A GTAP Analysis of the Proposed BRICS Free Trade Agreement

A GTAP Analysis of the Proposed BRICS Free Trade Agreement Working Draft Dr. Sachin Kumar Sharma Dr. Murali Kallummal Submitted to 15th Annual Conference on Global Economic Analysis “New Challenges for Global Trade and Sustainable Development”, Geneva, Switzerland June 27 – 29, 2012 Table of Contents SECTION 1: INTRODUCTION ............................................................................................................... 3 SECTION2: ECONOMIC PROFILE OF BRICS MEMBERS ............................................................. 5 SECTION 3: METHODOLOGY .............................................................................................................. 8 3.1 Aggregation Strategy .......................................................................................................................... 8 3.2 Experiment Design............................................................................................................................ 10 SECTION 4: SIMULATION RESULTS ................................................................................................ 11 4.1 WELFARE EFFECTS: ..................................................................................................................... 12 4.2 MACROECONOMIC EFFECTS: .................................................................................................... 12 4.3 OUTPUT EFFECT: .......................................................................................................................... 13 4.4 Employment Effect: .......................................................................................................................... 13 4.5 IMPACT ON TRADE ...................................................................................................................... 14 SECTION 5: CONCLUSION .................................................................................................................. 16 REFERENCE ............................................................................................................................................ 18 List of Tables Table 1: Region aggregation in the GTAP Model ........................................................................................ 8 Table 2: Commodity Aggregation in the GTAP model ................................................................................ 9 Table 3: Tariff profile of different regions across different sectors ............................................................ 10 Table 4: Decomposition of Welfare Effect ................................................................................................. 12 Table 5: Change in Macroeconomic indicators .......................................................................................... 13 Table 6: Change in Industrial Output .......................................................................................................... 13 Table 7: Change in Demand for Labor ....................................................................................................... 14 List of Figures Figure 1: Intra-BRICS Trade (by destination) .............................................................................................. 6 Figure 2: Impact on Trade balance After Simulation ................................................................................. 15 Figure 3: Impact on Trade balance After Simulation (Aggregate Sectors)................................................. 16 List of Appendix Table Appendix Table 1: India’s base Protection levels in GTAP database......................................................... 19 Appendix Table 2: Level of Protection Faced by India in other Regions in GTAP database.................... 20 Appendix Table 3: Sector-wise Changes in Industrial Output................................................................... 21 Appendix Table 4: Demand for Unskilled Labour .................................................................................... 22 Appendix Table 5: Demand for Skilled Labour......................................................................................... 23 Appendix Table 6: Sector-wise Changes in Exports.................................................................................. 