LAND POLICY AND FARM EFFICIENCY: THE LESSONS OF MOLDOVA

》｝《＝〕÷｝ ≠｝÷ 【〔 〔｛｝』÷ ｝『〕 〔 The Hebrew University of Jerusalem ≠｝ 《×］ 〔《〉《〉 ÷×］「《 ［〉÷「〔 《〔『「〕 ≠｝ 《×］ 〔《〉《〉《 〔×《］「〔 The Center for Agricultural Economic Research The Department of Agricultural Economics and Management Discussion Paper No. 4.08 Land Policy and Farm Efficiency: The Lessons of Moldova by Dragos Cimpoies & Zvi Lerman Papers by members of the Department can be found in their home sites: ‫י‬ ‫נ‬ ‫ח‬ : ‫ח י‬ ‫י‬ ‫י י‬ http://departments.agri.huji.ac.il/economics/indexe.html P.O. Box 12, Rehovot 76100 76100 ‫ ח‬,12 . . 1 LAND POLICY AND FARM EFFICIENCY: THE LESSONS OF MOLDOVA* DRAGOŞ CIMPOIEކ; ZVI LERMAN** 1 INTRODUCTION Since 1991, Moldova has carried out a wide range of radical reforms affecting its social and economic system. The reforms have been aimed at the creation of political, legal and economic foundations for a market economy based predominantly on the private sector. Within this general framework, agrarian reform proceeded in the following main directions: - Mass privatization of agricultural land, culminating in physical distribution of land plots and issue of land titles to individual owners; - Transformation of traditional collective and state farms into new forms of market-oriented organizations. Over 1 million residents became landowners as a result of this process, which ended between 1998 and 2000. Many of them used their privately owned land to establish independent family farms, while others entrusted their land to managers of newly created corporate farms. As of today, 50% of agricultural land in Moldova is used by individual producers. This is in stark contrast to the pre-reform situation, when individuals cultivated only 2% of agricultural land. Meanwhile, the progress in land privatization has not led to the individualization of agriculture. Half of agricultural land in Moldova is farmed by the corporate sector. Although this is a positive result compared with other CIS countries, such as Russia and Ukraine, it is far from satisfactory when compared with market economies, where the share of corporate farms in agricultural land is much smaller. One of the main features of Moldovan agriculture is its structural duality, expressed by the existence of a relatively small number of large corporate farms at one extreme and a large number of small and very small family farms at the other. There are virtually no “medium-sized” family farms, which constitute the main farm structure in market economies. The relationship between organizational form and farm size is not always the same. Usually, family farms are small, but some of * Paper presented at the 104th joint EAAE-IAAE Seminar on Agricultural Economics and Transition: What was Expected, What We Observed, the Lessons Learned, Corvinus University, Budapest, Hungary, September 6-8, 2007. † Department of Management, The State Agricultural University of Moldova, MD 2049 Chişinău, Republic of Moldova. Email: dcimpoies@uasm.md ** Department of Agricultural Economics and Management, The Hebrew University, Rehovot 76100, Israel. Email: lerman@agri.huji.ac.il 2 them fall in the category of large farms. A similar picture is observed with corporate farms, which are typically large, but not all of them. Therefore, the structural duality in agriculture in transition will be analyzed in two dimensions: the organizational form dimension and the farm size dimension. 2 INDIVIDUAL VERSUS CORPORATE FARMS The emergence of two well-defined categories of organizational forms as a result of the post-socialist land and farm structure reforms has triggered an ongoing debate among policy makers and economists concerning the efficiency and performance advantages of corporate farms versus individual farms in transition countries. The traditional socialist thinking believed in economies of scale and thus gave preference to large corporate farms. The Western market-oriented thinking attaches more importance to individual incentives and thus emphasizes the advantages of smaller family farms. GORTON and DAVIDOVA (2004) note that, contrary to prior expectations, there is no clear-cut empirical evidence in transition economies that family farms are more efficient than corporate farms in all farming activities. While significant differences have been found in favor of family farms against the average corporate farm, the best corporate farms still tend to perform as well as the best family farms. Yet these findings clearly support the previous conclusion (LERMAN ET AL., 2004) that, contrary