collected), so we assume there are no measurable distortions for the six nontraded
staples.
The treatment of exchange rate distortions is similar for all our NRA estimates:
because we have no information on the share of currency traded on the black
market, we assume the undistorted exchange rate is a simple average of the nominal and parallel market exchange rates. We make a number of other general
assumptions. First, we treat cash crops like a semiprocessed traded product, that
is, the primary crop is treated as a nontradable, and the analysis is conducted for
the processed equivalent (for example, price and production data for coffee are for
the clean equivalent that is exported). Second, we assume equiproportionate
transmission throughout the value chain. Third, we assume domestic and foreign
products are of the same quality. Fourth, we use an international reference price
where available, otherwise we use the free-on-board export price.
The measures we estimate do not explicitly account for “excess” international
trading costs. Recent analysis (Kweka 2006) suggests that Tanzanian exporters
face trading costs above those prevailing in competitive markets, specifically
because of inefficiencies in transport and customs (which increase costs, delays,
and wastage). We represent these as an implicit tax, because they cannot be
passed on to foreign buyers. In the case of import-competing products, we treat
the marketable product as the primary product and do not consider the
processed product separately, and we use the cost-insurance-freight import price
for reference.
Results
The NRA results for the various crops are given in table 11.1. A mixed pattern is
evident, reflecting in part the limited quality of the domestic price data available.
In effect, each observation is computed at one point in the marketing chain and
may not reflect the rates of assistance or taxation that would apply at other locations in the country. Despite the inevitable measurement errors, however, plausible trends of clear importance are visible in the NRA results.
Coffee, traditionally one of the more important crops, faced relatively high
negative NRAs from 1976 to the early 1990s. During this period of high state control, producers received about 30 percent of the reference price. After 1995, marketing was liberalized, exchange rate distortions were largely eliminated, and there
were no subsidies. Even so, the industry was under severe stress in recent years,
Table 11.1. NRAs for Covered Farm Products, Tanzania, 1976–2004
(percent)
Product indicator
Exportablesa,b
Beans
Tobacco
Tea
Sisal
Pyrethrum
Cotton
Coffee
Cashew
Import-competing productsa
Wheat
Sugar
Rice
Maize
Nontradablesa
Yam
Sorghum
Millet
Potato
Plantain
Cassava
Total of covered productsa
Dispersion of covered productsb
Percent coverage (at undistorted prices)
1976–79
1980–84
1985–89
1990–94
1995–99
2000–04
77.9
76.7
64.4
90.7
39.1
82.4
83.1
69.3
66.1
53.1
31.5
8.7
50.7
51.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50.3
37.4
83
80.6
76.1
65.9
93.9
40.7
71.4
87.4
74.2
71.6
55.5
54.8
57.7
63.9
51.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
60.3
39.1
93
81.6
81.8
65.2
93.5
29.2
73.5
84.2
77.4
69.1
16.2
47.1
14.7
39.6
2.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
51.9
41.3
87
65.9
44.5
56.5
89.5
13.1
37.0
85.4
44.0
39.0
10.3
44.6
22.9
2.0
13.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
29.8
46.5
81
52.3
47.8
37.0
91.0
0.5
67.8
72.8
0.0
8.1
14.9
76.4
39.6
24.8
28.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
29.1
47.0
79
48.7
45.0
55.2
90.8
0.0
47.7
70.2
0.0
9.6
5.8
95.3
103.1
16.5
1.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
16.6
51.9
74
319
Source: Data compiled by the authors.
a. Weighted averages, with weights based on the unassisted value of production.
b. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
320
Distortions to Agricultural Incentives in Africa
with the share of coffee in export earnings falling from 17 percent in 1999 to
4 percent or lower from 2002 (WTO 2007).
Obtaining reliable local price data was a particular problem for cotton, and we
experimented with alternative estimates (see Morrissey and Leyaro 2007 for a discussion). The results presented here are based on estimating the producer price
(inclusive of all margins) as a ratio of the export price. The NRA was most distorted at 80 percent or more from the mid-1970s to the mid-1990s, but the distortion eased a little, to about 70 percent, starting in the mid-1990s. It seems
likely that the extent of disincentive is overestimated. Poulton and Maro (2007)
note that significant reforms have been implemented for the cotton sector in
Tanzania, especially since 2004, and that the sector now looks quite healthy.
The situation for producers of tea experienced little change over the whole
period, with the NRA remaining at about 90 percent. Information on the industry was difficult to obtain, and there are no reports of reforms being implemented,
which is consistent with the estimated continuous high taxation of the sector. The
estimates could overstate the extent of negative distortions, but it is clear that producers face large disincentives. The tea industry in Tanzania involves strong
monopsony power, with a few companies dominating processing and marketing. It
is surprising, however, that the significant reduction in exchange rate distortions
starting in the mid-1990s did not reduce distortions. The data available to us may
not have captured the true situation for the sector. Or, alternatively, producers may
have in effect been receiving a diminishing share of the export price, with increased
marketing distortions that offset reductions in exchange rate distortions.
Similar conclusions can be drawn for tobacco and pyrethrum. The NRA for
tobacco has remained over 60 percent, while for pyrethrum it appears to have
fallen from over 70 percent to less than 50 percent. There is no evidence that
elimination of the exchange rate distortion has reduced distortions, so one must
assume that inefficiencies remain high as farmers receive a diminishing proportion of the export price. Although the results suggest a subsidy for consumers,
there are few actual consumers of these products in Tanzania, so the results should
be interpreted as implying a potential subsidy for processors and traders (at least
in the sense that producer prices are lower than they should be). As with tea, the
results may be capturing market distortions rather than actual policy distortions,
limiting the ability of government to address the problems.
The results for cashew nuts are consistent with observations that marketing
and processing efficiency in the sector has increased in recent years, reflecting the
increased competition in the sector. This change has helped farmgate prices keep
pace with export prices. An NRA of nearly 70 percent for 1976–89 drew close to
zero for the period 1995–2004. Sisal appears to have been the least negatively distorted product, and by the mid-1990s to be freely traded. Beans are the only
Tanzania
321
example of a nontraditional export covered in our study: the results suggest
relatively unchanged marketing efficiency, so the elimination of exchange rate
distortions is reflected in a reduction in distortions as the NRA declined from
75 percent 45 percent.
For maize, the sustained negative assistance to producers implies a subsidy to
domestic consumers. A combination of trade and exchange rate policies help to
explain this implication. Until the mid-1990s, access to the overvalued exchange
rate lowered the cost of foreign currency and hence the price of imports, and that
lower price was less than offset by the relatively high import tariff (45 percent
until 1994). Marketing inefficiencies also kept producer prices (net of margins)
relatively low, although the trend in distortions decline from 50 percent to close
to zero. This estimate overstates effective rates of assistance to the extent that fertilizer subsidies, accessed by maize farmers during some periods before 1990 and
after 2000 are not incorporated in the analysis because of lack of data. Fertilizer
accounted for 30 percent of production costs on average, and the subsidy averaged
50 percent of the fertilizer costs for those who received it, so production costs of
assisted producers were reduced by 15 percent on average.
The results for rice are somewhat similar to maize, although the timing of
turning points differs. Negative assistance to producers declined from 50 percent to close to zero by the 1990s and became even slightly positive in the early
2000s. Producers were able to avail themselves of fertilizer subsidies after about
2000 (as they were before 1990). As with maize, the combination of trade and
exchange rate policies help to explain the trend.
The results for sugar are harder to interpret, and data limitations are severe (in
particular in distinguishing stages of production). The industry appears to be
highly protected in Tanzania, as sugar typically is in other countries. A larger proportion of the producer subsidy may be retained by the processor at the expense
of the cane farmer than our NRAs suggest, however.
The aggregate NRAs for exportable, import-competing, and all covered farm
products are summarized in figure 11.1. A clear antitrade bias is evident from that
figure, although it was smaller in 2000–04 than it was in the 1980s before the
reforms began.
The aggregate NRA for covered products is repeated at the top of table 11.2.
Also reported there is a guesstimate of the NRA for noncovered products, which
account for 20–25 percent of production. Those goods (largely nontraded fruits,
vegetables, and livestock products) are assumed to face distortions only from the
market for foreign currency.
Aggregate distortions to agriculture appear to have been reduced quite significantly, from worse than 50 percent in the early 1980s to 25 percent in the
1990s and to just 12 percent in the early 2000s.
322
Distortions to Agricultural Incentives in Africa
Figure 11.1. NRAs for Exportable, Import-Competing, and All
Farm Products, Tanzania, 1976–2004
60
percent
30
0
30
60
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
82
19
80
19
19
78
19
19
76
90
year
import-competing products
exportables
total
Source: Data compiled by the authors.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
How does this compare with the NRA for producers of nonagricultural tradables? The RRA estimates comparing agricultural and nonagricultural policies are
shown in the middle rows of table 11.2. The RRA measures the overall bias against
farm production, relative to nonagricultural tradables. The bias has halved since
the latter 1980s, from 70 percent to 35 percent in the early 2000s. The overall
bias against agriculture has been reduced but remains considerable. This change is
also depicted in figure 11.2.
The final set of rows in table 11.2 shows what the distortion indicators would
have been had the distortions to exchange rates not been taken into account. They
suggest that more than one-quarter of the RRA in the 1980s was attributable
solely to exchange rate distortions but that they have since disappeared.
Prospects and Implications
It is important to emphasize that the estimates reported here are based on many
assumptions and limited data that in at least some cases were not really up to the
task. For cash crops, it was difficult if not impossible to distinguish the effect of
Table 11.2. NRAs for Agriculture Relative to Nonagricultural Industries, Tanzania, 1976–2004
(percent)
Indicator
1976–79
1980–84
1985–89
1990–94
1995–99
2000–04
NRA, covered products
NRA, noncovered products
NRA, all agricultural productsa
Trade bias indexb
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAc
Memo item, ignoring exchange
rate distortions:
NRA, all agricultural products
Trade bias indexb
RRAc
50.3
1.2
41.8
0.43
59.6
35.5
70.3
60.3
3.1
56.3
0.55
68.2
69.9
81.3
51.9
2.1
45.3
0.71
55.4
39.8
68.1
29.8
0.3
25.2
0.58
32.3
16.6
41.3
29.1
0.0
23.2
0.29
31.7
11.9
38.9
16.6
0.0
12.4
0.35
20.1
10.3
27.6
33.0
0.02
58.5
39.8
0.42
66.1
29.1
0.35
47.9
20.8
0.45
34.0
22.3
0.24
36.9
12.3
0.35
27.3
Source: Data compiled the authors.
a. NRAs including product-specific input subsidies and non-product-specific (NPS) assistance. NRA is the total of assistance to primary factors and intermediate inputs divided
by total value of primary agriculture production at undistorted prices (percent).
b. Trade bias index is TBI (1 NRAagx/100) / (1 NRAagm/100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and exportable
parts of the agricultural sector.
c. The RRA is defined as 100*[(100 NRAagt )/(100 NRAnonagt ) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural and
nonagricultural sectors, respectively.
323
324
Distortions to Agricultural Incentives in Africa
Figure 11.2. NRAs for All Agricultural and Nonagricultural
Tradables and the RRA, Tanzania, 1976–2004
90
60
percent
30
0
30
60
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
82
19
80
19
78
19
19
19
76
90
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the authors.
Note: For definition of the RRA, see table 11.2, note c.
policy distortions from inefficiencies in marketing and market structures.2 This is
particularly important for estimates since the mid-1990s when policy distortions
relating to the exchange rate and export taxes were eliminated.3 It is quite possible
that for cash crops such as tea, cotton, beans, and tobacco, the negative estimates
reflect market inefficiencies in addition to (and perhaps even more than) policy
distortions. Nonetheless, we believe the relative estimates are reasonably reliable
for later decades, though probably less so for the 1970s. Our results point clearly
to the conclusion that, among the cash crops, products with high NRA estimates
are those with limited competition and inefficient marketing or processing (cotton, tea, and tobacco), whereas NRAs are small for products where competition
has been introduced and efficiency increased (coffee, cashew nuts, and sisal).
The agricultural sector performed reasonably well starting in the mid-1990s,
and especially in the early 2000s. By 2005, the policy emphasis was on ensuring
that the poor shared in growth. For agriculture, this implied a need to focus on
improved functioning of output and input markets (especially credit) and on
Tanzania
325
public spending on agricultural sector development, especially irrigation and
strengthening research and extension (World Bank 2006). Our results, showing
continuing and widespread distortions that are mostly negative, reinforce the
need for this focus.
Overall, the study leads to two specific conclusions and one general implication. First, although liberalization of the exchange rate reduced the black market
premium in the 1990s and removed it by about 2000, exchange rate reforms did
not translate fully into a reduction in distortions to producers in all crops. Benefits in terms of less negative NRA measures can be seen for coffee, cashew nuts,
cotton, and beans among major exports and for food crops, but many export
crops (such as tea and tobacco) appeared unaffected. This finding implies that for
many cash crops, other distortions, stemming from high transport costs, marketing inefficiencies, and the prices paid to farmers, grew worse. Addressing these distortions will require institutional changes.
Second, there is little evidence of improvements in marketing, processing, and
transport efficiency for most products. This conclusion may simply reflect limitations in the data available, but we do find evidence that high transport costs were
still a major distortion for export crops in the 2000s. For food crops such as beans
and maize, where distortions were reduced progressively but remained high, the
lessening of distortion can be fully attributed to exchange rate liberalization. For
crops such as tea and tobacco, where producer distortions did not decline despite
exchange rate liberalization, other distortions must have risen to offset that
change, suggesting that commodity boards were still not functioning in the interest of farmers.
The general implication is that policy reforms in agriculture have some way to
go to eliminate distortions, but certain products may provide examples of what to
do: for example, coffee and cashews for exports, and rice for import-competing
food. Overall, the negative distortions to agriculture have been reduced, but they
still remain high for a number of crops and have not fallen sufficiently relative to
the rest of the economy. Given that agriculture is such a large share of the economy, sector growth is essential to achieving sustained economic growth in Tanzania.
Measures to improve crop yields and production efficiency are important, but the
analysis presented here suggests that measures to improve competitiveness and
efficiency in processing, transport, and distribution remain highly desirable.
Growth in agriculture can contribute significantly to poverty reduction: the
rural poor as producers benefit, and provided productivity and efficiency increase
so that real prices can be reduced, the poor as consumers of food can also benefit.
In this respect, measures relating to regional cross-border trade, typically omitted
from official statistics and often from policy discussions, have a potentially high
payoff. Intraregional trade facilitation and other measures associated with
326
Distortions to Agricultural Incentives in Africa
regional integration could make cross-border trade easier, benefiting those in
border areas. The typical focus of analysis of marketing and transport costs is on
getting products to Dar-es-Salaam, either as the major domestic market or as the
main port for export. While some attention to Dar-es-Salaam is appropriate, it
should not be at the expense of local, and especially border, markets.
Notes
1. There were often exports of maize and sugar, sometimes even net exports, but they are treated
as import-competing products because imports tend to be significant and producers do compete with
imports. In the case of maize, informal cross-border exports, especially to Kenya, are often significant
but are not included in official trade statistics. This observation highlights the fact that our estimates
relate to the aggregate national sector, whereas specific regions and farmers tend to face regional price,
marketing, and trading variations that imply a different level of distortion compared with the national
average. This concern applies to all food crops and, to a lesser extent, cash crops (margins and marketing costs may vary by region but prices should be fairly uniform). Unofficial cross-border trade may be
important for many horticultural products omitted from the analysis, and in some cases for crops that
we define as nontraded.
2. Four “levels” of agricultural market can be identified in Tanzania (Eskola 2005). Local (village)
markets are where farmers sell surplus production, typically of (noncereal) staples; these markets are
seasonal and not integrated into regional markets. Regional markets are typically based in district capitals or urban centers and sell a wide variety of food products. Although some farmers may trade, the
markets are dominated by traders who collect products from producers and other markets (and largerscale traders may supply the national market). The national market is essentially Dar-es-Salaam, the
marketing hub of the country (given the nature of transport systems, regional markets are usually
linked through this city) and the largest urban market. It is dominated by relatively large-scale traders.
Finally, cash crops serve the export market, and most cash crop production is exported (in largely
unprocessed form); these exports are dominated by large-scale, often foreign, traders.
3. Policy distortions have not been entirely eliminated because commodity boards were established for the cash crops (except beans) and sugar after liberalization to replace the monopoly marketing boards. These commodity boards announce minimum prices to be paid to farmers and impose a 2
percent levy on exports. There are also a variety of other taxes or levies (imposed at various points on
the production chain), some of which vary across districts (WTO 2007).
References
Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675–704.
Baffes, J. 2004. “Tanzania’s Cotton Sector: Reforms, Constraints and Challenges.” Development Policy
Review 22 (1): 75–96.
Cooksey, B. 2003. “Marketing Reform? The Rise and Fall of Agricultural Liberalization in Tanzania.”
Development Policy Review 21 (1): 67–92.
Eskola, E. 2005. “Agricultural Marketing and Supply Chain Management in Tanzania: A Case Study.”
Working Paper Series 16. Economic and Social Research Foundation, Dar-es-Salaam.
ESRF (Economic and Social Research Foundation). 2005. Assessment of the Relevancy and Adequacy of
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Isinika, A., G. Ashimogo, and J. Mlangwa. 2005. “From Ujamaa to Structural Adjustment: Agricultural
Intensification in Tanzania.” In The African Food Crisis: Lessons from the Asian Green Revolution, ed.
G. Djurfeldt, H. Holmén, M. Jirström, and R. Larsson, pp. 197–218. Wallingford, UK: CABI
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Kweka, J. 2006. “Trade and Transport Costs in Tanzania.” CREDIT Research Paper 06/10. School of
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CREDIT-CSAE Workshop on Trade and Fiscal Reforms in Sub-Saharan Africa, January 6–8,
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WTO.
12
Uganda
Alan Matthews, Pierre Claquin,
and Jacob Opolot*
Uganda, a society of diverse ethnicity and religion, secured its independence in
1962. Since then, its history has been characterized by long periods of violence
and political instability that culminated in military takeovers in 1971, 1979, 1985,
and 1986. Since 1986, when President Yoweri Museveni’s National Resistance
Movement came to power, most parts of the country have experienced relative
peace. In the north and northeast, however, rebels fought a civil war for over two
decades until a ceasefire was declared in August 2006, although final peace negotiations had not yet been concluded as of mid-2008.
Uganda remains one of the poorest countries in Africa. Its gross domestic
product (GDP) per capita averaged $235 in 2000–04, compared with the SubSaharan Africa average of $585—despite a remarkable growth rate in annual GDP
per capita of 5.9 percent in the period 1980–2004. 1 Uganda’s population increased
from 7.1 million in 1960–64 to about 26.0 million in 2000–04. Annual population
growth averaged 3.4 percent from 1980 to 2004, one of the highest growth rates in
Africa and the world.
High transportation costs limit the landlocked country’s participation in
international trade. Exports of goods and services amounted to 7 percent of
GDP in 1985–89, increasing to 13 percent in 2000–04. The share of imports in
GDP increased from just 14 percent to 32 percent over the same period. The gap
is met through aid inflows, which rose from 5.9 percent of GDP to 13.8 percent
of GDP. In part because of the prolonged disorder and civil strife, agriculture
is the most important sector in the country’s economy and remains more
* The authors are grateful for helpful comments from workshop participants. Detailed data and estimates of distortions reported in this chapter can be found in Matthews, Claquin, and Opolot (2007).
329
330
Distortions to Agricultural Incentives in Africa
important than in comparable countries in Sub-Saharan Africa. The performance of agriculture, and especially coffee, has been the driving force for the
economy as a whole.
Uganda’s early postindependence economic policy followed a rather conventional development strategy, emphasizing private sector participation with mild
import substitution. This model was soon abandoned in favor of public sector
dominance, however, and as elsewhere in Africa, the state-led model of economic development quickly ran into trouble. In Uganda, its demise was accelerated by a particularly chaotic period of economic policy making in the 1970s
following Idi Amin’s seizure of power in 1971. During this period, which devastated the economy, the Asian business community was expelled and business
management was put in the hands of inexperienced Africans on the pretext of
Africanizing the economy. There was a huge expansion of the public sector and
in the number of parastatal enterprises, which quickly became a drain on public
resources.
Amin fell in 1979, and an economic reform program was initiated in 1981
with support from the International Monetary Fund (IMF) and the World
Bank. However, economic policy continued to follow a zigzag course until an
economic recovery program, again supported by the IMF and the World Bank,
was launched in 1987. Since then, Uganda has experienced sustained growth,
with the annual real GDP growth rate averaging 6.2 percent. This growth has
been accompanied by a dramatic drop in the proportion of the population
experiencing income poverty, which fell from 56 percent in 1992 to about
38 percent in 2002.
This study investigates the impact of various policy regimes on the agricultural
sector, which is critically important as a vehicle for income growth and poverty
reduction. Direct and indirect policy-induced distortions are computed based on
a database of agricultural production, prices, policies. and margins for the period
1961–2004. The study finds a clear relationship between agricultural incentives
and the different periods of economic policy. Agriculture was lightly taxed in the
1960s, but the burden of taxation increased significantly during the chaotic years
of the 1970s and 1980s. Since the onset of agricultural liberalization at the beginning of the 1990s, the discrimination against agricultural production has been
greatly reduced. The main challenge now facing the Ugandan government is to
improve the competitiveness of agriculture through a supply-side investment
strategy as the key element in its poverty reduction strategy.
This chapter turns now to a discussion of the growth performance and structural changes in the economy, followed by a review of the evolution of policies
over time. Then distortion indicators are presented, and finally the findings are
summarized and future prospects reviewed.
Uganda
331
Growth and Structural Changes in the Economy
Uganda’s growth performance until 2004 can be divided into four phases: the
prelude to independence and the immediate postindependence era (1961–70); the
period of economic collapse during the Amin era (1971–80); the period of intermittent growth episodes (1981–86); and the period of sustained growth and
recovery (1987–2004).2 A brief discussion of each of these periods is followed by a
survey of structural change and of agriculture’s performance.
Growth performance
At independence, Uganda was well positioned to embark on a successful development path. Agriculture was an important foreign exchange earner through the
export of coffee, cotton, and tea while at the same time providing basic selfsufficiency in food. The manufacturing sector produced inputs for the agricultural sector and consumer goods and was becoming a significant source of foreign
exchange through the export of textiles. The country’s current account balance
was in surplus and domestic savings averaged 13 percent of GDP. A good transportation system was in place, in part facilitated by cooperation in the East
African Community; the system included a road network, railways, and port and
air services.
Immediately after independence, the economy experienced an initial period of
significant progress. Real per capita GDP grew at an average rate of 2.9 percent,
despite the high population growth rate. However, economic progress started to
decline in the late 1960s as a result of growing political turmoil, which culminated
in a coup d’etat led by Idi Amin, who deposed Milton Obote in 1971.
This initial economic progress was ruined by the political turmoil and economic mismanagement of the 1970s. A series of negative external shocks during
the mid-1970s also contributed to the collapse economy, including higher oil
prices and the breakup of the East African Community, which disrupted international traffic movements. Increased military and other expenditures led to large
fiscal deficits, which were financed by domestic borrowing, with inflation as a predictable outcome. Consequently, real GDP fell 25 percent during the Amin period,
with particularly sharp falls recorded in the value added of the industrial and
monetary agricultural sectors. The only sector that recorded steady growth was
the subsistence sector, which provided individual food security and supplied the
thriving and lucrative parallel markets.
The Amin government was overthrown in April 1979 by a combined force of
the Tanzanian army and a Ugandan rebel group, the United National Liberation
Front. In December 1980, Milton Obote assumed power for the second time, with
332
Distortions to Agricultural Incentives in Africa
the economy in deep crisis and infrastructure in complete ruins. The first attempt
to revive the economy was made in 1981, when the government implemented the
Stabilization and Structural Adjustment Program, with financial and technical
assistance from the IMF and World Bank. The program collapsed after barely four
years, following the government’s failure to comply with program benchmarks.
The economic crisis, together with growing political opposition, led to the
removal of the second Obote government in a military coup in 1985. The military
coup led to further repression and economic chaos. After a further six months of
civil war, Museveni’s National Resistance Movement (NRM) took power in 1986.
Between 1981 and 1986, the annual GDP growth rate averaged 2.2 percent,
while the annual average for growth in the agricultural sector was 2.5 percent.
This modest average performance stemmed largely from the recovery in the first
half of this period. Then, after an initial period of indecisiveness, the NRM government agreed to a new policy package with the IMF and World Bank in May
1987, formalized in an economic recovery program. The program aimed to
restore fiscal discipline and monetary stability and to rehabilitate the economic,
social, and institutional infrastructure. Since then, significant unilateral agricultural, trade, and exchange rate reforms have been undertaken aimed, in part, at
removing policy-induced distortions in the agricultural sector. Following these
reforms, real annual GDP growth averaged 6.2 percent, well above the average
annual growth rate of 2.2 percent during the early 1980s and the average annual
decline of 1.6 percent during the 1970s. Annual agricultural growth averaged
3.7 percent between 1987 and 2004, although it declined in 2004 largely on
account of drought. An important question is how much of this buoyant growth
represents a “bounce-back” from the devastation of the previous two decades as a
result of improved security and whether it can be sustained (IMF 2005).
Structural changes in the economy
The British colonial policy turned Uganda into a reservoir of cheap raw materials
for British industry and a market for its finished goods. There was very limited
effort to develop the manufacturing sector, save for the setting up of cotton ginneries and coffee processing plants and the provision of transport infrastructure
to reduce transport costs while at the same time protecting the quality of the raw
materials. Consequently, the structural composition of economic activity was
skewed in favor of agriculture, and this dependence on agriculture has continued
to a rather remarkable extent. In the late 1960s, 92 percent of the labor force
depended on agriculture, and the sector contributed 46 percent of GDP and
97 percent of exports. In 1990, agriculture accounted for around 50 percent of
GDP, 85 percent of employment, 99 percent of export earnings, and 40 percent of
Uganda
333
government revenue. Even in 2000–04, agriculture accounted for 31 percent of
GDP, was the primary source of income for 80 percent of the population, and
contributed 81 percent of exports (Sandri, Valenzuela, and Anderson 2006). The
share of the secondary sector, which includes manufacturing, electricity generation, and construction, has increased only modestly, and the share of the service
sector has increased by about 10 percentage points since 1961.
Characteristics and performance of the agricultural sector
Uganda has a variety of agroclimatic conditions across its regions. Five distinct
farming systems or areas can be defined by the rainfall pattern and soil characteristics. These include the high rainfall area around Lake Victoria where bananas,
robusta coffee, and other food crops are grown; eastern Uganda, with two distinct
rainy seasons separated by a four-month dry period, where the main crops
include millet, cassava, groundnuts, maize, and cotton; the northern region, where
the rainfall pattern restricts cultivation to one season, with the main crops being
cotton, maize, and millet; the mountainous areas, where the altitude permits the
cultivation of temperate fruits, vegetables, and some traditional food crops; and
northeastern Uganda, where the annual rainfall of 80 millimeters is suitable for
pastoralism and the cultivation of sorghum and millet (World Bank 1993). The
country’s natural environment provides good grazing for cattle, sheep, and goats,
with indigenous breeds dominating the livestock industry. The most important
cash crops are coffee, tobacco, cotton, and tea. Coffee has been the main foreign
exchange earner since colonial times. Its share in total agricultural exports was
about 50 percent in the 1960s, grew to more than 80 percent in the early 1980s, but
then to about 20 percent in the early 2000s. Maize and beans have become important nontraditional exports, especially in regional trade.
The number of people dependent on agriculture increased from 3.7 million in
1960–64 to 9.4 million in 2000–04. During the same period, the agricultural land
area increased from 9 million hectares to only 12 million. As a result, agricultural
land per agricultural worker nearly halved, falling to 1.3 hectares over this period.
Ugandan agriculture is largely dependent on small-holder production, where production for household consumption constitutes a significant proportion of the
consumption basket. In 2001/02 the subsistence sector accounted for 44 percent
of total agricultural output, compared with 52 percent in 1991/92. Large-scale
estates are only significant in the tea and sugar subsectors.
The typical diet varies from region to region, a result of differences in staple
crops, of which the most important are plantains (matooke), yam, cassava, maize,
millet, and sorghum. Food production has not kept pace with population growth.
Based on statistics from the Food and Agriculture Organization, mean daily
334
Distortions to Agricultural Incentives in Africa
dietary intake deteriorated between 1992/93 and 1999/2000, from 1,890 calories
to 1,640 calories. The proportion of the population receiving less than 60 percent
of required calories rose from 32 percent to 44 percent over the same period
(Opolot, Wandera, and Atiku 2005).3
The annual growth rate of Uganda’s agricultural GDP averaged 3.4 percent
between 1980–2004, only slightly above the average of 3.2 percent for Africa as a
whole during the same period (Sandri, Valenzuela, and Anderson 2006). The production of cotton, tea, and tobacco virtually collapsed during the late 1970s and
early 1980s. Since the late 1980s, the government’s export strategy has concentrated on reviving traditional exports as well as encouraging diversification in
commercial agriculture that would lead to a variety of nontraditional exports.
Evolution of Policy
The colonial administration created a highly open economy. By 1960, the economy was heavily dependent on import-export trade characterized by the supply of
raw materials for export and the import of consumer goods for the domestic market. The policy framework in the immediate postindependence period (1962–66),
which was built on the recommendations of a World Bank mission, did not deviate much from the policy framework inherited from the colonial administration.
It emphasized the promotion of commodity exports, external financing to bridge
the savings-investment gap, and the promotion of private investment by encouraging existing investors and creating incentives to attract new ones, including
African entrepreneurs. As discussed earlier, commendable economic progress was
recorded during this period.
The second development plan, which came into force in 1967, instituted radical changes aimed at promoting the dominance of the public sector in the economy. The policy emphasis shifted to import-substituting industrialization, and
import tariffs and customs refunds on imported raw materials were introduced,
although the level of protection remained modest (Bigsten 2000). In the same
vein, the government made pronouncements (commonly referred to as the
Nakivubo Pronouncements) directed at socializing the means of production in
1969. Consequently, the government acquired 60 percent of ownership in most if
not all private sector ventures. In addition, the export marketing of all cash crops
was nationalized through the formation of statutory marketing boards. At the
local level, the processing factories (cotton ginneries and coffee factories) originally owned and run by non-Africans were handed over to the cooperative movement managed mainly by Africans. Export taxes, price controls by state marketing
boards, exchange controls, subsidies provision, and administered credit to the
agricultural sector were the order of the day.
Uganda
335
Amin took power in early 1971 and in 1972 declared an “economic war,” during which 50,000 Asians were expelled and their productive and personal assets
confiscated. This huge loss in skilled personnel affected both agricultural and
industrial production. Further damage was caused by economic mismanagement
and a substantial expansion of the public sector, which quickly became a drain on
public resources. The agricultural sector suffered from poor service delivery,
shortage of agricultural inputs, market deterioration, and delayed payments to
farmers. Corruption and the bureaucratic tendencies of marketing boards contributed to high costs. As a result, marketing boards absorbed a larger percentage
of the world market prices, leaving producers with low producer prices. This was
exacerbated by the practice of late payment, which acted as a further tax on farmers’ incomes.
The rehabilitation of the economy was the first task facing the post-Amin governments along with the creation of political stability. The first attempt at policy
reform was in 1981 with the support of the IMF and the World Bank. The policy
reforms included, among other things, the floating of the shilling, an increase in
producer prices for export crops, removal of price controls, and rationalization of
the tax structure and government expenditure.
This reform program collapsed in 1984 after the IMF and World Bank cut off
lending, following the government’s failure to meet the program benchmarks. In
1984 alone, public sector wages increased fourfold, bank credit to government
increased by 70 percent, and the money supply increased by 127 percent. Further,
foreign exchange controls were tightened in the face of insufficient foreign
exchange inflows. The return to economic crisis was both prompted by and a factor in the renewed civil war following which the National Resistance Movement
came to power in 1986.
The new government first reintroduced controls, revalued the currency, and
sought to support the import-substituting sector. The consequences of this policy
stance were economically devastating. The budget remained in serious deficit,
export duties eroded, producer prices and export revenue fell in real terms, the
balance of payments worsened, reserves were depleted, and arrears accumulated.
Underground market activities flourished, inflation rose to over 200 percent
between 1985 and 1987, and the parallel exchange rate rocketed to several times
the official rate (Loxley 1989).4
In early 1987, the NRM government turned to the IMF and the World Bank for
financial assistance. This led to a more consistent and successful phase of policy
reforms launched in May 1987. The reforms embraced monetary and credit policy, fiscal policy, exchange rate policy, and trade policy as well as institutional,
pricing, and domestic market reforms in the agricultural sector (for details, see
the appendix in Matthews, Claquin, and Opolot 2007). In 1997 the national vision
336
Distortions to Agricultural Incentives in Africa
and strategies for the reduction of poverty were articulated in the Poverty Eradication Action Plan, which was further revised in 2000 and 2003. Its overarching
objective is to reduce absolute poverty to less than 10 percent by 2017.
Measurement of Agricultural
Policy Distortions
The main focus of the current study’s methodology (see appendix A in this volume and Anderson et al. 2008) is on government-imposed distortions that create
a gap between domestic prices and what they would be under free markets.
Because the characteristics of agricultural development cannot be understood
from a sectoral view alone, the project’s methodology not only estimates the
effects of direct agricultural policy measures (including distortions in the foreign
exchange market), but it also generates estimates of distortions in nonagricultural
sectors for comparative evaluation.
More specifically, this study computes a nominal rate of assistance (NRA) for
farmers. It also generates an NRA for nonagricultural tradables, for comparison
with that for agricultural tradables through the calculation of a relative rate of
assistance (RRA). Although distortions undoubtedly existed in farm input markets in Uganda during the period analyzed, purchased farm inputs are so little
used in Uganda (with the possible exception of cotton) that we have ignored their
impact.
In our analysis, we have assumed that the farmgate price equals the wholesale
(market) price for primary products, in the absence of detailed information on
the average farm-to-market margin. More problematic is an assumption about
the proportion of the protection or taxation of the processor (as measured by the
processor’s NRA) that is passed back to the primary good wholesaler. For much of
the period before liberalization, government marketing policy set both the wholesale price for the processed product and the market (wholesale) price for the primary product. To the extent that these announced prices were effective (which
was more often the case for export crops than for food crops), processors were
constrained in the extent to which they could pass back the (mostly negative)
effects of government interventions to farmers. The pass-through of distortions
from processors to wholesalers was effectively determined by the margin allowed
by government policy.
Various assumptions about government price-setting behavior are possible for
the period before liberalization. For example, if the government set the producer
price in relation to the processed good wholesale price by allowing for a competitive (undistorted) margin, then the pass-through value should be calculated on
the basis of the inverse of the input-output coefficient between the primary good
Uganda
337
and the processed one at the wholesale level. It turns out that the absolute margin
varies considerably from year to year, making this hypothesis unlikely. We have
thus assumed equiproportionate pass-through of the processed product distortion. In other words, for the preliberalization period we have assumed that, in
setting prices and the processing margin, the government distributed the incidence of its interventions proportionately along the marketing chain.
Product coverage
The commodities covered in our study are coffee, cotton, tea, rice, maize, sugar,
beans, cassava, groundnuts, plantains, cassava, yam, millet, and sorghum. These
commodities account for between 75 and 85 percent of the (nondistorted) value
of output. The trade status of each commodity depends on its net trade position
in volume terms, as determined using FAOSTAT data.5 A commodity was
assumed to be nontraded in any year if either the percentage share of exports or
imports in production was less than 2.5 percent. The reason for nontraded status
needs to be assessed in the calculation of distortions. Where an (otherwise
import-competing) product is not traded because of high trade taxes or nontariff
barriers, the analysis takes that into account. We find that most of the staple foods
were nontraded throughout the period. It is reasonable to assume that the lack of
trade results from trade cost rather than from trade policy reasons. Maize and
beans were nontraded in the early part of the period but were increasingly traded
in the latter part of the period.
Marketing costs of the state marketing boards
Parastatal marketing boards dominated agricultural marketing in Uganda from
independence until the early 1990s. These boards had the sole right to export coffee, cotton, and tea, and they regulated internal marketing as well. Thus, coffee
growers could sell only at licensed markets or to licensed traders at a fixed minimum price, and the processing margin was also fixed by the marketing board.
Similarly, in the case of cotton, growers had to sell to ginners in a particular zone
at a predetermined price, and the margins allowed for ginners were fixed by the
Lint Marketing Board. To the extent that the margins of the boards themselves or
the margins determined for processors were higher than what would have been
expected in an unregulated situation, then the extensive government regulation of
agricultural marketing counts as an additional distortion that should be included
in the NRA of these commodities. The parastatal marketing boards also undermined the efficiency of the marketing system. Payments to cooperative unions
and thus to farmers were often delayed, resulting in a real reduction in the prices
338
Distortions to Agricultural Incentives in Africa
received, particularly when inflation was high. Stock levels were often unnecessarily high, and crop finance was inadequate. Delays in collection and transport
caused qualitative losses, for example, in coffee. Although the likelihood of inefficiencies can be documented, trying to quantify their magnitude is more difficult.
One approach is to compare the marketing margins after liberalization with those
before liberalization, on the assumption that greater competition after liberalization would lead to increased efficiency and drive margins closer to opportunity
costs. We report on the results of this comparison when discussing the NRAs for
coffee and cotton.
Treatment of foreign exchange distortions
For most of the period, Uganda had a parallel exchange rate, which often was a
large multiple of the official rate (figure12.1). The premium increased rapidly in
the 1970s, when the parallel rate grew to 10 times the official rate, and grew again
in the mid-1980s as detailed in the appendix to Matthews, Claquin, and Opolot
(2007). We assume that all agricultural exports were converted at the official
exchange rate until liberalization began in 1991 and that food imports were purchased at the parallel market rate. This assumption may exaggerate the bias
against agricultural exports in some years, because some agricultural exporters
Figure 12.1. Parallel Market Exchange Rate Premium over the
Official Exchange Rate, Uganda, 1961–2004
12
10
proportion
8
6
4
2
Source: Data compiled the authors.
03
00
20
97
20
94
19
91
19
88
19
85
year
19
82
19
79
19
76
19
73
19
70
19
67
19
64
19
19
19
61
0
Uganda
339
may have had access to foreign exchange at official rates.6 This overvaluation of
the exchange rate was by far the most important policy distortion affecting agricultural incentives over the period. The size of this distortion can be measured relative to an estimated equilibrium exchange rate. The estimated division of the
total foreign exchange distortion between an implicit export tax and an implicit
import tax depends on the estimated elasticities of supply of exports and of
demand for exports (Anderson et al. 2008). In the absence of more specific information, we assume that these elasticities are equal and estimated the equilibrium
exchange rate to be the mean of the official and parallel market rates.
Treatment of input distortions
In calculating the overall NRA for an agricultural product, distortions in relevant
input markets should also be taken into account. Government agencies had a virtual monopoly on the marketing of agricultural inputs in Uganda. They provided
different levels of price subsidies for inputs based on the exchange rate margins
between the official and parallel market rates. In the early 1990s the government
withdrew entirely from the marketing of agricultural inputs. Liberalization was
followed by the government’s removal of tariffs on imports of these inputs. The
availability of inputs, including agrochemicals, farm tools, and implements, is
now much improved compared with the situation before liberalization. However,
the market for agricultural inputs remains very small and these input market distortions have not been taken into account in the computations.7
Subsidized credit was an important instrument of development policy. The
Uganda Development Bank and several other institutions supplied credit to local
farmers, although small farmers also received credit directly from the government
through agricultural cooperatives. However, for most small farmers, the main
source of any short-term credit was the policy of allowing farmers to delay payments for seeds and other agricultural inputs provided by cooperatives. While
government-imposed fixed lending rates and poor recovery rates implied that
those farmers fortunate enough to secure a loan received an implicit subsidy, the
sharp curtailment of lending as a result of these financial losses implied that
the agricultural sector as a whole was disadvantaged. In addition, donor funds
were made available (often at negative interest rates) for the rehabilitation of the
agroprocessing sector during the 1980s. In the absence of data, we have not been
able to incorporate these credit subsidies into our analysis, but in quantitative
terms they are not likely to have been significant.
Other interventions, such as high fuel taxes and duties on imported vehicles,
adversely affect the cost of agricultural marketing. But these policies do not discriminate specifically against agriculture so they are not counted as distortions in
340
Distortions to Agricultural Incentives in Africa
this analysis. A specific distortion in the preliberalization period was the monopoly held by the Uganda Railways Corporation on the transport of coffee to
Mombasa. The state-run railway system was very inefficient, as shown by the very
long turnaround times both in Kampala and Mombasa. Transportation of coffee to
ports for export was liberalized in 1992. Competition among freight and shipping
companies reduced the cost of moving commodities from Uganda to Mombasa by
over 40 percent in the five years between 1997 and 2002 (NRI/IITA 2002).8 This
sharp fall in the cost of shipping exports to Mombasa means that the Uganda freeon-board (fob) prices relative to the international price should have increased.
Because we have used fob prices as the relevant international prices for our analysis, we do not capture this distortion and its subsequent removal in our analysis.
Trends in Agricultural Distortions in Uganda
We begin with estimates of distortions in the two most important traditional
export products, coffee and cotton, before discussing distortion estimates for the
rest of the farm sector and for nonagricultural tradables.
Coffee
Robusta coffee has been Uganda’s traditional coffee export; however, arabica production has increased over time and in the early 2000s accounted for around
15 percent of production. Given its importance in the Ugandan economy, the
industry has been under tight government control since the colonial era. A Coffee
Industry Board was established in 1953 to administer the price-fixing provisions
previously covered by the defense regulations. Uganda joined the International
Coffee Organization which came into being in 1962, and had to conform to the
export quota allocated by that organization. To manage this export quota, a Coffee
Marketing Board was established by the 1962 Coffee Act and given a monopoly over
robusta marketing and export. This monopoly was extended to all coffee in 1969.
The preliberalization system was based on fixed producer prices and processing margins, with small-holders delivering coffee to primary cooperatives or
private traders. The coffee was then transported to either cooperative unions or
private traders for hulling. The processors had to pay a minimum price to
growers, although this price could be discounted at markets to account for the
transport cost to the factory. The hulled coffee was then sold, at prices fixed by the
government, to the marketing board, which in turn sold to exporters overseas
(NRI/IITA 2002). With all margins fixed by the government, the difference
between export receipts and the government-set price of exports in local currency
remained with the government. The marginal tax rate was 100 percent (World
Uganda
341
Bank 1993). Marketing-chain costs and margins after liberalization are described
in NRI/IITA (2002).
With the adoption of the economic reform program in 1987, a series of institutional and marketing reforms was implemented in the coffee sector. In 1990, the
marketing board’s export monopoly was removed, giving cooperative unions and
private exporters access to the export market. To separate regulatory and trading
functions, two new institutions were created within the marketing board: the
Uganda Coffee Development Authority (UCDA) took on regulatory authority, and
Coffee Marketing Board Limited took on the trading functions. In July 1991, controls on prices and margins were removed; however, the administered prices were
replaced by indicative prices announced by the UCDA, and a floor price was
announced daily for exports. Competition in the industry was further enhanced in
November 1991, when government guarantees for crop financing were withdrawn,
effectively making life more difficult for the cooperatives who had been the beneficiaries of the guarantees. In March 1992, exporters were permitted to exchange coffee proceeds at the open-market rate and in July 1992 the export tax on coffee was
removed, although it was briefly reimposed in the wake of the coffee boom in 1994.
Currently, there are no restrictions on coffee trading or processing of coffee,
although since 1995 the UCDA has levied a cess (currently 1 percent) to finance its
activities of quality control and promotion and monitoring of coffee marketing.
International prices for coffee (a weighted average, using Ugandan production
weights, of robusta and arabica world prices) in 2004 were close to those in 1961
in nominal U.S. dollar terms, but in the intervening years the coffee market experienced three price spikes: in 1977, 1987, and 1995. The Uganda fob (US$) price
closely follows the international price, though at some discount that probably
reflects the transport cost of shipping coffee from Kampala to Mombasa and
onward to international markets. The fob price in local currency expressed in constant prices bore little relationship to the fob price in U.S. dollars between the
early 1970s and the mid-1980s, largely because of the increasing misalignment of
Uganda’s exchange rate during this period. Thus, local currency proceeds from
coffee exports declined in the 1970s, despite the coffee boom in the second half of
that decade, and increased significantly in the first half of the 1980s, thanks to successive devaluations of the shilling. Since the early 1990s, the two series have
moved in tandem. Compared with the local producer price, the fob price in local
currency appears to be much more volatile.
Real producer prices were stable in the 1960s but fell drastically during the
1970s. There was some recovery in the first half of the 1980s, but the nonadjustment of the nominal farmgate price in an environment of high inflation in the late
1980s again resulted in a serious loss of real value. It was only after liberalization
that real prices recovered sharply. The reforms led to increased competition
342
Distortions to Agricultural Incentives in Africa
among processors and exporters of coffee. Prices to coffee farmers not only went
up following liberalization but farmers were also paid promptly, reportedly leading to a rapid reversal of the previous neglect of coffee trees. However, the collapse
in international coffee prices since the mid-1990s, attributable in part the emergence of Vietnam as a serious competitor in robusta coffee, has been reflected in
falling real producer prices as well.
Margins were high in the 1960s but collapsed during the 1970s, appearing to
become even negative in some years. Margins recovered during the 1980s, leading
the World Bank to report that “margins were set at or above average processing
costs, and had grown to ‘comfortable levels’ by 1990” (World Bank 1993). That
appears to have been the case, because margins have approximately halved in real
terms since liberalization began in 1991. According to the NRI/IITA (2002), coffee
supply chains are now reasonably competitive and efficient, with no clear areas
within the supply chain where potential exists for major and significant reductions to transactions costs. All the evidence suggests that the domination of coffee
marketing by the marketing board and cooperative unions in the preliberalization
period led to marked inefficiencies, although we could not see this effect in the
data.9 Because of the behavior of margins in 1975–85, margins before liberalization were no higher on average than they were after liberalization.10
The overall primary coffee NRA at the farmgate, including the distortion introduced by foreign exchange market misalignment, is shown in figure 12.2. This is
Figure 12.2. Coffee and Cotton NRAs, Uganda, 1961–2004
0
collapse
recovery
postliberalization
NRA (percent)
20
40
postindependence
60
80
19
6
19 1
6
19 3
6
19 5
6
19 7
6
19 9
7
19 1
7
19 3
7
19 5
77
19
7
19 9
8
19 1
83
19
8
19 5
87
19
8
19 9
9
19 1
93
19
9
19 5
97
19
9
20 9
0
20 1
03
100
year
coffee
Source: Data compiled by the authors.
cotton
Uganda
343
also the NRA at the processing level, given our assumption of equiproportionate
pass-through. Coffee became increasingly taxed even in the immediate postindependence period, reaching a negative NRA of over 40 percent in 1971. However,
the agony became worse during the 1970s, when the implied taxation of producers increased to reach a negative NRA of over 90 percent in the late 1970s.
Although export taxation continued to weigh heavily, the main contribution to
the NRA during this period came from the requirement to exchange foreign currency earnings from coffee exports at the increasingly unrealistic official exchange
rate. The situation of coffee growers improved during the recovery period of the
1980s, with the setback in the mid-1980s coinciding with the stalling of the first
effort at economic reforms. Only following the initiation of the economic recovery program in 1987 did a lasting improvement in the NRA take place, and since
1995 there have been no distortions in Uganda’s coffee market.
Cotton
Cotton production and marketing has also been regulated by the government
since colonial times. The licensing of ginneries was initiated in 1907. In 1933, the
Cotton Zone Ordinance divided the country into fourteen zones and allocated an
area to each ginnery in which it was the monopoly buyer. The government established a minimum pricing scheme, in collaboration with the ginners, and a
maximum charge was set for ginning and baling. The revised 1964 Cotton Act
provided for the zoning of cotton production, the setting of fixed seed and cotton
lint prices, restrictions on cotton imports and trade, and the licensing of ginneries. This system of controlled marketing and prices continued until 1993.
The Lint Marketing Board Ordinance of 1949 established the Lint Marketing
Board with the right to purchase all cotton for export, although ginneries were
still free to sell to domestic mills.11 The price the board paid to the ginners was
fixed by the government based on the price the ginner had to pay to the grower,
which was also fixed by the government. Thus both ginning and exporting had
monopsony buyers—the cooperative unions and the Lint Marketing Board—
working with captive clients on a predetermined margin (World Bank 1993). The
lint was sold to exporters by auction in Kampala. Whether the board made a profit
or loss on its operations depended on the price fixed for seed cotton in relation to
world prices.
Cotton marketing reforms were undertaken in sequence since 1990, when
earnings from cotton exports were allowed to be valued at the market exchange
rate. From 1993 private buyers were permitted to buy cotton, but the cooperative
unions continued to monopolize the ginning sector until mid-1995, when a transfer of ginneries to the private sector commenced. Cooperative unions continue to
344
Distortions to Agricultural Incentives in Africa
play an important role in processing and marketing, but many now source their
cotton through private buyers in addition to cooperative societies (Shepherd and
Farolfi 1999). Information on cotton market costs and margins since liberalization is given in NRI/IITA (2002).
The Cotton Development Organization was established in 1994 to carry out
regulatory and development activities. The agency publishes an indicative farmgate price at the beginning of each cotton season, which the ginneries treat as a
maximum farmgate price (NRI/IITA 2002). It charges a levy of 35 percent of the
value of seeds produced by a ginnery to cover the costs of a seed distribution fund.
Ginneries that are approved sources of seeds can offset the cost of the levy by supplying farmers with seeds or by selling seeds to those ginneries that are not
approved seed sources.
The international price for cotton lint (the Cotlook A Index) increased during
the commodity price boom of the mid-1970s before declining to its lowest level
ever at the close of the 1970s. It recovered in the early 1980s but has since
displayed a declining trend. The Ugandan fob price (converted using the market
exchange rate) has largely moved in tandem with the international price, with the
exception of the mid-1970s. This is not surprising because cotton lint was sold at
auction throughout the period.
In the early years of administered prices, the Lint Marketing Board had access
to a price assistance fund built up on the basis of the profits earned in the bulkpurchasing era. During the 1950s, it had a deliberate policy of subsidizing the
producer price, with the consequent losses covered by the price assistance fund. Producer prices were not adjusted to keep pace with inflation, however, and fell dramatically in real terms; by the 1970s the assistance policy had changed to one of
producer taxation. Cotton production collapsed and smuggling increased as
farmers tried to take advantage of better prices in neighboring countries. Prices
recovered in real terms in the first half of the 1980s but have followed the downward trend in international prices since then.
The marketing and processing margin, calculated as the difference between the
fob price (converted at the official exchange rate) less the export tax and producer
price, has fluctuated widely. In years when the fob price increased, the margin also
increased, and vice versa. This pattern is consistent with the observed behavior in
the cotton market where the indicative price announced at the beginning of the
season is treated as a fixed price and any volatility in the fob price is reflected in
agents’ margins rather than in the producer price. Margins were slightly larger, on
average, after liberalization.12 However, our method of calculating the producer
price in this period could have exaggerated the margin. We took the indicator
price as the producer price, although some observers believe the indicator prices in
recent years acted only as floor prices. We conclude that the data do not allow us
Uganda
345
to quantify the effects of marketing inefficiencies through a comparison of margins before and after liberalization, and thus we do not incorporate any estimate
of marketing distortions in the cotton NRA.
Soon after independence, a moderate export tax was placed on cotton of
around 15 percent of the (pretax) export price, and the NRA averaged about 13
percent. During the economic collapse in the 1970s, the export tax continued
albeit at a slightly lower rate (see figure 12.2). The main contributor to the
increased negative NRA was the requirement to convert cotton foreign exchange
earnings into local currency at the increasingly overvalued official rate. Producer
prices fell precipitately in real terms and cotton production collapsed. The steps
taken by the new government in 1981 to devalue the shilling show up in an immediate reduction in the negative NRA, helped by the absence of export taxation in
1980–84. The collapse of the first reform program led to a further temporary
overvaluation of the exchange rate, which shows up as an increased burden on
farmers—the NRA reached 72 percent in 1986, just before the NRM government took power. By 1992, however, distortions had been effectively removed and
the NRA was zero, although it was not until 1995 that the cotton market was fully
liberalized.
Other farm products
The remaining commodities covered in this study can be classified into predominantly exportables, predominantly import-competing products, or predominantly nontradables. It is characteristic for the three tradables—maize, beans, and
to a small extent, rice—that their status shifts between all three categories over the
period. Cassava, groundnuts, plantains, yam, millet, and sorghum are treated as
nontradables whose price is formed entirely domestically.
At independence in 1962, the government introduced minimum producer
prices that were set higher than the equilibrium market prices for some crops. Buyers refused to buy at these prices, and there was no state institution to act as a buyer
of last resort to support these minimum prices. In the case of groundnuts, the state
required the cooperative unions to purchase at the minimum price. It guaranteed
them against the losses involved, but such a system was not sustainable because
there were no price assistance funds (as had built up for cotton and coffee) to fall
back on. To address this deficit, the Produce Marketing Board was established in
1968. The stated purpose of this board was to stabilize the prices of food crops by
buying when prices were low, storing the surplus, and releasing stock when prices
were high. In addition, the board was exclusively responsible for the procurement
and export of maize, beans, sesame (simsim), soybeans, and groundnuts.13 The
board’s influence as a market agent appears to have been insignificant, in part
346
Distortions to Agricultural Incentives in Africa
because it had no facilities in rural areas to effectively buy from producers, and in
part because its predetermined prices were lower than market equilibrium prices.
Its role was limited to buying what was offered to it and selling mainly on request
to government institutions (Ngategize and Kayobyo 2001). In 1989, the board’s
market monopoly of in foodstuffs trade was brought to an end. These market
reforms were accompanied by the removal of restrictions on the movement of produce across districts in 1992 (Opolot, Wandera, and Atiku 2005).
Another marketing body, Foods and Beverages Ltd., was a government-owned
trading company intended to protect consumers so that prices did not go beyond
the controlled prices, to ensure constant supplies, and to protect domestic producers through import control. The company handled both exports and imports,
but established private traders were allowed to import or export so that the statetrading enterprise should not become a monopoly.
Beans have been an export crop in Uganda, although during the 1970s they
effectively became nontraded and in other years they have been an importable
(leading to a sharp increase in the border price of beans in 1998, for example).
In general, the producer price and the border price are closely aligned in years
when beans are exported. Retail prices lie above both producer and border prices.
Bean prices in real terms more than doubled after independence, but fell during
the economic collapse of the 1970s, possibly because resources shifted from the
traditional export crops into subsistence farming and staple crops. Real bean
prices rose in the economic recovery period but stabilized later.
Maize is not a traditional staple food crop for Uganda’s population, but it plays
an important part in the rural and urban diet. Maize was one of the crops controlled
by the Produce Marketing Board. Following the liberalization of the grain sector,
there have been no significant policy, regulatory, or institutional constraints to its
development. Maize marketing costs and margins after liberalization are given in
NRI/IITA (2002). Maize producer prices (for grain) are closely aligned to the fob
export price in the years when maize was exported; the prices diverge in years (such
as 1969–70, 1980–82, and 1997–99) when the status of maize changed to a net
importable. Retail and producer prices broadly follow the same pattern as for beans.
Real prices increased after the independence period, fell during the 1970s, recovered
somewhat during the 1980s, and have remained relatively stable since then.
Uganda produces a significant amount of rice but generally not enough to
meet domestic demand, and in most years rice is an importable. Rice prices
trended upward in real terms in the 1960s, and the limited information available
on producer and retail prices suggests they too increased. Prices fell during the
1970s, and after some recovery in the first half of the 1980s, gradually trended
downward. Between 1981 and 1995, the producer price closely followed the border price (the producer price refers to paddy rice and the fob price to imports of
Uganda
347
milled rice, this is consistent with positive protection of local rice production during this period). Since 1994, domestic producer prices have exceeded the fob price,
suggesting a further strengthening of protection.
Cassava is shown as an example of the other nontradables that all follow
exactly the same NRA pattern. It is a major staple food in Uganda and is consumed either in fresh or dried flour form. Dried cassava had a complex marketing
chain (NRI/IITA 2002). From harvest to purchase at the local store, cassava must
be dried, bulked, transported, stored, milled, and finally retailed. This report gives
an example of costs and margins in dried cassava trading between rural and urban
areas based on data from early 2000. The markup on the producer price of 10,000
shillings per 100 kilograms was 200 percent. Fresh cassava trading is more streamlined, driven by the perishability of cassava roots, which are unsalable after five
days. Margins are also higher, up to 400 percent in 2000, given the greater price
and physical product risk borne by traders. Generally, the NRA for cassava and
other nontradables was zero throughout the period.
Rice as an importable has always had positive protection. In the 1960s, this was
due mainly to assumed tariff protection. Protection grew dramatically in the 1970s,
largely because of exchange rate protection, and gradually subsided in the 1980s as
the official exchange rate moved toward the equilibrium rate. The observed positive NRA during 1994–2004 is attributable exclusively to tariff protection. NRAs
for maize and beans jump around but are generally low throughout the period.
Positive protection occurred in years when these products became importcompeting products, while negative protection represents the implicit exchange
rate tax in years when they were exportables.
Aggregate NRA for the agricultural sector
The aggregate NRA for the primary agricultural sector is obtained by weighting the
NRAs for individual commodity by their undistorted value of production. NRAs
are also calculated for each subgroup of exportables, import-competing products.
and nontradables (table 12.1 and figure 12.3). The commodities examined account
for 75–85 percent of the total value of agricultural output (at undistorted prices).
The noncovered farm products were allocated to each of the three groups. In the
case of exportables among this group, we assume that the foreign exchange rate
misalignment was the sole source of distortions. In the case of import-competing
products, we assume that the sources of distortion included the foreign exchange
rate misalignment as well as the applied tariff rate.14 The main import-competing
commodities not covered are sugar, dairy products, wheat flour, vegetables oils, and
meat products. In the case of nontradables, we assumed that the sole source of distortion was the differential application of value added tax after 1995.
348
Table 12.1. NRAs for Covered Farm Products, Uganda, 1961–2004
(percent)
Product indicator
Exportablesa,b
Cotton
Coffee
Tea
Import-competing productsa,b
Nontradablesa,d
Cassava
Millet
Yam
Plantains
Sorghum
Groundnuts
Mixed trade statusa
Rice
Maize
Bean
Sugar
Total of covered productsa
Dispersion of covered productsc
Percent coverage (at undistorted prices)
1961–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
8.9
13.4
11.4
1.1
16.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
15.4
18.9
21.7
6.5
22.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
43.7
42.3
50.9
36.4
42.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
89.8
79.6
90.8
77.6
79.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
66.6
52.0
71.5
52.0
54.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
65.0
58.5
67.7
9.9
57.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
9.6
7.5
13.0
7.5
14.8
0.4
0.4
0.4
0.4
0.4
0.4
0.4
1.3
0.2
2.1
0.2
13.9
0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.0
1.0
0.0
15.0
0.3
0.3
0.3
0.3
0.3
0.3
0.3
13.7
1.0
5.9
1.0
3.0
8.1
83
19.7
3.4
1.6
6.5
5.1
12.1
84
42.8
15.0
3.2
20.2
11.6
24.3
87
48.0
0.0
0.0
15.4
24.5
46.6
86
54.5
25.8
0.0
34.7
11.5
43.2
75
45.5
18.6
0.0
57.8
14.1
40.5
77
4.2
7.5
3.5
14.7
1.1
7.8
75
13.1
6.5
3.8
16.1
0.6
6.6
79
17.3
0.0
0.1
16.9
0.5
6.9
77
Source: Data compiled by the authors.
a. Weighted averages, with weights based on the unassisted value of production.
b. Mixed trade status products included in exportable or import-competing groups depending upon their trade status in the particular year.
c. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
d. Nontradables cassava, millet, yam, plantains, sorghum, and groundnuts have the same NRA as the nontradables average in all periods.
Uganda
349
Figure 12.3. NRAs for Exportable, Import-Competing, and All
Farm Products, Uganda, 1961–2004
120
80
percent
40
0
40
80
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
120
year
import-competing products
exportables
total
Source: Data compiled by the authors.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
The main exportables not explicitly covered are tea and tobacco. Tobacco is the
second largest cash crop after coffee. Tobacco production, processing, and marketing are vertically integrated. Inputs and extension services were provided as a
package to farmers on credit. Production peaked in the early 1970s but collapsed
during the late 1970s when management was brought under the monopoly of the
National Tobacco Corporation. There was a divestiture of the industry to British
American Tobacco in 1984. The tobacco industry has since been opened to other
competitors, although British American Tobacco continues to control up to
93 percent of the market.
Tea in Uganda is grown mostly on large estates because of its more rigorous
processing requirements although small-holder tea production has existed since
1966. Management of the tea industry was originally under the control of the
Uganda Tea Association, a voluntary association of tea producers established
in 1948. In 1972, the Uganda Tea Authority took control, but production
350
Distortions to Agricultural Incentives in Africa
subsequently collapsed in 1979 when war forced closure of the factories. In 1983,
the industry was liberalized and the Uganda Tea Association was revived. Since
then, policy reforms such as the removal of the Uganda Tea Authority monopoly
on exports, valuation of export proceeds at the market exchange rate after 1987,
and liberalization of export marketing have stimulated production. For both sectors, taking account of the exchange rate misalignment may underestimate the
extent of distortions at certain periods, but the impact on the overall NRA is likely
to be small.
The results of our calculation show marked differences in the stance of policy
toward the three main groups. Most striking is the heavy taxation of exportables
until the 1990s. The situation for producers of exportables deteriorated in the
1960s and worsened further during the 1970s. Much of this deterioration was
driven by the overvalued exchange rate and the gap between the official and parallel market rates which grew enormously during this period. Matters improved,
but only slightly, in the 1980s. Only in the first half of the 1990s did a major
improvement occur, and since 1995 all direct distortions against exportable crops
have been effectively removed (see figure 12.3).
The situation for import-competing products was almost the mirror opposite, again mainly driven by exchange rate movements. From a moderate level in
the 1960s, protection increased substantially in the second half of the 1980s.
Particularly during the 1970s, when agrifood imports required the purchase of
foreign exchange at the parallel market rate, there was very large positive
protection of import-competing agricultural sectors in Uganda. As the foreign
exchange market gradually returned to equilibrium at the beginning of the
1990s, the implicit protection of import-competing products also fell, although
it continued at a relatively modest rate during the 1990s and the early 2000s,
mainly representing continuing tariff protection of these commodities (see
figure 12.3).
Given our assumption of the ineffectiveness of the Produce Marketing Board,
there were no policy interventions that affected the incentives to produce nontradable agricultural products over the period. After 1990 there was a very small
negative bias stemming from the operation of the value added tax system. Thus,
despite the very large swings in the distortions affecting the two tradable subsectors of agriculture, the overall (negative) NRA indicator for agriculture remained
at modest levels—a result of the predominance of largely nontraded food crops in
Uganda’s agricultural production, and the relatively small share of these crops that
were marketed; most of this production was consumed by the growers themselves.
While the overall magnitude of the distortions remained low throughout the
period, the strong bias against export crops undoubtedly held back the development of the sector.
Uganda
351
Nonagricultural NRAs
As already mentioned, the total effect of distortions on the agricultural sector
depends not just on the size of agricultural policy interventions but also on the
magnitude of the distortions generated by direct policy measures in nonagricultural tradable sectors. The RRA measures the size of distortions in agriculture relative to those in other sectors. The higher the nonagricultural NRA, the more
other sectors are in a position to attract resources away from the agricultural sector, adding further to the discrimination against this sector or reducing the value
of any direct positive assistance that may be granted to farmers.
Various policy measures were included in the computation of the nonagricultural NRA. We included customs duties, export taxes (which were imposed on
copper and hides and skins in some years up to 1977), the import commission
and withholding tax, and the differential application of sales tax and value added
taxes (the calculations are described in the appendix to Matthews, Claquin, and
Opolot 2007). Other nontariff barriers could not be included because of an
absence of specific information; these may have been important in earlier decades
but were eliminated after liberalization. Exportable nonagricultural goods were
heavily taxed throughout the 1970s and 1980s, largely through the unfavorable
exchange rate regime, while import-competing products were strongly protected
in the 1960s and 1970s by the distorted exchange rate regime and more recently by
effectively higher value added tax rates and import tariffs. Overall, relatively limited protection of around 8 percent in the late 1960s increased to 15–20 percent
during the 1970s and 1980s, before falling back to 9–13 percent during the 1990s
and early 2000s.
The resulting NRAs for nonfarm tradables, and the RRA, are shown in
table 12.2 and figure 12.4. The trend in the RRA can be divided into four periods.
During the 1960s, the RRA was initially negative but small. During the Amin
period in the 1970s, the position of agriculture worsened considerably, mainly
because of an increase in support to the nonagricultural sector that averaged over
50 percent; however, an increase in direct distortions also negatively affected agriculture. The 1980s saw limited dismantling of the heavy antiagriculture bias in
government policy, with the RRA averaging just under 50 percent; that was still
worse than the level that prevailed at the beginning of the 1970s. The improvement in the RRA resulted primarily from an improvement in the agricultural
NRA, although the level of protection for the nonagricultural sector decreased
slightly. The RRA continued to improve in the 1990s and the early 2000s. Indeed,
by 2004 there was now some small positive protection of the agricultural sector
arising from direct policies alone, including the continued protection of importcompeting products and a complete abolition of government interventions on
352
Table 12.2. NRAs for Agriculture Relative to Nonagricultural Industries, Uganda, 1961–2004
(percent)
Indicator
1961–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
NRA, covered products
NRA, noncovered products
NRA, all agricultural products
Trade bias indexa
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAb
Memo item, ignoring exchange rate
distortions:
NRA, all agricultural products
Trade bias indexa
RRAb
3.0
4.4
1.8
0.20
4.6
9.6
13.0
5.1
7.2
3.1
0.30
8.6
19.4
23.1
11.6
16.9
7.8
0.58
24.3
34.9
43.1
24.5
18.6
19.2
0.94
70.6
68.1
82.1
11.5
10.7
5.9
0.77
22.8
53.6
49.5
14.1
17.0
6.8
0.77
25.1
52.9
50.6
1.1
0.8
0.6
0.21
1.3
21.6
18.8
0.6
0.2
0.5
0.13
4.0
31.0
20.6
0.5
0.1
0.4
0.13
3.4
26.1
18.0
1.5
0.20
12.0
1.5
0.25
15.7
0.6
0.36
11.0
3.1
0.70
39.8
1.4
0.54
15.7
0.8
0.53
5.6
0.5
0.16
13.2
0.5
0.13
20.5
0.4
0.13
17.9
Source: Data compiled by the authors.
a. Trade bias index is TBI (1 NRAagx兾100)兾(1 NRAagm兾100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and
exportable parts of the agricultural sector.
b. The RRA is defined as 100*[(100 NRAagt)兾(100 NRAnonagt ) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural
and nonagricultural sectors, respectively.
Uganda
353
Figure 12.4. NRAs for Agricultural and Nonagricultural
Tradables and the RRAs, Uganda, 1961–2004
100
80
60
40
percent
20
0
20
40
60
80
67
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
19
19
64
19
19
61
100
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the authors.
Note: For a definition of the RRA, see table 12.2, note b.
exportables. The limited protection of agricultural production is slightly smaller
than the assistance to producers of nonagricultural goods, however, so the RRA is
slightly below zero.
Conclusions
The results reported here suggest a number of important conclusions. First of all,
we note that the data are limited and the measurement of distortion rates could
undoubtedly be improved. For example, we have not taken into account the
impact of input market distortions. The use of purchased farm inputs is very limited, however, so this omission is unlikely to significantly alter the conclusions.
More importantly, we have not been able to take into account all of the impact of
state control over agricultural marketing before liberalization. We did not find
evidence that margins were higher in this period, but there were probably inefficiencies that adversely affected farmers and yet are not captured in the published
354
Distortions to Agricultural Incentives in Africa
prices, such as the effect of delayed payment, the impact of the Uganda Railways
monopoly on the transport of coffee to the coast, or the restrictions on food marketing across regions. Finally, nontariff barriers to imports of nonfarm products
in the preliberalization period mean we underestimate the size of the negative
RRA in those years.
Despite the caveats described above, the broad story that emerges from our
limited data is plausible. In the early years of independence, agricultural incentives were broadly neutral, although positive protection to the nonagricultural
sector meant that some discrimination existed against the agricultural sector.
The shift to a state-led development strategy in the late 1960s was reflected in
increased direct taxation of the agricultural sector, particularly of export crops.
However, the NRA for the agricultural sector as a whole turned only slightly negative. Despite the importance of the cash crop sector as a source of foreign
exchange earnings and in underpinning the growth of the monetary economy,
most Ugandan agricultural production consisted of, and still consists of, staple
food production, much of it of a subsistence nature and composed predominantly of nontraded products. Despite regulations affecting food marketing, and
the existence of the Produce Marketing Board for much of the period, the evidence suggests that food markets remained mainly local and were not much
affected by direct policy interventions. This explains the resilience of the sector
when incentives for the exportables sector were totally undermined during the 15
years of economic chaos between 1971 and 1986 and the early hesitation in
introducing reforms by the new government in 1986. Much of this distortion
resulted from the substantial overvaluation of the shilling during those years,
which gave significant protection to import-competing substitutes, although the
overall extent of economic disorder meant that the agricultural sector received
little benefit from these incentives. The nonagricultural sector was potentially a
bigger beneficiary from the overvalued exchange rate, but the impact of other
events that cannot be captured in price policies, such as the expulsion of the
Asian business community or the effect of war on industrial capacity, severely
limited any likely benefits there.
Liberalization of agricultural marketing began in earnest in 1991, and the subsequent 13 years saw a remarkable change in policy toward the agricultural sector.
Direct disincentives were eliminated, while direct assistance to the nonagricultural
sector remained relatively unchanged over this period, at around 8 percent,
despite the simplification and reduction in nominal tariff rates. Thus there continued to be some relative discrimination against the agricultural sector in
Uganda, but it was tiny compared with previous periods.
Despite this improved policy environment for agricultural growth, the sector
remains in great difficulty. Even after liberalization, real value added in primary
Uganda
355
agriculture has grown at markedly lower rates than the average for the overall
economy, and is only slightly higher than the rural population growth rate of
3 percent a year. Producer prices close to the cost of production threaten the viability of the coffee and cotton sectors. Improving profitability will be dependent
on improved efficiencies in production, marketing, and processing. Also, rural
infrastructure remains very poor. Considerable effort has been put into roads
improvement; the average distance of households to a tarred road fell from
32 kilometers in 1997 to 22 kilometers in 1999/2000, and communities on average
live within 2 kilometers of all-season feeder roads. But access to electricity in rural
areas remains low: only 12 percent of all villages and only 2.1 percent of all rural
households have electricity connections in Uganda, rates that are among the lowest in the world. The implicit taxation of exports caused by poor infrastructure
and high transport costs in 1994 was estimated to be equal to nearly two-thirds of
value added. Correspondingly, transport-induced trade barriers provide effective
protection for domestic sales even after liberalization. These “nonpolicy” barriers
to trade have been blamed for the sluggish response of the Ugandan economy to
the extensive trade policy reforms undertaken over this period (Milner, Morrissey,
and Rudaheranwa 2001).
Uganda’s current economic strategy as laid out in its Poverty Eradication
Action Plan sets the long-term goal of reducing the incidence of income poverty
in Uganda from 44 percent in 1997 to less than 10 percent by 2017. Agriculture
still dwarfs any other sector in terms of its share of economic activity and employment and as a source of income, especially for poor people. The potential for
growth resulting from economic reforms and rehabilitation of the economy from
the past devastation had largely been exploited by the mid-2000s. There is a need
to focus more systematically on raising the growth rate of agricultural production
to supply domestic, regional, and overseas markets.
Raising existing levels of protection to the agricultural sector as a way of providing additional incentives would be a fruitless strategy. Tariff protection to
industry, although lower in nominal terms than on agricultural products and
food processing, does contribute to a relative bias against agricultural production
simply because of the greater importance of import-competing products in
domestic nonagricultural production. However, it would be better to deal with
this discrimination through a further reduction in manufacturing tariffs rather
than by raising agricultural tariffs. The latter would benefit a very small subset of
agricultural products—wheat, dairy products, sugar, vegetable oils—where the
impact on poverty of increased production, except perhaps in sugar, would be
limited.
Ugandan agriculture now needs to concentrate on improving its competitiveness through a supply-side investment strategy, including in agricultural research
356
Distortions to Agricultural Incentives in Africa
and extension and rural infrastructure. The key to this strategy is additional
investment in rural areas, not higher protection. The government’s Program for
the Modernization of Agriculture points in the right direction (Government of
Uganda 2000). If Uganda is to meet the poverty reduction targets set out in its
poverty eradication plan, then investment in enhancing agriculture’s supply
capacity must be given much higher priority both in government budget allocations and in donor aid flows than is currently the case.
Notes
1. The figures in this paragraph are drawn from Sandri, Valenzuela, and Anderson (2006), based
on the World Development Indicators of the World Bank (2006).
2. More extensive reviews of economic policy during this period are Bigsten and Kayizzi-Mugerwa
(1999), Reinikka and Collier (2001), and World Bank (1987).
3. These nutrition trends based on agricultural statistics are not consistent with the figures quoted
earlier for the very significant decline in income poverty during this period, as reported by household
budget surveys, and suggest that there may be underreporting of agricultural production in Uganda.
4. With a base of 1980 100, the consumer price index topped 150,000 by mid-1992, largely
attributable to the devastation caused by wartime inflation. Only the Democratic Republic of Congo
(then Zaire) had a worse experience (Donovan 1996).
5. The Food and Agriculture Organization’s FAOSTAT data were checked against national sources
and mistakes and errors corrected.
6. A World Bank paper reported that certain tea plantation companies with access to foreign
exchange at official rates found it privately profitable to purchase tea-picking machines, even though
hand picking was more cost-effective from the standpoint of the economy as a whole (quoted in
Donovan 1996).
7. See Nkonya and Kato (2001) for a description of agricultural input marketing.
8. Bigsten reports that the creation of a Mombasa-Kampala express cargo train service and
removal of the need to unload merchandise at the border for customs purposes cut transport time to
Kampala from two weeks to two days (Bigsten 2000).
9. There were instances, most notably in 1988, when the marketing board was unable to pay
farmers for new deliveries of coffee or to repay loans for previous purchases and when the government had to step in to provide funds to meet these obligations. Such subventions should, in principle,
be netted off against export tax receipts in any year. In the absence of data, however, we had to ignore
this offset.
10. We estimated a simple ordinary least squares regression (OLS) of the margin on time with a
dummy variable taking the value of 1 for the years before liberalization (up to and including 1990).
The coefficient on the dummy variable yields the excess marketing margin before 1990. However, the
coefficient on the dummy variable was not significant, and thus we have not counted any marketing
board distortion in the computation of the coffee NRA. The OLS regression gave the following results
(with t statistics in brackets): for the time trend 0.056 (1.77), preliberalization dummy 0.110 (0.11).
The overall adjusted R2 was only 0.064.
11. The Lint Marketing Board purchased from the ginners all lint and cotton seed produced, and
the ginners were compelled by law to sell all their production to the board.
12. This is confirmed by the results of a simple OLS regression of the margin on time with a
dummy variable taking the value of one for the years after liberalization (1995 and after). Although
the goodness-of-fit is low, the margin exhibits a slight (although significant) downward trend over
time and the dummy variable is positive and significant. The coefficient on time is 0.058 with a
Uganda
357
t value of 2.02, the coefficient on the liberalization dummy is 3.637 with a t value of 4.2, and the
adjusted R2 is 0.29.
13. Ugandan notifications to the General Agreement on Tariffs and Trade on state-trading enterprises give different dates regarding the origin and functions of the Produce Marketing Board. The
1963 notification stated that the main function of this board was to provide or create efficient marketing facilities for all controlled “minor” cash crops, defined as wheat, maize, beans, soya beans, tobacco,
sorghum, and millet. According to the 1970 notification, the Produce Marketing Board was established
by Act of Parliament (Laws of Uganda Act 37 of 1970) to give guaranteed minimum price to farmers,
to facilitate export sales. and to protect domestic producers and consumers by regulating both exports
and imports. The board was both importer and exporter of produce. Private traders were allowed to
export and import with the approval of the board. Board approval for exports depended on there
being no shortage of the produce in question.
14. Support for this procedure can be found in the comment that, in 1991, the wholesale price of
sugar charged by the two sugar factories was comparable to the price charged by importers of sugar
after tax and duty (World Bank 1993).
References
Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675–704.
Bigsten, A. 2000. “Globalisation and Income Inequality in Uganda.” Paper prepared for conference on
Poverty and Income Inequality in Developing Countries: A Policy Dialogue on the Effects of Globalisation. OECD Development Centre, Paris.
Bigsten, A., and S. Kayizzi-Mugerwa. 1999. Is Uganda an Emerging Economy: A Report for the OECD
Project “Emerging Africa. Göteborg: University of Göteborg.