24 Appendix Table 7: Sector-wise Changes in Imports.................................................................................. 25 Appendix Table 8: Trade balance in Million US $ .................................................................................... 26 2 A GTAP Analysis of the Proposed BRICS Free Trade Agreement:1 Dr. Sachin Kumar Sharma Dr. Murali Kallummal ABSTRACT The negotiations for the BRICS FTA have made a significant progress with the four summit level meeting among proposed BRICS FTA. This study used the GTAP model on 57 tradable commodities and nine regions of the world to understand the likely impact of possible BRICS FTA. . In this study, 113 regions given in GTAP data base is mapped to nine regions namely Brazil, Russia, India, China, South Africa, ASEAN, USA, EU and Rest of the World by using GTAP database. This study updates the tariff protection for the nine regions and analyses the possible impacts on various indicators. A scenario of a full FTA between BRICS members is simulated using the GTAP model. Under this scenario, import protection within the BRICS member were removed but maintained between the Non­BRICS countries. Overall, the impact of proposed BRICS FTA would be positive for India as macroeconomics indicators (except trade balance) show positive change. However, at the disaggregate level, result vary across 57 sectors. SECTION 1: INTRODUCTION The world trading system witnessed a drastic change due to proliferation of RTA. Provision for Regional Trade Agreement (RTA) was built as exception to one of the basic principles of the WTO i.e. Most Favoured Nation Rule. The structure of RTAs varies widely, but all have one thing in common-the objective of reducing barriers to trade between member countries. The proliferation in RTAs around the globe reflects commercial, socio-economic and political interests. RTAs can be a cornerstone of larger economic and political efforts to increase regional cooperation beyond the multilateral agenda. They can also stimulate inward foreign direct investment (Kimura and Ando, 2005) and growth through technological transfers. Their proliferation can also be motivated by a growing sense that regional agreements elsewhere put the excluded countries at a disadvantage (Baldwin, 1993). Also the prevailing deadlock in the Doha round negotiations of the WTO resulted in the proliferation of RTAs (Tumbarello, 2007). 1 We are grateful to Prof Abhijit Das and Sajal Mathur of the Centre for WTO Studies and Devender Pratap, Associate Fellow, National Council of Applied Economic Research (NCEAR) for their valuable comments and suggestions. 3 India has been a staunch supporter of multilateral trading system and always stood for open, equitable, predictable, non-discriminatory and rule-based trading system. India never used Regional Trade Agreements like FTAs or PTAs as a trade policy instrument for its economic engagement till 2000. India started pursuing engagement through RTAs in 2003. It was perhaps felt that if it did not do so, it will be locked-out of the markets of its important trading partners. India’s increased engagement in RTAs, be they bilateral, regional or extra-regional in nature, is a break from the past when she undertook trade liberalisation mostly at the MFN level. India is seen to be seeking deeper forms of economic integration via comprehensive RTAs as a development strategy to exploit the potential of “efficiency-seeking” industrial restructuring and strengthen overall competitiveness. India began negotiating agreements with a view to moving, in some cases, towards Comprehensive Economic Cooperation Agreements (CECAs) covering FTA in Goods Services, Investment and other identified areas of economic cooperation. In addition, India also began actively engaging with regional bock like EU, ASEAN, South Africa Customs Union (SACU) and MERCOSUR. Thus, India’s RTAs increasingly include deeper and wider commitments in non-goods areas, which go beyond India’s commitments under the WTO. While the widely acknowledged move towards regionalism driven by the “Look East” policy announced by the Indian government in 1992 played an important role in leading to the new RTA initiatives in East Asia, the