to the economies-of-scale school of thought, large corporate farms do not have a significant performance advantage over individual farms. We use national statistics and survey data to examine the comparative performance of individual and corporate farms in Moldova. Figure 1: Increasing role of the individual sector Gross Agricultural Product Agricultural land 100% 100% 90% Corporate Farms 80% 80% 70% 60% Corporate Farms 60% 50% 40% 40% Individual Farms 30% 20% 20% Individual Farms 10% Source: 20 06 20 04 20 02 20 00 19 98 19 96 19 94 19 92 19 90 20 06 20 04 20 02 20 00 19 98 19 96 19 94 0% 19 92 19 90 0% Statistical Yearbooks of Moldova, various years; State Cadastre, end of year data. In the process of reform agricultural land shifted from corporate to individual farms (Figure 1, right-hand panel). The shift of agricultural land from corporate to individual farms has led to significant changes in the production structure of 3 Moldovan agriculture: the output of the corporate farm sector decreased, while the output of the individual sector shows a steady growth (Figure 1, left-hand panel). At the beginning of agricultural reforms in the early 1990s, the individual sector was producing 20% of agricultural output on less than 10% of agricultural land; in 2003 individual farms produce three-quarters of agricultural output on half the agricultural land. The discrepant shares of the two farm sectors in land and output clearly show that the individual farms use their land more productively than the corporate farms. This phenomenon has persisted since 1990, as the share of individual output has always been greater than the share of land in individual tenure. While the partial productivities of land and labour decreased over time in both corporate and individual farms (Figure 2), the land productivity of individual farms is statistically significantly higher than that of corporate farms over the entire transition period 1990-2003. The difference in labor productivity, on the other hand, is not statistically significant, although the mean for the entire period 1990-2003 is observed to be higher for individual farms. In other transition countries we also observe that the productivity of land is higher for individual farms, but the productivity of labor is actually higher for corporate farms. For Moldova, the two partial productivity measures for land and labour do not give a consistent picture: while land productivity is definitely higher for individual farms, the results for labor productivity are ambiguous. To resolve the ambiguity, we have to calculate a measure of Total Factor Productivity (TFP). Figure 2: 20 Agriculture land and labour productivity for corporate and individual farms '000 lei/ha (2000 prices) 35 '000 lei/worker (2000 prices) 30 15 25 Corporate Individual 10 20 Corporate Individual 15 10 5 5 0 1990 1992 1994 1996 1998 2000 2002 0 1990 a) Agricultural land productivity Source: 1992 1994 1996 1998 2000 2002 b) Labour productivity Own calculations based on national statistics. In the absence of market prices for valuing the cost of inputs (such as the price of land), TFP is usually determined by estimating a production function and then using the estimated input coefficients as the weights to calculate the value of the bundle of inputs. Unfortunately, the time series of national statistical data for 19902003 was too short to estimate even a simple production function based on two inputs only – land (as a proxy for capital) and labour. We accordingly constructed a qualitative picture of TFP changes over time by assuming a conventional Cobb- 4 Douglas production function with stylized factor shares of 0.7 for land and 0.3 for labour (these are the factor shares that we consistently obtained in production functions estimated using various farm surveys in Moldova). Figure 3 presents the TFP results calculated with these land and labour weights using the full time series of land, labor, and output data from national statistics. The TFP for individual farms is higher than for corporate farms over the entire period 1990-2003. The respective means for 1990-2003 are 11.5 for individual farms and 4.4 for corporate farms (the difference is statistically significant). Figure 3: Total factor productivity for individual and corporate farms 1990-2003 25 lei output per unit aggregated inputs 20 15 Individual Corporate 10 5 0 1990 1992 1994 1996 1998 2000 2002 Notes: Inputs from national statistics aggregated using hypothetical factor shares of 0.7 to land and 0.3 to labor. Source: Own