Donovan, G. 1996. “Agriculture and Economic Reform in Sub-Saharan Africa.” AFTES Working Paper
18. World Bank, Washington, DC.
Government of Uganda, 2000. Plan for Modernisation of Agriculture: Eradicating Poverty in Uganda.
Kampala: Government of Uganda.
IMF (International Monetary Fund). 2005. “Uganda: Selected Issues and Statistical Appendix.” IMF
Country Report 05/172. IMF, Washington, DC.
Loxley, J. 1989. “The IMF, the World Bank, and Reconstruction in Uganda.” In Structural Adjustment in
Africa, ed. B. Campbell and J. Loxley. London: Macmillan Press.
Matthews, A., P. Claquin, and J. Opolot. 2007. “Distortions to Agricultural Incentives in Uganda.” Agricultural Distortions Working Paper 51. World Bank, Washington, DC.
Milner, C., O. Morrissey, and N. Rudaheranwa. 2001. “Policy and Non-Policy Barriers to Trade and
Implicit Taxation of Exports in Uganda.” In Globalisation and Trade: Implications for Marginalised
Economies, ed. O. Morrissey and I. Filatochev. London: Cass.
NRI/IITA (Natural Resources Institute and the International Institute of Tropical Agriculture,
Foodnet). 2002. “Transaction Cost Analysis: Final Report.” Prepared for the Plan for the Modernization of Agriculture. NRI and IITA, Kampala.
Ngategize, P., and G. Kayobya. 2001. “Agricultural Marketing.” In Agriculture in Uganda, vol. 1, ed. J.
Mukiibi. Kampala: Fountain Publishers/CTA/NARO.
Nkonya, E., and E. Kato. 2001. “Agricultural Input Marketing in Uganda.” International Food Policy
Research Institute, Kampala.
Opolot J., A. Wandera, and Y.A. Atiku. 2005. “Uganda Country Case Study on the Impact of Agricultural Trade and Related Reforms on Domestic Food Security.” Trade Reforms and Food Security.
Rome: Food and Agriculture Organization.
Reinikka, R., and P. Collier. 2001. Uganda’s Recovery: The Role of Farms, Firms and Government.
Washington, DC: World Bank.
358
Distortions to Agricultural Incentives in Africa
Sandri, D., E. Valenzuela, and K. Anderson. 2006. “Compendium of National Economic and Trade
Indicators by Region, 1960 to 2004.” Agricultural Distortions Research Project Working Paper 01.
World Bank, Washington. DC.
Shepherd, A., and S. Farolfi. 1999. “Export Crop Liberalization in Africa: A Review.” FAO Agricultural
Services Bulletin 135. Food and Agriculture Organization, Rome.
World Bank. 1987. Uganda: Country Economic Memorandum. Washington DC: World Bank.
———. 1993. “Uganda: Agriculture.” Country Study. World Bank, Washington, DC.
———. 2006. World Development Indicators. Washington, DC: World Bank.
Part V
WESTERN AFRICA
13
Cameroon
Ernest Bamou
and William A. Masters*
Cameroon is among the more prosperous countries in Africa, thanks to relatively
abundant agricultural land and offshore petroleum. These spurred an economic
boom from 1972, when the country was unified, until 1986. But for the next
decade, the economy declined, and it has enjoyed only a limited recovery since
1995. Social indicators also declined. Primary school enrollment rates fell from
nearly 100 percent in the 1980s to 62 percent in 1997, and the child mortality rate
worsened from 139 per 1,000 in 1990 to 151 per 1,000 in 1995, and the rate was
still 149 in 2006 (World Bank 2008). Over the past decade, poverty has remained
widespread. In 2001, 17 percent of the population had income of less than $1 dollar
a day in purchasing power parity terms, and 51 percent had income under $2 a
day (World Bank 2006).
Before the economic crisis of the late 1980s, Cameroon’s development strategy
efforts were managed through a series of five-year development plans. In these
plans, agriculture was described as the priority sector, and the government intervened massively in rural development, both directly, through the establishment of
state-owned agroindustries, rural corporations, and settlements, and indirectly,
through various support programs. Later reforms and the currency devaluation of
1994 improved performance by allowing more market incentives to play a role. In
this chapter, we use the methodology of Anderson et al. (2008) to quantify the
evolution of those distortions to farmer incentives, measuring the incidence of
* The authors are grateful for helpful comments from several Cameroonian colleagues and workshop
participants. Detailed data and estimates of distortions reported in this chapter can be found in
Bamou and Masters (2007).
361
362
Distortions to Agricultural Incentives in Africa
government policy on producers and consumers each year in Cameroon from
1961 to 2004. For each of the major activities, we compute nominal rates of assistance (NRAs), which are then aggregated into a variety of other indexes.
Before discussing the NRAs, the chapter provides a brief overview of agriculture’s role in the economy over the study period and a summary of the main agricultural policy incentives, interventions, and reforms. After describing the country’s growth performance over time, the chapter analyzes the estimates of
government distortions to agricultural incentives and then speculates on
prospects for future policy reform.
Agriculture’s Role in the Economy
Cameroon is a bilingual country. Its French- and English-speaking regions were
granted independence on January 1, 1960, and October 1, 1961, respectively, and
were united in 1972. At independence, about 85 percent of the people lived in
rural areas and relied principally on agriculture for their livelihoods. Since then,
the country has urbanized faster than most other African countries. By 2005, the
share of the population living in rural areas was estimated to have fallen below
50 percent, compared with an African average of 64 percent (FAOSTAT 2006).
As oil exports grew after 1977, the resulting Dutch disease turned incentives
against production of all other tradable products and contributed to stagnation in
both industry and agriculture. The boom in the oil and services sectors squeezed out
other activities, whose share of gross domestic product (GDP) sometimes fell below
one-third (Benjamin and Devarajan 1989; Blandford et al. 1995). Agriculture is
particularly vulnerable to the Dutch disease, since its output is largely tradable,
whereas the land and labor inputs are nontradable. There were also some shifts in
production within the sector, as described by Courade and Alary (1994), Janin
(1996), and Touna Mama (1996). Changes in input use were also important, particularly after the government phased out its subsidies for fertilizers, pesticides, and
herbicides in 1989–92 (Ndoye and Kaimowitz 2000; Sunderlin et al. 2000).
Main Agricultural Policy Incentives,
Interventions, and Reforms
The evolution of Cameroon’s agricultural policy may be divided into four phases.
The first phase runs from independence to the end of the 1960s and is marked by
a continuation of French and British colonial agricultural policies and institutions. The second, characterized by a proliferation of new agricultural interventions, covers the late 1960s to the late 1970s. A third phase, marked by attempts at
agricultural policy reform, runs from the late 1970s to the late 1980s; and the
Cameroon
363
fourth phase, dominated by agricultural policy liberalization, began around 1990
and continues into the 2000s.
Colonial agricultural policies and institutions
Cameroon was colonized first by the Germans (1894–1916) and later by the French
(1916–60) and British (1916–61), who partitioned the country between them.
Agriculture was characterized by a strong dualism between European-owned,
large-scale plantations and Cameroonian peasant smallholdings. Agricultural policies were closely linked to the politics of colonialism, as well as to the changing economic conditions in the colonies. Emphasis was placed exclusively on export crops.
At the start of colonial rule, development of the indigenous food sector
received little attention or was actively discouraged when it conflicted with the
labor needs of the large, European-owned plantations. The colonial administrations took numerous measures to stimulate the creation and expansion of plantations: large expanses of fertile land were appropriated from natives without compensation and given to planters; taxation, forced labor, and other methods were
used to ensure an abundant and cheap labor supply to the plantations; and a network of transportation and marketing facilities was developed to serve the plantation areas and link them to the coast (Ntangsi 1988).
Because large farms are relatively inefficient producers of most crops, colonial
powers eventually shifted their emphasis to peasant production, which provided
the basis for the rapid expansion of exports (Secrétariat Général du Gouvernement 1961). As peasant production expanded, an attempt was made to extend
roads and railways beyond the plantation areas into the major peasant-producing
areas.1 Several agricultural institutions were established to provide extension and
marketing services to farmers. On the French side, the most important of these
was the Secteurs de Modernisation, financed by Fonds d’Investissement pour le
Développement Economique. It provided a tight network of technical and croporiented extension services as well as seed production, pest control, and some
agroprocessing activities such as rice milling. The Société Africaine de Prévoyance
provided credit, and the Caisse de Stabilisation handled marketing. Specialized
research institutes were also established for cotton (Compagnie Française pour le
Développement des Fibres et Textiles), for cocoa and coffee (Institut des Fruits et
Agrumes), and for palm oil (Institut de Recherches sur les Huiles et Oléagineux). On
the British side, there was less emphasis on small-holders, where priority was
given to private, large-scale plantations operated by the Cameroon Development
Corporation, Elders and Fyffes Ltd., and others. A Department of Agriculture,
Cooperatives, and Community Development provided extension services and
research, and a marketing board marketed export crops.
364
Distortions to Agricultural Incentives in Africa
The 1960s
Substantial continuity in the colonial agricultural policies and institutional structure characterized the period immediately after independence. Until 1972, the
country was ruled under a federal system with two states, East and West
Cameroon. The Department of Agriculture and Rural Animation was created in
1964 under the federal Ministry of Planning to coordinate the agricultural development efforts of the two states. Implicit in the first five-year development plan
(1961–65) was an approach to agriculture referred to as the diffusion-modernization
model, which viewed peasant small-holders as the agents of agricultural development. Government intervention was limited to research, extension, provision of
inputs, and other services that would encourage adoption and progressive diffusion of farming innovations.
Signs of dissatisfaction with the outcome of the diffusion approach were noted
in the second development plan (1966–70), which clearly stated that, notwithstanding the satisfactory performance of the agricultural sector, growth in output
had come from increases in the area under cultivation and not from gains in yield.
This second plan envisaged experimentation with other forms of intervention
structures in agriculture and new forms of production, and in 1972 the unification of the country and creation of a new Ministry of Agriculture led to substantial modification in the colonial institutional structure.
The 1970s
As in most countries around the world, Cameroon in the late 1960s and early
1970s saw a movement toward greater intervention in agriculture, with the direct
involvement of government in functions hitherto carried out by the private sector,
such as distribution of agricultural inputs and marketing of food crops. In
Cameroon, increased government intervention and planning was concentrated on
the plantation sector, with almost complete neglect of small-holders. In fact, indirect taxation of peasants increased through the National Produce Marketing
Board, which had been created mainly for cocoa and coffee. This period also witnessed the multiplication of new intervention institutions and new forms of production as recommended by the second plan.2 By 1970, a total of 10 parastatal
development agencies had been created, and 14 more were formed under the third
plan during 1971–75. Under the fourth plan (1976–80), the government
attempted a further expansion of intervention, proposing some 20 new projects.
Most of these were never implemented, however, because foreign aid donors were
no longer willing to fund them.
The growth of Cameroon’s state-led agricultural interventions in the 1970s was
supported by donors for a variety of reasons. These agencies were to be run as
Cameroon
365
quasi-private enterprises, with administrative, technical, and financial autonomy
and therefore potential efficiency. In addition, most of the projects aimed to combine marketable output with basic farmer needs, an idea that fitted very well
within the basic-needs approach to rural development widely adopted by donors
and the international intellectual community during the early 1970s. But
Cameroon’s attempt to create a modern agricultural sector through this kind of
intervention proved to be very costly and had only a marginal impact on total
agricultural output. The proliferation of new institutions and structures was particularly counterproductive. Agencies were supervised by different government
ministries with little coordination of activities. Lines of responsibility often overlapped, agencies worked at cross purposes, and leaders were occupied in power
conflicts among themselves. The poor performance of the interventionist strategy
led to donor retreat and helped to awaken government doubts about the
approach.
The 1980s
Cameroon’s oil boom began in 1977, the same year farmers were offered a large
increase in real producer prices for cocoa, coffee, and cotton. Those gains were
quickly eroded by subsequent inflation, however, and on balance agricultural production was heavily burdened during the boom years.
During the boom, three distinct kinds of resource misallocation became
increasingly severe. The most fundamental were classic Dutch disease misallocations stemming from unsustainable price incentives, which limited investment in
small-holder agriculture. Before the oil boom, the sectoral balance had already
leaned heavily against agriculture as a whole, and within agriculture, resources
were concentrated in the relatively small estate sector, which produced no more
that 10 percent of total agricultural output. These biases worsened during the
boom, which made small-holder farming even less attractive and increased the
number of unskilled workers seeking nonfarm work.
A second kind of misallocation came about because of the unsustainable management structures within government institutions. Before the oil boom, an
extreme centralization of decision making had resulted in heavy red tape and
fragmentation of responsibilities in the bureaucracy and the extension service,
which led to poor policy implementation and misallocation of what little expenditure was targeted to small-holder agriculture during the boom.
A third kind of misallocation was underinvestment in new technology.
Although Cameroon did have a significant public agricultural research and development program, during the boom there were few incentives for technology
adoption, so yields for most crops stagnated or declined (MINAGRI 1980).
366
Distortions to Agricultural Incentives in Africa
All three kinds of problems were widely recognized in Cameroon during the oil
boom, but significant policy change did not take place until the boom ended and
the debt crisis of the mid-1980s made reform unavoidable.
Continuing liberalization since the late 1980s
Faced with a brutal fall in living standards after 1986, the government felt it had to
implement structural adjustment programs supported by international donors.
Sector-specific policy reforms in agriculture included both privatization and
liberalization. Those reforms targeted input production, transfer of technology
and know-how through research and development, marketing, training, and
information as well as sanitary and phytosanitary control. The reforms aimed to
guarantee food security, promote and diversify agricultural exports, and increase
income in the rural area.
The reforms that attracted the greatest attention involved liberalization of
product marketing. The Food Crop Development Authority and the National
Produce Marketing Board, which had controlled cocoa and coffee, were both
liquidated along with many other development agencies. Their withdrawal
improved average incentives, but for many products and regions very few private
traders were available, so marketing costs for these farmers actually rose, at least
temporarily. This deterioration of local marketing conditions inhibited farmers’
production, which in turn limited the speed and number of new entrants into
private trading to serve these markets.
Liberalization of international trade involved gradual abandonment of the
existing quantitative restrictions and the adoption of a simplified tax system. With
the adoption in 1994 of a regional fiscal reform program initiated at the subregional level through the Economic and Monetary Community for Central Africa,
tax rates on exports and imports of agricultural and food products were simplified, and average taxation rates were reduced (Bamou, Njinkeu, and Douya 2003).
On the input side, one particularly important set of changes were two
programs—one launched in 1987 with the assistance of the U.S. Agency for International Development and the other launched in 1988 with the support of the
European Development Fund—aimed at creating an effective private system for
importing and distributing fertilizers. But Ntsama (2000) found that importers
formed an oligopoly that enabled them to fix sale prices at an unusually high level
relative to cif (cost, insurance, and freight) values. In general, Ntsama argues that
the fertilizer programs were more concerned with serving existing importers than
with expanding the size of the market; for example, the programs did not offer a
credit mechanism to expand the number of farmers able to buy fertilizers.
Retrenchment in the public sector hit all kinds of services, including agricultural
research for new crop varieties and growing techniques. Despite the promising
Cameroon
367
results recorded by Cameroonian research programs and the desperate need for
yield-increasing technologies at that time, funding levels for these activities fell
significantly. In nominal terms, agricultural research institutes received CFAF
5.9 billion in fiscal1984/85 (of which 95 percent was from the state), whereas
between 1992 and 1994 they received only CFAF 5.7 billion of which only 58 percent was from the state, and 42 percent had to be sourced from external resources
(IRAD 1996).
The public national system for agricultural education was virtually abandoned,
with increasingly degraded facilities and weak staff. Its training programs were
unsuitable, current budgets and equipment insignificant, installations and equipment poor, and trainers demoralized and lacking regular work. Private educational institutions emerged that were better equipped with human and financial
resources, but they covered a limited range of skills and served only some regions
of the country (Matiké, Bidja, and Kapto 2001).
The national extension system was less affected by the cutbacks, although it did
face a slowing down of its activities. The National Agricultural Extension and
Research Program launched in 1990 by the government with the financial assistance of the World Bank made it possible to reinforce the extension services, but
the value of extension to farmers was constrained by the limited availability of
new technologies from research.
After the liquidation of the Cameroon Agricultural Bank (Crédit Agricole) in
1997, only a few parastatal or private agroindustrial enterprises were able to offer
farm production loans. Smaller and more remote farmers have no access at all to
formal credit. The emergence of financial intermediaries has been limited by high
risk and limited availability of collateral, so farmers must rely on loans from family members and local informal lenders. Some microfinance has been available
through donor-funded institutions, but these remain poorly distributed in the
country and sometimes lack credibility and professionalism, with no links
between them and commercial banks.3
A very important and ambitious area of reform concerns the use of forest land,
launched in 1994 with the approval of a new forestry law (Law 94-01). Reforms in
forest use are based on an effort to clarify the rules of the game and enforce them
with strong institutions that enjoy high-level political support; to draw a clear
separation of functions between public institutions and private entities and collaborative frameworks to enable collaboration among actors; to ensure that conservation of globally relevant biodiversity contributes to, rather than hinders,
local economies; and to use transparency and public information in the fight
against corruption and vested interests. As detailed by Kazianga and Masters
(2006), appropriate changes in property rights can have a powerful influence on
the adoption and effects of new technology in this context, particularly for cocoa,
which is typically planted in forest areas.
368
Distortions to Agricultural Incentives in Africa
Finally, despite the withdrawal of the government from most agricultural
activities, the semi-arid north part of country has continued to benefit ever since
independence from special government agricultural policies, such as food grants,
incentives for food crops production, and cotton extension and marketing services. This political support has typically been preserved over time, although with
varying effectiveness.
Growth Performance and Agricultural Output
Before and during its oil boom, Cameroon experienced rapid economic expansion. From 1973 to 1986, incomes grew by more than 7 percent per year (Bamou
and Masters 2007, appendix figure 1). Growth was led by an unsustainable expansion of the agricultural sector, followed by petroleum exports and government
borrowing (Benjamin and Devarajan 1989). Oil revenue shot from zero to 46 percent of exports between 1978 and 1982, and domestic absorption soared to
103 percent of GDP, driven by massive government spending (World Bank 2004).
Resource abundance allowed the government to pursue an inward-looking
import-substitution industrialization strategy, supported by a restrictive trade
policy and fiscal subsidies. This contributed to higher inflation (10 percent over
the period 1977–85), primarily resulting from price increases for nontradables
and higher real wages, as measured by rising unit labor costs and an appreciating
real exchange rate. The resulting deterioration in competitiveness led to a sharp
decline in non-oil exports (agriculture and manufactured goods), while imports
surged with domestic absorption, contributing to the deterioration of the trade
balance, which eventually led to the unsustainable indebtedness of the 1980s.
The accumulated consequences of these policy choices slowly unwound in the
long downturn from 1986 to 1993, and the country did not fully recover until after
the currency devaluation of 1994 and structural reforms of the second half of the
1990s. During the downturn, GDP contracted by 5 percent per year on average, and
by 1993 per capita income was almost half its 1986 level. Meanwhile, current public
spending rose from 11 percent to 19 percent of GDP while investment decreased
drastically, falling from 12.4 percent of GDP in 1986 to 3.5 percent in 1993. Investment rates were driven down in part by growth in external debt service payments.
The economic recovery started in 1994 and continued through 2005, thanks to
the combined efforts of authorities to implement more prudential economic policies aimed at restoring economic stability, trade and fiscal policies undertaken to
conform to Central African Economic and Monetary Community standards, and
the nominal 50 percent devaluation of the CFAF in January 1994. However, the
structural constraints of domestic demand and supply limited response to the
devaluation, and its incentive effects were short-lived.
Cameroon
369
Annual average real GDP growth of about 5 percent between 1995 and 2003
was spurred by the invigorated non-oil private sector, despite problems with the
energy sector that inhibited growth in general and that of the manufacturing
industry in particular. The spike of inflation that followed the CFAF devaluation
gradually subsided during this period, and public finance improved because of
prudential budgetary policy and changes in the tax administration. Non-oil government revenue rose by more than 4 percent of GDP, entirely eliminating the
budget deficit and generating surpluses starting in 2000. The external debt ratio
fell from 77 percent of GDP in 2000 to 44 percent in 2003.
Financial and fiscal recovery after 1995 has been reflected in rising living standards. For example, the poverty index decreased by about 13 percent between
1996 and 2001 (World Bank 2005), thanks largely to recovery of the agricultural
sector. Agriculture has registered remarkable growth but still has not brought
the country’s food production back to the level enjoyed in the early years of
independence.
On the trade side, Cameroon was a net exporter of agricultural products before
the crisis period. The 1994 devaluation had a significant effect that quickly eroded
as imports declined but then rose again in 1996, while exports fell. Increased civil
service salaries and real appreciation stimulated the increase in imports. A further
boom in imports was recorded with the start of construction on the ChadCameroon oil pipeline in 1998, while total exports dropped significantly with
enforcement of the a forestry law forbidding the export of whole logs for most
kinds of trees. On average, rice and cereal imports increased sharply in the 1990s
despite price hikes stemming from the devaluation.
Cameroon has been frequently cited as one of the few countries in SubSaharan Africa to have achieved satisfactory agricultural development. But past
growth was based on an early and unsustainable expansion of cropped area,
with very limited growth of land productivity. The area under cultivation grew
sharply in the 1960s and 1970s, particularly for coffee and groundnuts, but
growth then slowed markedly, with planting areas expanding only for cotton
and sorghum in the 1980s and only for roots and tubers in the 1990s. Despite a
significant growth in fertilizer use, growth in yields for the key crops has been
relatively low (Bamou and Masters 2007, appendix figures 3 and 4). The net
result, measured by per capita production of both food and nonfood crops, is
shown in figure 13.1. The numbers suggest that Cameroon has done little better
than the average for Sub-Saharan Africa since the late 1960s. These trends in
output are influenced by changes in resources, technology, and incomes that
shift the domestic supply and demand curves as well as by product pricing and
particularly the distortions to agricultural incentives imposed by government
policy.
370
Distortions to Agricultural Incentives in Africa
Figure 13.1. Per Capita Output of Food and Nonfood Farm Products,
Cameroon and All Sub-Saharan Africa, 1961–2005
200
index (1961 = 100)
175
150
125
100
19
6
19 1
63
19
6
19 5
67
19
6
19 9
7
19 1
73
19
7
19 5
77
19
7
19 9
8
19 1
83
19
8
19 5
8
19 7
8
19 9
9
19 1
93
19
9
19 5
97
19
9
20 9
0
20 1
03
20
05
75
year
Cameroon (nonfood)
Cameroon (food)
Sub-Saharan Africa (nonfood)
Sub-Saharan Africa (food)
Source: Compiled by the authors using FAOSTAT (2006).
Distortions to Agricultural Incentives
Farm policies in Cameroon have changed frequently since independence. The
resulting distortions are measured and analyzed in this section for the entire agricultural sector and for selected agricultural products, using the methodology presented in appendix A of this volume and in detail in Anderson et al. (2008). Our
key measure is the nominal rate of assistance, which compares domestic prices
with the border-price equivalents that would prevail in the absence of distortions.
The NRA is adjusted to take account of other taxes and subsidies.
Estimated distortions are computed for all main agricultural products. We
have data for four major exportable products (bananas, cocoa, coffee, and cotton),
and six basic food crops (cassava, maize, millet, plantain, sorghum, and other
roots and tubers). There is some international trade in the latter group of basic
food crops, both formally and informally, but the quantities traded and the
distances covered are too small to influence national prices significantly, so in our
analysis these crops are considered nontradables.
Three of our commodities (cocoa, coffee, and cotton) are marketed both as
primary products and as lightly processed. In these cases, we compute distortions
Cameroon
371
Figure 13.2. Composition of Farm Production at Distorted Prices,
Cameroon, 1966–2003
100
90
80
percent
70
60
50
40
30
20
10
19
66
19
68
19
70
19
72
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
0
year
noncovered
maize
banana
sorghum
millet
plantain
cotton
cocoa
cassava
coffee
other roots, tubers
Source: Compiled by the authors using FAOSTAT (2006).
to incentives for both farm production and off-farm processing. For coffee, the
primary product is exportable but the processed item is importable. Cocoa
is exportable. For cotton, the primary product is nontradable and only the
processed good is exported.
We do not compute distortion estimates for the nontradable basic food crops,
because the domestic markets for them are not subject to significant intervention
by the government. They play an important role when computing value-weighted
averages, though, because they account for the lion’s share of primary agricultural
production (figure 13.2).
Because the characteristics of agricultural development cannot be understood
from a sectoral view alone, the project’s methodology not only estimates the
effects of direct agricultural policy measures (including distortions in the foreign
exchange market) but also generates estimates of distortions in nonagricultural
sectors for comparative evaluation. The NRA for nonagricultural tradables is used
for comparison with that for agricultural tradables through the calculation of a
relative rate of assistance (RRA).
372
Distortions to Agricultural Incentives in Africa
Data sources and assumptions
Our analysis begins with the quantity data needed to compute weighted averages
of incentive effects, which also use farmgate agricultural prices, border prices,
exchange rates, and fiscal data on taxes and subsidies. Production and trade volumes for bananas, cassava, cocoa, coffee, cotton, maize, millet, plantain, sorghum,
and other roots and tubers are from FAOSTAT (2006). Prices at the farmgate
for most exportable products are from MINAGRI (1980) for 1961 to 1980;
MINEFI/DSCN (various years) for 1981 to 2003; and INS (2005) for 2004. Exceptions are detailed here: prices for bananas are derived from the assumptions used
by MINFOF (2006).4 Wholesale prices for lightly processed cocoa are fob (free on
board) prices minus the 17 percent cost margin estimated by CHOCOCAM, the
main cocoa-processing enterprise created in 1964. Wholesale prices for coffee are
from the Brulerie Moderne, created in 1955. Prices for cotton lint and seed cotton
are from Baffes (2007), extrapolated back to 1961 from his data for 1970. The
wholesale prices of cocoa and coffee are from the National Council of Coffee and
Cocoa. The farmgate prices, farm-to-market margins, and wholesale prices of
importable and nontradable products are estimated using data from the pricemonitoring department of the Cameroon’s official statistical agency. Additional
data on taxes and subsidies includes government payments to parastatal producers
from Varlet (2002), and consumer taxes from République du Cameroun (2006 and
earlier years). Import and export tariffs are from the subregional common external
tariffs established by the Central African Economic and Monetary Community.
Except for cotton, all fob (cif) prices are unit values, calculated from FAOSTAT
(2006), as the total value of the country’s exports (imports) divided by the volume
of exports (imports). Trade prices for cotton are compiled by Baffes (2007) from
the Cotlook A Index.
Official exchange rates are from IMF (various years). Distortions to the
exchange rate are computed relative to the parallel exchange rate, for which we use
black market rates from 1961 to 1993 as reported by Easterly (2006), whose principal source is International Currency Analysis (1993 and earlier years). To complete the series after 1993, we use year-to-year changes based on the changes
in real exchange rate misalignment estimated by Elbadawi (2006). Figure 13.3a
shows the evolution of the country’s real exchange rate and black market premium after 1980s, to show the Dutch disease period and subsequent recovery.
During the boom period, all of the exchange rate indexes appreciated significantly. During the economic decline after 1986, the real effective exchange rate
depreciated more slowly than the underlying equilibrium rate, leading to increasing misalignment and a sustained black market premium until the devaluation of
1994 sharply lowered the real exchange rate. Economic recovery after the devaluation was associated with renewed real appreciation and a return to significant
misalignment relative to Elbadawi’s estimate of the underlying equilibrium rate.
Figure 13.3. Foreign Exchange Rates, Cameroon
a. Real exchange rates, 1980–2004
160
150
140
130
index
120
110
100
90
80
70
60
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
year
real effective exchange rate
real exchange rate misalignment
equilibrium real exchange rate
black market premium
800
30
700
20
10
600
0
500
10
400
percent
20
300
30
200
40
100
50
19
6
19 1
63
19
6
19 5
67
19
6
19 9
7
19 1
73
19
7
19 5
77
19
7
19 9
8
19 1
83
19
8
19 5
87
19
8
19 9
9
19 1
93
19
9
19 5
97
19
9
20 9
0
20 1
03
20
05
CFA franc per U.S. dollar
b. Nominal exchange rates, 1961–2005
year
official rate (left scale)
parallel rate (left scale)
undistorted rate (left scale)
misalignment index (right scale)
Source: Compiled by the authors using official exchange rates from IFS 2006, black market parallel rates
from Easterly 2006, and real exchange rate indexes from Elbadawi 2006.
Note: The estimates of undistorted exchange rates are based on the methodology of Anderson et al. 2008.
374
Distortions to Agricultural Incentives in Africa
The influence of exchange rate changes on our distortion estimates is shown in
figure 13.3b, for the entire 1961–2004 period. On the left axis are nominal rates, in
terms of CFAF per U.S. dollar. All movements stem from fluctuations in the dollar
vis-à-vis the French franc and then the Euro, except for the jump in 1994. The
official rate shows significant overvaluation, with positive misalignment on the
right axis, through the 1960s and episodically in the 1970s. Then, as shown in figure 13.3a, there was some overvaluation until the 1994 devaluation, whose effects
were then gradually eroded by real appreciation. Following the methodology of
Anderson et al. (2008), we use an average between the official rate and the parallel
rate as our estimate of the undistorted exchange rate.
Results
The overall picture in agricultural distortions is clearly one of worsening price
distortions during the 1960s and 1970s, followed by reform and reversal during
the oil boom and ultimately by a period of sustained reforms after 1986.
Table 13.1 presents five-year averages of estimated distortions to farm-level
incentives for production of key crops affected by trade policy, along with a valueweighted average of the crops shown. During the 1960s, taxation of key crops was
substantial, on the order of 30–50 percent. These rates rose above 50 percent in
the late 1970s before declining with reforms and fluctuating in the 1980s and
1990s. They have remained at historically low levels since 2000. The bottom section of the table presents a weighted average for all products, with taxation worsening to a peak of 25 percent in the late 1970s, then settling to near zero after
2000. Dispersion in tax rates among products also declined, to a standard deviation of less than 10 percentage points.
Figure 13.4 provides annual value-weighted composite measures aggregated by
trading status for all primary agricultural products. This listing includes not only
the exportable primary products shown earlier (bananas, cocoa, coffee, and cotton), but also nontradable primary products (cassava, maize, millet, plantain,
sorghum, and cassava plus other roots and tubers). No importable primary products are included in this study. On average over these crops, the burden of taxation
facing production of exportables grew from about 15 percent in the early 1960s to
a peak of over 50 percent in the late 1970s, before shrinking in the late 1980s and
remaining well below 15 percent in most years since then. We find no comparable
distortion on nontradables, so the result is a significant antitrade and antiagricultural bias through the 1960s and 1970s but with both kinds of distortion being
much less significant over the past two decades.
The covered products account for half or more of the value of agricultural
production (at undistorted prices and excluding forestry and fisheries). We
Table 13.1. NRAs for Covered Farm Products, Cameroon, 1961–2004
(percent)
Product indicator
a,b
Exportables
Banana
Cocoa
Coffee
Cotton
Nontradablesa
Maize
Millet
Sorghum
Cassava
Other roots and tubers
Plantain
Total of covered productsa
Dispersion of covered productsb
Percent coverage (at undistorted prices)
1961–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
22.1
2.4
28.6
31.2
—
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.5
12.8
70
38.5
4.3
47.8
31.5
—
0.0
0.0
0.0
0.0
0.0
0.0
0.0
8.3
17.2
71
43.7
0.1
44.7
43.3
43.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
11.6
21.0
70
56.9
1.5
60.3
56.2
41.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25.1
28.8
61
40.5
1.2
37.7
43.7
29.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
19.7
20.6
61
9.1
0.9
1.9
15.0
18.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
5.1
16.7
56
14.1
3.1
32.7
15.8
4.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
4.6
15.3
47
14.1
4.5
34.1
8.7
14.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
4.5
12.4
48
5.7
1.1
12.2
2.0
1.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.1
7.1
48
Source: Data compiled by the authors.
Note: — no data are available.
a. Weighted averages, with weights based on the unassisted value of production.
b. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
375
376
Distortions to Agricultural Incentives in Africa
Figure 13.4. NRAs for Exportable and All Covered Farm
Products, Cameroon, 1961–2005
20
10
0
percent
10
20
30
40
50
60
70
03
00
20
97
20
94
19
91
19
88
19
85
19
82
19
79
19
73
76
19
19
70
67
19
19
64
19
19
19
61
80
year
exportables
total
Source: Data compiled by the authors.
Note: The total NRA can be above or below the exportable average because assistance to nontradables
and non-product-specific assistance are also included.
guesstimate that the NRA for noncovered farm products is zero, but a portion of
them are exportable and so are adversely affected by distortions in the exchange
rate. Table 13.2 presents estimated results that account for this effect, showing
how the overall total NRA for the agricultural sector is a little less negative than
for just covered products (see upper half of table 13.2)
Figure 13.5 and the lower half of table 13.2 capture policy effects on incentives
for production of tradables in primary agriculture as opposed to those in the nonfarm sector. These effects are summarized in the relative rate of assistance. Distortions have strongly favored nonfarm (including agroprocessing) activities, with an
average rate of subsidy above 20 percent for almost all of the 1960s, 1970s, and
1980s, until reforms after 1986 drew protection rates steadily down below their
initial 1960s level. Meanwhile, primary agriculture faced worsening average tax
rates from the early 1960s to 1977, when reforms were introduced for a brief
period and then reversed; not until 1985 did sustained reform begin. The net
result was a relative disincentive that worsened from about 25 percent in the early
Table 13.2. NRAs for Agriculture Relative to Nonagricultural Industries, Cameroon, 1961–2004
(percent)
Indicator
TNRA, covered products
NRA, noncovered products
NRA, all agricultural products
Non-product-specific assistance
NRA, total agriculturea
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAb
Memo item, ignoring exchange
rate distortions:
NRA, all agricultural products
RRAb
1961–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
3.5
0.6
3.3
0.4
2.3
11.4
18.3
22.0
8.3
1.3
6.3
0.3
6.0
24.7
24.5
38.5
11.6
0.0
8.1
0.6
7.5
27.0
25.5
41.9
25.1
0.5
15.1
0.7
14.4
36.9
30.0
51.0
19.7
0.4
12.2
0.8
11.4
27.3
31.1
43.6
5.1
0.3
3.3
0.9
2.4
5.2
21.3
23.1
4.6
0.9
1.5
0.3
1.1
3.7
19.9
18.8
4.5
1.4
1.5
0.2
1.3
4.2
17.3
19.0
1.1
0.3
0.3
0.2
0.1
0.5
11.7
13.4
1.9
20.0
5.0
34.6
7.4
41.9
13.9
50.1
10.9
42.6
2.1
21.7
2.1
21.0
2.8
24.2
0.4
14.7
Source: Data compiled by the authors.
Note: TNRA total NRA.
a. NRAs including product-specific input subsidies and non-product-specific assistance. Total of assistance to primary factors and intermediate inputs divided by total value of
primary agriculture production at undistorted prices (percent).
b. The RRA is defined as 100*[(100 NRAagt )兾(100 NRAnonagt ) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural and
nonagricultural sectors, respectively.
377
378
Distortions to Agricultural Incentives in Africa
Figure 13.5. NRAs for Agricultural and Nonagricultural
Tradables and the RRA, Cameroon, 1961–2004
60
40
percent
20
0
20
40
60
67
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
19
64
19
19
19
61
80
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the authors.
Note: For a definition of the RRA, see table 13.2, note b.
1960s to an RRA of 64 percent in 1977, before moving toward zero in recent
decades. Even in 2000–04, the RRA still was nontrivial at 13 percent, but that
was a huge improvement for farmers over the rates before the 1980s.
The policy mix of direct and indirect taxes through fiscal policy, marketing
boards, trade barriers, foreign exchange restrictions, and other development policies imposed a significant burden on farmers for the benefit of urban industry,
particularly in the 1970s. The exchange rate distortions do not appear to have had
a very significant effect on the NRAs and RRA, however (see final two rows of
table 13.2). These general results are in line with those of Njinkeu (1996), who
concludes that, “the performance of the exporting sectors [in Cameroon], for
example agriculture, may be partly explained by the implicit tax resulting from
protection of import-substituting sectors.” Reforms in the 1980s and 1990s
relieved that earlier burden on farmers and reduced support to processors, with,
on balance, some taxation of processors since the 1990s.
Underneath these aggregates are some pronounced differences in distortions
facing producers and consumers of particular products. Perhaps most important
are the effects on policy across crops in primary production, influencing the
Cameroon
379
welfare of farmers in different regions and the incentives for them to change cropping patterns. Cameroon’s broad pattern of heavy taxation against tree crops was
typical of African countries. McMillan and Masters (2003) explain this tendency
in terms of the time-consistency of alternative policies: in the absence of commitment mechanisms, governments may have a short-term incentive to set taxes so
that farmers earn only the marginal cost of harvesting their tree crops, even if the
taxes discourage tree replacement or maintenance investments and thus come at
the cost of future productivity. In Cameroon, the government’s incentive to tax
tree crops could be exacerbated by the relative political influence in general of the
forested southern areas as opposed to the drier north of the country. The northern region, in part because it often faced seasonal food insecurity, has benefited
from special agricultural policies since independence.
Summarizing our results, the significant increases in the taxation of primary
agriculture and the subsidization of nonagriculture from the early 1960s to the
late 1970s was successfully reversed during the 1980s. Those reforms are likely to
have significantly raised farm incomes and farmer incentives to increase production, relative to a continuation of past policies, accounting for at least some of the
upswing in agricultural yields and fertilizer use as well as for the economy-wide
growth in per capita incomes.
Prospects for Continued Agricultural
Policy Reforms
Through Cameroon’s Poverty Reduction and Growth Facility strategy of 2005–08,
underpinned by the Heavily Indebted Poor Countries (HIPC) Initiative,5 the
government of Cameroon once again considers agriculture and rural development to be a key means to raise economic growth rates and further reduce poverty
while maintaining macroeconomic stability and debt sustainability. At the same
time, movement on the stalled multilateral trade negotiations under the Doha
Agenda of the World Trade Organization (WTO), with their embedded market
access, export subsides, and domestic support challenges, could eventually lead to
greater liberalization of agricultural trade worldwide. Improving agricultural performance in such a context requires that more attention be given to programs for
enhancing agricultural productivity and competitiveness. Such programs should
lift supply constraints on the flow of agricultural products to the external market,
build complementarities between formal and informal domestic markets, and
continue reform of the institutions needed for a more productive agricultural
sector. These goals are central to the long-term development of agriculture in
Cameroon. Such a development approach depends mainly on improving governance and combating corruption, strengthening legal security for investment in
380
Distortions to Agricultural Incentives in Africa
general and agricultural investment in particular, and raising the quantity and
quality of infrastructures and key public services such as research and education.
Government actions in these areas will then make it more worthwhile for enterprises to invest in productive techniques and to diversify production in a sustainable manner.
The negative effect of corruption on the development of all sectors, including agriculture, is very well known. According to Transparency International,
Cameroon topped the list of the most corrupt countries in the world in 1998 and
1999. The country has done a bit better in recent years. However, it still holds a
dishonorable place in this shameful hit parade. Corruption is still endemic in the
country, and reducing corruption remains a very high priority. The government
has formed an ad hoc committee to coordinate the work of observers and groups
carrying out anticorruption work in every ministry and public service.
The development of basic infrastructure, notably inland and cross-border road
infrastructure, is crucial for the enhancement of agricultural production and the
promotion of agricultural exports. The development of the inland infrastructure
is expected to determine the competitiveness of subsistence agriculture, an important source of input for the agroindustrial sector, while the cross-border infrastructure will enhance the subregional agricultural competitiveness, which constitutes a platform for Cameroon’s involvement in the global agricultural market.
Improvements in agricultural productivity are needed to raise the payoffs from
new investment and thereby induce farmers to update their production techniques. A number of public goods are involved, calling for government intervention in areas such as quality standards, education and training, and access to
information and communication technologies. These public investments are
important not only for the productivity of existing activities but also for the emergence of new ones. Currently, exports in Cameroon are limited to only a few primary products, as shown by the Export Diversification Index of UNCTAD (2001)
and by Bonaglia and Fukasaku (2003).6 Improved incentives as well as appropriate
public investments will lead to new exports, but toward which agricultural products should export promotion be directed? Bamou and Bamou (1999) give an
insight to this question by identifying 19 non-oil, nontraditional competitive and
profitable exports, of which 4 are primary agriculture. Growth in these sectors has
been stifled by prices below world levels, and their emergence in the future could
be crucial to help agriculture play the historical role it has played elsewhere
throughout the world in inducing food security, increasing the savings rate, and
funding an emerging manufacturing sector.
The extent to which the agricultural sector is directly affected by developments
in world markets for agricultural products sheds light on a country’s interests
in future agricultural trade negotiations. Given that those negotiations could
Cameroon
381
provide an opportunity to examine key issues with important implications for
developing countries’ agricultural sectors in general and for that of Cameroon in
particular, Cameroon will need to focus its negotiating positions on preference
erosion, tariff escalation and tariff peaks, tariff rate quotas, export subsidies,
domestic subsidies, capacity building, state trading, special and differential treatment, and consideration of multifunctional character of agriculture, especially as
it relates to food security.
To improve market access for Cameroon’s agricultural products, the negotiations should strive to remove remaining nontariff barriers and reduce tariff peaks
and tariff escalation in developed-country markets. The country could offer to
reduce the level of its agricultural tariff binding and set it closer to the current
applied tariff level by locking in at the current level of commitment within the
Central African Economic and Monetary Community. Further liberalization of
nonagricultural tariffs could also reduce the bias against agricultural exports. This
would improve policy predictability and encourage investment and associated
spillover effects on efficiency and market access.
Overall, implementation of the Uruguay Round agreement on domestic
support to agriculture increased imbalances in the legitimate use of trade- and
incentive-distorting measures. The agreement legalized the use of these measures
by developed countries while developing countries were curtailing their use, and
it failed to properly define the nontrade concerns that should be taken into
account in implementing them (Shirotori 2000). Cameroon could perhaps eventually request reform of each of these dimensions, so that there are new incentives
for deeper liberalization in the input sectors and for enhanced reliance on market
mechanisms to promote crop development.
Notes
1. To link the important cocoa economy of South-Central Cameroon to the coast, the railway was
extended from Douala to Yaoundé and from Otélé to Mbalmayo.
2. The second plan had recommended the expansion of the estate sector (either privately or publicly owned), rural settlement projects to move the population from densely populated to sparsely
populated areas, specialized crop development corporations charged with organizing and supervising
the production of specific crops grown by small farmers, and integrated rural development projects
stimulating production as well as providing social services.
3. The World Bank participated in funding the Investment Fund for Agricultural and Community
Micro-Projects, which had 160 branches and 31,000 participants. The project funded 3,000 projects
for a total of CFAF 2 million during the period 1989–98. Canada and France provided support for the
Fund for Rural Savings and Self-Managed Credits project.
4. Because enterprises were exporting directly, MINFOF (2006) estimated the farmgate prices as
the difference between the wholesale prices for primary products and the cost of transportation, storage, and other services (the markup on farmgate prices). The wholesale prices for primary products
are equal to fob prices at local currency.
382
Distortions to Agricultural Incentives in Africa
5. On May 1, 2006, Cameroon reached its completion point under the Enhanced Heavily Indebted
Poor Countries (HIPC) Initiative, becoming the 19th country to reach that point. Debt relief to
Cameroon under HIPC is expected to be approximately $1.3 billion in 1999 net present value terms,
equivalent to a 27 percent net present value reduction of Cameroon’s debt after traditional debt relief.
This relief will reduce Cameroon’s future debt service payments by about $4.9 billion in nominal
terms. See IMF press release 06/85 dated September 7, 2006. http://www.imf.org/external/np/
sec/pr/2006/pr0685.htm.
6. A higher value of the Export Diversification Index (EDI) and primary commodities’ share of
total exports (PCS) indicates a greater degree of export concentration. UNCTAD (2001) shows that in
2001, Cameroon was the most concentrated country in its trade, with EDI 0.90, even compared with
some poorer countries such as Senegal (EDI 0.77) or Mozambique (EDI 0.83). In like manner,
Bonaglia and Fukasaku (2003) show that in 2000, despite the slight decrease of the PCS of Cameroon
(from 0.99 between 1966 and 1970 to 0.97 between 1996 and 2000), it was still higher compared with
that of other middle-income countries (0.86 for Botswana and 0.88 for Ghana and Kenya between
1996 and 2000).
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Ntsama, E. 2000. “Etude Relative à l’Evaluation et à la Révision du Système de Financement du PRSSE.”
Rapport définitif. MINEFI, Yaoundé.
République du Cameroun. 2006. Loi des Finances 2006: Rapport Economique et Financier Exercice 2005.
Yaoundé.
Secrétariat Général du Gouvernement. 1961. “La République du Cameroun.” Notes et Etudes Documentaires. Janvier, Paris.
Shirotori, M. 2000. “Notes on the Implementation of the Agreement on Agriculture.” In Positive
Agenda and Future Trade Negotiations. Geneva: UNCTAD.
Sunderlin, W. D., O. Ndoye, H. Bikié, N. Laporte, B. Mertens, and J. Pokam. 2000. “Economic Crisis,
Small-Scale Agriculture, and Forest Cover Change in Southern Cameroon.” Environmental Conservation 27 (3): 284–90.
Touna Mama. 1996. Crise Économique et Politique de Déréglementation au Cameroun. Paris: L’Harmattan.
UNCTAD (United Nations Conference on Trade and Development). 2001. “Export Diversification
Index.” UNCTAD Handbook of Statistics. Geneva: UNCTAD.
Varlet, F. 2002. “Institutions Publiques et Croissance Agricole au Cameroun.” Thèse de Doctorat, Ecole
Nationale Supérieure Agronomique de Montpellier, France.
World Bank. 2004. “Republic of Cameroon Development Review: A New Resolve to Sustain Reforms
for Inclusive Growth.” Report 29268-CM. Poverty Reduction and Economic Management Sector
Unit, Africa Region, World Bank, Washington, DC.
———. 2008. World Development Indicators 2008. Washington, DC: World Bank. http://devdata
.worldbank.org/data-query/.
14
Côte d’Ivoire
Philip Abbott*
After independence in 1960, the economy of Côte d’Ivoire was heralded as one of
the success stories of Sub-Saharan Africa. Gross domestic product (GDP) grew at
an annual average of 8.1 percent from 1960 to 1979, as per capita GDP increased
in real terms from $595 to $1,114.1 This economic boom was led by increasing
agricultural exports, principally cocoa and coffee. In 1961, these two exports
equaled $112 million, or 51 percent of total exports, with agricultural exports
accounting for 61 percent of total exports. By the late 1970s, cocoa and coffee
exports amounted to $1.5 billion, and were then 53 percent of total exports, with
agricultural exports still accounting for 61 percent of total exports (FAOSTAT
2006; World Bank 2006b). Côte d’Ivoire has emerged as the world’s largest cocoa
exporter, now accounting for as much as 40 percent of world cocoa trade. The
country was also Africa’s largest coffee exporter during the 1960s and 1970s,
although by 2004 coffee exports had fallen to only 4 percent of agricultural
exports, while cocoa had increased to more than 70 percent; Total agricultural
exports still account for 43 percent of total merchandise exports.
The agriculture-based economic performance of Côte d’Ivoire was stronger
than any found elsewhere in Africa, and several economists and political scientists
have sought to explain the unique features of agricultural policy that gave rise to it
(Boone 1995; Hecht 1983; Widner 1993; Woods 2003, 2004). Those studies generally focus on policy for the cocoa and coffee sectors. This study shares that focus
but also considers another agricultural export success, cotton, and Côte d’Ivoire’s
most important agricultural import, rice. Also examined briefly are wheat, which
* The author is grateful to Jean Luc Agkpo, BNEDT, Abidjan, Côte d’Ivoire, and to Marianne Kurzweil,
Ernesto Valenzuela, and John Baffes at the World Bank for input and assistance in collecting national
data and to Kym Anderson and Will Masters for helpful comments. Detailed data and estimates of
distortions reported in this chapter can be found in Abbott (2007).
385
386
Distortions to Agricultural Incentives in Africa
is imported but not produced in Côte d’Ivoire, and coarse grains, roots, and
tubers, which are traded only on a small scale, mainly with neighboring countries
rather than the broader international market.
Despite Côte d’Ivoire’s relative success, like most developing countries it
engaged in structural adjustment reforms beginning in the early 1980s as economic recession set in, and export revenues failed to keep pace with imports. Côte
d’Ivoire is part of the West African currency union, sharing its currency, the CFA
franc (CFAF), with neighboring French West African countries and receiving support from the French central bank. Devaluation was (politically) hard to implement and did not occur until 1994, when the CFA franc was devalued by 50 percent. Agricultural policy was managed by parastatal monopolies, such as
CAISTAB (Caisse de stabilisation) in the cases of cocoa and coffee and the CIDT
(Compagnie Ivoirienne pour le développement des fibres textiles) for cotton, using
institutional frameworks derived from French colonial heritage. Privatization of
those parastatals was an objective of international donors but was slow in coming
and sporadic in Côte d’Ivoire, where it was resisted by the government. CAISTAB
continued to regulate cocoa and coffee trade until 2000, and the government’s
majority interest in cotton companies created from the CIDT was not divested
until 2002 (IMF 2002). Trade liberalization, a part of the structural adjustment
program, was implemented in fits and starts, with periods when tariffs were
reduced, followed by periods when they rose again. Quantitative restrictions have
accompanied parastatal management of agricultural trade and may still remain in
place for rice through “voluntary” administered prices (OECD 2006).
Côte d’Ivoire’s agricultural economy has focused on small-holder farming and
export crops. Those farmers and their exports were heavily taxed. Despite structural adjustment reforms, which included the reduction of agricultural export
taxes as one of the goals, taxation of cocoa and coffee exports (especially cocoa)
remains a hallmark of Ivorian policy. Those taxes were reduced briefly around the
time CAISTAB was privatized but were subsequently raised, and export tax revenue in 2003 amounted to nearly a quarter of government revenue. Import tariff
revenue is also important, at 30 percent of government revenue in 2003 (World
Bank 2006b).
Policy has usually discouraged food crop production, against the wishes of
farmers. Rice and wheat are the predominant cereal imports, with coarse grains,
like roots and tubers, behaving like nontradables. Rice imports surged during the
commodity boom of the late 1970s, were generally flat during the recession until
1994 (apart from a brief surge in the mid-1980s), and increased again after 1994.
The mid-1980s import surge gave rise to a policy focus on self-sufficiency, which
briefly slowed but never eliminated imports. Wheat imports emerged in the late
1970s as well and have also increased since 1994.
Côte d’Ivoire
387
The recent need for tax revenue from exports derives from political events that
have also negatively affected economic performance. While the devaluation in
1994 initially led to a resurgence in economic growth, a coup d’état in 1999 and
continuing civil conflict have hampered the economy; and from 2002 until 2007
conflict divided the country, with rebel troops holding the northern part of
the country. Cocoa and coffee are grown in the south, so the effects of the civil war
have been seen mostly in the resumption of export taxes and increased trader
margins on these key exports. Crops predominantly grown in the north, such as
cotton and maize, have been more severely affected, and smuggling to neighboring countries has affected both management of the cotton sector, another successful agricultural export at one time, as well as collection of data on conditions in
the Ivorian agricultural economy. The need for rice and wheat imports must result
in part because they are mostly produced and consumed in the north and not
delivered to the urban areas of the south where there is a need for food. In its
assessment of the outlook for the Ivorian economy more generally, the Organisation for Economic Co-operations Development (OECD 2006) cited resolution of
the civil conflict as the key to future economic performance.
The mystery of Côte d’Ivoire’s agricultural policy and economic performance
is the continuing success of the cocoa sector despite heavy taxation. Hecht (1983,
p. 26) wrote, “the government has consistently followed a set of policies designed
to encourage expansion of cocoa and coffee production, while at the same time
taxing small-holders heavily for capital accumulation and investment elsewhere in
the economy. Other countries . . . have also tried to finance public expenditure in
a similar fashion, but have ended up by either crippling or retarding this sector.
The Ivory Coast, on the other hand, has successfully nurtured this golden goose,
and exploited its precious eggs—without killing the animal.” This quote remains
remarkably relevant. Cocoa export volume grew steadily since 1960, with a
plateau from 1987 until 1994, and another plateau after 1999. Throughout this
period there were never sustained increases in farmgate prices. Attempts to estimate supply response for cocoa are plagued by data showing increases in production even as prices fell, particularly in international markets (Maizels, Bacon, and
Mavrotas 1997). CAISTAB stabilized pricing (somewhat), so farmers did not feel
the full effect of drops in international commodity prices, did not see nominal
price declines, and, because of currency stability, did not experience the erratic
pricing seen in some neighboring cocoa-exporting countries, such as Ghana
(Brooks, Croppenstedt, and Aggrey-Fynn 2007). Analysts attribute increasing
production in the face of low and sometimes falling real prices to liberal immigration and land tenure policies (Boone 1995; Widner 1993; Woods 2003, 2004). This
theory goes a long way toward explaining growth until 1994, which resulted
largely from area expansion, but it cannot account for the increasing yields and
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Distortions to Agricultural Incentives in Africa
constant area planted since then, as well as the change since 1993 in attitudes and
policy toward immigrants that lay behind the civil conflict of the early 2000s.
Measures of distortions to agricultural incentives reflect this continuing taxation of agricultural exports and in the case of rice, administered pricing. While
structural adjustment reforms in Côte d’Ivoire have aimed at, and at times succeeded in, liberalizing trade, the civil conflict since 1999 has driven the government’s desire for tax revenue from agriculture and continued limitations on
imports. Stabilization in the face of volatile international prices, effects of the
recent civil conflict, and earlier structural adjustment reforms earlier, are all evident in the extent of taxation of export agriculture in Côte d’Ivoire.
The remainder of the chapter provides more detail on Côte d’Ivoire’s economic
performance, followed by an exploration of the role of agriculture in the economy, and particularly in exports. A brief historical overview of agricultural policy
shows the colonial roots of policy institutions and the importance of structural
adjustment reforms. Policies and performance for the four key agricultural
sectors—cocoa, coffee, cotton, and cereals— are then examined, and data on
prices and performance are used to quantify the extent of distortions to agricultural incentives in Côte d’Ivoire. The concluding section summarizes what has
been learned about both the extent of distortions and the political economy factors determining those distortions.
Economic and Trade Performance
In 2005, real GDP per capita in Côte d’Ivoire stood at $563 (in constant 2000 U.S.
dollars). This low income level reflected an inability to sustain the economic success that prevailed during the first 20 years after independence, from 1960 to 1979,
and was also attributable to the costs of continuing civil conflict.2 Annual GDP
growth averaged 8.1 percent from 1960 until 1979 and reached nearly 10 percent
during the commodity boom from 1975 to 1979, before declining to, and remaining at, a level below that found in 1960. A recession driven by low export earnings
and an overextended public debt burden ensued from 1979 and led to persistent
negative economic growth until 1994. The devaluation of the CFA franc in 1994
briefly spurred economic growth, which averaged 6.3 percent annually until 1999,
but stagnation returned with the civil conflict, and annual economic growth was
negative in 1999–2004, averaging 0.55 percent.
Trade, especially agricultural trade, has been important to the evolution of the
Ivorian economy. In 2005, exports represented 50 percent of GDP, and imports
equaled 40 percent of GDP. At peak GDP in 1978, exports and imports were each
already 37 percent of GDP. Just before the devaluation of 1994, exports had
declined to 29 percent of GDP, whereas imports were only 26 percent of GDP at
Côte d’Ivoire
389
the overvalued exchange rate (World Bank 2006b). Immediately after the devaluation, exports rose to 40 percent of GDP, while imports averaged about one-third
of GDP.
Trade taxes have been an important source of revenue for the government.
Export taxes accounted for 24 percent of revenue in 2003, while customs duties
contributed 30 percent of revenue. Export taxes were only 12 percent of revenue
in 1998, a consequence of structural adjustment reforms, while customs duties
have remained steady at about one-third of revenue. Since the completion of the
Uruguay Round under the General Agreement on Tariffs and Trade, Côte d’Ivoire
has maintained a relatively uniform tariff schedule, with a typical ad valorem rate
of 20 percent (with some exceptions). A value added tax (VAT), now at 18 percent,
also applies to imports as well as to domestically produced goods that are locally
consumed (World Bank 2006a).
Trade and economic growth have both been influenced by exchange rate policy. Côte d’Ivoire’s currency is the West African CFA franc, which is also used in
Benin, Burkina Faso, Mali, Niger, Senegal, and Togo. The Banque Centrale des
Etats de l’Afrique de l’Ouest was created in 1946 by France to support its colonies
and remained in force after independence. This currency continued to be supported and managed by the French central bank, which also attempted to impose
monetary and fiscal disciplines on the governments of participating countries
(van de Walle 1991). When borrowing evaded those disciplines and the currency
became overvalued, the French central bank was required to inject considerable
capital into the West African central bank and thereby into the economy of Côte
d’Ivoire. In the early period, from 1960 to 1979, this system created a stable foreign
currency, avoiding hyperinflation or large black market premiums, in contrast to
many experiences elsewhere in Africa.
Easterly (2006) has calculated a parallel (black market) exchange rate for the
CFA franc, which shows only very small back market premiums from 1960 to
1970 and again in the late 1970s to early 1980s, and no premiums in other years.
Given the capital inflows from France and the extent of convertibility of this
currency, it is not surprising that black market premiums were never large. But
the real exchange rate (REER) estimated by the International Monetary Fund,
based on differential inflation, shows an overvaluation during the recession of
the 1980s and the need for the devaluation of 1994, which brought this measure
of the real exchange rate and the official rate back into alignment.3 This index
suggests overvaluation of 54 percent in 1980, and of more than 40 percent from
1987 until the devaluation in 1994. The Fund’s REER is used as this study’s
proxy for a parallel market exchange rate: as discussed later, it shows a bias
against agricultural exports in favor of food imports only during this protracted
recession.
390
Distortions to Agricultural Incentives in Africa
Agriculture’s Role in the Economy
Côte d’Ivoire has remained a largely rural society: 82 percent of the population
was rural in 1960, 64 percent remained rural in 1979, and still 55 percent in 2005
(World Bank 2006b). As of 2003, value added from agriculture contributed nearly
one-quarter of GDP, compared with nearly half of GDP in 1960. At $1,048 per
worker, agricultural value added was 2.7 times greater than that found elsewhere
in Sub-Saharan Africa (FAO 2003). These data reflect some industrialization and
urbanization, but as the trade statistics demonstrate, agricultural exports remain
critically important to this economy. Although coffee has declined in importance,
cocoa remains Côte d’Ivoire’s key export, and a number of other tropical products
(such as bananas and pineapples) and cotton are also important exports as well.
Nevertheless, in many respects, Côte d’Ivoire is a classic example of a developing
economy heavily dependent on a single commodity export. Cognizant of this fact,
the government has on several occasions pursued diversification strategies but to
little effect.
Côte d’Ivoire’s 32 million hectares can be divided into two distinct parts—the
tropical rain forests of the south and the savannahs of the north. Cocoa and coffee
as well as tropical fruits and vegetables are grown in the southern region, while cotton, maize, and cassava are grown in the north. Rice is mostly grown in the north,
although some is grown in the forest areas of the southwest. Only 7 percent of the
rice area is irrigated, and upland varieties make up most of the rice grown
(WARDA 2004; FAO 2003). Forests accounted for 31 percent of area in 1995 but
only 22 percent in 2002, reflecting serious deforestation. Traditional cocoa planting
techniques coexist with rain forest, but modern techniques using fertilizer eliminate the forest cover. This deforestation reflects the limitations on expanding the
area planted to cocoa and coffee and on shifting to new techniques in some areas
(Ahmed, Kazianga, and Sanders 2005). Land nevertheless remains relatively abundant: cultivable land represents 75 percent of total area, of which actually cultivated
land is only 30 percent. Only 4 percent of area in Côte d’Ivoire is devoted to cereal
production, while pasture accounts for more than 40 percent of area (FAO 2003).
The product composition of agricultural output is summarized in figure 14.1,
illustrating the importance not only of the export crops (especially cocoa and coffee) but also of nontraded food staples (especially cassava and yams).
Small-scale farmers, who on average own four hectares, are the rule for most
agricultural activities, including cocoa, coffee, and cotton production. More than
500,000 small-holders plant cocoa in Côte d’Ivoire. Large plantations are found
mainly for bananas, rubber, palm oil, and pineapple and account for only a small
share of agricultural production (FAO 2003).
While cocoa and coffee, including processed product exports, contributed on
average more than 70 percent of agricultural exports during the late 1990s, other
Côte d’Ivoire
391
Figure 14.1. Share of Agricultural Production at Undistorted
Domestic Prices, Côte d’Ivoire, 1961–2005
100
90
80
percent
70
60
50
40
30
20
10
19
6
19 1
63
19
6
19 5
6
19 7
6
19 9
7
19 1
7
19 3
7
19 5
7
19 7
7
19 9
8
19 1
8
19 3
85
19
8
19 7
8
19 9
91
19
9
19 3
9
19 5
9
19 7
9
20 9
01
20
0
20 3
05
0
year
noncovered
rice
yam
cotton
plantain
coffee
cassava
cocoa
Source: Data compiled by the author.
agricultural exports matter as well. Cotton averaged nearly 7 percent of agricultural exports, and other important exports included pineapple (2.1 percent),
bananas (3.0 percent), palm oil (2.7 percent), rubber (3.5 percent) and logs (0.6
percent) (FAOSTAT 2006). Canned fish also accounted for nearly 6 percent of
exports. Shares of food imports in the late 1990s were 20 percent for rice, 29 percent for fish, 8.8 percent for dairy products, 9.5 percent for wheat, 3.7 percent for
sugar, and 3.8 percent for tobacco (FAO 2003).
Because Côte d’Ivoire is dependent on commodity exports, performance is
strongly determined by international prices, which have been quite volatile since
1960.4 These nominal prices show a pattern of correlation between international
commodity prices, and key periods when high and low prices have occurred. High
prices prevailed for all these commodities during the mid- to late 1970s, with
declines particularly evident for cocoa and coffee starting in 1979. A second common peak occurs around 1995, and low prices for all these commodities are found
around 2000. The magnitude of these variations is also striking. The export price
for a metric ton of cocoa reached nearly $3,800 before the decline (in 1977), fell
below $1,000 in 2000, increased because of civil conflict in 2002,5 and was only
392
Distortions to Agricultural Incentives in Africa
about $1,500 in 2007. The price for a metric ton of coffee reached nearly $5,000 in
1976 but then fell to less than $1,000 in 1991 and from 2000 to 2003. By comparison, rice, maize, and cotton prices seem less volatile, but these prices also reveal
considerable variability. There are some commodity-specific trends, but strong
correlation among all the international commodity prices. Côte d’Ivoire’s export
revenues have been dependent on some of the most volatile commodity prices,
and these international price variations are much larger than domestic distortions. Despite the government’s efforts to stabilize prices, domestic prices of key
exports have seen some effects from these trends. This is more evident in recent
years because structural adjustment reforms have eliminated mechanisms to stabilize domestic prices, but private traders have absorbed some price instability.
History of Agricultural Policy Incentives,
Interventions, and Reforms
Various analysts have offered different period delineations of Côte d’Ivoire’s economic and political events, depending on their objectives. In particular, the recession and structural adjustment period has been divided by some, to account for
ups and downs in liberalization efforts and the end of the presidency of Felix
Houphouet-Boigny. Political events have influenced the evolution of agricultural
policy and helped to define these periods. For the purposes of this chapter’s focus
on distortions to agricultural incentives, it will be sufficient to follow the divisions
used to this point, namely, 1961–1979 (initial economic success after independence), 1980–1993 (recession and structural adjustment), 1994–1998 (postdevaluation reforms and resurgence), and 1999–2005 (civil conflict and economic
decline). For background, however, this chapter begins with the period before
independence.
Colonial heritage
The institutional development behind agricultural policy, and indeed all policy
evolution, was conditioned by Côte d’Ivoire’s experience as a French colony. Côte
d’Ivoire officially became a French colony in 1893, became an autonomous republic within the French community in 1958, and achieved full independence in
August 1960. As a colony, it was a source of agricultural exports to Europe, with
cocoa and coffee plantations being established alongside small-holder farms
beginning in the 1920s (FAO 2003). Cotton production was also developed from
about the same time. According to Bassett (1988, p. 269), “the first period
(1910–22) saw the establishment of the conditions for commodity production
through the development of transportation networks, the activities of merchant
houses and the imposition of export-oriented cotton production.”
Côte d’Ivoire
393
Establishment of the infrastructure and institutional structures during this
period characterized Ivorian agriculture and policy afterward. It is still the case
that transportation costs within Côte d’Ivoire are lower than elsewhere in
Africa, largely because of the roads and railroad built by the French. And the
cotton parastatal, the CIDT, was fashioned after the French public company
Compagnie Française pour le Développement des Fibres Textiles. Parastatals dominated agricultural export policy institutions until well after the 1994 devaluation and privatization demands of structural adjustment reforms. Even though
the colonial era included periods of forced labor and coercion and French settlers had established plantations for cocoa and coffee in the south that required
significant, sometimes forced, labor from other areas of Côte d’Ivoire, the structure of small-holder agriculture now found in cocoa, coffee, and cotton had
been established by the time of independence in 1960 (Bassett 1988). The focus
of policy on export crops at the expense of food production also emanated from
the colonial period.
Success following independence, 1961–79
From independence until 1993, Houphouet-Boigny served as president, and the
first multiparty elections did not occur until 1990. Several analysts (Boone 1995;
Hecht 1983; Widner 1993; Woods 2003, 2004) debate the importance of having a
president with rural roots who continued to own agricultural assets, but it is
clear that Houphouet-Boigny pursued policies to support Ivorian export agriculture, while managing to extract significant export taxes from the sector. Hecht
(1983) in particular notes the success of this regime, contrasting it with other
African economies where agricultural taxation ultimately harmed export revenue generation.
While some authors claim that the regime was responsible for high farmgate
prices, those prices as a share of international prices for cocoa, coffee, and cotton
were only somewhat higher, at 40–55 percent, during the 1960s and 1970s than
they were during the recession period of the 1980s or in the early 2000s. International price levels probably played a bigger role in determining these shares than
did domestic or trade policy. Administered prices for cocoa never fell in nominal
terms, and the stability of the CFA franc meant that hyperinflation never eroded
the value of those administered prices.
The growth in exports, particularly of cocoa, is attributed to available rain
forest and supportive immigration and land tenure policies that allowed immigrants from elsewhere in West Africa not only to provide labor but also to “own”
their own farms with the knowledge that they could maintain control of their land
as long as they were productive. Ruf (1995) and Lopéz (1998) argue that this
394
Distortions to Agricultural Incentives in Africa
regime exploited a forest rent that led not only to area expansion as the engine of
growth but also to pioneering new areas rather than replanting older trees to
maintain yields. The opportunities offered to immigrants on small-holder cocoa
farms, particularly relative to returns to subsistence crops in their home countries,
therefore played a key role in explaining the country’s agricultural success. Bassett
(1998) also notes the importance of the technical package for cotton, which gave
rise to its initial success in the mid-1960s, and which came from the French
through the CIDT. Several authors note that during this period, parastatals not
only administered markets but also provided extension and research services to
farmers as well as organizing input supplies.
French and other African colonial agricultural institutions are often contrasted, especially for cocoa. Boone (1995, p. 447) in particular describes Ivorian
parastatal management as “relatively laissez faire.” Although the parastatal
(CAISTAB) set administered prices for cocoa and coffee and provided public
goods (extension services, inputs), private agents were allowed to conduct trade,
and the state intervened little in the production process itself. Ivorian management of cocoa and coffee can be contrasted not only with the approaches in
Ghana and other important cocoa-producing countries, where state agents
bought and sold all cocoa and influenced production techniques, but also with its
own management of cotton by the CIDT, which is similar to public management
found elsewhere. This greater state intervention was probably necessitated by the
agronomy of cotton, which requires much more intensive use of inputs and more
sophisticated technology than does traditional cocoa production. The need for
fewer inputs permitted the laissez-faire approach to cocoa, which may have
become less successful as access to new rainforest diminished and more intensive
practices as well as methods to avoid disease became necessary.
Recession and structural adjustment, 1980–93
During the structural adjustment era, the country experienced significant variation in the extent of protection and in liberalization, driven in part by variations
in export earnings (Kouassy, Pegatienan, and Ngaladjo 2004). Tariffs reached an
average of 32 percent by 1989, fell to 24 percent by 1993, and following the 1994
devaluation were reduced to an average of 20 percent, similar to current levels
(FAO 2003). Despite these and other trade and macroeconomic reforms, significant changes to agricultural policy were a long time in coming. Parastatals persisted despite international donors’ insistence on privatization, until 1995 in the
case of rice, 1998 (really 2002) in the case of cotton,6 and 2000 in the cases of
cocoa and coffee. Effective protection had significantly increased in the early
1980s, so in 1984 tariff reforms were instituted to foster industrialization
Côte d’Ivoire
395
(FAO 2003). Variations in world prices, especially for cocoa and coffee, and financial difficulties following from the liberalization, led to a reversal of policies in the
late 1980s and then to a return to liberalization in the early 1990s, which was
consolidated by the devaluation of 1994 (Kouassy, Pegatienan, and Ngaladjo
2004). Parastatals and the government implemented quantitative restrictions on
trade during this period as well.
Rice self-sufficiency was maintained through a parastatal (Caisse générale de
péréquation des prix) created during this period, which managed the market, provided extension services, and invested in irrigation. Rice prices even exceeded
border prices by more than 50 percent for a few years in the mid-1980s (when
world prices were very low). This, and quantitative restrictions on wheat
imports, were the only significant deviations in policy focus away from export
crops. Investments in sectors to diversify exports from cocoa and coffee had been
made in earlier periods, including in the late 1970s, and were made in later periods, as stabilization revenues for cocoa and coffee were instead spent on public
investments in other sectors. Few of these diversification projects succeeded,
however.
The debate over CFA franc devaluation is also characteristic of the structural
adjustment reform era. Evidence of overvaluation as high as 50 percent (based on
the REER) can be seen as early as 1980, but nothing was done until the 1994 devaluation. French intervention and the political problems of devaluing a currency
shared by several countries delayed the devaluation, which was also resisted by
Houphouet-Boigny until his death in 1993 (van de Walle 1991). But public debt
accumulated to crisis levels, so the devaluation was undertaken as an economic
necessity.
Variations in cocoa and coffee prices and in export revenue lay behind the
weakening international financial positions in West Africa before devaluation.
CAISTAB shielded Ivorian cocoa farmers from much of the international price
variation, with remarkably stable nominal, domestic cocoa prices over this period
of enormous change in international prices. Farmgate coffee prices showed more
variability, though hardly all of it was attributable to international price variability. From 1979 to 1999, the standard deviation of domestic cocoa prices was 37
percent of that for border prices, with both measured in CFA francs. For coffee,
the standard deviation of the domestic price was 39 percent of the border price in
CFA francs and 167 percent of the standard deviation in cocoa domestic prices.
The 1994 devaluation was also more evident in nominal coffee, cereals, and cotton
prices than in cocoa prices. Administered prices for cocoa prevented operation of
the mechanism by which devaluation could succeed. The surprising result is that
cocoa remained the dominant crop and continued to expand even when land
availability restrictions began to bind.
396
Distortions to Agricultural Incentives in Africa
Devaluation and privatization, 1994–98
More serious efforts to liberalize Ivorian trade and to privatize Ivorian agricultural markets followed the 1994 devaluation, if slowly. Privatization of the staterun economy, as noted above, was an important part of the reform package and
was eventually implemented for these crops, although gradually and with resistance from the government and the sector. Tariffs were also reduced following the
devaluation. By 1995, tariffs averaged 24 percent and the VAT averaged 17 percent.
These were somewhat lower for agricultural products (at 17 and 9.5 percent,
respectively) but about the same for food products (at 25 and 14 percent) (WTO
1995). The devaluation succeeded in stimulating the Ivorian economy, which
grew rapidly again after 1994 until 1999, when the civil conflict began. The efforts
to privatize continued from the mid-1990s until 2002, when the conflict became a
full-scale civil war.
The devaluation period also marked the beginning of change in the immigration policy that had fueled growth in cocoa production. Houphouet-Boigny’s successor ran on a liberal immigration campaign but subsequently introduced the
concept of “Ivoirité,” when limitations on expansion of cocoa cultivation and less
economic success made it more difficult for Ivorians to share the benefits of agricultural production with immigrants. A military coup d’état in 1999, fueled in
part by the immigration controversy, brought an end to the postdevaluation
period, and continuing civil conflict has since hampered economic performance
and particularly agriculture in the north of the country. Remarkably, cocoa output
has remained relatively stable over this period.
Civil conflict, 1999–2005
Elections were reestablished in 2000, but another failed coup d’état occurred in
2002, and then a rebel uprising divided the country between the north and south.
Immigration and eligibility for the presidency were key issues in the dispute, and
in 2004 there was a mass exodus of workers from the south (OECD 2006). In
2007, after the period studied here, a peace agreement was reached, and elections,
which had been postponed for some years were tentatively scheduled to be held in
late 2008.
The political division between north and south affected agricultural subsectors
differently. Cocoa and coffee are produced in the rain forests of the south, and
exports for cocoa have remained steady despite the conflict. But cotton and most
cereals are grown in the north, in areas held by rebels. Most cotton production is
apparently sold and ginned in neighboring Mali and Burkina Faso (OT Africa
Line 2006), so the Ivorian cotton companies have been facing difficult financial
times. They have also had difficulty obtaining credit in part because of the conflict
Côte d’Ivoire
397
and in part because of structural adjustment reforms. Most rice is also produced
in the north, so imports of rice to feed people in the urban areas of the south
increased markedly in the early 2000s. “Voluntary administered prices” for rice in
urban areas were established, but these appear to have helped traders more than
farmers, raising wholesale-to-retail margins (OECD 2006; Oryza 2004).
Agricultural Policies, Output, and Trade
In this section, pricing and performance data are examined for the four key sectors that are the focus of this study—cocoa, coffee, cotton, and cereals. In addition, critical issues relevant to each sector are identified, and events in that sector
are related to the policy evolution.
Cocoa
Cocoa remains Côte d’Ivoire’s leading agricultural export, accounting for 40 percent of export revenue in 2002, 37 percent in 2003, and 30 percent in 2004, despite
continued heavy taxation and low farmgate prices relative to border prices. Export
volume was higher in 2004 than in the two previous years, so changes in world
prices explain these revenue variations. Exports for Côte d’Ivoire were 41 percent
of world cocoa trade in 2001 and 35 percent in 2003, making it the world’s largest
exporter and giving it the motivation to maintain its export taxes (ICCO 2006).
The most fundamental reform to trade policy in this sector was the privatization
of CAISTAB in 2000, emanating from structural adjustment reforms. But when
export taxes were briefly lowered at the insistence of international donors, export
trader margins increased while farmgate prices did not, and short-run international price variability was not passed through to the farmgate (Wilcox and
Abbott 2004). That and the civil conflict have led to a reinstatement of some
export taxes.7
The area planted to cocoa increased steadily until the mid-1980s, after which it
remained flat except for a brief but significant expansion around the 1994 devaluation. Yields rose erratically until 1994; between 1994 and 2004, they increased
steadily and significantly. These area and yield increases have allowed production
and exports to grow, with a strong increase in output after 1994. Although little of
Côte d’Ivoire’s cocoa is consumed locally, the share of beans processed locally
increased considerably after 1999, encouraged by a reduction in export taxes on
processed cocoa products (BNETD 2002).
High export taxes, averaging 34 percent of fob (free on board) export value
from 1995 to 2004, accounted for much of the difference between farmgate and
border prices.8 Abbott (2007, appendix table 2) presents cocoa farmgate prices as
398
Distortions to Agricultural Incentives in Africa
a percentage of border prices and shows export taxes since the privatization initiatives began in 1995, when excess profits to the parastatal exporter were replaced by
explicit export taxes. Export taxes and exporter margins both steadily increased
after 1998, all at the expense of farmers—in 2003 and 2004, farmgate prices as a
share of border were at their lowest levels since the late 1970s, when world prices
were much higher.
As a result of CAISTAB’s stabilization efforts, nominal farmgate prices for
cocoa stayed fixed for many years before devaluation in 1994. The resulting tax
rate varied with world prices, without reflecting any change in Ivorian government policy. When policy changes were made, they typically reflected earlier
changes in the level of world prices. The result was that the correlation between
domestic and world prices from 1979 to 1994 was only 61 percent, and the standard deviation of farmgate prices was only 33 percent of that for border prices
measured in CFA francs.