dynamics of multilateral trade negotiations at the WTO and the proliferation of RTAs initiated by the ASEAN became important catalysts that accelerated India’s trade policy shift involving RTAs with other regions. As more and more countries become members of multiple RTAs, the desire of the Indian government to avoid the perceived negative effects of discrimination and marginalisation (the domino effect suggested by Baldwin in 1993) has played an important role, as the country does not want to be excluded from a share in the benefits of belonging to the RTAs. In this context, India has a dialogue with Brazil, Russia, China and South Africa for deeper economic cooperation. With Russia joining the WTO in 2011, all BRICS member countries are also the member of WTO. Growing engagement between these countries and their combined strength in global decision making process provides a favourable environment for a possible FTA. Already, four summit level meetings have been held during 2009-12. The Fourth BRICS Summit was hosted in New Delhi on 29 March 2012 under the overarching theme of “BRICS Partnership for Global Stability, Security and Prosperity.” The Summit has imparted further 4 momentum to the BRICS process. The proposed FTA led liberalisation of trade between BRICS members will have implications in terms of overall welfare, macroeconomic and trade indicators. These implications can be further traced across sectors by using GTAP model. With this background, the objective of this study is to examine the effect of possible BRICS FTA on various sectors as well as on macro-economic and trade indicators by using GTAP model and database. SECTION2: ECONOMIC PROFILE OF BRICS MEMBERS This section gives an overview of economic and trade profiles of the BRICS members. To understand and analyse BRICS as a group, it is necessary to get a sense of how these five emerging giants spread across four continents are situated in the global context. The BRICS together account for 26 % of the world’s GDP (PPP) in 2011 and over 40% of the global population. In terms of land mass, Russia is by far the largest in the grouping (it is also the largest country in the world). In terms of demographics, China closely followed by India, are the two most populous nations in the world. Together these two countries account for over one third of the world’s population. Over the past two decades, the rate of growth of per capita GDP in the BRICS has outpaced the global trend line. The investment and savings numbers are impressive. Across the BRICS members the gross saving and investment rates as a percentage of GDP averaged around 28.8 percentages. In terms of FDI flows, the BRICS as a group accounted for over US $ 300 billion of FDI or over 20% of global FDI flows. China is a single biggest recipient of FDI followed by Brazil, Russia and India in that order. Total foreign exchange reserves of all the BRICS together amounts to US $ 4,025.0 billion or about 37% of global foreign exchange reserves in 2010. China alone accounts for nearly 75 percentages with close to $ 3 trillion of reserves. All the BRICS economies run a surplus on the capital account except India which had a small deficit in 2010. The situation in the current account is mixed with only China and Russia running a surplus. This is also reflected in the balance of trade numbers. The BRICS as a grouping account for over 40% of the world’s labour force. According to UN projections, by 2020, the working age population is expected to rise by 240 million in India and by 20 million in Brazil. China’s demographic projections suggest that the labour force will peak by 2015 and decline thereafter. A growing population will only yield a demographic dividend if there is a matching increase in the available jobs. Improvements in total factor productivity are also critical for growth prospects. On the other hand the unemployment rate is over 20% in 5 South Africa, over 8% in Brazil and Russia and just under 4.5% in India and China. With a large informal sector and a significant proportion of the work force still underemployed there is an ever growing need for skill and human resource development. More and better jobs require investment in education, health, and the soft skills to train the work force for jobs in the 21st