calculations. The TFP results in Figure 3 are derived by production-function methodology using national statistics and they reflect Total Factor Productivity in a sectoral perspective. To obtain comparative productivity results on the farm level, we used the data of several farm surveys conducted in Moldova by international organizations. Instead of production-function methodology, we used here production-frontier methodology that calculates the technical efficiency (TE) of farms on a scale between 0 and 1 (with TE score of 1 corresponding to technically efficient farms on the production frontier). Table 1presents the mean TE scores obtained for farms of different types – corporate and individual – using the data of two samples from 2003 surveys in Moldova.‡ While all farms surveyed are relatively inefficient (compared to the efficiency benchmark of TE = 1), individual farms achieve higher TE scores than corporate farms (the difference is statistically significant in both samples). This indicates that the individual farms on average utilize the two inputs (land and labor) more efficiently than the corporate farms: for any given bundle of inputs, they produce on average more than the corporate farms. These results are consistent with the ‡ The TE scores were derived by Stochastic Frontier Analysis (SFA), an econometric production frontier technique that is conceptually close to production function estimation. For details, see COELLI ET AL. (2005). 5 TFP results: individual farms are more productive and more efficient than corporate farms. Table 1: TE scores obtained by Stochastic Frontier Analysis (SFA) Corporate Individual Notes: WB 2003 survey (n = 198) 0.46a (n = 22) 0.64a (n = 176) WB 2003 survey pooled with PFAP 2003 corporate farm survey (n = 719) 0.67b (n = 543) 0.70b (n = 176) a Difference statistically significant at p = 0.10 by parametric and nonparametric tests. Difference statistically significant at p = 0.10 by nonparametric test only. Source: Authors‟ calculations based on DUDWICK ET AL. (2007) for WB 2003 survey; MURAVSCHI, BUCATA (2005) for PFAP 2003 survey. b 3 LARGE VERSUS SMALL FARMS The second dimension of farm-structure duality involves farm sizes – large versus small. The optimum farm size is difficult to define because opinions about the farmers‟ objective function differ and because the same determinants can affect farm size in different ways across different farms or countries (KOESTER 2003). The optimality of farm size for a given country is largely an empirical question (SWINNEN 2006). In general, the optimal farm size is a relative notion that depends on the local conditions, such as the share of rural population and the land endowment. In the absence of a universal optimum, average farm sizes can be meaningfully compared only for countries with similar natural conditions. In this context, an appropriate benchmark for Moldova is provided by the relatively densely populated and land-poor European countries, such as Portugal, Greece, and Italy. These three countries actually have the smallest family farms among the EU-15 – 5-10 hectares, compared with an average farm size of around 20 hectares for EU15 as a group (Eurostat data from EUROPEAN COMMISSION (2005)). The family farms in Portugal, Greece, and Italy are thus not dramatically larger than the average peasant farm in Moldova (2 hectares national average, 4-5 hectares in various surveys), but they are certainly much smaller than the average corporate farm in Moldova. Table 2 presents the size characteristics and the partial productivity measures for small and large farms in three recent surveys in Moldova. While the large farms as a group are substantially larger than the small farms by all measures – output, land, and labour, the partial productivities show a mixed picture:  The partial productivity of land (output per hectare) is higher for small farms.  The partial productivity of labour (output per worker) is lower for small farms.  The number of workers per hectare is much higher in small individual farms than in large corporate farms (the “labour sink” effect of individual farms). 