Price stability may have stimulated cocoa production, but price levels were relatively low: over the years of successful expansion from 1960 to 1979, farmgate
prices averaged only 47 percent of border prices. The key incentive for cocoa production seems to have come from immigration and land tenure policies, which
encouraged area expansion despite high taxation. The key role of immigration
and land tenure rather than price levels in determining cocoa production could
explain why many attempts to estimate cocoa supply functions from price data,
such as those by Maizels, Bacon, and Mavrotas (1997), find that production did
not rise with prices. The CFA devaluation of 1994 did succeed in stimulating
cocoa exports and even yield increases, but farmgate prices from 1994 to 1999
were still only 45 percent of border prices. Only during the 1980–93 recession
period were farmgate prices higher than border prices, and that effect is negated
when prices are measured at real exchange rates, when a similar 44 percent share is
found.
The structural adjustment reforms led to very successful marketing of cocoa by
private traders. But it also caused the provision of various public goods to suffer.
Complaints focused on lack of credit availability, market information, input
provisions, and disease control. Moreover, BNETD (2006) reported significant
declines in the quality of cocoa exported from Côte d’Ivoire and a diminished
premium for Côte d’Ivoire cocoa on the LIFFE (London International Financial
Futures Exchange) commodity exchange. Although new institutions were created
to fill these gaps , the continuing civil conflicts made governance problems very
difficult to resolve.
Another important part of the cocoa story since 1999 is the increase in processing of cocoa beans into butter, powder, and paste. Before 1999, such processing was
Côte d’Ivoire
399
small, and the products were considered to be of inferior quality. Both Archer
Daniels Midland (ADM) and Cargill have built processing plants in Côte d’Ivoire
that meet the output specifications of their European plants. Processing also benefited from reduced export taxes. In 1999, export taxes on processed cocoa beans
were only 9 percent, compared with 33 percent for whole beans. As taxes on raw
beans increased, so did taxes on processed products, but those taxes remained
nearly 20 percent lower in 2004. Plant managers at ADM and Cargill argue that
the quality of products now coming from African plants is as good as that from
European plants, but costs are much higher. Without the export tax reduction
incentives, processing would still be in Europe (or North America); but with these
incentives, more than 25 percent of cocoa beans from Côte d’Ivoire are now
processed before export.
Coffee
The coffee story for Côte d’Ivoire is markedly different in some respects from the
cocoa story. Most notably, Côte d’Ivoire was Africa’s largest coffee exporter in the
1960s, but then experienced declines in its very erratic production and exports.
Coffee contributed 35–40 percent of the country’s export revenue in the early
1960s, but that contribution fell steadily to only 7 percent in the late 1990s and to
only 1.7 percent in 2004. Export taxes were not as high for coffee as they were for
cocoa, in part because the drop in world coffee prices was greater. But farmgate
prices remained low, averaging 47 percent of border prices.
The area planted to coffee grew steadily until the mid-1980s, then leveled
off, before falling around 1990; it has declined steadily from 1999. Yield has been
extremely volatile, declining considerably until 1994, when a resurgence occurred.
As a consequence, production and exports rose slowly but erratically until the
early 1980s, declined until the mid-1990s, increased considerably with the yield
advances of the late 1990s, and fell back again after 2001. Exports of processed
coffee products have never been large, in contrast to the cocoa case.
Export taxes averaged only 8.3 percent between 1995 and 2004, smaller than the
export taxes for cocoa. Trader margins were somewhat higher, with exporter margins reaching 35 percent after 2002 (Abbott 2007, appendix table 17). Farmgate
prices averaged 44 percent of border prices from 1960 to 1979, 49 percent from
1980 to 1993, 56 percent from 1994 to 1999, and 48 percent from 2000 to 2005.
In addition to lower prices, coffee producers in the early 2000s were facing
many of the same institutional changes and problems as cocoa producers faced.
New government entities meant to replace some of the functions of CAISTAB had
so far been able to fulfill their promise.
400
Distortions to Agricultural Incentives in Africa
Cotton
The cotton sector in Côte d’Ivoire has been managed somewhat differently from
cocoa or coffee, largely because of agronomic and institutional differences. Unlike
cocoa and coffee trees, which, once planted, produce crops with few inputs other
than labor, cotton requires fertilizer, pesticides, and varietal changes over time.
Seed cotton is also ginned in-country, and lint, cotton seed, and other products
are then sold. The parastatal CIDT held a monopoly in cotton until privatization
began in 1998, when it was broken into three regional companies. But each of
those held a monopoly over its specific region, and the state did not divest a
majority interest in these companies until 2002. Advocates of liberalization have
not insisted on as great a degree of privatization for cotton, and parastatal management has extended to monopoly control of trade since the French colonial
period (Goreux and Macrae 2003).
Cotton farmers and cotton exports are also heavily taxed, if less so than cocoa
or coffee farmers when ginning costs are considered, and with sustained periods
of low world cotton prices leading to apparently higher farmgate prices as a share
of border prices.9 Lint and other products, not seed cotton, are exported. The
international index of cotton lint prices is transformed to a seed-cotton equivalent using the methodology and ginning ratios taken from Baffes (2007). FAO
reports cotton lint “producer prices,” which are simply seed-cotton producer
prices converted to a lint basis using a very similar ginning ratio (FAOSTAT 2006).
Seed-cotton prices paid to farmers have been a small fraction of the transformed
A Index, averaging 54 percent from 1966 to 1979, 51 percent from 1980 to 1993,
51 percent from 1994 to 1999, and 63 percent from 2000 to 2004. When the overvaluation of the CFA franc is taken into account, the extent of implicit taxation of
cotton was even higher in the years before the 1994 devaluation.
The cotton margins include ginning costs, but ginning was done by parastatals
that were not privatized until 2002 and still involves some government control.
Thus, taxation of cotton is implicit in any excess profits collected by ginners but is
hard to measure because ginning costs appear to be reported as the difference
between sales prices for lint exports and the prices ginners paid to farmers for seed
cotton. Mismanagement has led to losses by these ginners in years of very low
world cotton prices. Baffes (2007) adjusts cotton margins to reflect excess costs of
these parastatals, and the nominal rate of assistance (NRA) calculations discussed
later in this chapter reflect assumptions necessary to make these adjustments.
The patterns seen here are quite similar to those for cocoa and coffee, though
conditioned by the unique history of world cotton prices. Moreover, seed-cotton
prices from 1966 to 1999 are much like cocoa prices under parastatal management. They remained fixed in nominal terms for several years and only increased
(they were never lowered). Increases occurred well after international prices had
Côte d’Ivoire
401
increased; the price decline in 1991 reflected a 50 percent drop in international
cotton prices. Higher farmgate price shares in the later 1990s and early 2000s
reflect low world cotton prices in those years.
The area planted to cotton grew steadily after 1960, leveling off around 1989.
Area planted jumped in 1994 with devaluation and then declined during the civil
conflict. Seed cotton yields also grew during the 1960s and 1970s. Production
grew until 1987, and again after the devaluation, with increased variability. Cotton
lint production has mirrored seed cotton production, and because most lint is
exported, exports follow the same pattern. Some cotton seed has also been
exported since 2000.
These trends indicate that policies during the recession and after the devaluation hurt cotton exports, but that cotton has become an increasingly important
export despite the sustained taxation. Recent BNETD data suggest farmers may
have received somewhat better prices as the second phase of privatization took
effect. But cotton is grown in the north, in territory that was held by rebels for several years. Reports indicate that farmers were selling cotton at lower prices for
cash in neighboring countries rather than on credit to the financially troubled
Ivorian cotton companies (OT Africa Line 2006). The apparent implicit taxation
of cotton farmers since 2000 probably reflects these problems, and BNETD as well
as Baffes report that cotton farmgate prices continued to fall after 2004.
Cereals
Rice is one of Côte d’Ivoire’s most important agricultural imports; rice imports
totaled $218 million in 2004, or nearly 3 percent of total imports. Imported rice
accounts for almost half of the country’s rice consumption. Côte d’Ivoire also
imported $73 million worth of wheat, which it does not produce. It does produce
maize, millet, and sorghum (as well as rice), but none of these other cereals are
traded to any degree. According to the FAO (2003), roots and tubers, especially
cassava, are important sources of calories in Ivorian diets, but these are not traded
either. Nontradable cereals and roots and tubers (cassava, plantains, yams)
accounted for more than half of agricultural production value in the 1960s and
for more than one-third in recent years. As noted earlier, a parastatal marketing
board managed rice trade until its privatization in 1995, and rice self-sufficiency
was a policy goal in the mid-1980s, supported by quantitative restrictions on
imports. It appears that the government still influences rice prices and trade, in
urban areas, through “voluntary” administered pricing (OECD 2006).
Rice and maize farmgate prices, relative to their international values, are much
higher than those typically found for exportables. Rice farmgate prices averaged
96 percent of border prices from 1961 to 1979, 121 percent from 1980 to 1993,
402
Distortions to Agricultural Incentives in Africa
110 percent from 1994 to 1999, and 125 percent from 2000 to 2003. Maize farmgate price ratios were well above these ratios for rice, and those domestic prices
were well above border prices for most of this time. Maize prices averaged 113 percent of the international price from 1966 to 1979, 174 percent from 1980 to 1993,
133 percent from 1994 to 1999, and 134 percent from 2000 to 2004. Maize has
never been traded to any significant extent, however, because the cost of importing
would exceed that price difference.10 There are tariffs on food crop imports, but
their impact is limited because cereals, roots and tubers are mainly nontradable.
For cereals the tariff rate is uniform, averaging 8 percent. Tariffs on roots and
tubers are somewhat higher, but the main trade restrictions come from the operations of parastatals using quantitative restrictions and market segmentation.
The area planted to rice has been relatively constant, rising in the mid-1980s
when the self-sufficiency policy applied and prices were higher and falling since
the devaluation of 1994. Area planted to maize shows a similar pattern. Yields
were relatively stable until 1994, when dramatic increases were recorded. These
increases look suspiciously like data problems rather than actual technical
improvements. Diagne (2006) and WARDA (2004) report that Ivoirian farmers
are adopting new rice varieties that could increase yield, but any effect of these
varieties would have occurred well after the yield increases shown in the FAO data.
In any case, imports of wheat and rice grew until the self-sufficiency period of the
1980s, and remained relatively constant thereafter. Rice imports grew again after
1999, with imports in 2004 more than double those in the mid-1990s.
Information on recent urban rice prices (BNETD 2006; Oryza 2004) show
two characteristics of the rice market. One is that local rice commands a premium over imported rice. That premium was 27 percent in 2001 and 41 percent
in 2002. The second is that urban retail rice prices are substantially higher than
are farmgate or import prices, even after tariffs and the VAT are applied. In 2002,
farmgate prices were CFAF 166 for a kilogram of milled rice, import unit values
were CFAF 123, imported rice in the Abidjan market averaged CFAF 207, and
local rice averaged CFAF 271, according to Oryza (2004). During this same year
BNETD reported an urban wholesale price of CFAF 250 and a retail price of
CFAF 300 (reflecting the VAT). As noted earlier, the OECD (2006) reports that
traders were asked to set urban prices voluntarily (probably at the BNETD reported
levels). The BNETD wholesale price yields an urban-rural margin of 63 percent,
and an import-to-wholesale margin of 68 percent. The rural-import price differential reflects both transportation costs and the premium on local rice. Taking
those into account still leaves a substantial margin for urban rice traders. It
appears the current policy restricts imports just as quantitative restrictions did in
the past, with little benefit accruing to farmers. Urban traders appear to collect
any rents in this system, but restrictions on imports are needed to account for the
Côte d’Ivoire
403
import-to-wholesale margin, with segmented markets and the voluntary pricing
scheme enabling collusion.
Despite this recent protection, rice imports have expanded greatly in recent
years. Because most rice is grown in the north, trade within the country was
severely affected by the ongoing civil conflict. This situation would help account
for the large urban-rural margin and the urban rice price.
Distortions to Agricultural Incentives
The main focus of the empirical part of the current study’s methodology (see
appendix A in this volume and Anderson et al. 2008) is on government-imposed
distortions that create a gap between domestic prices and what they would be
under free markets. Because the characteristics of agricultural development cannot be understood from a sectoral view alone, the project’s methodology not only
estimates the effects of direct agricultural policy measures (including distortions
in the foreign exchange market) but also generates estimates of distortions in
nonagricultural sectors for comparative evaluation. More specifically, a nominal
rate of assistance for producers of the main traded crops is computed. Also generated is an NRA for nonagricultural tradables, for comparison with that for agricultural tradables through the calculation of a relative rate of assistance (RRA).
An assessment of the extent of “average” distortions to agriculture in Côte
d’Ivoire is limited somewhat by the focus on the four key commodities the country trades, which account for only about 40 percent of the value of agricultural
production. But these commodities are the ones gaining attention in policy discussions and are important in determining the behavior of Côte d’Ivoire’s trade
both for agriculture and in total. Data and information limitations prevent going
much beyond these focus commodities, particularly for historical comparisons.
Strong assumptions must be invoked to compute average protection rates for even
these four traded products in Côte d’Ivoire. Included , however, are three important nontradable staple food products (cassava, plantains, and yams), whose markets are not directly distorted by government price or trade policies; they raise the
product coverage ratio to between 70 and 80 percent.
For the three exportables focused on here, farmgate prices are low relative to
world prices. In 2001, farmgate prices for cocoa and coffee were at 50–55 percent
of world prices, and cotton was at 57 percent. In 2004, they fell to about 36 percent
for cocoa and coffee, and rose to 61 percent for cotton. Explicit export taxes
explain these low farmgate prices for cocoa, while high margins and high profits
for coffee and cotton traders suggest barriers to entry of some kind.
The civil war has played a significant role in agriculture, increasing domestic
trading margins for cocoa. In the case of cotton, privatization appears to have
404
Distortions to Agricultural Incentives in Africa
briefly raised the share of the border price going to farmers, and the effective nontariff barrier has fallen, but after privatization, margins remain high. A very small
explicit export tax (prélèvement professionel) was recently added for cotton; but it
is not big enough to affect these results, and explicit export taxes have not been
found for other exportables.11
Import-competing products considered here are rice and also wheat, which is
not produced domestically. Similar tariffs apply to both crops. Producer price data
reveal protection to rice, but wholesale-to-retail margins are larger, which suggests
that quantitative restrictions limit entry of competitors.12
Table 14.1 presents NRAs for cocoa, coffee, cotton, and rice from 1961 to 2005,
while figure 14.2 shows average NRAs for exportables and the one importable.
The averages for the exportables show heavy taxation of export agriculture.
These estimates appear to show a great deal of variability over time in agricultural protection (or rather taxation, because the estimates are negative in most
cases). NRAs are higher, and taxation of agriculture is lower, in years when commodity prices are low, and they are lower at times of high commodity prices.
The individual crop histories discussed earlier showed much greater similarity
in the average extent of taxation during the critical political-economic periods
identified earlier. In large part this is because each period witnessed both low and
higher international prices. The transition from one period to the next (for example, the beginning of the protracted recession) was often brought about by a sustained change in the relative level of the key international commodity prices.13 A
key point is that border policy and domestic agricultural policy in Côte d’Ivoire
have both responded to world market conditions, isolating to some extent farmers
from those extremes, but continuing to tax farmers in most years, especially when
world prices were high.
The NRA for the whole sector is generated after making assumptions about the
NRA for the exportable, import-competing, and nontradable parts of farm products not covered in this study. Those NRAs are shown in the top rows of table 14.2.
The NRA for tradable farm products is then compared with that for nonagricultural tradables using the relative rate of assistance, shown in the lower part of
table 14.2 and illustrated in figure 14.3. These RRAs suggest that the prices of tradable farm products, relative to those received by producers of nonfarm tradables,
has been depressed by between one-third and one-half over the past five decades.
Conclusions
Côte d’Ivoire is an export-oriented agricultural economy, and the world’s
largest exporter of cocoa. The country has managed to maintain and grow exports
of cocoa despite heavy taxation, thanks to abundant land and immigration of
Table 14.1. NRAs for Covered Farm Products, Côte d’Ivoire, 1961–2005
(percent)
Product indicator
Exportablesa
Cocoa
Coffee
Cotton
Import-competing productsa
Rice
Nontradables
Cassava
Plantains
Yams
Total of covered productsa
Dispersion of covered productsb
Percent coverage (at undistorted prices)
1961–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–05
46.5
33.3
51.6
—
22.3
22.3
0.0
0.0
0.0
0.0
28.6
22.9
75
50.4
45.4
52.2
20.6
37.4
37.4
0.0
0.0
0.0
0.0
35.4
27.5
75
48.6
40.4
52.6
29.2
12.2
12.2
0.0
0.0
0.0
0.0
32.7
33.1
76
58.6
50.2
64.0
24.9
41.0
41.0
0.0
0.0
0.0
0.0
39.8
46.2
75
59.8
51.9
69.9
46.9
17.8
17.8
0.0
0.0
0.0
0.0
40.1
33.3
75
43.4
37.1
57.6
34.9
8.4
8.4
0.0
0.0
0.0
0.0
28.5
33.1
80
Source: Data compiled by the author.
Note: — no data are available.
a. Weighted averages, with weights based on the unassisted value of production.
b. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
47.4
44.1
57.9
38.4
5.4
5.4
0.0
0.0
0.0
0.0
21.7
26.2
76
39.4
41.1
39.1
21.9
7.2
7.2
0.0
0.0
0.0
0.0
22.5
23.4
71
47.1
49.4
48.0
15.0
23.6
23.6
0.0
0.0
0.0
0.0
28.7
32.6
72
405
406
Distortions to Agricultural Incentives in Africa
Figure 14.2. NRAs for Exportable, Import-Competing, and All
Farm Products, Côte d’Ivoire, 1961–2005
80
60
40
percent
20
0
20
40
60
80
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
100
year
import-competing products
exportables
total
Source: Data compiled by the author.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
farmworkers from neighboring countries. From 1961 to 2004, the NRA for cocoa
showed an average effective taxation of 44 percent. The comparable NRA on
coffee implies even higher taxation, at 55 percent, and coffee exports diminished
substantially during this period. Tax rates for cotton were lower, at 29 percent, and
that crop has expanded.
The NRA for rice production, a key agricultural import, has averaged 1.3 percent since 1961, but in the early 2000s it stood at 26 percent. Despite rising protection, rice imports have grown over the period of study, driven by increased consumption in urban areas.
Taxation of agriculture appears to be remarkably stable over the four critical
political-economic periods in the past 45 years of Ivorian history, but year-to-year
variations are significant. In each of the four periods, averages of the NRAs are
very close to the long-term average, and the extent of taxation since 1980 is very
close to the average before 1980. Taxes for cocoa averaged 43 percent before 1980
and 44 percent afterward. Coffee taxes averaged 55 percent in each of those periods, and cotton taxes averaged about 30 percent in both periods. The change was
Table 14.2. NRAs for Agriculture Relative to Nonagricultural Industries, Côte d’Ivoire, 1961–2005
(percent)
Indicator
1961–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–05
NRA, covered products
NRA, noncovered products
NRA, all agricultural products
Trade bias indexa
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAb
28.6
8.5
23.5
0.53
32.9
15.9
42.1
35.4
11.2
29.3
0.50
38.1
11.7
44.6
32.7
13.7
28.1
0.55
35.0
9.6
40.7
39.8
2.5
30.8
0.70
38.6
20.2
48.7
40.1
8.9
32.2
0.64
42.9
14.7
50.2
28.5
8.5
24.3
0.54
33.3
17.2
43.1
21.7
12.2
19.5
0.55
32.7
11.2
39.5
22.5
14.3
20.0
0.49
27.5
7.5
32.6
28.7
16.3
25.2
0.55
33.7
4.3
36.5
Source: Data compiled by the author.
a. Trade bias index is TBI (1 NRAagx/100)兾(1 NRAagm兾100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and
exportable parts of the agricultural sector, respectively.
b. The RRA is defined as 100*[(100 NRAagt)兾(100 + NRAnonagt) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural
and nonagricultural sectors, respectively.
407
408
Distortions to Agricultural Incentives in Africa
Figure 14.3. NRAs for Agricultural and Nonagricultural
Tradables and the RRA, Côte d’Ivoire, 1961–2005
40
20
percent
0
20
40
60
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
80
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the author.
Note: For a definition of the RRA, see table 14.2, note b.
greatest for rice, where effective tariffs were 1 percent from 1960 to 1979 and
24 percent afterward.
The long-term stability of export taxes, despite large variations in yearly taxation rates, reflects the stabilization objective of Ivorian agricultural policy, and the
endogeneity of agricultural taxation. Very high tax rates have been lowered in
years of low international prices, sheltering farmers from the full effects of international price volatility, but taxing them nevertheless.
One of the main forces for change of Côte d’Ivoire’s agricultural policy has
been structural adjustment reforms. These have included pressure to reduce
export taxes and to privatize the parastatal agencies that have managed the key
agricultural sectors. The government of Côte d’Ivoire in the past has not taken
ownership of these reforms, and since the first reforms began in 1981, trade liberalization efforts have begun and stalled and then begun again. More recent efforts
since the 1994 devaluation and particularly after 2000, when CAISTAB was finally
privatized, might have finally been effective in making this a more open, marketoriented economy, but the recent civil conflict has put reduced agricultural taxation on hold.
Côte d’Ivoire
409
It is not entirely evident that these reforms are always in the national interest.
Farmers have objected to the price variability they now face. More important, as a
large exporter of cocoa, some export taxes may be in the national interest even if
not in farmers’ interests. Yilmaz (1999) estimated that optimal export taxes for
cocoa from Côte d’Ivoire were around 30 percent, only somewhat lower than the
historical rate of taxation. Others have shown that quotas, and parastatal management, can also exploit Côte d’Ivoire’s market power in cocoa (Panagariya and
Schiff 1992). Tax revenues were intended to help stabilize prices but were more
often used to finance diversification of exports and industrial development.
Gilbert and Varangis (2003) argue that if structural adjustment raised farmgate
prices for all the African exporters of cocoa, supply expansion could have frustrated the intent of this initiative to improve farmer welfare by lowering world
prices. Abbott, Wilcox, and Muir (2005) note that imperfectly competitive private
traders have at times raised margins when structural adjustment reduced taxation, and those margins fell again as taxes were subsequently raised. In neighboring countries, where reforms have gone further, farmgate prices remain a fraction
of world prices, and imperfectly competitive behavior by traders is found, resulting
in weak transmission to farmers of world price fluctuations. The share of farmgate prices in consumer goods prices is notoriously small, and large multinationals that may have market power intervene between consumers and cocoa
farmers (Dorin 2003; Fold 2002; Losch 2002). Thus, the effects of the longstanding structural adjustment reforms in Côte d’Ivoire, even in the brief periods when
they were more seriously applied, have not led to significantly higher farmgate
prices.
Early analysts emphasized the institutional structure of markets and policy in
Côte d’Ivoire. Immigration and land tenure policies were important, at least
before 1994, in explaining supply response and expansion of cocoa exports. The
laissez-faire parastatal management of cocoa and coffee interfered little with
cocoa production beyond the collection of taxes at the port. Lessons after privatization have been that the private sector can continue to market cocoa effectively,
that taxes are not necessarily reduced, and that a role for government remains.
Farmers’ complaints about prices reflect as much the problems of poor market
information when panterritorial, stable prices no longer apply. Quality deterioration, credit availability, ineffective disease and pest management, and the need for
research and extension show that some government involvement must persist;
each of these aspects had been addressed by policy before 2000. Newly invented
“private” institutions have attempted to cope with some of these problems in a
difficult political environment.
One must be careful in advocating simplistic policy solutions for Côte
d’Ivoire’s agricultural sector. Multilateral trade liberalization, if it involves only
410
Distortions to Agricultural Incentives in Africa
tariff changes, is unlikely to have a large effect. It is difficult to find any effect of
the 1995 Uruguay Round agreement (FAO 2003), in part because structural
adjustment, not trade commitments, dictated any actual reforms, and in part
because the trade agreement occurred at the same time as the 1994 devaluation.
But institutionally set prices changed only slowly in response to these forces. That
sectors improved even in cases where positive changes in farmgate prices are not
immediately evident demonstrates the importance of accompanying institutional
changes.
The most powerful political economy factor dictating policy and performance
in Ivorian agriculture has been civil conflict. It has influenced the specifics of agricultural policy through the north-south division of the country and through
impacts on immigrant labor. It has frustrated the intent of recent, more serious
liberalization efforts. It is unfair to judge the potential of greater agricultural liberalization until those problems are solved. But both the successes and the problems of agricultural exports in Côte d’Ivoire highlight the need to solve governance problems so the state can perform its appropriate role in agriculture.
Notes
1. GDP per capita measured in constant 2000 U.S. dollars (World Bank 2006b).
2. Economic performance data are from World Bank (2006b) and IMF (2006).
3. Abbott (2007, appendix figure 4) shows the official exchange rate in Côte d’Ivoire from 1960
until 2005. It also shows the consumer price index, a measure of inflation, as well as two indicators of
real exchange rates, and so the extent of overvaluation over time.
4. Abbott (2007, appendix figure 5) shows international price indexes for key agricultural goods:
cocoa, coffee, cotton, maize, and rice.
5. Because Côte d’Ivoire exports as much as 40 percent of the world’s cocoa, it may be a large
country affecting the world price. Yilmaz (1999) has investigated the optimal export tax under this
circumstance, and argues this is the case. In the trade, an increase in world market prices for cocoa
has been attributed to the civil conflict in Côte d’Ivoire, with spikes evident at critical times.
6. The CIDT was broken into regional companies in 1998, including Nouvelle CIDT, Compagnie
Cotonniere, and Ivoire Coton, but the government did not divest its majority interest in these regional
companies until 2002.
7. Abbott (2007, appendix figure 6) shows the evolution of cocoa production and trade in
response to these distorted incentives.
8. The DUS (Droite unique de sortie) is a specific tax, as are most of the prelevements professionels,
but they have been changed often, even during seasons, in response to changing world market
conditions.
9. Abbott (2007, appendix table 18) shows cotton farmgate prices for seed cotton, compared to the
Cotlook A Index, an international indicator of cotton lint prices. That table also compares cotton lint
export unit values to the FAO cotton lint “producer price,” which show a very similar pattern to the
seed cotton prices.
10. Data showing very limited trade of maize and other staple home goods and the disconnection
between domestic and world maize prices support this assertion.
11. Data reported for bananas reveal low farmgate prices relative to border prices, suggesting the
presence of a nontariff barrier or high margins, as in the case of cotton. Farmgate prices for palm oil
are higher, indicating little intervention. Both bananas and palm oil are produced on plantations,
Côte d’Ivoire
411
which were to be privatized in 2002, but this has resulted in little change in the share of the world price
accruing to farmers.
12. Fruits and vegetables and other agricultural products are now typically charged a 20 percent
most-favored-nation tariff. The average tariff for fruits and vegetables was somewhat higher in 2001,
and somewhat lower for agricultural products overall. These current tariffs are similar to the protection afforded to manufactured goods. There are exceptions to all these most-favored-nation tariffs for
special cases, however.
13. Abbott (2007, appendix figure 5) shows that these international prices tended to move
together, if imperfectly, with peaks (mid-1970s, mid-1990s) and valleys (around 2000, mid-1980s)
occurring simultaneously.
References
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Abbott, P., M. Wilcox, and W. Muir. 2005. “Corporate Social Responsibility in International Cocoa
Trade.” Paper presented at the International Food and Agribusiness Management Association
symposium, Chicago, June 25–26.
Ahmed, M., H. Kazianga, and J. Sanders. 2005. “West African Cocoa: Modernization or Loss of
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Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675–704.
Baffes, J. 2007. “Distortions to Cotton Sector Incentives in West and Central Africa.” Agricultural
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Bassett, T. 1988. “The Development of Cotton in Northern Ivory Coast, 1910–1965.” Journal of African
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Boone, C. 1995. “The Social Origins of Ivoirian Exceptionalism: Rural Society and State Formation.”
Comparitive Politics 27 (July): 445–63.
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Ghana.” Agricultural Distortions Working Paper 47. World Bank, Washington, DC.
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Diagne, A. 2006.”Diffusion and Adoption of Nerica Rice Varieties in Côte d’Ivoire.” Developing
Economies 44 (2): 208.
Dorin, B. 2003. “ From Ivorian Cocoa Bean to French Dark Chocolate Tablet.” AMIS-36, CP-1602.
CIRAD (Centre de Cooperation Internationale en Recherche Agronomique pour le Développement), Paris.
Easterly, W. 2006. “Global Development Network Growth Database.” Development Research Institute,
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Implementation Experience-Developing Country Case Studies.” Commodities and Trade Division,
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FAOSTAT. 2006. Food and Agriculture Organization Statistics Databases. FAO, Rome.
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Fold, N. 2002. “Lead Firms and the Competition in ‘Bi-Polar’ Commodity Chains: Grinders and Branders in the Global Cocoa-Chocolate Industry.” Journal of Agrarian Change 2 (2): 228–47.
Gilbert, C. L., and P. Varangis. 2003. “Globalization and International Commodity Trade with Specific
Reference to the West African Cocoa Producers.” Working Paper W9668. National Bureau of
Economic Research, Cambridge, MA.
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Goreux, L., and J. Macrae. 2003. “Reforming the Cotton Sector in Sub-Saharan Africa.” Africa Region
Working Paper Series 47. World Bank, Washington, DC.
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———. 2006. International Financial Statistics. Washington, DC: IMF. http://www.imfstatistics.org/
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Policy in Africa, ed. C. Soludo, O. Ogbu, and H-J. Chang. Ottawa: Africa World Press/International
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López, R. 1998. “The Tragedy of the Commons in Côte d’Ivoire Agriculture: Empirical Evidence and
Implications for Evaluating Trade Policies.” World Bank Economic Review 12 (1): 105–31.
Losch, B. 2002. “Global Restructuring and Liberalization: Côte d’Ivoire and the End of the International Cocoa Market?” Journal of Agrarian Change 2 (2): 206–27.
Maizels, A., R. Bacon, and G. Mavrotas. 1997. Commodity Supply Management by Producing Countries:
A Case Study of the Tropical Beverage Crops. Oxford: Clarendon Press.
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.com/africa//ivorycoast/index.shtml.
Panagariya, A., and M. Schiff. 1992. “Taxes versus Quotas: The Case of Cocoa Exports.” In Open
Economies: Structural Adjustment and Agriculture, ed. I. Goldin and A. Winters. Cambridge, U.K.:
Cambridge University Press.
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African Affairs 90: 383–405.
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d’Ivoire.” WARDA, Bouake, Côte d’Ivoire.
Widner, J. A. 1993. “The Origins of Agricultural Policy in Ivory Coast 1960–86.” Journal of Development
Studies 93: 25–59.
Wilcox, M. D., and P. C. Abbott. 2004. “Market Power and Structural Adjustment: The Case of West
African Cocoa Market Liberalization.” Selected paper, American Agricultural Economics Association Annual Meeting, Denver, Colorado, August 1–4.
Woods, D. 2003. “The Tragedy of the Cocoa Pod: Rent-Seeking, Land and Ethnic Conflict in Ivory
Coast.” Journal of Modern African Studies 41 (4): 641–55.
———. 2004. “Predatory Elites, Rents and Cocoa: A Comparative Analysis of Ghana and Ivory Coast.”
Commonwealth and Comparative Politics 42 (2): 224–41.
World Bank. 2006a. “Country Brief: Côte d’Ivoire.” World Bank, Washington, DC.
———. 2006b. World Development Indicators 2006. Washington DC: World Bank. http://devdata
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Geneva. http://www.wto.org/English/tratop_e/tpr_e/tp8_e.htm.
Yilmaz, K. 1999. “Optimal Export Taxes in a Multicountry Framework.” Journal of Development
Economics 60 (2): 439–65.
15
Ghana
Jonathan Brooks, Andre Croppenstedt,
and Emmanuel Aggrey-Fynn*
Ghana’s economic performance of the recent past can be described as a qualified
success. Since 1986, real gross domestic product (GDP) has grown at an annual
average of more than 4 percent, enabling per capita incomes to increase by a total
of 30 percent between then and 2004. With rising incomes has come an associated
decline in poverty: the incidence of food poverty has fallen from an estimated
37 percent of the population in fiscal 1991 to 27 percent in fiscal1998 (Ghana Statistical Service 2000). This performance is much better than that recorded elsewhere in Sub-Saharan Africa, where per capita incomes have on average remained
static and poverty reduction has been sparse. On the other hand, it has done little
more than return Ghana’s per capita income to its level at independence in 1957,
and it compares unfavorably with the faster pace of growth and poverty reduction
in other regions, notably in Asia.
Nevertheless, the stable state of the economy, linked to more than a decade of
democratic government, contrasts sharply with the situation in the early 1980s,
when the economy lay in ruins. Stryker (1990, 1991), in his contribution to the
study led by Krueger, Schiff, and Valdés (1991), notes that agricultural distortions
played a key role in the disintegration of the Ghanaian economy. That study, which
examined the evolution of agricultural policies and their consequences from the
period before independence to the mid-1980s, when liberalization and structural
adjustment were initiated, identified chronic macroeconomic instability, increasing
* The authors would like to thank Ivy Drafor for information on agricultural markets in Ghana. They
are also grateful to for helpful comments from Will Masters and other workshop participants. Detailed
data and estimates of distortions reported in this chapter can be found in Brooks, Croppenstedt, and
Aggrey-Fynn (2007).
413
414
Distortions to Agricultural Incentives in Africa
currency overvaluation, strict controls over the economy in general and the agricultural sector in particular, and ineffective state interventions as the sources of decline.
Mismanagement of the cocoa sector had a particularly damaging effect on Ghana’s
economic performance. At the political level, there was great instability, with regime
changes leading to policy reversals and with rent seeking by vested interests to such
an extent that by 1983 the economy had effectively devoured itself, and there were
no more rents left to extract.
This chapter aims to bring Stryker’s analysis up to the 21st century. In recent
years Ghana has followed International Monetary Fund (IMF) stabilization and
World Bank structural adjustment programs and moved into a “postreform”
phase, where the effects of liberalizing reforms are being digested and the benefits
of further reforms are being queried. Numerous studies have described Ghana’s
economic and agricultural policies and performance, including periodic World
Bank reviews. However, since Stryker’s empirical analysis, there has been no comparable attempt to quantify agricultural policy distortions, assess their economic
impacts, and place their importance in the context of Ghana’s broader development challenges.
A general finding of the current analysis is that the profound policy distortions
that characterized Ghana’s agricultural sector until 1984 have been reduced substantially. The exchange rate, which now floats, is no longer consistently overvalued, and trade policies are relatively even in their treatment of different sectors,
with relatively uniform tariffs and with logical exemptions—for example, for
inputs and products conducive to improved health and education. Improved
macroeconomic and political stability and greater transparency in the policy
process have meant that the prospects for agricultural development are much
enhanced.
Nevertheless, as of the mid-2000s important distortions still afflicted Ghana’s
agricultural sector. Import-competing sectors were protected by the standard tariff of 20 percent, and there was some implicit taxation of exports. In the case of
cocoa, the marketing board’s share of the export price had risen with increases in
the world market price, dampening incentives to invest. However, the main distortions lay not in the realm of explicit sectoral policies but in the way in which
underdevelopment of physical infrastructure, weak credit markets, and stalled
structural reforms (including to the country’s financial markets) hampered
progress.
Government spending on agriculture remained low, at consistently less than
2 percent of all public spending. The 2004 share of just 1.3 percent contrasted
with the target established in the Maputo Declaration of 2003, where African
heads of state and the government committed themselves to increasing national
expenditures on agriculture and rural development to 10 percent of all budgetary
Ghana
415
expenditures. Donor aid increased substantially, with the net inflow of aid climbing from an average of 2.8 percent of GDP between 1996 and 2000 to 7.1 percent
of GDP between 2001 and 2003, in part a result of debt relief (Bank of Ghana
2005); but that aid was not systematically targeted to agriculture.1 As a complement to domestic spending, this injection provided real opportunities to remedy
deficiencies in the functioning of both output and factor markets. The key challenge was to ensure that these monies are spent in suitable public investments,
rather than in measures that distort producers’ incentives by leading them to
invest in agricultural activities without a sustainable future or that use purchased
inputs excessively.
With such reforms, agriculture can play its part in lifting Ghana’s growth rate
from levels that barely exceed population growth to the 6–8 percent target established in Ghana’s revised poverty reduction strategy (National Development Planning Commission 2005), a level that, it is estimated, would enable Ghana to
achieve middle-income country status by 2015.
Economic Growth and Structural Changes
Ghana’s economic development can be divided into four broad phases: the period
before independence in 1957, the postindependence period from 1957 to 1983,
the years of stabilization and adjustment between 1983 and 1992, and the postreform period from the elections of 1992 onward.
Before independence in 1957
Before independence, agricultural policy in Ghana emphasized the production of
export commodities, such as cocoa, coffee, and oil palm and paid little attention to
noncommercial production or the development of staple food crops for domestic
consumption. In general, overall economic policy focused on natural resource
extraction, with minimal colonial oversight of other sectors of the economy.
Some of the subsequent apparatus of government intervention, notably marketing boards, were established during this period. A particularly important institution, the Cocoa Marketing Board, was established by the colonial government
during the Second World War, and became the monopoly buyer of cocoa at a fixed
price paid to producers. Until 1951, the majority of the marketing board’s profits
were absorbed by the reserves of the board. In that year, however, taxes were raised
and cocoa profits were diverted to general public investment.
Internal self-government was ceded to Ghana in 1951, and the country’s first
leader, Dr. Kwame Nkrumah, attempted to foster rapid economic and social development by investing reserves that had accumulated during the Second World War
416
Distortions to Agricultural Incentives in Africa
and cocoa earnings that were boosted by the commodities boom induced by the
Korean War.
Postindependence, 1957–83
Ghana’s economic performance after independence in 1957 was undermined by
political instability, ideological splits, and policy reversals.
At independence, Ghana had one of the highest per capita incomes in Africa,
placing it on a par with middle-income countries by today’s standards. The country was the world’s largest producer of cocoa and had external reserves equal to
three years of imports. Cocoa prices began to decline significantly after 1957, yet
the government continued to spend money on a large scale, even when revenues
fell, and from about 1961 onward became more heavily involved in central planning, rather than limiting spending to public goods.
In 1961, the Cocoa Marketing Board was granted a monopoly on all purchases
of cocoa from farmers in Ghana, replacing the existing network of private agents,
traders, brokers, and other middlemen. Despite falling cocoa prices, substantial
increases in production as a result of new planting meant that Ghana’s export revenues remained relatively constant. Because production and marketing costs
increased with the expansion of output, profits were squeezed and government
revenues declined. With rising imports for public investment, Ghana’s current
account deteriorated and its foreign exchange reserves dwindled. In response, the
government introduced foreign exchange controls and import licensing. From
1961, public spending shifted away from the provision of public goods toward the
development of large state-owned enterprises (SOEs) designed to substitute
domestic production for imports.
When world cocoa prices collapsed in the second half of 1964, the only way the
government could meet its expenses was by printing money. This move fueled
inflation and lowered real wages, thereby undermining support for the Nkrumah
regime, which was ousted by a military coup in February 1966. By this time, per
capita GDP was not much higher than it had been in 1951. After a brief adjustment of policies, government was handed over to the democratically elected Kofi
Abrefa Busia (1969–71). He too was ousted by the military, whose (corrupt) rule
and continued mismanagement of the economy further depressed real incomes
between 1972 and 1979. The deteriorating economic and political situation eventually led to a coup by junior members of the armed forces, led by Flight Lieutenant Jerry J. Rawlings. A brief return to civilian rule (1979–81), marked by ineffectiveness and allegations of corruption, was ended by Rawlings’ second coup
and the establishment of the Provisional National Defense Council in 1981.
Rawlings’ government embarked initially upon a course of populist policies,
but after two years it became apparent that these policies would not arrest the
Ghana
417
country’s economic decline. In addition to the already serious economic and
political situation, Ghana faced drought and bushfires in 1983 as well as the forced
return of more than 1 million Ghanaians from Nigeria.
The nadir was reached in 1983. At the root of this collapse lay unsustainable
levels of government expenditure, an increasingly overvalued exchange rate,
import licensing, inflation and price controls, and heavy state involvement in the
running of the economy (Tsikata 1999; Leith and Söderling 2000). For example, in
1984, about 2.5 percent of the population was employed in the civil service, one of
the highest ratios in Africa at the time. Public enterprises and boards employed
another 2 percent. Preliminary audits conducted in 1986 indicated that tens of
thousands of “ghost workers” were on the public sector payroll (Alderman, Canagarajah, and Younger 1993).
Agricultural policy (discussed later) was fundamental to the dissolution of the
Ghanaian economy in the early 1980s. In particular, cocoa prices were falling, and
the overvaluation of the cedi implied that the domestic currency equivalent of the
fob (free on board) export price of cocoa was falling faster still, exacerbating the
struggle between farmers and the government over cocoa revenue. This situation
was further aggravated by the rising costs of the Cocoa Marketing Board and by
the smuggling of cocoa to neighboring countries where producer prices were
much higher at the black market exchange rate (Stryker 1990). The result was a
steadily deteriorating economic situation and widespread rent seeking, which
increasingly undermined Ghanaian institutions and society.
By the early 1980s, Ghana had been surpassed by at least half the countries of
Sub-Saharan Africa in per capita GDP. Government revenues fell from 15 percent
of GDP in the early 1970s to 6 percent in 1982. Public sector wages fell by an
annual average of 10 percent in real terms between 1975 and 1983. Export earnings fell to a low of 7 percent of GDP, and external financing dried up. Moreover,
price controls led to much economic activity taking place in parallel markets and
to a general shortage of goods and services.
Reform and adjustment, 1983–92
The government responded by introducing a number of ad hoc programs to deal
with the emergencies and in April 1983, under the auspices of the IMF and the
World Bank, initiated a program of economic stabilization and market reform
known as the economic recovery program. The reform strategy included a
realignment of relative prices, the removal of direct controls and interventions, a
restoration of fiscal discipline, and the implementation of structural and institutional reforms. It also reinstated the necessary fundamentals for economic
growth. In conjunction with increased inflows of external financing, real GDP
rose by about 4 percent per year between 1983 and 1992.
418
Distortions to Agricultural Incentives in Africa
Of central importance to the economic recovery program was exchange rate
policy. By 1982, the cedi was estimated to be overvalued by 1,000 percent (Leechor
1994). In April 1983, the government established a multiple exchange rate system,
which was abolished six months later in October. Following a series of devaluations, a public auction system was established in 1986 for most transactions that
did not involve cocoa, petroleum, and official debt service. In February 1987 the
official and auction exchange rates were unified. Devaluation rapidly lowered the
black market premium, and the introduction of foreign exchange auctions with a
gradual move to a managed exchange rate virtually eliminated it by the 1990s.
The budget was balanced by 1986, thanks to stronger government revenues
deriving from exchange rate and tax reforms. With improved fiscal discipline and
lower government financing needs, monetary growth was also kept in check.
Inflation was thus brought under control, falling from 123 percent in 1983 to
10 percent in 1992. But it was difficult to sterilize inflows of foreign assistance,
which became increasingly important from the mid-1980s onward, and so inflation was not fully tamed. Moreover, fiscal and monetary discipline started to
weaken in the run-up to elections in 1992.
State-owned enterprises were a major area for reform. In the mid-1980s more
than half of value added and employment was reported to be in SOEs. But reform
proved more complex for both practical and political reasons, and not until 1990
were any sell-offs actually made. Similarly, financial reforms involved an evaluation of nonperforming loans and a deregulation of credit and interest rates. However, the reform of rural banks proved difficult.
Despite pursuing populist policies, the Rawlings government did not incur
debt, but with the adoption of more orthodox economic management, foreign
governments and multilateral agencies were increasingly eager to invest in Ghana.
As a result, the ratio of debt to GDP increased from 41 percent at the outset of the
economic recovery program to 63 percent at the end of the decade, and to 85 percent by the mid-1990s.
1992–2004
When democratic elections were held in 1992, several politically sensitive and
administratively complex reforms that remained unfinished became subject to the
vagaries of electoral competition. These included the reform of the cocoa sector, the
divestiture of state-owned enterprises, and the establishment of effective tax collection and expenditure control systems for government (Leith and Söderling 2000).
With civilian rule, government expenditures continued to rise and the public
deficit mounted. A significant share of this deficit was financed by printing
money, which led to a surge in consumer price inflation. From 1994 onward, there
Ghana
419
was also significant borrowing from abroad (more than 3 percent of GDP).
Accordingly, the ratio of total external debt to GDP spiraled from 88 percent in
1994–96 to 119 percent in 2000–02, although by 2004 it was down to 80 percent.
Through the 1990s, debt service as a ratio of export earnings averaged 25–30 percent, which exceeds the 20–25 percent level that is deemed to be sustainable under
the Heavily Indebted Poor Countries Initiative. However, the ratio dropped significantly in the early 2000s and was down to 7 percent by 2004 (World Bank 2006b).
With a market-determined exchange rate and a weakening fiscal position, the
real exchange rate depreciated sharply in the early 1990s (table 15.1). This stimulated export growth, with the share of exports to GDP increasing to rates comparable to those in the 1960s before exchange controls started to bite in 1995. Yet the
substantial financing of the government’s budget by transfers from foreign donors,
foreign borrowing, and a surge in private remittances meant that the rapid depreciation of the real exchange rate had little dampening effect on imports.
The government had difficulty in constraining the public deficit and, with limited domestic savings, the balance of payments deficit. A value added tax was
introduced in 1986, only to be withdrawn shortly afterward following protests. It
was successfully reintroduced in 1998 but at a lower rate (10 percent compared
with an original proposal of 17.5 percent). The tax actually replaced a sales tax
but was applied on a broader base and linked to improved record keeping and
enhanced compliance. As a result, revenues ultimately increased. A constitutional
amendment passed in 2002 made it illegal for expenditures to exceed revenues by
more than 10 percent.
A structural problem arose when support for the SOEs was removed—the private sector did not have the capacity to fill the gap, and many services were not
provided. One might ask if a phased government withdrawal, through publicprivate partnerships, may not have been more appropriate. In that context, the
initially slow pace of privatization may have been a blessing. The divestiture of
SOEs gathered pace in the 1990s and has been favorably reviewed (Ghana Divestiture Implementation Committee 1997).
Only in the late 1990s were the nonperforming assets of the economy tackled.
In 1998, 23 of the 133 rural banks that were in operation had their licenses withdrawn (Leith and Söderling 2000). But human capital remained a problem for
rural banking, with the result that management was still often poor, and rural
banks continued to accumulate bad debts.
After 1992, modifications made in trade policy were relatively minor. In the mid2000s, Ghana had a relatively simple tariff structure, comprising three rates: a low
rate of zero (with some items recently raised to 5 percent) reserved primarily for primary products, capital goods, and some basic consumer goods; a moderate rate of
10 percent applied primarily to other raw materials and intermediate inputs, as well
420
Table 15.1. Trade and Exchange Rate Performance, Ghana, 1966–2004
Trade indicator
Exports of goods and services (percent of GDP)
Exports of goods and services (annual percent growth)
Trade (percent of GDP)
Official exchange rate (LCU per US$, period average)
Real effective exchange rate index (2000 100)
Black market premium (percent)
Source: World Bank (2006a).
Note: — no data are available. LCU local currency unit.
1966–70 1971–75 1976–80 1981–85 1986–90 1991–95 1996–2000 2001–04
19
1.9
39
0.9
—
72
19
2.8
38
1.2
—
35
11
7.9
22
1.9
802
367
7
1.6
14
21
1,306
1,289
18
9.2
42
208
190
47
21
7.1
53
722
139
3
36
12.3
87
2,825
137
1
41
1.1
97
8,196
101
0
Ghana
421
as to some consumer goods; and a higher rate of 20 percent, mainly on final consumer goods. In addition, imports could be exempted from import duties under
several programs, and manufacturers could apply for permission to import raw
materials and intermediate inputs at concessionary duty rates. Zero-rated goods
accounted for an estimated 13.5 percent of imports (Haizel et al. 2002). In addition,
Ghana did not differentiate between imported and locally produced commodities in
its domestic indirect taxes, so there were no distortions in this area.
In 1999, Bajracharya and Flatters argued for more comprehensive tariff
reforms, suggesting that additional revenues could be obtained by tightening
exemptions, adjusting the tariff rate structure, and making administrative
reforms. They concluded that the greatest potential for revenue improvement, as
well as for significantly enhanced trade facilitation, was most likely to be found in
administrative reform of customs and related procedures; they suggested that revenue increases of 20 percent were possible (on a base that included import-related
excises and value added taxes as well as import duties). Inspection agencies
charged a 1 percent fee for these services, and an ECOWAS (Economic Community of West Africa States) customs duty of 0.5 percent is levied on imports from
non-ECOWAS countries.
In a subsequent review undertaken for the United Kingdom’s Department of
International Development (Haizel et al. 2002), it was similarly concluded that
low tariffs could enable Ghana to abolish the duty drawback and would help
ensure fairness, transparency, consistency, and efficiency in customs administration. The study also noted the need to improve port clearance and turnaround
time, a point reinforced in a World Bank study (World Bank 2006a), which noted
that it took an average of 55 days for imported goods to clear customs and reach
factory warehouses, and an average of 47 days for exports to leave the factory and
clear the port of exit. That was much longer than the efficient benchmark (5 days
for exports and imports in Denmark), and also substantially higher than the
recorded times in Côte d’Ivoire, Nigeria, Senegal, and Togo.
In overall terms, the policy environment in Ghana in the mid-2000s contrasted
sharply with that prevailing up to 1983. Yet policy reforms had not been fully consolidated, nor had they been accompanied by the structural reforms needed to
make them work. As a result some reform fatigue had set in, along with some
questioning of the process itself. A loss of momentum could threaten improvement in the design and implementation of reforms.
Economic performance
In the early 2000s, growth was holding steady at about 4–5 percent annually. With
population increasing at 2.5 percent per year, per capita income had grown
2–3 percent per year since the mid-1980s.
422
Distortions to Agricultural Incentives in Africa
With such growth rates, it is estimated that absolute poverty in Ghana could be
eradicated in 30–40 years (Hadjimichael et al. 1996). Indeed, 20 years of 4–5 percent growth has done little more than bring per capita incomes back to the levels
enjoyed in 1957, when Ghana attained independence. Recent economic performance has been more robust, with real GDP growth reaching 5.8 percent in 2004, a
percentage point above the average for 2001–03. Agriculture was the strongest
component of overall growth, with particularly strong production growth in the
cocoa sector, which has benefited from government-sponsored crop improvement
and disease control programs.
Inflation rebounded in the 1990s, reaching 60 percent in 1995 and 25 percent
in 2000 as the government failed to contain budget deficits. The government’s
overall fiscal deficit worsened to 8.2 percent of GDP in 2000, and the current
account deficit deteriorated to 10.6 percent of GDP. The real effective exchange
rate reached a corresponding low in 2000 and remained relatively stable afterward. A particular problem has been fiscal profligacy in election years and government responsiveness to special interest groups, such as doctors, cocoa board
members, railway employees, and civil servants (Leite et al. 1999). The failure to
consolidate macroeconomic stability has undermined investment and, with it, the
country’s long-term growth.
Ghana’s trade performance improved considerably after the mid-1980s. In
response to lower taxation and fewer controls, exports grew at an annual average
of 10 percent between 1984 and 1994, while imports grew at a similar pace. This
growth enabled the share of exports in GDP to recover from an average of 6 percent in 1981–85 to more than 20 percent in the 1990s and to more than 40 percent
between 2001 and 2004 (table 15.1).
Following reform, the strongest performing sectors were mining, utilities, construction, and most services, in particular transport and the wholesale-retail sector. Manufacturing grew rapidly in the 1984–86 period, but its rate of growth then
fell below the economy’s overall rate. More recently, nontraditional exports—
mainly processed and semiprocessed goods—have become increasingly important. Exports of nontraditional goods (both agricultural and nonagricultural)
increased from $24 million in 1986 to $402 million in 1998, and to $636 million in
2005; their share of total exports grew from about 5 percent to more than 25 percent over this period.
Reforms have been complemented by increased aid flows and migrant remittances. Total aid flows jumped significantly between 1989 and 1992 as donors
aimed to support institution-building activities in the run-up to the multiparty
elections set for 1992 (Tsikata 1999). More recently they have climbed again as
part of a concerted effort to accelerate growth in Sub-Saharan Africa. Private
remittances exceed the combined total of official transfers, official capital, and
Ghana
423
private capital flows, amounting to $1.3 billion, or 15 percent of GDP, in 2004
(IMF 2005) and reportedly exceeding $3 billion in 2005.
Ghana’s varied economic fortunes have been reflected in the performance and
relative importance of the agricultural sector. As the economy collapsed, agriculture
assumed an important buffer role, with its share of GDP rising to 60 percent in the
early 1980s. Since then, agriculture’s relative importance has declined, conforming
to the general pattern whereby economic development is accompanied by a shift of
resources to nonagricultural activities. Yet at one-third of national income, agriculture was still almost as important as it had been 40 years earlier. Agricultural growth
was, equivalently, slower than growth in other sectors, partly reflecting the aforementioned shift of resources between sectors, and partly as a consequence of lower
commodity prices. Since 2001, agricultural growth on average matched the overall
growth rate of 5 percent, as commodity prices have recovered.
Poverty
On the basis of the Ghana Living Standards Survey data and a food poverty line
set at the estimated annual expenditure per person required to meet minimum
nutritional requirements, the poverty incidence in Ghana fell from 37 percent in
fiscal 1991 to 27 percent in fiscal 1998. Given the rise in the population numbers,
this decline means a drop from 5.8 million to 5.0 million people faced with food
poverty. Christiaensen, Demery, and Paternostro (2002) report consumption
poverty indexes for 1992 and 1998 of 51 and 39 percent, respectively, based on the
food intake required to meet a minimum caloric intake with adjustments for
essential nonfood consumption.
There were large rural and regional differences in poverty levels and their
changes. Poverty fell steeply in greater Accra and other regions but increased in
the central, northern, and upper eastern regions. At the national level, the reduction in poverty resulted almost entirely from economic growth. The overall redistribution effect was negligible, although it played an important role in the Accra
region where reduced inequality helped to reduce poverty significantly (IMF
2000). Worsening inequality elsewhere, especially in the urban coastal region,
offset this positive development.
The economic recovery program and the resulting economic growth led to significant improvements for households engaged in export farming and for those in
formal employment, in both the public and private sectors. Households in the food
crop farming sector continued to perform worst, with the incidence of food
poverty falling from about 52 to 45 percent for this group between fiscal 1991 and
fiscal 1998. By fiscal 1998, households in the food crop farming sector accounted
for 65 percent of national poverty, up from 62 percent in seven years earlier,
424
Distortions to Agricultural Incentives in Africa
indicating that the recovery program primarily benefited export-oriented farmers.
Outside the export sector, agriculture grew sluggishly and, with weaker income
growth and fewer nonfarm income-earning opportunities, the welfare of food crop
farmers was negatively affected. Growing poverty was particularly prevalent in the
northern parts of the country, where farmers were most dependent on food crops
and experienced lower agricultural incomes and also lower off-farm earnings.
Agricultural Policies in Ghana
Agricultural policies in Ghana during the study period formed an important part
of the general setting of policy, and shifts in sectoral policy generally matched
reorientations in overall policy. In particular, policy toward the cocoa sector went
through dramatic changes, which had a hugely important impact on Ghana’s collapse and subsequent recovery.
Ghana’s agricultural policies before 1983 are thoroughly described by Stryker
(1990, 1991). They included price controls; input and credit subsidies; obligatory
credit allocations; and heavy state involvement in production, distribution, and
marketing. As with economic policy in general, 1983 saw a completely new
approach to agricultural policies. The government privatized state farms, removed
price controls, and gradually reduced subsidies on inputs such as fertilizer. In
1990, the government removed the guaranteed minimum price paid to farmers
for selected food crops (mainly maize and rice) and in 1992 abolished input subsidies altogether.
Before reforms, procurement was facilitated through the Agricultural Development Board, which was set up in the 1960s to buy maize and rice at guaranteed
prices and store them in an effort to stabilize prices. This organization was superseded by the Ghana Food Distribution Corporation, which was established in
1975 and dissolved in 1987. On average, the corporation bought less than 5 percent of the maize and rice produced in the country; its effectiveness was constrained by a lack of storage facilities and weak infrastructure (Puplampu 1999).
In 1986–88, the government drafted a new agricultural policy, called the Ghana
Agricultural Policy: Action Plan and Strategies 1986–88. Key objectives outlined
in this initiative were self-sufficiency in cereals, starchy staples, and animal protein
food, with priority for maize, rice, and cassava in the short term; maintenance of
adequate buffer stocks for price stabilization and food security during shortfalls;
and improvements in institutional facilities such as research, credit, and marketing. Putting these objectives into practice proved difficult, however, in part
because of the weak institutional capacity of the country.
The government, in collaboration with the World Bank, consequently
embarked on the Agricultural Services Rehabilitation Project over the 1987–90
Ghana
425
period. The main objectives of the project were to strengthen the institutional
framework for formulating and implementing agricultural policies and programs,
improve the delivery of public sector services, and improve the procurement and
distribution of agricultural inputs by way of privatization.
The project did succeed in strengthening the capacity of agricultural research,
extension, irrigation, and policy-planning institutions. To build on these shortterm improvements, the government, with support from the World Bank, decided
to implement a more strongly resourced medium-term program, focusing on the
key areas of agricultural research, extension, livestock, fisheries development, and
export promotion. The Medium Term Agricultural Development Program covered the 1991–2000 period and was broadly aimed at increasing productivity and
competitiveness in the agricultural sector. A number of stand-alone projects were
launched under the program, such as the National Agricultural Research Program, the National Agricultural Extension Program, and the Fisheries Capacity
Building Project.
Despite the increased attention given to agriculture, growth in the sector
remained relatively sluggish throughout the 1980s and the first half of the 1990s.
The much-improved performance in the second half of the 1990s was largely a
result of the improved macroeconomic environment. Structural weaknesses, such
as inadequate roads, poor access to markets, inappropriate agricultural practices,
and low technology, were and (despite some improvements) remain key constraints to growth.
In 2003, the Ministry of Agriculture developed a Food and Agriculture Sector
Development Policy, intended to enhance food security, reduce poverty, supply
raw materials to industry, and ensure the sector’s continued contribution to economic growth, foreign exchange, and government revenue. Reflecting the market
orientation of government policies more generally, the private sector was seen to
be the main engine for delivering on these objectives. The main break with the
past was policy’s focus on a sectorwide approach to agricultural development,
contrasting with the discrete project approach pursued in the past. The new policy
was expected to contribute to Ghana’s poverty reduction strategy through infrastructure development, the promotion of appropriate technologies, and improved
extension services.
However, a 2004 Poverty and Social Impact Assessment of the strategic objectives for agricultural policy criticized the strategy as a one-size-fits-all policy that
did not take account of the diverse needs of different stakeholders in the agricultural sector, notably the very poor and women. Accordingly, a broader revision of
the policy was being developed in the mid-2000s, spelling out more clearly what a
sectorwide approach entails, providing guidance for a six-year policy plan, and
achieving consensus among stakeholders including donors.
426
Distortions to Agricultural Incentives in Africa
Cocoa policy
The government’s policy toward cocoa, the country’s biggest export earner, has
been a major component of its overall economic policy and has changed along
with the general orientation of economic policy over time.
Ghana became the world’s leading producer of cocoa by 1911, a position it
retained until the mid-1970s. By 1921, Ghana produced 32 percent of the world’s
cocoa. Small farms have always been the basis of Ghana’s production (there are
about 1.6 million small-holder farmers growing cocoa, mostly on plots of three
hectares or less) with plantations never of much importance. Until the Second
World War, private firms handled domestic and external marketing, but during
the war the colonial government took over the purchase of cocoa, selling it to the
British Food Ministry (Leith and Söderling 2000). In 1947, the Cocoa Marketing
Board was established, with a monopoly over internal and external marketing. The
influence of this board (after 1979 called the Ghana Cocoa Board, or COCOBOD)
in the industry was pervasive, covering extension services, input marketing, and
the maintenance and rehabilitation of roads in cocoa-producing villages.
Initially set up to protect farmers from price volatility, the Cocoa Marketing
Board gradually turned into an instrument of public taxation (Stryker 1990).
Rents were extracted by keeping producer prices well below the world price, and
by using an overvalued exchange rate to make payments to farmers. Inefficiency,
corruption, the increasingly poor state of roads, and the shortage of spare parts
meant that costs accounted for an increasingly large proportion of the fob export
price. In 1981, the black market exchange rate was 44 times the official rate, and
the marketing board’s costs exclusive of the price paid to producers exceeded the
fob sales at the official exchange rate. Continued inflation meant that even after
the official exchange rate was devalued during 1985 and 1986 by a factor of 33,
from 2.75 to 90 cedis per U.S. dollar, the board’s costs still accounted for 28 percent of the total value of sales (Stryker 1990).
Between 1967 and 1977, the system for purchasing and marketing cocoa gradually broke down as the economic situation deteriorated. By 1982, the amount of
unshipped cocoa was about one-half of that harvested. Smuggling had also become
increasingly attractive, with an estimated 20 percent of the crop being smuggled
out of the country in the late 1970s and early 1980s. Output had stagnated following independence and began to fall in the early 1970s. Falling world cocoa prices
from the late 1970s, aging trees, widespread disease, and poor weather (bushfires in
1983 destroyed some 60,000 hectares under cocoa) also contributed to the decline.2
Production dropped from an average of 450,000 tons to a low of 159,000 tons
in the 1983–84 growing season, when the crop was just 28 percent of the peak
1964–65 crop. Ghana’s share of the world market fell accordingly, from 36 percent
in 1965 to 17 percent in the early 1980s. It is worth noting that as a result of
Ghana
427
strengthening world prices, export revenues remained steady initially, a factor that
helped successive governments avoid painful reforms. The key sources of decline
over the longer term were the overvalued exchange rate and high taxation,
effected by means of a monopsonistic marketing board (Teal and Vigneri 2004).
By 1983, cocoa farmers received only 21 percent of the fob price.
With implementation of the economic recovery program in the mid-1980s,
agricultural policy focused on improving the terms of trade for cocoa. Producer
prices rose in part because the government raised the farmer’s share in cocoa
earnings to 40 percent by 1995 and to 50 percent by 2001 (AfDB 2002). In addition, falling inflation helped boost real producer prices. By 1988, real producer
prices had increased threefold from their low in 1984. Producer prices were also
strengthened by squeezing COCOBOD’s share in cocoa revenues from 30 percent
to 15 percent of the fob price. While the share of the producer price in the world
price has fluctuated in recent years, the real producer price has increased steadily,
helping to raise COCOBOD purchases and exports (figure 15.1).
Efforts to improve the efficiency of COCOBOD led to wide-ranging changes in
its structure and activities. Transport of cocoa shifted to the private sector after
Figure 15.1. Cocoa Production and Producer Prices, Ghana,
1964–2002
cocoa production (metric tons)
2,000,000
1,800,000
600,000
1,600,000
500,000
1,400,000
1,200,000
400,000
1,000,000
300,000
800,000
600,000
200,000
400,000
100,000
200,000
0
19
6
19 4–
6 6
19 6– 5
6 6
19 8– 7
7 6
19 0– 9
7 7
19 2– 1
7 7
19 4– 3
76 75
19 –
7 7
19 8– 7
8 7
19 0– 9
82 81
19 –
8 8
19 4– 3
86 85
19 –
8 8
19 8– 7
9 8
19 0– 9
9 9
19 2– 1
9 9
19 4– 3
96 95
19 –9
9 7
20 8–
0 99
20 0–
02 01
–0
3
0
year
production
Source: Ghana Cocoa Board (www.cocobod.gh).
real producer price
producer prices (constant 1995 cedis per metric ton)
700,000
428
Distortions to Agricultural Incentives in Africa
1984, while responsibility for cocoa feeder roads shifted to the Ministry of Roads
and Highways. A cocoa rehabilitation project was initiated in 1987 with donor
funding (AfDB 2002). From 1989, COCOBOD began phasing out input subsidies,
which led to a substantial increase in input prices over a relatively short period of
time. However, following pressure from farmer organizations, the government
reduced the price of insecticides and fungicides in 1994.
It was not until after the 1992 elections that reform of COCOBOD gained
momentum. Major changes were a reduction in staff levels from more than 100,000
in the early 1980s to 10,400 in 1995 and to just over 5,100 staff by 2003, an end to
input marketing, and the introduction of competition into internal marketing.
Licensed buying companies were set up to compete with the state-owned Produce
Buying Company. By 1996, the public company’s share of purchases had declined to
80 percent and by 2001 to 37 percent. Monopsonistic price setting by COCOBOD
remains in place.3 Liberalization of COCOBOD’s export monopoly started in 2001,
and licensed buying companies can now export 30 percent of their cocoa purchases
directly to external buyers. However, a minimum tonnage requirement has meant
that only nine of the companies qualified, and none actually marketed externally.
The reforms had an impact. In 2004, the cocoa sector accounted for 7.8 percent
of GDP and contributed 21 percent of exports. Strong growth in the cocoa sector
resulted primarily from government assistance and favorable weather conditions.
The former included free mass spraying of cocoa farms, which reduced the incidence of pests and diseases, especially black pod, swollen shoot disease, and capsid
insect attack; a steady increase in the farmer’s share of the export price; rehabilitation and replanting of old farms with new varieties; and road rehabilitation work
in cocoa-growing areas, which facilitated transport and reduced costs (USDA
2005; ISSER 2005). The public dissemination of higher-productivity, fastermaturing tree varieties played an especially important role in helping farmers
respond to the new policy environment (Edwin and Masters 2005).
The growth of Ghanaian cocoa exports also reflected the influx of cocoa smuggled from Côte d’Ivoire, partly as a result of that country’s civil conflict. The
inflow is estimated to have been between 120,000 and 150,000 metric tons in
2004. However, cocoa from Côte d’Ivoire is of inferior quality, and the smuggling
may have contributed to a fall in the premium that Ghanaian cocoa receives—
typically between $50 and $80 a ton—to about $20 a ton. Maintaining quality is
the responsibility of the COCOBOD’s Quality Control Division, which carries out
inspection, grading, and sealing of cocoa for the international and local markets.
Of increasing economic importance are exports of processed cocoa products,
in particular cocoa butter, liquor, powder, and cake. In 2005, Ghana had a processing capacity of 145,000 metric tons, and export earnings from these products
tripled between 1992–94 and 2002–04, from $32 million (about the level achieved
in the early 1970s) to $102 million (FAO 2008).
Ghana
429
The government’s policy with regard to producer prices is to reach a level of
70 percent of the world price. Price distortions persist partly because producer
prices are not allowed to adjust quickly in response to upward movements in
world prices. Cocoa supply is expected to increase gradually, especially if price
incentives are coupled with improved husbandry techniques, pest control, and
adequate transportation infrastructure. The ability of licensed buying companies
to generate competition has yet to be determined. Seini (2002) reports that these
companies rarely pay more than the government producer price. Moreover, their
role in the export market is limited by their inability to operate beyond a minimum scale. However, support for full liberalization of the sector is also limited by
concerns over quality—an issue in which both producers and buyers have a stake.
Measuring Distortions to Agricultural
Incentives
It is clear from this discussion that government policies have had a strong impact
on the price incentives facing producers in Ghana. This section assesses the extent
of those price distortions over the past half century. Our focus is on governmentimposed distortions that create a gap between actual domestic prices and the
prices that would have existed under free markets (see Appendix A in this volume
and Anderson et al. 2008). Because the characteristics of agricultural development
cannot be understood from a sectoral view alone, the project’s methodology not
only estimates the effects of direct agricultural policy measures (including distortions in the foreign exchange market) but also generates estimates of distortions
facing nonagricultural producers for comparative evaluation. More specifically,
this study computes a nominal rate of assistance (NRA) for farmers. It also generates an NRA for nonagricultural tradables, which can be compared with the rate
for agricultural tradables through the calculation of a relative rate of assistance
(RRA).
Price distortions are measured for four tradable crops: cocoa, rice, maize, and
groundnuts. The presence or absence of support for three nontraded or lightly
traded staples (cassava, plantains, and yams) is assessed as well. Collectively, these
seven crops account for more than 70 percent of the value of agricultural production in Ghana (figure 15.2).4
The net trade positions of these commodities are diverse. Cocoa is Ghana’s
main agricultural export; rice is the main imported food commodity; maize has
traditionally been imported, but there was an exportable surplus in some recent
years; and groundnuts were for many years not traded internationally but became
a significant export in the 1990s. Cocoa, rice, and maize were included in Stryker’s
analysis, which considered the period up to 1985 and found evidence of extensive
distortions in all three sectors.
430
Distortions to Agricultural Incentives in Africa
Figure 15.2. Composition of Farm Production at Distorted
Domestic Price, Covered Products, Ghana, 1966–2003
100
90
80
percent
70
60
50
40
30
20
10
98
20
00
20
02
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
19
78
19
76
19
74
19
72
19
70
19
68
19
19
19
66
0
year
residual
plantain
rice
cocoa
groundnut
cassava
maize
yam
Source: Compiled by the authors using FAOSTAT producer price and quantity data.
The cocoa sector was heavily mismanaged, and only a minor share of the
export price was returned to the producer. COCOBOD’s share of export earnings
declined somewhat in the 1990s, but as cocoa prices strengthened in the early
2000s, that share rose again. Export tax payments made by COCOBOD to the
government declined from an average of 40–50 percent of fob earnings during the
mid-1990s to less than 10 percent by 2004. This decline further allowed COCOBOD to increase its retained share of the export price, with the result being a
much milder reduction in the implicit taxation of the Ghanaian producer
(Brooks, Croppenstedt, and Aggrey-Fynn 2007, appendix figure 6).
Before the mid-1980s, rice producers received less than the imported price (at
the farmgate) suggesting some implicit taxation, while maize producers’ prices
were at a similar level to imported prices (again, compared at the farmgate). In
both cases, domestic prices increased sharply in the mid-1980s, but the degree of
price protection to producers since diminished to levels somewhat higher than the
statutory import tariff of 20 percent. The evidence for rice and maize thus points
to significant protection of import-competing commodities. In the case of
groundnuts, the product became a significant export in recent years, and producers received slightly less than the export fob price (Brooks, Croppenstedt, and
Ghana
431
Aggrey-Fynn 2007, appendix figures 7 and 8). There is no evidence of direct policy
interventions in the markets for staples such as cassava, plantains, and yams.
These observations are reflected in table 15.2, which shows NRAs for the four
tradable crops computed at an estimated “equilibrium” exchange rate. Protection
for import-competing crops (rice and maize) declined in the second half of the
1990s but reemerged in the early 2000s.5 Disprotection (that is, taxation) of exports
of cocoa beans declined steadily until the latter 1980s. Further reforms through the
1990s lowered the rate of implicit export taxation to less than 20 percent.
Figure 15.3 shows that history back to 1955 but groups products according to
their net trade status.6 Importable crops were effectively taxed before the economic collapse of the early 1980s. From the period of adjustment until the 1992
elections, significant protection was provided, with the NRA averaging more than
60 percent. This protection was mostly dismantled in the 1990s, but those reforms
were not secured. Exports of cocoa beans were heavily taxed in the years between
independence and the crisis that precipitated reforms and adjustment (1958 to
1982). The tendency to tax exportables diminished over time but remained significant, with an NRA averaging close to 20 percent in the period 1995–2004.
When nontradables are factored in, the overall pattern is one of very low net taxation of agriculture before independence in 1957, heavy net taxation in the period
after independence, and an overall balance declining to almost zero in recent
years. This net balance masks a consistent tendency to tax exports and protect
imports.
For much of the postindependence period, exchange rate distortions had an
important impact on producers’ incentives. Based on the assumed equilibrium
exchange rate, the cedi was overvalued by 13 percent between 1958 and 1982, with
the degree of overvaluation falling to 8 percent between 1984 and 1992. Overvaluation taxed producers of exportables and increased the degree of price protection
provided through quantitative restrictions to import-competing products. In the
case of cocoa beans, exchange rate overvaluation accounted for a significant share
of implicit taxation before 1992. For import-competing products, the net taxation
before the crisis would have been more severe but for overvaluation, while some
of the high protection provided between 1984 and 1992 is explained by overvaluation. From 1992 onward, the foreign exchange market functioned freely, so the
NRA estimates reflect direct sector-specific distortions.
Continued protection of nonagricultural sectors has reinforced the discrimination against exportables throughout the period analyzed and provided disincentives for producers of nontradables. Nonagricultural protection also added to
the bias against import-competing products in the period before the crisis, when
they were effectively taxed, and dampened the degree of protection provided in
subsequent years. These impacts are reflected in the differences between the NRAs
and RRAs (table 15.3) and are illustrated in figure 15.4.
432
Table 15.2. NRAs for Covered Farm Products, Ghana, 1955–2004
(percent)
Product indicators
Exportablesb,c
Cocoa
Import-competing productsb,c
Rice
Nontradablesb
Yams
Cassava
Plantains
Mixed trade statusb
Maize
Groundnuts
Total of covered productsb
Dispersion of covered productsd
Percent coverage (at undistorted prices)
1955–59 1960–64 1965–69 1970–74 1975–79 1980–84a 1985–89 1990–94 1995–99 2000–04
14.1
14.1
12.1
6.3
0.0
0.0
0.0
0.0
23.7
23.7
10.4
27.9
0.0
0.0
0.0
0.0
57.3
57.3
13.6
36.9
0.0
0.0
0.0
0.0
49.6
49.6
0.3
15.1
0.0
0.0
0.0
0.0
80.9
80.9
0.1
21.3
0.0
0.0
0.0
0.0
83.2
83.2
40.2
26.6
0.0
0.0
0.0
0.0
56.6
56.6
69.4
79.6
0.0
0.0
0.0
0.0
36.2
36.2
33.2
21.7
0.0
0.0
0.0
0.0
19.4
30.9
13.2
10.9
0.0
0.0
0.0
0.0
19.6
21.7
35.8
30.9
0.0
0.0
0.0
0.0
14.2
0.0
7.0
11.4
73
4.1
0.0
13.5
19.4
73
1.3
0.0
28.2
30.2
74
6.7
0.0
23.0
29.0
69
21.3
0.0
41.0
47.9
66
56.2
0.0
32.5
69.6
71
66.1
0.0
8.3
56.3
82
38.5
0.0
3.1
26.2
77
3.8
14.4
4.6
17.2
78
39.0
14.7
2.4
25.5
80
Source: Data compiled by the author.
a. Data for 1983 are omitted because they are unreliable.
b. Weighted averages, with weights based on the unassisted value of production.
c. Mixed trade status products included in exportable or import-competing groups depending on their trade status in the particular year.
d. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
Ghana
433
Figure 15.3. NRAs for Exportable, Import-Competing, and All
Farm Products, Ghana, 1955–2004
200
150
percent
100
50
0
50
100
19
55
19
58
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
150
year
import-competing products
exportables
total
Source: Data compiled by the authors.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontaxable products and non-product-specific assistance are also included.
The final rows of table 15.3 show what the key indicators would be had
exchange rate distortions not been taken into account. Those numbers reinforce
the point that the exchange rate distortions contributed very significantly to agriculture’s overall negative NRA and to the negative RRA from the 1960s to the
1980s.
Market deficiencies affecting the agricultural sector
Ghana’s agricultural sector also suffers heavily from implicit distortions in the
form of market underdevelopment. In particular, transport costs are high (prohibitively so for many small-scale farmers with a potential surplus to sell), while
credit is expensive, with formal interest rates of 25 percent or more, and effectively
unavailable for most producers without established links to international markets.
Moreover, there are few signs of improvement in Ghana’s social infrastructure and
in the development of human capital. In the early 2000s, less than 18 percent of
the country’s roads were paved and their condition had deteriorated over recent
434
Table 15.3. NRAs for Agriculture Relative to Nonagricultural Industries, Ghana, 1955–2004
(percent)
1980–84a
Indicator
1955–59 1960–64 1965–69 1970–74 1975–79
1985–89 1990–94 1995–99 2000–04
NRA, covered products
NRA, noncovered products
NRA, all agricultural products
Trade bias indexb
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAc
Memo item, ignoring exchange
rate distortions:
NRA, all agricultural products
Trade bias indexb
RRAc
7.0
2.7
4.4
0.22
9.3
3.7
12.5
13.5
3.2
9.0
0.34
16.6
1.5
18.0
28.2
3.6
19.8
0.59
38.8
0.3
38.4
23.0
3.2
14.9
0.53
28.9
2.7
30.8
41.0
3.5
25.6
0.79
50.2
5.5
47.5
32.5
3.2
21.2
0.84
39.9
0.1
39.3
8.3
3.4
6.3
0.69
17.3
1.0
18.7
3.1
2.7
1.7
0.46
5.7
3.8
9.2
4.6
2.6
3.0
0.32
8.8
3.4
11.7
2.4
2.6
1.4
0.37
3.3
5.2
8.0
3.4
0.19
10.9
1.1
0.11
6.2
8.6
0.22
21.9
10.6
0.39
25.4
8.2
0.42
24.5
0.7
0.05
5.4
0.7
0.53
7.3
1.4
0.44
8.5
2.9
0.31
11.6
1.4
0.37
8.0
Source: Data compiled by the authors.
a. Data for 1983 are omitted because they are unreliable.
b. Trade bias index is TBI (1 NRAagx兾100)/(1 NRAagm兾100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and exportable
parts of the agricultural sector.
c. The RRA is defined as 100*[(100 NRAagt )兾(100 NRAnonagt) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural and
nonagricultural sectors, respectively.