century. The literacy rate in Brazil, China, Russia, and South Africa is 90% or above. In India, however, the literacy rate is just over 60%. In 1990, the BRICS as a group accounted for only 3% of global trade. This share had doubled by the turn of the century. In 2010, the BRICS as a group accounted for 15% of global exports and 14% of global imports of goods and services. The share of the BRICS in global trade has increased significantly over the last two decades. The double digit growth in merchandise trade has catapulted China to the top ranking in exports and it is the second largest importer of merchandise goods in 2010. Russia and India have also broken into the top 20 list of world merchandise exporters and importers. Brazil is in the top 20 from the merchandise export side. The merchandise trade balance is in surplus for China, Russia, and Brazil. India and South Africa have a merchandise trade deficit. Figure 1: Intra-BRICS Trade (by destination) (a) Trade between Brazil and rest of the (b) Trade between Russia and rest of the BRICS BRICS 6 Trade between India and rest of the (e) Trade between South Africa and rest of the BRICS BRICS (c) (d) Trade between China and rest of the BRICS Source: Based on UN Comtrade data Without exception, China is the largest trade partner for each of the other BRICS with a trade share ranging between 70 to 80% in intra-BRICS trade. India has a share ranging between 10 to 30% in intra-BRICS trade. Brazil’s trade share is in single digits except with China where its share is 30%. Russia too has a small slice of the intra-BRICS trade pie in all markets barring China where its share is 27%. South Africa’s share is the smallest in each of the other BRICS markets. 7 SECTION 3: METHODOLOGY The impact of possible BRICS FTA on different regions is estimated by using GTAP static model. This study is conducted with a multi country, general equilibrium closure. The model assumes perfect competition, constant return to scale and profit and utility maximising behaviour of firms and household respectively. Hertel (1997) provides detail information about the structure and overview of GTAP model. The data used in this study is the version 7 of the GTAP database. The reference year for this database is 2004. 3.1 Aggregation Strategy The GTAP database is compiled for 113 regions across the world and for 57 tradable commodities of the world. In this study, 113 regions given in GTAP data base is mapped to nine regions namely Brazil, Russia, India, China, South Africa, ASEAN, USA, EU and Rest of the World by using GTAP database. ASEAN, USA and EU have been taken as a separate region due to the importance of these regions in world trade. Table 1: Region aggregation in the GTAP Model New Code Region Description Comprising old regions INDIA INDIA India. RUSSIA SOUTH AFRICA RUSSIA Russian Federation. BRAZIL CHINA ASEAN USA EU_25 BRAZIL CHINA SOUTH AFRICA ASEAN (except Brunei Darussalam) USA European Union 25 Brazil. China. South Africa. Cambodia; Indonesia; Lao People's Democratic Republ; Myanmar; Malaysia; Philippines; Singapore; Thailand; Viet Nam. United States of America. Austria; Belgium; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Hungary; Ireland; Italy; Latvia; Lithuania; Luxembourg; Malta; Netherlands; Poland; Portugal; Slovakia; Slovenia; Spain; Sweden; United Kingdom. 8 Rest of World Rest of World Source: GTAP 7 database Australia; New Zealand; Rest of Oceania; Hong Kong; Japan; Korea; Taiwan; Rest of East Asia; Rest of Southeast Asia; Bangladesh; Pakistan; Sri Lanka; Rest of South Asia; Canada; Mexico; Rest of North America; Argentina; Bolivia; Chile; Colombia; Ecuador; Paraguay; Peru; Uruguay; Venezuela; Rest of South America; Costa Rica; Guatemala; Nicaragua; Panama; Rest of Central America; Caribbean; Switzerland; Norway; Rest of EFTA; Albania; Bulgaria; Belarus; Croatia; Romania; Ukraine; Rest of Eastern Europe; Rest of Europe; Kazakhstan; Kyrgyztan; Rest of Former Soviet Union; Armenia; Azerbaijan; Georgia; Iran Islamic Republic of; Turkey; Rest of Western Asia; Egypt; Morocco; Tunisia; Rest of North Africa; Nigeria; Senegal; Rest of Western Africa; Central Africa; South Central Africa; Ethiopia; Madagascar; Malawi; Mauritius; Mozambique; Tanzania; Uganda; Zambia; Zimbabwe; Rest of Eastern