6 The ambiguity in partial productivity measures is resolved by calculating total factor productivity (TFP) from survey data, which contrary to national statistics allow estimation of production functions for the sampled farms. TFP calculations conclusively show decreasing returns to scale: large farms produce less per unit of inputs in the margin than small farms. Table 2: Size characteristics and productivity measures for small and large farms in Moldova: survey data WB 2003 survey Small farms Number of observations Ag land (ha) Workers Ag output („000 lei) Output/ha (lei) Output/worker (lei) TFP Workers/ha PFAP 2003 surveys Large farms Small farms Large farms WB 2000 baseline survey Small Large farms farms 176 22 1,166 521 170 180 4.48 4.51 25.8 6,765 6,857 6,426 1.42 971 332 3,230 2,745 17,135 4,745 0.26 4.02 6.27 25.3 9,535 5,145 7,424 3.25 918 150 2,038 2,085 17,824 3,464 0.19 5.7 1.6 75.4 6,414 55,304 8,420 533 43.7 1,642 3,145 54,393 4,010 Note: All differences between small and large farms are statistically significant at p = 0.1 (except the differences in productivity of labour – output/worker – in the WB 2000 survey). Source: DUDWICK ET AL. (2007) for WB 2003 survey; MURAVSCHI, BUCATA (2005) for PFAP 2003 surveys; LERMAN (2001) for WB 2000 survey. We have shown that in Moldova individual farms are more productive than corporate farms and small farms are more productive than large farms. Typically, individual farms are small while corporate farms are large, and there is a fairly sharp size gap between the farms of two organizational forms (WORLD BANK 2005). It could therefore be argued that the farm size effect observed in our analysis is simply a result of the organizational form effect, or vice versa. To try and disentangle the two effects, we have looked at two homogeneous samples: a sample of corporate farms (without any individual farms) and a sample of peasant farms (without any corporate farms). Table 3: TFP of corporate farms by land size categories in PFAP 2003 survey <500 ha (1) Number of farms Land productivity (output/ha, lei) Labour productivity (output/worker, lei) TFP (lei per unit of aggregated inputs) Source: 238 1,927 18,660 3,162 500-2000 ha (2) 225 2,162 16,580 3,603 Authors‟ calculations from MURAVSCHI, BUCATCA (2005). >2000 ha (3) 58 2,430 19,219 4,167 7 The homogeneous sample of 521 corporate farms from the 2003 PFAP survey (MURAVSCHI, BUCATCA 2005) was grouped into three size categories (Table 3). The productivity of land clearly increases with farm size, whereas the productivity of labour does not. Most importantly for our purposes, total factor productivity calculated by aggregating land and labour with appropriate weights from the production function shows a definite increase with farm size in the homogeneous sample of corporate farms. A similar effect is observed in the homogeneous sample of individual farms. Here family income and family well-being obtained in various surveys are used as a proxy for TFP. The findings of the WB 2000 survey for individual farms conclusively show that family income increases with farm size. As we see from Figure 4 (left-hand panel), a substantial increase in family income is observed for individual farms larger than 10 ha. Also, the findings indicate that the level of commercialization is higher for larger individual farms and, contrary to very small farms, they consume less than what they sell (Figure 4, right-hand panel). Figure 4: 160 Family income and its structure as a function of farm size thousand lei 100% 140 80% 120 100 60% 80 Personal Consumption Farm sales Income 40% 60 40 20% 20 0 Up to 2 2-10 10--100 >100 farm size, ha Source: 0% Up to 1 1-2 2-5 5-10 >10 farm size, ha World Bank Survey, 2000 In a homogeneous sample of peasant farms – excluding the household plots – from the 2005 WB survey (WORLD BANK 2005), the standard of living of rural families was observed to increase with farm size. Among peasant farms, a comfortable standard of living is associated with much larger family farms than lower standards of living. Peasant farmers reporting a comfortable standard of living had 11 hectares on average, compared with less than 5 hectares for farms in the two lower categories – poverty, when family income is not sufficient to buy food, and subsistence, when family income is sufficient to buy food and daily necessities (the difference between farm sizes is statistically significant at p < 0.01). The standard of living of peasant farmers is thus an increasing function of farm size, as is commonly observed in farm surveys in CIS and other transition countries. A different view of the relationship between standard of living and farm size for peasant farmers is presented in Figure 5, which plots the probability of being in one of the three standard-of-living levels as a function of farm size. The probability of being in the highest standard of living (gray curve) increases with farm size, while the probability of being on the lowest “poverty” level (thick black curve), 8 sharply decreases with farm size.