Ghana
435
Figure 15.4. NRAs for Agricultural and Nonagricultural
Tradables and the RRA, Ghana, 1955–2004
20
10
0
percent
10
20
30
40
50
60
70
19
55
19
58
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
80
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the authors.
Note: For a definition of the RRA, see table 15.3, note c.
years (World Bank 2006b), while the country’s railway network was almost nonfunctional (OECD 2003).
One positive development for farmers is the advent of mobile phone use, with
usage increasing from 6.6 users per 1,000 population in 2000 to 78.2 per 1,000 in
2004. Health and education show few signs of improvement. Public health expenditures declined from 1.9 percent of GDP in 2000 to 1.4 percent in 2003 (World
Bank 2006a). Male and female literacy improved somewhat since the early 1980s,
but the rate of improvement has stalled, and concerns have been raised about the
quality of both primary and secondary education and the particularly low rate of
primary school enrollment in northern rural areas.
The determinants of policy changes
Before the adoption of liberalizing reforms in 1983, any attempts by the government to influence farmers’ incentives through price policy were ineffective,
because the available policy instruments could not offset the huge distortions
deriving from the conjunction of high inflation and a fixed exchange rate. Accordingly the government tried to influence the allocation of resources through
436
Distortions to Agricultural Incentives in Africa
import licensing, exchange controls, marketing board operations, input distribution, and the direct allocation of credit. The government also spent heavily on
projects and public investments. This policy environment created enormous
scope for arbitrage between informal markets and formal, government-controlled
channels and led to rent seeking on a massive scale.
The importance of political connections in the pre-1983 environment led to a
strong bias in favor of large farmers with contacts and influence. As Stryker put it,
“government regulations were subverted, graft and corruption were rampant, and
patron-client relations became entrenched as the principal means by which most
people could gain access to scarce goods and services” (Stryker 1991, p. 116).
Rawlings came to power as a populist leader dedicated to cleaning up government, but his attempts to reduce rent seeking were counterproductive because
they did not deal with the fundamental problem of distorted incentives. Once a
decision was made to liberalize the economy and reduce price distortions, however, the incentives for rent seeking diminished.
From 1983 onward, the imperative was to resurrect the macroeconomy, and
the government signed up to IMF and World Bank-led programs. International
financial institutions thus played a key role in policy setting through the remainder of the 1980s, first through the economic recovery program and then through
subsequent structural adjustment programs. National lenders, as joint underwriters of reform, also had significant input. While lenders and donors broadly supported the macroeconomic tenets of reform and adjustment, they had a specific
interest in ensuring that money was spent on worthwhile projects and public
investments. This meant additional focus on the microeconomics of development
policies, as well as macroeconomic distortions and price incentives.
An increasing focus on microeconomic incentives coincided with a refinement
of orthodox policy thinking in the 1990s, with undistorted price signals seen as a
necessary but by no means sufficient prerequisite for economic development.
Outside the international financial institutions, a number of lenders and nongovernmental organizations started to argue for a fresh look at infant industry
arguments for agricultural protection in developing countries. However, until
recently donors consistently neglected agriculture. The need to devote more
resources to agricultural development has been formally recognized, but that has
so far not been reflected in foreign aid flows.
In contrast to the World Bank and IMF, the World Trade Organization (WTO)
has had little direct impact on policy in Ghana. As a signatory to the General
Agreement on Tariffs and Trade, Ghana was a founding member of the WTO and
acceded with “least developed country” status. Accordingly, it established ceiling
bindings of 99.5 percent on agricultural tariffs. Ghana’s highest applied rate now
stands at 20 percent, and there is little reason to expect tariffs to be constrained by
the ceilings at this time.
Ghana
437
Policies in Ghana have never been fully liberalized, but after the most profound
policy distortions were removed and the economy recovered, the pace of
growth—and associated poverty reduction—has been disappointing compared
with the experience of other developing countries outside Africa. Two alternative
views of the situation reflect a controversy about the policies needed to stimulate
growth in Africa more generally. One posits that liberalizing reform needs to be
pushed through all the way but accompanied by more effective policies to facilitate adjustment and improve competitiveness. The other contends that the
process of liberalization itself should be addressed selectively and with circumspection. While the experience of massive intervention left such policies totally
discredited, there is a divergence of views, both within Ghana and among donors,
on the direction that policy should now take.
In agriculture, Ghana’s experience with its most recent agricultural development and poverty reduction strategies, and their associated review mechanisms,
illustrates the difficulty of achieving consensus among stakeholders when few of
those stakeholders hold to ideological certainties. One important issue is that
agriculture is affected by policies in other sectors, where reforms have also lost
momentum. In particular, further reforms to financial markets could help
increase the flow of credit into the farm sector.
Prospects and Policy Options
Ghana’s major current challenge is to choose appropriate investments that can
raise productivity and growth from the 4–5 percent of the last 25 years to the
6–8 percent target set out in the poverty reduction strategy. In the 50 years since
independence, Ghana’s economic growth has been circumscribed by currency
overvaluation, excessive state interventions, excess demand (and repeated painful
adjustments), discrimination against sectors in which the country holds a comparative advantage (notably cocoa), and suppression of the financial sector. Of
these problems, the first two—heavily emphasized in Stryker’s examination of
Ghana’s trade, exchange rate, and agricultural policies through the mid-1980s—
have essentially been resolved. Progress on the latter three has been positive but
more fitful. In short, Ghana has not fully addressed the policy deficiencies that
have constrained growth for half a century. On the other hand, the transition to a
stable democracy has made policy making a more transparent and consistent
process, itself a major accomplishment.
The current study shows that policy biases have been reduced but not eliminated: import-competing producers continue to receive significant protection,
and COCOBOD continues to extract significant rents from farmers. However,
there appears to be little appetite for fully eliminating distortions, because of
concerns about the ability of farmers to compete and about the implications of
438
Distortions to Agricultural Incentives in Africa
further tariff reductions for government revenue. Greater emphasis is attached,
arguably with good reason, to boosting investments that can address structural
weaknesses and thereby improve competitiveness and reduce poverty.
A difficulty with the investment-oriented approach—and one identified in the
assessment of the government’s 2003 agricultural development program—is that
policies that improve competitiveness generally may not be pro-poor, either
because they are geared toward the most viable farmers or because they intensify
competitive pressures and the gap between modern commercial producers and traditional farmers. Thus, current policy debate, as in many other African countries,
revolves around how to reconcile structural adjustment with poverty reduction.
Some broad principles should be able to guide policy design in Ghana. First is
a need to address the structural weaknesses that impede development. These
include a weak manufacturing sector, including in agriculture-related industries
such as food processing, and a lack of outward orientation in potential export sectors. These weaknesses derive in part from deficient investment in public goods,
such as transport systems and education and training, and from market failures
that are inherently correctable (for example in the financial sector). Agriculture is
also plagued by specific structural problems, including small and fragmented
agricultural land holdings, weak organization at the farm level (notably a lack of
grassroots institutions), unsuitable technologies, and a dearth of agricultural
lending. These are key areas where government intervention, specifically to correct market failures, could be of benefit. The importance of, indeed the relevance
of, eliminating Ghana’s outstanding policy distortions needs to been seen in the
context of these broader strategic needs.
Notes
1. The value of assistance under the Heavily Indebted Poor Country Initiative was about half that
of loans and grants in 2002–03.
2. In 1983–84, farmers were provided with seedlings to replace trees lost in the drought and trees
more than 30 years old (about one-quarter of all trees).
3. Cocoa producer prices (and related rates and fees in cocoa purchasing and marketing) are fixed
by the Producer Price Review Committee, made up of representatives of the cocoa farmers; licensed
cocoa buyers; cocoa haulers; the Ministry of Finance (the minister of finance is the chairman of the
committee); the Bank of Ghana; the Institute of Statistical, Social, and Economic Research of the University of Ghana, Legon; and COCOBOD officials.
4. For rice and maize, international reference prices are converted into local currency at the black
market exchange rate on the assumption that importers must obtain hard currency at that price. Note
that maize was exported in some recent years, but by then the official and black market exchange rates
had converged. Conversely, producers of cocoa beans and groundnuts are assumed to have been
obliged to convert their foreign currency earnings into cedis at the official exchange rate but implicitly
allowed to sell half their foreign currency earnings on the parallel market. To measure the extent of
exchange rate distortions, and to gauge the sensitivity of the NRAs to the particular choice of exchange
rate, all NRAs are computed at an estimated equilibrium exchange rate corresponding to a weighted
average of the official and black market rates (see Anderson et al. 2008 for a discussion).
Ghana
439
5. Maize was exported between 1996 and 1999. Given the absence of export subsidies, import protection was therefore redundant in these years.
6. Data for 1983 are dropped from the analysis. In this year, the economy and trade collapsed, and
domestic and international price comparisons are not reliable.
References
AfDB (African Development Bank). 2002. “Ghana: Cocoa Rehabilitation Project: Project Performance
Evaluation Report.” AfDB, Tunis.
Alderman, H., S. Canagarajah, and S. D. Younger. 1993. “Consequences of Permanent Lay-off from
Civil Service: Results from a Survey of Retrenched Workers in Ghana.” Cornell Food and Nutrition
Policy Program Working Paper 35, Cornell University, Ithaca, NY.
Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675–704.
Bajracharya, R., and F. Flatters. 1999. Ghana’s Trade Policies: Exemptions from Import Duty. Washington, DC: U.S. Agency for International Development.
Bank of Ghana. 2005. “The HIPC Initiative and Ghana’s External Debt: An Empirical Assessment and
Policy Challenges.” Policy Brief (January 20). Special Studies Office, Research Department, Bank of
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Brooks, J., A. Croppenstedt, and E. Aggrey-Fynn. 2007. “Distortions to Agricultural Incentives in
Ghana.” Agricultural Distortions Working Paper 47. World Bank, Washington, DC.
Christiaensen, L., L. Demery, and S. Paternostro. 2002. “Growth, Distribution, and Poverty in Africa:
Messages from the 1990s.” Research Working Paper 2810. World Bank, Washington, DC.
Edwin, J., and W. A. Masters. 2005. “Genetic Improvement and Cocoa Yields in Ghana.” Experimental
Agriculture 41 (October): 491–503.
FAO (Food and Agricultural Organization). 2008. Food and Agricultural Organization Statistical
Databases (FAOSTAT). FAO, Rome. www.faostat.fao.org.
Ghana Divestiture Implementation Committee. 1997. Divestiture of State-Owned Enterprises in Ghana:
Summary Proceedings of a Seminar Held for Finance and Public Accounts Committees of Parliament.
Ghanaian Parliament, Accra.
Ghana Statistical Service. 2000. Poverty Trends in Ghana in the 1990s. Accra: Ghana Statistical Service.
Hadjimichael, M. T., M. Nowak, R. Sharer, and A. Tahari. 1996. “Adjustment for Growth: The African
Experience.” Occasional Paper 143. International Monetary Fund, Washington, DC.
Haizel, J. E. B., K. Yahya, G. K. Fynn, B. Y. Ntim, and J. E. Bannerman. 2002. “Tariff Review of Ghana.”
Report prepared for the Department of International Development, United Kingdom, London.
IMF (International Monetary Fund). 2000. “Ghana: Selected Issues.” IMF Staff Country Report 2.
International Monetary Fund, Washington, DC.
———. 2005. “Ghana.” IMF Country Report 05/292, International Monetary Fund, Washington, DC.
ISSER (Institute of Statistical, Social, and Economic Research). 2005. “The State of the Ghanaian Economy in 2004.” Institute of Statistical, Social, and Economic Research, University of Ghana, Legon.
Krueger, A. O., M. Schiff, and A. Valdés, eds. 1991. The Political Economy of Agricultural Pricing Policy,
vol. 3, Africa and the Mediterranean. Baltimore: John Hopkins University Press.
Leechor, C. 1994. “Ghana: Frontrunner in Adjustment.” In Adjustment in Africa: Lessons from Country
Case Studies, ed. I. Husain and R. Faruqee. Washington, DC: World Bank.
Leite, S. P., A. Pellechio, L. Zanforlin, G. Begashaw, S. Fabrizio, and J. Harnack. 1999. “Ghana: Economic
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Leith, J. C., and L. Söderling. 2000. “Ghana: Long-Term Growth, Atrophy, and Recovery.” Report
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Co-operation and Development, Paris.
Puplampu, K. P. 1999. “The State, Agricultural Policies and Food Security in Ghana (1983–1994).”
Canadian Journal of Development Studies 20 (2): 337–59.
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National Development Planning Commission. 2005. Growth and Poverty Reduction Strategy (GPRS II)
2006–2009. Accra: National Development Planning Commission, Republic of Ghana.
OECD (Organisation for Economic Co-operation and Development). 2003. African Economic
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Seini, A. W. 2002. “Agricultural Growth and Competitiveness under Policy Reforms in Ghana.” Technical Publication 61. Institute of Statistical, Social, and Economic Research, University of Ghana,
Legon.
Stryker, J. D. 1990. Trade, Exchange Rate, and Agricultural Pricing Policies in Ghana. Washington, DC:
World Bank.
———. 1991. “Ghana.” In The Political Economy of Agricultural Pricing Policy, vol. 3, Africa and the
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Teal, F., and M. Vigneri. 2004. “Production Changes in Ghana Cocoa Farming Households under Market Reforms.” Discussion Paper. Centre for the Study of African Economics, Oxford University,
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Tsikata, Y. M. 1999. “Aid and Reform in Ghana.” In Aid Effectiveness Research. Washington, DC: World
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USDA (U.S. Department of Agriculture). 2005. “Ghana: Cocoa Annual Report 2005.” GAIN Report
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———. 2006b. World Development Indicators. Washington, DC: World Bank.
16
Nigeria
Peter Walkenhorst*
Nigeria is a major player in the developing world. The federal republic, with its
140 million people, is the largest country in Africa and ninth largest in the world.
It is also one of the world’s top-10 petroleum exporters, and its proven reserves
would allow Nigeria to sustain current oil export levels for at least another
25 years. Within Sub-Saharan Africa, Nigeria’s gross domestic product is second
only to South Africa’s and is bigger than that of the other 14 members of the Economic Community of West African States (ECOWAS) combined. Nigeria also
used to be a formidable agricultural exporter. Up to the mid-1960s, the country’s
share of world agricultural exports was more than 1 percent. Nigeria had a leading
position for several of its export crops, supplying more than half of all traded
palm kernel, more than one-third of all groundnuts, and more than one-fifth of
all palm oil. However, agricultural exports collapsed as the economy shifted
toward petroleum exploitation, and by the mid-1980s, Nigeria’s world market
share for agricultural products had dwindled to less than 0.1 percent. None of the
country’s export crops, with the exception of cocoa, commands any significant
world market share.
The poor performance of Nigerian export agriculture was to a considerable
extent the result of changes in incentives facing farmers. Public neglect of agricultural infrastructure, erratic changes in agricultural policies, and distortions in the
exchange rate regime combined to create an economic environment that hampered agricultural producers while at the same time burdening consumers with
high food prices. More than half of all Nigerians lived on less than $1 a day in the
* The author is grateful for helpful comments from Kym Anderson, John Baffes, Simeon Ehui,
Marianne Kurzweil, William Masters, and Ernesto Valenzuela. Detailed data and estimates of distortions reported in this chapter can be found in Walkenhorst (2007).
441
442
Distortions to Agricultural Incentives in Africa
early 2000s (FOS 2005), and the poverty incidence exceeded 60 percent in rural
areas, where people overwhelmingly depend on agricultural activities for their
livelihood. Hence, getting agricultural incentives right is of utmost importance
not only for fostering economic development and growth but also to fight poverty
directly.
To increase the efficiency of government interventions that can foster agricultural development and poverty reduction, policy makers need detailed information on the effectiveness of past policies. The indicators of policy distortions
reported in this study aim to contribute to a better understanding of the direction
and magnitude to which policy instruments have affected incentives facing agricultural producers and food consumers over the past 50 years. In particular, the
distortion indicators attempt to measure the divergence between the price actually
paid to the agricultural producer and the price that the farmer would have
received in a distortion-free policy environment.
The findings indicate that policies toward agricultural producers have shifted
significantly over time, with support to agricultural producers first declining after
the country’s independence, then increasing between the mid-1970s and the mid1980s, before moving toward an incentive-neutral stance. The sectoral averages
hide large support differences across commodities, however. Export commodities
have consistently been explicitly or implicitly taxed, while import-competing
commodities have benefited from producer support through tariff and nontariff
barriers and, to a lesser extent, budgetary payments. In this context, recent policy
reforms toward greater regional and global trade integration promise to remove
the remaining antitrade bias and provide producers with a more market-friendly
policy environment.
The remainder of the discussion begins with an overview of economic developments and structural changes in Nigeria. The agricultural policies that were
pursued during the colonial period are briefly discussed before greater detail is
provided on agricultural and food policies since the country’s independence in
October 1960. That sets the stage for presenting quantitative indicators of
producer support and taxation and discussing the underlying policies. The final
section reflects on prospects for more agricultural and trade policy reform.
Economic Performance over Time
Nigeria’s long-term economic performance has been lackluster. Between 1950 and
2004, gross domestic product (GDP) per capita increased on average by a mere
1.1 percent per year. Similar to the general trend in Africa, economic growth fell
well short of the economic expansion in other developing regions such as East
Asia and Latin America and was only half as vigorous as worldwide growth.
Nigeria
443
The poor long-term performance results partly from the strong economic contractions that Nigeria experienced first in the run-up to and during the Biafran
war (1967–70) and then during the post-oil boom period in the early 1980s, when
rigid economic policies hampered adjustment to lower oil prices and higher interest rates (Pinto 1987). Ultimately the country pursued a structural adjustment
program (1986–94), which was sponsored by the International Monetary Fund
and the World Bank, to stabilize the economy and put it back on a growth path.
The return to a democratic government in 1999 further set the stage for greater
market orientation, and a number of fundamental economic reforms have been
initiated since 2003, such as the accelerated privatization of state enterprises and
the reduction of trade barriers.
Before independence and up until the late 1960s, Nigeria’s economy was dominated by agricultural activities in terms of the sector’s contribution to national
GDP, employment, and exports. But the discovery and commercial exploitation of
petroleum soon led to a fundamental structural transformation of the economy.
Between the mid-1960s and the mid-1970s, the share of value added generated by
the agricultural sector fell by almost half, to less than 30 percent, while the corresponding share of the fuels and mining sector expanded. The contribution of
manufacturing to aggregate value added doubled to almost 10 percent by the early
1980s but then fell back to 5 percent in the 1990s. The services sector gained in relative importance in the early years after independence but peaked at 45 percent in
1970. By the late 1980s, the share of services in aggregate value added had declined
below the 30 percent share that had prevailed in the early 1960s.
The growth of the petroleum sector at the expense of other parts of the economy, notably agriculture, is mirrored in other economic indicators. In particular,
the relative importance of agriculture as an employer started to decline markedly
in the early 1970s, and by the early 2000s, the sector’s share in total employment
had halved. The most dramatic change, however, occurred with respect to
Nigeria’s export structure. Until the mid-1960s, agricultural exports accounted for
more than 70 percent of total merchandise exports, but this share had dwindled to
less than 5 percent a decade later and has never recovered.
Within agriculture, some shifts in the pattern of production over time have
been notable. Livestock production expanded almost continuously after Nigeria’s
independence, while crop output dropped during the 1970s and early 1980s when
the economy switched toward petroleum exploitation. Because of the predominant importance of crops for feeding the growing population, domestic production of food per capita declined markedly. Subsequently, crop output and food
availability outpaced the growth of the population, and since the early 1990s,
the food per capita ratio has surpassed the level that prevailed at the time of
independence.
444
Distortions to Agricultural Incentives in Africa
Figure 16.1. Composition of Farm Production at Distorted
Producer Prices, Nigeria, 1967–2003
percent, at distorted producer prices
100
90
80
70
60
50
40
30
20
10
19
67
19
69
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
0
years
noncovered
rice
cotton
millet
cocoa
sorghum
groundnut
cassava
palm oil
yam
maize
Source: Compiled by the author, based on FAO (2006) data.
The long-term growth of agricultural output was driven mainly by root crops.
Production of cassava has more than quadrupled since the early 1960s, and the
output of yams increased nearly sixfold. In contrast, most cereals and traditional
export crops, such as cocoa, groundnuts, oil palm fruit, showed below-average
production growth. As a result, cassava and yams now account for more than
50 percent of the total value of Nigeria’s agricultural production (figure 16.1).
Policies before Independence
During the colonial period, Nigeria’s economy was largely geared toward exports
of agricultural raw materials. British administration in the country formally
began in 1861, when Lagos became a crown colony, and by 1906, present-day
Nigeria was under British control. The administration built a railroad network
and constructed roads at an accelerating rate after the 1930s. These infrastructural
investments, along with the introduction of the pound sterling as the universal
medium of exchange, facilitated export trade in cocoa, cotton, groundnuts, and
palm oil (Wells 1974). Most of this trade occurred directly with Britain: as late as
Nigeria
445
1955, 70 percent of Nigeria’s exports were destined for the home market of its
colonial power, and 47 percent of its imports originated in Britain.
Three periods during the colonial era can be distinguished (Helleiner 1966).
The first of these is the period of rapid and sustained export growth from 1900 to
1929, the second is the period of depression and wartime regulation during
1930–45, and the third is the period of slow recovery between 1945 and independence in 1960. Governmental involvement in agricultural production increased
markedly during World War II—marketing boards pegged the prices of agricultural commodities below the world market rate, workers faced wage ceilings,
traders encountered price controls, and Nigerian consumers experienced shortages of imported goods.
After 1945, agricultural prices recovered and export growth resumed. The government’s role in the economy shifted from strict control to fiscal management.
The centralized single-commodity wartime marketing boards were transformed
into regional multicrop organizations in 1954 (Oyejide 1986a), and the share of
government expenditure in GDP increased from 3.4 percent in 1950 to 6.2 percent in 1962. Capital expenditure increased notably, but the funds were allocated
mostly to social services, transport, and communication, while industry and agriculture received less than 10 percent of the investment budget. Moreover, the
funds that went into agriculture were focused on improving and enhancing
export agriculture; public authorities devoted little attention to subsistence crops
and their producers, so the majority of Nigerian farmers did not benefit from the
governmental spending programs.
Incentives and Disincentives to Agriculture
Since independence, agricultural policy in Nigeria has been characterized by
instability and inconsistency. Frequently changing governments tried to make
their mark by adopting entirely new policies and programs, so many initiatives
were formulated and scrapped in rapid succession. There was generally a lack of
focus on effective implementation, with the result that many policies were undermined by bureaucratic inertia, poor management, and corruption. Moreover,
inadequate institutional arrangements for policy and program coordination often
led to duplication of effort and inefficient resource use among agencies and ministries of the same government, between federal and state agencies, and between
agencies located in different states.
Four distinct phases of agricultural policy making can be distinguished
(Manyong et al. 2003, World Bank 2006b, Daramola et al. 2007). During the
1960s, governments continued to pursue an export-oriented, laissez-faire attitude
toward agriculture. Public policy remained largely confined to agricultural
446
Distortions to Agricultural Incentives in Africa
research, extension, and export crop marketing, with most activities and institutions being regionally based. Agriculture was the country’s major foreign
exchange earner and an important source of fiscal revenues through export taxation. The end of the decade saw a marked contraction in export agriculture, but
this development was initially seen as temporary and related to the Biafran war.
After the end of that war, and in the face of the persistent decline in agriculture,
the policy paradigm changed fundamentally: during the second phase, which
spanned 1970 to 1986, heavy governmental intervention in the agricultural sector
became the norm. There was a feeling that the increasingly serious problems of
agricultural production and food supply required strong governmental engagement, including from federal authorities. The emerging inflows of fiscal resources
from oil exports provided the government with the financial means to launch a
multitude of agricultural policies, programs, projects, and institutions. Major new
initiatives included the elimination of export taxes, the reduction of import tariffs
on agricultural inputs, the establishment of national commodity boards to administer guaranteed minimum prices, the provision of substantial subsidies for fertilizer use and other farm inputs, and the launch of agricultural credit support
schemes. These policies did not, however, yield the hoped-for benefits for agricultural development, and Nigeria evolved from a net exporter of agricultural crops to
a large-scale importer of agricultural and food products during this period. Eventually, the high fiscal spending and prevalent state control proved unsustainable
when revenues from oil exports plummeted, and government debt levels surged in
the early 1980s.
The beginning of the third agricultural policy phase coincided with the launch
of economy-wide structural adjustment reforms, as a result of which government
largely withdrew from directly controlling production activities. Government
expenditure was cut back, subsidies and price controls were withdrawn, and input
and output marketing activities were liberalized. The currency was devalued with
a view to strengthening the price competitiveness of export commodities and
import-competing goods. Moreover, trade policy reforms were implemented with
the aim of diversifying the production and export base (for example through nonfuel export subsidies) and increasing the country’s self-sufficiency for food and
agricultural raw materials, including through import bans.
The fourth phase came about with the restoration of democracy in 1999 and
has been marked by efforts to create a business environment that is conducive to
greater private investment in the agricultural sector. A new agricultural policy
strategy was published in 2001 that spelled out definitive responsibilities for the
federal, state, and local governments in an effort to remove duplicated roles and
overlapping functions. Greater control over policy implementation was
exercised—for example, through a fundamental scaling back and reform of the
Nigeria
447
nonfuel export subsidy regime that had been undermined by corruption and
fraud. Moreover, in October 2005, Nigeria adopted the ECOWAS common external tariff, which involved a substantial reduction in import duties, and reaffirmed
the country’s commitment to its regional partners to phase out the remaining special tariffs on sensitive products and quantitative import restrictions.
Methodology and data to measure agricultural distortions
Those four different policy phases presented producers with noticeably differing
distortions to prices. Using the methodology outlined in appendix A of this volume and detailed in Anderson et al. (2008), this study estimates the nominal rate
of assistance (NRA) to farmers. The main focus is on government-imposed distortions that create a gap between domestic prices and what they would be under
free markets. Hence, the analysis is based on the assumption that the economy of
the country under scrutiny, in this case Nigeria, is small relative to the world
market and hence that domestic policies do not influence international prices.
Because the characteristics of agricultural development cannot be understood
from a sectoral view alone, the project’s methodology not only estimates the effects
of direct agricultural policy measures (including distortions in the foreign exchange
market) but also generates estimates of distortions in nonagricultural sectors for
comparative evaluation. More specifically, nominal rates of assistance are computed
for farmers, including an adjustment for direct interventions in input markets,
along with an NRA for nonagricultural tradables for comparison with that for agricultural tradables through the calculation of a relative rate of assistance (RRA).
The conversion of import and export parity prices to local currency is carried
out at an equilibrium exchange rate that is estimated from the official rate and the
proportion of export receipts traded on the parallel or sanctioned secondary market (when there were retention schemes for exporters) or the illegal (black) secondary market for foreign currency. In Nigeria, the institutional arrangements up
to 1986 were such that all import and export transactions had to take place at the
official exchange rate; since then nonfuel trade occurred at the free-market rate.
Unit border prices for imports and exports were obtained from trade volume
and value data published in the Food and Agriculture Organization’s database
FAOSTAT. Information on domestic producer prices came from several different
sources. Farmgate prices for 1982–2004 were obtained from the Nigeria’s Federal
Office of Statistics and (for cocoa and palm oil) from the Central Bank of Nigeria.
Earlier information on producer prices was based on Oyejide (1986a) for
1961–62, Oyejide (1986b) for 1963–76, and Robertson (1983) for 1977–81. It
should be noted that different sources sometimes report quite divergent price
information, and the selection of the price data sources was undertaken with the
448
Distortions to Agricultural Incentives in Africa
aim of using the same source across the largest number of commodities and years
to minimize bias from differing reporting methodologies.
The available information on transport, marketing, and processing margins
showed large variability over time, to the extent that differences in margins
appeared to be caused by data problems rather than by underlying changes in cost
structure. To minimize the impact of these data problems on the policy analysis,
data on margins reported in Robertson (1983) for the late 1970s and early 1980s
were averaged, converted to ad valorem equivalents, and taken as representative
for the entire study period. The quality of domestically produced and consumed
products was assumed to be identical to that of traded commodities.
A commodity was classified as an exportable if exports exceeded imports and
accounted for more than 2.5 percent of domestic production. Conversely, if
imports exceeded exports and accounted for more than 2.5 percent of domestic
production, a product was classified as import-competing. Commodities were
classified as (nontradable) home goods if neither exports nor imports accounted
for 2.5 percent or more of domestic production. Multiyear averages were thereby
considered to avoid frequent switches in the tradability status of a commodity.
A dominant share of the products not individually covered in the quantitative
analysis are fruit and vegetables, which are rarely traded and thus qualify as home
goods. Yet, about one-tenth of the value of the uncovered agricultural output in
2004 consisted of exportables, such as ginger, natural rubber, and cashew nuts. At
the same time, about one-third of the value of uncovered agricultural production
consisted of import-competing products, notably livestock products, wheat, and
tobacco. The evolution over time of the value of exportables and importcompeting products in the uncovered commodities group was assumed to follow
the trend of the respective groups of covered products.
The shares of different nonagricultural sectors were derived from data on valueadded in the World Bank’s World Development Indicators database. In addition, it
was assumed that the food industry and the beverage and tobacco industry, respectively, accounted for 20 percent and 2 percent of the total manufacturing value
added, which corresponds to the sectors’ employment share. Information on tariff
protection for the different nonagricultural sectors was obtained from the UN
Conference on Trade and Development’s Trade Analysis and Information System
(Trains) and the World Trade Organization’s integrated databases.
Total governmental expenditure on agriculture at the federal, regional, and
local level was assumed to amount to twice the federal government’s spending on
agriculture. Half of this amount was assumed to benefit agricultural producers
through production-related subsidies, such as fertilizer subsidies. That part of the
budgetary support is allocated across commodities in proportion to the production value of the commodity, while the rest is treated as non-product-specific
assistance to farmers.
Nigeria
449
NRA patterns
The weighted average NRA for covered agricultural products (which account for
about 70 percent of all farm products valued at undistorted prices) fell gradually
from above 20 percent in the early 1960s to below 10 percent in the 1970s, then
rose to 15 percent in the late 1980s before falling gradually over the 1990s as the
structural adjustment program came into force; it then became negative on average
in the early 2000s (table 16.1).
Throughout the past five decades, however, the dispersion of NRAs across the
10 covered products was huge. Even though the standard deviation in 2004 was
only half what it was before the 1990s, it was still above 50 percent. That high
intrasectoral variance in covered NRAs suggests the welfare cost of agricultural
programs has been higher than might be implied by the relatively low average
NRA for the sector.
In particular, while producers of import-competing crops, such as maize, rice,
and sorghum have benefited from substantial governmental support ever since
the independence period, the producers of traditional export crops such as cocoa
beans, cotton, groundnuts, and palm oil have implicitly or explicitly been taxed by
governmental policies in most years. This difference has narrowed over time,
however, and the strong antitrade bias in the structure of Nigeria’s agricultural
distortions of the past has largely disappeared (see table 16.1; figure 16.2). Meanwhile, agricultural nontradables, namely, cassava, millet, and yams, have been subject to relatively little intervention, and their NRAs were close to zero until the
introduction of the value added tax in 1994, after which they turned negative (see
middle rows of table 16.1). The assumed NRA values for the roughly 25–40 percent of the agricultural sector’s products not covered here do not alter the sectoral
average NRA very much, nor does non-product-specific assistance except in the
first half of the 1980s (see upper half of table 16.2).
RRA trends
Because of the low rates of assistance to nontradable farm products, and the
large weights of them and of highly protected import-competing products
within the farm sector (see figure 16.1), the NRA for tradable agricultural products is substantially higher than for the sector as a whole. It is also much higher
than the NRA for nonagricultural tradables (which is dominated by petroleum;
manufacturing is well under 10 percent of GDP). Hence from independence to
the mid-1990s, the RRA is between 25 and 67 percent, suggesting that on average the price of tradable farm products relative to that for nonfarm tradables
was inflated by policies by between one-quarter and two-thirds. The premium
was slightly lower at one-fifth in the latter 1990s, and that difference had
450
Table 16.1. NRAs for Covered Farm Products, Nigeria, 1961–2004
(percent)
Product indicators
Exportablesa,b
Cocoa
Cotton
Import-competing productsa,b
Rice
Nontradablesa
Cassava
Millet
Yams
Mixed trade statusa
Maize
Sorghum
Groundnuts
Palm oil
Total of covered productsa
Dispersion of covered productsc
Percent coverage (at undistorted prices)
1961–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04
34.0
35.1
75.7
214.9
64.7
0.2
0.3
0.2
0.2
48.6
56.1
66.9
173.2
21.1
0.3
0.4
0.3
0.3
55.8
48.9
76.1
146.1
37.3
0.6
0.7
0.6
0.5
49.1
51.8
71.7
81.0
28.5
1.3
1.5
1.2
1.0
37.3
22.1
72.8
58.7
49.4
2.7
3.2
2.6
2.2
49.5
32.5
75.3
85.4
66.5
0.9
1.0
0.8
0.7
19.6
4.5
82.8
35.6
11.1
0.7
0.7
0.7
0.8
10.5
2.6
82.7
20.9
3.7
4.8
4.8
4.8
4.8
18.0
16.2
82.3
9.5
9.6
4.4
4.2
4.4
4.5
259.2
216.1
20.7
24.9
21.1
111.8
73
166.7
209.6
45.5
31.0
12.2
94.2
70
155.7
193.8
58.6
44.2
7.3
92.4
67
166.3
183.4
11.4
17.2
5.3
89.4
65
190.3
151.5
30.1
25.3
7.8
90.4
65
180.1
163.1
5.6
11.8
14.8
92.1
59
73.7
104.7
2.6
107.5
4.2
62.6
69
128.9
89.5
43.6
41.2
0.1
66.2
66
78.6
80.8
57.5
12.6
5.4
53.1
72
Source: Data compiled by the author.
a. Weighted averages, with weights based on the unassisted value of production.
b. Mixed-trade-status products included in exportable or import-competing groups depending upon their trade status in the particular year.
c. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
Nigeria
451
Figure 16.2. NRAs for Exportable, Import-Competing, and All
Farm Products, Nigeria, 1961–2004
280
240
200
percent
160
120
80
40
0
40
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
70
67
19
64
19
19
19
61
80
year
import-competing products
exportables
total
Source: Data compiled by the author.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
disappeared by the first half of the 2000s, suggesting that for the first time since
independence, there was no longer an incentive to have more resources in agriculture than would be the case without product price distortions (table 16.2 and
figure 16.3).
The final three rows of table 16.2 show what the agricultural NRA (including
nontradables), the trade bias index, and the RRA would be if exchange rate distortions had been ignored. Because the three nontradable crops account for
roughly half the value of farm production, it is not surprising that the exchange
rate distortion does not have a large effect on the overall agricultural NRA. But it
does have a significant effect on the RRA for tradables: if the exchange rate distortion had been ignored, the RRA would have still trended slightly upward
before the 1980s and steeply down to zero after the 1980s, but the absolute size of
the RRA would have been overestimated before the 1980s and underestimated
since then.
452
Table 16.2. NRAs for Agriculture Relative to Nonagricultural Industries, Nigeria, 1961–2004
(percent)
Indicator
NRA, covered productsa
NRA, noncovered products
NRA, all agricultural productsa
Non-product-specific (NPS) assistance
Total agricultural NRAb
Trade bias indexc
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAd
Memo item, ignoring exchange rate
distortions:
NRA, all agricultural products
Trade bias indexc
RRAd
1961–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
21.1
17.9
20.3
0.4
20.7
0.79
54.4
1.4
52.3
12.2
9.4
11.3
0.6
11.9
0.82
30.5
1.1
29.0
7.3
2.3
5.7
1.1
6.7
0.81
18.7
1.7
20.8
5.3
2.1
4.1
2.3
6.3
0.74
19.2
2.9
22.6
7.8
1.1
4.5
4.9
9.4
0.66
41.8
2.9
45.6
14.8
3.3
6.9
1.3
8.2
0.70
24.8
2.2
27.4
4.2
2.4
3.5
0.4
3.9
0.45
20.7
6.2
28.8
0.1
0.6
0.1
0.3
0.4
0.36
14.9
9.0
26.2
5.4
9.3
6.6
1.2
5.4
0.04
7.5
0.5
7.0
22.3
0.77
57.7
16.5
0.76
41.6
13.1
0.71
39.1
11.1
0.53
35.0
12.9
0.00
53.0
13.1
0.39
41.7
3.6
0.18
21.2
0.6
1.36
15.5
5.5
0.04
7.9
Source: Data compiled by the author.
a. NRAs including product-specific input subsidies.
b. NRAs including product-specific input subsidies and non-product-specific (NPS) assistance. Total of assistance to primary factors and intermediate inputs divided to total
value of primary agriculture production at undistorted prices (percent).
c. Trade bias index is TBI (1 NRAagx兾100)兾(1 NRAagm兾100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and
exportable parts of the agricultural sector.
d. The RRA is defined as 100 * [(100 NRAagt)兾(100 NRAnonagt ) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural
and nonagricultural sectors, respectively.
453
Nigeria
Figure 16.3. NRAs for Agricultural and Nonagricultural
Tradables and the RRA, Nigeria, 1961–2004
160
140
120
percent
100
80
60
40
20
0
19
61
19
64
19
67
19
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
20
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the author.
Note: For a definition of the RRA, see table 16.2, note d.
Factors Driving Policy Developments
The persistent divergence between domestic and world parity prices that is
revealed in the agricultural NRAs for Nigeria can be attributed to several forms of
governmental intervention including exchange rate policies, tariffs and quantitative restrictions on imports or exports and associated licensing requirements, and
domestic market price supports and budgetary payments.
Exchange rate policies
Exchange rate policies have had a marked impact on agriculture. Nigeria has pursued a policy of maintaining a relatively constant nominal exchange rate in the
face of strong real exchange appreciation stemming from petroleum-related capital inflows. The resulting real appreciation of the currency squeezed non-oil tradables, notably agricultural commodities. The opposite occurred when petroleum
prices slumped in the mid-1970s and again in the mid-1980s.
Up to 1986, exporters were required by law to render all foreign currency to the
central bank at the official exchange rate. Imports were subject to licensing
requirements, and the government set annual quotas for “essential” and
454
Distortions to Agricultural Incentives in Africa
Figure 16.4. Black Market Premium over Official Exchange
Rate, Nigeria, 1960–2004
500
450
400
percent
350
300
250
200
150
100
50
0
1960
1965
1970
1975
1980
1985
year
1990
1995
2000
2005
Source: Cowitt (various years).
“nonessential” imports. The difference between the official exchange rate and the
black market rate was considerable during periods of overvaluation, with spikes of
several hundred percent in the mid-1980s and mid-1990s (figure 16.4). The overvaluation served as an implicit impediment to producers of agricultural and other
export crops. But insofar as importers had to pay more than the equilibrium price
for foreign exchange, the regime also served as an implicit tax on imports and
hence a form of protection to import-competing producers. Those implicit trade
taxes have therefore been incorporated in the calculation of the NRAs for farm
and nonagricultural sectors, using the project’s methodology (see Anderson et al.
2008).
Border taxation
After independence, Nigeria wholeheartedly embraced an import substitution strategy to foster industrialization. Manufacturing industries received high levels of protection through tariffs and quantitative restrictions, which had the effect of pushing
up manufacturing wages and the costs of manufactured inputs to the detriment of
other sectors, notably agriculture. Moreover, up to the mid-1970s, agriculture was
seen as a reservoir for resources to support the process of industrialization.
Nigeria
455
For a long time, agricultural trade policy was primarily determined by balance
of payment considerations. Import tariffs, export duties, and quantitative restrictions, such as import bans and licensing requirements, were used to adjust the level
of imports to the available foreign reserves. Since the 1970s, tariff escalation, with
high rates on finished products and lower ones on inputs, gradually took root, and
tariff reforms in 1978 and 1982 introduced high import duties of 50 to 100 percent
for food commodities such as maize, rice, wheat, and sorghum, while tariffs on
production inputs and capital equipment were set in the range of zero to 15 percent (Oyejide 1986b). Tariffs on agriculture and food were very high in the 1990s
(averaging 30 and 35 percent) and have been even higher since 2002, exceeding the
import duties on primary nonagricultural and nonfood manufacturing, which
averaged about 20 and 25 percent, respectively, in the 1995–2004 period.
Up until the mid-1970s, exports of agricultural produce were subject to taxation. In fact, they were taxed through three different means: export duties, sales
taxes, and the marketing board surpluses (World Bank 1973). From independence
to 1977, export duties levied by the federal government amounted to 15–20 percent. In addition, state governments levied, collected, and retained sales taxes
based on the volume of produce delivered to the marketing boards.
The third form of export taxation consisted of the trading profits of the marketing boards, which have fluctuated considerably over time. The boards were the
major instrument of agricultural commodity marketing and pricing policy since
their establishment as regional, multicommodity organizations in 1954. Producers were required by law to sell their crops at officially determined prices to the
boards, which were the sole exporters for the products covered. In 1977, the existing regional boards were replaced by six new national commodity boards responsible for the marketing of cocoa, groundnut, palm produce, cotton, rubber, and
food grains (Manyong et al. 2003).
Domestic market price support
The creation of the grains marketing board in 1977 was particularly remarkable
because it represented a first effort to extend the marketing board system to cover
food crops. The National Grains Board handled maize, millet, sorghum, wheat,
rice, and cowpeas. It administered a guaranteed minimum price policy whereby
floor prices were nationally set for each of the six grain crops as guaranteed
minimum prices at which the board would intervene as a buyer of last resort
(Manyong et al. 2003). However, the official floor prices were set substantially
below farmgate and retail prices and thus had little effect; because farmers were
free to sell on the open market, the National Grains Board made very few intervention purchases (Oyejide 1986b).
456
Distortions to Agricultural Incentives in Africa
Nontariff measures
Nigeria has made extensive use of nontariff barriers, notably import bans, to shelter
domestic producers from foreign competition. The practice of prohibiting imports
of selected products was widespread in the 1980s and early 1990s, and after the
national government replaced a number of prohibitions with high tariffs from the
late 1990s, major expansions in the list of prohibited imports occurred again in
2001, 2003, and 2004. In November 2005, 944 tariff lines (down from 1,130 lines in
January 2004) were subject to import bans. In other words, nearly one-fifth of all
products in the tariff schedule could not be legally imported into Nigeria. In addition, there were partial bans in 76 tariff lines, which mostly relate to imports of consumer durables in used form or prescribe minimum import quantities or specific
import locations. Ruffer (2004) estimates that banned products might, in the
absence of the prohibitions, account for 5–10 percent of total imports.
Frequent changes in trade regulations have also been harmful. For example, the
1988 ban on vegetable oil imports induced large-scale investments in domestic
production capacity. When the ban was lifted four years later, the market was
flooded with imports, and the uncompetitive domestic industry suffered losses.
In addition to the often unpredictable yet official barriers to imports in the
form of tariffs and import prohibitions, substantial informal trade barriers in
Nigeria’s logistics sector add further distortions to the import regime. Importers
face long clearance procedures, high berthing and unloading costs, erratic application of customs regulations, and corruption. A recent World Bank project collected information on the number of necessary documents and signatures as well
as the time required to undertake import or export transactions. Nigeria scored
worse than regional comparators in all dimensions (World Bank 2006a).
Budgetary payments
In addition to influencing producer prices, the government has also tried to foster
agricultural development through direct spending policies. Public funds were
made available to improve rural infrastructure and institutions and to subsidize
production inputs, notably fertilizer, and agricultural credit. Public outlays for
agriculture and rural development by federal, state, and local governments are
reported by the authorities as recurrent and capital expenditure. Unfortunately,
consistent and reliable data are available only for the approved budgets, not the
executed ones. Also, a substantial part of actual spending has occurred through
extrabudgetary means, such as “authorized to incur expenditure” arrangements
and stabilization accounts (World Bank 1996). Hence, the available budgetary
information can only be indicative of the support actually received by farmers.
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457
The budgeted funds available for agriculture have fluctuated considerably over
time, both in absolute outlays and in budget shares (Garba 2000). During the late
1970s and early 1980s, the federal government significantly increased its spending
on agriculture; its share in the total budget exceeded 10 percent by 1983. During
the subsequent structural adjustment period, the budget share fell back to an
average of about 3.5 percent. This dropback was somewhat cushioned through
continued agricultural loan assistance from international development partners,
whose funding increased in relative importance, from one-tenth to one-quarter of
federal outlays during the structural adjustment period (World Bank 2001).
In addition to spending at the federal level, state and local governments had
their own spending programs, which frequently overlapped with federal initiatives. The relative importance of agriculture has varied widely across state budgets, ranging during the 1980s and 1990s from less than 1 percent to more than
10 percent, with most states, similar to the federal government, devoting the bulk
of funds to capital improvements rather than recurrent expenditure (World Bank
2001). In contrast, local authorities, who support agriculture through funding
programs for road maintenance, rural health facilities, and community development, spent most of their funds on a recurrent basis. While no reliable figures on
overall agricultural spending are available, estimates of the share of federal spending in total spending range from 40 percent to 60 percent.
One of the most prominent governmental programs in the agricultural sector
concerned fertilizer subsidies, which accounted at times for half of total agricultural spending. Since the 1950s, regional governments increasingly arranged purchases of fertilizer and other key inputs for resale at an official, subsidized price,
with a focus on supporting the production of export crops. In 1976, the federal
government assumed responsibility, with state and local governments taking on
parts of the costs of the subsidy as well as the expenses related to distribution.
At the same time, the program was extended to cover food crops.
Available information indicates that subsidy rates were very high, at 75–85 percent
of total fertilizer costs during the late 1970s to the mid-1980s, and then fell to less
than 60 percent in the mid-1990s (Etuk 1986; World Bank 1996). Other production
inputs, such as improved seeds (50 percent subsidy rate), agrochemicals (50 percent),
and tractor services (25 to 50 percent) also received governmental support (Manyong
et al. 2003). However, inefficiencies and lack of timeliness in the distribution system
frequently undermined the programs and further raised their costs.
Another means of financial support to agriculture has consisted of concessional credit and credit guarantees. The National Agricultural Cooperative and
Rural Development Bank was established in 1972 at the federal level to channel
financial funds at concessional rates to individual farmers and farmers’ cooperatives. In 1977, the Agricultural Credit Guarantee Scheme Fund was set up to
458
Distortions to Agricultural Incentives in Africa
counter the shortage of credit available, particularly to small-scale agricultural
producers. The fund was jointly established by the federal government (60 percent
of the paid-up capital) and the central bank (40 percent) and provides guarantee
cover for loans to agricultural producers through participating commercial banks.
The cover pledges to pay the banks 75 percent of any outstanding default balance
under the condition that existing collateral has been realized (Olaitan 2006).
The fund’s loan portfolio built up quickly, reaching 0.2 percent of GDP in 1985
and 1986. After the structural readjustments were implemented, the fund rapidly
became less important. Support for livestock operations, which were important
during the boom phase of the fund, shifted toward food crops, which since the late
1980s have accounted for the majority of the guaranteed loans. From 1978 to
2004, the fund guaranteed a total of almost 400,000 loans, of which about 250,000
(64 percent) were subsequently fully repaid (Olaitan 2006). The costs of covering
the guarantees for nonperforming loans were financed out of the retained earnings on treasury bonds that the fund had been accumulating over time.
Recent Developments and Prospects for
Domestic Policy Reform
The democratically elected government that came to power in 1999 has realized
the shortcomings of past policies and has embarked on reforms of the country’s
policies that are imposing distortions to agricultural and other sectors’ incentives.
In 2002, the government approved an ambitious and comprehensive agenda for
policy and institutional reform on trade policy. Moreover, the National Economic
Empowerment and Development Strategy of 2004 confirms the government’s
intention to lower or remove barriers to trade. Since then, the national government has launched major initiatives to modernize customs and port management, and it adopted the ECOWAS common external tariff (CET) in October
2005.
The adoption of the CET implies a major change in Nigerian trade policy. The
ECOWAS CET consists of four bands (zero, 5, 10, and 20 percent), similar to those
already being applied by members of the West African Economic and Monetary
Union, a subset of ECOWAS member countries. During the transition period,
which closed at the end of 2007, Nigeria applied 50 percent duty rates to imports
in 102 tariff lines, or 1.9 percent of all lines. The resulting tariff profile was significantly less dispersed and carried lower average duty rates than Nigeria’s pre-CET
schedule. Indeed, the adoption of the CET is bringing simple average import
duties, which had reached almost 30 percent, down to 12.1 percent (11.6 percent
once the CET is fully implemented in 2008). The liberalization is particularly
marked for agricultural products, which formerly received high protection.
Nigeria
459
What are the likely impacts of the ongoing trade reforms, and how are poor
people, in particular, being affected? Predicting the effects of trade regime changes
on income distribution is a complex and challenging undertaking. The extent to
which changes in trade policy alter the prices of goods and services that are produced and consumed by poor households will naturally have a major impact on
poverty levels. Moreover, price transmission, labor market flexibility, and the incidence of replacement taxes will have to be taken into account, although tax
replacement is likely to be of less significance than it is in many other developing
countries, given Nigeria’s relatively minor dependence on trade taxes.
Nigeria’s Federal Office of Statistics carried out a household survey in 2004 and
found that the prevalence of poverty in the country had fallen over time, but that
more than half of all Nigerians continued to live on less than $1 a day (FOS 2005).
As in many other countries, the share of households living in poverty is higher in
rural (61 percent) than in urban areas (40 percent).
Some insights into how poor households will likely be affected by ongoing
trade reforms can be obtained by assessing the impact of liberalization on the production and consumption patterns of the poor. The very poorest households tend
to consume a relatively large amount of food, but they produce it themselves
rather than rely on the market. Poor people in general spend a larger share of their
monetized income on food than richer households. In Nigeria, the richest quintile
of households devotes less than 43 percent to food purchases, while poorer households spend up to 60 percent on food (table 16.3). Hence, any change in food
prices has a more pronounced impact on poorer than on richer households. The
tariff changes stemming from the adoption of the ECOWAS CET imply that
Table 16.3. Structure of Annual Household Expenditure by
Income Quintile, Nigeria, 2004
(in Nigerian nairas unless indicated otherwise)
Income
quintile
Total per capita
expenditure
Per capita
nonfood
expenditure
Per capita
food
expenditure
Share of food in
total expenditure
(percent)
1
2
3
4
5
Average
7,226
13,263
19,234
28,261
68,952
35,600
3,520
5,467
7,572
11,880
39,543
18,506
3,706
7,796
11,663
16,381
29,408
17,094
51
59
61
58
43
48
Source: FOS (Federal Office of Statistics) 2005.
Note: 133 nairas US$1.
460
Distortions to Agricultural Incentives in Africa
average import duties on agricultural products would fall from 41 percent to
13 percent, while duties on manufacturing goods would drop from 28 percent to
12 percent. Even if price transmission for agricultural products is somewhat lower
than for nonagricultural goods, agricultural and food prices should decrease by
more than nonfood prices, thereby increasing the purchasing power of the poor
by relatively more than that of richer households.
On the production side, the household survey reported substantial differences
in the types of crops that different households grow. For example, more than half
of all eggplant and tobacco is grown by households in the poorest quintile. Conversely, more than half of all coconut, papaya, and pineapple is planted by the
richest quintile of households. Neither eggplant nor tobacco are subject to import
prohibitions, while coconut, papaya, and pineapple all are. Moreover, the tariff
protection for tobacco under the old national tariff schedule (import duty of
15 percent) and the CET (5 percent) is substantially below the average for agricultural products, while coconut, papaya, and pineapple each benefit from very high
protection under the old regime (import duty of 100 percent) and the new import
regime (20 percent). These observations suggest that rich households have in the
past been able to influence the political process so that the structure of domestic
market protection favors their interests rather than those of the poor. In this context, the full adoption of the CET and the phasing out of import prohibitions will
reduce the antipoor bias in the trade regime and put poor household producers
on a more equal footing with their richer counterparts in terms of the policygenerated transfers they receive.
References
Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675–704.
Central Bank of Nigeria. Various years. Annual Report and Statement of Accounts. Abuja: Central Bank
of Nigeria.
Cowitt, P. P., ed. Various years. World Currency Yearbook. Brooklyn: Currency Data and Intelligence,
Inc.
Daramola, A., S. Ehui, E. Ukeje, and J. McIntire. 2007. “Agricultural Export Potential.” In Economic
Policy Options for a Prosperous Nigeria, ed. P. Collier and C. Pattillo. London: Palgrave Macmillan.
Etuk, O. E. U. 1986. “Fertilizer Pricing in Nigeria.” In Fertilizer Producer Pricing in Developing Countries: Issues and Approaches, ed. L. Segura, T. Shetty, and M. Nishimizu. World Bank: Washington,
DC.
FAO (Food and Agriculture Organization). 2006. Food and Agriculture Organization Statistics
Databases (FAOSTAT). FAO, Rome.
FOS (Federal Office of Statistics) 2005. “Draft Poverty Profile for Nigeria.” Federal Office of Statistics,
Abuja and Lagos.
———. Various years. “National Average Producer Prices.” Federal Office of Statistics, Abuja and
Lagos.
Garba, P. K. 2000. “An Analysis of the Implementation and Stability of Nigerian Agricultural Policies,
1970–1993.” AERC Research Paper 101. African Economic Research Consortium, Nairobi.
Nigeria
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Helleiner, G. K. 1966. “Peasant Agriculture, Government and Economic Growth.” In Nigeria. Homewood, IL: R. D. Irwin.
International Monetary Fund. Various years. Exchange Arrangements and Exchange Restrictions:
Annual Report. Washington, DC: International Monetary Fund.
Manyong, V. M., A. Ikpi, J. K. Olayemi, S. A. Yusuf, R. Omonona, and F.S. Idachaba. 2003. “Agriculture
in Nigeria: Identifying Opportunities for Increased Commercialization and Investment.” Report
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Olaitan, M. A. 2006. “Finance for Small and Medium Enterprises: Nigeria’s Agricultural Credit
Guarantee Scheme Fund.” Journal of International Farm Management 3 (2): 1–9.
Oyejide, T. A. 1986a. “Agricultural Marketing and Pricing Policy in Nigeria.” Working Paper. Development Research Department, World Bank, Washington, DC.
———. 1986b. “The Effects of Trade and Exchange Rate Policies on Agriculture in Nigeria.” Research
Report 55. International Food Policy Research Institute, Washington, DC.
Pinto, B. 1987. “Nigeria During and After the Oil Boom: A Policy Comparison with Indonesia.” World
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Robertson, J. W. 1983. “An Analysis of Agricultural Trade and Subsidy Policies in Nigeria.” Country
Policy Department Discussion Paper 1983-11. World Bank, Washington, DC.
Ruffer, T. 2004. “An Assessment of Nigeria’s Import Prohibitions Policy.” Study prepared for the U.K.
Department of International Development. Oxford Policy Management, Oxford.
Walkenhorst, P. 2007. “Distortions to Agricultural Incentives in Nigeria.” Agricultural Distortions
Working Paper 37. World Bank, Washington, DC.
Wells, J. C. 1974. Agricultural Policy and Economic Growth in Nigeria 1962–1968, Ibadan: Oxford
University Press for the Nigerian Institute of Social and Economic Research.
World Bank. 1973. “Agricultural Sector Survey: Nigeria.” Report PA-115. World Bank, Washington,
DC.
———. 1996. “Nigeria Federal Public Expenditure Review.” Report 14447-UNI. World Bank,
Washington, DC.
———. 2001. “Public Expenditure Issues in Rural Development.” In Nigeria Rural Sector Strategy
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———. 2006a. Doing Business 2006. Washington, DC: World Bank.
———. 2006b. “Getting Agriculture Going in Nigeria: Framework For a National Growth Strategy.”
Report 34618-NG. World Bank, Washington, DC.
17
Senegal
William A. Masters*
This chapter provides an overview and measurement of distortions to agricultural
incentives in Senegal from 1961 through 2004. Senegalese agriculture is unusually
specialized in just three products: groundnuts, rice, and millet. Groundnuts have
remained Senegal’s premier export, rice remains the principal import-competing
food, and millet is the principal food crop. The data also include cotton, primarily
because of its role elsewhere in the region. Several other products are of significance to particular communities within Senegal but are much less important at
the national level. These include exportables such as fish, import-competing
products such as meat or maize, and a range of items with little international
trade such as sorghum and cowpeas. Fertilizers also play an important role, with
Senegal exporting phosphates and importing nitrogenous compounds.
Most descriptions of Senegal begin by noting that it was the favored capital of
French West Africa, with Dakar as the French center for colonial administration
and industry. This status led to an unusual economic structure, with a very large
government and service sector relative to the country’s size. Adjustment after
independence in 1960 was slow and painful. Real gross domestic product (GDP)
measured in purchasing power parity fell by more than 20 percent during the
1960s and 1970s. This long decline ended in 1980, when Senegal became the
world’s first country to enter a World Bank–sponsored structural adjustment program. Incomes rose in the 1980s, fell again from 1988 to 1994, and have risen
steadily since then. Policy changes were spread out over more than a decade, but
* The author is grateful for the assistance of Harounan Kazianga, Marianne Kurzweil, and the project
team in Washington, as well as for helpful comments from the World Bank country office in Dakar.
Detailed data and estimates of distortions reported in this chapter can be found in Masters (2007).
463
464
Distortions to Agricultural Incentives in Africa
since 1993 the country has enjoyed sustained growth, fueled by an exchange rate
devaluation in 1994 and subsequent aid flows.
A remarkable feature of Senegal’s long decline and eventual turnaround is its
relative steadiness. There was no growth collapse, and internal conflict was limited
to a long but relatively small insurgency in the Casamance region, which did not
break out until after the economic decline had ended. For most Senegalese, relative peace and stability prevailed throughout the period of economic decline,
despite wrenching changes in every aspect of Senegalese life that could easily have
involved widespread violence and macroeconomic instability. Instead, the restructuring of Senegal’s inefficient and inequitable colonial economic institutions was
spread out over more than 40 years. Many challenges remain and growth reversals
may again occur, but the country now has a much more open and competitive
economic structure and a more favorable outlook for the future.
This chapter focuses on Senegal’s policy choices. Other countries’ policies are
taken as given, considered to be part of Senegal’s market environment. France has
been particularly important, of course, through both fiscal transfers and market
prices. French decisions set the starting point for Senegalese policy in 1960 and
heavily influenced the opportunity costs for any subsequent reforms. Those
opportunity costs are measured using Senegal’s actual border prices, even though
these include European trade preferences and other countries’ export subsidies, to
capture the net effect of all influences on Senegal’s market opportunities.
The net effects within Senegal are also examined, with each commodity category treated as a single market. In fact, Senegalese policy involved significant discrimination within markets, using quota allocations, fiscal transfers, and crosssubsidies to favor particular groups, especially marabout religious leaders whose
political support was of great value to the government. These cross-subsidies do
not appear when measuring the aggregate average distortion from world prices.
They may have been necessary for political stability, but they were probably costly
for economic growth, making the reforms of the 1980s and 1990s even more valuable for future growth than the estimates in the data would imply.
Economic and Structural Change since 1955
Senegal’s economic structure was built by French colonials in the 19th and early
20th centuries. The country served as the administrative and logistical hub for
French West Africa, exporting groundnuts and groundnut oil from the region to
metropolitan France while importing low-quality rice from French colonies in
Southeast Asia. Revenues from this system were generally repatriated to France
rather than reinvested within Senegal, so even before independence, the country
was in serious economic difficulty. Data are limited, but as Diawa-Mory Traore
Senegal
465
(1969, pp. 37–38) noted, “the post-1955–56 period . . . was characterized by a general decline of output in (most) major industrial groups.”
At independence, agriculture continued to employ the vast majority of workers, so living standards for the poor were determined mainly by the country’s farm
productivity. From 1960 through the mid-1980s, Senegal’s total food output fluctuated but did not grow at all, whereas population more than doubled. As a result,
food output per capita declined by more than 50 percent. Since the reforms of the
1980s, total agricultural output has doubled, but population has doubled again, so
per capita production has been about constant. In Sub-Saharan Africa as a whole,
total output has grown much faster, producing much less decline in output per
capita than has occurred in Senegal.
The consequences of stagnant farm productivity for Senegal’s trade are noteworthy. Exports of groundnut products grew briefly in the 1970s and again in the
late 1980s, but in each case they then fell back to their 1961 level. An expansion of
the local groundnut-oil industry virtually eliminated the export of raw groundnuts in the late 1960s, but the sector as a whole did not grow (figure 17.1). Stagnation of this sector is often attributed to limited demand on world markets, but the
Figure 17.1. Net Merchandise Trade, Senegal, 1961–2004
exports minus imports (US$ millions)
500
250
0
250
500
750
1,000
1,250
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001
year
groundnuts (all products)
rice
total food (excluding fish)
cereals
total merchandise trade
Source: Compiled by the author, using FAO 2006 data.
Note: Value for total net merchandise trade in 2004 was $1.6 billion (not shown).
466
Distortions to Agricultural Incentives in Africa
lack of aggregate growth despite local value added suggests that supply constraints
were also important. At prevailing prices and productivity levels, farmers have
been unable to devote more land or labor to any export, and the country as a
whole has survived (albeit with high malnutrition rates) thanks only to steadily
increasing food imports.
Net imports of all kinds can be a desirable counterpart to aid and capital
inflows. In aggregate, imports grew very rapidly in the 1970s and again from 1997,
but food trade followed a trend of its own, with imports of food steadily increasing since the late 1970s. Only a small fraction of this trend is attributable to
increasing imports of rice. Increasing imports of other cereal grains add to the
trend, and since 1989 imports of other foods have seen even larger increases. In
sum, stagnation of local agricultural production has led Senegal to devote a large
fraction of available foreign exchange to food imports (see figure 17.1), with continued poverty allowing very limited improvement in dietary quality.
Table 17.1 presents the food balance sheet, compiled by the Food and Agriculture Organization (FAO), for Senegal, for 1961 and 2003. The first pair of columns
shows self-sufficiency ratios, and the second pair shows dietary composition.
Cereals continue to dominate the diet, providing over 60 percent of calories, of
which the share supplied by local production declined from 0.73 to 0.43 between
1961 and 2003. Starchy roots account for a small and falling fraction of the food
supply. The most unusual aspect of the Senegalese diet is its extraordinarily high
consumption of vegetable oils, with lower-cost soybean oil replacing much of the
groundnut oil that had been the focus of colonial development policy.
Most African countries have significantly increased their cropped area since
the early 1960s, under pressure of rural population growth, but in Senegal there
has been almost no increase. One reason Senegalese farmers have not undertaken
similar expansion into previously unattractive areas is that they lack profitable
technologies with which to do so. That lack of profitable expansion opportunities
results in part from the country’s unusual focus on groundnuts and millet. Some
combination of a legume such as groundnuts with a cereal crop such as millet is
typical of rainfed systems around the world, but Senegal’s focus on these particular crops reflects the country’s political history as much as its agronomic conditions. Groundnuts were deliberately imposed on farmers by the French in the late
1800s and early 1900s, while millet became the dominant food grain by default
because of a lack of investment in farmers’ alternatives.
Raising incomes without a change of crop species is difficult. Some farmers are
turning from groundnuts to cowpeas and have recently also been planting maize
instead of millet. These other crops are widely grown in countries whose agronomic conditions are similar to Senegal’s, but Senegalese farmers have had only
limited access to appropriate new varieties that would stimulate substitution. The
Senegal
467
Table 17.1. Food Balance Sheet Data, Senegal, 1961 and 2003
Self-sufficiency ratioa
(Production/
utilization)
Cereals, excluding beer
Wheat
Rice (milled equivalent)
Maize
Millet
Sorghum
Starchy roots
Cassava
Sugar and sweeteners
Pulses
Groundnuts (shelled equivalent)
Vegetable oils
Groundnut oil
Soybean oil
Palm oil
Vegetables
Tomatoes
Onions
Vegetables, other
Fruits
Bananas
Meat
Bovine
Poultry
Milk (excluding butter)
Eggs
Fish, seafood
Dietary composition
(Percent of total
calories)
1961
2003
1961b
2003c
0.73
—
0.34
0.59
1.00
0.95
0.94
1.00
0.00
0.98
1.62
4.15
5.03
—
0.55
0.55
0.12
0.43
0.97
0.70
0.91
0.99
0.98
0.97
0.78
0.88
—
0.43
—
0.15
0.66
1.00
1.00
0.83
0.99
0.61
0.96
1.00
0.50
1.56
—
0.17
0.88
0.55
0.62
0.98
0.83
0.36
0.92
0.97
0.84
0.48
0.99
—
60.6
5.2
20.4
4.6
23.1
6.8
5.7
5.0
8.5
1.4
3.4
8.3
6.9
—
1.2
0.7
0.3
0.2
0.2
0.6
0.0
2.8
1.8
0.1
2.4
0.1
1.5
60.4
9.2
32.0
4.5
9.6
5.1
2.3
1.9
6.0
1.2
2.1
15.1
5.0
7.7
1.3
1.6
0.1
0.6
1.0
0.7
0.1
3.2
1.0
1.1
2.2
0.4
2.3
Source: Compiled by the author from FAO (2006) food balance sheet data.
Note: — no data are available.
a. The self-sufficiency ratio is computed as production plus stock change, divided by total utilization
(labeled as “domestic supply” by the FAO).
b. Total calories for 1961 2,290.
c. Total calories for 2003 2,374.
468
Distortions to Agricultural Incentives in Africa
only crop with significant yield growth has been rice, which is grown under
irrigation. Rice output has benefited from a relatively high level of public research
(Fisher, Masters, and Sidibe 2000), but total irrigable area is small and limited. The
major rainfed crops have a larger area under cultivation and probably more
opportunity for expansion if only farmers had access to more productive technologies.
Fertilizer use is a key contributor to sustainable crop productivity growth.
Senegal is a significant exporter of phosphates, but it imports nitrogenous fertilizers. The value of phosphate exports rose suddenly in the mid-1970s but declined
steadily thereafter. Consumption of fertilizers grew throughout the 1970s but was
not associated with significant crop yield increases and quickly fell back to earlier
levels. Since 1990, however, fertilizer consumption has steadily increased, helping
to lay a foundation for sustainable crop yield growth in the more competitive
farming systems.
Government Policy in the Colonial Era
French colonial policies gave Senegal a distinctive social history. One key legacy is
Africa’s oldest tradition of electoral democracy. In 1848, France gave all Senegalese
the right to vote in its national elections. This was the first universal suffrage vote
in Sub-Saharan Africa, and it resulted in the first African representative to a European parliament. Those elections may have had little practical influence on the
colonial policies of the day, but they could have helped establish the culture of
representative government that Senegal has enjoyed since independence. Despite
the political stress imposed by low and falling per capita incomes, independent
Senegal is one of the very few African countries to have experienced repeated contested elections and only peaceful transfers of power, from Léopold Sédar Senghor
to his chosen successor Abdou Diouf in 1981, and then to longtime opposition
party leader Abdoulaye Wade in 2000; Wade was reelected in 2007.
A second key legacy of French colonialism is Senegal’s unusually high level of
urbanization. From 1902, Dakar was developed as the capital for all of French
West Africa, with a far larger urban population than the Senegalese economy
could efficiently support. At independence, 32 percent of the population was
urbanized, more than twice the average for Sub-Saharan Africa. By comparison,
Ghana’s urbanization rate at the time was also above average but still only 23 percent (World Bank 2006). The city’s administrative role left independent Senegal
with an extraordinarily large civil service. The national government absorbed
almost all of the functionaries who had previously governed French West Africa
and then the Mali Federation, doubling the state operating budget during the
transition period from 1957 to 1961 (Schumacher 1975).
Senegal
469
If the city of Dakar had been developed for commercial or industrial reasons,
one might expect Dakar’s size to be a source of economic dynamism, but France’s
pacte colonial severely constrained local growth opportunities. Boone (1992)
describes in detail how French trading houses were established and protected by
colonial authorities. Their traite was a closed circuit of trade between France and its
colonies, exporting groundnuts in exchange for high-priced French manufactures
and consumer goods, including the lowest-quality broken rice from Southeast
Asian colonies. After World War II, some import-substituting industries were
established in Dakar, competing with French products but heavily protected
against imports from elsewhere, with market shares dictated by negotiation among
the trading houses and with the colonial government. The development of these
subsidized industries imposed a double burden on the Senegalese economy, first by
reducing the savings available for any more efficient investment at that time and
later by requiring massive adjustment costs when subsidies were removed.
Within agriculture, the country has a long history with groundnuts and millet.
There was a long rise in groundnut production from the late 19th century until
independence, when it began to fall and was replaced by millet for domestic consumption. Now millet itself is being replaced by other foods.
Important questions in Senegalese economic history are why the colonial government chose to focus on groundnuts and why that focus proved to be so
durable. Bonnefond and Couty (1991) suggest a number of contributing factors.
One was the availability then of emancipated slaves, who had been freed in 1848
and could be put to the task under the leadership of local marabout religious leaders in what became the groundnut basin. A second was the completion of a railroad from that region to the sea. With abundant labor, an outlet to trade, and few
other alternatives at hand, African farmers’ groundnut production grew steadily
throughout the colonial era, from an annual average of 31 thousand metric tons
in 1886–90 to its eventual peak after independence. Growth was fastest in the early
years, with production expanding by an annual average of 7.5 percent from 1885
until 1930. Growth slowed after 1930, partly because of a slowdown in area expansion but also because there was no further productivity growth: average yields
were 870 metric tons a hectare in the 1930s, and they have fluctuated around that
level ever since.
France’s 19th-century investment in transportation and marketing infrastructure, which facilitated agricultural exports, unlocked the potential of inland areas
to supply the coasts. Groundnut was an attractive product to export, but without
colonial restrictions farmers would probably have been much more diversified,
particularly if the alternative included government policies to support other
crops. French colonial policy focused on groundnut, however, and so it remained
the only possible source of cash income for farmers who relied on rainfed crops.
470
Distortions to Agricultural Incentives in Africa
Agricultural Policy since Independence
After independence in 1960, Senegal’s political leadership used the colonial-era
bureaucracy for a sequence of “socialist” and “nationalist” initiatives, to replace
French entities with Senegalese ones. Schumacher (1975) and Boone (1992)
describe this process in detail, focusing on agriculture and industry, respectively.
For agriculture, the single most important institutional change was the introduction, in January 1960, of the Office de Commercialisation Agricole (OCA), a
state-owned enterprise created to replace the small group of French trading firms
that had dominated the circuit of groundnut exports and imports of rice and farm
inputs. In particular, the OCA was given a legal monopoly over groundnut marketing, to be exercised by licensing either private buyers or, preferably, one of the statepromoted rural cooperatives. It was also charged with arranging for increased
imports of farm inputs, using its legal monopoly over the groundnut trade to
recoup operating loans to farmers for the purchase of those inputs. The OCA was
also given a monopoly over rice imports, which it allocated to local traders with
some limited controls over resale prices. Loans were administered by another new
entity, the Banque Sénégalaise de Développement (BSD), in collaboration with the
rural development services, which were reorganized into a set of Centres Régionaux
de l’Assistance pour le Développement (CRADs) and local cooperatives.
The OCA-BSD-CRAD-cooperative system was able to maintain the groundnut
circuit in the first few years of independence, avoiding the most likely alternative,
which would have been a sudden collapse of trade volumes and a period of
extreme hardship. Replacing French traders with state-owned enterprises kept
trade flowing, but the whole enterprise was almost certainly unsustainable. Margins were shrinking, and within the marketing chain, agents at each stage found
opportunities for diversion: individual farmers against their cooperatives, cooperative managers against their lenders, loan officers against the OCA. As detailed by
Schumacher (1975), similar problems had plagued colonial administrators.
Instead of liberalizing, however, the new government responded by attempting to
eliminate private markets entirely and to use administrative means to control corruption within the bureaucracy.
In 1966–67, the OCA was replaced by the Office Nationale de Cooperation et
d’Assistance au Développement. This agency, which was charged with input distribution and transport as well as groundnut marketing, lasted for about a decade
before being dissolved in 1980. The pace of change was dictated in part by France’s
willingness to support the Senegalese structures it had helped create. But decolonization coincided with European integration, so France’s trade preferences had
to be extended to Europe as a whole. These trade preferences, and some fiscal
transfers, were governed by a series of agreements among European countries
with their former colonies: first the Yaoundé Convention of 1963, soon followed
Senegal
471
by the Lomé Convention and more recently the Cotonou Agreement, which took
effect in 2002. It is not clear whether these agreements improved or worsened conditions for Senegal, or what the counterfactual might have been. In this study, this
external environment is taken as given.
By the end of the 1970s, the Senegalese economy was among the most distorted
in West Africa. In 1980, Senegal became the first of the region’s countries to start a
World Bank–sponsored structural adjustment program, but the reform process
was slow. In the rice market, for example, a comparison of government interventions across 12 West African countries in 1979 gave Senegal a score of 0.5 on a 0to-9 scale, where 9 is “generally competitive, with market determined prices”
(Randolph 1994, table 2). The only other country to score below 2 was Mauritania, with a score of 0.7. By 1993, after more than a decade of reform, Senegal had
raised its score to 3.9, but it still had the most highly controlled market of the
region (Randolph 1994, table 5). Jammeh (1987) provides a detailed description
of the reforms undertaken in the 1980s.
In retrospect, what is most notable is how many of the changes introduced
between 1986 and 1988 under the New Industrial Policy were subsequently
reversed. By 1993, just before the regionwide devaluation of the CFA franc, Senegalese tariff rates were very high (75 percent on consumer goods produced locally;
45 percent on other consumer goods). Government limited competition among
domestic firms as well, with conventions speciales protecting privately owned
monopolies in sugar, cement, and petroleum, and continued its control of rice
imports, groundnut processing, and the ports (IMF 1995).
Price Comparisons and the Measurement
of Distortions
To measure distortions over time in a consistent way, this study uses the methodology described in appendix A of this volume and in Anderson et al. (2008). The
focus is on government-imposed distortions that create a gap between domestic
prices and what they would be under free market conditions. The method relies
on historical observations of prices paid or received in foreign trade, combined
with a set of assumptions about the marketing margins that would have applied.
Because the characteristics of agricultural development cannot be understood
from a sectoral view alone, the project’s methodology not only estimates the
effects of direct agricultural policy measures (including distortions in the foreign
exchange market) but also generates estimates of distortions in nonagricultural
sectors for comparison. A nominal rate of assistance (NRA) is computed for
various farm industries, along with an estimate of NRAs for nonagricultural
tradables, which is compared with that of agricultural tradables through the
calculation of a relative rate of assistance (RRA).
472
Distortions to Agricultural Incentives in Africa
The analysis does not consider interventions in input prices. For Senegal, those
are likely to have been very small relative to distortions to prices of outputs, and in
any case there are insufficient observations to provide useful estimates. Thus, the
results hinge on simple price comparisons in each product market, net of the
assumptions about marketing margins and the estimate (again following the project’s methodology outlined in Anderson et al. 2008) of exchange rate distortions
in each year.
Groundnut prices and marketing margins
The approach to the groundnut market taken here focuses on the opportunity
cost of the raw nuts (in their shells), before they are processed into groundnut
oil. This method measures the NRA for the production of the groundnuts themselves. An attempt was made to obtain satisfactory data on processing costs and
market prices for groundnut oil, to measure the nominal protection afforded to
the operations of SONACOS, the parastatal groundnut processor. But the effort
proved futile because of the lack of transparency in SONACOS, which since
2003 has been slowly privatized under intense political scrutiny. In January
2007, SONACOS was renamed Suneor and was majority-owned by Advens, a
private consortium. Looking back over the history of SONACOS, it is clear from
the pricing of raw nuts that its operations have been highly subsidized at the
expense of farmers, taxpayers, and oil consumers. One estimate for marketing
year 2001–02 suggests that, given all of SONACOS’s procurement costs, its tradable inputs were subsidized at a rate of about 23 percent, which more than offset the 8.5 percent premiums it paid on nontradable factors such as labor and
which was much larger than the 7.7 percent implicit subsidy that SONACOS
received from protection on it sales. The net effect was a substantial transfer to
SONACOS, amounting to 20 percent of the firm’s market revenue (République
du Sénégal 2003). In the absence of a time series for such operational data,
however, the full extent of distortions in the processing sector cannot be
determined.
The price comparison method used here starts with the unit values of Senegal’s
raw nut exports, obtained from FAO file data, and compares them with estimated
farmgate selling prices reported by a sequence of published sources for various
periods of time. The farmgate prices are from Boone (1992) for 1959 and
1966–79, Kelly and Delgado (1991) for 1980–89, and the IMF (2005) for
1997–2004, with linear interpolations for the periods between those observations.
These published sources report prices from a variety of official publications and
official file data. There appears to be no contemporary publication or file data
with a complete time series for the entire 1960–2004 period.