Africa; Botswana; Rest of South African Customs . The analysis has been done for 57 sectors given in GTAP database. It will help in assessing the impact of possible BRICS-FTA at the disaggregated level (see table 1) Table 2: Commodity Aggregation in the GTAP model Agriculture (20 items) Non­Agriculture (22 items) Service (15 items) Paddy, Rice Forestry Electricity Cereal Grain nec Coal Water Wheat Fishing Gas Manufacturer Distribution Vegetable, Fruits Oil Construction Sugarcane, Sugar Beet Mineral Nec Transport Nec Oilseeds Plant Based Fiber Gas Trade Textiles Sea Transport Cattle,sheep, goat, horse Leather Products Communication Raw Milk Paper Products, Publishing Insurance Meat: Cattle, Sheep, Goats, Chemical Rubber Plastic Recreation and other Vegetable Oils And Fats Ferrous Metal Dwelling Processed Rice Metal Products Crop Nec Animal Product Nec Wool, Silk‐Worm Cocoons Meat Products Nec Dairy Products Wearing Apparel Air Transport Wood Products Pertoleum, Coal Product Mineral Products Nec Metal Nec Sugar Motor Vechicle Parts Beverages And Tobacco Products Electronic Equiptment Source: GTAP data base Manufacturers nec Food Product Nec Transport Equip Machinary and Equipments 9 Financial Services Business service Public Adm/Defence/Health 3.2 Experiment Design Given the unstable economic environment, unemployment is a general phenomenon around the world. Therefore, to make this study more realistic, standard closure is altered by changing the assumption of full employment for skilled and unskilled labour. It is to be noted that the protection data supplied in GTAP is intended to represent a starting point for analysis. Data on protection is needed to adjust to make analysis more realistic and meaningful for the simulation. Protection data in GTAP is available for the reference year 2004. In GTAP database the protection level (See Appendix Tables 1 &2 for India’s protection levels) is different from Table 3 given below. Therefore, the protection information in GTAP database for the BRICS member is altered to better reflect the reality. The tariff data is extracted from WITS. The possible FTA among BRICS countries will require substantial reduction in tariff rate for the intra-BRICS trade and thereby will provide vast market for the member countries. For the year 2009, the tariff profile of member countries for the goods sector is given in table 1. Table 3: Tariff profile of different regions across different sectors Sectors 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Paddy, Rice Wheat Cereal Grain nec Vegetable, Fruits Oilseeds Sugarcane, Sugar Beet Plant Based Fiber Crop Nec Cattle,sheep, goat, horse Animal Product Nec Raw Milk Wool, Silk‐Worm Forestry Fishing Coal Oil Gas Mineral Nec Meat: Cattle, Sheep, Goats, Horse Meat Products Nec Vegetable Oils And Fats Dairy Products Indi a Braz il China 30 26 26 31 26 8 5 5 9 5 23 11 11 13 11 Russian Federatio n 9 6 6 9 6 26 31 5 8 11 13 6 8 26 27 24 5 2 7 11 6 South Africa ASEA N United States Europea n Union ROW GTAP 6 5 5 6 5 9 8 8 10 8 4 4 4 4 4 22 10 10 9 10 14 11 11 14 11 5 5 8 9 4 3 10 8 11 13 5 3 1 15 10 7 5 4 5 2 2 2 2 19 1 1 0 0 0 0 0 62 10 2 8 0 0 0 0 23 13 7 11 4 5 5 5 11 3 26 21 12 6 5 13 6 11 10 5 5 5 5 15 3 4 2 0 0 0 1 29 10 16 5 15 16 9 9 11 0 12 11 8 11 1 2 2 2 17 10 4 18 6 5 9 0 0 0 4 10 4 9 32 24 20 29 6 5 4 5 31 8 17 5 11 7 11 7 10 6 16 12 8 4 8 4 1 3 3 3 10 28 12 10 14 23 11 11 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 Processed Rice Sugar Food Product Nec Beverages And Tobacco Products Textiles Wearing Apparel Leather Products Wood Products Paper Products, Publishing Pertoleum, Coal Product Chemical Rubber Plastic Mineral Products Nec Ferrous Metal Metal Nec Metal Products Motor Vechicle Parts Transport Equip Electronic Equiptment Machinary and Equipments Manufacturers nec Source: WITS 33 41 32 11 16 12 36 35 18 11 5 11 10 16 15 5 10 15 8 14 95 19 26 8 11 9 8 12 20 10 10 6 23 34 22 9 14 76 5 11 4 5 7 7 5 9 10 12 24 25 14 5 14 5 10 17 14 16 8 11 8 16 11 14 10 20 8 8 2 6 6 10 7 1 10 18 37 19 9 4 11 5 12 34 46 18 18 17 16 15 45 7 14 10 7 8 11 8 1 7 11 7 3 12 19 14 11 0 0 9 5 4 2 1 1 5 14 6 7 3 3 11 6 11 5 5 11 6 11 12 8 10 9 7 3 1 2 8 3 3 4 7 2 9 1 3 3 1 3 3 5 2 2 7 6 11 9 12 17 7 2 3 1 2 8 15 8 8 3 3 14 1 3 3 4 6 2 2 6 7 The implication of reducing