§ These results provide support for increasing the average size of the individual farms through land market development and land consolidation policies. Figure 5: Probability of achieving a given standard of living as a function of farm size for peasant farmers 1 probability 0.8 0.6 Poverty Subsistence Comfortable 0.4 0.2 0 0 10 20 30 land use, ha 40 50 Definition of standard of living levels: “poverty” – family income not sufficient to buy food; “subsistence” – family income just sufficient to buy food and daily necessities; “comfortable” – family income sufficient to buy food, daily necessities, and durables. Source: Authors‟ calculations based on WB 2005 survey (WORLD BANK, 2005). Note: These results for corporate and individual farms separately demonstrate that farm performance actually improves with increasing farm size for farms of the same organizational form. The inverse productivity–farm size relationship is observed for mixed samples that include farms of different organizational forms (both individual and corporate). This suggests that the decrease of productivity with farm size is primarily an organizational form effect, and not a farm size effect: individual farms are more productive than corporate farms, and the size effect observed in our analysis appears to be simply a proxy for the organizational form effect. 4 NEGATIVE IMPACTS OF LAND FRAGMENTATION Common wisdom argues that consolidation of small disjointed parcels into contiguous holdings is preferred by farmers and landowners. This kind of consolidation should reduce production costs and improve net income for a farm of given size. Land consolidation that produces larger farms (keeping the number of parcels fixed) is also believed to be beneficial, as it should reduce the ratio of fixed costs per unit of land, allow more efficient use of technology, and ultimately increase productivity and efficiency. These theoretical arguments, however, are difficult to substantiate empirically and world experience does not unanimously support either position. § The probabilities of achieving a given standard of living were obtained in a multinomial logistic regression with the three-level standard of living as the discrete dependent variable and farm size as the continuous covariate. 9 Some evidence that supports the advisability of reducing the number of parcels through land consolidation is provided by a 2003 World Bank survey of household plot operators in Moldova. This survey shows a clear negative relationship between productivity and the number of parcels held by the operator. The partial productivities of land and labor are calculated from the survey data as the value of farm income (including cash revenue from sales of farm products and value of own consumption) per hectare of land and per work day (including family workers and outsiders). The results presented in Figure 6 clearly show that both the productivity of land (farm income per hectare) and the productivity of labor (farm income per work day) decrease as fragmentation (i.e., the number of parcels) increases. The negative relationship between productivity and fragmentation in Figure 6 is statistically significant by all standard measures. lei/ha lei/w ork day 1000 6 Farm income per ha 800 5 700 600 4 500 3 400 300 2 200 1 100 0 Farm income per work day 7 900 0 1 2 3 4 5 6 7 8 9 10 Number of parcels Farm income per ha Figure 6: Farm income per work day Partial productivity measures versus number of parcels for household plots in Moldova Source: 2003 WB survey of household plots This conclusion is supported by the analysis of a 2003 survey of individual farms in Georgia. The Georgian survey also shows that productivity decreases with the increase of fragmentation, controlling for a number of other relevant factors (LERMAN 2005). 