Senegal
473
Because the FAO unit values are measured at Dakar whereas the farmgate
prices are paid in the groundnut basin, the observed price difference between
them includes transport and marketing costs. The price distortion attributable
to trade restrictions is the observed price difference minus the estimate of what
those costs would be in the absence of government trade restrictions. The best
estimate of this margin is borrowed from Kite (1993), who quotes a margin
from the groundnut basin to Dakar for competitive traders of cereal grains
equal to 17 percent of the farmgate price. That is likely to be an upper bound for
the cost of groundnut marketing, because at least some of the margin would be
a per ton charge for transport, and groundnuts have a higher value than grains.
If the margin was lower, implied rates of taxation would be greater. To proceed
conservatively, this study applies this same percentage margin to this crop for all
years.
In addition, the FAO unit values refer to much-higher-grade nuts than the
national average. An adjustment must be made for quality differences as well as
for transport costs. No independent estimate for the historical market value of
this quality differential could be found, and so a conservative calibration
approach was used. This approach sought the percentage quality differential that,
when applied over all years, resulted in the smallest level of taxation, given the
observation that there was no period of sustained subsidies for groundnut production. This method is conservative in the sense that it might understate the
absolute value of taxation, if the market value of the quality premium for
exported nuts is actually smaller than the calibrated value. The calibration procedure yields a plausible price premium estimate of 35 percent for export-quality
nuts, as opposed to the national average quality. One important aspect of this
result is that it includes the policy rent paid by European importers deriving from
trade preferences for Senegalese country of origin, in addition to European consumers’ valuation of the product’s intrinsic quality. From Senegal’s point of view,
however, this policy rent can be taken as given, serving as a marginal incentive just
like any other type of willingness to pay.
Rice prices and marketing margins
The approach to rice is similar to that for groundnuts, in that FAO file data on the
unit values of Senegal’s rice imports are compared with published estimates of
farmgate prices, net of the study’s estimates for the marketing margins and quality
premiums that would be paid for these transactions in the absence of trade
restrictions. The import unit values from the FAO, which refer principally to broken rice from Southeast Asia, are compared with farmgate prices reported by
Randolph (1997) for 1961–95 and IMF (2005) for 1997–2004. In this case there is
474
Distortions to Agricultural Incentives in Africa
only one missing value, for 1996, which is interpolated linearly from the 1995 and
1997 observations. As with groundnuts, there appears to be no publication or data
source with a continuous time series.
For transport costs between Dakar and rice farmers, the 17 percent estimate of
Kite (1993) is used and applied uniformly to all years. Adjustments in product
quality were required because imported rice is usually of a much lower quality
than that produced domestically in Senegal. In the absence of an independent
estimate for the historical market value of this quality differential, a calibration
approach was taken similar to that used for groundnuts. The goal in this case was
to find the uniform percentage quality differential that, when applied over the
entire period, is consistent with the policy observation of approximately zero net
taxation or subsidies over the decade of the 1960s. This calibration procedure
yields an estimated discount for imported rice of 30 percent, which was consistent
with anecdotal evidence.
An important caveat is that this quality discount is calibrated to fit historical
prices, and it is possible that quality values have not only fluctuated but also
trended over the years. (No such trend error would have occurred in the groundnuts case, because that calibration was based on observations about policy over
the entire period.) But it turns out that the 30 percent quality differential calibrated for the 1960s is also consistent with the absence of nontariff barriers to rice
traders after liberalization in 1995, which gives some confidence in the stability of
this parameter over time.
Millet prices and marketing margins
Millet is included in this study to represent the large fraction of Senegalese agriculture that is produced and consumed primarily within rural areas. This basic
food is actively traded across short distances, but its low value-to-weight ratio
limits the extent of long-distance transport and international trade. This grain is a
necessity for the rural poor, but effective market demand is limited because
higher-income consumers prefer foods that require less preparation time or have
other attractive characteristics. There is no price distortion from government
intervention. At the same time, there is also little public investment in new technology or other drivers of productivity growth. This product is treated as nontradable internationally.
Millet is normally much less valuable than rice, but it appears to have become
more costly than rice since the mid-1990s. This switch in national average farmgate
prices probably stems mainly from differences in the location of production—rice
is increasingly abundant in irrigated and urban areas, whereas millet remains in
the dryland regions, where it is grown for local consumption.
Senegal
475
Quantities produced
Quantities produced are used for the computation of aggregate NRAs. Weights are
based on FAO estimates of total production valued at undistorted prices. Rice
production grew rapidly from 1973 to 1990, when real farmgate prices fluctuated
with no trend, and then production stayed constant after 1990 even as real farmgate prices fell sharply. This pattern suggests significant shifts in the rice supply
curve, attributable perhaps to public investment in genetic improvement and
infrastructure, especially for irrigation. In contrast, estimated production of both
groundnuts and millet has trended down in recent years, despite roughly constant
real prices.
Exchange rates and macroeconomic distortions
Distortions to the market for foreign exchange have been small in Senegal relative
to other African countries. Like most other former French colonies in Africa,
Senegal has never had its own monetary policy. After independence, the colonial
currency, the franc des Colonies Françaises d’Afrique (CFA franc) was simply
renamed the franc de la Communauté Financière de l’Afrique using the same
acronym and the same fixed rate of CFAF 50 per French franc. Convertibility was
guaranteed by capital inflows from France, underwriting the balance of payments
deficit of the CFA region with the rest of the world. Senegal accounted for a very
small fraction of these inflows, but the total payment needed to support the currency became increasingly unsustainable and on January 12, 1994, the region’s
currency was devalued to CFAF 100 per French franc. It has remained convertible
at that valuation ever since, switching its peg to the Euro in January 1999.
The real exchange rate consequences for Senegal of the CFA franc’s fixed
nominal rate are illustrated in figure 17.2a. The real effective exchange rate
(REER) shown there is the International Monetary Fund’s measure of differential inflation between Senegal and its trading partners, after conversion between
currencies at official exchange rates. What is most noticeable is the relative stability of Senegal’s real exchange rate. The country did have faster inflation than its
trading partners during the 1981–86 period, resulting in an appreciation of its
REER totaling about 24 percent over five years, but then it had slower inflation
and a depreciation until 1994 that returned the REER back to its 1981 level.
There was only one year of appreciation after the devaluation of 1994, followed
by another five years of low inflation and REER depreciation, before a slight
upturn in the REER in 2001–03.
Clearly, Senegal has not experienced the same inflation-induced overvaluation
as many other countries, including many of its neighbors in the CFA zone. Indeed,
relative to other countries, Senegal’s macroeconomic policies caused the country’s
476
Distortions to Agricultural Incentives in Africa
Figure 17.2. Foreign Exchange Rates, Senegal, 1960–2005
a. Real exchange rates, 1980–2004
240
220
index (2004 100)
200
180
160
140
120
100
80
60
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
year
real effective exchange rate
real exchange rate misalignment
equilibrium real exchange rate
black market premium
b. Nominal exchange rates, 1960–2005
800
CFAF per US$
700
600
500
400
300
19
6
19 0
6
19 2
6
19 4
66
19
6
19 8
7
19 0
7
19 2
7
19 4
76
19
7
19 8
8
19 0
82
19
8
19 4
86
19
8
19 8
9
19 0
9
19 2
9
19 4
96
19
9
20 8
0
20 0
0
20 2
04
200
year
official
undistorted
parallel
Source: Official exchange rates, IMF 2006; black market or parallel rates, Easterly 2006; real exchange
rate indexes, Elbadawi 2006. Author’s estimate of the undistorted rate is based on the methodology of
Anderson et al. 2008.
Senegal
477
price level at official exchange rates to gain only about 30 percent in value in the
decade before the 50 percent devaluation imposed by France. This limited degree
of overvaluation is shown in figure 17.2a by the difference between the IMF’s
REER and the estimated equilibrium real exchange rate (EqRER), which is the
econometric result of an exercise conducted by Elbadawi (2006), using a worldwide panel of REERs and their determinants to estimate what each country’s
REER would be without the influence of short-term fluctuations in unsustainable
fiscal and monetary policies. The difference between the REER and the EqRER is
an estimate of RER misalignment (RERmis), with an increase in RERmis reflecting an increasingly overvalued currency. The 1994 devaluation much more than
compensated for any of Senegal’s own macroeconomic imbalances, although the
overshooting was quickly eroded, and by 2004, the RERmis index was back to
where it started in 1980.
For a consistent measure of policy-induced distortions in agriculture, instead
of RER misalignment, this study uses the information implied by the Easterly
(2006) data on black market premiums paid for the CFA franc in parallel markets.
These data, reported in figure 17.2b, show that despite the French effort to support the CFA franc, a small degree of excess demand for foreign currency prevailed from 1960 through 1970, and again in most years from 1978 through 1993,
and also in 2002–04. The project’s approach (Anderson et al. 2008) is to compute
an undistorted marginal value of foreign exchange earned or saved as a blended
average between the black market premium and the official exchange rate. This is
shown in figure 17.2b as the dashed line, roughly halfway between the other two.
Because the black market premium is small in Senegal, this kind of distortion is of
little consequence for the estimates.
NRA estimates
The net effect of government policies on agricultural incentives is summarized
by the prices shown in figure 17.3 and the NRAs shown in figure 17.4 and
table 17.2. During the early 1960s, groundnut production was moderately taxed
(and groundnut processors thereby helped), whereas rice production was slightly
subsidized (and rice consumers thereby harmed). This pattern of protection,
restricting both exports and imports, imposed a moderate level of antitrade bias,
which widened considerably over the 1970s. For groundnuts and cotton, export
prices rose much faster than the farmgate price in the 1970s, then fell in the 1980s
before rising again after 1995. Domestic prices followed the trend but with much
greater stability. A similar story applies to rice. In both cases, domestic prices were
institutionally fixed, and year-to-year changes in distortions were driven by
changes in foreign prices. During the brief period of high import prices in
Figure 17.3. Wholesale and Undistorted Prices, Selected Crops,
Senegal, 1961–2004
1,200,000
real CFAF per metric ton
1,000,000
800,000
600,000
400,000
200,000
19
6
19 1
6
19 3
65
19
6
19 7
6
19 9
7
19 1
7
19 3
75
19
7
19 7
7
19 9
8
19 1
8
19 3
85
19
8
19 7
8
19 9
9
19 1
9
19 3
95
19
9
19 7
9
20 9
0
20 1
0
20 3
05
0
year
cotton (undistorted)
groundnuts (undistorted)
rice (undistorted)
cotton (wholesale)
groundnuts (wholesale)
rice (wholesale)
Source: Data compiled by the author. Data shown are in real CFA francs at 2004 prices, deflated by the
consumer price index in the International Monetary Fund’s International Financial Statistics, 2005.
Figure 17.4. NRAs for Exportable, Import-Competing, and All
Farm Products, Senegal, 1961–2005
160
120
percent
80
40
0
40
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
67
19
64
19
19
19
61
80
year
import-competing products
exportables
total
Source: Data compiled by the author.
Note: The total NRA can be above or below the exportable and import-competing averages because
assistance to nontradables and non-product-specific assistance are also included.
Table 17.2. NRAs for Covered Farm Products, Senegal, 1961–2004
(percent)
Product indicator
a,b
Exportables
Groundnuts
Cotton
Import-competing productsa,b
Rice
Nontradablea
Millet
Total of covered productsa
Dispersion of covered productsc
Percent coverage (at undistorted prices)
1961–64 1965–69 1970–74 1975-79 1980–84 1985–89 1990–94 1995–99 2000–04
19.9
19.9
—
9.5
9.5
0.0
0.0
14.6
20.3
70
17.3
17.3
—
1.4
1.4
0.0
0.0
11.7
16.1
70
44.6
44.4
47.9
2.3
2.3
0.0
0.0
33.2
33.5
70
47.8
47.7
50.6
30.5
30.5
0.0
0.0
33.7
44.5
70
45.4
44.7
55.7
6.6
6.6
0.0
0.0
30.3
38.2
70
7.7
7.4
15.0
99.4
99.4
0.0
0.0
5.2
58.8
70
5.2
5.0
11.1
117.1
117.1
0.0
0.0
6.7
67.1
70
Source: Data compiled by the author.
Note: — no data are available.
a. Weighted averages, with weights based on the unassisted value of production.
b. Mixed-trade-status products included in exportable or import-competing groups depending upon their trade status in the particular year.
c. Dispersion is a simple five-year average of the annual standard deviation around the weighted mean of NRAs of covered products.
14.2
13.7
26.5
2.1
2.1
0.0
0.0
9.9
14.3
70
20.8
21.1
10.0
5.9
5.9
0.0
0.0
12.1
18.6
70
479
480
Distortions to Agricultural Incentives in Africa
1974–75, rice producers were slightly taxed to the benefit of consumers in contrast
to the 20 years thereafter when lower international prices resulted in a very high
level of protection for rice producers. Both of these were largely eliminated after
1995, although it is likely that moderate taxation of groundnut and cotton
producers remained. There was very little short-term correlation between
domestic and foreign prices until the experience with groundnuts after 2000 (see
figure 17.3).
When combined with the zero distortion to the price of nontradable millet
(whose share of the value of farm production has been in the range of 15–30 percent), the overall NRA for the four covered products fluctuated from less than 15
percent taxation in the 1960s to more than 30 percent taxation in the 1970s and
early 1980s, before turning to slightly positive support in the latter 1980s, when
international national prices were extremely low, and then settling at about
10 percent taxation since the mid-1990s.
For other farm products (roughly one-third of overall farm production), in the
absence of commodity-specific data, the study guesstimates that 30 percent is
import-competing, with an average NRA of 20 percent from import restrictions;
another 30 percent is exportable, with an average NRA of 10 percent from
export restrictions; and 40 percent is nontradable, with no distortions. That yields
an average NRA for noncovered farm products of about 3 percent when the distortions to exchange rates also are taken into account and hence a slightly less negative NRA average for the entire sector than for just covered products (upper half
of table 17.3).
The lower half of table 17.3 compares the NRAs for the tradable part of the
agricultural sector with the guesstimate of the NRA facing producers of tradable
nonagricultural goods. For the latter, it is assumed that two-thirds of the value
of production of those goods is import-competing, with an average NRA of
20 percent from import restrictions, and that one-third is exportable, with an
average NRA of 10 percent from export restrictions. That yields an average
NRA for nonagricultural tradables of about 7 percent when the distortions
to exchange rates also are taken into account, and hence a more negative RRA
than NRA for agricultural tradables (lower half of table 17.3). That is, this
guesstimate for assistance to nonfarm producers worsens the estimate of the
antiagricultural bias in Senegal. As can be seen from the annual data in figure 17.5, that bias was present for all but three years in the period from independence to 2004.
Finally, the bottom three rows of table 17.3 show what some key indicators
would have been if exchange rate distortions had not been included. The NRAs
and RRA change little, suggesting that exchange rate policy was not a significant
part of the distortions to agricultural incentives in Senegal.
Table 17.3. NRAs for Agriculture Relative to Nonagricultural Industries, Senegal, 1961–2004
(percent)
Indicator
1961–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
NRA, covered products
NRA, noncovered products
NRA, all agricultural products
Trade bias indexa
NRA, all agricultural tradables
NRA, all nonagricultural tradables
RRAb
Memo item, ignoring exchange
rate distortions:
NRA, all agricultural products
Trade bias indexa
RRAb
14.6
3.2
9.3
0.32
12.7
11.1
21.4
11.7
3.3
7.2
0.27
10.5
11.6
19.8
33.2
3.1
22.4
0.47
30.9
10.3
37.4
33.7
3.2
22.7
0.53
31.1
11.1
37.9
30.3
2.8
20.5
0.47
28.0
9.1
34.1
5.2
3.4
4.7
0.42
8.2
12.4
3.6
6.7
3.2
5.6
0.42
9.7
10.9
1.0
9.9
3.0
6.1
0.20
8.1
9.8
16.3
12.1
3.2
7.5
0.30
10.9
11.4
20.1
8.2
0.29
19.3
5.8
0.22
16.8
22.2
0.47
36.9
22.0
0.51
36.5
21.0
0.49
35.0
6.6
0.36
1.2
6.2
0.40
0.7
6.2
0.21
16.6
6.6
0.25
17.7
Source: Data compiled by the author.
a. Trade bias index is TBI (1 NRAagx兾100)兾(1 NRAagm/100) 1, where NRAagm and NRAagx are the average percentage NRAs for the import-competing and
exportable parts of the agricultural sector.
b. The RRA is defined as 100*[(100 NRAagt )兾(100 + NRAnonagt) 1], where NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the agricultural
and nonagricultural sectors, respectively.
481
482
Distortions to Agricultural Incentives in Africa
Figure 17.5. NRAs for Agricultural and Nonagricultural
Tradables and the RRA, Senegal, 1961–2005
40
percent
20
0
20
40
67
70
19
73
19
76
19
79
19
82
19
85
19
88
19
91
19
94
19
97
20
00
20
03
19
64
19
19
19
61
60
year
NRA, agricultural tradables
NRA, nonagricultural tradables
RRA
Source: Data compiled by the author.
Note: For a definition of the RRA, see table 17.3, note b.
Conclusions
Senegal’s groundnut and rice trade policies have maintained relatively stable
domestic prices for these two products. This has had the effect of providing an
antitrade bias within the agricultural sector. It also meant an increase during the
1970s and a decrease in the latter 1980s in the country’s antiagricultural bias.
More recently, the completion of agricultural market reforms, toward liberalized
rice trade in the late 1990s and the privatization of groundnut processing in the
2000s, has led to a somewhat smaller level of distortion now than existed before
the mid-1980s.
The unwinding of Senegal’s colonial institutions has been among the slowest in
Africa, extending over more than 40 years. Senegalese incomes fell significantly
over the first half of that period, but there was no sudden growth collapse and no
countrywide civil strife. A continuous practice of electoral democracy has been
maintained, with peaceful transfers of political power. This remarkable political
achievement, together with the establishment of new institutions for competitive
markets in agriculture and throughout the economy, provides a potentially strong
foundation for sustained economic growth in the future. It will take decades for the
Senegal
483
country to overcome the legacy of widespread malnutrition and low agricultural
productivity, but with open trade policies and macroeconomic stability, there is
now the opportunity for new investments in both the private and public sectors
that could have a dramatic payoff in reduced poverty and economic growth.
References
Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675–704.
Bonnefond, Philippe, and Philippe Couty. 1991. “Agricultural Crisis: Past and Future.” In C. Delgado
and S. Jammeh, eds., pp. 31–45.
Boone, Catherine. 1992. Merchant Capital and the Roots of State Power in Senegal 1930–1985. New
York: Cambridge University Press.
Delgado, C., and S. Jammeh, eds. 1991. The Political Economy of Senegal under Structural Adjustment.
New York: Praeger.
Easterly, W. 2006. Global Development Network Growth Database. www.nyu.edu/fas/institute/dri/
global percent20development percent20network percent20growth percent20database.htm.
Elbadawi, I. A. 2006. Unpublished estimates of real exchange rate misalignment in developing countries, presented at the World Bank’s Methodology Workshop on Distortions to Agricultural Incentives, March 27–28, Washington, DC.
FAO (Food and Agriculture Organization). 2006. Food and Agriculture Organization Statistics Databases (FAOSTAT). FAO, Rome. http://faostat.fao.org.
Fisher, M., W. A. Masters, and M. Sidibe. 2000. “Technical Change in Senegal’s Irrigated Rice Sector:
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IMF (International Monetary Fund). 1995. “Senegal: Background Papers and Statistical Appendix.”
Report 95/124. International Monetary Fund, Washington, DC.
———. 2005. “Senegal: Selected Issues and Statistical Appendix.” IMF Country Report 05/155. International Monetary Fund, Washington, DC.
———. 2006. International Financial Statistics 2006. International Monetary Fund, Washington, DC.
Jammeh, Sidi C. 1987. “Politics of Agricultural Price Decision-Making in Senegal.” In The Political
Economy of Risk and Choice in Senegal, ed. Mark Gersovitz and John Waterbury, pp. 223–44.
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Kelly, Valerie, and Christopher L. Delgado. 1991. “Agricultural Performance under Structural Adjustment.” In The Political Economy of Senegal under Structural Adjustment, ed. C. Delgado and S.
Jammeh, pp. 97–118. New York: Praeger.
Kite, Rod. 1993. “A Review of Food Marketing Costs, Price and Income Elasticities and Food
Consumption Estimates for Senegal.” U.S. Agency for International Development/Senegal, Dakar.
Masters, W. A. 2007. “Distortions to Agricultural Incentives in Senegal.” Agricultural Distortions
Working Paper 41. World Bank, Washington, DC.
Randolph, Thomas Fitz. 1994. “The Impact of Structural Adjustment Programs on the West African
Rice Economy.” WARDA (Africa Rice Center), Bouake, Côte d’Ivoire.
———. 1997. “The Economics of Rice Production in Senegal.” Background paper for the DAI rice sector study. WARDA (Africa Rice Center), Bouaké, Côte d’Ivoire.
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et al Rentabilité des Filières Agricoles avec la Matrice d’Analyse des Politiques (MAP) : Analyse de
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18
Benin, Burkina Faso,
Chad, Mali, and Togo
John Baffes*
Following decades of development efforts, cotton became the dominant cash crop
in most countries of West and Central Africa (WCA). Apart from suitable agroclimatic conditions, the increase in cotton production is believed to have reflected
the vertically integrated structure of the cotton industry—similar in all WCA cotton-producing countries—which circumvented the free-riding risks that would
have otherwise constrained its performance.
The WCA cotton sectors share a number of similarities. The industries were
pioneered by the French state-owned company CFDT (Compagnie Française de
Développement des Fibres Textiles)—renamed DAGRIS (Développement des AgroIndustries du Sud) in 2001—in conjunction with national state-owned cotton
companies.1 Initially, cotton was used to supply the French textile industry. The
cotton companies had a legal monopsony in cotton buying, and most had a
monopoly on primary processing, marketing, and input supply. Typically, the
companies would announce a panterritorial base buying price before planting,
sometimes supplementing that price with a second payment (payable in the following season as a bonus) based on the company’s financial health. Throughout
the 1980s and 1990s, several attempts were made to change the ownership, management structure, and the pricing mechanisms of the cotton companies, but the
panterritorial and panseasonal pricing along with the heavy government involvement in the sector remained the key characteristics of the sectors all along.
* The author would like to thank Kym Anderson for providing numerous comments and suggestions
on earlier drafts, Gerald Estùr for providing detailed country data, and Marianne Kurzweil for
performing statistical analysis.
485
486
Distortions to Agricultural Incentives in Africa
Most cotton used to be marketed through COPACO (Compagnie Cotonnière), a
CFDT subsidiary, but that changed during the mid-1980s when most cotton companies began marketing their cotton through independent marketing channels.
The cotton industries also benefited from research carried out by the French agricultural research institute CIRAD (Centre de Cooperation Internationale en
Recherche Agronomique pour le Développement).2
All WCA countries are also similar in that they share a common currency, the
CFA franc, which is fixed against the euro. Consequently, their cotton industries
(along with their other export-oriented sectors) enjoy the benefits or suffer the
consequences of the euro-dollar exchange rate fluctuations. Moreover, the fact
that the CFA franc is fixed against the euro often leads to episodes of misalignment. For example, the overvaluation of the CFA franc during the early 1990s
adversely affected the competitiveness of the export sectors in all WCA countries,
including cotton. In 1994, the CFA franc was devalued against the French franc,
thus temporarily restoring the currency equilibrium and competitiveness of the
cotton industries.
The objective of this chapter is to review cotton policies and reform efforts of
Benin, Burkina Faso, Chad, Mali, and Togo and to examine the nature and degree
of distortions to price incentives.3 The period under consideration spans 1970 to
2005. During this period, the prices received by growers in all the focus countries
were remarkably stable, fluctuating between CFAF 150 and CFAF 200 per kilogram of seed cotton (in real 2000 terms). Given the high variability of world
prices, the fluctuating gap between world and domestic prices reflected, for the
most part, world price movements.
There have been four periods with distinct but also similar characteristics
regarding incentives to cotton growers in these countries. First, from 1970 to 1984
(when the price collapse took place), the cotton sectors were heavily taxed with
growers receiving about one-third of the world price (ranging as low as 30 percent
in Mali). The second period, which spans 1985 through 1993 (the year before the
CFA franc devaluation), was characterized by low world prices and an overvalued
currency, with growers in the region receiving about half the world price. The
WCA cotton companies faced severe financial difficulties toward the end of that
period, and they had to be rescued repeatedly through budgetary support measures. The third period begins in 1994 and ends in 1997, when the East Asian financial crisis caused a collapse of commodity prices, including cotton. This period
mirrors the first period, with a high world price and a low share received by growers (about 40 percent of the world price). Similarly, the last period, 1998 to 2005,
is a mirror image of the 1985–93 period, with world prices being low, growers
receiving about 60 percent of the world price, the CFA franc being (most likely)
overvalued, and the cotton companies facing financial difficulties. The similarities
Benin, Burkina Faso, Chad, Mali, and Togo
487
between the second and fourth periods extend to the consideration of policy
reforms; the key difference is that during the second period, policy reforms called
for restructuring the cotton companies so they would become more efficient
without altering their ownership structure. In contrast, current policy reforms call
for privatizing them.
The chapter concludes that when all costs are considered, including inefficiencies in the ginning operations, the sector has been taxed quite heavily, with all five
countries being taxed during all periods. Consistent with the share of prices
received by producers, the rates of taxation were high during 1970–84 and
1994–97 (averaging more than 40 percent) and low during 1985–93 and
1998–2005 (averaging less than 10 percent). With a few exceptions, these tax rates
are remarkably similar across all countries. Note, however, that when ginning
inefficiencies are not factored into the analysis, the second and fourth periods are
characterized by subsidization.
The rest of the chapter begins with a discussion of the stylized facts of the cotton sector in these countries and then outlines the reasons why the reform efforts
currently under consideration should be deepened. Next, summary descriptions
of the history and structure of each cotton sector are presented, along with the
(limited) reform efforts. Finally, the chapter makes a quantitative assessment of
the price distortions involved and then draws some conclusions.
Stylized Facts
In the five WCA countries studied here, cotton provides income to nearly 1.2 million households, equivalent to some 10 million people. During 2001–03, cotton
accounted for between 16 and 76 percent of the merchandise exports of these
countries, and between 2.1 and 6.2 percent of their gross domestic product (GDP)
(table 18.1). In three of the countries—Benin, Burkina Faso, and Mali—cotton is
perhaps the single most important commercial economic activity.4
The performance of the cotton industries in this region has been viewed as a
success story (Lele, van de Walle, and Gbetobouo 1989). Indeed, between 1970
and 1988, cotton yields grew at an annual rate of 6 percent compared with 2 percent annual growth in world yields. Yet this seemingly successful performance
masked a number of weaknesses that called into question the industry’s long-term
sustainability. The post-1980 production increase was attributable solely to
expansion of the area planted to cotton (in contrast to pre-1980 production,
which reflected yield increases, mainly in response to increased fertilizer use).5
The WCA experience also contrasts with the 1.7 percent annual growth rate of
global—and southern and eastern African—cotton output, which is attributable
solely to yield increases.
488
Table 18.1. Summary Statistics for Cotton-Producing Countries of West and Central Africa, 2001–03
Focus countries
Indicator
Country-level statistics
Per capita GDP (constant 2000 dollars)
Per capita GNI (current PPP dollars)
Population (million)
Rural population (percent of total)
Merchandise exports (millions of dollars)
Cotton-related statistics
Value of cotton exports (millions of dollars)
Cotton’s export share (percent)
Cotton’s contribution to GDP (percent)
Cotton’s share of agricultural production valued
at undistorted prices (percent, 2001–05)
Cotton production (thousand tons, lint)
Cotton area (000 hectares)
Cotton yields (kilogram/hectare, lint)
Grower price (CFAF/kilogram, seed cotton)
Average cotton plot (hectares)
Households in cotton production (thousands)
Benin
Burkina Faso Chad
322
1,023
7.7
56
454
241
1,087
12.0
83
263
168
36.9
4.9
4.1
201
76.6
5.0
4.8
152
331
459
202
1.0
325
177
408
435
190
1.9
210
Source: Compiled by the author, using data from FAO 2006, IMF 2006, and World Bank 2006b.
Comparator countries
Mali
Togo
192
231
242
987
893
1,433
8.8
6.2
5.7
75
68
65
325
842
461
64
253
19.7 30.0
2.6
6.2
2.2
3.7
59
277
213
162
1.4
200
225
510
439
193
2.6
300
Cameroon Côte d’Ivoire Senegal
709
1,913
15.5
49
1,932
593
1,435
17.3
56
5,000
435
1,503
10.9
51
1,109
76
16.4
4.2
4.3
111
5.7
0.8
4.0
146
2.9
1.0
2.0
20
1.8
0.3
1.0
68
185
368
183
1.3
150
99
200
498
186
0.7
300
139
253
532
190
1.3
200
18
38
468
185
0.6
70
Benin, Burkina Faso, Chad, Mali, and Togo
489
The panterritorial cotton pricing mechanism is common to all WCA countries.
While it delivered remarkable price predictability and stability, it also turned out
to be a convenient and socially popular income redistribution mechanism, in
effect transferring resources from efficient cotton growers (or growers with transportation or locational advantages) to higher-cost growers. This common price
within each country has thus constrained overall growth and innovation in the
industry by penalizing the most productive entities (or areas) of the sector.
Furthermore, growers received low prices even when world prices were
extremely high (Baffes 2007, figures 3–10). For example, during the early 1980s,
WCA cotton producers were receiving CFAF 60–70 per kilogram for their seed
cotton, while the world price ranged between the equivalent of CFAF 200 and
CFAF 250.6 Similarly, following the 1994 devaluation of the CFA franc, producer
prices were adjusted upward but far less than the increase in world price, thus
denying WCA cotton growers the high prices enjoyed by cotton producers elsewhere. In fact, the econometric evidence in Baffes (2007) shows practically no
comovement between world prices and prices received by cotton growers in these
countries. This finding is ironic considering that the various price formulas
devised to determine the price to be paid to growers by the cotton companies used
the world price of cotton as their starting point.
On the other hand, prices were announced early in each season. The price often
reflected political considerations rather than market realities, and there was no
proper hedging mechanism in place, so the cotton companies (and hence taxpayers of the respective countries or even aid agencies) assumed all the risks associated with world price and currency movements. It meant that in periods of low
prices or overvalued currency (or both), most cotton companies experienced
financial difficulties that in turn led to demands for fiscal transfers from government budgets, thus putting into jeopardy the fiscal position of these countries. For
example, during the late 1990s, the cotton company of Mali was in no position to
manage the downturn in cotton prices because the stabilization fund, created to
set aside a portion of profits from earlier periods of high prices, turned out to be
empty and the company ended up incurring financial losses of CFAF 56 billion
($100 million).7 Eventually, the cotton company was bailed out. Similar bailouts
took place in several WCA countries following the two cotton price collapses, in
the mid-1980s and in the late 1990s.8 More recently, Burkina Faso, which was supposed to be the star cotton performer in the WCA, revealed a three-year cumulative deficit of more than €100 million.
Because of their inefficient and inflexible structure, the cotton companies were
not sufficiently prepared (with improved sales strategies, price and exchange rate
risk management tools, and adoption of new technologies) to respond to the
changing nature of the external environment, especially the downward trend and
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Distortions to Agricultural Incentives in Africa
volatile nature of world prices—a reflection of technological changes and to some
extent subsidies by some countries.9 For example, consider that more than onethird of global cotton output is now of genetically modified origin. Yet with the
exception of Burkina Faso, none of the WCA countries has allowed even field trials to assess the likely benefits and risks of such technology.10 Furthermore,
research has shown that the benefits of fully using biotechnology may be even
higher than the benefits from the elimination of all cotton trade distortions
(Anderson, Valenzuela, and Jackson 2008).
The fact that the CFA franc is fixed against the euro (or the French franc prior
to 1999) and has been subjected to only one adjustment since 1948—from CFAF
50 to CFAF 100 per French franc in 1994—means that WCA governments have
one less policy tool at their disposal. WCA cotton growers may lose (or gain) from
an over (under)-valued CFA franc, and they have been adversely affected by the
recent weakness of the dollar against the euro. Consider, for example, that during
marketing year 2005/06 the Cotlook A Index of average cotton prices in U.S. dollars was roughly the same as it was in 2000/01. However, during the same period,
the WCA currency appreciated from CFAF 731 to the U.S. dollar to CFAF 535 to
the dollar, effectively reducing the world price of cotton in terms of CFA francs by
37 percent. Because it is beyond the control of an individual WCA government to
choose the exchange rate regime that is consistent with the structure of its economy, the case for cotton policy reform is even stronger.
The Case for Revisiting Reform Strategies
Faced with these constraints, a number of WCA countries accepted financial and
technical assistance from the donor community, especially the International
Monetary Fund and the World Bank, to consider policy reforms that could return
the cotton sector to a sustainable development path and ultimately increase the
welfare of cotton growers. However, because the local and international press
often portrayed the reforms as ideologically driven, these changes were widely
viewed with suspicion and, not surprisingly, were subjected to considerable opposition from the countries themselves as well as from bilateral donors. For example,
a lively debate between French and World Bank analysts on WCA cotton reforms
is chronicled in ICAC (1998a, 1998b). The World Bank’s views can also be found
in Baffes (2001).
In a survey of the cotton sectors of Benin, Burkina Faso, and Mali, Bourdet
(2004, p. 41) describes the reasons for opposition to reform:
There are two reasons behind this limited ownership [of reforms] of the
home government. The first is the strong opposition on the part of the
urban elite and some farmer associations in cotton-producing countries to
Benin, Burkina Faso, Chad, Mali, and Togo
491
the privatization of the state-owned ginning enterprises, which are at the
center of the network of institutions and actors composing the cotton sector. The second is the opposition of some bilateral donors, in particular
France as the main bilateral donor, to the deregulation of the sector. No
doubt this “lack of enthusiasm” on the part of the home government of cotton-producing countries and some bilateral donors has contributed to the
slow pace and mixed outcome of reforms.
Note that the unwillingness to engage in a serious reform effort during the
mid-1990s—especially after the CFA franc devaluation—reflected that cotton
prices were high and hence the cotton companies did not face any financial stress
while the respective governments were benefiting from the taxation.
Following the price decline that began in 1997, however, it became increasingly
evident that reforming the cotton industry and allowing the private sector to
undertake some of the industry’s activities was, perhaps, the only feasible way forward.11 This view was slowly accepted, to various degrees, by bilateral donors as
well as by the countries themselves. For example, Edwards (2000, p. 2) concluded
that “it is encouraging to note that the sometimes acrimonious nature of the
recent debate with regard to the future of cotton in the Francophone producing
countries appears to be giving way to a more constructive dialogue, even if consensus on all issues remains elusive.” Despite the understanding and “constructive
dialogue,” policy reforms have been limited, while the paths to reforms are quite
diverse, as the following summary of the five countries indicates.
Reforms in Benin, which were undertaken “by function,” consist of three key
elements: separation of the various links in the cotton supply chain according to
the different functions (input provision and distribution, seed cotton production,
transport, ginning, and trading); division of the responsibility for handling these
functions among a large number of actors (except for research and extension,
which was considered a semipublic good that needed to be jointly funded by the
private and public sectors); and organization of the key decision-making process
(including issues such as the price-setting mechanism and cotton delivery time)
into horizontally organized entities, which must all agree before any sectorwide
decision is made.
The reform process in Burkina Faso was undertaken “by region,” in a sense
reflecting the view that free-riding risks of the cotton sector are high, especially
regarding the provision of inputs (and hence credit recovery) as well as research
and extension services. The market is currently structured into three regional
monopsonies—a dominant state-owned company accounting for about 90 percent of cotton purchases, plus two private companies accounting for the rest.
In Chad, reforms can be characterized, perhaps, as nonexistent. Although the
government of Chad announced that it would disengage from the cotton sector in
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Distortions to Agricultural Incentives in Africa
1999, with the single exception of the privatization of the cotton oil company, so
far it has failed to act accordingly. Factors behind the unwillingness to reform
include the fiscal difficulties of the cotton company (and hence limited interest by
the private sector), the lack of ownership of reform by the government, and more
recently the windfall revenue from crude oil, which has absorbed practically all
capacity and energy by officials who, otherwise, would have been in charge of the
reform process.
Mali, which has contemplated reforms for quite some time, reconsidered its
reform commitment in July 2004 and decided to proceed cautiously by carefully
assessing the pros and cons of the reform process in other WCA countries. In
November 2005, the government increased its share in the capital of the cotton
company (from 60 to 70 percent) and publicly announced that reforms would be
delayed for several years.
In Togo, which has not undertaken any comprehensive reforms, the structure
of its cotton sector is less rigid than those of the other countries. Half of Togo’s
cotton is privately ginned on behalf of the publicly held cotton company (the
remaining is ginned by the cotton company). The government does not interfere
much with the sector, neither taxing it directly nor supporting it in periods of low
prices. Discussions for reforms have been held recently, but no specific action plan
has been proposed.
Details of Each Country’s Policies
One can safely argue that cotton reforms in WCA countries are far less advanced
compared with reforms undertaken by cotton-producing countries in eastern and
southern Africa. This section summarizes the structure of the cotton sectors along
with the key elements and reform processes of the five focus countries.
Benin: 30 years of reform experimentation and
still lots of problems
During 2001–03, cotton contributed 37 percent to total merchandize exports and
almost 5 percent to GDP for Benin. An estimated 325,000 households depend on
cotton cultivation, implying that the livelihoods of nearly 2 million people are
directly linked to the industry’s performance. The average cotton plot in Benin is
about 1 hectare and the typical household produces 450 kilograms of cotton lint,
generating roughly $330 in gross annual income. Cotton in Benin is a rainfed
crop. Two-thirds of cotton growers prepare their land manually, and only some
use fertilizer and chemicals.
Although Benin has a long tradition in cotton cultivation, which started well
before the colonial period, cotton became a commercial crop only in 1952 when
Benin, Burkina Faso, Chad, Mali, and Togo
493
the French state-owned company CFDT introduced a high-yielding cotton variety. Following independence in 1960, the CFDT expanded its operations in northern Benin while another French state-owned company SATEC (Société d’Aide
Technique et de Coopération) introduced cotton in central Benin. Toward the end
of the 1960s numerous village associations (Groupements Villageois) were formed,
specializing in input distribution, credit provision, and marketing.
Under the leftist regime of the 1970s, a new parastatal was created and took
over all activities of the sector. In 1975, six rural development agencies were created—corresponding to the six provinces—with the responsibility of handling
input supply and extension services. Responsibility for ginning operations was
given to another company. Despite the changes, the sector performed dismally.
During 1976–81, cotton output averaged 7,000 tons, 8,000 tons less than the corresponding average during 1970–75 (Baffes 2007, table B1). Following renewed
interest by the government, all cotton-related activities were transferred in 1984 to
the new parastatal SONAPRA (Société Nationale pour la Promotion Agricole),
while numerous cotton development projects were introduced. In the meantime,
the government’s relationship improved with the CFDT, from whom Benin
accepted limited technical assistance.
Reforms were first contemplated in the early 1990s, mainly in response to an
earlier crisis. Following an exceptionally good crop, cotton output increased form
34,000 tons in 1985 to 48,000 tons in 1986. However, the existing ginning operations were unable to process all the cotton. Moreover, the decline in the world price
of cotton (from $1.52 a kilogram in 1985 to $1.08 in 1986) coupled with the appreciation of the CFA franc (from CFAF 378 to the U.S. dollar to CFAF 316 to the
dollar) combined with unchanged producer prices of CFAC 110 for a kilogram of
seed cotton, caused SONAPRA to incur considerable financial losses. Under
Benin’s World Bank–supported structural adjustment program of 1991, the government issued a Letter of Rural Development Policy that envisaged the transfer of
the management of the sector to a new entitity whose operations would be based
on the principles of a common guaranteed panterritorial price to producers,
panterritorial prices for inputs, obligation for producers to sell their cotton to
specific ginners, and obligation for ginners to buy all cotton from producers.
As a result of this policy shift, the equivalent of 20 percent of input supply
activities was privatized in 1993 on a pilot basis; by 1995, 80 percent of such
activities were privatized. SONAPRA eventually withdrew from the input supply
market in 2000. A second step included issuing licenses to three new private ginning operations in 1995, followed by several more in 1998. That added 225,000
tons of seed-cotton ginning capacity to an existing 335,000 tons by SONAPRA.
Yet, the new structure caused numerous conflicts resulting in frequent political
interference.
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Distortions to Agricultural Incentives in Africa
In response, the government created a number of entities that assumed
responsibilities for various aspects of the cotton industry. They included a cooperative belonging to the regional producers unions (Coopérative d’Approvisionnement et de Gestion des Intrants Agricoles), formed in 1998. A second entity (l’Association Professionnelle des Egreineurs du Bénin) was created in 1999 with key
responsibility for coordinating activities among ginneries. Another organization
(l’Association Interprofessionnelle du Coton) was established in 1999 to manage
supply chain-related functions. Finally, a fourth organization (CSPR, or Centrale
de Sécurisation des Paiements et de Recouvrement) was formed in 2000 with the
mandate to recover debts from growers, collect and deliver cotton to ginners, and
make payments to producers.
Despite the creation of all these organizations and associations, it appears that
the performance of the sector has not improved. During the 2003–04 season, private traders bought one-quarter of the seed cotton, which meant that those farmers who sold to the independent traders escaped the credit recovery scheme set up
by CSPR. Consequently, tensions among different actors escalated. The difficulties
faced by the sector can be gauged by the sharp decline in cotton production from
171,000 tons of lint in 2004–05 to 82,000 tons in 2005–06.
Burkina Faso: The implosion of a star performer
Cotton is the most important cash crop in Burkina Faso, accounting for almost
two-thirds of total merchandise exports and contributing 5 percent to the country’s GDP in 2001–03. The sector provides income to an estimated 210,000 households, implying that as many as 1.5 million people are affected by the industry.
The average cotton plot in Burkina Faso is a little less than 2 hectares.
Cotton was introduced in Burkina Faso toward the end of the colonial period.
The development of the sector was the responsibility of the CFDT, which
remained in charge until 1975, when it was replaced first by a joint venture
between the government and the CFDT and in 1979 by a new cotton parastatal
company, SOFITEX (La Société Burkinabè des Fibres et Textiles).
Reforms were first considered in 1991, when, under a World Bank–supported
structural adjustment program, it was decided that management responsibilities
for the cotton sector would be transferred to growers and the cotton company.
In 1998, the government reduced its stake in the cotton company by transferring
30 percent of its shares to a producer organization, UNPCB (Union Nationale des
Producteurs de Coton du Burkina Faso), and 34 percent to DAGRIS (formerly
CFDT). As a second step, a 12-member committee was formed in 1999 to coordinate the functions of SOFITEX and UNPCB for activities such as determination
of the farmgate and input prices and management of the research program. The
Benin, Burkina Faso, Chad, Mali, and Togo
495
committee’s representation consists of seven producers, three SOFITEX representatives, and two government representatives. The third step involved the introduction of two private companies in 2004 with exclusivity zones for eight years,
representing about 15 percent of cotton production—the two companies are
SOCOMA (Société Cotonnière du Gourma) and FASE COTON. In 2006, an
umbrella organization was created to coordinate the actions of all three cotton
companies.
Until very recently, the reform process in Burkina Faso was considered a success compared with other WCA cotton-producing countries. In fact, Agence
Française Développement (2004, p. 1) produced a report noting that “Burkina
Faso developed its cotton sector in an original homegrown way. Now one of the
world’s most competitive cotton industries, it has modern tools and institutions
to sustain its development.” Indeed, between 1995 and 2005, cotton output in
Burkina Faso increased fivefold, from 64,000 tons to almost 300,000 tons (Baffes
2007, table B2). Moreover, Burkina Faso is the only country in Sub-Saharan Africa
(apart from South Africa) that is in the process of introducing genetically modified cotton.
Yet, the expansion of the sector along with the drying up of the cotton stabilization fund, as well as the recently revealed €110 million, three-year cumulative
deficit, may call into question the sector’s long-term sustainability. Furthermore,
it appears that despite the entrance of private ginneries as well as the restructuring
of the ownership of SOFITEX, the government is still the key decision maker in
the sector. To address the crisis, the cotton companies and the producers agreed to
a new pricing formula as of March 2006. The pricing formula is part of a newly
established smoothing fund (fonds de lissage)—to be distinguished from the earlier stabilization fund (fonds de soutien). The smoothing fund is expected to be
professionally managed on agreed and easily monitored parameters (such as
world price and exchange rate). However, as is the case with all stabilization funds,
there is always the risk of running large deficits if adverse prices or exchange rate
conditions persist for long.
Chad: Windfall oil revenue shelves cotton reform
Chad’s cotton sector is a major part of the economy, contributing 20 percent to
total merchandize exports and 2.4 percent to GDP in 2001–03. The sector is the
key source of income to some 200,000 households (or as many as 350,000 according to some sources); with an average household size of 5–6 people, this amounts
to 1.2–1.4 million people. The average cotton plot is about 1.5 hectares. Chad’s
cotton yields are very low, even by WCA standards (about half the yields in Benin
or Burkina Faso).
496
Distortions to Agricultural Incentives in Africa
Cotton cultivation was introduced in 1928 under forced-labor conditions—
Chad was the first WCA country to cultivate cotton. Production grew steadily to
40,000 tons during the early 1960s, making Chad the leading cotton producer in
the WCA. During 1970–75, Chad’s cotton output averaged 46,000 tons of cotton
lint, almost twice as much as Mali’s average of 25,000 tons and three times as
much as Benin’s and Burkina Faso’s averages of 15,000 tons each.
The cotton company of Chad—Cotonchad—was created in 1971, replacing
the earlier parastatal, Cotonfran. The government is the majority shareholder
(75 percent), followed by DAGRIS (19 percent) and the local private banking sector (6 percent). The key missions of Cotonchad were (and still are) to distribute
inputs, purchase and gin seed cotton, and trade cotton through its commercial
offices in Paris. Cotonchad faced serious difficulties during the price decline of
1985, which were further exacerbated by a drought during that year. Production
declined from 60,000 tons in 1983–84 to 36,000 tons in 1984–85. It took the sector
five years to return to earlier levels of output.
However, Contonchad’s financial stress, the heavy taxation by the government,
along with civil war and a war with Libya, imposed a heavy burden on the sector
(Azam and Djimtoingar 2004). For example, prices paid to cotton growers fluctuated at the low level of CFAF 80–100 between 1983 and 1993 (Baffes 2007, table
B4). The 1994 devaluation provided temporary relief to the sector, as prices paid
to growers increased gradually from CFAF 90 in 1993 to CFAF 195 in 1997 (cotton
output exceeded 100,000 tons that year). However, the boom was short-lived—
world price declines along with mismanagement of the sector and heavy taxation
soon forced Cotonchad to reduce the grower price to CFAF 160.
In response to these developments, the government set up a Cotton Sector
Reform Committee in 1999 to evaluate likely reform strategies. The committee’s
primary focus was on improving the incomes of cotton farmers through liberalizing the sector along with improving the performance of producer organizations.
In 2002, the Cotonchad-owned factory that made oil and soap was privatized, but
that was the only policy reform. The government, together with Cotonchad,
organized a workshop in April 2004 in Ndjamena to find ways to improve the
financial situation of Cotonchad and boost cotton production. However, undertaking deeper reforms was not placed high on the agenda.
Since then, the momentum for reforms has weakened even further following
the country’s windfall revenue from crude oil; not surprisingly, the cotton reform
agenda has been affected in two interrelated ways. First, crude oil has displaced
cotton as the key source of income for the government. Consider, for example,
that during 2007, the export earnings from cotton were expected to be less than
$70 million, just a fraction of oil revenue, which was expected to reach $1.2 billion—$930 million from taxes and $250 million from royalty fees. Second,
Benin, Burkina Faso, Chad, Mali, and Togo
497
increased activity in the crude oil sector has left officials with little time or energy
to address reforms in the cotton sector.
Mali: Not wanting to engage in reforms
Cotton is Mali’s most important cash crop. During 2001–03, it contributed
30 percent to total merchandise exports and more than 6 percent to the country’s
GDP. An estimated 300,000 households depend on the crop, which implies that as
much as one-third of Mali’s population is affected by the sector’s performance.
The average cotton plot in Mali is 2.6 hectares. As is the case with other WCA
countries, cotton is a rainfed crop, and most of the land is prepared manually.
Cotton is typically rotated with food crops such as millet, sorghum, maize, and
groundnuts.
Cotton was introduced in Mali during the late 1940s by the CFDT, which continued its involvement even after independence in 1960. A national cotton company,
the CMDT (Compagnie Malienne pour le Développement du Textile), was formed in
1974 as a joint venture between the government (60 percent) and the CFDT
(40 percent). The CMDT has played a key role in the ownership, management, and
control of the various components in the supply chain, including the cottonoil-processing sector. It has also assumed responsibility for rural development,
particularly road maintenance and some extension services in the major cottongrowing areas. In addition to the CMDT, another regional organization, Office de la
Haute Vallee du Niger, has been involved in the cotton sector since 1970. This organization was allocated a specific part of the country in which to operate and has
responsibility for the promotion of all crops. It is involved in all cotton production
activities but not in ginning; instead it pays the CMDT, which currently owns and
operates two ginneries in the organization’s zone, for the ginning.
The first comprehensive review of the cotton sector in Mali was undertaken in
1989, and to a large degree the sector’s current institutional setting reflects that
review.12 The key steps taken in 1989, which were supported by the donor community, included financial autonomy for the CMDT, the introduction of a minimum producer price, and establishment of a stabilization fund. The CMDT’s
weak management, along with the 1999 decline of cotton prices, resulted in a
financial crisis. In response, the CMDT set a low price for the 2000–01 season,
causing many growers to abandon cotton cultivation. Cotton output declined
from 197,000 tons in 1999–2000 to 102,000 tons in 2000–01 (Baffes 2007,
table B6). Faced with these difficulties, the government prepared a comprehensive
restructuring plan (Lettre de Politique de Développement du Secteur Coton), which
envisaged reforming the CMDT’s institutional arrangements in order to restore
the competitiveness of the sector and ultimately foster broad-based growth. The
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Distortions to Agricultural Incentives in Africa
poor financial shape of the CMDT, however, has persisted. Between 1997 and
2004, it generated profits only twice, while the losses in 2005 alone amounted to
some CFAF 48 billion ($91 million).
Togo: Lots of problems
Cotton is Togo’s second largest primary commodity export after phosphate fertilizer. It contributed 16 percent to export earnings and 4.2 percent to GDP in
2001–03. Togo’s cotton production is in the same range as that of Chad: during
2001–03, it averaged 68,000 tons. Its yields, however, are much higher than in
Chad but lower than in Benin, Burkina Faso, and Mali.
Cotton was introduced in Togo relatively recently. For example, during the
early 1970s, cotton production averaged only 2,000–3,000 tons. In 1974, the stateowned company SOTOCO (Société Togolaise de Coton) began its operations by
handling most of the input supply and marketing activities as well as research,
extension, and maintenance of the road network (World Bank 1988). Production
increased significantly after the 1980s and exceeded 50,000 tons following the
1994 devaluation (Baffes 2007, table B8).
Togo’s cotton sector differs from the other WCA countries in that, following
the purchase of cotton, half of the crop is sold to three private ginneries at a price
equal to the price paid to the producers plus marketing and transportation costs.
The share of cotton delivered to each ginnery is fixed, set in proportion to its ginning capacity. While Togo’s cotton sector was affected by the late-1990s decline in
prices, SOTOCO responded quickly by cutting down operating costs and reducing the prices paid to growers. That was the only feasible alternative because no
stabilization fund was in place to cover losses, and the government’s tight financial situation did not allow any budgetary support (IMF 2003). However, the
recent price declines appear to have derailed the sector’s performance. During
2005–06, cotton production dropped to 28,000 tons, less than half of the decade’s
average.
Estimating Distortions to Cotton Sector Incentives
The task of quantifying the distortions to cotton sector incentives in the WCA
contains elements of both simplicity and complexity. The simple part reflects the
presence of a well-defined world price indicator, the Cotlook A Index, one component of which is WCA cotton (Baffes 2007, appendix A). Because the price of
WCA cotton tracks the A Index very closely, one can use it as the world price
benchmark.13 Second, all WCA cotton companies pay panterritorial and panseasonal prices, making it easy to calculate the gap between the world price and prices
Benin, Burkina Faso, Chad, Mali, and Togo
499
received by growers. Third, almost all cotton is exported and hence there is no
need to deal with domestic marketing distortion issues. Fourth, most of the value
of cotton comes from cotton lint, so calculating the distortion to cotton lint, to a
large extent, captures the distortions in the entire cotton market. Last, the rate of
conversion (that is, the ginning ratio) between the farm product (seed cotton) and
the internationally traded commodity (cotton lint) is a well-known parameter
and very similar across countries and years.
Nonetheless, quantification of the distortions is a complex task for several reasons. First, in addition to explicit taxation, the governments “used” the profits from
the cotton companies for a number of other activities without explicitly documenting the financial transactions. Second, in periods of low prices when the national
cotton companies incurred losses, the governments would rescue them through
budgetary transfers. Third, and most important, numerous inefficiencies are inherent in the value chain—especially ginning—making it difficult to distinguish
between inefficiencies and taxation. Fourth, the cotton companies often transferred
resources to producers through the provision of public services, such as construction and maintenance of rural roads, which again are very difficult to quantify.
The rest of this section examines distortions to cotton prices, calculated using
the methodology of Anderson et al. (2008) to show nominal rates of assistance
(NRA) to cotton farmers for the five focus countries, taking into account international and domestic transportation costs as well as ginning costs. The NRAs are
expected to vary widely over time, because new econometric evidence shows that
the domestic cotton price bears little resemblence to prices in the international
marketplace (Baffes 2007).14
Quantifying the distortions requires three calculations and subsequent adjustments to the world price of cotton. First, the free on board (fob) price for exports
and the cost, insurance, and freight (cif) cost of imports are calculated; these are
common to all WCA countries. The A Index adjustment by the cif-to-fob costs
consists of two components: international freight rates—costs from the export
port to the final destination port— and marketing charges. International freight
rates are very similar regardless of the port of origin (Baffes 2007, table B9). Marketing charges are standard charges across the industry, representing 3 percent of
the A Index until 2002–03 and 2.6 percent after that. These two costs account for
an average of 8 percent of the A Index.
The second calculation involves domestic transport costs, which differ substantially between landlocked countries and countries with access to seaports
(Baffes 2007, table B10). For example, in 2005–06, the costs of transporting 1 kilogram of cotton lint from Chad to the port of Douala in Cameroon was CFAF 100,
whereas transportations costs were less than half of that for Benin, Senegal, and
Togo, which have easier access to seaports.
500
Distortions to Agricultural Incentives in Africa
The third calculation concerns ginning costs, which ranged between CFAF 50
for a kilogram of cotton lint in the early 1970s to more than CFAF 200 after the
mid-1990s (Baffes 2007, table B9). These figures represent the costs as they are
reported in the financial statements of the cotton companies, which are characterized by numerous inefficiencies, and consequently do not reflect the costs of ginning under free market conditions. To obtain the true costs of ginning, these
reported costs must be adjusted downward. Analysis performed during 2005
found that the actual ginning costs during that year were 18 percent lower than
the amounts the cotton companies reported.15 However, it is believed that in earlier years, the true ginning costs were much lower, because the companies could
finance public good activities (such as road maintenance). Hence, the adjustment
factor used to estimate the actual ginning costs was 25 percent, that is, ginning
costs are assumed to be 25 percent lower than what is reported.
Specifically, the NRA for period t is calculated as follows:
NRAt ⫽ {PtD兾[(PtW ⫺ CtF)Rt ⫺ CtI ⫺ CtG]} ⫺ 1,
where PtD denotes the price received by cotton growers, PtW denotes the A Index
price; CtF denotes freight rates and marketing charges; Rt denotes the CFAF/$
March-to-July average bilateral exchange rate, consistent with the WCA cottonmarketing season; CtI denotes inland transport costs; and CtG denotes actual ginning costs (including farm-to-ginnery transport costs). This calculation of the
NRA is consistent with the distortion taking place at farmgate level (that is, a production tax), a specification chosen on the basis that the cotton companies
become the owners of seed cotton at the farmgate level. The price data (in constant 2000 terms) are summarized in table 18.2, along with their ratio (the grower
price as a percentage of the A Index price). These confirm the earlier assertion that
the producers’ share has been low during the first (1970–84) and third (1994–97)
periods and much higher during the second period when international prices
were low (1985–93) and the fourth period (1998–2005).
The estimates in table 18.3 report the NRAs when all costs are taken into consideration (that is, freight rates and inland transport costs as well as ginning costs
and the “inefficiency” factor). They reveal that cotton growers in the focus countries were taxed, on average, by 50 percent during 1970–84. That tax was reduced
to 25 percent on average in the 1990s (although during 1985–89 it was only 8 percent), before the taxation was largely removed; it averaged less than 4 percent after
1998. The heaviest taxation took place in Mali, where during 1970–84 and the
1990s, farmers were taxed at average rates of 57 and 29 percent, respectively, but
the rates were not much less in the other focus countries.
Finally, the variability of prices farmers received versus international prices
has also been examined. This is done using the Z-statistic (because prices are
Table 18.2. Cotton Price Statistics, West and Central African Countries, 1970–2005
Indicator
Benin
Burkina Faso
Cameroon
Chad
Cotlook A Index (constant 2000, CFAF/kilogram of seed cotton)
1970–84
532
438
508
405
1985–93
380
290
284
326
1994–97
503
466
445
468
1998–2005
309
304
322
291
Prices received by cotton growers (constant 2000, CFAF/kilogram of seed cotton)
1970–84
195
146
208
134
1985–93
209
148
178
170
1994–97
218
176
198
183
1998–2005
190
177
176
161
Producer’s share of Cotlook A Index (percent)
1970–84
38
35
42
34
1985–93
56
52
64
53
1994–97
45
39
44
40
1998–2005
62
59
59
56
Price variability (Z statistic)
Cotlook A Index
124
116
111
96
Domestic
18
19
24
18
Ratioa
7
6
5
5
Côte d’Ivoire
Mali
Senegal
Togo
639
392
497
312
585
329
465
298
506
289
467
316
532
345
478
303
282
204
204
178
172
156
168
170
171
156
199
183
188
179
204
177
45
53
42
57
30
49
37
59
35
55
43
59
37
53
43
59
150
26
6
130
22
6
115
13
9
135
19
7
Source: Baffes 2007, table 7.
501
a. This ratio is the ratio of the Z statistic of the Cotlook A Index price to that of the domestic price, where the Z statistic is the square root of the average squared deviation
of the price from its value lagged one period (or the first difference in the price; see Schiff and Valdes 1992, appendix 3-2). For example, for Benin the year-to-year
variability of the world price has been seven times higher than the year-to-year variability of the price received by cotton growers (both prices having been expressed in
domestic currency and in real terms using the GDP deflator).
502
Distortions to Agricultural Incentives in Africa
Table 18.3. NRAs for Cotton Growers, Benin, Burkina Faso,
Chad, Mali, and Togo, 1970–2005
(percent)
Country
1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–05
Benin
Burkina Faso
Chad
Mali
Togo
Unweighted
average
⫺44
⫺44
⫺47
⫺56
⫺41
⫺46
⫺49
⫺48
⫺48
⫺55
⫺46
⫺49
⫺49
⫺58
⫺52
⫺59
⫺60
⫺56
⫺5
⫺8
6
⫺17
⫺14
⫺8
⫺24
⫺26
⫺21
⫺25
⫺25
⫺24
⫺22
⫺28
⫺21
⫺33
⫺24
⫺26
⫺6
1
⫺3
3
⫺13
⫺5
Source: Baffes 2007.
nonstationary and hence measures such as standard deviation may give misleading results), which is the square root of the average squared deviation of the price
from its value lagged one period (or the first difference in the price). The results
are summarized in the fourth panel of table 18.2. They indicate that the world
prices have been, on average, five to seven times more volatile than domestic
prices in year-to-year variation. This finding simply confirms that the pricesetting mechanism in the focus countries has indeed stabilized the domestic price
of cotton—albeit at a very low level until recently—compared with prices in the
international market, as is illustrated in figure 18.1 for Burkina Faso, the most
populous of the focus countries.
Conclusion
This study of incentives to WCA African cotton growers is divided into four subperiods. During 1970–84, cotton growers in the five focus countries effectively
received only half what they would have received under free-market conditions.
During the second period, 1985–93, even though the average tax rate fell to only
13 percent, the cotton companies faced severe financial difficulties because of the
crash in international prices, and they had to be rescued repeatedly through budgetary support measures. In the third period, which begins with the devaluation of
the CFA franc in 1994 and ends with the beginning of the next price decline in
1997, the sectors were taxed, on average, by 35 percent. During the last period,
1998 to 2005 (which in many ways is a mirror image of the 1985–93 period), cotton growers were taxed, on average, at 4 percent. Note that the last period was
characterized by low world prices (see figure 18.1), the CFA franc being (most
likely) overvalued, and most cotton companies facing financial difficulties. It is
thus not out of the question that taxation rates could rise again in a future period
of high international prices.
Benin, Burkina Faso, Chad, Mali, and Togo
503
Figure 18.1. International Price and Grower Price for Cotton,
Burkina Faso, 1970–2005
CFAF per kilogram (real 2000 prices)
700
600
500
400
300
200
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
74
19
72
19
19
19
70
100
year
international price (Cotlook A Index)
grower price
Source: Baffes 2007, based on data from SOFITEX and the World Bank’s commodity price series.
Notes
1. In addition to their core activity, which is ginning, the cotton companies often engaged in
numerous other activities such as input distribution, provision of research and extension services, and
maintenance of rural roads. Detailed data and estimates of distortions reported in this chapter can be
found in Baffes (2007).
2. See Baffes (2007, table 1) for key institutions involved in the cotton sectors of WCA countries.
3. Together with Cameroon, Côte d’Ivoire, and Senegal, these countries account for 99 percent of
WCA cotton output and about 3.5 percent of global cotton production. Cotton produced by WCA
countries Cameroon, Côte d’Ivoire, and Senegal is analyzed elsewhere in this volume in separate chapters (chapters 13, 14 and 17), and those countries are also included in a fuller comparative analysis in
Baffes (2007). Three minor WCA cotton producers not included here are Central Africa Republic,
Guinea, and Niger.
4. In all five countries, cotton is not a large share of the overall value of agricultural production
when subsistence crops are taken into account. Nontradable grains and tubers are crucial sources of
carbohydrates for the poor, food-insecure farm families in these countries, with cassava, millet,
sorghum, and yams accounting for between 30 and 55 percent of the value of their farm production .
5. A growth decomposition analysis for the 1980–2005 period reveals that cotton yields in WCA
countries remained (statistically) stagnant (Baffes 2007).
6. Cotton refers to cotton lint, sometimes called cotton fiber (the internationally traded commodity). When reference to seed cotton (the farm product) is made, it is explicitly mentioned. The rate of
conversion from seed cotton to cotton lint—the ginning outturn ratio—is currently about 42 percent
504
Distortions to Agricultural Incentives in Africa
in all WCA countries, that is, 1 kilogram of seed cotton produces 0.42 kilograms of cotton lint and
0.58 kilograms of seeds, which, in turn, are transformed into cotton oil and cotton cake.
7. Despite the poor performance of price stabilization funds and supply controls (Gilbert 1996),
there have been renewed calls for such mechanisms. See, for example, discussions in Ravry et al. (2006)
and OXFAM (2007). The failure of stabilization mechanisms should not be surprising if one considers
that during the seven 12-month intervals between March 1995 and March 2002, cotton prices declined
six times and remained at the same level once, without experiencing any increase. Under such circumstances, any stabilization fund is likely to go bankrupt no matter how well it is run. Conversely, if prices
experience continued increases—a less likely scenario considering their long-term downward trend—
the stabilization fund is likely to be subject to misuse, as was the case in several WCA countries.
8. The 1985 cotton price collapse was a result of a policy shift in U.S. commodity programs
(including cotton). It also reflects a policy shift in China that favored cotton production there. The
decline in the late 1990s reflects the East Asian financial crisis, again common to most commodities.
Nevertheless, cotton has not been part of the recent price boom, with the likely reasons reflecting a
combination of the following: cotton subsidies continue to depress prices considerably; productivity
gains from genetically modified cotton and other technological advances have kept production costs
low compared with other commodities; and the price increase in the overall commodity price index
stems from the increasing demand for certain commodities for biofuels production (such as maize and
sugarcane for ethanol and rapeseed for biodiesel).
9. For a review of the distortions in the global cotton market, see Baffes (2005). The U.S. cotton
subsidies were subject to a WTO (World Trade Organization) case brought by Brazil (Schnepf 2004).
Benin, Burkina Faso, Chad, and Mali also brought a case to the WTO demanding compensation from
the countries that subsidize their cotton sectors (see Sumner 2006 and Anderson and Valenzuela
2007).
10. Under the West Africa Regional Biosafety Program, a $23.4-million World Bank technical
assistance operation, the members of the West African Economic and Monetary Union are expected to
establish national and regional biosafety policies and procedures to ensure proper assessment of the
risks and benefits of biotechnology products (World Bank 2006a).
11. Reform strategies in the WCA have been discussed in various contexts. See, for example,
Pursell (1998), Badiane et al. (2002), Goreux (2004), and Baghdadli (2006).
12. Developments in the Malian cotton sector were also influenced by an uprising by cotton farmers in the early 1990s (Bingen 1998).
13. In a study that examined the comovement of the various components of the A Index as well as
the comovement between the A Index and its components, Baffes and Ajwad (2001) found that the
WCA cotton prices tracked the A Index very closely.
14. An econometric model was used in Baffes (2007) to estimate the degree to which world
price movements influence the domestic price determination mechanism in the five focus countries
as well as in Cameroon, Côte d’Ivoire, and Senegal. Only in those latter three countries (where cotton
is less important to the economy than in the five focus countries) was the domestic-world price link
significant.
15. Personal communication with Gerald Estùr, March 16, 2007.
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Appendix A
METHODOLOGY FOR
MEASURING
DISTORTIONS
TO AGRICULTURAL
INCENTIVES
Kym Anderson, Marianne Kurzweil, Will Martin,
Damiano Sandri, and Ernesto Valenzuela*
This appendix outlines the methodological issues associated with the task of measuring the impact of government policies on incentives faced by farmers and food consumers. The focus is on those border and domestic measures that arise exclusively
from government actions, that, as such, may be altered by a political decision, and
that have an immediate effect on consumer choices, producer resource allocations,
and net farm incomes. Most commonly, these measures include import or export
taxes, subsidies, and quantitative restrictions, supplemented by domestic taxes or
subsidies for farm outputs or inputs, and consumer subsidies for food staples. The
incentives faced by farmers are affected not only by the direct protection or taxation
of primary agricultural industries, but also indirectly via policies assisting nonagricultural industries, given that the latter may have an offsetting effect by drawing
resources away from farming. This appendix begins by outlining what theory
suggests should be measured directly and indirectly. It then outlines the way the
theory is put into practice through this study.
* Thanks for invaluable comments are due to many project participants, including Bruce Gardner, Tim
Josling, Will Masters, Alan Matthews, Johan Swinnen, Alberto Valdés, and Alex Winter-Nelson, plus
Ibrahim Elbadawi. The information in this appendix is also available in Anderson et al. 2008a and 2008b.
507
508
Distortions to Agricultural Incentives in Africa
What, According to Theory,
Should Be Measured
The key objective of this study—obtaining a long time series on a wide range of
countries that are at different stages of development—requires that the indicators
be simple. If the indicators are simple, this also means that it would be easier to
update the indicators subsequently for policy monitoring. Throughout, we have
followed the concept of Bhagwati (1971) and Corden (1997) whereby a market
policy distortion is, by definition, imposed by a government to create a gap
between the marginal social return to a seller and the marginal social cost to a
buyer in a transaction. The distortion creates an economic cost to society that may
be estimated using welfare measurement techniques such as those pioneered by
Harberger (1971). As Harberger notes, this focus allows for great simplification in
the evaluation of the marginal costs of a set of distortions: changes in economic
costs may be evaluated by taking into account the changes in volumes directly
affected by the distortions and ignoring all other changes in prices. In the absence
of divergences such as externalities, the measure of a distortion is the gap between
the price paid and the price received, irrespective of whether the level of these
prices is affected by the distortion.
Other developments that change the incentives facing producers and consumers
may include flow-on consequences of the distortion, but these should not be confused with the direct price distortion that we aim to estimate. If, for instance, a country is large in world trade for a given commodity, the imposition of an export tax may
raise the price in international markets, thereby reducing the adverse impact of the
distortion on producers in the taxing country. Another flow-on consequence is
the effect of trade distortions on the real exchange rate, which is the price of traded
goods relative to nontraded goods. Neither of these flow-on effects is of immediate
concern, however, because, if the direct distortions are accurately estimated, they may
be incorporated as price wedges into an appropriate country or global economywide computable general equilibrium model, which, in turn, will be able to capture
the full general equilibrium impacts (inclusive of the real exchange rate effects) of the
various direct distortions to producer and consumer prices.
Importantly, the total effect of distortions on the agricultural sector will depend
not only on the size of the direct agricultural policy measures, but also on the magnitude of distortions generated by direct policy measures that alter the incentives in
nonagricultural sectors. It is the relative prices and, hence, the relative rates of government assistance that affect producer incentives. In a two-sector model, an import
tax has the same effect on the export sector as an export tax: this is the Lerner (1936)
symmetry theorem. This carries over to a model that has many sectors and is unaffected if there is imperfect competition domestically or internationally or if some of
the sectors produce only nontradables (Vousden 1990). The symmetry theorem is
Methodology for Measuring Distortions to Agricultural Incentives
509
therefore also relevant in the consideration of distortions within the agricultural
sector. In particular, if import-competing farm industries are protected, such as
through import tariffs, then this has similar effects on the incentives to produce
exportables as does an explicit tax on agricultural exports; and, if both measures are
in place, this represents a double imposition on farm exporters.
In what follows, we begin by focusing on direct distortions to agricultural
incentives before turning to those distortions affecting the sector indirectly
through nonagricultural policies.
Direct agricultural distortions
Consider a small, open, perfectly competitive national economy that encompasses
many firms producing a homogeneous farm product with only primary factors.
In the absence of externalities, processing, and producer-to-consumer wholesale
marketing, plus retail marketing margins, exchange rate distortions, and domestic
and international trading costs, such a country would maximize national economic welfare by allowing both the domestic price of the farm product and the
consumer price of the farm product to equal E, times P, where E is the domestic
currency price of foreign exchange, and P is the foreign currency price of the identical product in the international market. Thus, any government-imposed diversion from this equality, in the absence of any market failures or externalities,
would be welfare-reducing in the small economy.
Price-distorting trade measures at the national border
The most common distortion is an ad valorem tax on competing imports (usually
called a tariff), tm. Such a tariff on imports is the equivalent of a production subsidy and a consumption tax, both at rate tm. If this tariff on the imported primary
agricultural product is the only distortion, its effect on producer incentives may
be measured as the nominal rate of assistance (NRA) to farm output conferred by
the border price support, (NRABS), which is the unit value of production at the
distorted price, less its value at the undistorted free-market price expressed as a
fraction of the undistorted price, as follows:1
E ⫻ P(1 tm) ⫺ E ⫻ P
NRABS ⫽ ᎏᎏᎏ ⫽ tm.
E⫻P
(A.1)
The effect of this import tariff on consumer incentives in this simple economy
is to generate a consumer tax equivalent (CTE) on the agricultural product for
final consumers:
CTE ⫽ tm.
(A.2)
510
Distortions to Agricultural Incentives in Africa
The effects of an import subsidy are identical to those in equations (A.1) and
(A.2) for an import tax, but tm would have a negative value in that case.
Governments sometimes also intervene through an export subsidy, sx (or an
export tax, in which case sx would be negative). If this is the only intervention,
then:
NRABS ⫽ CTE ⫽ sx.
(A.3)
If any of these trade taxes or subsidies are specific rather than ad valorem (for
example, US$ per kilogram rather than z percent), the ad valorem equivalent may
be calculated using slight modifications of equations (A.1), (A.2), and (A.3).
Domestic producer and consumer price-distorting measures
Governments sometimes intervene through a direct production subsidy for
farmers, sf (or a production tax, in which case sf is negative, including through
informal taxes in kind by local and provincial governments). In that case, if only
this distortion is present, the effect on producer incentives may be measured as
the NRA to farm output conferred by the domestic price support (NRADS),
which is as above except that sf replaces tm or sx, but the CTE is zero in this case.
Similarly, if the government imposes only a consumption tax, cc, on this product
(or a consumption subsidy, in which case cc is negative), the CTE is as above
except that cc replaces tm or sx, but the NRADS is zero in this case.
The combination of domestic and border price support provides the total rate
of assistance to output and domestic consumer tax equivalent:
NRAo ⫽ NRABS ⫹ NRADS, CTE ⫽ NRABS ⫹ ct .
(A.4)
What if the exchange rate system is also distorting prices?
Should a multitier foreign exchange rate regime be in place, then another policyinduced price wedge exists. A simple two-tier exchange rate system creates a gap
between the price received by all exporters and the price paid by all importers for
foreign currency, thereby changing both the exchange rate received by exporters
and the exchange rate paid by importers relative to the equilibrium rate, E, that
would prevail without this distortion in the domestic market for foreign currency
(Bhagwati 1978).
Exchange rate overvaluation of the type we consider here requires controls by
the government on current account transfers. A common requirement is that
exporters surrender their foreign currency earnings to the central bank for exchange
to local currency at a low official rate. This is equivalent to a tax on exports to the
extent that the official rate is below the level of the exchange rate in a market without
government intervention. This implicit tax reduces the incentive of exporters to
Methodology for Measuring Distortions to Agricultural Incentives
511
export and, hence, the supply of foreign currency flowing into the country. With
less foreign currency, demanders are willing to bid up the purchase price. This
provides a potential rent for the government that may be realized by auctioning
off the limited supply of foreign currency extracted from exporters or creating a
legal secondary market. Either mechanism will create a gap between the official
and parallel rates.
Such a dual exchange rate system is depicted in figure A.1, in which it is
assumed that the overall domestic price level is fixed, perhaps by holding the
money supply constant (Derviş, de Melo, and Robinson 1981). The supply of foreign
exchange is given by the upward sloping schedule, Sfx, and demand by Dfx, where
the official exchange rate facing exporters is E0 and the secondary market rate
facing importers is Em. At the low rate, E0, only QS units of foreign currency are
available domestically, instead of the equilibrium volume QE that would result if
exporters were able to exchange, at the equilibrium rate, E units of local currency
per unit of foreign currency.2 The gap between the official and the secondary market exchange rates is an indication of the magnitude of the tax imposed on trade
by the two-tier exchange rate: relative to the equilibrium rate, E, the price of
importables is raised by em x E, which is equal to (Em ⫺ E), while the price of
exportables is reduced by Ex x E, which is equal to (E ⫺ E0), where em and ex are the
fractions by which the two-tier exchange rate system raises the domestic price of
an importable and lowers the domestic price of an exportable, respectively. The
estimated division of the total foreign exchange distortion between an implicit
export tax, ex , and an implicit import tax, em , will depend on the estimated elasticities
of supply of exports and of demand for imports.3 If the demand and supply curves
in figure A.1 had the same slope, then em ⫽ ex and (em ⫽ ex) is the secondary market
premium or proportional rent extracted by the government or its agents.4
local currency per unit
of foreign currency
Figure A.1. A Distorted Domestic Market for Foreign Currency
Sfx
Em
E⬘m
E
E⬘x
E0
Dfx
QS Q⬘S
QE
quantity
Sources: Martin 1993. See also Derviş, de Melo, and Robinson 1981; Kiguel and O’Connell 1995; Kiguel,
Lizondo, and O’Connell 1997; Shatz and Tarr 2000.
512
Distortions to Agricultural Incentives in Africa
If the government chooses to allocate the limited foreign currency to different
groups of importers at different rates, this is called a multiple exchange rate system.
Some lucky importers may even be able to purchase foreign currency at the low
official rate. The more that is allocated and sold to demanders whose marginal
valuation is below Em, the greater the unsatisfied excess demand at Em, and, hence,
the stronger the incentive for an illegal or black market to form and for lessunscrupulous exporters to lobby the government to legalize the secondary market
for foreign exchange and to allow exporters to retain some fraction of their
exchange rate earnings for sale in the secondary market. Providing a right to
exporters to retain and sell a portion of foreign exchange receipts increases their
incentives to export and thereby reduces the shortage of foreign exchange and,
thus, the secondary market exchange rate (Tarr 1990). In terms of figure A.1, the
available supply increases from QS to QS, bringing down the secondary rate from
Em to Em, such that the weighted average of the official rate and Em received by
exporters is Ex; the weights are the retention rate, r, and (1 ⫺ r). Again, if the
demand and supply curves in figure A.1 had the same slope, then the implicit
export tax and import tax resulting from this regime would each be equal to half
the secondary market premium.