tariff across various sectors would vary among the BRICS members as these countries have comparative advantage in different commodities. Similarly the effect of possible BRICS FTA on welfare and macroeconomic indicators would be varied due to different socio-economic conditions prevailing in these countries. A scenario of a full FTA between BRICS members is simulated using the GTAP model. Under this scenario, import protection within the BRICS member were removed but maintained between the Non-BRICS countries. Although it is unlikely that an agreement would result in the complete removal of all import tariffs, this experiment provides an upper bound for the benefits of BRICS FTA that can be captured by the model. SECTION 4: SIMULATION RESULTS This section shows the GTAP simulation results of the proposed BRICS FTA. It reports welfare, macro-economic, sectoral trade and employment effects of the proposed BRICS FTA. 11 4.1 WELFARE EFFECTS: The net welfare gains from the proposed BRICS FTA are measured by equivalent variation (EV) in income. The EV measures the amount of income that would have to be given or taken away from an economy before trade liberalisation so as to leave the economy as well off as it would be after the policy has been changed. The welfare effects of the simulation for the concerned regions are given in table 3. In terms of absolute value, highest welfare gain is attained by China, Brazil, India and Russia whereas South Africa gained least in terms of welfare effect. It is revealed that Non-BRICS member experienced net welfare loss due to BRICS FTA. The decomposition of the welfare effects suggest that India’s gain from the proposed FTA is primarily driven by endowment and allocation effects. BRICS members would experience gain in allocative efficiency as resources will divert from inefficient sectors to the more efficient sectors. Table 4: Decomposition of Welfare Effect (Million US $) Region INDIA BRAZIL CHINA RUSSIA SOUTH AFRICA ASEAN USA EU_25 RoW Total Allocation Source: Simulation Result 300 409 473 119 335 ‐64 ‐1172 ‐3348 ‐1625 ‐4572 Endowment 1332 703 2617 869 469 ‐200 ‐1934 ‐2156 ‐2328 ‐627 Terms of Trade ‐6 770 1293 593 101 ‐209 ‐641 ‐1201 ‐704 ‐3 Investment and Saving ‐24 ‐144 ‐79 ‐44 3 49 ‐174 100 313 1 Welfare 1603 1739 4304 1537 908 ‐424 ‐3920 ‐6604 ‐4346 ‐5203 4.2 MACROECONOMIC EFFECTS: Table 4 presents the impact on some macro-economic variables for the countries under the consideration. All the members of possible BRICS FTA would experience an increase in GDP and all the components of GDP from the base run. China and Brazil would be major beneficiaries in terms of GDP gain whereas South Africa and India would be least beneficiaries. Non-BRICS regions would experience fall in GDP as well as other component of GDP. 12 Table 5: Change in Macroeconomic indicators (Million US $) Region INDIA BRAZIL CHINA RUSSIA SOUTH AFRICA ASEAN USA EU_25 RoW Total Consumption Source: Simulation result 894 3130 3558 739 414 ‐496 ‐6661 ‐6967 ‐5176 ‐10564 Investment 1090 2786 3962 534 947 ‐294 ‐2125 ‐2977 ‐2674 1247 Government Expenditure 204 1105 996 321 177 ‐84 ‐1471 ‐2544 ‐1505 ‐2802 Export 3146 1965 7284 2772 1705 ‐310 ‐709 ‐2153 ‐1725 11974 Import 4092 3612 7724 2764 2608 ‐404 ‐1989 ‐3661 ‐2772 11973 Total 1242 5374 8075 1603 634 ‐781 ‐8977 ‐10980 ‐8307 ‐12118 4.3 OUTPUT EFFECT: The impact of proposed BRICS FTA on output varies across different sectors and different regions. To show the result at aggregate level, 57 sectors are mapped into three broad sectors (agriculture, non-agriculture and service) after the simulation. About the agriculture sector, India, China, South Africa, USA and EU_25 have negative change in agriculture output, whereas Brazil and Russia have positive growth in agriculture output. At the disaggregate level, India would experience negative growth in sugarcane, wool silk, vegetable oil, sugar and beverages. However, for non-agricultural sector, all the BRICS countries except Brazil has positive growth after simulation. In case of India, sectors like oil, paper, coal, transport equipments and electronic not performed well after the simulation. For service sector, BRICS members have experienced positive change in comparison to the base data. At the disaggregate level, all service sub-sectors