5 CONCLUSIONS AND RECOMMENDATIONS Analysis based on national statistics and survey data shows that individual farms are more efficient than corporate farms. This conclusion does not necessarily mean that corporate farms should be eliminated and replaced with family farms. Corporate farms do exist in market economies, which proves that they are able to compete with individual farms. The market economies have achieved an equilibrium farm structure, which includes a mix of individual farms (the dominant majority) and corporate farms (a small minority) determined by resource availability, managerial capacity, and personal preferences of farmers and 10 investors. A similar process can unfold in Moldova, but the development of corporate farms must be left to market forces, free from government intervention and programming. Analyzing the dichotomy between small and large farms, we conclude based on several surveys that small farms are more productive and more efficient than large farms. This result is based on a mixed sample of both individual and corporate farms, which overall show decreasing returns to scale. On the other hand, a homogeneous sample comprising only corporate farms shows increasing returns to scale, i.e., among farms of the same type size has a beneficial effect on performance. Similarly, in a homogeneous sample comprising only individual farms, family income and well-being increase with farm size. Based on these findings we tend to believe that the different behaviour is determined primarily by organizational form: small farms do better than large farm not because of a size effect, but because individual farms (which happen to be small) outperform corporate farms (which happen to be large). In this context, the Government of Moldova should abandon its preference for large-scale corporate farms and concentrate on improving the operating conditions for small individual farms. REFERENCES COELLI, T., RAO, D. S. P., BATTESE, G. (1998): An Introduction to Efficiency and Productivity Analysis, Kluwer, Boston. DUDWICK, N., FOCK, K., SEDIK, D. (2007): Land Reform and Farm Restructuring in Transition Countries. The Experience of Bulgaria, Moldova, Azerbaijan and Kazakhstan, World Bank Working Paper 104, World Bank, Washington, DC [http://go.worldbank.org/2W17PBZ490]. KOESTER, U. (2003): “A Revival of Large Farms in Eastern Europe? – How Important are Institutions?” Plenary paper presented at the Conference of International Association of Agricultural Economists, Durban, South Africa, 16-22 August. LERMAN, Z. (2001): Moldova Baseline Farm Survey October-November 2000. Part I: Survey of Corporate Farm Managers and Peasant farmers; Part II. Survey of Rural Families with Household Plots, Draft analytical report, World Bank, Washington, DC (unpublished). LERMAN, Z. (2005): Farm Fragmentation and Productivity: Evidence from Georgia, Center for Agricultural Economic Research Working Paper 8.05, The Hebrew University of Jerusalem, Rehovot [http://departments.agri.huji.ac.il/economics/lerman-gru.pdf]. LERMAN, Z., CSAKI, C., FEDER, G. (2004): Agriculture in Transition: Land Policies and Evolving Farm Structures in Post-Soviet Countries, Lexington Books, Lanham, MD. MURAVSCHI, A., BUCATCA, A. (2005): Agricultural Policy in Farmers’ Opinion. PFAP – Private Farmers Assistance Program, East-West Management Institute, and USAID, Chisinau, Moldova. SWINNEN, J. (2006): “Endogenous Agricultural Structures: Insights from Transition Countries,” Paper presented at the 96-th EAAE Seminar Causes and Impacts of Agricultural Structures, Taenikon, Switzerland, 10-11 January. WORLD BANK (2005): Moldova Agricultural Policy Notes: Agricultural Land, Draft analytical report, World Bank, Washington, DC (unpublished). PREVIOUS DISCUSSION PAPERS 1.01 Yoav Kislev - Water Markets (Hebrew). 2.01 Or Goldfarb and Yoav Kislev - Incorporating Uncertainty in Water Management (Hebrew). 3.01 Zvi Lerman, Yoav Kislev, Alon Kriss and David Biton - Agricultural Output and Productivity in the Former Soviet Republics. 4.01 Jonathan Lipow & Yakir Plessner - The Identification of Enemy Intentions through Observation of Long Lead-Time Military Preparations. 5.01 Csaba Csaki & Zvi Lerman - Land Reform and Farm Restructuring in Moldova: A Real Breakthrough? 6.01 Zvi Lerman - Perspectives on Future Research in Central and Eastern European Transition Agriculture. 7.01 Zvi Lerman - A Decade of Land Reform and Farm Restructuring: What Russia Can Learn from the World Experience. 8.01 Zvi Lerman - Institutions and Technologies for Subsistence Agriculture: How to Increase Commercialization. 9.01 Yoav Kislev & Evgeniya Vaksin - The Water Economy of Israel--An Illustrated Review. (Hebrew). 10.01 Csaba Csaki & Zvi Lerman - Land and Farm Structure in Poland. 11.01 Yoav Kislev - The Water Economy of Israel. 12.01 Or Goldfarb and Yoav Kislev - Water Management in Israel: Rules vs. Discretion. 1.02 Or Goldfarb and Yoav Kislev - A Sustainable Salt Regime in the Coastal Aquifer (Hebrew). 2.02 Aliza Fleischer and Yacov Tsur - Measuring the Recreational Value of Open Spaces. 3.02 Yair Mundlak, Donald F. Larson and Rita Butzer - Determinants of Agricultural Growth in Thailand, Indonesia and The Philippines. 