In the absence of a secondary market and in the presence of multiple rates for
importers below Em and for exporters below E0, a black market often emerges.
The rate for buyers in this market will rise above E, the more the government sells
its foreign currency to demanders whose marginal valuation is below Em, and the
more active the government is in catching and punishing exporters selling in the
illegal market. If the black market were allowed to operate frictionlessly, there would
be no foreign currency sales to the government at the official rate, and the black
market rate would fall to the equilibrium rate, E. So, even though, in the latter
case, the observed premium would be positive (equal to the proportion by which
E is above the nominal official rate E0), there would be no distortion. For our
present purposes, since the black market is not likely to be completely frictionless, it may be considered similar to the system involving a retention scheme. In
terms of figure A.1, E⬘m would be the black market rate for a proportion of sales,
and the weighted average of this and E0 would be the return going to exporters.
Calculating E⬘x in this situation (and thereby being able to estimate the implicit
export and import taxes associated with this regime) by using the same approach
as in the case with no illegal market thus requires not only knowledge about E0
and the black market premium, but also a guess about the proportion, r, of sales
in the black market.
In short, if a country exhibits distortions in its domestic market for foreign
currency, the exchange rate relevant for calculating the NRAo or the CTE for a
particular tradable product depends, in the case of a dual exchange rate system,
Methodology for Measuring Distortions to Agricultural Incentives
513
on whether the product is an importable or an exportable, while, in the case of
multiple exchange rates, it depends on the specific rate that applies to the product each year.
What about real exchange rate changes?
A change in the real exchange rate alters equally the prices of exportables and
importables relative to the prices of nontradable goods and services. Such a
change may arise for many different reasons, including changes in the availability
of capital inflows, macroeconomic policy adjustments, or changes in the international terms of trade. If the economy receives a windfall, such as a greater inflow of
foreign exchange from remittances, foreign aid, or a commodity boom, the community moves to a higher indifference curve (Collier and Gunning 1998). While
net imports of tradables may change in response to this inflow of foreign
exchange, the domestic supply of and demand for nontradables must balance. The
equilibrating mechanism is the price of nontradables. The price of nontradables
rises to bring forth the needed increase in the supply of nontradables and to
reduce the demand for these products so as to bring the demand into line with
supply (Salter 1959).
While this type of alteration in the real exchange rate affects the incentive to
produce tradables, it is quite different in two respects from the distortions in the
market for foreign currency analyzed above. First, this real exchange rate appreciation reduces the incentives to produce importables and exportables to the same
degree. In contrast with the case of the multiple-tier exchange rate, the appreciation
does not generate any change in the prices of exportables relative to importables.
Second, most such changes do not involve direct economic distortions of the type
measurable using tools such as producer surplus or consumer surplus. If the
government or the private sector chooses to borrow more from abroad to increase
domestic spending, this may raise the real exchange rate, but such an outcome is
not obviously a distortion. Moreover, the symmetric treatment of any such overvaluation during periods of high foreign borrowing would require that one take
into account exchange rate undervaluation during periods of low foreign borrowing or the repayment of foreign debt. For these reasons, we do not follow Krueger,
Schiff, and Valdés (1988) or Orden et al. (2007) in including deviations of real
exchange rates from benchmark values unless these deviations arise from direct
exchange rate distortions such as multiple-tier exchange rates.5
What if trade costs are too high for a product to be traded internationally?
Suppose the transport costs of trading are sufficient to make it unprofitable for
a product to be traded internationally, such that the domestic price fluctuates
over time within the band created by the cost, insurance, and freight import
514
Distortions to Agricultural Incentives in Africa
price and the free on board export price. Then, any trade policy measure (tm or sx)
or the product-specific exchange rate distortion (for example, em or ex) is redundant.
In this case, in the absence of other distortions, NRAo ⫽ 0, and the CTE ⫽ 0.
However, in the presence of any domestic producer or consumer tax or subsidy
(sf or tc), the domestic prices faced by both producers and consumers will
be affected. The extent of the impact depends on the price elasticities of domestic
demand and supply for the nontradable (the standard closed-economy tax
incidence issue).
Thus, for example, suppose only a production tax is imposed on farmers
producing a particular nontradable, so that sf ⬍ 0 and tc ⫽ 0. In this case:
sf
NRADS ⫽ ᎏ
ᎏ
1 ⫹ ᎏ
(A.5)
⫺sf
CTE ⫽ ᎏ
,
1 ⫹ ᎏᎏ
(A.6)
and
where is the price elasticity of supply, and is the (negative of the) price elasticity
of demand.6
What if farm production involves primary factors,
but also intermediate inputs?
Where intermediate inputs are used in farm production, any taxes or subsidies on
the production, consumption, or trade of these inputs would alter farm value
added and thereby also affect farmer incentives. Sometimes, a government will
have directly offsetting measures in place, such as a domestic subsidy for fertilizer
use by farmers, but also a tariff on fertilizer imports. In other situations, there will
be farm input subsidies, but an export tax on the final product.7 In principle, all
these items might be brought together to calculate an effective rate of direct assistance to farm value added (the effective rate of assistance). The nominal rate of
direct assistance to farm output, NRAo, is a component of this, as is the sum of the
nominal rates of direct assistance to all farm inputs, call it NRAi. In principle, all
three rates may be positive or negative.
The participants in this project have not been required to estimate effective
rates of assistance because to do so requires a knowledge of each product’s value
added share of output. Such data are not available for most developing countries
for every year in the time series nor even for every few years. And, in most developing countries, distortions to farm inputs are small compared with distortions to
farm output prices, and these purchased inputs are a small fraction of the value
of output. However, where there are significant distortions to input costs, the ad
Methodology for Measuring Distortions to Agricultural Incentives
515
valorem equivalent is accounted for by summing each input’s NRA, multiplying
this by the input-output coefficient to obtain the combined NRAi , and adding this
to the farm industry’s nominal rate of direct assistance to farm output, NRAo, to
obtain the total NRA in farm production, call it simply NRA.8
NRA ⫽ NRAo ⫹ NRAi.
(A.7)
What about postfarmgate costs?
If a state trading corporation is charging excessively for its marketing services,
thereby lowering the farmgate price of a product (for example, as a way of raising
government revenue in place of an explicit tax), the extent of the excess should be
treated as if it were a tax.
Some farm products, including some that are not internationally traded, are
inputs into a processing industry that may also be subject to government interventions. In this case, the effect of these interventions on the price received by
farmers for the primary product also needs to be taken into account. Before we
explain how, it may be helpful first to review the possible role the marketing and
distribution margins of the value chain may play in the calculation of distortions
in primary agricultural activities so as to ensure that nondistortionary price
wedges are not inadvertently included in any distortion calculations.
Nondistortionary price wedges
So far, it has been assumed that there are no divergences among farmer, processorwholesaler, consumer, and border prices other than those arising because of subsidies or taxes on production, consumption, trade, or foreign currency. In practice,
this is not so, and these costly value chain activities need to be explicitly recognized and netted out in using comparisons of domestic and border prices to
derive estimates of government policy-induced distortions.9 Such recognition
also offers the opportunity to compare the size of the NRA with wedges associated
with, for instance, trade and processing costs (used in trade facilitation and value
chain analyses, respectively). It may also expose short-term situations where the
profits of importers or exporters are amplified by less-than-complete adjustment
by agents in the domestic value chain.
Domestic trading costs
Trading costs may be nontrivial both intra- and internationally, especially
in developing countries with poorly developed infrastructure.10 For example, domestic trading costs are involved in delivering farm products to port or to domestic
wholesalers (assuming the latter are at the international border; otherwise, another
set of domestic transport costs needs to be added to obtain a relevant price
516
Distortions to Agricultural Incentives in Africa
comparison). Suppose, for instance, that domestic transport costs are equal to the
fraction Tf of the price received by the farmer.
Processor-wholesaler costs
Domestic processing costs and wholesale and retail distribution margins may represent a large share of the final retail price. Indeed, Reardon and Timmer (2007)
argue that these costs and margins are an increasingly important part of the value
chain in developing countries because consumers desire more postfarm processing and services added to their farm products, aided by the contribution of the
supermarket revolution to globalization.11 We denote the increases in the consumer price caused by these processing and wholesaling activities, over and above
the farmgate price plus domestic trade costs, as mp and mu, respectively (or simply
mu above the price of the imported processed product if the processing must be
done before the product is internationally tradable), in the absence of market
imperfections or government distortions along the value chain.
International trading costs
International trading costs are not an issue in the distortions calculations if the
international price used is the cost, insurance, and freight import unit value for an
importable or the free on board export unit value for an exportable. But these
costs are relevant if there is no trade (because of, say, a prohibitive trade tax on the
product) or if the border prices are unrepresentative (because of low trade volumes,
for example). In these instances, it is recommended that one select an international indicator price series (such as those of the World Bank or the International
Monetary Fund) and account for international trading costs (ocean or air freight,
insurance, and so on).12 We denote Tm as the proportion by which the domestic
price of the import-competing product is raised above what it would otherwise be
at the country’s border, or, equivalently, we denote Tx as the fraction of the free on
board price by which the price abroad of the exported product is greater.
Product quality and variety differences
The quality of a product traded internationally is usually considered to differ from
the quality of the domestically sold substitute, and consumers typically have a
home-country bias.13 Whenever appropriate, the domestic price should be
deflated (inflated) by the extent to which the good imported is deemed by domestic
consumers to be inferior (superior) in quality to the domestic product.14 We
denote qm as the deflating fraction for the adjustment for product quality and
variety differences in the case of importables.
The situation is similar for exported goods. Especially if an international indicator
price has to be used in lieu of the free on board export unit value (for example, if
Methodology for Measuring Distortions to Agricultural Incentives
517
exports are close to zero and unrepresentative), the international price needs to be
deflated (inflated) by the extent to which the good is deemed by foreign consumers to be inferior (superior) in quality relative to the indicator good. We
denote qx as the deflating fraction to adjust for product quality and variety differences in the case of exportables.
Net effect of nondistortionary influences
If one takes into consideration all these influences and so long as the product is
still traded internationally, the relationships between the price received by domestic farmers and the international price, in the absence of government-imposed
price and trade policies, are described by the following for an importable:
Pf (1 ⫹ Tf)(1 ⫹ mp)(1 ⫺ qm)
E ⫻ P ⫽ ᎏᎏᎏ ,
1 ⫹ Tm
(A.8)
and for an exportable it is the following:
Pf (1 ⫹ Tf)(1 ⫹ mp)(1 ⫹ Tx)
E ⫻ P ⫽ ᎏᎏᎏ ,
1 ⫺ qx
(A.9)
while the urban consumer price is above the producer price to the following
extent:
Pc ⫽ Pf (1 ⫹ Tf)(1 ⫹ mp)(1 ⫹ mu),
(A.10)
where Pf is the farmgate price.
The impact of distortions in food processing
on agricultural NRAs
Some farm products that are not internationally traded in their primary form (for
example, raw milk and cane sugar) are tradable once they have been lightly
processed, and the downstream processing industry may also be subject to government interventions. In this case, the effect of the latter interventions on the
price received by farmers for the primary product also needs to be taken into
account, and the primary product should be classified as tradable.
Some analysts have assumed that any protection to processors, if it is passed
back fully to primary agriculture (as may be the case with a farmer-owned cooperative processing plant, for example), effectively raises the farmer price by the
amount of the rise in the processor price, divided by the proportional contribution of the primary product to the value of the processed product. Another
equally extreme, but opposite assumption is that there is zero pass-through by the
processor back down the value chain to the farmer. This is likely to be the case if
518
Distortions to Agricultural Incentives in Africa
the raw material may be sourced internationally, but seems unlikely if the primary
product is nontradable and there is a positive price elasticity of farm supply (since
an assisted processor would want to expand). A more neutral assumption is that
there is a proportional pass-through by the processor down the value chain to
farmers and their transporters or up the value chain to consumers. This would be
equivalent to an equal sharing of the benefits along the value chain, which is more
likely to be the case, the more equally market power is spread among the players in
the chain.
This trio of examples illustrates the importance both of separating primary and
processed activities for the purpose of calculating agricultural assistance rates
and of being explicit about the extent of pass-through that is occurring in
practice and, hence, the consequences for the NRAs in primary agricultural and
processing activities.15
The above examples involving processors may also be generalized to any participants in the value chain. In particular, state trading enterprises and parastatal
marketing boards may intervene significantly, especially if they have been granted
monopoly status by the government. Such interventions by domestic institutions
may explain the low econometrically estimated degree of transmission of price
changes at a border to farmgate domestic prices even following a significant
reform of more-explicit price and trade policies (see Baffes and Gardner 2003 and
the references cited therein). Where reform has also involved the freeing up of previously controlled parts of the marketing chain, the lowered marketing margin
may provide a benchmark against which to compare the prereform margin (as in
Uganda beginning in the mid-1990s; see chapter 12 in this volume).
The mean and standard deviation of agricultural NRAs
We need to generate a weighted average NRA for covered products in each country because only then will we be able to add the NRA for noncovered products to
obtain the NRA for all agriculture. If one wishes to average across countries, each
polity is an observation of interest; so, a simple average is meaningful for the purpose of political economy analysis. But, if one wants a sense of the distortions in
agriculture in a whole region, a weighted average is needed. The weighted average
NRA for covered primary agriculture may be generated by multiplying the value
share of each primary industry in production (valued at farmgate equivalent
undistorted prices) by the corresponding NRA and then adding across industries.16 The overall sectoral rate, which we denote as NRAag, may be obtained by
also adding the actual or assumed information for the commodities not covered
and, where it exists, the aggregate value of non-product-specific assistance to
agriculture.
Methodology for Measuring Distortions to Agricultural Incentives
519
A weighted average may be similarly generated for the tradables part of
agriculture—including those industries producing products such as milk and
sugar that require only light processing before they are traded—by assuming that
the share of the non-product-specific assistance goes to producers of tradables.
Call this NRAagt.
In addition to the mean, it is important also to provide a measure of the dispersion or variability of the NRA estimates across the covered products. The cost
of government policy distortions in incentives in terms of resource misallocation
tends to be greater, the greater the degree of substitution in production (Lloyd
1974). In the case of agriculture involving the use of farmland that is sector specific,
but transferable among farm activities, the greater the variation of NRAs across
industries within the sector, the higher the welfare cost of these market interventions. A simple indicator of dispersion is the standard deviation of industry NRAs
within agriculture.17
Trade bias in agricultural assistance
A trade bias index also is needed to indicate the extent to which a country’s policy
regime has an antitrade bias within the agricultural sector. This is important
because, as the Lerner (1936) symmetry theorem demonstrates, a tariff that assists
import-competing farm industries has an effect on farmer incentives that is the
same as the effect of a tax on agricultural exports (see elsewhere above), and, if
both measures are in place, this is a double imposition on farm exports. The
higher the NRA for import-competing agricultural production (NRAagm) relative
to the NRA for exportable farm activities (NRAagx), the more incentive producers
in the subsector will have to bid for mobile resources that would otherwise have
been employed in export agriculture, all else being equal.
Once each farm industry has been classified as import-competing, as a producer of exportables, or as a producer of a nontradable (the status may sometimes
change over the years; see below), it is possible to generate, for each year, the
weighted average NRAs for the two different groups of tradable farm industries.
These may then be used to generate an agricultural trade bias index, TBI, which is
defined as follows:
1 ⫹ NRAagx
TBI ⫽ ᎏᎏ ⫺ 1 ,
1 ⫹ NRAagm
冤
冥
(A.11)
where NRAagm and NRAagx are the average NRAs, respectively, for the importcompeting and exportable parts of the agricultural sector (their weighted average
is NRAagt). This index has a value of zero whenever the import-competing and
export subsectors are equally assisted, and its lower bound approaches ⫺1 in the
most extreme case of an antitrade policy bias.
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Distortions to Agricultural Incentives in Africa
Indirect agricultural assistance and taxation through
nonagricultural distortions
In addition to direct assistance to or taxation of farmers, the Lerner (1936) symmetry theorem also demonstrates that farmer incentives are affected indirectly by
government assistance to nonagricultural production in the national economy.
The higher the NRA for nonagricultural production (NRAnonag), the more
incentive producers in other sectors will have to bid up the value of mobile
resources that would otherwise have been employed in agriculture, all else being
equal. If NRAag is below NRAnonag, one might expect there to be fewer resources
in agriculture than there would be under free-market conditions in the country,
notwithstanding any positive direct assistance to farmers, and, conversely, if
NRAag is greater than NRAnonag. A weighted average may be generated for the
tradables part of nonagriculture, too; call it NRAnonagt.
One of the most important negative effects on farmers arises from protections
for industrialists from import competition. Tariffs are part of this, but so too (especially in past decades) are nontariff barriers to imports. Other primary sectors
(fishing, forestry, and minerals, including the extraction of energy raw materials)
tend, on average, to be subject to fewer direct distortions than either agriculture or
manufacturing, but there are important exceptions. One example is a ban on logging;
however, if such a ban is instituted for genuine reasons of natural resource conservation, it should be ignored. Another example is a resource rent tax on minerals.
Unlike an export tax or quantitative restriction on the exports of such raw materials
(which are clearly distortive and would need to be included in the NRA for mining),
a resource rent tax, like a land tax, may be fairly benign in terms of resource reallocation and, so, may be ignored (see Garnaut and Clunies Ross 1983).
The largest part of most economies is the services sector. This sector produces
mostly nontradables, many of which are provided through the public sector. Distortions in service markets have been extraordinarily difficult to measure, and no
systematic estimates across countries are available over time or even for a recent
period. The only feasible way to generate time series estimates of NRAnonag in
this project has therefore involved the assumption that all services are nontradable, and that they, along with other nonagricultural nontradables, face no distortions. All the other nonagricultural products may be separated into exportables
and import-competing products for purposes of estimating correctly their
weighted average NRAs, ideally using production valued at border prices as
weights (although, in practice, most of our authors have had to use shares of gross
domestic product).
Foreign exchange rate misalignment relative to the value of a country’s currency—
as suggested by the fundamentals—will be ignored (see elsewhere above). This is
because a real appreciation of the general foreign exchange rate uniformly lowers
Methodology for Measuring Distortions to Agricultural Incentives
521
the price of all tradables relative to the price of nontradables; the converse is true
for a real devaluation. If a change in the exchange rate has been caused by aid or
foreign investment inflows, then the excess of tradables consumption over tradables production leads to a new equilibrium. Certainly, such a new inflow of funds
would reduce the incentives among farmers producing tradable products, but this
is not a welfare-reducing policy distortion. Thus, it is only the exchange rate distortions caused by a dual or multiple exchange rate system that need to be
included in the calculation of the NRAs for the exportable and import-competing
parts of the nonagricultural sector and, hence, of NRAnonagt, and this should be
accomplished in the same way discussed above for the inclusion of these distortions in the calculation of NRAagt.
Assistance to agricultural production relative
to nonagricultural production
Given the calculation of NRAagt and NRAnonagt as above, it is possible to reckon
a relative rate of assistance (RRA), defined as follows:
1 ⫹ NR Aag t
RRA ⫽ ᎏᎏt ⫺ 1 .
1 ⫹ NRAnonag
冤
冥
(A.12)
Since an NRA cannot be less than ⫺1 if producers are to earn anything, then
neither can the RRA. The RRA is a useful indicator in undertaking international
comparisons over time of the extent to which a country’s policy regime has an antior proagricultural bias.
The Ways the Theory Is Put into
Practice in This Study
Making the theory described above operational in the real world, where data are
often scarce, especially over a long time period, is as much an art as a science.18
Thankfully, for many countries, we have not had to start from scratch. NRAs are
available from as early as 1955 in some cases and at least from the mid-1960s to
the early or mid-1980s for the 18 countries included in Krueger, Schiff, and Valdés
(1988, 1991a) and Anderson and Hayami (1986). Much has been done to provide
detailed estimates since 1986 of direct distortions in farmer incentives (though
not in food processing) in the high-income countries that are now members of
the Organisation for Economic Co-operation and Development (OECD) and,
since the early to mid-1990s, in selected European transition economies and
Brazil, China, and South Africa (OECD 2007a, 2007b). At least for direct distortions, the Krueger, Schiff, and Valdés measures (1988, 1991a) have been updated
to the mid-1990s for some Latin American countries (Valdés 1996) and have also
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Distortions to Agricultural Incentives in Africa
been provided for some countries in Eastern Europe (Valdés 2000), and a new set
of estimates of simplified producer support estimates for a few key farm products
in China, India, Indonesia, and Vietnam since 1985 is now available from the
International Food Policy Research Institute (Orden et al. 2007). The methodology described above is, in some sense, a variation on each of these studies, and the
basic price data, at least, as well as the narratives attached to the estimates in these
studies, are invaluable springboards for our study.19
Time period coverage of the study
For Europe’s transition economies, it is difficult to find meaningful data on the
situation prior to 1992. For the same reason, estimates are not particularly useful
before the 1980s for China and Vietnam. For all other countries, the target start
date has been 1955, especially if this date includes years before and after a year of
independence so that one might examine the effects of independence, although,
for numerous developing countries, the data simply are not available. The target
end date has been 2004, but, where available, 2005 data have also been included. In
most cases, the most recent few years offer the highest quality data.
Farm product coverage of the study
The agricultural commodity coverage includes all the major food items (rice, wheat,
maize or other grains, soybeans or other temperate oilseeds, palm oil or other
tropical oils, sugar, beef, sheep and goat meat, pork, chickens and eggs, and milk),
plus other key country-specific farm products (for example, other staples, tea,
coffee or other tree crop products, tobacco, cotton, wine, and wool). Globally, as of
2001, one-third of the value added in all agriculture and food industries has been
highly processed food, beverages, and tobacco (GTAP Database; Dimaranan
2006). We have also addressed these products briefly, in the same cursory way we
have addressed nonagricultural products. Fruits and vegetables are another onesixth; so, the rest constitute the other half. Of that other half, meats are one-third;
grains and oilseeds are almost another one-third; dairy products are one-sixth;
and sugar, cotton, and other crops account for slightly more than one-fifth. If the
high-income countries are excluded, these shares change quite sharply. Then,
highly processed food, beverages, and tobacco are only half as important; fruits
and vegetables are somewhat more important, and, if these two groups (which
together account for 41 percent of the total) are excluded, the residual is equally
divided between three groups: meats, grains and oilseeds, and other crops and
dairy products. By focusing on all major grain, oilseed, and livestock products,
plus any key horticultural and other crop products, the coverage of our project
Methodology for Measuring Distortions to Agricultural Incentives
523
reaches the target of 70 percent of the value added of most countries in agriculture and lightly processed food. Priority has been assigned to the most distorted
industries because the residual will then have not only a low weight, but also a low
degree of distortion.
If highly processed food, beverages, and tobacco are excluded, then fruits and
vegetables account for almost one-quarter of household food expenditure in
developing countries. If fruits and vegetables are also excluded, three groups each
then account for almost 30 percent of expenditure: pig and poultry products, red
meat and dairy products, and grains and oilseed products. All other crops account
for the remaining one-eighth. So, from the consumer tax viewpoint, the desired
product coverage is the same as the coverage outlined above from a production
viewpoint.
Each product is explicitly identified as import-competing, exporting, or nontradable. For many products, this categorization changes over time. In some cases,
products move monotonically through these three categories, and, in others, they
fluctuate in and out of nontradability. Hence, an indication of a product’s net
trade status is given for each year rather than for only one categorization for the
whole time series. In large-area countries with high internal and coastal shipping
costs, some regions may be exporting abroad, even while other regions are net
importers from other countries. In such cases, it is necessary to estimate separate
NRAs for each region and then generate a national weighted average.
Farm input coverage
The range of input subsidies considered in any particular country study in our
project has depended on the degree of distortions in that country’s input markets.
In addition to fertilizer, the large inputs and distortions are likely to involve electrical or diesel power, pesticides, and credit (including, occasionally, large-scale
debt forgiveness, as in Brazil and Russia, although how this is spread out beyond
the year of forgiveness is an issue).20 There are also distortions revolving around
water, but the task of measuring water subsidies is especially controversial and complex; so, these distortions have not been included in the NRA calculations. (The
OECD has also ignored them in its producer support estimates.) Similarly, distortions in land and labor markets have been excluded, apart from qualitative discussions in the analytical narratives in some of the country case studies.
Trade costs
For the calculation of distortions in international trading costs, Tm and Tx, the free
on board–cost, insurance, and freight gap in key bilateral trade in products during
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Distortions to Agricultural Incentives in Africa
years when the products have been traded in significant quantities is used. Both
international and domestic trading costs are a function of the quality of hard
infrastructure (roads, railways, ports) and soft infrastructure (business regulations and customs clearance procedures at state and national borders), each of
which may be affected by government actions. However, because it is difficult to
allocate these costs between items that are avoidable and those that are unavoidable, measuring the aggregate size of the distortions involved in a comparable way
for a range of countries is beyond the scope of this study.21
Classifying farm products as import-competing,
exportable, or nontradable
The criteria used in classifying farm industries as import-competing (M), exporting (X), or nontrading (H) are not straightforward. Apart from the complications
raised above about whether a product is not traded simply because of trade taxes
or nontariff barriers, there will be cases where trade is minimal, or the trade status
has been reversed because of policy distortions, or the industry is characterized by
significant imports and exports. A judgment has to be made for each sector each
year as to whether it should be classified as M, X, or H. In the case of the two tradable classifications (that is, leaving out nontradables), this judgment will determine which exchange rate distortion to use. If trade is minimal for reasons of
trade cost rather than reasons of trade policy, then a product is classified as nontradable if the share of production exported and the share of consumption
imported are each less than 2.5 percent, except in situations (for example, rice in
China) in which the product is clearly an exportable year after year even though
the self-sufficiency rate is rarely above 101 percent. Otherwise, if the share of production exported is substantially above (below) the share of consumption
imported, the product is classified as exportable (importable).
In cases in which the trade status has been reversed because of a policy distortion (for instance, an export subsidy, in combination with a prohibitive import
tariff, is large enough to encourage sufficient production to generate an export
surplus), the product should be given the classification of the trade status that
would prevail without the intervention (that is, import-competing). The same
applies if tariff preferences reverse a country’s trade status with respect to a product. The exports of many countries enjoy preferential access into the protected
markets of other countries. In some cases, these arrangements are based on bilateral or plurilateral free trade agreements or customs unions. In other cases, the
preferences are unilaterally offered by higher-income countries to developing
countries through schemes such as the generalized system of preferences, the
Cotonou Agreement (between the Africa, Caribbean, and Pacific group and the
Methodology for Measuring Distortions to Agricultural Incentives
525
European Union), and the European Union’s Everything But Arms Initiative. In
the few extreme cases where these preferences are such that they (in combination
with a prohibitive import tariff) cause the developing country to become an exporter
of a product that would otherwise be import-competing (such as sugar in the
Philippines), the product should nonetheless be classified as import-competing
because the developing country’s import-restrictive policy is allowing the domestic
price of the product to equal the price reached in exporting to the preferenceproviding country.
If there are significant exports and imports in a given year, closer scrutiny is
required. If, for example, there are high credit or storage costs domestically, a
product may be exported immediately following harvest, but imported later in the
year to satisfy consumers out of season. The product would be considered an
exportable for purposes of calculating the NRA because, even if there are policies
restricting out-of-season imports (which would affect the CTE calculation), they
would not represent an encouragement for the production earlier in the year in
the presence of high credit or storage costs.
If trade or exchange rate distortions are sufficiently large to choke off international trade in a product, then they contribute to the NRA and CTE only to the
extent required to drive that trade to zero: any trade taxes that exceed this requirement have an element of redundancy. If there are trade policy distortions, but no
trade passes over them (that is, they are prohibitive), there may still be policy
effects that need to be measured, but they will differ from those involved in the
other cases above. An example would be a prohibitive tariff that is high enough to
take the price of imported goods above the autarchy price and thus results in no
imports. The NRA would therefore be less than the prohibitive tariff rate. Another
common example is an import tariff in a context in which the world price is sufficiently high so that the country is freely exporting the product at issue. In this
case, the domestic price would be determined by the world price, less the export
trade costs; the import tariff would be irrelevant, and there would be no distortion despite the presence of the import tariff.
Similar conditions apply to exportable goods in a context in which a prohibitive
export tax creates a distortion at a level lower than the tax rate. Then, the distortion
wedge would be equal to the difference between the autarchy price and the world
price, less the export trade costs; if the country were freely importing the good, the
export tax would be irrelevant, and there would be no distortion despite the presence
of the export tax. The choice of the international price to be compared with domestic
prices is therefore not based only on the actual trading status of a country (Byerlee
and Morris 1993). Moreover, different prices may be needed for different regions
of a large country that simultaneously exports and imports because internal trading
costs (including coastal shipping) are so high relative to international trading
526
Distortions to Agricultural Incentives in Africa
costs (Koester 1986). In this case, the value of production is split according to the
regional production shares in the country. If the only intervention in this sector is
a tariff on imports, the tariff rate is the NRA estimate for the import-competing
part, and the NRA is zero for the other part of the sector; these different NRAs are
then included in the weighted average calculations of the NRAs for the importcompeting and exportable subsectors of agriculture.
The transmission of assistance and taxation
along the agricultural value chain
A crucial aspect of the NRA calculation for agricultural products is the way any
policy measure beyond the farmgate is transmitted back to farmers and forward
to consumers. Only a few parameters and exogenous variables are needed to
obtain meaningful estimates of an individual agricultural product’s NRA and
CTE. Specifically, to take account of the pass-through of distortions along the
value chain, parameters have been identified as follows (although the default is an
equiproportionate pass-through):
• f , the extent to which any distortion to a primary farm product at the wholesale
level is passed back to farmers
• , the extent to which any distortion to the downstream processed product is
passed back to wholesalers of a primary farm product that is nontradable
The CTEs of farm products
Many farm products are processed and are used as ingredients in the additional
processing of food products before the food products are purchased by final consumers. (For example, wheat is ground to flour and then mixed with other ingredients before baking, slicing, and packaging for sale as bread.) Other farm products
are used as inputs in various farm activities, often after the farm products have
undergone some processing. (Thus, soybeans are crushed, and the meal is mixed
with maize or other feed grains for use as animal feed, while the oil is sold for
cooking.) Because of these many and varied value chain paths and because, in
practice, it is difficult anyway to determine the extent to which a change in the
primary farm product would be passed along any of these value chains, the OECD
expresses its consumer support estimate simply at the level at which a product is
first traded (for example, as wheat, or soybeans, or beef). This practice has been
adopted here, too, to generate a consistent set of CTEs across countries to use in the
analysis in chapter 1 (even though our authors of individual country studies may
report CTEs that they have estimated in a more-sophisticated way farther along
the value chain). In the absence of any domestic production or consumption taxes
or subsidies directly affecting a product, the CTE at the point at which the product
Methodology for Measuring Distortions to Agricultural Incentives
527
is first traded will be the same as the NRAo. (Also recall that the NRAo in this case
also equals the NRA if NRAi is zero.)
Key required information
A template spreadsheet has been designed to aid in the management of individual
country information and ensure a consistent comparison across regions and periods. The precise ways in which parameters and exogenous variables have entered
each country spreadsheet to generate the NRAs and CTEs endogenously are
detailed in Anderson et al. (2008a, 2008b). Most are straightforward; the main
exception is the treatment of exchange rate distortions that is described below.
The key exogenous variables needed are the agricultural quantities produced
and consumed (or imported and exported if the proxy for consumption is production, plus net imports); the wholesale and border prices of primary and lightly
processed agricultural goods (along with, where relevant, a quality adjustment to
match border prices); agricultural domestic input and output subsidies and taxes
(the default is zero); if there are distorted farm input markets, the share of the
input in the value of farm output at border prices (and, if there are only farmgate
prices rather than wholesale prices for a primary good, the proportion of the farmgate value in the value at the wholesale level measured at the border price); the
final domestic food consumer subsidies or taxes (the default is zero); and the official
exchange rate (and, where prevalent, the parallel exchange rate and the share of
currency going through the secondary or illegal market, plus the product-specific
exchange rate if a multiple exchange rate system is in place).
Exchange rate distortions
The treatment of exchange rate distortions is worth spelling out since it differs
from the method used by Krueger, Schiff, and Valdés (1988, 1991a).
If there are no exchange rate distortions, the official exchange rate is used.
However, in the presence of a parallel market rate (which might be the black
market rate if no legal secondary market exists), this is reported, along with an
estimate of the proportion of foreign currency that is actually sold by exporters
at the parallel market rate. This proportion is the formal retention rate if a formal dual exchange regime is in place; otherwise, it is based on a guesstimate of
the proportion traded on the black market. (The black market premiums are
provided in Cowitt, various years; Cowitt, Edwards, and Boyce, various years;
and the Global Development Network Growth Database). The spreadsheet is
then used to compute an estimate for the equilibrium exchange rate for the
economy; this is the rate at which international prices are converted into local
currency for the computation of each NRA.
528
Distortions to Agricultural Incentives in Africa
Relevant exchange rates for importers and exporters are also then computed
endogenously. If they are distorted away from the official exchange rate, the relevant
exchange rate for importers and exporters are, respectively, the discounted parallel market rate and the weighted average of the official exchange rate and the discounted parallel rate according to the proportion of the exporter’s currency that is
sold on the parallel market. However, if a multiple exchange rate system is in place
and this system provides for a specific rate for a product that differs from the general
rates automatically calculated as above, then the automatically computed relevant
exchange rate is replaced by this industry-specific rate.
Guesstimates of NRAs for agricultural products not covered
In the calculation of the weighted average rates of assistance for a subsector or
sector, NRAs must be guesstimated for the agricultural products that are not
covered (30 percent or so) and for which price comparisons are not calculated.
The OECD, in its work on producer support estimates, assumes that the part not
measured enjoys the same market price support as the average of the measured
part. Another default is the assumption that the rates are zero. Orden et al. (2007)
show that these two alternatives produce significantly different results for India. It
is therefore preferable to make informed judgments about the import-competing,
exportable, and nontradable parts of the residual group of farm products. An
average applied import tariff is often the best guess for only the import-competing
products among this set if there is no evidence of the existence of explicit production, consumption, or export taxes or subsidies. Even though this approach will
miss the nontariff trade barriers affecting these residual products, the bias will be
small if the weight is small.
Non-product-specific assistance to agriculture
If, in addition to the product-specific subsidies or taxes, there are non-productspecific forms of agricultural subsidies or taxes that one is unable to allocate
among importables, exportables, and nontradables, these are included in the
NRAag using the same method (as a percentage of the total value of production)
used for these types of interventions in the OECD’s calculations of its total
support estimate (see OECD 2007a, 2007b).
No attempt is made to estimate the discouraging effects of underinvestment
in rural infrastructure or underdevelopment among pertinent institutions. The
structure of the related expenditure within the rural sector is also important.
This may well be a nontrivial part of the distortions in agricultural incentives,
but, unfortunately, it is not captured in the measures of distortions outlined
above.
Methodology for Measuring Distortions to Agricultural Incentives
529
In some higher-income countries, governments also assist farm households
through payments that are purported to be decoupled from production incentives.
An example is the single farm payment in the European Union. We do not count
such payments as part of NRAag because the latter refers specifically to measures
that alter producer incentives. However, we do include the ad valorem equivalent of
these payments in discussing assistance to farmers as a social group so as to be able
to compare the order of magnitude of this equivalent with the support provided
through measures that alter production incentives.
Assistance to nonagricultural sectors
If nonagricultural sectors are assisted only through import tariffs on manufactures or export taxes on minerals, it is a relatively easy task to estimate a
weighted average NRAnonag once the shares of import-competing, exporting,
and nontradable production have been determined. In practice, however, nontariff trade measures must also be considered among the measures affecting
tradables (Dee and Ferrantino 2005; OECD 2005), and most economies have
myriad regulations affecting the many service industries. These regulations may
be complex (see Findlay and Warren 2000). Because most of the outputs of service
industries (including the public sector) are nontradable, the default in this
study is to assume that the average rate of government assistance, along with
that of nontradable nonagricultural goods, is zero. Then, the task of estimating
the NRAnonag is reduced to obtaining only the NRAs for the producers of
import-competing products and of export-oriented nonagricultural goods, plus
the shares of these products and goods in the undistorted value of the production
of nonagricultural tradables, so as to derive the weighted average NRAnonagt to
be entered into the RRA calculations.
The use of percentages in the chapters
To simplify the presentation in the chapters, the NRAo, NRAi, NRA, CTE, and RRA
are expressed there as percentages rather than proportions.
Dollar values of farmer assistance and consumer taxation
For chapter 1, we have taken the country authors’ estimate of NRA and multiplied
it by the gross value of production at undistorted prices to obtain an estimate in
current US dollars of the direct gross subsidy equivalent of assistance to farmers
(GSE). This can then simply be added up across products for a country and across
countries for any or all products to get regional aggregate transfer estimates for the
studied countries. To get an aggregate estimate for the rest of the region, we assume
the weighted average NRA for nonstudied countries is the same as the weighted
530
Distortions to Agricultural Incentives in Africa
average NRA for the studied countries, and that the nonstudied countries’ share of
the region’s gross value of farm production at undistorted prices each year is the
same as its share of the region’s agricultural GDP measured at distorted prices.
All current US dollar values are then converted to constant 2000 dollars using the
GDP deflator for the United States.
To obtain comparable dollar value estimates of the consumer transfer, we have
taken the CTE estimate at the point at which a product is first traded and multiplied it by the gross value of consumption at undistorted prices (proxied by production at undistorted prices plus net imports) to obtain an estimate in current
US dollars of the tax equivalent to consumers of primary farm products (TEC).
This too can then be added up across products for a country and across countries
for any or all products to get regional aggregate transfer estimates for the studied
countries and converted to US dollars again using the GDP deflator. We do not
attempt to get an aggregate estimate for noncovered products in the studied countries nor for the region’s nonstudied countries.
The GSE and TEC dollar values can be illustrated in a supply-demand diagram
for a distorted domestic market for a farm product (see figure A.2). In the case of
an import-competing product subjected to an import tariff tm plus a production
subsidy sf and a consumption tax cc, the GSE is the rectangle abcd and the TEC is
the rectangle ahfg. The GSE estimate is an overstatement to the extent of triangle
cdj and the TEC estimate is an understatement to the extent of triangle efg, where
those triangles are smaller the more price-inelastic are the supply and demand
curves S and D, respectively. In the case of an exportable product subjected to an
export tax tx, the GSE is the negative of the rectangle kruv and the TEC is the negative of the rectangle nquv.
Figure A.2. Distorted Domestic Markets for Farm Products
(a) An import-competing product subjected to an import tariff tm plus a production subsidy sf and a consumption tax cc
price
S
pm(1 tm)(1 sf) b
h
pm(1 tm)(1 cc)
pm(1 tm)
j
pm a
c
f
d
g
e
D
quantity
Methodology for Measuring Distortions to Agricultural Incentives
531
(b) An exportable product subjected to an export tax tx
k
n
S
q
r
price
px v
px(1 ⫺ tx) u
D
quantity
Source: Authors’ derivation.
Notes
1. The NRA therefore differs from the producer support estimate calculated by the Organisation
for Economic Co-operation and Development (OECD) in that the producer support estimate is
expressed as a fraction of the distorted value (see the OECD PSE-CSE Database). It is thus tm/(1 tm),
and, so, for a positive tm, it is smaller than the NRA and is necessarily less than 100 percent.
2. Equilibrium here refers to the situation that would prevail without the distortion in the domestic
market for foreign currency. In figure A.1 and in the discussion that follows, the equilibrium exchange
rate, E, exactly balances the supply and demand for foreign currency. Taken literally, this implies a zero
balance on the current account. The approach here may readily be generalized to accommodate exogenous capital flows and transfers, which would shift the location of QE. With constant-elasticity supply
and demand curves, all of the results would carry through, and any exogenous change in the capital
flows or transfers would imply a shift in the Dfx or Sfx curves.
3. From the viewpoint of using the NRAo and CTE estimates later as parameters in a computable
general equilibrium model, it does not matter which assumptions are made here about these elasticities because the model’s results for real variables will not be affected. What matters for real impacts is
the magnitude of the total distortion, not its allocation between an export tax and an import tax; this
is the traditional incidence result from tax theory that also applies to trade taxes (Lerner 1936). For an
excellent general equilibrium treatment using an early version of the World Bank’s 1–2–3 model, see de
Melo and Robinson (1989). There, the distinction is drawn between traded and nontraded goods
(using the Armington [1969] assumption of differentiation between products sold on the domestic
market and products sold on the international market), in contrast to the distinction between tradable
and nontradable products made below in the text.
4. Note that this same type of adjustment might be made if the government forces exporters to
surrender all foreign currency earnings to the domestic commercial banking system and importers
to buy all foreign currency needs from that banking system and if that system is allowed by regulation to charge excessive fees. This apparently occurs in, for example, Brazil, where the spread is
reputedly 12 percent. If actual costs in a nondistorted competitive system are only 2 percent (as they
are in the less-distorted Chilean economy), the difference of 10 points might be treated as the equivalent of a 5 percent export tax and a 5 percent import tax applying to all tradables (although, as with
nontariff barriers, there would be no government tariff revenue, but rather rent, which, in this case,
would accrue to commercial banks instead of to the central bank). This is an illustration of the
point made by Rajan and Zingales (2004) about the power of financial market reform to expand
opportunities.
532
Distortions to Agricultural Incentives in Africa
5. The results of a multicountry research project that has had macropolicy as its focus are reported
in Little et al. (1993).
6. As in the case of the two-tier exchange rate, the elasticities are used merely to identify the incidence of these measures; as long as both the NRAo and the CTE are included in any economic model
used to assess the impact of the production tax, the real impacts will depend only on the magnitude of
the total distortion, sf , not on the estimated NRA and CTE.
7. On this general phenomenon of offsetting distortions for outputs and inputs (and even direct
payments or taxes), see Rausser (1982).
8. Bear in mind that a fertilizer plant or livestock feed mix plant might be enjoying import tariff
protection that raises the domestic price of fertilizer or feed mix to farmers by more than any consumption subsidy (as was the situation with respect to fertilizer in Korea; see Anderson 1983). In such
a case, the net contribution of this set of input distortions to the total NRA for agriculture would be
negative.
9. This is not to say that there is no interest in comparisons across countries or over time in, for
example, the farmgate price as a proportion of the free on board export price, which summarizes the
extent to which the producer price is depressed by the sum of internal transport, processing, and marketing costs, plus items such as explicit or implicit production or export taxes. Prominent users of this
proportion—which may be less than half in low-income countries even if there is little or no processing—
include Bates (1981) and Binswanger and Scandizzo (1983). Users need to be aware, though, that this
ratio understates the extent of farmer assistance (that is, it understates the rate of protection or overstates the rate of disprotection to farmers), possibly by a large margin.
10. On the basic economics of trading costs as affected by, for example, infrastructure within the
country, at the border (ports, airports), and, in the case of landlocked countries, in transit countries, as
well as international freight costs and so on, and their impact on both the aggregate volume and product
structure of international trade, see Limão and Venables (2001), Venables and Limão (2002), and
Venables (2004). See also the survey by Anderson and van Wincoop (2004), where it is reported that the
tax equivalent of trading costs are estimated at more than 170 percent in high-income countries and
higher in developing and transition economies, especially those that are small, poor, and remote. By lowering these trading costs (for example, by streamlining customs clearance procedures), trade facilitation
may be the result not only of technological changes, but also of government policy choices such as restrictions on the ships that may be used in bilateral trade. For example, Fink, Mattoo, and Neagu (2002) estimate that the policy contribution to the cost of shipping goods from developing countries to the United
States is greater than the border import barriers. More generally, on imperfect competition in services
markets, including cartelized international shipping, see Francois and Wooten (2001, 2006).
11. The costs of processing and of wholesale and retail distribution, as well as domestic trading
costs, change over time not only because of technological advances, but also following policy changes.
For example, government investment in rural infrastructure may lower trading costs. Reardon and
Timmer (2007) argue that the global supermarket revolution is, in part, driven by the opening of
domestic markets following the relaxation of government restrictions on foreign direct investment
since the 1980s. These types of government policies are not included in our project’s measurement of
distortions.
12. Trading costs may be unrelated to the product price (that is, specific rather than ad valorem), in
which case the formulas should be adjusted accordingly (for example, if Tf is in dollars per ton). If this
were the case with international trading costs, the domestic price of importables (exportables) would
change less (more) than proportionately with P. The ad valorem assumption is preferable to the specific
one in situations where international price and exchange rate changes are less than those that are fully
passed though the domestic value chain to the farmer and consumer because of incomplete market
integration caused, for example, by poor infrastructure or weak institutions. Ideally, in such cases, one
would estimate econometrically the extent to which the price transmission elasticity is below unity and
use this to calculate the margin each year.
Trading costs include the storage costs that would be incurred to hold domestic products until the
time in the season when international trade takes place. Any subsidies or taxes on these or any other
Methodology for Measuring Distortions to Agricultural Incentives
533
trading costs should be included in the distortion calculus. On the importance of these domestic trading costs in low-income countries, see Khandker, Balkht, and Koolwal (2006) on Bangladesh; Moser,
Barrett, and Minten (2005) on Madagascar; and Diop, Brenton, and Asarkaya (2005) on Rwanda.
13. On the how and the why of the variation by country of origin in the quality and variety of
traded goods, see Hummels and Klenow (2005).
14. We assume that the quality difference arises because one good provides more effective units of
service than another, so that the relative price is a constant proportion of the value of the first good. If
products are simply differentiated, without such a quality dimension (as in Armington 1969), there
will be no fixed relationship between the two prices.
15. In using the NRA and the CTE estimates later as parameters in a computable general equilibrium model, as in the case of the incidence of the exchange rate distortion discussed elsewhere above,
the assumptions made here about the extent of pass-though along the value chain may not greatly
affect the model’s results for real variables such as prices, output, and value added.
16. Corden (1971) proposed that free trade volumes be used as weights, but, because these are not
observable (and an economy-wide model is needed to estimate them), the common practice is to compromise by using actual distorted volumes, but undistorted unit values or, equivalently, distorted values,
divided by (1 NRA). If estimates of own-and cross-price elasticities of demand and supply are available, a partial equilibrium estimate of the quantity at undistorted values might then be generated, but,
if these estimated elasticities are unreliable, this may introduce additional error over and above the
error one seeks to correct.
17. The mean and standard deviations might be captured by a single measure, namely, the trade
restrictiveness index developed by Anderson and Neary (2005). Calculating this index even in its simplest partial equilibrium mode requires that one know the own-and cross-price elasticities of demand
and supply (or, at least, the elasticity of import demand, but this shortcut is only usable if the NRA and
CTE are identical).
18. In addition to the methodologies of Krueger, Schiff, and Valdés (1988, 1991a) and the OECD
(2007a, 2007b) for estimating agricultural distortion and producer support indicators, see the recent
review by Josling and Valdés (2004) of methodologies in earlier studies.
19. Other trade policy studies have also been of great help, particularly studies on trade and
exchange rate distortions. These include various multicountry studies such as the one summarized in
Bhagwati (1978) and Krueger (1978) and more-recent ones summarized in Bevan, Collier, and Gunning
(1989); Michaely, Papageorgiou, and Choksi (1991); Bates and Krueger (1993); and Rodrik (2003).
20. For an analysis of input subsidies in Indian agriculture, see Gulati and Narayanan (2003).
21. That these costs vary hugely across countries and often dwarf trade taxes has now been clearly
established. See, for example, World Bank (2006a, 2006b), the Doing Business Database, and the governance and anticorruption indicators in the WGI Database. Also now available is a database on information and communications cost indicators for 144 countries; see the ICT at a Glance Database.
In some settings, price bands induced by trading costs arising because of missing or imperfect markets
in rural areas lead poor farmers to forgo cash crops to ensure sufficient food production for survival
(de Janvry, Fafchamps, and Sadoulet 1991; Fafchamps 1992). This contributes to the low supply
responsiveness among poor producers to international price changes for the cash crops.
References
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Cambridge, MA: MIT Press.
Anderson, James E., and Eric van Wincoop. 2004. “Trade Costs.” Journal of Economic Literature 42 (3):
691–751.
Anderson, Kym. 1983. “Fertilizer Policy in Korea.” Journal of Rural Development 6 (1): 43–57.
Anderson, Kym, and Yujiro Hayami, eds. 1986. The Political Economy of Agricultural Protection: East
Asia in International Perspective. London: George Allen and Unwin.
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Distortions to Agricultural Incentives in Africa
Anderson, Kym, Marianne Kurzweil, Will Martin, Damiano Sandri, and Ernesto Valenzuela. 2008a.
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Appendix B
ANNUAL ESTIMATES
OF DISTORTIONS
TO AGRICULTURAL
INCENTIVES IN AFRICA
Ernesto Valenzuela, Marian Kurzweil,
Johanna Croser, Signe Nelgen, and Kym Anderson
This appendix summarizes the key distortion indicators defined in appendix A
and in Anderson et al. (2008) for the 21 focus countries of this study on Africa. It
also provides some summary statistics for the region’s estimates, including the
focus countries’ share of global volume of production and consumption of covered agricultural products and of the regional and global value shares of imports
and exports of those products. In a longer, working paper version of this appendix
(Valenzuela et al. 2007), four tables are provided for each country: the nominal
rate of assistance (NRA) to individual farm products covered in the study and
their weighted average, using as weights production valued at undistorted prices;
the relative rate of assistance (RRA) to producers of agricultural (relative to nonagricultural) tradables, again using as weights production valued at undistorted
prices, and the component parts of the RRA calculation; the weights themselves
for individual covered farm products and for the residual noncovered group of
products, shown as percentages, so they sum to 100 percent; and the trade status
of each covered product each year.
The NRA in the case of a product whose output price distorted by government
policies is the percentage by which the domestic producer price exceeds the price
that would prevail under free markets, that is, the border price appropriately
adjusted to account for differences in product quality, transport costs, processing
costs, and the like. A negative value indicates the domestic price is below that
539
540
Distortions to Agricultural Incentives in Africa
comparable border price. If producers of that product also are affected by distortions to product-specific input prices, their ad valorem equivalent is accounted for
by subtracting the ad valorem input price distortion times its input-output coefficient from the farm industry’s output NRA to obtain the total nominal rate of
assistance to production of that farm product.
The RRA is defined as 100*[(100 ⫹ NRAagt )兾(100 ⫹ NRAnonagt ) ⫺ 1], where
NRAagt and NRAnonagt are the percentage NRAs for the tradables parts of the
agricultural and nonagricultural sectors, respectively.
The sources of the tables in this appendix are the working paper versions of the
chapters in this volume, each of which is downloadable in the working paper
section of the project’s Web site, www.worldbank.org/agdistortions. Also available
at that Web site are the fuller version of this appendix (Valenzuela et al. 2007) and
the complete global distortions database (Anderson and Valenzuela 2008). The
references are provided at the end of the tables.
Annual Estimates of Distortions to Agricultural Incentives in Africa
541
Table B.1. Annual NRA Estimates, Benin, 1970–2005
(percent)
Year
Cassava
Cotton
Millet
Sorghum
Yam
All covered
products
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺31
⫺43
⫺43
⫺69
⫺42
⫺51
⫺63
⫺41
⫺50
⫺48
⫺52
⫺33
⫺46
⫺55
⫺46
14
5
⫺19
⫺10
⫺42
⫺30
⫺15
17
⫺19
⫺61
⫺37
⫺28
⫺32
3
⫺9
⫺23
6
⫺16
⫺17
15
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
⫺2
⫺3
⫺7
⫺2
⫺2
⫺2
0
⫺1
⫺1
⫺1
0
⫺1
⫺2
⫺3
1
0
⫺1
⫺1
⫺3
⫺2
⫺1
1
⫺2
⫺14
⫺8
⫺5
⫺5
0
⫺1
⫺3
1
⫺1
⫺1
1
0
Source: Baffes 2007.
542
Distortions to Agricultural Incentives in Africa
Table B.2. Annual NRA Estimates, Burkina Faso, 1970–2005
(percent)
Year
Cassava
Cotton
Millet
Sorghum
Yam
All covered
products
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺28
⫺44
⫺45
⫺69
⫺41
⫺50
⫺68
⫺37
⫺47
⫺45
⫺54
⫺45
⫺60
⫺68
⫺51
6
0
⫺20
⫺14
⫺41
⫺30
⫺13
8
⫺14
⫺68
⫺43
⫺34
⫺36
⫺12
⫺6
⫺27
15
⫺14
⫺20
38
13
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
⫺2
⫺2
⫺5
⫺2
⫺3
⫺8
⫺1
⫺2
⫺3
⫺3
⫺2
⫺4
⫺6
⫺4
0
0
⫺2
⫺1
⫺5
⫺4
⫺1
0
⫺1
⫺10
⫺5
⫺4
⫺7
⫺1
⫺1
⫺5
1
⫺1
⫺3
6
2
Source: Baffes 2007.
Table B.3. Annual NRA Estimates, Cameroon, 1961–2004
(percent)
543
Year
Banana
Cassava
Cocoa
Coffee
Cotton
Maize
Millet
Other roots
& tubers
Plantain
Sorghum
All covered
products
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
⫺3
⫺1
⫺4
⫺2
⫺4
⫺4
⫺3
⫺2
⫺8
0
0
0
0
0
1
0
0
⫺8
⫺1
1
0
⫺2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺29
⫺28
⫺37
⫺21
⫺31
⫺43
⫺50
⫺55
⫺61
⫺46
⫺29
⫺35
⫺53
⫺61
⫺42
⫺64
⫺78
⫺66
⫺52
⫺31
⫺31
⫺30
⫺35
⫺38
⫺26
⫺26
⫺34
⫺30
⫺29
⫺30
⫺35
⫺43
⫺44
⫺43
⫺39
⫺48
⫺37
⫺63
⫺74
⫺56
⫺51
⫺41
⫺30
⫺44
—
—
—
—
—
—
—
—
—
⫺34
⫺46
⫺37
⫺64
⫺39
⫺46
⫺57
⫺30
⫺43
⫺33
⫺28
⫺17
⫺31
0.0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺4
⫺4
⫺5
⫺4
⫺5
⫺6
⫺8
⫺9
⫺13
⫺12
⫺9
⫺9
⫺13
⫺16
⫺8
⫺22
⫺40
⫺30
⫺25
⫺16
⫺12
⫺17
(Table continues on the following page.)
544
Table B.3. Annual NRA Estimates, Cameroon, 1961–2004 (continued)
Year
Banana
Cassava
Cocoa
Coffee
Cotton
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
⫺4
⫺1
1
1
⫺2
⫺1
⫺3
⫺2
⫺1
⫺1
⫺1
20
9
6
7
2
⫺1
5
3
1
⫺1
⫺1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺44
⫺53
⫺37
⫺16
⫺1
17
27
⫺15
⫺23
⫺19
⫺44
⫺63
⫺18
⫺32
⫺46
⫺51
⫺24
⫺20
⫺15
⫺20
⫺9
2
⫺49
⫺55
⫺44
⫺39
1
3
4
⫺10
⫺4
17
⫺11
⫺70
⫺27
6
⫺4
⫺8
⫺10
⫺5
⫺8
⫺9
0
12
⫺45
⫺25
35
45
20
32
⫺41
⫺28
⫺11
14
46
⫺44
⫺25
⫺22
⫺21
4
⫺6
0
8
⫺11
⫺21
30
Source: Bamou and Masters 2007.
Note: — ⫽ no data are available.
Maize
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Millet
Other roots
& tubers
Plantain
Sorghum
All covered
products
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺19
⫺33
⫺19
⫺14
0
4
3
⫺3
⫺3
⫺1
⫺4
⫺12
⫺4
⫺2
⫺6
⫺6
⫺4
⫺1
⫺1
⫺3
⫺2
1
Annual Estimates of Distortions to Agricultural Incentives in Africa
545
Table B.4. Annual NRA Estimates, Chad, 1970–2005
(percent)
Year
Cassava
Cotton
Millet
Sorghum
Yam
All covered
products
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺39
⫺49
⫺50
⫺73
⫺34
⫺46
⫺63
⫺40
⫺50
⫺47
⫺47
⫺45
⫺53
⫺63
⫺40
19
13
⫺5
3
⫺37
⫺25
⫺7
21
⫺21
⫺62
⫺46
⫺32
⫺25
2
3
⫺29
2
⫺15
⫺26
37
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺5
⫺10
⫺11
⫺27
⫺8
⫺14
⫺21
⫺7
⫺9
⫺6
⫺5
⫺5
⫺9
⫺16
⫺5
1
1
⫺1
0
⫺6
⫺3
⫺1
1
⫺1
⫺11
⫺5
⫺5
⫺4
0
0
⫺4
0
⫺1
⫺1
3
1
Source: Baffes (2007)
Table B.5. Annual NRA Estimates, Côte D’Ivoire, 1961–2005
(percent)
Year
Cassava
Cocoa
Coffee
Cotton
Plantain
Rice
Yam
All
covered
products
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺36
⫺28
⫺39
⫺31
⫺28
⫺40
⫺42
⫺52
⫺65
⫺43
⫺28
⫺33
⫺49
⫺49
⫺15
⫺53
⫺69
⫺64
⫺50
⫺55
⫺49
⫺44
⫺52
⫺59
⫺55
⫺47
⫺43
⫺29
⫺11
⫺49
⫺46
⫺40
⫺44
⫺42
⫺42
⫺45
⫺40
⫺36
⫺43
⫺39
⫺39
⫺43
⫺56
⫺60
⫺58
⫺54
⫺53
⫺48
⫺52
⫺55
⫺51
⫺50
⫺50
⫺54
⫺55
⫺57
⫺55
⫺48
⫺48
⫺43
⫺84
⫺66
⫺69
⫺58
⫺65
⫺66
⫺73
⫺75
⫺71
⫺67
⫺58
⫺54
⫺53
⫺55
⫺51
⫺40
⫺66
⫺79
⫺53
⫺27
⫺42
⫺44
⫺36
⫺46
⫺32
⫺39
⫺51
⫺58
⫺62
⫺46
—
—
—
—
—
⫺16
⫺20
⫺20
⫺25
⫺17
⫺32
⫺33
⫺54
⫺11
⫺17
⫺35
⫺17
⫺32
⫺24
⫺52
⫺43
⫺49
⫺52
⫺38
⫺16
⫺30
⫺41
⫺37
⫺50
⫺48
⫺43
⫺30
⫺29
⫺42
⫺36
⫺27
⫺24
⫺12
⫺11
⫺12
⫺3
⫺21
⫺23
⫺10
⫺22
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺20.3
⫺25
⫺24
⫺19
⫺22
⫺36
⫺50
⫺40
⫺38
⫺12
22
17
55
⫺21
34
70
53
6
42
⫺27
⫺41
⫺11
⫺12
3
15
45
38
⫺25
⫺31
⫺11
⫺18
⫺9
22
⫺11
6
⫺2
34
⫺7
5
20
35
19
48
19
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺31
⫺22
⫺28
⫺33
⫺30
⫺35
⫺32
⫺37
⫺43
⫺37
⫺31
⫺33
⫺28
⫺33
⫺14
⫺61
⫺48
⫺43
⫺32
⫺41
⫺42
⫺38
⫺43
⫺37
⫺44
⫺32
⫺29
⫺22
⫺16
⫺26
⫺20
⫺19
⫺21
⫺23
⫺19
⫺26
⫺23
⫺23
⫺22
⫺18
⫺23
⫺29
⫺33
⫺35
⫺34
Source: Abbott 2007.
Note: — ⫽ no data are available.
Annual Estimates of Distortions to Agricultural Incentives in Africa
547
Table B.6. Annual NRA Estimates, Arab Republic of Egypt,
1955–2005
(percent)
Year
Beef
Cotton
Maize
Milk
Rice
Sugar
Wheat
All covered
products
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
⫺21
⫺17
⫺14
⫺8
⫺7
⫺20
⫺29
⫺39
⫺31
⫺44
⫺46
⫺53
⫺44
⫺49
⫺57
⫺59
⫺59
⫺53
⫺59
⫺10
24
19
47
15
⫺44
⫺27
⫺18
13
66
98
34
193
205
187
163
⫺10
3
⫺21
⫺21
⫺22
⫺22
⫺22
⫺35
⫺55
⫺46
⫺56
⫺58
⫺67
⫺66
⫺55
⫺61
⫺71
⫺64
⫺63
⫺56
⫺70
⫺71
⫺60
⫺41
⫺53
⫺38
⫺58
⫺56
⫺47
⫺33
⫺21
⫺36
⫺57
⫺21
6
7
⫺3
⫺60
⫺46
⫺45
⫺39
⫺32
⫺25
⫺19
⫺19
⫺42
⫺37
⫺38
⫺40
⫺47
⫺34
⫺13
⫺32
⫺33
⫺26
⫺31
⫺8
⫺19
⫺28
⫺13
⫺15
64
52
31
10
⫺40
⫺20
81
35
11
178
386
350
262
44
60
⫺77
⫺75
⫺70
⫺64
⫺55
⫺57
⫺73
⫺63
⫺55
⫺37
⫺63
⫺44
⫺42
⫺55
⫺48
⫺40
⫺45
⫺56
⫺55
⫺19
⫺16
⫺28
⫺21
⫺36
⫺44
⫺34
⫺48
⫺64
⫺45
⫺28
⫺44
20
97
102
112
⫺5
4
⫺71
⫺68
⫺64
⫺60
⫺58
⫺56
⫺60
⫺67
⫺64
⫺65
⫺62
⫺56
⫺51
⫺60
⫺58
⫺32
⫺39
⫺33
⫺62
⫺77
⫺64
⫺27
16
3
⫺42
⫺35
⫺37
⫺36
⫺11
21
⫺8
10
15
103
142
⫺26
19
⫺34.3
⫺30.8
⫺28.6
⫺22.9
⫺17.9
⫺30.4
⫺41.6
⫺35
⫺79
⫺79
⫺71
⫺51
⫺11
⫺21
⫺19
⫺50
⫺57
⫺56
⫺63
⫺71
⫺66
⫺33
⫺8
⫺4
⫺21
⫺60
⫺62
⫺10
28
59
6
52
170
97
82
⫺36
⫺15
⫺49
⫺45
⫺41
⫺37
⫺32
⫺40
⫺45
⫺53
⫺50
⫺54
⫺46
⫺40
⫺23
⫺30
⫺32
⫺11
⫺32
⫺24
⫺35
⫺48
⫺32
⫺22
5
18
⫺32
⫺32
⫺46
⫺52
⫺24
⫺3
⫺21
139
207
128
193
31
115
⫺39
⫺37
⫺34
⫺29
⫺27
⫺35
⫺51
⫺48
⫺52
⫺54
⫺59
⫺55
⫺43
⫺52
⫺59
⫺51
⫺54
⫺48
⫺58
⫺55
⫺39
⫺22
⫺7
⫺6
⫺42
⫺36
⫺41
⫺26
14
22
⫺15
68
127
132
125
⫺15
8
(Table continues on the following page.)
548
Distortions to Agricultural Incentives in Africa
Table B.6. Annual NRA Estimates, Arab Republic of Egypt,
1955–2005 (continued)
Year
Beef
Cotton
Maize
Milk
Rice
Sugar
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
⫺27
⫺19
⫺4
24
35
34
42
37
19
1
⫺10
8
⫺15
⫺13
⫺45
⫺27
⫺23
22
⫺36
5
⫺25
⫺38
⫺36
⫺50
⫺51
⫺10
⫺37
⫺21
10
26
14
11
⫺7
35
40
36
43
24
⫺12
⫺10
16
46
⫺29
⫺25
⫺22
⫺28
⫺26
⫺18
⫺15
⫺10
⫺13
⫺20
⫺34
⫺25
⫺20
⫺5
⫺20
⫺15
⫺19
⫺24
⫺22
⫺27
⫺12
⫺6
⫺31
⫺27
⫺39
⫺9
⫺17
⫺20
⫺35
⫺21
⫺15
⫺28
⫺16
⫺18
10
24
59
33
⫺20
⫺11
4
⫺22
Source: Cassing, et al. 2007.
Wheat
All covered
products
20
31
41
⫺1
⫺7
70
39
47
28
8
⫺15
-14
1
28
⫺22
⫺11
⫺5
⫺2
⫺9
10
15
15
5
⫺9
⫺24
⫺8
⫺11
⫺4
Annual Estimates of Distortions to Agricultural Incentives in Africa
549
Table B.7. Annual NRA Estimates, Ethiopia, 1981–2005
(percent)
Year
Chat Coffee
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
⫺51
⫺52
⫺53
⫺53
⫺51
⫺50
⫺37
⫺46
⫺43
⫺44
⫺45
⫺45
⫺45
⫺46
⫺43
⫺45
⫺44
⫺43
⫺41
⫺41
⫺43
⫺47
⫺26
⫺41
—
⫺15
⫺26
⫺35
⫺37
⫺46
⫺23
⫺34
⫺41
⫺21
⫺32
⫺39
⫺43
⫺39
⫺41
⫺39
⫺42
⫺39
⫺34
⫺28
⫺15
⫺4
2
⫺10
⫺7
⫺3
Hides,
All covered
skins Maize Oilseed Pulse Teff Wheat products
⫺46
⫺47
⫺47
⫺48
⫺46
⫺46
⫺53
⫺52
⫺52
⫺52
⫺49
⫺52
⫺51
⫺53
⫺50
⫺52
⫺51
⫺47
⫺45
⫺50
⫺50
⫺49
⫺47
⫺46
—
Source: Rashid, Assefa, and Ayele 2007.
Note: — ⫽ no data are available.
⫺2
⫺4
⫺2
⫺10
⫺9
⫺6
⫺8
⫺6
⫺5
⫺8
⫺9
⫺8
⫺6
⫺6
⫺4
⫺1
⫺4
⫺3
⫺7
⫺8
⫺2
⫺7
⫺10
⫺4
⫺6
⫺52
⫺48
⫺29
⫺44
⫺45
⫺39
⫺46
⫺65
⫺46
⫺49
⫺55
⫺63
⫺66
⫺52
⫺55
⫺62
⫺52
⫺50
⫺44
⫺46
⫺40
⫺32
—
—
—
⫺35
⫺34
⫺36
⫺25
⫺54
⫺58
⫺55
⫺57
⫺57
⫺44
⫺44
⫺62
⫺56
⫺54
⫺36
⫺43
⫺36
⫺32
⫺29
⫺31
⫺17
⫺14
—
—
—
⫺2
⫺4
⫺2
⫺11
⫺10
⫺7
⫺9
⫺6
⫺6
⫺9
⫺11
⫺9
⫺6
⫺7
⫺5
⫺1
⫺5
⫺4
⫺8
⫺9
⫺2
⫺8
⫺12
⫺5
⫺7
⫺3
⫺6
⫺3
⫺16
⫺14
⫺9
⫺13
⫺9
⫺8
⫺13
⫺15
⫺12
⫺9
⫺10
⫺7
⫺1
⫺6
⫺5
⫺11
⫺12
⫺3
⫺11
0
0
0
⫺10
⫺12
⫺10
⫺16
⫺15
⫺14
⫺18
⫺16
⫺12
⫺16
⫺21
⫺19
⫺15
⫺15
⫺10
⫺9
⫺10
⫺8
⫺11
⫺12
⫺5
⫺10
⫺7
⫺3
⫺3
550
Distortions to Agricultural Incentives in Africa
Table B.8. Annual NRA Estimates, Ghana, 1955–2004
(percent)
Year Cassava Cocoa Groundnut Maize Plantain
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
0
0
0
0
0
0
0
0
0
⫺6
⫺5
⫺6
⫺32
⫺23
⫺15
⫺1
⫺25
⫺37
⫺39
⫺44
⫺59
⫺56
⫺63
⫺64
⫺55
⫺22
⫺49
⫺62
⫺60
⫺58
⫺84
⫺92
⫺84
⫺87
⫺75
⫺93
⫺92
—
⫺72
⫺76
⫺73
⫺57
⫺43
⫺34
⫺38
⫺26
⫺25
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
0
0
0
0
0
0
0
0
0
⫺19
⫺2
⫺34
3
⫺18
⫺18
27
⫺11
⫺15
⫺2
⫺6
8
⫺38
⫺8
38
⫺6
41
38
⫺16
⫺23
⫺14
2
47
81
⫺10
161
11
⫺42
—
95
18
46
172
79
14
60
66
54
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
0
0
0
0
0
0
0
0
0
Rice
Yam
All covered
products
⫺8.1
⫺2.9
⫺3.1
⫺8.9
⫺8.8
⫺17
⫺25
⫺54
⫺12
⫺32
⫺29
⫺25
⫺43
⫺55
⫺33
⫺19
35
5
⫺38
⫺58
⫺30
0
⫺22
⫺7
⫺48
5
⫺56
⫺50
—
207
53
21
87
94
143
40
23
25
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
0
0
0
0
0
0
0
0
0
⫺3
⫺2
⫺3
⫺15
⫺12
⫺8
0
⫺14
⫺21
⫺24
⫺22
⫺25
⫺30
⫺32
⫺32
⫺28
⫺6
⫺19
⫺31
⫺31
⫺27
⫺43
⫺47
⫺35
⫺53
⫺23
⫺46
⫺59
—
⫺1
⫺18
⫺19
⫺1
⫺1
⫺3
⫺4
1
⫺1
551
Annual Estimates of Distortions to Agricultural Incentives in Africa
Year Cassava Cocoa Groundnut Maize Plantain
Rice
Yam
All covered
products
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
24
⫺4
1
1
18
10
24
8
47
30
33
37
0
0
0
0
0
0
0
0
0
0
0
0
⫺3
⫺9
⫺5
⫺8
⫺4
⫺3
⫺3
⫺7
1
1
⫺5
⫺1
0
0
0
0
0
0
0
0
0
0
0
0
⫺40
⫺52
⫺34
⫺38
⫺36
⫺28
⫺18
⫺38
⫺25
⫺8
⫺23
⫺13
0
0
0
⫺2
21
43
10
⫺52
7
⫺5
⫺12
⫺12
17
⫺4
19
0
0
0
0
39
67
22
17
50
Source: Brooks, Croppenstedt, and Aggrey-Fynn 2007.
Note: — ⫽ no data are available.
0
0
0
0
0
0
0
0
0
0
0
0
552
Distortions to Agricultural Incentives in Africa
Table B.9. Annual NRA Estimates, Kenya, 1956–2004
(percent)
Fruits,
Fruits,
vegetables, vegetables,
All covered
Year Coffee nontradable tradable Maize Sugar Tea Wheat products
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
⫺13
⫺17
⫺4
⫺10
⫺6
1
⫺12
20
⫺6
⫺10
⫺22
⫺5
⫺11
⫺15
⫺24
⫺18
⫺20
⫺21
⫺14
1
⫺1
⫺9
⫺7
⫺5
⫺13
⫺21
⫺17
⫺9
⫺17
⫺11
⫺21
⫺16
⫺24
⫺2
⫺5
⫺12
⫺32
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
—
—
—
—
⫺1
⫺1
⫺2
⫺1
⫺3
⫺12
⫺12
⫺9
⫺15
⫺19
⫺15
⫺22
⫺21
⫺11
⫺5
⫺7
⫺2
⫺6
⫺8
⫺12
⫺12
⫺16
⫺10
⫺10
⫺3
⫺4
⫺12
⫺7
⫺3
⫺1
⫺6
⫺19
54
64
72
48
63
⫺16
76
62
36
⫺40
⫺32
53
56
28
⫺31
⫺56
0
⫺8
⫺26
3
7
⫺61
⫺59
24
⫺60
⫺42
⫺67
⫺24
⫺39
⫺10
23
18
⫺24
⫺14
0
⫺32
⫺82
—
—
—
—
—
—
—
—
⫺29
93
32
26
68
⫺5
⫺24
⫺36
⫺52
⫺62
⫺66
⫺69
⫺54
⫺4
9
⫺6
⫺65
⫺70
⫺49
⫺24
⫺31
81
29
18
2
⫺25
⫺41
⫺33
⫺57
—
2
2
6
6
16
19
8
8
4
⫺2
⫺5
⫺17
⫺13
⫺15
⫺11
⫺22
⫺18
⫺11
⫺5
⫺3
6
3
⫺6
⫺12
⫺7
⫺19
⫺24
10
3
6
⫺14
⫺35
⫺25
⫺13
⫺22
⫺63
3
5
22
19
13
⫺2
⫺5
⫺7
27
26
⫺10
12
22
1
⫺8
⫺6
⫺20
⫺52
⫺49
4
⫺2
8
⫺5
⫺44
⫺31
⫺22
⫺23
⫺13
⫺15
⫺3
32
56
20
⫺12
12
16
⫺48
18
24
33
20
26
⫺7
18
29
13
⫺22
⫺21
16
15
1
⫺23
⫺36
⫺15
⫺21
⫺26
⫺9
⫺2
⫺30
⫺29
⫺3
⫺38
⫺33
⫺45
⫺19
⫺14
⫺3
1
⫺1
⫺22
⫺15
⫺10
⫺22
⫺67
Annual Estimates of Distortions to Agricultural Incentives in Africa
553
Fruits,
Fruits,
vegetables, vegetables,
All covered
Year Coffee nontradable tradable Maize Sugar Tea Wheat products
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
⫺41
⫺20
⫺6
⫺1
1
⫺15
⫺3
⫺8
5
⫺23
⫺2
11
0
0
0
0
0
0
0
0
0
0
0
0
⫺26
0
0
⫺3
⫺3
⫺6
0
0
0
0
0
0
Source: Winter-Nelson and Argwings-Kodhek 2007.
Note: — ⫽ no data are available.
⫺51
⫺8
⫺16
⫺11
9
⫺20
12
⫺1
24
⫺10
⫺6
⫺5
⫺24
20
36
4
10
30
73
8
⫺1
62
55
58
⫺34
⫺15
⫺25
⫺20
⫺20
⫺6
⫺3
⫺3
7
⫺4
⫺1
2
⫺59
26
34
15
57
36
42
48
48
53
51
31
⫺41
⫺9
⫺11
⫺9
⫺1
⫺9
8
⫺1
12
⫺1
3
5
554
Distortions to Agricultural Incentives in Africa
Table B.10. Annual NRA Estimates, Madagascar, 1961–2003
(percent)
Year Cassava Clove Cocoa Coffee Maize Pepper Rice Sugar Vanilla Yam
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
—
—
—
—
⫺57
⫺54
⫺59
⫺8
8
18
26
⫺69
⫺74
⫺74
⫺84
⫺82
⫺85
⫺78
⫺85
⫺91
⫺95
⫺96
⫺93
⫺79
⫺80
⫺89
⫺91
⫺86
⫺86
⫺82
⫺68
⫺45
⫺32
⫺56
⫺61
⫺74
31
24
⫺3
⫺55
2
—
—
—
—
—
—
⫺12
⫺20
⫺37
⫺57
⫺29
⫺7
⫺14
⫺42
⫺61
⫺46
⫺78
⫺78
⫺85
⫺69
⫺58
⫺58
⫺75
⫺78
⫺73
⫺63
⫺58
⫺79
⫺66
⫺36
⫺37
⫺7
⫺50
⫺52
17
0
⫺21
⫺35
⫺34
⫺24
⫺24
1
⫺23
⫺28
Source: Maret 2007.
Note: — ⫽ no data are available.