indicated positive growth for India (disaggregate sector level see Appendix Table: 3). Table 6: Change in Industrial Output Sector Total AGRI Total N.AGRI Total Service Unit US $ million % age US $ million % age US $ million % age India Brazil China Russia South Africa ASEAN USA EU_25 Rest of World -447.1 1895.8 -4.0 534.8 -58.0 -307.1 -178.9 -125.4 48.5 -0.169 1.014 -0.001 0.230 -0.105 -0.103 -0.016 -0.006 0.002 2126.9 -2695.5 6094.2 2191.2 323.5 -37.8 -82.7 -3192.0 -2583.4 0.560 -0.749 0.252 0.569 0.199 -0.005 -0.002 -0.042 -0.034 1806.4 1878.3 3738.5 1396.7 749.0 -198.3 -4634.4 -5680.0 -4462.3 0.367 0.317 0.214 0.259 0.289 -0.029 -0.031 -0.039 -0.033 Source: Simulation result 4.4 Employment Effect: Overall, all the BRICS members have higher demand for skilled and unskilled labour, however for Non-BRICS members demand for labour is negative. It is noteworthy that Brazil has negative 13 demand for labour in non-agriculture sector. For India, demand for labour across all the broad sectors is positive. At disaggregate level, impact of proposed BRICS FTA is mixed across 57 sectors (disaggregate sector level see Appendix Tables: 4 & 5). Table 7: Change in Demand for Labor (Percentage) India Brazil China Russia Total Agri. Total N.Agri. T. Services All Sectors 0.085 0.814 0.782 0.572 1.380 -0.504 0.438 0.317 0.195 0.414 0.418 0.373 0.522 0.770 0.695 0.691 Total Agri. Total N.Agri. T. Services All Sectors 0.229 0.870 0.573 0.573 1.706 -0.508 0.307 0.307 0.094 0.456 0.364 0.364 1.113 0.911 0.507 0.507 South Africa ASEAN Un-skilled 0.316 -0.143 0.072 -0.055 0.858 -0.070 0.633 -0.077 Skilled 0.443 -0.341 0.430 -0.041 0.794 -0.064 0.794 -0.064 USA EU_25 Rest of World -0.053 -0.007 -0.042 -0.036 -0.009 -0.063 -0.069 -0.064 -0.032 -0.059 -0.055 -0.054 -0.047 -0.009 -0.039 -0.039 -0.035 -0.055 -0.067 -0.067 -0.058 -0.050 -0.053 -0.053 Source: Simulation result 4.5 IMPACT ON TRADE At the aggregate level, all the BRICS members have shown positive sign for exports, whereas non-BRICS members have negative growth. At broad sub-sector level, India has positive growth for agriculture and non-agriculture sector; however, it is negative for service sector. In case of import, all the BRICS members have experienced positive growth across all the broad subsectors, whereas Non-BRICS regions have negative change after the simulation. At the disaggregate impact of proposed FTA on Export and Import is given in the Appendix Tables 6 and 7. Table 5: Change in Exports Sector Total AGRI Total N.AGRI Total Service Unit India Brazil China Russia South Africa ASEAN USA EU_25 Rest of World US $ million 226.6 1225.8 109.2 -346.4 76.4 -210.1 -125.4 152.8 318.2 % age 1.642 3.049 0.334 -0.356 0.533 -0.268 -0.151 0.046 0.044 US $ million 3016.5 284.2 6434.1 1910.2 1570.8 -15.0 -316.8 -1824.3 -1822.8 % age 21.865 0.707 19.656 1.964 10.963 -0.019 -0.381 -0.545 -0.252 US $ million -75.2 -300.4 -562.1 -206.0 -54.0 131.1 173.3 832.3 617.5 % age -3.375 -7.337 -6.290 -1.292 -0.586 1.438 1.104 1.348 0.523 Source: Simulation Result 14 Table 6: Change in Imports Sector Total Agri Total N.Agri Total Ser. Unit India Brazil China Russia South Africa ASEAN EU_25 Rest of World -288.3 -658.4 1369.0 -0.215 -0.125 -0.113 3.039 2695.1 -286.5 -2060.6 -2751.5 3113.6 2.386 5.624 -0.065 -0.151 -0.090 2.913 453.7 235.8 44.4 -50.4 -143.8 -635.8 90.9 0.761 0.796 0.680 -0.065 -0.063 -0.075 0.517 US $ million 1369.0 129.0 1390.9 471.8 182.7 -153.5 % age 3.039 1.069 1.745 2.171 1.703 US $ million 3113.6 3388.4 6561.9 2081.2 % age 2.913 5.122 1.209 US $ million 90.9 224.3 % age 0.517 1.318 USA Source: Simulation Result About the trade balance, all the BRICS members except Russia have negative trade balance due to higher positive change in import in comparison to change in exports after the simulation. NonBRICS members have positive trade balance after the simulation. Figure 2: Impact on Trade balance After Simulation Source: Simulation Result 15 Figure 3: Impact on Trade balance After Simulation (Aggregate Sectors) Source: Simulation Result About broad sector-wise trade balance, India, China and South Africa have negative trade balance in agriculture sector. Brazil gained maximum in agriculture sector but experienced huge negative trade balance in non-agriculture sector. Trade balance across