4.02 Yacov Tsur and Amos Zemel - Growth, Scarcity and R&D. 5.02 Ayal Kimhi - Socio-Economic Determinants of Health and Physical Fitness in Southern Ethiopia. 6.02 Yoav Kislev - Urban Water in Israel. 7.02 Yoav Kislev - A Lecture: Prices of Water in the Time of Desalination. (Hebrew). 8.02 Yacov Tsur and Amos Zemel - On Knowledge-Based Economic Growth. 9.02 Yacov Tsur and Amos Zemel - Endangered aquifers: Groundwater management under threats of catastrophic events. 10.02 Uri Shani, Yacov Tsur and Amos Zemel - Optimal Dynamic Irrigation Schemes. 1.03 Yoav Kislev - The Reform in the Prices of Water for Agriculture (Hebrew). 2.03 Yair Mundlak - Economic growth: Lessons from two centuries of American Agriculture. 3.03 Yoav Kislev - Sub-Optimal Allocation of Fresh Water. (Hebrew). 4.03 Dirk J. Bezemer & Zvi Lerman - Rural Livelihoods in Armenia. 5.03 Catherine Benjamin and Ayal Kimhi - Farm Work, Off-Farm Work, and Hired Farm Labor: Estimating a Discrete-Choice Model of French Farm Couples' Labor Decisions. 6.03 Eli Feinerman, Israel Finkelshtain and Iddo Kan - On a Political Solution to the Nimby Conflict. 7.03 Arthur Fishman and Avi Simhon - Can Income Equality Increase Competitiveness? 8.03 Zvika Neeman, Daniele Paserman and Avi Simhon - Corruption and Openness. 9.03 Eric D. Gould, Omer Moav and Avi Simhon - The Mystery of Monogamy. 10.03 Ayal Kimhi - Plot Size and Maize Productivity in Zambia: The Inverse Relationship Re-examined. 11.03 Zvi Lerman and Ivan Stanchin - New Contract Arrangements in Turkmen Agriculture: Impacts on Productivity and Rural Incomes. 12.03 Yoav Kislev and Evgeniya Vaksin - Statistical Atlas of Agriculture in Israel - 2003-Update (Hebrew). 1.04 Sanjaya DeSilva, Robert E. Evenson, Ayal Kimhi - Labor Supervision and Transaction Costs: Evidence from Bicol Rice Farms. 2.04 Ayal Kimhi - Economic Well-Being in Rural Communities in Israel. 3.04 Ayal Kimhi - The Role of Agriculture in Rural Well-Being in Israel. 4.04 Ayal Kimhi - Gender Differences in Health and Nutrition in Southern Ethiopia. 5.04 Aliza Fleischer and Yacov Tsur - The Amenity Value of Agricultural Landscape and Rural-Urban Land Allocation. 6.04 Yacov Tsur and Amos Zemel – Resource Exploitation, Biodiversity and Ecological Events. 7.04 Yacov Tsur and Amos Zemel – Knowledge Spillover, Learning Incentives And Economic Growth. 8.04 Ayal Kimhi – Growth, Inequality and Labor Markets in LDCs: A Survey. 9.04 Ayal Kimhi – Gender and Intrahousehold Food Allocation in Southern Ethiopia 10.04 Yael Kachel, Yoav Kislev & Israel Finkelshtain – Equilibrium Contracts in The Israeli Citrus Industry. 11.04 Zvi Lerman, Csaba Csaki & Gershon Feder – Evolving Farm Structures and Land Use Patterns in Former Socialist Countries. 12.04 Margarita Grazhdaninova and Zvi Lerman – Allocative and Technical Efficiency of Corporate Farms. 13.04 Ruerd Ruben and Zvi Lerman – Why Nicaraguan Peasants Stay in Agricultural Production Cooperatives. 14.04 William M. Liefert, Zvi Lerman, Bruce Gardner and Eugenia Serova Agricultural Labor in Russia: Efficiency and Profitability. 1.05 Yacov Tsur and Amos Zemel – Resource Exploitation, Biodiversity Loss and Ecological Events. 2.05 Zvi Lerman and Natalya Shagaida – Land Reform and Development of Agricultural Land Markets in Russia. 3.05 Ziv Bar-Shira, Israel Finkelshtain and Avi Simhon – Regulating Irrigation via Block-Rate Pricing: An Econometric Analysis. 4.05 Yacov Tsur and Amos Zemel – Welfare Measurement under Threats of Environmental Catastrophes. 5.05 Avner Ahituv and Ayal Kimhi – The Joint Dynamics of Off-Farm Employment and the Level of Farm Activity. 6.05 Aliza Fleischer and Marcelo Sternberg – The Economic Impact of Global Climate Change on Mediterranean Rangeland Ecosystems: A Spacefor-Time Approach. 7.05 Yael Kachel and Israel Finkelshtain – Antitrust in the Agricultural Sector: A Comparative Review of Legislation in Israel, the United States and the European Union. 8.05 Zvi Lerman – Farm Fragmentation and Productivity Evidence from Georgia. 9.05 Zvi Lerman – The Impact of Land Reform on Rural Household Incomes in Transcaucasia and Central Asia. 10.05 Zvi Lerman and Dragos Cimpoies – Land Consolidation as a Factor for Successful Development of Agriculture in Moldova. 11.05 Rimma Glukhikh, Zvi Lerman and Moshe Schwartz – Vulnerability and Risk Management among Turkmen Leaseholders. 12.05 R.Glukhikh, M. Schwartz, and Z. Lerman – Turkmenistan’s New Private Farmers: The Effect of Human Capital on Performance. 13.05 Ayal Kimhi and Hila Rekah – The Simultaneous Evolution of Farm Size and Specialization: Dynamic Panel Data Evidence from Israeli Farm Communities. 