—
—
—
—
—
⫺29
⫺20
⫺21
⫺37
⫺15
⫺14
⫺8
⫺11
⫺28
⫺22
⫺75
⫺74
⫺76
⫺68
⫺60
⫺58
⫺83
⫺85
⫺81
⫺68
⫺59
⫺64
⫺58
⫺44
⫺21
⫺31
⫺61
⫺69
38
⫺31
⫺16
⫺20
7
⫺4
⫺27
⫺18
⫺46
⫺59
—
—
—
—
—
⫺41
⫺25
0
⫺44
0
13
0
0
0
0
0
63
25
0
0
0
0
0
⫺21
0
0
16
⫺26
⫺23
40
53
14
38
⫺2
⫺30
0
⫺41
0
0
40
30
18
—
—
—
—
—
—
⫺62
⫺48
⫺41
16
⫺9
⫺19
6
6
⫺5
⫺24
⫺47
⫺35
⫺57
⫺34
⫺19
⫺38
⫺57
⫺54
⫺65
⫺73
⫺77
⫺88
⫺83
⫺78
⫺71
⫺27
⫺16
⫺22
⫺15
⫺50
⫺49
⫺78
⫺70
⫺63
20
6
⫺56
—
⫺27
⫺15
⫺21
⫺25
⫺25
⫺24
⫺5
⫺40
⫺21
5
3
⫺1
⫺51
⫺64
⫺32
⫺31
13
⫺43
⫺7
⫺21
⫺51
⫺55
⫺54
⫺30
16
⫺3
⫺23
⫺1
⫺2
⫺3
⫺6
0
⫺1
1
⫺4
⫺2
⫺3
1
3
9
9
6
6
⫺2
3
1
0
0
⫺2
⫺2
⫺2
⫺2
⫺1
⫺2
⫺1
1
⫺2
⫺4
⫺4
0
⫺3
⫺1
⫺1
0
⫺3
⫺1
0
2
0
⫺1
⫺1
⫺1
⫺1
⫺1
⫺1
1
2
⫺1
2
⫺1
0
⫺3
⫺2
⫺1
0
0
⫺62
⫺61
⫺66
⫺53
⫺55
⫺42
⫺57
⫺52
⫺57
⫺43
⫺35
⫺34
⫺37
⫺46
⫺46
⫺68
⫺47
⫺75
⫺49
⫺57
⫺67
⫺87
⫺86
⫺85
⫺83
⫺81
⫺91
⫺87
⫺85
⫺84
⫺89
⫺73
⫺73
⫺71
⫺69
⫺49
9
⫺5
⫺29
⫺9
6
⫺35
—
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
All covered
products
⫺24
⫺13
⫺19
⫺21
⫺21
⫺24
⫺17
⫺32
⫺23
⫺2
⫺2
⫺3
⫺38
⫺55
⫺28
⫺47
⫺35
⫺52
⫺27
⫺35
⫺52
⫺63
⫺58
⫺49
⫺22
⫺20
⫺39
⫺30
⫺20
⫺10
⫺13
⫺8
⫺8
2
⫺10
⫺4
⫺6
1
0
3
⫺2
⫺4
1
Annual Estimates of Distortions to Agricultural Incentives in Africa
555
Table B.11. Annual NRA Estimates, Mali, 1970–2005
(percent)
Year
Cassava
Cotton
Millet
Sorghum
Yam
All covered
products
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺47
⫺54
⫺57
⫺78
⫺47
⫺59
⫺73
⫺47
⫺58
⫺43
⫺55
⫺48
⫺61
⫺67
⫺59
⫺6
⫺14
⫺25
⫺20
⫺49
⫺33
⫺15
21
⫺21
⫺64
⫺45
⫺42
⫺40
⫺10
⫺22
⫺32
15
⫺9
⫺11
43
11
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺2
⫺5
⫺5
⫺11
⫺4
⫺8
⫺17
⫺5
⫺6
⫺5
⫺6
⫺4
⫺7
⫺10
⫺6
0
⫺1
⫺3
⫺2
⫺9
⫺6
⫺1
2
⫺2
⫺17
⫺11
⫺8
⫺11
⫺1
⫺3
⫺5
2
⫺1
⫺2
6
1
Source: Baffes 2007.
556
Distortions to Agricultural Incentives in Africa
Table B.12. Annual NRA Estimates, Mozambique, 1976–2003
(percent)
Year
Maize
Bean Cashew Cassava Cotton Groundnut (South)
Maize
(Center
and North)
Millet
1976
—
⫺79
0
⫺79
⫺79
⫺86
⫺86
0
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
26
26
26
42
42
58
52
52
52
52
46
⫺92
⫺86
⫺85
⫺90
⫺90
⫺82
⫺89
⫺99
⫺98
⫺99
⫺98
⫺79
⫺76
⫺75
⫺65
⫺58
⫺79
⫺88
⫺33
⫺15
⫺9
⫺7
⫺4
⫺1
⫺12
⫺5
⫺4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺85
⫺43
⫺50
⫺48
⫺53
⫺52
⫺69
⫺97
⫺97
⫺96
⫺80
⫺53
0
0
0
0
⫺3
⫺3
⫺3
⫺3
⫺2
⫺2
⫺2
⫺2
⫺2
⫺2
⫺2
⫺82
⫺53
⫺58
⫺74
⫺49
⫺51
⫺71
⫺95
⫺95
⫺96
⫺77
⫺63
5
5
5
5
5
5
5
8
8
20
52
46
46
46
46
⫺83
⫺50
⫺35
⫺52
⫺46
⫺29
⫺53
⫺94
⫺91
⫺94
⫺64
⫺42
⫺40
8
8
8
8
8
8
8
8
8
—
20
20
20
20
⫺74
⫺88
25
⫺62
⫺48
⫺56
⫺57
⫺57
⫺57
⫺57
⫺72
⫺59
⫺63
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Annual Estimates of Distortions to Agricultural Incentives in Africa
557
Year
Potato
Rice
Sorghum
Sugar
Tobacco
Yam
All covered
products
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺85
⫺82
⫺56
⫺45
⫺46
⫺46
⫺26
⫺48
⫺94
⫺91
⫺93
⫺67
⫺64
⫺63
⫺51
⫺43
⫺59
⫺49
⫺46
⫺40
13
—
—
26
26
26
—
—
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺80
⫺79
⫺44
⫺36
⫺58
⫺58
⫺58
⫺61
⫺93
⫺94
⫺96
⫺49
⫺43
⫺47
⫺38
36
31
31
34
6
40
152
146
108
94
97
114
102
⫺78
⫺80
⫺53
⫺46
⫺27
⫺45
⫺51
⫺71
⫺95
⫺96
⫺70
⫺54
⫺35
⫺18
⫺52
⫺56
6
⫺44
⫺12
⫺33
⫺62
0
0
0
0
0
0
—
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺64
⫺64
⫺44
⫺21
⫺45
⫺33
⫺25
⫺31
⫺75
⫺74
⫺79
⫺50
⫺30
⫺25
⫺8
⫺3
⫺3
⫺2
⫺4
2
4
5
6
8
7
6
8
8
Source: Alfieri, Arndt, and Cirera 2007.
Note: — ⫽ no data are available.
558
Table B.13. Annual NRA Estimates, Nigeria, 1961–2004
(percent)
Year
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
Cassava
0
0
0
0
0
0
0
0
1
0
1
1
1
1
1
1
1
1
3
4
3
Cocoa
Cotton
Groundnut
Maize
⫺31
⫺30
⫺42
⫺38
⫺54
⫺36
⫺63
⫺62
⫺65
⫺69
⫺58
⫺39
⫺34
⫺44
⫺37
⫺39
⫺64
⫺62
⫺58
2
29
⫺76
⫺77
⫺77
⫺74
⫺74
⫺66
⫺73
⫺53
⫺70
⫺78
⫺78
⫺74
⫺73
⫺77
⫺56
⫺69
⫺82
⫺75
⫺77
⫺71
⫺66
⫺15
⫺17
⫺29
⫺23
⫺34
⫺29
⫺45
⫺55
⫺65
⫺68
⫺69
⫺59
⫺63
⫺35
⫺10
⫺10
86
⫺40
30
⫺51
⫺48
279
310
214
234
144
249
98
160
182
109
208
287
108
66
122
256
153
178
122
199
276
Millet
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
2
3
3
Palm oil
Rice
Sorghum
⫺18
⫺13
⫺35
⫺34
⫺43
⫺34
⫺42
⫺10
⫺26
⫺57
⫺51
⫺25
⫺47
⫺42
⫺8
20
⫺58
⫺27
⫺13
1
1
70
68
51
70
49
60
⫺12
4
4
33
103
87
⫺4
⫺33
8
103
7
⫺4
30
27
35
238
248
176
202
201
278
197
215
157
165
194
305
177
129
149
203
171
261
134
113
245
Yam
0
0
0
0
0
0
0
0
0
0
0
1
1
0
1
1
1
1
2
3
2
All covered
products
23
28
16
18
15
20
7
13
7
⫺2
10
12
10
5
11
16
⫺5
2
3
9
11
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
4
4
1
2
1
0
0
1
1
0
0
0
⫺5
⫺5
⫺5
⫺5
⫺5
⫺5
⫺5
⫺3
⫺4
⫺5
⫺4
Source: Walkenhorst 2007.
⫺11
⫺64
⫺67
⫺72
⫺76
⫺33
⫺26
44
18
15
⫺35
⫺40
20
46
10
22
⫺31
⫺34
⫺37
⫺16
⫺14
⫺31
16
⫺68
⫺91
⫺68
⫺50
⫺78
⫺75
⫺94
⫺81
⫺81
⫺69
⫺91
⫺94
⫺78
⫺79
⫺85
⫺81
⫺84
⫺85
⫺82
⫺81
⫺84
⫺85
⫺79
42
⫺74
⫺20
⫺5
⫺16
55
42
⫺47
⫺56
226
⫺57
⫺78
⫺48
⫺63
⫺45
⫺35
⫺37
⫺37
⫺53
⫺55
⫺59
⫺61
⫺60
341
53
82
127
363
264
88
59
92
107
84
37
48
56
9
83
226
271
189
66
58
43
36
4
3
0
2
1
0
0
1
1
0
0
0
⫺5
⫺5
⫺5
⫺5
⫺5
⫺5
⫺5
⫺4
⫺4
⫺5
⫺4
⫺4
⫺62
⫺63
⫺43
⫺19
⫺27
80
⫺50
⫺49
95
97
⫺10
405
191
27
7
3
⫺22
⫺24
⫺17
⫺13
⫺9
0
98
15
71
109
29
129
55
11
57
31
0
⫺18
⫺15
⫺17
⫺24
3
⫺3
21
14
30
12
5
⫺12
239
31
129
165
95
348
131
77
122
127
103
54
118
73
26
104
112
132
164
76
63
51
49
3
2
0
1
1
0
0
0
1
0
0
0
⫺5
⫺5
⫺5
⫺5
⫺5
⫺5
⫺5
⫺4
⫺4
⫺5
⫺4
17
⫺5
7
13
20
27
9
4
4
13
⫺2
⫺7
13
3
⫺5
1
0
1
⫺3
⫺4
⫺6
⫺8
⫺6
559
560
Table B.14. Annual NRA Estimates, South Africa, 1961–2005
(percent)
Year
Apple,
nontradable
Apple,
tradable
Grape,
nontradable
Grape,
tradable
Maize,
yellow
Maize,
white
Orange,
nontradable
Orange,
tradable
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
⫺2
⫺2
⫺2
⫺3
⫺3
⫺5
⫺5
⫺15
0
⫺6
2
⫺26
5
5
⫺3
⫺14
40
⫺1
⫺12
⫺20
⫺34
25
0
⫺24
⫺15
⫺49
6
⫺13
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
⫺2
⫺2
⫺2
⫺3
⫺3
⫺24
⫺30
⫺10
⫺19
⫺27
⫺30
⫺26
⫺12
⫺9
⫺6
⫺21
19
17
6
21
6
⫺10
17
⫺32
⫺22
⫺42
⫺41
⫺38
17
4
⫺3
1
5
12
14
33
31
12
19
25
⫺14
⫺20
⫺10
⫺14
20
30
43
74
62
87
⫺13
2
⫺11
⫺18
⫺15
⫺11
⫺3
⫺2
12
9
⫺6
⫺5
⫺5
⫺36
⫺48
⫺43
⫺39
⫺9
1
12
37
27
47
21
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
⫺2
⫺2
⫺2
⫺3
⫺3
⫺4
⫺3
⫺3
2
⫺26
⫺24
⫺6
⫺13
⫺12
⫺34
⫺43
⫺36
⫺54
⫺47
⫺22
⫺27
⫺14
⫺52
⫺15
⫺34
15
⫺33
⫺28
⫺7
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
⫺4
⫺6
⫺6
⫺6
⫺6
⫺6
⫺7
⫺5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺16
24
25
39
⫺17
⫺5
11
5
⫺7
⫺2
38
⫺3
8
⫺5
⫺1
⫺36
2
⫺10
6
2
2
2
⫺4
⫺6
⫺6
⫺6
⫺6
⫺6
⫺7
⫺5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺23
5
61
39
21
⫺7
⫺6
⫺4
56
⫺11
⫺8
4
1
12
14
14
⫺6
49
2
⫺2
⫺2
⫺1
⫺14
16
98
218
69
30
56
78
4
86
56
93
22
⫺14
⫺27
⫺10
39
54
⫺2
⫺20
⫺19
66
⫺31
⫺42
66
143
⫺23
34
59
81
⫺3
⫺11
38
⫺15
0
83
⫺26
⫺18
20
⫺27
8
⫺30
⫺32
13
⫺6
⫺6
⫺6
⫺6
⫺6
⫺7
⫺5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺24
⫺38
⫺7
⫺17
⫺40
11
⫺2
⫺8
4
⫺15
⫺1
⫺4
23
5
⫺17
8
29
⫺16
26
8
10
21
(Table continues on the following page.)
561
562
Table B.14. Annual NRA Estimates, South Africa, 1961–2005 (continued)
Year
Poultry
Sheep meat
Sugar
Sunflower
Wheat
All covered products
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
⫺13
⫺13
⫺13
⫺13
⫺13
⫺13
⫺13
⫺13
⫺13
⫺31
⫺15
⫺16
⫺10
⫺7
⫺21
⫺34
⫺29
⫺22
⫺12
20
23
6
31
12
⫺6
37
18
29
12
14
12
11
18
13
65
80
33
9
66
65
42
15
6
47
36
7
42
10
33
33
33
33
22
36
61
64
34
27
⫺15
⫺29
⫺6
⫺53
⫺41
⫺12
24
13
33
⫺25
8
65
142
58
9
23
24
20
12
11
23
20
23
13
8
14
6
⫺10
0
8
9
14
6
29
23
20
27
1
2
⫺1
⫺7
⫺2
6
10
9
15
19
16
21
87
7
⫺3
24
38
89
71
85
8
8
118
121
81
0
12
4
⫺2
1
8
11
16
12
1
4
6
⫺5
⫺22
⫺10
⫺3
10
14
8
15
31
45
46
19
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
⫺21
⫺13
9
18
⫺7
⫺3
⫺4
5
20
14
15
20
21
4
5
⫺2
⫺15
⫺10
20
20
22
Source: Kirsten, Edwards, and Vink 2007.
⫺5
35
75
54
4
10
30
40
40
45
32
12
25
23
25
51
0
⫺23
⫺7
⫺3
6
63
54
51
22
5
⫺3
25
109
123
141
55
13
40
30
42
49
28
1
78
53
57
⫺3
16
19
2
2
8
18
13
1
⫺5
⫺5
⫺7
⫺8
⫺15
1
⫺1
⫺15
⫺7
0
4
1
42
92
154
69
⫺27
6
18
16
16
12
7
⫺5
⫺5
⫺8
11
20
4
⫺1
10
15
⫺1
⫺4
21
42
15
4
10
10
2
2
22
13
11
17
⫺6
⫺1
7
⫺8
⫺6
6
3
19
563
Table B.15. Annual NRA Estimates, Senegal, 1961–2004
(percent)
Year
Cotton
Groundnut
Millet
Rice
All covered
products
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
—
—
—
—
—
—
—
—
—
⫺39
⫺49
⫺49
⫺69
⫺34
⫺45
⫺62
⫺45
⫺55
⫺45
⫺46
⫺41
⫺56
⫺70
⫺65
0
⫺8
⫺15
⫺12
⫺39
⫺27
⫺6
22
10
⫺54
⫺42
⫺31
⫺38
⫺12
⫺10
⫺30
⫺5
⫺16
⫺23
24
⫺24
⫺19
⫺20
⫺16
⫺16
⫺18
⫺11
⫺9
⫺32
⫺36
⫺29
⫺39
⫺53
⫺64
⫺45
⫺39
⫺40
⫺52
⫺62
⫺67
⫺65
⫺9
⫺30
⫺52
⫺42
⫺9
26
9
⫺21
⫺13
⫺12
17
16
⫺34
⫺15
⫺9
⫺18
⫺5
⫺21
⫺35
⫺34
⫺20
⫺2
⫺14
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
8
10
8
12
23
12
⫺13
⫺18
⫺10
15
31
29
⫺26
⫺60
5
42
40
12
52
4
⫺24
17
3
33
68
142
172
73
42
102
162
147
142
32
10
1
⫺14
2
⫺9
6
⫺1
11
13
1
⫺18
⫺14
⫺15
⫺11
⫺11
⫺11
⫺9
⫺6
⫺22
⫺21
⫺23
⫺26
⫺43
⫺53
⫺35
⫺29
⫺23
⫺40
⫺40
⫺43
⫺54
⫺6
⫺17
⫺32
⫺16
5
28
13
⫺4
6
4
18
31
⫺26
⫺12
⫺8
⫺12
⫺3
⫺15
⫺24
⫺22
⫺8
⫺1
⫺5
Source: Masters 2007.
Note: — ⫽ no data are available.
Table B.16. Annual NRA Estimates, Sudan, 1955–2004
(percent)
565
Year
Beef
Camel
Cotton
Groundnut
Gum
arabic
Milk
Millet
Sesame
Sheep
meat
Sorghum
Sugar
Wheat
All covered
products
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
24
26
3
⫺40
⫺25
⫺33
⫺37
⫺29
⫺40
⫺42
⫺49
⫺50
⫺38
⫺33
⫺53
⫺62
⫺51
⫺49
⫺71
⫺66
⫺26
⫺43
⫺50
⫺25
⫺16
⫺19
⫺2
7
14
40
⫺32
⫺29
⫺31
⫺36
⫺48
⫺51
⫺58
⫺65
⫺66
⫺60
⫺59
⫺69
⫺53
1
⫺28
⫺23
5
22
19
48
54
⫺18
2
⫺6
⫺9
18
35
3
8
3
12
0
⫺1
8
⫺24
⫺17
⫺25
⫺23
1
1
2
⫺32
⫺26
⫺16
⫺7
8
4
6
⫺32
⫺42
⫺33
⫺47
⫺53
⫺58
⫺56
⫺52
⫺53
⫺58
⫺52
⫺61
⫺50
⫺36
⫺59
⫺59
⫺63
⫺54
⫺60
⫺63
⫺58
⫺50
⫺64
⫺60
⫺63
⫺61
⫺46
⫺41
⫺41
1
⫺39
⫺43
⫺35
⫺13
⫺35
⫺41
⫺30
⫺25
⫺48
⫺56
⫺52
⫺47
⫺57
⫺55
⫺57
⫺76
⫺42
⫺54
⫺53
⫺45
⫺43
⫺63
⫺17.9
⫺3.2
35.4
69.7
13.0
30.8
33
25
13
⫺6
0
⫺1
⫺32
⫺22
⫺26
⫺27
⫺39
⫺48
⫺48
⫺44
⫺24
42
56
44
14
⫺20
⫺80
⫺78
⫺77
⫺75
⫺74
⫺73
⫺72
⫺71
⫺74
⫺75
⫺73
⫺73
⫺76
⫺68
⫺69
⫺40
⫺63
⫺56
⫺28
⫺19
⫺29
⫺19
⫺24
0
⫺21
⫺11
⫺37
⫺31
⫺30
⫺54
⫺49
⫺46
⫺51
⫺57
⫺56
⫺53
⫺55
⫺59
⫺65
⫺69
⫺70
⫺60
⫺67
⫺64
⫺64
⫺72
⫺67
⫺63
⫺68
⫺68
⫺73
⫺64
⫺6
1
⫺22
⫺45
⫺40
⫺39
⫺42
⫺45
⫺46
⫺52
⫺49
⫺53
⫺51
⫺50
⫺57
⫺69
⫺62
⫺59
⫺63
⫺71
⫺55
⫺40
⫺63
⫺43
⫺49
⫺45
⫺35
⫺20
⫺40
⫺34
⫺47
⫺51
⫺52
⫺44
⫺46
⫺51
⫺42
⫺40
⫺30
⫺39
⫺50
⫺46
⫺62
⫺54
⫺57
⫺53
⫺52
⫺43
⫺23
⫺29
⫺52
⫺65
—
—
—
—
—
—
47
47
50
26
22
40
41
49
54
89
90
59
33
⫺46
⫺51
⫺5
65
84
40
⫺51
7
8
10
12
13
26
12
8
⫺4
⫺18
⫺11
14
⫺7
39
⫺32
⫺16
⫺39
⫺29
⫺43
⫺51
⫺21
⫺11
8
86
⫺9
⫺15
⫺18
⫺13
⫺12
⫺17
⫺20
⫺22
⫺22
⫺21
⫺26
⫺36
⫺33
⫺33
⫺40
⫺37
⫺42
⫺47
⫺46
⫺43
⫺51
⫺55
⫺40
⫺27
⫺28
⫺19
⫺28
⫺36
(Table continues on the following page.)
566
Table B.16. Annual NRA Estimates, Sudan, 1955–2004 (continued)
Year
Beef
Camel
Cotton
Groundnut
Gum
arabic
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
⫺13
⫺38
⫺55
⫺39
⫺63
⫺67
⫺61
⫺55
⫺64
⫺48
⫺74
⫺88
⫺79
⫺84
⫺43
⫺67
⫺60
⫺47
2
⫺49
⫺67
⫺19
⫺50
⫺40
48
32
⫺2
⫺56
⫺30
⫺57
⫺84
⫺81
⫺94
⫺75
⫺79
⫺85
⫺93
⫺95
4
⫺48
67
29
66
76
56
66
62
178
29
17
⫺15
⫺26
⫺25
23
27
⫺17
⫺12
⫺3
⫺34
⫺52
⫺44
⫺26
0
⫺5
⫺9
⫺18
⫺20
⫺10
22
46
11
15
⫺62
⫺39
⫺53
⫺62
⫺51
⫺42
⫺22
⫺18
⫺34
8
⫺17
⫺64
⫺48
⫺61
⫺33
⫺71
⫺45
⫺55
⫺58
⫺18
⫺38
⫺26
⫺31
⫺32
⫺59
⫺52
⫺69
⫺62
⫺66
⫺80
⫺67
⫺51
⫺69
⫺49
⫺78
⫺85
⫺29
⫺45
⫺36
⫺70
⫺50
⫺70
⫺73
⫺73
⫺67
⫺56
⫺60
⫺80
Source: Faki and Taha 2007.
Note: — = no data are available.
Milk
⫺13
⫺41
⫺8
65
116
54
91
92
43
18
⫺39
⫺68
⫺71
⫺5
⫺28
⫺34
⫺19
39
33
60
30
9
44
3
Millet
Sesame
Sheep
meat
Sorghum
Sugar
Wheat
All covered
products
46
⫺28
⫺17
⫺21
⫺20
⫺59
42
63
13
31
332
⫺27
1
44
81
90
⫺29
⫺35
⫺63
⫺6
3
⫺11
6
10
⫺59
⫺59
⫺51
⫺64
⫺29
⫺63
⫺57
⫺39
⫺54
⫺58
⫺2
⫺61
⫺66
⫺54
⫺30
⫺63
⫺59
⫺47
⫺50
⫺55
⫺53
⫺53
⫺32
2
⫺22
⫺45
⫺43
⫺57
⫺64
⫺61
⫺71
⫺57
⫺59
⫺67
⫺69
⫺83
⫺72
⫺72
⫺73
⫺80
⫺47
⫺52
⫺37
⫺34
⫺44
⫺39
⫺31
24
⫺31
⫺61
⫺37
⫺49
⫺25
⫺52
⫺45
⫺37
41
95
390
⫺34
⫺60
⫺13
⫺21
⫺52
⫺2
⫺29
0
51
⫺4
⫺31
⫺45
⫺26
⫺33
⫺37
⫺30
⫺28
⫺20
⫺42
⫺5
2
⫺16
93
⫺6
⫺69
⫺69
⫺50
⫺42
⫺66
18
⫺47
15
104
83
164
136
116
⫺23
27
⫺12
⫺11
28
⫺13
4
47
92
153
291
⫺65
⫺75
⫺9
⫺49
⫺31
⫺24
0
5
44
30
21
21
⫺5
⫺21
⫺40
⫺38
⫺30
⫺28
⫺43
⫺42
⫺30
⫺51
⫺25
⫺34
⫺76
⫺75
⫺60
⫺38
⫺52
⫺31
⫺22
⫺3
⫺7
⫺33
⫺10
⫺15
⫺9
Annual Estimates of Distortions to Agricultural Incentives in Africa
567
Table B.17. Annual NRA Estimates, Tanzania, 1976–2004
(percent)
Year
Bean Cashew Cassava Coffee Cotton Maize Millet Plantain Potato Pyrethrum
1976
⫺84
⫺65
0
⫺68
⫺88
⫺24
0
0
0
1977
⫺79
⫺62
0
⫺72
⫺87
⫺51
0
0
0
⫺92
1978
⫺76
⫺69
0
⫺63
⫺75
⫺55
0
0
0
⫺76
⫺87
1979
⫺67
⫺69
0
⫺74
⫺82
⫺76
0
0
0
⫺74
1980
⫺83
⫺86
0
⫺81
⫺88
⫺57
0
0
0
⫺80
1981
⫺69
⫺85
0
⫺67
⫺87
⫺57
0
0
0
⫺69
1982
⫺55
⫺49
0
⫺68
⫺85
⫺35
0
0
0
⫺62
1983
⫺86
⫺70
0
⫺78
⫺88
⫺54
0
0
0
⫺70
1984
⫺88
⫺68
0
⫺77
⫺90
⫺56
0
0
0
⫺77
1985
⫺83
⫺46
0
⫺74
⫺83
68
0
0
0
⫺71
1986
⫺87
⫺81
0
⫺83
⫺80
⫺13
0
0
0
⫺85
1987
⫺82
⫺82
0
⫺79
⫺82
⫺4
0
0
0
⫺77
1988
⫺81
⫺75
0
⫺81
⫺89
⫺17
0
0
0
⫺80
1989
⫺77
⫺61
0
⫺70
⫺87
⫺21
0
0
0
⫺55
1990
⫺79
⫺49
0
⫺54
⫺91
⫺42
0
0
0
⫺17
1991
⫺62
⫺43
0
⫺51
⫺87
⫺41
0
0
0
⫺17
1992
⫺43
⫺35
0
⫺42
⫺78
68
0
0
0
⫺25
1993
⫺4
⫺32
0
⫺50
⫺84
30
0
0
0
⫺52
1994
⫺35
⫺36
0
⫺23
⫺87
54
0
0
0
⫺74
1995
⫺43
⫺10
0
0
⫺84
⫺29
0
0
0
⫺68
1996
⫺33
0
0
0
⫺68
⫺3
0
0
0
⫺67
1997
⫺45
⫺18
0
0
⫺78
2
0
0
0
⫺71
1998
⫺64
⫺5
0
0
⫺71
⫺39
0
0
0
⫺72
1999
⫺55
⫺7
0
0
⫺63
⫺71
0
0
0
⫺61
2000
⫺42
0
0
0
⫺81
⫺39
0
0
0
⫺49
2001
⫺24
2
0
0
⫺66
⫺42
0
0
0
⫺43
⫺41
2002
⫺38
⫺24
0
0
⫺69
16
0
0
0
2003
⫺56
⫺7
0
0
⫺74
47
0
0
0
⫺48
2004
⫺65
⫺19
0
0
⫺61
12
0
0
0
⫺57
(Table continues on the following page.)
568
Distortions to Agricultural Incentives in Africa
Table B.17. Annual NRA Estimates, Tanzania, 1976–2004 (continued)
Year
Rice
Sisal
Sorghum
Sugar
Tea
Tobacco
Wheat
Yam
All covered
products
1976
⫺67
—
0
⫺40
⫺95
⫺70
⫺60
0
⫺52
1977
⫺53
—
0
9
⫺95
—
⫺15
0
⫺54
1978
⫺41
—
0
2
⫺86
⫺60
⫺12
0
⫺44
1979
⫺42
⫺39
0
⫺6
⫺86
⫺63
⫺39
0
⫺51
1980
⫺71
⫺37
0
⫺74
⫺94
⫺62
⫺67
0
⫺60
1981
⫺67
⫺20
0
⫺77
⫺92
⫺59
⫺58
0
⫺59
1982
⫺50
⫺31
0
⫺55
⫺94
⫺66
⫺37
0
⫺50
1983
⫺67
⫺55
0
⫺47
⫺94
⫺69
⫺58
0
⫺67
1984
⫺66
⫺60
0
⫺36
⫺96
⫺74
⫺54
0
⫺66
1985
⫺35
⫺49
0
39
⫺92
⫺64
⫺24
0
⫺41
1986
⫺31
⫺27
0
⫺22
⫺95
⫺67
⫺39
0
⫺58
1987
⫺44
⫺49
0
⫺6
⫺93
⫺64
⫺44
0
⫺53
1988
⫺37
⫺25
0
⫺42
⫺94
⫺68
⫺66
0
⫺56
1989
⫺52
5
0
⫺43
⫺93
⫺62
⫺63
0
⫺51
1990
⫺60
⫺4
0
⫺29
⫺94
⫺75
⫺68
0
⫺57
1991
⫺51
⫺12
0
13
⫺90
⫺77
⫺27
0
⫺49
⫺22
1992
15
⫺23
0
26
⫺87
⫺55
18
0
1993
55
9
0
73
⫺88
⫺34
148
0
⫺9
1994
51
⫺36
0
31
⫺89
⫺41
152
0
⫺12
1995
—
⫺3
0
9
⫺88
⫺41
46
0
⫺30
1996
65
0
0
66
⫺91
⫺33
43
0
⫺18
1997
56
0
0
100
⫺92
⫺28
208
0
⫺19
1998
11
0
0
3
⫺94
⫺32
71
0
⫺36
1999
⫺32
0
0
21
⫺89
⫺51
14
0
⫺43
2000
⫺4
0
0
72
⫺93
⫺45
121
0
⫺23
2001
32
0
0
96
⫺91
⫺50
138
0
⫺18
2002
38
0
0
96
⫺90
⫺61
107
0
⫺11
2003
25
0
0
137
⫺90
⫺59
61
0
⫺8
2004
⫺10
0
0
115
⫺91
⫺61
51
0
⫺23
Source: Morrisey and Leyaro 2007.
Note: — ⫽ no data are available.
Annual Estimates of Distortions to Agricultural Incentives in Africa
569
Table B.18. Annual NRA Estimates, Togo, 1970–2005
(percent)
Year
Cassava
Cotton
Millet
Sorghum
Yam
All covered
products
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺28
⫺42
⫺43
⫺65
⫺34
⫺42
⫺65
⫺38
⫺46
⫺44
⫺53
⫺48
⫺63
⫺70
⫺57
⫺2
⫺8
⫺21
⫺22
⫺44
⫺31
⫺12
6
⫺19
⫺59
⫺41
⫺35
⫺29
⫺8
⫺2
⫺24
7
⫺19
⫺28
6
⫺5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
—
—
—
—
—
—
—
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
⫺1
⫺1
⫺1
0
⫺1
⫺1
⫺1
⫺1
⫺2
⫺3
⫺4
0
0
⫺2
⫺2
⫺4
⫺3
⫺1
0
⫺1
⫺15
⫺5
⫺5
⫺4
⫺1
0
⫺3
1
⫺2
⫺3
0
0
Source: Baffes 2007.
Note: — ⫽ no data are available.
570
Table B.19. Annual NRA Estimates, Uganda, 1961–2004
(percent)
Year
Bean Cassava Coffee Cotton Groundnut Maize Millet Plantain Rice Sorghum Sugar
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
⫺1
26
0
⫺2
28
⫺2
⫺10
⫺9
0
⫺16
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺4
⫺6
⫺14
⫺21
⫺18
⫺15
⫺26
⫺24
⫺26
⫺32
⫺38
⫺45
⫺62
⫺78
⫺84
⫺93
⫺94
⫺95
⫺87
⫺87
⫺69
⫺11
⫺16
⫺13
⫺14
⫺11
⫺14
⫺22
⫺22
⫺25
⫺25
⫺29
⫺34
⫺53
⫺71
⫺78
⫺81
⫺76
⫺84
⫺79
⫺82
⫺60
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
⫺1
⫺1
⫺2
0
⫺2
0
0
19
22
0
0
53
0
0
0
0
0
0
83
61
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
12
14
14
15
15
16
23
22
24
26
29
35
54
70
77
83
0
0
80
83
62
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
⫺1
⫺1
⫺2
0
⫺2
⫺10
⫺9
⫺12
⫺16
29
34
54
0
0
⫺79
76
0
80
83
62
Tea
⫺1
⫺1
⫺1
⫺2
0
⫺2
⫺10
⫺9
⫺12
⫺16
⫺20
⫺28
⫺50
⫺68
⫺75
⫺79
⫺73
⫺82
⫺79
⫺82
⫺60
Yam
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
All covered
products
⫺2
⫺1
⫺3
⫺5
⫺2
⫺4
⫺7
⫺6
⫺7
⫺6
⫺5
⫺8
⫺14
⫺25
⫺25
⫺26
⫺25
⫺33
⫺13
⫺9
⫺4
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
0
0
0
0
0
0
0
0
0
⫺12
⫺4
⫺1
⫺1
0
0
0
20
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
0
0
0
0
0
0
0
0
0
⫺68
⫺70
⫺64
⫺71
⫺75
⫺72
⫺68
⫺53
⫺36
⫺20
⫺5
⫺1
⫺3
⫺4
⫺3
⫺1
⫺1
⫺1
⫺1
⫺1
⫺1
⫺1
⫺1
⫺51
⫺41
⫺27
⫺56
⫺71
⫺61
⫺60
⫺44
⫺20
⫺12
⫺4
⫺1
⫺1
0
0
0
0
0
0
0
0
0
0
571
Source: Matthews, Claquin, and Opolot 2007.
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
0
0
0
0
0
0
0
0
0
53
⫺41
⫺27
⫺49
0
0
0
⫺44
⫺20
⫺12
⫺4
⫺1
⫺1
0
0
10
11
12
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
0
0
0
0
0
0
0
0
0
54
44
29
51
67
62
0
47
0
0
0
10
12
13
13
12
14
14
14
19
17
19
18
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
0
0
0
0
0
0
0
0
0
0
0
29
51
67
62
62
47
25
17
11
9
12
13
14
15
18
19
20
17
16
16
15
⫺51
⫺41
⫺27
⫺49
⫺66
61
60
44
20
12
4
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺1
0
0
0
0
0
0
0
0
0
⫺15
⫺15
⫺14
⫺15
⫺23
⫺15
⫺9
⫺8
⫺2
⫺2
⫺1
0
0
0
0
1
1
1
0
1
1
0
1
572
Table B.20. Annual NRA Estimates, Zambia, 1961–2004
(percent)
Year
Cotton
Groundnut
Maize
Millet
Rice
Sorghum
Soybean
Sunflower
Tobacco,
Virginia
Tobacco,
burley
Wheat
All covered
products
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
—
—
—
—
⫺27
⫺39
⫺20
⫺38
⫺33
⫺20
⫺18
⫺45
⫺62
⫺38
⫺33
⫺45
⫺54
⫺40
⫺21
⫺40
⫺11
—
—
—
—
⫺51
⫺41
⫺22
⫺38
⫺55
⫺42
⫺56
⫺67
⫺64
⫺68
⫺76
⫺55
⫺76
⫺74
⫺62
⫺79
⫺56
⫺22
⫺32
⫺44
⫺9
⫺2
⫺20
⫺27
⫺42
⫺77
⫺24
⫺55
⫺42
⫺40
⫺46
⫺64
⫺32
⫺76
⫺68
⫺47
⫺51
⫺10
—
—
—
—
—
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
—
—
—
—
—
—
⫺24
⫺20
⫺58
⫺64
⫺59
⫺54
⫺30
⫺11
⫺24
⫺22
⫺20
7
12
3
—
—
—
—
—
⫺12
13
⫺30
⫺32
⫺22
⫺21
⫺44
⫺50
⫺36
⫺48
⫺62
⫺73
⫺72
⫺66
⫺72
⫺55
—
—
—
—
—
—
—
—
—
—
—
—
⫺82
⫺65
⫺68
12
⫺72
⫺66
⫺4
⫺40
⫺28
—
—
—
—
—
—
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺10
⫺14
⫺7
⫺5
3
⫺10
⫺6
⫺40
⫺38
⫺13
⫺25
⫺27
⫺44
⫺45
⫺54
⫺56
⫺72
⫺67
⫺38
⫺1
⫺46
⫺34
⫺2
⫺23
⫺9
⫺32
⫺45
⫺65
⫺48
⫺47
⫺24
⫺34
⫺40
⫺50
⫺37
⫺32
⫺42
⫺65
⫺68
⫺42
⫺2
⫺50
—
—
—
—
—
⫺73
⫺76
⫺76
⫺82
⫺63
⫺71
⫺68
⫺54
⫺44
⫺34
⫺30
⫺50
⫺26
⫺1
⫺6
22
⫺21
⫺29
⫺38
⫺9
⫺11
⫺22
⫺22
⫺38
⫺69
⫺25
⫺50
⫺43
⫺45
⫺47
⫺63
⫺39
⫺74
⫺66
⫺45
⫺49
⫺13
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
⫺34
⫺44
⫺61
⫺61
⫺67
⫺91
⫺87
⫺76
⫺77
⫺70
13
⫺57
16
⫺2
⫺5
⫺19
⫺44
⫺68
⫺53
⫺51
⫺64
⫺38
—
⫺58
⫺67
⫺72
⫺69
⫺69
⫺91
⫺81
⫺81
⫺92
⫺89
⫺74
⫺75
⫺55
⫺40
⫺75
⫺62
⫺88
⫺68
⫺78
⫺79
⫺71
⫺48
—
⫺4
⫺12
⫺40
⫺53
⫺52
⫺79
⫺85
⫺68
⫺77
⫺66
⫺53
⫺20
⫺47
⫺17
⫺52
⫺31
⫺32
⫺9
⫺53
⫺37
⫺9
⫺4
⫺47
Source: Robinson, Govereh, and Ndlela 2007.
573
Note: — ⫽ no data are available.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
53
47
35
⫺7
⫺33
⫺78
⫺81
⫺55
⫺70
⫺62
⫺65
66
⫺4
72
37
⫺23
⫺13
⫺26
⫺48
⫺19
⫺31
3
—
⫺52
⫺43
⫺64
⫺64
⫺60
⫺80
⫺89
⫺76
⫺82
⫺71
⫺62
⫺34
⫺19
⫺8
⫺61
⫺54
⫺73
⫺59
⫺64
⫺67
⫺12
5
12
⫺10
⫺32
⫺58
⫺45
1
⫺92
⫺90
⫺77
⫺86
⫺65
⫺45
⫺69
⫺9
⫺39
⫺24
⫺17
⫺26
⫺49
23
⫺44
⫺29
28
⫺56
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
⫺23
⫺11
⫺52
⫺60
⫺82
⫺89
⫺81
⫺74
⫺73
⫺36
⫺73
12
15
⫺4
59
⫺5
⫺46
⫺30
⫺8
⫺19
⫺35
⫺56
⫺28
⫺39
⫺34
⫺62
⫺68
⫺85
⫺89
⫺85
⫺74
⫺75
⫺28
⫺74
50
9
⫺16
17
⫺32
⫺54
⫺35
⫺46
⫺49
⫺63
⫺71
⫺61
39
29
⫺22
⫺60
⫺42
⫺87
⫺87
⫺71
⫺82
⫺84
⫺74
⫺78
17
0
60
⫺7
11
⫺4
10
12
7
20
68
⫺8
⫺15
⫺42
⫺52
⫺54
⫺82
⫺85
⫺69
⫺79
⫺69
⫺51
⫺31
⫺37
⫺15
⫺46
⫺31
⫺47
⫺29
⫺50
⫺41
⫺27
⫺19
⫺41
Table B.21. Annual NRA Estimates, Zimbabwe, 1955–2004
574
(percent)
Year
Cotton
Groundnut
Maize
Sorghum
Soybean
Sunflower
Tobacco
Wheat
All covered
products
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
⫺92
⫺88
⫺87
⫺86
⫺81
⫺47
113
261
68
25
⫺27
⫺26
⫺27
⫺29
⫺29
⫺53
⫺51
⫺47
⫺52
⫺14
⫺42
⫺65
⫺67
⫺60
⫺45
⫺46
⫺39
⫺29
⫺35
⫺33
⫺32
⫺22
⫺82
⫺81
⫺87
⫺80
⫺78
⫺74
⫺78
⫺82
⫺82
⫺68
⫺72
⫺70
⫺74
⫺79
⫺78
⫺73
47
34
51
28
35
24
⫺20
⫺5
⫺12
⫺12
⫺60
⫺20
⫺13
⫺6
⫺10
40
⫺23
⫺42
⫺40
⫺46
⫺49
⫺60
⫺42
⫺32
—
—
—
—
—
11
1
⫺13
⫺25
⫺23
⫺18
44
⫺17
⫺43
⫺49
⫺63
⫺62
⫺38
⫺56
⫺66
⫺60
⫺61
⫺28
⫺25
—
—
—
—
—
—
—
—
—
—
—
—
—
0
⫺29
⫺43
⫺40
⫺41
⫺11
⫺7
⫺35
⫺52
⫺59
⫺20
—
—
—
—
—
0.0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
—
—
—
—
⫺56
⫺39
⫺33
⫺39
⫺47
⫺33
⫺22
⫺43
⫺45
⫺53
⫺62
⫺58
⫺50
⫺38
⫺21
⫺55
⫺61
⫺54
⫺46
17
51
18
21
28
23
42
38
32
34
42
57
78
58
47
6
29
47
16
⫺23
⫺20
⫺28
⫺2
⫺39
27
20
34
18
21
⫺48
⫺35
⫺26
⫺38
⫺46
⫺49
⫺27
⫺37
⫺29
⫺37
⫺44
⫺44
⫺45
⫺44
⫺44
⫺53
⫺64
⫺57
⫺50
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
⫺48
⫺54
⫺44
⫺17
⫺77
⫺70
⫺61
⫺31
⫺32
⫺49
⫺67
⫺56
⫺75
⫺77
⫺47
⫺32
⫺30
⫺30
⫺33
⫺42
⫺44
⫺44
⫺80
⫺88
⫺83
⫺22
⫺62
⫺73
⫺65
⫺55
⫺75
⫺75
⫺32
⫺57
⫺41
⫺26
⫺52
⫺50
⫺72
5
⫺69
⫺61
⫺60
⫺36
⫺8
⫺56
⫺69
⫺76
⫺81
⫺75
⫺95
⫺77
575
Source: Ndlela and Robinson 2007.
Note: — = no data are available.
⫺45
⫺44
⫺40
⫺22
⫺14
⫺34
⫺28
⫺38
⫺20
⫺45
⫺49
⫺48
⫺62
⫺72
⫺49
⫺14
3
⫺32
⫺37
⫺24
⫺74
17
⫺91
⫺93
⫺62
⫺85
⫺19
⫺25
⫺7
⫺24
⫺57
⫺41
⫺35
⫺6
⫺41
⫺56
⫺46
⫺58
⫺66
⫺63
⫺57
⫺74
⫺80
⫺69
⫺55
⫺87
⫺80
⫺45
⫺75
⫺92
⫺95
⫺78
⫺44
⫺54
⫺58
⫺25
⫺61
⫺13
⫺24
⫺30
⫺22
⫺45
⫺47
⫺27
⫺65
⫺60
⫺38
⫺52
⫺33
⫺49
⫺65
⫺67
⫺57
⫺54
⫺81
⫺86
⫺93
⫺29
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺49
⫺56
⫺19
⫺42
⫺65
⫺47
⫺44
⫺47
⫺57
⫺32
⫺50
⫺25
⫺31
⫺53
⫺44
⫺32
⫺24
⫺22
⫺42
⫺44
⫺43
⫺59
⫺64
⫺80
⫺83
⫺44
⫺29
⫺25
⫺17
4
2
⫺22
⫺21
0
28
⫺11
⫺40
⫺51
⫺50
⫺62
⫺50
⫺23
⫺55
⫺25
⫺36
⫺56
⫺47
⫺69
⫺81
⫺81
⫺90
⫺62
⫺48
⫺52
⫺39
⫺30
⫺61
⫺51
⫺41
⫺40
⫺40
⫺40
⫺52
⫺40
⫺51
⫺58
⫺47
⫺28
⫺27
⫺27
⫺38
⫺43
⫺57
⫺49
⫺82
⫺85
⫺77
⫺72
576
Table B.22. Annual NRA Estimates for Covered Farm Products, African Focus Countries, 1955–2005
(percent)
Year
Apple
Banana
Bean
Beef
Camel
Cashew
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
—
—
—
0
0
0
⫺4
⫺4
⫺13
0
⫺5
1
⫺22
5
4
⫺2
⫺11
33
⫺1
⫺9
⫺15
⫺24
19
0
—
—
—
—
—
—
⫺3
⫺1
⫺4
⫺2
⫺4
⫺4
⫺3
⫺2
⫺8
0
0
0
0
0
1
0
0
⫺8
—
—
—
—
—
—
⫺1
26
0
⫺2
28
⫺2
⫺10
⫺9
0
⫺16
0
0
0
0
0
⫺45
⫺46
⫺60
⫺16
⫺11
⫺11
⫺16
⫺10
⫺23
⫺25
⫺13
⫺16
⫺30
⫺28
⫺31
⫺21
⫺26
⫺37
⫺41
⫺38
⫺38
⫺49
⫺20
20
4
10
11
⫺2
7
14
40
⫺32
⫺29
⫺31
⫺36
⫺48
⫺51
⫺58
⫺65
⫺66
⫺60
⫺59
⫺69
⫺53
1
⫺28
⫺23
5
22
19
48
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺88
⫺73
⫺82
⫺78
Cassava
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
1
1
1
1
Chat
Clove
Cocoa
Coffee
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺57
⫺54
⫺59
⫺8
8
18
26
⫺69
⫺74
⫺74
⫺84
⫺82
⫺85
⫺6
⫺5
⫺6
⫺32
⫺23
⫺15
⫺16
⫺27
⫺39
⫺36
⫺43
⫺47
⫺55
⫺59
⫺64
⫺58
⫺36
⫺41
⫺50
⫺53
⫺39
⫺61
⫺74
⫺68
—
⫺13
⫺17
⫺4
⫺10
⫺6
⫺37
⫺30
⫺27
⫺37
⫺38
⫺38
⫺31
⫺38
⫺38
⫺42
⫺43
⫺43
⫺42
⫺49
⫺46
⫺75
⫺64
⫺69
577
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
⫺18
⫺11
⫺36
3
⫺10
⫺12
14
16
24
⫺14
⫺6
6
3
⫺5
⫺1
25
⫺2
6
⫺3
⫺1
⫺21
1
⫺6
4
1
1
2
⫺1
1
0
⫺2
⫺4
⫺1
1
1
⫺2
⫺1
⫺3
⫺2
⫺1
⫺1
⫺1
20
9
6
7
2
⫺1
5
3
1
⫺1
⫺1
—
⫺41
⫺51
⫺49
⫺38
⫺63
⫺62
⫺70
⫺81
⫺64
⫺60
⫺54
⫺49
⫺37
⫺29
2
⫺12
⫺15
⫺10
⫺19
⫺40
⫺39
⫺24
⫺10
⫺12
⫺30
⫺49
—
⫺26
⫺19
8
11
13
42
⫺18
28
41
48
16
⫺17
⫺30
⫺50
⫺50
⫺42
⫺5
⫺6
0
⫺6
12
⫺21
⫺46
⫺17
⫺24
⫺23
⫺3
54
⫺18
48
32
⫺2
⫺56
⫺30
⫺57
⫺84
⫺81
⫺94
⫺75
⫺79
⫺85
⫺93
⫺95
4
⫺48
67
29
66
76
56
66
62
178
—
⫺78
⫺88
⫺88
⫺69
⫺77
⫺80
⫺80
⫺93
⫺91
⫺78
⫺72
⫺58
⫺52
⫺47
⫺52
⫺59
⫺14
⫺6
⫺16
⫺5
⫺6
0
⫺2
⫺19
⫺7
⫺21
—
2
2
3
4
3
0
2
1
0
0
0
1
0
0
0
⫺3
⫺3
⫺3
⫺3
⫺3
⫺3
⫺3
⫺2
⫺3
⫺3
⫺3
0
—
—
⫺51
⫺52
⫺53
⫺53
⫺51
⫺50
⫺37
⫺46
⫺43
⫺44
⫺45
⫺45
⫺45
⫺46
⫺43
⫺45
⫺44
⫺43
⫺41
⫺41
⫺43
⫺47
⫺26
⫺41
—
⫺78
⫺85
⫺91
⫺95
⫺96
⫺93
⫺79
⫺80
⫺89
⫺91
⫺86
⫺86
⫺82
⫺68
⫺45
⫺32
⫺56
⫺61
⫺74
31
24
⫺3
⫺55
2
—
—
—
⫺60
⫺50
⫺47
⫺50
⫺53
⫺61
⫺59
⫺51
⫺39
⫺26
⫺3
⫺34
⫺31
⫺35
⫺43
⫺31
⫺29
⫺34
⫺31
⫺34
⫺34
⫺38
⫺33
⫺33
⫺42
⫺34
⫺58
⫺56
⫺57
⫺45
⫺54
⫺60
⫺51
⫺55
⫺45
⫺43
⫺40
⫺29
⫺31
⫺29
⫺43
⫺49
⫺33
⫺20
⫺19
⫺24
⫺20
⫺20
⫺13
⫺7
⫺13
⫺15
⫺12
⫺20
(Table continues on the following page.)
578
Table B.22. Annual NRA Estimates for Covered Farm Products, African Focus Countries,
1955–2005 (continued)
Year
Cotton
Fruit & veg.
Grape
Groundnut
Gum arabic
Hides, skin
Maize
Milk
Millet
Oilseed
Orange
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
⫺15
⫺17
⫺18
⫺18
⫺13
⫺28
⫺46
⫺36
⫺44
⫺51
⫺56
⫺51
⫺48
⫺49
⫺59
⫺55
⫺50
⫺45
⫺58
⫺62
⫺54
⫺46
⫺55
⫺38
—
—
—
—
—
—
0
0
0
0
⫺1
⫺2
⫺3
⫺2
⫺4
⫺6
⫺5
⫺7
⫺8
⫺4
⫺1
⫺3
⫺1
⫺3
—
—
—
0
0
0
⫺22
⫺28
⫺9
⫺17
⫺24
⫺28
⫺23
⫺11
⫺8
⫺6
⫺20
17
15
5
17
5
⫺8
15
⫺22
⫺28
⫺26
⫺30
⫺37
⫺43
⫺20
⫺18
⫺30
⫺26
⫺33
⫺32
⫺34
⫺40
⫺52
⫺52
⫺49
⫺49
⫺54
⫺52
⫺47
⫺43
⫺44
⫺48
⫺46
⫺41
⫺41
1
⫺39
⫺43
⫺35
⫺13
⫺35
⫺41
⫺30
⫺25
⫺48
⫺56
⫺52
⫺47
⫺57
⫺55
⫺57
⫺76
⫺42
⫺54
⫺53
⫺45
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺26
⫺5
3
4
3
3
16
17
9
15
⫺13
5
5
12
3
5
⫺1
3
⫺10
⫺31
⫺17
⫺8
⫺18
⫺12
⫺56
⫺47
⫺34
⫺18
⫺23
⫺18
⫺34
⫺22
⫺18
⫺17
⫺29
⫺16
⫺36
⫺40
⫺37
⫺34
⫺42
⫺51
⫺51
⫺34
⫺20
5
20
3
⫺80
⫺78
⫺77
⫺75
⫺74
⫺73
⫺5
⫺4
⫺7
⫺9
⫺7
⫺6
⫺7
⫺7
⫺5
⫺4
⫺8
⫺7
⫺1
0
⫺1
⫺1
⫺2
0
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0
0
0
⫺2
⫺2
1
⫺19
⫺17
⫺4
⫺9
⫺8
⫺24
⫺31
⫺27
⫺40
⫺31
⫺15
⫺21
⫺9
⫺39
⫺11
579
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
⫺53
⫺53
⫺44
⫺33
⫺41
⫺45
⫺51
⫺27
⫺16
⫺35
⫺27
⫺59
⫺53
⫺64
⫺47
⫺46
⫺31
⫺43
⫺30
⫺39
⫺47
⫺46
⫺51
⫺56
⫺46
⫺32
⫺16
⫺4
⫺6
⫺6
⫺7
⫺5
⫺5
⫺1
⫺2
⫺5
⫺3
⫺1
0
⫺3
⫺9
⫺12
0
0
⫺1
⫺1
⫺3
0
0
0
0
0
0
—
⫺29
⫺19
⫺37
⫺36
⫺32
⫺20
0
33
23
13
⫺7
⫺6
⫺4
39
⫺9
⫺7
3
0
10
13
12
⫺5
44
2
⫺2
⫺2
⫺1
⫺47
⫺53
⫺57
⫺18
⫺57
⫺37
⫺32
⫺24
1
3
⫺33
⫺39
17
⫺35
⫺51
⫺41
⫺41
⫺41
⫺29
⫺34
⫺33
⫺40
⫺43
⫺40
⫺39
⫺40
46
⫺43
⫺63
⫺59
⫺52
⫺69
⫺62
⫺66
⫺80
⫺67
⫺51
⫺69
⫺49
⫺78
⫺85
⫺29
⫺45
⫺36
⫺70
⫺50
⫺70
⫺73
⫺73
⫺67
⫺56
⫺60
⫺80
—
—
—
⫺46
⫺47
⫺47
⫺48
⫺46
⫺46
⫺53
⫺52
⫺52
⫺52
⫺49
⫺52
⫺51
⫺53
⫺50
⫺52
⫺51
⫺47
⫺45
⫺50
⫺50
⫺49
⫺47
⫺46
—
⫺7
7
0
⫺3
5
⫺5
⫺5
48
85
29
31
12
21
⫺4
2
10
6
⫺4
9
4
⫺3
8
⫺11
⫺3
⫺8
⫺13
6
⫺10
⫺26
⫺27
⫺51
⫺24
21
38
37
93
95
69
10
⫺21
⫺55
⫺58
⫺10
⫺28
⫺32
⫺18
20
19
36
16
⫺1
25
⫺2
⫺5
⫺2
0
7
⫺2
0
⫺2
0
⫺6
2
2
2
1
4
⫺1
0
⫺2
4
1
⫺5
⫺5
⫺10
⫺3
⫺2
⫺3
⫺2
⫺1
0
—
—
⫺52
⫺48
⫺29
⫺44
⫺45
⫺39
⫺46
⫺65
⫺46
⫺49
⫺55
⫺63
⫺66
⫺52
⫺55
⫺62
⫺52
⫺50
⫺44
⫺46
⫺40
⫺32
—
—
—
⫺27
10
⫺24
⫺21
⫺6
⫺17
⫺29
⫺7
⫺13
⫺28
2
⫺4
⫺5
2
⫺9
0
⫺3
15
3
⫺12
6
20
⫺12
19
7
8
17
(Table continues on the following page.)
580
Table B.22. Annual NRA Estimates for Covered Farm Products, African Focus Countries,
1955–2005 (continued)
Year
Other tubers
Palm oil
Pepper
Plantain
Potato
Poultry
Pulse
Pyrethrum
Rice
Sesame
Sheep meat
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
—
—
—
—
—
—
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
—
—
—
—
—
⫺18
⫺13
⫺35
⫺34
⫺43
⫺34
⫺42
⫺10
⫺26
⫺57
⫺51
⫺25
⫺47
⫺42
⫺8
20
⫺58
⫺27
⫺13
—
—
—
—
—
—
—
—
—
—
—
⫺62
⫺48
⫺41
16
⫺9
⫺19
6
6
⫺5
⫺24
⫺47
⫺35
⫺57
⫺34
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0
0
0
0
—
—
—
—
—
⫺13
⫺13
⫺13
⫺13
⫺13
⫺13
⫺13
⫺13
⫺13
⫺13
⫺31
⫺15
⫺16
⫺10
⫺7
⫺21
⫺34
⫺29
⫺22
⫺12
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺87
⫺92
⫺76
⫺74
⫺68
⫺65
⫺62
⫺58
⫺56
⫺54
⫺31
⫺31
⫺37
⫺38
⫺37
⫺34
⫺35
⫺47
⫺41
⫺11
5
⫺2
⫺39
⫺64
⫺40
⫺18
12
⫺14
⫺10
⫺37
⫺31
⫺30
⫺54
⫺49
⫺46
⫺51
⫺57
⫺56
⫺53
⫺55
⫺59
⫺65
⫺69
⫺70
⫺60
⫺67
⫺64
⫺64
⫺72
⫺67
⫺63
⫺68
⫺68
⫺73
⫺6
1
⫺14
⫺25
⫺17
⫺22
⫺21
⫺5
⫺12
⫺11
⫺16
⫺18
⫺18
⫺19
⫺19
⫺28
⫺6
⫺11
⫺27
⫺37
⫺13
⫺3
⫺35
⫺25
⫺30
581
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
1
1
⫺4
⫺62
⫺63
⫺43
⫺19
⫺27
80
⫺50
⫺49
95
97
⫺10
405
191
27
7
3
⫺22
⫺24
⫺17
⫺13
⫺9
0
—
⫺19
⫺38
⫺57
⫺54
⫺65
⫺73
⫺77
⫺88
⫺83
⫺78
⫺71
⫺27
⫺16
⫺22
⫺15
⫺50
⫺49
⫺78
⫺70
⫺63
20
6
⫺56
—
—
—
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
20
23
6
31
12
⫺21
⫺13
9
18
⫺7
⫺3
⫺4
5
20
14
15
20
21
4
5
⫺2
⫺15
⫺10
20
20
22
—
⫺35
⫺34
⫺36
⫺25
⫺54
⫺58
⫺55
⫺57
⫺57
⫺44
⫺44
⫺62
⫺56
⫺54
⫺36
⫺43
⫺36
⫺32
⫺29
⫺31
⫺17
⫺14
—
—
—
⫺80
⫺69
⫺62
⫺70
⫺77
⫺71
⫺85
⫺77
⫺80
⫺55
⫺17
⫺17
⫺25
⫺52
⫺74
⫺68
⫺67
⫺71
⫺72
⫺61
⫺49
⫺43
⫺41
⫺48
⫺57
—
⫺17
⫺27
⫺16
⫺20
11
21
11
28
45
38
3
16
⫺4
⫺3
⫺9
⫺16
⫺13
⫺8
⫺5
1
⫺11
⫺1
⫺13
3
⫺5
⫺12
⫺64
⫺59
⫺59
⫺51
⫺64
⫺29
⫺63
⫺57
⫺39
⫺54
⫺58
⫺2
⫺61
⫺66
⫺54
⫺30
⫺63
⫺59
⫺47
⫺50
⫺55
⫺53
⫺53
⫺32
2
—
⫺17
⫺7
⫺26
⫺17
⫺34
⫺46
⫺31
⫺40
⫺27
⫺42
⫺45
⫺40
⫺48
⫺54
⫺56
⫺60
⫺62
⫺35
⫺42
⫺27
⫺23
⫺38
⫺37
⫺27
18
6
(Table continues on the following page.)
582
Table B.22. Annual NRA Estimates for Covered Farm Products, African Focus Countries,
1955–2005 (continued)
Year
Sisal
Sorghum
Soybean
Sugar
Sunflower
Tea
Teff
Tobacco
Vanilla
Wheat
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺39
⫺37
⫺35
⫺20
⫺40
⫺34
⫺47
⫺51
100
109
72
78
89
107
88
72
77
41
44
52
61
47
29
47
26
36
5
7
—
—
—
—
—
—
—
—
—
—
—
—
—
0
⫺29
⫺43
⫺40
⫺41
⫺15
⫺10
⫺37
⫺51
⫺59
⫺25
⫺43
⫺54
⫺29
⫺25
⫺23
⫺18
⫺14
⫺24
13
15
⫺17
⫺16
⫺23
7
30
27
16
0
⫺18
⫺27
⫺19
⫺57
⫺51
⫺27
8
5
8
⫺41
—
—
—
—
—
0
9
23
24
19
12
10
22
19
22
13
8
14
6
⫺10
0
7
8
14
5
25
—
—
2
2
6
6
13
16
7
6
3
⫺2
⫺6
⫺15
⫺13
⫺15
⫺14
⫺24
⫺25
⫺22
⫺15
⫺48
⫺30
⫺28
⫺31
⫺37
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺56
⫺38
⫺32
⫺37
⫺45
⫺31
⫺21
⫺40
⫺45
⫺52
⫺58
⫺55
⫺48
⫺39
⫺24
⫺55
⫺62
⫺56
⫺49
⫺50
⫺55
—
—
—
—
—
⫺66
⫺62
⫺61
⫺66
⫺53
⫺55
⫺42
⫺57
⫺52
⫺57
⫺43
⫺35
⫺34
⫺37
⫺46
⫺46
⫺68
⫺47
⫺75
⫺49
⫺57
⫺16
⫺16
⫺11
⫺13
⫺8
⫺15
⫺24
⫺35
⫺32
⫺31
⫺24
⫺23
⫺6
⫺4
⫺5
3
⫺6
19
⫺15
⫺33
⫺13
0
29
32
13
⫺14
Yam
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
1
2
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
⫺20
⫺31
⫺55
⫺60
⫺49
⫺27
⫺49
⫺25
5
⫺4
⫺12
⫺23
9
⫺36
⫺3
0
0
0
0
0
0
0
0
0
—
39
9
⫺4
32
56
⫺3
72
44
37
52
83
20
⫺1
32
21
0
31
24
38
64
21
9
5
4
0
⫺56
⫺23
⫺56
⫺26
⫺28
⫺27
⫺38
⫺55
⫺54
⫺46
⫺65
⫺58
⫺52
⫺44
⫺35
⫺41
⫺56
⫺64
⫺55
⫺43
⫺75
⫺67
⫺38
⫺49
4
⫺35
4
38
29
25
36
78
45
27
⫺9
⫺1
⫺5
5
18
1
⫺9
11
1
30
51
35
27
54
51
12
20
15
19
1
⫺2
14
18
2
2
7
17
12
1
⫺5
⫺5
⫺6
⫺8
⫺14
1
⫺1
⫺14
⫺7
0
4
1
583
Source: Anderson and Valenzuela 2008, based on estimates in chapters 2⫺18 of this book.
Note: — ⫽ no data are available.
⫺32
⫺42
⫺41
⫺15
⫺18
⫺15
⫺28
⫺46
⫺38
⫺30
⫺34
⫺67
⫺43
⫺28
⫺33
⫺33
⫺35
⫺25
⫺14
⫺19
⫺9
⫺20
⫺17
⫺17
—
⫺2
⫺4
⫺2
⫺11
⫺10
⫺7
⫺9
⫺6
⫺6
⫺9
⫺11
⫺9
⫺6
⫺7
⫺5
⫺1
⫺5
⫺4
⫺8
⫺9
⫺2
⫺8
⫺12
⫺5
—
⫺24
⫺43
⫺65
⫺49
⫺46
⫺50
⫺58
⫺34
⫺51
⫺29
⫺34
⫺53
⫺43
⫺31
⫺25
⫺22
⫺40
⫺42
⫺42
⫺57
⫺60
⫺74
⫺77
⫺48
—
⫺67
⫺87
⫺86
⫺85
⫺83
⫺81
⫺91
⫺87
⫺85
⫺84
⫺89
⫺73
⫺73
⫺71
⫺69
⫺49
9
⫺5
⫺29
⫺9
6
⫺35
—
—
—
⫺10
0
2
⫺3
⫺11
13
38
28
28
5
17
⫺5
0
3
⫺5
⫺4
7
4
4
4
1
⫺11
⫺2
2
7
2
2
1
0
1
0
0
0
0
0
0
0
0
⫺3
⫺4
⫺4
⫺4
⫺3
⫺3
⫺3
⫺3
⫺3
⫺3
⫺3
0
584
Table B.23. Annual NRAs for Exportable, Import-Competing, and All Covered Farm Products, for
Nonagricultural Tradables, and for the RRAs, 16 African Focus Countries, 1955–2005
(percent)
NRA, total agricultural productsa
Covered products
Year
Inputs
Outputs
Noncovered
products
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺22
⫺18
⫺16
⫺17
⫺15
⫺23
⫺8
⫺4
⫺11
⫺14
⫺18
⫺13
⫺15
⫺17
⫺23
⫺20
⫺16
⫺16
⫺24
⫺29
⫺19
⫺20
⫺20
⫺16
1
1
0
1
1
1
5
6
3
4
3
5
1
2
0
⫺3
0
3
0
0
2
2
⫺2
⫺3
NRA, agricultural tradablesb
All
products
⫺17
⫺13
⫺13
⫺13
⫺13
⫺18
⫺4
⫺1
⫺7
⫺9
⫺12
⫺8
⫺10
⫺11
⫺16
⫺15
⫺11
⫺10
⫺17
⫺21
⫺12
⫺12
⫺15
⫺11
Exportables
Importcompeting
⫺21
⫺17
⫺17
⫺25
⫺23
⫺32
⫺27
⫺25
⫺32
⫺35
⫺40
⫺35
⫺33
⫺37
⫺46
⫺43
⫺40
⫺34
⫺45
⫺50
⫺41
⫺44
⫺47
⫺43
⫺31
⫺26
⫺22
⫺12
⫺11
⫺15
25
42
23
18
10
23
12
10
5
7
9
6
⫺6
⫺5
12
24
25
19
All
NRA,
nonagricultural
tradables
RRA
⫺30
⫺25
⫺23
⫺22
⫺20
⫺30
⫺7
⫺2
⫺13
⫺15
⫺22
⫺14
⫺16
⫺19
⫺26
⫺25
⫺20
⫺18
⫺28
⫺33
⫺21
⫺21
⫺25
⫺21
17
17
20
23
23
22
⫺2
⫺2
1
⫺3
1
⫺5
6
4
5
6
1
0
0
⫺2
⫺3
⫺5
11
12
⫺41
⫺35
⫺36
⫺37
⫺35
⫺42
⫺6
0
⫺13
⫺13
⫺22
⫺10
⫺21
⫺22
⫺30
⫺29
⫺21
⫺18
⫺28
⫺32
⫺18
⫺17
⫺32
⫺29
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
⫺20
⫺18
⫺10
⫺9
⫺11
⫺7
⫺12
1
13
9
2
⫺8
⫺3
⫺17
⫺19
⫺7
⫺4
⫺10
⫺2
⫺3
0
⫺2
⫺10
⫺7
⫺5
⫺5
⫺1
0
2
1
2
⫺13
⫺9
⫺14
⫺11
⫺2
⫺6
⫺5
⫺6
⫺3
⫺7
⫺7
⫺1
⫺4
⫺7
⫺6
⫺4
⫺5
⫺7
⫺5
⫺5
⫺5
⫺5
⫺2
⫺13
⫺11
⫺5
⫺4
⫺11
⫺9
⫺12
⫺3
8
4
⫺1
⫺8
⫺4
⫺12
⫺15
⫺6
⫺5
⫺10
⫺5
⫺5
⫺4
⫺5
⫺9
⫺8
⫺7
⫺6
⫺2
⫺38
⫺36
⫺28
⫺29
⫺41
⫺42
⫺48
⫺40
⫺31
⫺30
⫺35
⫺36
⫺29
⫺42
⫺41
⫺31
⫺27
⫺32
⫺27
⫺25
⫺19
⫺19
⫺36
⫺22
⫺25
⫺21
⫺11
Source: Anderson and Valenzuela 2008, based on estimates in chapters 2–17 of this book.
585
a. The NRAs include assistance to nontradables and non-product-specific assistance.
b. The NRAs include product-specific input subsidies.
⫺4
⫺2
8
18
13
29
26
61
98
65
47
12
24
⫺12
⫺15
18
10
0
17
13
10
4
6
⫺6
4
⫺1
7
⫺23
⫺18
⫺10
⫺7
⫺19
⫺13
⫺21
⫺5
17
9
0
⫺13
⫺5
⫺23
⫺27
⫺9
⫺8
⫺17
⫺7
⫺8
⫺5
⫺8
⫺17
⫺13
⫺11
⫺11
⫺2
9
3
⫺10
⫺15
17
9
12
12
1
12
7
8
1
6
4
⫺8
0
3
0
0
5
9
3
6
8
6
14
⫺29
⫺21
0
10
⫺30
⫺21
⫺29
⫺15
15
⫺2
⫺6
⫺19
⫺6
⫺27
⫺29
⫺1
⫺8
⫺19
⫺7
⫺7
⫺9
⫺15
⫺19
⫺18
⫺18
⫺16
⫺14
586
Distortions to Agricultural Incentives in Africa
Table B.24. Annual Value Shares of Agricultural Production for
Farm Products, African Focus Countries, 1955–2005
(percent)
Year Bean Beef Camel Cassava Cocoa Coffee Cotton Groundnut Maize
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
—
—
—
—
—
—
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
0
0
1
1
1
0
0
0
0
0
0
0
9
9
8
8
8
8
6
5
5
6
6
7
7
7
7
7
7
8
9
5
4
5
4
5
7
7
5
5
7
5
6
7
7
7
8
6
7
8
1
1
1
1
1
1
0
0
0
0
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
2
2
5
1
1
0
1
1
1
1
1
1
6
7
6
6
5
8
5
4
3
4
6
5
4
3
5
6
7
8
7
7
12
10
5
8
7
7
10
8
6
8
11
10
5
5
4
6
6
5
4
4
4
5
3
3
4
4
5
5
4
3
4
3
3
4
6
5
6
4
3
2
2
4
3
3
3
3
2
2
2
2
—
1
1
1
1
1
3
2
3
4
3
4
3
4
3
4
3
4
4
2
3
8
8
6
5
4
3
4
4
3
4
5
3
3
2
2
1
1
15
15
18
15
17
17
8
8
8
7
9
7
7
7
10
8
7
7
7
7
6
6
7
5
5
5
3
3
4
4
4
4
4
5
4
4
4
5
1
1
1
1
1
1
4
4
4
4
5
4
4
3
3
3
3
3
3
4
4
3
2
3
3
3
3
1
2
2
1
2
1
1
2
2
1
1
5
6
5
5
5
4
7
7
7
6
8
7
9
7
7
6
8
7
6
9
9
7
7
6
5
7
8
8
8
8
11
7
6
9
8
9
7
7
Annual Estimates of Distortions to Agricultural Incentives in Africa
587
Year Bean Beef Camel Cassava Cocoa Coffee Cotton Groundnut Maize
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
0
1
0
1
1
1
1
1
0
1
1
—
9
8
4
4
4
4
4
6
9
5
7
7
8
2
1
0
0
0
0
0
0
0
0
0
0
—
9
9
9
9
11
11
10
10
11
10
9
9
2
2
2
2
3
2
3
2
2
3
3
3
3
4
1
3
2
2
2
2
1
1
1
1
1
1
1
3
2
2
3
3
2
2
2
3
2
2
2
3
2
1
2
2
2
2
2
2
2
2
2
2
0
8
9
8
8
8
8
10
8
7
8
10
10
13
(Table continues on the following page.)
588
Distortions to Agricultural Incentives in Africa
Table B.24. Annual Value Shares of Agricultural Production
for Farm Products, African Focus Countries,
1955–2005 (continued)
Year
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
Milk Millet Orange
7
7
6
6
7
6
3
2
2
2
3
2
3
3
2
2
2
3
3
2
2
2
2
2
2
2
2
3
3
2
2
2
2
2
2
2
1
1
1
1
1
1
4
4
4
3
4
3
4
4
3
4
4
4
4
3
3
3
2
2
3
2
2
3
2
2
2
3
3
2
2
2
—
—
—
0
0
0
0
0
0
0
0
0
0
0
1
1
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Other
tubers
—
—
—
—
—
—
1
1
2
1
1
1
1
2
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
Palm oil Plantain Poultry Pulse Rice
—
—
—
—
—
—
1
1
1
1
1
1
1
1
1
1
1
0
0
1
1
0
1
1
1
1
1
0
0
1
1
0
1
0
0
0
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
1
2
2
2
2
2
2
1
1
2
2
1
1
1
2
2
2
—
—
—
—
—
1
0
0
0
0
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
1
2
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0
1
1
1
0
1
0
0
0
1
4
4
4
4
4
3
2
3
3
3
3
3
4
6
4
2
2
2
4
6
5
4
2
3
3
3
3
3
3
2
2
3
3
2
3
3
Annual Estimates of Distortions to Agricultural Incentives in Africa
Year
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Milk Millet Orange
2
2
3
3
3
3
3
3
3
3
3
4
3
4
2
2
2
2
2
2
2
2
3
2
2
2
2
2
2
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
Other
tubers
0
0
0
0
0
0
0
0
0
0
0
0
0
0
—
589
Palm oil Plantain Poultry Pulse Rice
0
0
1
0
0
1
1
1
1
1
1
1
1
1
—
1
2
2
3
4
2
2
2
2
3
2
2
2
2
1
2
2
2
2
2
2
1
1
1
2
2
2
2
2
4
1
0
0
0
0
0
0
0
0
0
0
0
—
—
—
2
3
3
3
3
3
3
3
3
3
3
3
3
3
5
(Table continues on the following page.)
590
Distortions to Agricultural Incentives in Africa
Table B.24. Annual Value Shares of Agricultural Production
for Farm Products, African Focus Countries,
1955–2005 (continued)
Year
Sesame
Sheep
meat
Sorghum
Sugar
Tea
Teff
Tobacco
Wheat
Yam
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1
1
1
1
1
1
0
1
0
0
0
0
0
0
0
0
1
1
1
1
1
1
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
1
1
4
5
4
4
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
2
2
2
2
2
2
2
2
2
1
2
2
2
2
1
1
2
1
3
3
3
2
4
5
4
4
4
3
3
3
3
4
4
3
3
4
3
3
3
3
3
3
3
4
3
3
2
3
3
2
2
2
2
3
1
1
1
1
1
1
2
2
2
2
2
2
1
1
2
1
2
2
2
4
4
2
2
2
2
3
2
2
1
1
1
1
1
2
2
2
2
1
—
—
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0
1
0
1
1
0
0
0
0
0
1
0
—
—
—
—
—
5
2
2
2
2
1
1
1
1
1
1
1
1
1
0
1
1
0
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
4
5
5
4
4
4
2
2
2
2
2
2
2
2
2
2
2
2
2
3
2
2
1
1
2
2
4
5
6
4
4
5
4
4
5
3
5
4
5
4
4
4
4
3
7
7
7
7
5
7
5
5
5
6
8
6
6
8
7
6
6
7
7
7
7
7
4
6
5
4
5
5
5
6
8
8
Annual Estimates of Distortions to Agricultural Incentives in Africa
591
Year
Sesame
Sheep
meat
Sorghum
Sugar
Tea
Teff
Tobacco
Wheat
Yam
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
0
0
0
0
0
0
0
0
0
0
0
—
2
2
2
1
1
1
1
1
2
2
2
2
1
3
2
2
3
2
3
2
2
2
3
3
3
2
1
1
1
2
1
2
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
—
0
0
0
0
0
0
1
1
0
0
0
0
—
1
1
1
1
1
1
1
1
1
1
1
0
—
4
4
4
4
4
5
5
4
5
6
5
5
11
7
8
9
7
8
8
8
8
7
7
7
7
2
Source: Anderson and Valenzuela 2008, based on estimates in chapters 2–18 of this book.
Note: — ⫽ no data are available. Value shares are given in undistorted farmgate prices. Columns for
apple, banana, cashew, chat, clove, fruits and vegetables, grape, gum arabic, hides and skins, oilseed,
pepper, potato, pyrethrum, sisal, and soybean are omitted because their annual shares of the gross value
of regional production are each less than 0.5 percent.
592
Table B.25. Gross Subsidy Equivalents of Assistance to Farmers, African Focus Countries, 1955–2004
(constant 2000 US$ millions)
Year
Benin
Burkina Faso
Cameroon
Chad
Côte d’Ivoire
Egypt,
Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
BJ
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺3
⫺6
⫺7
⫺20
⫺5
⫺5
⫺6
⫺2
BF
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺1
⫺3
⫺4
⫺11
⫺4
⫺9
⫺18
⫺4
CM
—
—
—
—
—
—
⫺81
⫺74
⫺102
⫺76
⫺101
⫺126
⫺164
⫺203
⫺278
⫺238
⫺179
⫺183
⫺309
⫺406
⫺172
⫺469
⫺1,110
TD
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺8
⫺14
⫺15
⫺50
⫺15
⫺30
⫺44
⫺15
CI
—
—
—
—
—
—
⫺388
⫺253
⫺376
⫺606
⫺424
⫺638
⫺470
⫺726
⫺755
⫺735
⫺562
⫺632
⫺800
⫺982
⫺516
⫺3,819
⫺2,792
EG
⫺1,748
⫺1,673
⫺1,602
⫺1,442
⫺1,337
⫺1,831
⫺2,364
⫺2,268
⫺2,757
⫺3,142
⫺3,821
⫺3,205
⫺2,431
⫺3,250
⫺4,035
⫺2,937
⫺3,065
⫺2,902
⫺4,773
⫺7,087
⫺4,085
⫺1,926
⫺558
ET
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
GH
⫺33
⫺16
⫺36
⫺239
⫺190
⫺130
16
⫺174
⫺284
⫺369
⫺231
⫺312
⫺393
⫺360
⫺455
⫺341
⫺70
⫺204
⫺427
⫺626
⫺480
⫺679
⫺874
KE
—
119
142
168
121
142
29
157
255
227
⫺41
⫺64
180
189
112
⫺94
⫺246
⫺32
⫺110
⫺188
65
193
⫺858
MG
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
ML
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺6
⫺10
⫺11
⫺24
⫺10
⫺25
⫺46
⫺17
2
2
2
2
2
⫺12
⫺116
⫺68
⫺100
⫺123
⫺111
⫺201
⫺146
⫺309
⫺157
⫺14
⫺13
⫺18
⫺515
⫺1,229
⫺405
⫺621
⫺633
593
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
⫺4
⫺5
⫺3
⫺1
⫺4
⫺8
⫺9
2
1
⫺3
⫺2
⫺12
⫺11
⫺5
4
⫺9
⫺43
⫺33
⫺22
⫺25
2
⫺4
⫺12
3
⫺7
⫺10
7
⫺10
⫺12
⫺12
⫺7
⫺12
⫺17
⫺11
1
0
⫺6
⫺4
⫺16
⫺14
⫺4
2
⫺3
⫺32
⫺17
⫺17
⫺26
⫺5
⫺2
⫺11
6
⫺7
⫺16
27
⫺793
⫺636
⫺342
⫺183
⫺224
⫺208
⫺414
⫺192
⫺184
26
67
45
⫺42
⫺34
⫺3
⫺42
⫺45
⫺10
4
⫺47
⫺93
⫺46
6
5
⫺29
⫺21
19
⫺23
⫺14
⫺14
⫺8
⫺14
⫺30
⫺8
2
2
⫺1
1
⫺12
⫺8
⫺2
3
⫺3
⫺25
⫺16
⫺14
⫺12
0
1
⫺6
0
⫺3
⫺4
8
⫺2,026
⫺1,962
⫺1,735
⫺1,864
⫺1,147
⫺1,639
⫺1,291
⫺1,690
⫺1,215
⫺1,082
⫺774
⫺473
⫺852
⫺652
⫺669
⫺709
⫺879
⫺844
⫺955
⫺909
⫺942
⫺737
⫺643
⫺700
⫺1,025
⫺1,048
⫺1,139
⫺444
⫺3,216
⫺2,979
⫺3,432
⫺1,936
902
1,426
⫺941
4,212
7,063
7,758
8,648
⫺1,073
511
⫺1,388
⫺674
⫺287
⫺117
⫺728
679
954
980
338
⫺523
⫺1,426
⫺437
⫺808
—
—
—
⫺1,509
⫺1,917
⫺1,985
⫺2,039
⫺3,524
⫺2,203
⫺1,969
⫺2,277
⫺1,986
⫺2,360
⫺2,920
⫺2,270
⫺1,380
⫺2,008
⫺2,080
⫺1,785
⫺2,301
⫺2,039
⫺2,276
⫺1,513
⫺699
⫺1,227
⫺1,183
⫺945
⫺730
⫺874
⫺499
⫺611
⫺493
—
⫺13
⫺204
⫺217
1
⫺3
⫺31
⫺41
44
3
⫺37
⫺107
⫺94
⫺121
⫺64
⫺63
⫺47
⫺105
41
27
⫺112
⫺22
⫺436
252
⫺634
⫺382
⫺666
⫺266
⫺91
183
248
309
⫺179
281
31
⫺117
130
⫺441
11
⫺35
⫺16
81
⫺63
210
88
237
92
133
153
⫺756
⫺362
⫺553
⫺706
⫺566
⫺516
⫺554
⫺213
⫺230
⫺315
⫺244
⫺195
⫺101
⫺110
⫺80
⫺94
20
⫺103
⫺42
⫺60
9
3
30
⫺16
⫺37
⫺1
75
⫺28
⫺24
⫺23
⫺13
⫺23
⫺30
⫺19
⫺1
⫺5
⫺10
⫺9
⫺32
⫺23
⫺8
9
⫺8
⫺60
⫺46
⫺43
⫺43
⫺7
⫺14
⫺11
8
⫺5
⫺10
27
(Table continues on the following page.)
594
Table B.25. Gross Subsidy Equivalents of Assistance to Farmers, African Focus Countries,
1955–2004 (continued)
Mozambique
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
MZ
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺299
⫺301
⫺367
Nigeria
NG
—
—
—
—
—
—
2,272
2,827
1,647
2,029
1,417
2,298
605
1,057
502
⫺298
907
1,332
1,162
1,234
2,116
2,915
⫺776
⫺330
South Africa
Senegal
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
ZA
—
—
—
—
—
—
96
441
177
29
119
406
596
748
630
181
332
540
⫺205
⫺2,349
⫺676
⫺68
873
935
SN
—
—
—
—
—
—
⫺96
⫺70
⫺76
⫺61
⫺60
⫺55
⫺45
⫺22
⫺88
⫺77
⫺105
⫺111
⫺265
⫺612
⫺593
⫺327
⫺126
⫺419
SD
⫺347
⫺260
⫺298
⫺338
⫺478
⫺545
⫺509
⫺594
⫺712
⫺1,070
⫺996
⫺1,064
⫺1,313
⫺1,250
⫺1,374
⫺1,910
⫺1,945
⫺2,019
⫺2,901
⫺3,960
⫺2,545
⫺1,588
⫺1,875
⫺1,269
TZ
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
⫺1,085
⫺1,529
⫺1,601
TG
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0
⫺1
⫺1
⫺3
⫺1
⫺2
⫺3
⫺1
⫺3
UG
—
—
—
—
—
—
⫺12
⫺5
⫺45
⫺83
⫺34
⫺47
⫺81
⫺62
⫺96
⫺116
⫺107
⫺140
⫺185
⫺445
⫺462
—
—
—
ZM
—
—
—
—
—
—
—
—
—
—
⫺21
⫺74
⫺34
⫺103
⫺514
54
⫺182
⫺122
⫺150
⫺161
⫺407
⫺192
⫺790
⫺451
ZW
40
39
58
26
30
⫺478
⫺298
⫺211
⫺326
⫺420
⫺564
⫺206
⫺277
⫺204
⫺275
⫺267
⫺373
⫺481
⫺441
⫺811
⫺809
⫺1,083
⫺794
⫺613
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
⫺154
⫺344
⫺247
⫺161
⫺137
⫺101
⫺106
⫺131
⫺148
⫺124
⫺91
⫺28
⫺20
⫺17
⫺13
⫺22
13
41
48
72
82
52
45
58
71
49
1,004
2,281
5,179
5,293
⫺1,615
⫺147
474
770
3,733
1,278
753
456
2,825
⫺488
⫺1,285
2,464
858
⫺1,622
158
615
474
⫺1,118
⫺539
⫺959
⫺1,612
⫺942
587
1,520
2,797
2,749
2,302
966
⫺208
912
2,196
956
406
788
866
401
578
1,569
979
759
1,020
⫺371
⫺108
309
⫺406
⫺283
293
156
⫺421
⫺289
⫺612
⫺26
⫺61
⫺113
⫺70
46
172
87
⫺13
45
34
97
83
⫺71
⫺35
⫺16
⫺38
⫺5
⫺63
⫺111
⫺74
⫺16
3
⫺13
⫺2,027
⫺2,653
⫺1,967
⫺2,981
⫺2,536
⫺1,728
⫺1,548
⫺2,580
⫺2,874
⫺1,882
⫺6,035
⫺1,481
⫺1,826
⫺4,395
⫺5,904
⫺4,561
⫺2,351
⫺3,375
⫺1,928
⫺1,423
⫺161
⫺412
⫺2,923
⫺653
⫺1,236
⫺825
595
Source: Anderson and Valenzuela 2008, based on estimates in chapters 2–18 of this book.
Note: — ⫽ no data are available.
⫺1,886
⫺1,477
⫺1,066
⫺651
⫺986
⫺1,130
⫺567
⫺792
⫺645
⫺697
⫺623
⫺630
⫺458
⫺278
⫺95
⫺148
⫺566
⫺294
⫺393
⫺739
⫺889
⫺437
⫺396
⫺170
⫺155
⫺492
⫺4
⫺5
⫺3
⫺6
⫺7
⫺9
0
⫺1
⫺4
⫺4
⫺10
⫺8
⫺2
1
⫺3
⫺24
⫺11
⫺12
⫺11
⫺2
0
⫺4
1
⫺4
⫺8
1
—
—
22
⫺133
⫺260
⫺206
⫺165
⫺149
⫺134
⫺43
⫺61
10
⫺41
⫺11
⫺4
⫺16
⫺4
1
35
34
23
14
14
13
13
16
⫺101
⫺198
91
70
18
⫺134
⫺203
⫺216
⫺377
⫺733
⫺451
⫺422
⫺259
⫺4
⫺82
⫺123
⫺22
⫺352
⫺140
⫺272
⫺201
⫺237
⫺127
⫺128
⫺96
⫺205
⫺594
⫺762
⫺748
⫺377
⫺524
⫺598
⫺534
⫺480
⫺384
⫺574
⫺691
⫺512
⫺806
⫺490
⫺614
⫺257
⫺272
⫺396
⫺470
⫺393
⫺805
⫺504
⫺1,432
⫺782
⫺562
⫺975
596
Table B.26. Share of the Regional Value of Agricultural Production, 16 African Focus Countries, 1955–2004
a. Annual average
(percent)
Year
CM
CI
EG
ET
GH
KE
MG
MZ
NG
ZA
SN
SD
TZ
UG
ZM
ZW
CCa
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
—
—
—
—
—
—
7
8
8
7
7
7
7
8
7
7
6
7
7
5
5
5
6
—
—
—
—
—
—
4
4
4
5
4
5
5
6
5
5
4
5
5
4
5
10
9
50
47
47
49
48
45
18
18
19
20
23
20
20
22
23
17
16
18
20
22
20
17
13
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
17
17
14
17
16
15
6
5
5
5
4
4
5
4
5
4
4
4
4
3
4
3
3
—
4
4
4
3
3
2
2
2
2
3
3
2
2
2
2
2
2
2
2
2
2
5
9
8
7
7
7
6
4
4
4
4
4
4
4
5
4
3
3
3
4
4
3
2
3
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0
1
1
—
—
—
—
—
—
27
29
27
27
23
27
23
22
22
24
24
20
22
24
22
21
20
2
2
4
4
4
5
13
12
13
12
11
12
16
13
13
13
14
14
14
16
15
11
10
—
—
—
—
—
—
2
2
2
2
2
2
2
2
1
1
1
1
2
2
3
2
1
21
21
22
19
21
20
8
10
9
8
9
9
9
10
9
10
10
11
11
9
10
9
9
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
4
4
—
—
—
—
—
—
5
5
5
5
6
5
5
5
6
6
7
5
4
3
4
4
7
—
—
—
—
—
—
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
6
2
2
2
2
3
2
2
2
2
1
2
2
2
2
2
2
2
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
6
5
5
5
3
4
4
6
597
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
5
5
5
3
3
3
3
2
4
3
4
3
4
3
4
4
5
4
4
3
3
3
3
4
4
3
3
8
10
7
5
5
7
6
6
6
6
6
4
5
4
5
5
6
5
5
5
5
4
5
4
5
4
4
13
14
15
12
14
14
13
12
14
12
13
13
13
12
12
13
11
11
13
11
10
11
12
12
11
10
12
—
—
—
10
13
17
14
20
16
12
13
12
13
14
11
8
12
12
10
13
14
15
12
10
13
14
13
4
3
4
2
2
—
3
2
2
3
2
2
2
3
3
3
2
3
2
3
4
3
3
3
3
4
4
3
2
3
2
3
2
3
2
3
2
3
2
2
2
2
2
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
2
2
2
2
2
1
1
1
1
2
1
1
1
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
0
24
18
18
28
25
20
25
25
22
26
21
22
26
25
26
22
23
28
29
29
27
28
27
23
24
22
21
10
13
14
12
10
10
10
8
9
10
11
10
10
10
10
11
10
8
9
8
8
8
8
8
8
9
10
2
2
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
0
1
1
1
0
1
1
9
10
10
10
10
11
9
8
9
11
10
16
9
9
8
12
11
8
8
8
8
7
10
14
10
12
12
4
5
3
2
2
2
2
2
2
2
2
2
2
1
2
2
2
3
2
3
3
3
3
3
3
3
3
7
6
7
2
3
4
3
2
2
2
3
3
3
2
3
4
5
6
3
4
4
4
5
5
4
5
5
1
1
1
1
0
1
1
0
1
0
1
1
0
0
0
1
1
0
1
0
1
1
1
0
1
1
1
2
2
2
2
2
1
2
2
2
2
2
2
2
2
1
2
1
1
2
2
1
2
2
3
2
1
2
5
7
6
4
5
5
4
4
5
6
6
5
6
7
8
7
5
5
6
5
6
5
5
6
7
7
6
(Table continues on the following page.)
598
Table B.26. Share of the Regional Value of Agricultural Production, 16 African Focus Countries,
1955–2004 (continued)
b. Five-year averages
(percent)
1955–59
1960–64
1965–69
1970–74
1975–79
1980–84
1985–89
1990–94
1995–99
2000–04
CM
CI
EG
ET
GH
KE
MG
MZ
NG
ZA
SN
SD
TZ
UG
ZM
ZW
CCa
—
7
7
6
5
3
3
4
3
3
—
4
5
5
8
6
6
5
5
5
48
24
22
19
15
13
13
12
11
11
—
—
—
—
—
14
15
12
13
12
16
7
4
4
3
3
2
3
3
3
4
2
2
2
3
3
2
2
2
2
8
4
4
3
3
2
2
2
2
2
—
—
—
—
1
1
1
1
1
1
—
27
23
23
21
23
23
25
28
23
3
11
13
14
12
11
10
10
8
9
—
2
2
1
2
1
1
1
1
1
21
11
9
10
9
10
11
10
8
12
—
—
—
—
4
2
2
2
3
3
—
5
5
5
6
4
2
3
4
5
—
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
—
—
—
5
5
5
5
7
6
6
Source: Anderson and Valenzuela 2008, based on estimates in chapters 2–18 of this book.
Note: — ⫽ no data are available. See table B.27 for a definition of the country codes. The value of production is given at undistorted prices.
a. The cotton countries are Benin, Burkina Faso, Chad, Mali, and Togo.
Table B.27. Summary of NRA Data for 21 African Focus Countries
2000–04
Country
Benin
Burkina Faso
Cameroon
Chad
Côte d’Ivoire
Egypt, Arab Rep. of
Ethiopia
Ghana
Kenya
Madagascar
Mali
Mozambique
Nigeria
South Africa
Senegal
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
All African focus countries
ISO
code
BJ
BF
CM
TD
CI
EG
ET
GH
KE
MG
ML
MZ
NG
ZA
SN
SD
TZ
TG
UG
ZM
ZW
Maximum
number of
years
Maximum
number of
products
Number of
NRA
observations
NRA,
weighted
averagea
NRA,
standard
deviationa
Gross
value of
productionb
36
36
45
36
45
51
25
49
49
51
36
31
44
51
45
50
29
36
44
45
51
51
5
5
10
5
7
7
8
7
7
10
5
14
10
14
4
12
18
5
13
10
8
44
180
180
432
180
310
357
192
343
324
413
180
378
440
618
169
594
517
172
572
394
373
7,318
⫺0.5
⫺0.1
⫺0.1
⫺0.1
⫺24.5
⫺6.1
⫺11.2
⫺1.4
9.3
1.0
0.1
12.4
⫺5.4
⫺0.1
⫺7.5
⫺11.9
⫺12.4
⫺0.7
0.4
⫺29.6
⫺56.8
⫺7.3
7.2
10.4
7.5
10.3
33.1
22.1
23.6
25.5
25.6
22.5
9.9
37.9
53.2
20.3
18.6
63.2
51.9
7.7
6.9
38.1
33.9
25.2c
1.1
1.2
2.9
0.7
3.8
9.8
10.5
2.9
1.6
1.3
1.7
0.9
19.8
7.4
0.5
10.0
2.7
0.4
4.0
0.5
1.5
85.4
599
Source: Anderson and Valenzuela 2008, based on estimates in chapters 2–18 of this book.
a. Weighted average NRA and standard deviation NRA for covered products using the gross value of production at undistorted prices as weights.
b. Average annual gross value of total production at undistorted prices, in current US$ billions.
c. Simple average of country five-year averages.
600
Table B.28. Summary of NRA Data by Major Product, African Focus Countries, 2000–04
Product
Applec
Banana
Bean
Beef
Camel
Cashew
Cassava
Chat
Clove
Cocoa
Coffee
Cotton
Fruit and vegetablesc
Grapec
Groundnut
Gum arabic
Hides and skins
Maize
Milk
Millet
Oilseed
Orangec
NRA,
unweighted
average
NRA,
weighted
average
Gross value
of
productiona
0.0
0.2
1.1
⫺1.7
⫺18.1
87.7
⫺9.6
⫺0.4
⫺39.5
⫺18.7
⫺23.4
⫺13.5
⫺20.7
0.0
4.2
⫺27.3
⫺67.1
⫺48.4
3.5
3.5
⫺0.3
⫺39.4
0.0
0.3
1.1
⫺25.1
⫺26.0
87.7
⫺9.9
⫺2.6
⫺39.5
⫺18.7
⫺35.8
⫺12.0
⫺46.1
0.0
7.4
⫺40.3
⫺67.1
⫺48.4
⫺5.4
14.6
⫺2.3
⫺39.4
0.00
0.15
0.08
0.49
5.89
0.10
0.06
8.45
0.07
0.05
2.59
0.70
1.94
0.14
0.21
1.72
0.02
0.03
7.24
2.99
1.79
0.08
Countries included (by ISO code)b
ZA
CM
MZ, TZ, UG
EG, ZA, SD
SD
MZ, TZ
BJ, BF, CM, TD, CI, GH, MG, ML, MZ, NG, TZ, TG, UG
ET
MG
CM, CI, GH, MG, NG
CM, CI, ET, KE, MG, TZ, UG
BJ, BF, CM, CI, TD, EG, ML, MZ, NG, SN, SD, TZ, TG, UG, ZM, ZW
KE
ZA
GH, MZ, NG, SN, SD., UG, ZM, ZW
SD
ET
CM, EG, ET, GH, KE, MG, MZ, NG, ZA, TZ, UG, ZM, ZW
EG, SD
BJ, BF, CM, TD, ML, MZ, NG, SN, SD, TZ, TG, UG, ZM
ET
ZA
Roots & tubers
Palm oil
Pepper
Plantain
Potato
Poultry
Pulse
Pyrethrum
Rice
Sesame
Sheep meat
Sisal
Sorghum
Soybean
Sugar
Sunflower
Tea
Teff
Tobacco
Vanilla
Wheat
Yam
All covered products
5.7
0.0
⫺12.6
⫺10.2
⫺0.1
0.0
2.7
⫺20.4
⫺47.7
9.0
⫺38.1
⫺10.6
0.0
⫺2.5
⫺42.1
54.1
⫺1.3
⫺30.2
⫺7.1
⫺45.4
⫺12.8
14.5
⫺9.6
8.4
0.0
⫺12.6
⫺10.2
⫺0.1
0.0
2.7
⫺20.4
⫺47.7
⫺5.5
⫺38.1
⫺21.4
0.0
20.7
⫺54.2
43.7
⫺3.5
⫺16.4
⫺7.1
⫺63.0
⫺12.8
⫺1.1
⫺7.3
0.23
0.38
0.73
0.00
1.93
0.07
1.36
0.16
0.00
2.45
0.20
1.57
0.01
2.13
0.04
1.03
0.15
0.58
0.37
0.51
0.06
4.03
52.8
CM
NG
MG
CM, CI, GH, TZ, UG
MZ, TZ
ZA
ET
TZ
CI, EG, GH, MG, MZ, NG, SN, TZ, UG, ZM
SD
ZA, SD
TZ
ZM, ZW
EG, KE, MG, MZ, ZA, SD, TZ, UG
ZA, ZM, ZW
KE, TZ, UG
ET
MZ, TZ, ZM, ZW
MG
EG, ET. KE, ZA, SD, TZ, ZM, ZW
BJ, BF, TD, CI, GH, MG, ML, MZ, NG, TZ, TG, UG
Source: Anderson and Valenzuela 2008, based on estimates in chapters 2–18 of this book.
601
a. The average annual gross value of production of covered products is given at undistorted prices (current US$ billions).
b. See table B.27 for a definition of the country codes.
c. Even though apple, fruit and vegetables, grape, and orange are covered by only one country, the weighted and simple averages differ because traded and nontraded
products have been treated separately.
602
Table B.29. Shares of the Global Volume of Consumption (C) and Production (Q) of Covered Agricultural
Products, 16 African Focus Countries, 2000–04
(percent)
Product
Apple
Banana
Bean
Beef
Cassava
Cocoa
Coffee
Cotton lint
Cotton seed
Grape
Groundnut
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
CM
CI
EG
ET
GH
KE
MG
MZ
NI
ZA
SE
SD
TZ
UG
ZM
ZW
All studied
World
—
—
0.6
1.0
—
—
—
—
1.1
1.1
0.2
3.6
0.2
1.1
0.1
0.5
0.3
0.3
—
—
—
—
—
—
—
—
—
—
—
—
—
—
4.8
41.4
0.4
4.5
0.1
1.0
0.5
0.7
—
—
—
—
—
—
—
—
—
—
1.2
0.9
—
—
—
—
—
—
0.9
1.2
1.0
1.0
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
1.7
3.1
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
4.6
4.6
1.5
13.0
—
—
—
—
—
—
—
—
0.6
0.6
—
—
—
—
—
—
—
—
—
—
—
—
0.1
1.3
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
1.4
1.4
0.0
0.1
0.6
0.8
—
—
—
—
—
—
—
—
—
—
—
—
0.0
0.0
—
—
—
—
—
—
—
—
0.0
0.1
0.1
0.1
—
—
0.3
0.3
—
—
—
—
—
—
—
—
18.0
18.0
5.1
10.0
—
—
0.8
0.8
0.7
0.7
—
—
8.4
8.3
0.5
1.0
—
—
—
—
1.1
1.0
—
—
—
—
—
—
—
—
—
—
1.8
2.3
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0.0
0.0
0.0
0.0
—
—
2.1
3.0
—
—
—
—
—
—
0.5
0.5
—
—
—
—
—
—
0.0
0.3
0.3
0.3
—
—
2.7
2.7
—
—
—
—
1.6
1.6
—
—
4.0
4.0
—
—
0.0
0.6
0.1
0.2
0.2
0.2
—
—
—
—
—
—
—
—
2.4
2.5
—
—
2.8
2.8
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0.1
0.1
0.1
0.1
—
—
0.2
0.1
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0.1
0.7
0.5
0.6
—
—
0.5
0.5
0.5
1.0
0.6
1.0
4.0
4.1
2.8
2.4
31.9
31.8
11.6
68.2
3.2
13.3
2.3
4.9
3.9
4.2
1.8
2.3
15.3
16.1
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
0.1
1.9
0.0
0.1
0.1
0.1
—
—
0.4
0.4
Maize
Milk
Sheep meat
Poultry
Rice
Sorghum
Soybean
Sugar
Sunflower
Tea
Wheat
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
C
Q
0.1
0.1
—
—
—
—
—
—
—
—
0.7
0.8
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0.3
0.2
—
—
—
—
—
—
—
—
—
—
—
—
1.8
1.1
0.7
0.7
—
—
—
—
0.8
1.0
—
—
—
—
1.5
1.0
—
—
—
—
1.9
1.1
0.5
0.5
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0.4
0.2
0.2
0.2
—
—
—
—
—
—
0.1
0.0
—
—
—
—
—
—
—
—
—
—
—
—
0.5
0.4
—
—
—
—
—
—
—
—
—
—
—
—
0.4
0.3
—
—
1.1
6.2
0.1
0.0
0.0
0.0
—
—
—
—
—
—
0.5
0.4
—
—
—
—
0.1
0.1
—
—
—
—
—
—
Source: Based on data from the Food and Agriculture Organization, FAOSTAT.
603
Note: — ⫽ no data are available. See table B.27 for definition of country codes.
0.2
0.2
—
—
—
—
—
—
0.1
0.0
—
—
—
—
0.2
0.0
—
—
—
—
—
—
0.7
0.7
—
—
—
—
—
—
0.8
0.6
13.4
13.8
—
—
—
—
—
—
—
—
—
—
1.5
1.9
—
—
1.8
1.4
1.3
1.2
—
—
—
—
—
—
—
—
2.9
2.1
—
—
0.5
0.4
—
—
—
—
—
—
—
—
0.2
0.0
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0.8
0.8
2.3
2.3
—
—
—
—
5.2
4.5
—
—
0.3
0.4
—
—
—
—
0.2
0.0
0.5
0.4
—
—
—
—
—
—
0.2
0.1
1.1
1.2
—
—
0.2
0.1
—
—
0.1
0.6
0.1
0.0
0.2
0.2
—
—
—
—
—
—
0.0
0.0
0.6
0.6
—
—
0.1
0.1
—
—
0.1
0.8
—
—
0.2
0.1
—
—
—
—
—
—
0.0
0.0
0.1
0.1
0.0
0.0
—
—
0.1
0.1
—
—
0.0
0.0
0.3
0.4
—
—
—
—
—
—
—
—
0.1
0.2
0.1
0.1
—
—
0.1
0.1
—
—
0.1
0.0
6.7
6.1
1.5
1.5
4.1
3.7
1.3
1.2
3.0
2.4
21.2
21.1
0.1
0.1
2.7
1.9
3.1
2.3
1.2
7.6
3.3
2.9
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
604
Table B.30. Shares of the Global Value of Imports (M) and Exports (X) of Covered Agricultural Products,
16 African Focus Countries, 2000–03
(percent)
Product
Banana
Beana
Beef
Coffeeb
Cottonc
Groundnutd
Maize
Milk
M
X
M
X
M
X
M
X
M
X
M
X
M
X
M
X
CM
CI
EG
ET
GH
KE
MG
MZ
NI
ZA
SE
SD
TZ
UG
ZM
ZW
All
studied
Total,
world
0.0
1.2
—
—
—
—
0.0
1.0
0.0
1.0
—
—
0.0
0.0
—
—
—
—
—
—
—
—
0.0
2.5
0.0
2.2
—
—
—
—
—
—
—
—
—
—
1.6
0.0
—
—
0.1
1.9
—
—
5.3
0.0
0.7
0.0
—
—
—
—
—
—
0.0
2.6
—
—
—
—
0.1
0.0
—
—
—
—
—
—
—
—
—
—
—
—
0.0
0.1
0.0
0.0
—
—
—
—
—
—
—
—
0.0
1.6
—
—
—
—
0.8
0.0
—
—
—
—
—
—
—
—
0.0
0.0
—
—
—
—
0.0
0.0
—
—
—
—
0.0
0.0
—
—
—
—
0.0
0.1
0.0
0.0
0.2
0.0
—
—
—
—
—
—
—
—
—
—
0.1
0.0
0.2
0.0
0.0
0.0
—
—
—
—
—
—
0.1
0.1
—
—
—
—
—
—
0.3
0.8
—
—
—
—
—
—
—
—
—
—
0.0
0.1
0.0
0.2
—
—
—
—
—
—
—
—
0.0
0.0
—
—
0.0
0.8
0.0
0.5
—
—
0.1
0.0
—
—
0.0
0.2
—
—
0.0
1.1
0.0
0.5
—
—
0.1
0.0
—
—
—
—
0.0
0.2
—
—
0.0
1.2
0.0
0.2
0.0
0.0
0.0
0.0
—
—
—
—
—
—
—
—
—
—
0.0
0.1
0.0
0.0
0.0
0.0
—
—
—
—
—
—
—
—
—
—
0.0
2.6
0.2
0.2
0.0
0.1
—
—
0.0
1.2
0.0
0.4
1.6
0.1
0.0
9.9
0.2
9.6
0.4
1.1
6.8
1.0
0.7
0.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
Sheep meat
Poultry
Rice
Soybeane
Sugar
Tea
Wheat
M
X
M
X
M
X
M
X
M
X
M
X
M
X
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
1.4
0.0
—
—
—
—
—
—
—
—
—
—
—
—
0.0
1.7
—
—
0.7
0.0
—
—
4.2
0.0
—
—
—
—
—
—
—
—
—
—
—
—
1.0
0.0
—
—
—
—
0.7
0.0
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
0.5
0.0
0.0
15.7
0.7
0.0
—
—
—
—
0.6
0.0
—
—
0.1
0.0
—
—
—
—
Source: Based on data from the Food and Agriculture Organization, FAOSTAT.
Note: — ⫽ no data are available. See table B.27 for definition of country codes.
a. Includes green and dry beans.
b. Incudes green and roasted coffee.
c. Includes cottonseed and cotton lint.
d. Includes groundnuts in shell and shelled.
e. Soybean complex includes soybeans, cake of soybeans, and oil of soybean.
—
—
—
—
0.3
0.0
—
—
0.7
0.3
—
—
—
—
—
—
—
—
2.9
0.0
—
—
—
—
—
—
—
—
0.9
0.0
0.5
0.1
—
—
—
—
0.0
2.9
—
—
0.5
0.1
—
—
—
—
1.5
0.0
—
—
—
—
—
—
—
—
0.0
0.8
—
—
—
—
—
—
0.1
0.3
—
—
1.2
0.0
—
—
—
—
0.8
0.0
—
—
0.5
0.1
0.0
1.4
0.3
0.1
—
—
—
—
0.2
0.0
—
—
0.2
0.0
0.0
1.3
—
—
—
—
—
—
0.0
0.0
0.0
0.0
—
—
—
—
0.1
0.0
—
—
—
—
—
—
0.1
0.1
—
—
—
—
0.1
0.0
0.9
0.8
0.5
0.1
8.4
1.8
0.1
0.1
2.9
3.6
0.0
18.3
8.1
0.3
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
605
606
Distortions to Agricultural Incentives in Africa
References
Abbott, P. 2007. “Distortions to Agricultural Incentives in Côte D’Ivoire.” Agricultural Distortions
Working Paper 46. World Bank, Washington, DC.
Alfieri, A., C. Arndt, and X. Cirera. 2007. “Distortions to Agricultural Incentives in Mozambique.”
Agricultural Distortions Working Paper 54. World Bank, Washington, DC.
Anderson, K., M. Kurzweil, W. Martin, D. Sandri, and E. Valenzuela. 2008. “Measuring Distortions to
Agricultural Incentives, Revisited.” World Trade Review 7 (4): 675–704.
Anderson, K., and E. Valenzuela. 2008. Global Estimates of Distortions to Agricultural Incentives, 1955 to
2007. Database spreadsheets available at www.worldbank.ord/agdistortions.
Baffes, J. 2007. “Distortions to Cotton Incentives in West and Central Africa.” Agricultural Distortions
Working Paper 50. World Bank, Washington, DC.
Bamou, E., and W. Masters. 2007. “Distortions to Agricultural Incentives in Cameroon.” Agricultural
Distortions Working Paper 42. World Bank, Washington, DC.
Brooks, J., A. Croppenstedt, and E. Aggrey-Fynn. 2007. “Distortions to Agricultural Incentives in
Ghana.” Agricultural Distortions Working Paper 47. World Bank, Washington, DC.
Cassing, J., S. Nassar, G. Siam, and H. Moussa. 2007. “Distortions to Agricultural Incentives in Egypt.”
Agricultural Distortions Working Paper 36. World Bank, Washington, DC.
Faki, H., and A. Taha. 2007. “Distortions to Agricultural Incentives in Sudan.” Agricultural Distortions
Working Paper 44. World Bank, Washington, DC.
Kirsten, J., L. Edwards, and N. Vink. 2007. “Distortions to Agricultural Incentives in South Africa.”
Agricultural Distortions Working Paper 38. World Bank, Washington, DC.
Maret, F. 2007. “Distortions to Agricultural Incentives in Madagascar.” Agricultural Distortions Working Paper 53. World Bank, Washington, DC.
Masters, W. 2007. “Distortions to Agricultural Incentives in Senegal.” Agricultural Distortions Working
Paper 41. World Bank, Washington, DC.
Morrisey, O., and V. Leyaro. 2007. “Distortions to Agricultural Incentives in Tanzania.” Agricultural
Distortions Working Paper 52. World Bank, Washington, DC.
Matthews, A., P. Claquin, and J. Opolot. 2007. “Distortions to Agricultural Incentives in Uganda.”
Agricultural Distortions Working Paper 51. World Bank, Washington, DC.
Ndlela, D., and P. Robinson. 2007. “Distortions to Agricultural Incentives in Zimbabwe.” Agricultural
Distortions Working Paper 39. World Bank, Washington, DC.
Rashid, S., M. Assefa, and G. Ayele. 2007. “Distortions to Agricultural Incentives in Ethiopia.” Agricultural Distortions Working Paper 43. World Bank, Washington, DC.
Robinson, P., J. Govereh, and D. Ndlela. 2007. “Distortions to Agricultural Incentives in Zambia.”
Agricultural Distortions Working Paper 40. World Bank, Washington, DC.
Valenzuela, E., M. Kurzweil, J. Croser, S. Nelgen, and K. Anderson. 2007. “Annual Estimates of African
Distortions to Agricultural Incentives.” Agricultural Distortions Working Paper 55. World Bank,
Washington, DC.
Walkenhorst, P. 2007. “Distortions to Agricultural Incentives in Nigeria.” Agricultural Distortions
Working Paper 37. World Bank, Washington, DC.
Winter-Nelson, A., and G. Argwings-Kodhek. 2007. “Distortions to Agricultural Incentives in Kenya.”
Agricultural Distortions Working Paper 45. World Bank, Washington, DC.
Index
Figures, notes, and tables are indicated by f, n, and t, respectively.
A
Africa. See Economies of Africa
African Growth and
Opportunity Act, 109, 161
Amin, Idi, 330, 331, 335, 351
Antitrade policy bias
in African economies, 3, 6
Egypt, 71, 76
Madagascar, 112
Nigeria, 449
NRA features and, 25–26
Senegal, 482
Sudan, 296
Tanzania, 321
Asia
economic growth, 8
NRA patterns, 43, 49f
poverty patterns and
trends, 6
RRA patterns, 49f
B
Bananas, 108
Beans and pulses, production
and policies
Ethiopia, 239, 246
Mozambique, 135, 136,
141–142
Nigeria, 449
Tanzania, 320–321
Uganda, 333, 345–346
Zambia, 184
Zimbabwe, 216
Benin, 491, 492–494, 541t. See
also Economies of Africa;
West and Central Africa
Berseem, 73, 79
Burkina Faso, 489, 491,
494–495, 542t. See also
Economies of Africa; West
and Central Africa
C
Cameroon
agricultural NRAs, 374–379,
543–544t
agricultural productivity, 380
calculation of rates of
assistance, 361–362,
370–374
colonial period, 363
corruption in, 380
credit system, 367
data sources, 372
economic development, 361,
362, 368
evolution of agricultural
policies and performance,
362–369, 379
exchange rate, 372–374
extension services, 367
farm product output,
370f, 371f
forestry, 367, 379
future challenges and
opportunities, 379–381
goals for international trade
negotiations, 380–381
input subsidies, 362, 366
petroleum economy, 362,
365–366, 368
poverty in, 361
research and education
investments, 366–367
RRAs, 376–378
trade flows, 369, 382 n.6
trade policy, 366
Cassava production and
policies
Madagascar, 103, 108, 115
Mozambique, 130, 132,
135, 136
Nigeria, 444, 449
Uganda, 333, 347
Chad, 491–492, 495–497, 545t.
See also Economies of
Africa; West and
Central Africa
Chat, 239, 246
Chiluba, Frederick, 194, 196
Cloves, 103, 108–109, 117
Cocoa production and policies
Côte d’Ivoire, 385, 387, 390,
394, 395, 396, 397–399,
404, 406, 409, 410 n.5
Ghana, 414, 416, 417,
426–429, 430, 431
Madagascar, 117
Nigeria, 449
607
608
Index
Coffee production and policies
Cameroon, 369
Côte d’Ivoire, 385, 390, 392,
394, 395, 396, 404, 406
Ethiopia, 239, 245, 246
Kenya, 255, 257, 268–269,
276–277
Madagascar, 103, 108, 117
Tanzania, 308, 309, 311,
314–315, 318–320
Uganda, 333, 337, 340–343
Colonial governance
Cameroon, 363
Côte d’Ivoire, 392–393
Ghana, 415–416
Kenya, 260–261
Mozambique, 128–129
Nigeria, 444–445
Senegal, 463, 464–465,
468–469
Sudan, 287–289
West and Central African
countries, 485
Zambia, 175, 178–179
Zimbabwe, 205, 206
Comecon. See Council for
Mutual Economic
Assistance
Commodity differences,
agricultural NRAs in
Africa, 21, 25–26f, 27t,
35, 576–583t
by country, 541–575t
shares of global
consumption and
production, 602–603t
shares of global trade,
604–605t
summary, 600–601t
value shares of agricultural
production, 586–591t
Common Market for Eastern
and Southern Africa, 109
Comparative advantage
in agriculture and processed
foods, 15t
patterns and trends in
Africa, 15t
political economy of rates
of assistance, 43
rates of assistance and, 43,
51f, 52t
Consumer support
estimates, 15
Consumer tax equivalents
application, 13–15, 526
calculation, 15–19, 509–510,
526–527
commodity coverage, 18
definition, 11
Egypt, 82
general equilibrium
modeling, 531 n.3,
533 n.15
modeling exchange rate
effects, 512–513
NRAs and, 11–13, 53, 510
OECD measures and, 15,
17, 18
patterns and trends in
African economies, 53,
54–59t
South Africa, 170
U.S. dollar equivalents, 20,
57–59t, 530
Zambia, 187–189
Zimbabwe, 212
Corruption
in Cameroon, 380
in Ghana, 417, 426, 436
in Kenya, 279
Côte d’Ivoire
agricultural NRAs, 404,
406, 546t
calculation of rates of
assistance, 403–404
cocoa production and
policies, 385, 387–388,
390, 394, 395, 396,
397–399, 404, 406, 409,
410 n.5
colonial period, 392–393
economic development, 385,
387, 388
evolution of economic and
agricultural policies, 386,
387–388, 392–397,
404–409
exchange rate, 389, 395, 396
future prospects, 387, 409–410
immigrant workers,
387–388, 394, 396
land use, 390
political environment, 387,
388, 392, 396–397, 410
RRAs, 404
structure and performance
of agricultural sector,
385–387, 390–392,
397–403
trade flows, 385, 386,
388–389, 390–391, 393,
397, 399, 401, 402, 403
trade policy, 386, 389, 393,
394–395, 397–398, 399,
402–403
Cotton
African producers, 5
Cameroon’s production and
policies, 369
Côte d’Ivoire’s production
and policies, 387, 391,
394, 396–397, 400–401,
404, 406
Egypt’s production and
policies, 78, 79–81, 86,
87–88
Madagascar’s production
and policies, 108
Mozambique’s production
and policies, 130, 132, 134,
135, 136, 142
Nigeria’s production and
policies, 449
Senegal’s production and
policies, 477, 480
Sudan’s production and
policies, 285, 290, 291,
302, 304, 305 n.3
Tanzania’s production and
policies, 311, 314, 315, 320
Uganda’s production and
policies, 333, 337, 343–345
West and Central African
development, 485–490
West and Central African
reforms and distortions,
490–502
Zambia’s production and
policies, 197–198
Zimbabwe’s production and
policies, 213, 216, 222, 224
Council for Mutual Economic
Assistance, 72
Credit system
Cameroon, 367
Kenya, 291
Nigeria, 457–458
Uganda, 339
D
Distortions, generally
data sources for African
economies, 4, 5, 521–522
definition, 65 n.2
flow-on consequences, 508
food aid effects, 237–238,
242–243, 250 n.17
historical evolution in
Africa, 3, 6
nonagricultural, agricultural
assistance through,
520–521
postfarmgate costs, 515
Index
research goals, 4, 508–509
sources of, 17, 35, 36t, 63,
176, 181–184, 189–198,
207–208, 214–216,
218–225, 244–248, 255,
274–279, 300–303, 308,
330, 414, 442, 507
See also Nominal rates of
assistance (NRAs);
Relative rates of assistance
(RRAs)
Doha negotiations, 4,
60–62, 379
E
Eastern Africa, 5. See also
Economies of Africa;
specific country
Economic growth
antiagricultural policy biases
in Africa and, 3
Cameroon, 361, 362, 368
Côte d’Ivoire, 388
Egypt, 74–76, 77
Ethiopia, 234–235, 235t
future prospects for African
economies, 63–64
Ghana, 413, 415–423
international comparison, 8
Madagascar, 103, 104–111
Nigeria, 442–443
patterns and trends in Africa,
5, 6, 8
role of international institutions and multilateral
agreements, 60–62
Senegal, 463–464
South African agricultural
sector, 148–151
Sudan, 284–285, 290,
291–292, 293–294, 305 n.5
Tanzania, 308–309, 310, 315
Uganda, 329, 330,
331–332, 334
Zambia, 176, 189–190
Economic Partnership
Agreement, 4
Economies of Africa
antiagricultural policy bias, 3
antitrade bias, 3
common features, 62–63
consumer tax equivalents of
agricultural policies,
53, 54–59t
countries of interest, 5–6.
See also specific country
data sources, 4
diversity among, 5, 6, 43
future challenges and opportunities, 4–5, 63–65
key indicators, 7t
NRA patterns and trends,
21–41, 63, 576–583t
RRA patterns and trends,
29–30t, 41–43, 44f,
45–47t, 48f, 49f, 63,
584–585t
sectoral shares, 11
share of world GDP, 6
shares of global agricultural
trade, 604–605t
shares of global
consumption and
production of agricultural
products, 602–603t
structural patterns and
trends, 11
summary of NRA data,
599–601t
trade flows, 8, 11, 16t
value shares of agricultural
production, 586–591t
value shares of regional
agricultural production,
596–598t
See also Economic growth
Effective rate of assistance,
17–18
Egypt, Arab Republic of, 5
agricultural NRAs, 79–82,
547–548t
calculation of rates of
assistance, 79, 82
consumer tax equivalents, 82
crop-specific policies, 87–91
current policy reform
objectives, 72, 73–74
economic development,
74–76, 77
employment patters, 73
exchange rate policies and
outcomes, 84–85
food subsidies, 78–79, 85, 86,
87, 89–90, 92–93, 94t, 95
future challenges and opportunities, 96
historical evolution of
agricultural and economic
policy, 71–74, 76–79, 81,
85–87
income distribution, 72, 76
input subsidies and
distortions, 79, 91
land policy, 92
legacy of past
development, 72
609
nationalization experience,
72, 74
nonagricultural subsidies, 85
obstacles to economic
reforms, 72
petroleum economy,
75–76, 77
population patterns, 74
poverty patterns, 95
privatization movement, 77
repatriated earnings, 75
RRAs, 82–85
rural areas, 93–95
structure of agricultural
sector, 72–73, 74–75
trade bias index, 84
trade flows, 72, 75–76, 78
transition to marketoriented economy, 87
wages, 95
water use and management,
91–92
See also Economies of Africa
Employment
agriculture’s share, 13t
Egypt, 73, 77–78
farm population of Africa, 6
Madagascar, 101, 103
Nigeria, 443
patterns and trends in Africa,
3, 11, 13t
South Africa, 151
Uganda, 332
See also Labor markets
Eritrea, 233
Ethiopia
agricultural NRAs,
239–243, 549t
agricultural taxation,
245–246
calculation of rates of
assistance, 237–238
civil unrest in, 232–233
data sources, 238
economic growth, 234–235
Eritrea and, 233
evolution of economic and
agricultural policies,
231–234, 248–249
exchange rate policies,
244–245
food aid, 236, 237–238,
242–243
future prospects, 249
input subsidies and
distortions, 240, 247–248
land policies, 231, 233,
250 n.8
610
Index
Ethiopia (continued)
macroeconomic policies, 233
poverty and food security,
235–237
public spending in support
of agriculture, 234
RRAs, 243–244, 249
sources of distortions to
agricultural incentives,
244–248, 249
trade flows, 246
trade policies, 243, 246–247
transportation costs, 241
See also Economies of Africa
European Union, 4
Exchange rate
black market modeling, 512
Cameroon, 372–374
Côte d’Ivoire, 389, 395, 396
Egypt, 84–85
Ethiopia, 244–245
flow-on consequences of
trade distortions, 508
Ghana, 414, 418, 419, 420t,
422, 431, 438 n.4
Kenya, 254, 271
modeling methodology and
NRA calculations, 20,
510–513
Mozambique’s RRAs
and, 143
multiple exchange rate
system, 512–513
Nigeria, 447, 453–454
NRA calculation, 520–521,
527–528
real rate changes, 513
Senegal, 475–477
South Africa, 163–164
Sudan, 287, 290, 292–293,
294, 301, 302, 304
Tanzania, 313, 318, 325
Uganda, 335, 338–339,
343, 345
West and Central African
countries, 486, 490
Zambia, 176–177, 183, 193,
194, 199–200
Zimbabwe, 211–212,
214–216
Exports
African shares of global
agricultural production,
604–605t
Cameroon, 369
Côte d’Ivoire, 385, 386,
388–389, 390–391, 393,
397, 399, 401
Egypt, 72, 75–76, 78
Ethiopia, 246
Ghana, 422, 426, 429
Kenya, 256, 273–274
Madagascar, 104, 108–109,
116–117, 118
Nigeria, 441
NRA patterns and, 25–26,
28f, 35
patterns and trends in Africa,
8, 9t, 10t, 11, 16t
product classification for
NRA calculation, 524–526
sectoral shares, 11
Senegal, 465, 468
share of GDP, 8, 10t
South Africa, 150–151
Sudan, 285, 286f, 304
Tanzania, 311, 314
Uganda, 329
West and Central African
countries, 487
Zambia, 176, 194–195
See also Trade policy
F
Fertilizer use and subsidies
Egypt, 91
Ethiopia, 240
Senegal, 468
Tanzania, 310, 313–314
Zambia, 184, 195, 199
Zimbabwe, 223–224
Floraculture
See Horticulture and
floraculture
Food and commodity prices
Cameroon, 372
Côte d’Ivoire, 387, 391–392,
393, 394, 395, 397–398,
399, 400–402, 409
Egypt, 78–79, 85, 86, 87, 88,
89–90, 92–93, 95
Ethiopia, 233, 246–247
food aid effects, 237–238,
242–243, 250 n.20
future challenges and opportunities in Africa, 4–5
Ghana, 424, 426, 427, 429
Kenya, 253–254, 255,
260–261, 270, 274,
275–276
Madagascar, 106–107
Mozambique, 131
Nigeria, 447–448, 455,
459–460
nondistortionary price
wedges, 515–516
NRA calculation, 510
NRA patterns and trends
in Africa, 35
rationale for international
cooperation, 60
Sudan, 292, 293,
302–303
Tanzania, 311, 312, 313
Uganda, 336–337, 340–341,
343, 344–347
West and Central African
cotton, 486, 489, 495,
496, 498–499, 500–502,
504 nn.7–8
Zambia, 187–188,
190–192, 193
Zimbabwe, 210–211, 213,
221, 222–223
See also Consumer tax
equivalents
Food processing, distortions in,
517–518
Foreign aid
to Ethiopia, 236, 237–238,
242–243
to Ghana, 415, 422
to Uganda, 329
Foreign investment
to Egypt, 75
to Ghana, 418
Forestry and tree crops
Cameroon, 367, 379
Côte d’Ivoire, 393–394
Fruits and vegetables
Côte d’Ivoire’s tariff policy,
411 n.12
Kenya’s production and
policies, 266, 273–274
South Africa’s production
and policies, 149–150,
154–155
Uganda’s production and
policies, 333
See also Horticulture and
floraculture
G
General Agreement on
Tariffs and Trade,
60–62, 132
Ghana
agricultural NRAs, 429–433,
550–551t
agricultural policies and
performance, 416, 417,
423, 424–425
calculation of rates of
assistance, 429
Index
cocoa production and
policies, 414, 416, 417,
426–429, 430, 431
colonial period, 415–416
corruption and smuggling,
417, 426, 428, 436
determinants of economic
and agricultural policies,
435–437
economic development and
performance, 413,
415–423
economic recovery program
(1983-92), 417–418
evolution of agricultural
and economic policies,
413–414
exchange rate, 414, 418, 419,
420t, 422, 431, 438 n.4
external debt, 418, 419
foreign aid, 415
future challenges and opportunities, 415, 437–438
migrant remittances,
422–423
political economy, 414,
416–417, 435–436
population growth, 421
population health and
education, 435
poverty in, 413, 422,
423–424, 425
public spending to support
agriculture, 414–415
RRAs, 431–433
sources of distortions to
agricultural incentives, 414
trade flows, 419, 420t, 422,
426, 429
trade policy, 414, 419–421,
426, 431
transport costs, 433–435
See also Economies of Africa
Gross domestic product
African economies, 6, 9t
agriculture’s share, 8, 73, 74,
77–78, 101, 130, 175–176,
176, 185, 234, 256, 289,
307, 308, 309, 334, 423
Cameroon, 369
Côte d’Ivoire, 385, 388
Egypt’s, 74–75, 76, 77
Ethiopia, 234–235, 235t
export share, 8, 10t
Ghana, 413, 417, 422
Kenya, 256
Madagascar, 104
Mozambique, 130
patterns and trends, 5, 9t
Sudan, 289, 290, 293–294
Tanzania, 307, 308–309, 310
Uganda, 330, 332, 333, 334
Zambia, 175, 176,
189, 196
See also Income/GDP,
per capita
Groundnut production and
policies
Cameroon, 369
Ghana, 430
Mozambique, 130, 132, 133,
134, 135, 136, 142–143
Nigeria, 449
Senegal, 463, 465–466, 469,
472–473, 477, 480
Sudan, 285
Tanzania, 311, 314, 320
Uganda, 333, 345–346
Zambia, 184
Zimbabwe, 216
Gum arabic, 285,
302–303, 304
H
Hides and skins, 239
Horticulture and floraculture
in Kenya, 257–258, 266, 280
in Zambia, 185
in Zimbabwe, 216
See also Fruits and vegetables
Houphouet-Boigny, Felix,
392, 393
I
Immigrant workers in Côte
d’Ivoire, 387–388, 394, 396
Import-competing products
Egypt, 79
NRA patterns and, 25–26,
28f, 35
product classification for
NRA calculation,
524–526
research goals, 4
Sudan, 301
trade bias index
calculation, 519
Uganda, 350
Zambia, 184–185
Zimbabwe, 216
Imports
African shares of global
agricultural production,
604–605t
Cameroon, 369
611
Côte d’Ivoire, 386, 388–389,
401, 402, 403
Egypt, 75, 76, 78
Ghana, 429
Kenya, 259
Madagascar, 103–104, 113
patterns and trends in Africa,
11, 16t
Senegal, 466, 468
South Africa, 150
Sudan, 285, 286f
Tanzania, 316
Uganda, 329
Zambia, 194
See also Trade policy
Income/GDP, per capita
Côte d’Ivoire, 385, 388
Egypt, 72, 76, 94–95
Ethiopia, 235
Ghana, 413, 416, 417, 421
Kenya, 253, 254, 256–257
Madagascar, 107
Nigeria, 442
patterns and trends in
Africa, 8
political economy of rates
of assistance, 43
rates of assistance and,
43, 50f
Sudan, 305 n.5
Uganda, 329, 331
Indian Ocean Commission, 109
Industrial sector
Ghana, 438
indirect agricultural
assistance through
assistance to,
520, 529
Kenya, 256
Madagascar, 118–119
Nigeria, 443, 454
Input subsidies and
distortions
Benin, 493
calculation, 18, 523
Cameroon, 362, 366
Egypt, 91–92
Ethiopia, 240, 247–248
Mozambique, 133
Nigeria, 457
NRA modeling
methodology,
514–515
Uganda, 339–340
Zambia, 177
Zimbabwe, 223–224
See also Fertilizer use and
subsidies
612
Index
International institutions and
multilateral agreements
future of trade negotiations, 4
Madagascar’s
participation, 109
Mozambique’s participation, 132
potential benefits for African
economies, 62
research goals, 4
spillover effects, 60–62
Zambia’s policies and,
190–191, 192–193, 196
See also International
Monetary Fund; World
Bank; World Trade
Organization
International Monetary Fund
Ethiopia and, 233
Ghana and, 417, 436
Nigeria and, 443
Sudan and, 294
Uganda and, 330, 332, 335
West and Central African
countries and, 490
Zambia and, 190, 191, 193
K
Kaunda, Kenneth, 189, 193
Kenya
agricultural NRAs, 266–274,
552–553t
calculation of rates of
assistance, 261–263
colonial history, 260–261
corruption in
governance, 279
data sources, 259, 262–265
domestic marketing
problems, 254
economic performance,
253–264
evolution of agricultural
policies and outcomes,
254, 255–259
future prospects, 255,
279–280, 280
land policies, 260, 261
macroeconomic and
exchange rate policies,
254, 271
nonagricultural sectors, 256
per capita income, 256–257
population growth, 257
poverty, 254
regulatory environment, 279
RRAs, 263, 266
sources of distortions to
agricultural incentives,
255, 274–279
structure of agricultural
sector, 257–259, 262
trade flows, 11, 256, 259,
273–274
trade policy, 278
See also Economies of Africa
L
Labor markets
Côte d’Ivoire immigrant
workers, 387–388, 394, 396
Egypt, 74
South African
regulation, 160
See also Employment
Land ownership
Egypt, 92
Ethiopia, 231, 233, 250 n.8
Kenya, 260, 261
Madagascar, 106
Mozambique, 129
South Africa, 159
Sudan, 287–288
Uganda, 333
Zimbabwe, 205–207,
208–209, 210, 221,
224–225
Latin America, rates of
assistance in, 43, 49f
Livestock production
and policies
Egypt, 82, 91
Madagascar, 103, 108–109,
123 n.4
Nigeria, 443
South Africa, 149,
153–154
Sudan, 285, 290, 303
Tanzania, 317
Uganda, 333
Zimbabwe, 210
M
Macroeconomic policy
Ethiopia, 233
Madagascar, 104
significance of African
experience, 5
South Africa, 156–157
Sudan, 287
Zambia, 183–184, 192–193,
199–200
Zimbabwe, 206
See also Exchange rate
Madagascar
agricultural NRAs,
112–118, 554t
agricultural sector
performance, 101,
105, 113
calculation of rates of
assistance, 111
employment patterns,
101, 103
evolution of agricultural and
economic policies,
101–109, 121–122
future challenges and
opportunities, 105,
122–123
nonagricultural economic
sectors, 103, 118–119
political economy, 104–105
population patterns, 101, 103
poverty patterns, 101,
110–111
RRAs, 119–121
structure of agricultural
sector, 103, 108–109,
113, 115
trade flows, 11, 103–104,
108–109, 113, 116,
117, 118
trade policy, 109–110, 116,
117, 118–119
See also Economies of Africa
Maize production and
policies
Côte d’Ivoire, 387, 402
Egypt, 73, 78, 79–81, 82, 89
Ethiopia, 247
Ghana, 424, 430
Kenya, 255, 259, 260–261,
265, 270, 271, 275
Madagascar, 108, 115–116
Mozambique, 130, 132, 133,
135, 136, 141
Nigeria, 449
South Africa, 149, 150,
152–153, 166
Tanzania, 308, 310, 321
Uganda, 333, 345–346
Zambia, 178–179, 184,
187–188, 190–191, 195,
197, 198
Zimbabwe, 209–211,
213, 216, 219,
222–223, 225
Mali, 489, 492, 497–498, 555t.
See also Economies of
Africa; West and
Central Africa
Index
Mengistu Haile Meriam, 233
Milk and dairy products
and policies
Egypt, 82, 91
Sudan, 301
Millennium Development
Goals, 4–5
Millet production and policies
Nigeria, 449
Senegal, 463, 466, 469,
474, 480
Sudan, 301–302
Uganda, 333
Mozambique
agricultural data sources,
136–137
agricultural NRAs, 137–143,
556–557t
calculation of rates of
assistance, 134–137
colonial era, 128–129
evolution of agricultural and
economic policies, 127,
131–134, 143–144
exchange rate effects on
RRAs, 143
future prospects, 144
RRAs, 143
sociopolitical unrest, 127
structure and development
of agricultural sector,
127–131, 135–136
trade policies, 132
See also Economies of Africa
Mugabe, Robert, 206, 225
Museveni, Yoweri, 329
Mwanawasa, Levy, 196–197
N
Nasser, Gamal Abdel, 72
Nationalization
Egypt’s economic
development, 72, 74
Madagascar’s economic
development, 106
Uganda’s economic
development, 334
Zambian economic
development, 190
Nigeria
agricultural NRAs, 449,
558–559t
calculation of rates of
assistance, 447–448
causes of poor economic
performance, 441
colonial period, 444–445
credit system, 457–458
employment patterns, 443
evolution of economic
policies and performance,
442–443
exchange rate, 447, 453–454
future prospects, 459–460
input subsidies, 457
manufacturing and service
sectors, 443, 454
petroleum economy,
441, 443
population, 441
poverty, 441–442, 459
public spending in support
to agriculture, 456–458
recent reform efforts, 458
RRAs, 449–451
sources of distortions to
agricultural incentives,
442, 453–458
structure and performance
of agricultural sector,
443–447, 448
trade flows, 441, 446
trade policy, 446, 454–455,
456, 458–460
See also Economies of Africa
Nkrumah, Kwame, 415–416
Nominal rates of
assistance (NRAs)
application, 13–15
Benin, 541t
Burkina Faso, 542t
calculation, 15–19, 79, 111,
134–137, 162, 179–181,
207, 211–213, 237–238,
261–263, 295–296,
317–318, 336–340, 351,
353–354, 361–362,
370–374, 403–404, 429,
447–448, 471–477,
498–502, 509–515,
521–526
Cameroon, 370–379,
543–544t
Chad, 545t
commodity coverage, 18,
522–523
commodity differences, 21,
25–26f, 27t, 35
comparative advantage
correlations, 43, 51f
consumer tax equivalents
and, 11–13, 53, 510
Côte d’Ivoire, 403–404,
406, 546t
data sources, 521
definition, 11, 539
613
dispersion, 19, 21, 24t, 63
Egypt, 79–82, 547–548t
Ethiopia, 239–243, 549t
food processing distortions
and, 517–518
general equilibrium
modeling, 531 n.3,
533 n.15
Ghana, 429–433, 550–551t
information requirements
for calculation of, 527
international comparison,
43, 49f, 63
Kenya, 261–274, 552–553t
Madagascar, 112–118, 554t
Mali, 555t
modeling exchange rate
effects, 510–513, 527–528
Mozambique, 137–143,
556–557t
Nigeria, 447–449, 558–559t
nonagricultural, calculation
of, 520–521
noncovered farm products,
18, 528
nondistortionary price
wedges and, 515–517
non-product-specific
assistance, 528–529
OECD measures and, 15, 17,
18, 169, 531 n.1
pass-through effects, 526
patterns and trends in Africa,
21–41, 63, 576–583t
per capita income correlations, 43, 50f, 52t
regional aggregations, 18–19
regional comparison, 43
Senegal, 471–480, 564t
South Africa, 163–166,
560–563t
Sudan, 295–296, 297t, 298,
565–566t
summary of data for African
countries, 599–601t
Tanzania, 317–321, 567–568t
Togo, 569t
trade bias index
calculation, 519
trade cost modeling,
523–524, 532 nn.10–12
Uganda, 336–350, 570–571t
U.S. dollar equivalents, 20,
529–530, 592–595t
weighted averages, 18–19, 21,
518–519
West and Central African
agriculture, 498–502
614
Index
Nominal rates of assistance
(Continued)
Zambia, 181f, 182t, 184–185,
198, 572–573t
Zimbabwe, 207, 574–575t
See also Distortions,
generally; Relative rates of
assistance (RRAs)
O
Obote, Milton, 331–332
OECD. See Organisation for
Economic Co-Operation
and Development
Oils, edible
Egypt’s production and
policies, 93
Ethiopia’s production and
policies, 246
Mozambique’s production
and policies, 130–131
Nigeria’s production and
policies, 449
Sudan’s production and
policies, 285, 302
Zambia’s production and
policies, 184
Zimbabwe’s production and
policies, 216
Organisation for Economic
Co-Operation and
Development (OECD), 15,
17, 18, 169, 531 n.1
P
Pass-through computation, 526
Pepper, 117
Policy interventions and
outcomes
antiagricultural bias in
Africa, 3, 6
Cameroon, 362–369, 379
case studies, 64–65
Côte d’Ivoire, 386–388,
392–397, 404–409
Egypt, 71–74, 76–79, 81, 85–87
Ethiopia, 231–234, 248–249
evolution in Africa, 6
future prospects for African
economies, 63–64, 96,
122–123
Ghana, 413–414, 424–429, 437
lessons from experiences of
African economies, 62–63,
121–122, 143–144,
279–280, 354–355
Madagascar, 101–109,
111–112, 121–122
Mozambique, 127
overshooting, 63–64, 81
patterns and trends in
African economies, 21,
35, 36t, 62
research goals, 4, 6–8
significance of African
experience, 5
South Africa, 151–161, 162,
170–171
Sudan, 287–295, 300–303
Tanzania, 311–317
Uganda, 330, 334–336,
353–355
West and Central Africa,
491–498
Zambia, 175–179, 189–198
Zimbabwe, 207–211,
218–225
See also Distortions,
generally; Exchange rate;
Macroeconomic policy;
Nominal rates of
assistance (NRAs);
Relative rates of assistance
(RRAs); Trade policy
Political economy
Côte d’Ivoire, 387, 388, 392,
396–397, 410
Ethiopia’s modern history,
231–232
food subsidies in Egypt,
92, 93
Ghana, 414, 416–417,
435–436
international comparison
of rates of assistance, 43
Madagascar, 104–105
research goals, 4
Senegal, 464, 468, 482
Sudan, 292
Zambia, 190–191, 193
Zimbabwe’s future
prospects, 225
Population patterns and trends
agricultural population, 6
Kenya, 257
Madagascar, 101, 103
Sudan, 284
Uganda, 329
Port facilities
Ghana, 421
Madagascar, 115
Potatos, 103
Poverty
in Africa, 3, 5, 6, 8t
in Cameroon, 361
in Egypt, 95
in Ethiopia, 235–237
in Ghana, 413, 422,
423–424, 425
in Kenya, 254
in Madagascar, 101, 110–111
in Nigeria, 441–442, 459
prospects for reduction of, in
Africa, 5
recommendations for
economic policies of
African countries, 64
in rural areas, 6, 110–111
in Sudan, 284
in Tanzania, 310, 325
in Uganda, 335–336, 355
in Zambia, 177–178, 189
Privatization
Côte d’Ivoire, 396
Egypt’s economic
development, 77
West and Central African
cotton industry, 487
Producer support estimates, 15
Productivity, agricultural
Cameroon, 380
Madagascar, 105, 113
Pyrethrum, 320
Q
Quality of product, 516–517
R
Ramanantsoa, Gabriel, 106
Ratsiraka, Didier, 106,
107–108, 121
Ravalomanana, Marc, 123
Rawlings, Jerry, 416–417, 436
Regional Integration
Facilitation Forum, 109
Regional trade associations and
agreements
Madagascar’s participation, 109
South Africa’s participation, 161
Relative rates of assistance
(RRAs)
calculation, 19–20, 82, 263,
351, 521, 540
Cameroon, 376–378
Côte d’Ivoire, 404
Egypt, 82–85
Ethiopia, 243–244, 249
Ghana, 431–433
international comparison, 63
Kenya, 263, 266
Madagascar, 119–121
Mozambique, 143
Index
Nigeria, 449–451
patterns and trends in
African economies,
29–30t, 41–43, 44f, 45–47t,
48f, 49f, 63, 584–585t
per capita income correlations, 43, 50f
Senegal, 480, 481t, 482f
significance of, in distortion
research, 508–509
South Africa, 166–167, 168t
Sudan, 296–298, 299t
Tanzania, 322, 323t, 324f
trade bias index and,
60, 61f
Uganda, 351–353
Zambia, 185, 186t, 187f
Zimbabwe, 218
Remittances, 422–423
Research and development
in Cameroon, 366–367
in Kenya, 255
West and Central African
cotton industry, 490
Rice production and policies
Côte d’Ivoire, 386, 387, 395,
397, 401–403, 404, 406
Egypt, 73, 78, 79–81, 88–89,
91–92
Ghana, 424, 430
Madagascar, 103, 107–108,
113–115
Mozambique, 132, 133, 135,
136, 142
Nigeria, 449
Senegal, 463, 466–468,
473–474, 480
Tanzania, 308, 310, 321
Uganda, 346–347
Zambia, 181–183
Rural areas
Cameroon, 362
Côte d’Ivoire, 390
Egyptian population, 74
Egypt’s policies and
outcomes in, 93–95
Egypt’s political
economy, 86
Kenya, 254
Madagascar, 110–111
poverty patterns and trends,
6, 110–111
recommendations for
economic policies of
African countries, 64
Sudan, 284
Tanzania, 310
Zambia, 177–178
S
Selassie, Haile, 231–233
Self-sufficiency, agricultural
patterns and trends in Africa,
11, 17t
policy biases in African
economies, 3
Senegal, 466
Senegal
agricultural NRAs,
477–480, 564t
calculation of distortions to
agricultural incentives,
471–477
colonial period, 463,
464–465, 468–469
economic structure and
development, 463–469
evolution of agricultural
policy formulation,
470–471
food balance sheet, 466, 467t
future challenges and
opportunities, 482–483
input distortions, 472
land use patterns, 466
macroeconomic and
exchange rate distortions,
475–477
political economy, 464,
468, 482
RRAs, 480, 481t, 482f
structure and performance
of agricultural sector, 463,
465–468, 469, 482
trade flows, 11, 465–466, 468
urbanization, 468
See also Economies of Africa
Service economy
indirect agricultural
assistance through
assistance to, 520, 529
Kenya, 256
Nigeria, 443
Size of farms
Cameroon’s small-holder
production, 363, 364
Côte d’Ivoire, 390
Kenyan small-holder
production, 257, 269
Socialist economies
Egypt’s experience, 72, 74
Ethiopia’s experience, 233
Madagascar’s experience,
104, 106–107, 111
Sorghum production and
policies
Cameroon, 369
615
Nigeria, 449
Sudan, 301
Zimbabwe, 216
South Africa
agricultural NRAs, 163–166,
560–563t
calculation of rates of
assistance, 162
consumer tax
equivalents, 170
employment patterns, 151
evolution of agricultural
policies, 147–148,
151–161, 162, 170–171
exchange rate, 163–164
future challenges and
opportunities, 170, 171
land reform, 159
macroeconomic policy,
156–157
RRAs, 166–167, 168t
sociopolitical unrest, 155
state spending for agriculture
support, 161
strategies to reduce
distortions, 169–170
structure and performance
of agricultural sector,
148–151
trade flows, 150–151
trade policies, 152–153, 158,
160–161, 164
See also Economies of Africa
Southern Africa, 5. See also
Economies of Africa;
specific country
Southern Africa Customs
Union, 161
Southern Africa Development
Community, 109, 161
Spices, 131
Sub-Saharan Africa
economic performance, 5
employment patterns, 3
farm product output, 370f
poverty patterns and
trends, 5, 6
trade flows, 5
Sudan
agricultural NRAs, 295–296,
297t, 298, 565–566t
calculation of rates of
assistance, 295–296
colonial period, 287–289
credit system, 291
economic growth, 284–285,
290, 291–292, 293–294,
305 n.5
616
Index
Sudan (continued)
evolution of agricultural and
economic policies,
283–284, 287–295
future prospects, 295
irrigation system and
policies, 288, 289
macroeconomic and
exchange rate policies,
287, 290, 292–293, 294,
295, 301, 302, 304
National Economic Salvation
Program, 292–293
political economy and civil
unrest, 292
population growth, 284
poverty, 284
public spending to support
agriculture, 285
regulatory environment, 291
RRAs, 296–298, 299t
sources of distortions to
agricultural incentives,
300–303
strategies for improving
economic performance,
303–305
structure of agricultural
sector, 283, 284, 285,
289–290
trade flows, 11, 285, 286f
trade policy, 289
See also Economies of Africa
Sugar production and policies
Egypt, 79–81, 89–90, 93
Kenya, 265, 271–273,
277, 280
Madagascar, 103, 118
Mozambique, 132, 133–134,
135, 136, 143
South Africa, 149, 164
Sudan, 290
Tanzania, 321
Sunflower seeds, 213
Symmetry theorem, 19,
508–509, 519
T
Tanzania
agricultural NRAs, 318–321,
567–568t
calculation of rates of
assistance, 317–318
economic performance,
308–309, 310, 315
evolution of agricultural
policy, 307, 311–317
exchange rate, 313, 318, 325
future challenges and opportunities, 308, 309, 325–326
input subsidies and
distortions, 310, 313–314
poverty in, 310, 325
RRAs, 322, 323t, 324f
sources of distortions to
agricultural incentives,
308, 324–325
structure and performance
of agricultural sector, 307,
308–311
trade flows, 311, 314, 316
trade policy, 316–317
See also Economies of Africa
Tax and tariff policies
Cameroon, 366, 374,
376–378, 379
Côte d’Ivoire, 386, 388, 389,
394–395, 396, 397–398,
399, 400, 402, 406–409,
411 n.12
data sources, 4
Egypt, 76, 85, 96
Ethiopia, 243, 245–246
Ghana, 419–421
international spillovers, 60–62
Kenya, 278
lessons from experiences of
African economies, 62–63
Madagascar, 107, 108,
109–110, 116, 117
Mozambique, 132
Nigeria, 446, 447, 454–455,
456, 458, 459–460
NRA calculation, 509–510
NRA patterns and trends in
Africa and, 35
patterns in trends in African
economies, 21
Senegal, 477–480
South Africa, 160–161
Sudan, 288–289, 293, 303,
305 n.6
Tanzania, 313, 316–317
Uganda, 330, 343, 345,
350, 355
West and Central African
countries, 487, 502
Zambia, 194
Tea production and policies
Kenya, 255, 257,
268–269, 276
Mozambique, 133
Tanzania, 309, 311, 320
Uganda, 333, 349–350
Tobacco production and
policies
Mozambique, 131, 133, 135,
136, 142
Tanzania, 320
Uganda, 333, 349
Zambia, 184
Zimbabwe, 216, 219
Togo, 492, 498, 569t. See also
Economies of Africa; West
and Central Africa
Trade bias index
calculation, 19, 519
Egypt, 84
Nigeria, 451
patterns and trends in
African economies,
25–26, 31–34t
relative rates of assistance
and, 60, 61f
significance of, in distortion
research, 519
Trade policy
antitrade bias in Africa, 3, 6
Cameroon, 366
Côte d’Ivoire, 386, 389, 393,
394–395, 397–398, 399,
402–403
Egypt, 72, 77, 85
Ethiopia, 243, 246–247
future challenges and
opportunities, 4
Ghana, 414, 419–421,
426, 431
international spillovers,
60–62
Kenya, 278
lessons from African
experience, 63
Madagascar, 109–110,
118–119
Mozambique, 132
Nigeria, 446, 454–455, 456,
458–460
patterns and trends in
African economies, 63
South Africa, 152–153, 158,
160–161, 164
Sudan, 289, 293
Tanzania, 316–317
Uganda, 334, 357 n.13
Zambia, 194
See also Tax and tariff
policies; Trade bias index
Transportation costs
Ethiopia, 241
Ghana, 433–435
Kenya, 271
Tanzania, 325
Uganda, 329, 339–340
Index
West and Central African
cotton, 499
Transportation infrastructure
Cameroon, 380
Madagascar, 113
Senegal, 469
Sudan, 285
Zambia, 199
See also Port facilities
Tsirinana, Philibert, 121
U
Uganda
agricultural NRAs, 340–350,
570–571t
calculation of rates of
assistance, 330, 336–340,
351, 353–354
credit system, 339
economic performance, 329,
330, 331–332, 334
evolution of economic and
agricultural policies, 330,
334–336
food access and
consumption patterns,
333–334
future challenges and opportunities, 354–356
input distortions, 339–340
macroeconomic and
exchange rate policies,
335–336, 338–339,
343, 345
marketing costs, 337–338
national security, 329
nonagricultural sectors, 333,
351–353
population growth, 329
poverty, 335–336, 355
price-setting behavior,
336–337
RRAs, 351–353
sources of distortions to
agricultural incentives, 330
structure and performance
of agricultural sector,
329–330, 332–333, 334,
337, 354–355
subsistence agriculture, 333
trade flows, 329
trade policy, 334, 350,
357 n.13
See also Economies
of Africa
United States
dollar equivalents of CTEs,
20, 57–59t, 530
dollar equivalents of NRAs,
20, 529–530, 592–595t
dollar equivalents of
subsidies to farmers in
Africa, 35, 37–38t, 39f,
40–41t
Uruguay Round, 60, 381
V
Value added taxation
Côte d’Ivoire, 389
Ghana, 419
Kenya, 278
Mozambique, 132, 139–141
Zambia, 185
Vanilla, 103, 108–109,
116–117
W
Water use and irrigation
Egypt, 91–92
South Africa, 160
Sudan, 284, 285, 288, 289
West and Central Africa, 5
agricultural NRAs, 502
agricultural reform strategies
and outcomes, 491–498
calculation of distortions to
agricultural economy,
498–502
colonial legacy, 485
evolution of agricultural
policy, 486–487, 502
exchange rate effects,
486, 490
future prospects, 494, 495,
496–497
global competitiveness,
489–490
privatization movement, 487
resistance to reform, 490–491
sources of distortions to
agricultural incentives, 487
structure and performance
of agricultural sector,
485–486, 487–490,
492–493, 494, 495–496,
497, 498, 503 nn.3–6
trade flows, 487
transportation costs, 502
See also Benin; Burkina Faso;
Chad; Mali; Togo
Western Africa, 5. See also
specific country
Wheat production and
policies
Côte d’Ivoire, 386, 387, 401
Egypt, 79–81, 86, 90, 93
617
Kenya, 255, 259, 260,
270–271, 275, 276
Sudan, 290, 301
Tanzania, 310
Zambia, 181–183, 184
Zimbabwe, 213, 216
World Bank
Ethiopia and, 233
Ghana and, 417, 424,
425, 436
Nigeria and, 443
Senegal and, 463, 471
Sudan and, 292
Uganda and, 330, 332, 335
in West and Central African
countries, 490, 493, 494
Zambia and, 190, 191, 193
World Trade Organization, 4,
60–62, 109, 132, 171, 436
Y
Yam production and policies
Madagascar, 108, 115–116
Nigeria, 444
Z
Zambia
agricultural NRAs, 181f,
182t, 184–185, 198,
572–573t
Agricultural Sector
Investment Program, 196
calculation of rates of
assistance, 179–181
colonial era, 175, 178–179
consumer tax equivalents,
187–189
copper industry, 175, 176,
178, 189, 190, 194,
199, 200
economic growth, 176,
189–190, 196
evolution of agricultural and
economic policies,
175–179
future challenges and opportunities, 198–200
input subsidies and
distortions, 177,
195–196, 199
macroeconomic and
exchange rate policies,
176–177, 183–184,
192–193, 194, 199–200
natural resources, 175
political economy,
190–191, 193
poverty, 177–178, 189
618
Index
Zambia (continued)
relationship with Bretton
Woods organizations,
190–191, 192–193
RRAs, 185, 186t, 187f
sources of distortion to
agricultural incentives,
176, 181–184, 189–198
trade flows and policies, 176,
194–195
See also Economies of Africa
Zimbabwe
agricultural NRAs, 213–218,
574–575t
calculation of rates of
assistance, 207, 211–213
colonial era, 205, 206
consumer tax
equivalents, 212
evolution of agricultural
sector and policies,
208–211
future challenges and
opportunities, 225–226
historical background,
205–206, 208
input subsidies and
distortions, 223–224
land ownership, 205–207,
208–209, 210, 221,
224–225
macroeconomic and
exchange rate policy, 206,
211–212, 214–216
political economy, 225
RRAs, 218
sources of distortions to
agricultural incentives,
207–208, 214–216,
218–225
See also Economies
of Africa
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The vast majority of the world’s poorest households depend on farming for
their livelihoods. During the 1960s and 1970s, most developing countries
imposed pro-urban and anti-agricultural policies, while many high-income
countries restricted agricultural imports and subsidized their farmers.
Both sets of policies inhibited economic growth and poverty alleviation in
developing countries. Although progress has been made over the past two
decades to reduce those policy biases, many trade- and welfare-reducing
price distortions remain between agriculture and other sectors and within
the agricultural sector of both rich and poor countries.
Comprehensive empirical studies of the disarray in world agricultural
markets appeared approximately 20 years ago. Since then, the Organisation
for Economic Co-operation and Development has provided estimates each
year of market distortions in high-income countries, but there have been
no comparable estimates for the world’s developing countries. This volume
is the fourth in a series (other volumes cover Asia, Europe’s transition
economies, and Latin America and the Caribbean) that not only fills that
void for recent years but also extends the estimates in a consistent and
comparable way back in time—and provides analytical narratives for scores
of countries that shed light on the evolving nature and extent of policy
interventions over the past half-century.
Distortions to Agricultural Incentives in Africa provides an overview of the
evolution of distortions to agricultural incentives caused by price and trade
policies in the Arab Republic of Egypt plus 20 countries that account for
about 90 percent of Sub-Saharan Africa’s population, farm households,
agricultural output, and overall GDP. Sectoral, trade, and exchange rate
policies in the region have changed greatly since the 1950s, and there
have been substantial reforms since the 1980s. Nonetheless, numerous
price distortions in this region remain, others have been added in recent
years, and there have also been some policy reversals, such as in Zimbabwe.
The new empirical indicators in these country studies provide a strong
evidence-based foundation for assessing the successes and failures of the
past and for evaluating policy options for the years ahead.
ISBN 978-0-8213-7652-2
SKU 17652