14.05 Jonathan Lipow and Yakir Plessner - Death (Machines) and Taxes. 1.06 Yacov Tsur and Amos Zemel – Regulating Environmental Threats. 2.06 Yacov Tsur and Amos Zemel - Endogenous Recombinant Growth. 3.06 Yuval Dolev and Ayal Kimhi – Survival and Growth of Family Farms in Israel: 1971-1995. 4.06 Saul Lach, Yaacov Ritov and Avi Simhon – Longevity across Generations. 5.06 Anat Tchetchik, Aliza Fleischer and Israel Finkelshtain – Differentiation & Synergies in Rural Tourism: Evidence from Israel. 6.06 Israel Finkelshtain and Yael Kachel – The Organization of Agricultural Exports: Lessons from Reforms in Israel. 7.06 Zvi Lerman, David Sedik, Nikolai Pugachev and Aleksandr Goncharuk – Ukraine after 2000: A Fundamental Change in Land and Farm Policy? 8.06 Zvi Lerman and William R. Sutton – Productivity and Efficiency of Small and Large Farms in Moldova. 9.06 Bruce Gardner and Zvi Lerman – Agricultural Cooperative Enterprise in the Transition from Socialist Collective Farming. 10.06 Zvi Lerman and Dragos Cimpoies - Duality of Farm Structure in Transition Agriculture: The Case of Moldova. 11.06 Yael Kachel and Israel Finkelshtain – Economic Analysis of Cooperation In Fish Marketing. (Hebrew) 12.06 Anat Tchetchik, Aliza Fleischer and Israel Finkelshtain – Rural Tourism: Developmelnt, Public Intervention and Lessons from the Israeli Experience. 13.06 Gregory Brock, Margarita Grazhdaninova, Zvi Lerman, and Vasilii Uzun Technical Efficiency in Russian Agriculture. 14.06 Amir Heiman and Oded Lowengart - Ostrich or a Leopard – Communication Response Strategies to Post-Exposure of Negative Information about Health Hazards in Foods 15.06 Ayal Kimhi and Ofir D. Rubin – Assessing the Response of Farm Households to Dairy Policy Reform in Israel. 16.06 Iddo Kan, Ayal Kimhi and Zvi Lerman – Farm Output, Non-Farm Income, and Commercialization in Rural Georgia. 17.06 Aliza Fleishcer and Judith Rivlin – Quality, Quantity and Time Issues in Demand for Vacations. 1.07 Joseph Gogodze, Iddo Kan and Ayal Kimhi – Land Reform and Rural Well Being in the Republic of Georgia: 1996-2003. 2.07 Uri Shani, Yacov Tsur, Amos Zemel & David Zilberman – Irrigation Production Functions with Water-Capital Substitution. 3.07 Masahiko Gemma and Yacov Tsur – The Stabilization Value of Groundwater and Conjunctive Water Management under Uncertainty. 4.07 Ayal Kimhi – Does Land Reform in Transition Countries Increase Child Labor? Evidence from the Republic of Georgia. 5.07 Larry Karp and Yacov Tsur – Climate Policy When the Distant Future Matters: Catastrophic Events with Hyperbolic Discounting. 6.07 Gilad Axelrad and Eli Feinerman – Regional Planning of Wastewater Reuse for Irrigation and River Rehabilitation. 7.07 Zvi Lerman – Land Reform, Farm Structure, and Agricultural Performance in CIS Countries. 8.07 Ivan Stanchin and Zvi Lerman – Water in Turkmenistan. 9.07 Larry Karp and Yacov Tsur – Discounting and Climate Change Policy. 10.07 Xinshen Diao, Ariel Dinar, Terry Roe and Yacov Tsur – A General Equilibrium Analysis of Conjunctive Ground and Surface Water Use with an Application To Morocco. 11.07 Barry K. Goodwin, Ashok K. Mishra and Ayal Kimhi – Household Time Allocation and Endogenous Farm Structure: Implications for the Design of Agricultural Policies. 12.07 Iddo Kan, Arie Leizarowitz and Yacov Tsur - Dynamic-spatial management of coastal aquifers. 13.07 Yacov Tsur and Amos Zemel – Climate change policy in a growing economy under catastrophic risks. 14.07 Zvi Lerman and David J. Sedik – Productivity and Efficiency of Corporate and Individual Farms in Ukraine. 15.07 Zvi Lerman and David J. Sedik – The Role of Land Markets in Improving Rural Incomes. 16.07 Ayal Kimhi – Regression-Based Inequality Decomposition: A Critical Review And Application to Farm-Household Income Data. 17.07 Ayal Kimhi and Hila Rekah – Are Changes in Farm Size and Labor Allocation Structurally Related? Dynamic Panel Evidence from Israel. 18.07 Larry Karp and Yacov Tsur – Time Perspective, Discounting and Climate Change Policy. 1.08 Yair Mundlak, Rita Butzer and Donald F. Larson – Heterogeneous Technology and Panel Data: The Case of the Agricultural Production Function. 2.08 Zvi Lerman – Tajikistan: An Overview of Land and Farm Structure Reforms. 3.08 Dmitry Zvyagintsev, Olga Shick, Eugenia Serova and Zvi Lerman – Diversification of Rural Incomes and Non-Farm Rural Employment: Evidence from Russia. 4.08 Dragos Cimpoies and Zvi Lerman – Land Policy and Farm Efficiency: The Lessons of Moldova.