three broad sectors for India and South Africa is negative. At the disaggregate impact of proposed FTA on trade balance is given in the Appendix Table 8. SECTION 5: CONCLUSION This study used the GTAP model on 57 tradable commodities and nine regions of the world to understand the likely impact of possible BRICS FTA. The data in the GTAP model is available for 2004. This study updates the tariff protection for the nine regions and analyses the possible impacts on welfare, macro-economic variables, output, employment and trade indicators. In terms of absolute value, highest welfare gain is attained by China, Brazil, India and Russia whereas South Africa gained least in terms of welfare effect. It is revealed that Non-BRICS 16 member experienced net welfare loss due to BRICS FTA. All the members of possible BRICS FTA would experience an increase in GDP and all the components of GDP from the base run. China and Brazil would be major beneficiaries in terms of GDP gain whereas South Africa and India would be least beneficiaries. Non-BRICS regions would experience fall in GDP as well as other component of GDP. The impact on output varies across different sectors and different regions, for example, India, China, South Africa, USA and EU_25 has negative change in agriculture output, whereas Brazil and Russia has positive growth in agriculture output. At the disaggregate level, India would experience negative growth in sugarcane, wool silk, vegetable oil, sugar and beverages. All the BRICS members have higher demand for skilled and unskilled labour, however for Non-BRICS members demand for labour is negative. About the trade balance, all the BRICS members except Russia have negative trade balance. Non-BRICS members have positive trade balance after the simulation. Overall, the impact of proposed BRICS FTA would be positive for India as macroeconomics indicators (except trade balance) show positive change. However, at the disaggregate level, result vary across 57 sectors. 17 REFERENCE Ando M., and Kimura F., 2005, “The formation of international production and distribution networks in East Asia”, In Rose A. (eds), International Trade (NBER-East Asia Seminar on Economics, Volume 14). Chicago, IL: University of Chicago Press, 177–213. Asher, Mukul G and Rahul Sen 2005, “India-East Asia Integration: A win-win for Asia”, Economic & Political Weekly, September. Baldwin Richard, 1993, “A Domino Theory of Regionalism”, NBER Working Paper No. 4465, Issued in September. Francis S. and Murali Kallummal, 2011, “Preferential Trading Agreements and Emerging Conflicts between Trade and Industrial Policies: An analysis of India’s recent experience”, Prepared for the UNESCAP ARTNeT Symposium’ Towards a Return of Industrial Policy?, 25-26 July 2011, Bangkok, Thailand Hertel Thomas W, 1997, Global Trade Analysis: Modelling and Applications, (eds) Cambridge University Press, USA. Katti Vijaya, Sunitha Raju and Rajan Sudesh Ratna, 2010, “India’s Regional Trade Agreements: Impact on Indian Economy, Indian Institute of Foreign Trade, New Delhi. Kimura Fukunari, 2006, “International Production and Distribution Networks in East Asia: Eighteen Facts, Mechanics, and Policy Implications”, Asian Economic Policy Review, vol. 1, Issue 2, pp 326–344, December Pomfreta, R., and Sourdin Patricia, 2009, “Have Asian trade agreements reduced trade costs?”,Journal of Asian Economics, vol 20, Issue 3, May, pp 255-268. Tumbarello P., 2007, “Are Regional Trade Agreements in Asia Stumbling or Building Blocks? Some Implications for the Mekong-3 Countries”, IMF Working Paper, March. 18 Appendix Tables Appendix Table 1: India’s base Protection levels in GTAP database rTMS Paddy, Rice Wheat Cereal Grain nec Vegetable, Fruits Oilseeds Sugarcane, Sugar Beet Plant Based Fiber Crop Nec Cattle,sheep, goat, horse Animal Product Nec Raw Milk Wool, Silk‐Worm Forestry Fishing Coal Oil Gas Mineral Nec Meat: Cattle, Sheep, Goats, Horse Meat Products Nec Vegetable Oils And Fats Dairy Products Processed Rice Sugar Food Product Nec Beverages And Tobacco Products Textiles Wearing Apparel Leather Products Wood Products Paper Products, Publishing Pertoleum, Coal Product Chemical Rubber Plastic Mineral Products Nec Ferrous Metal Metal Nec Metal Products Motor Vechicle Parts Transport Equip Electronic Equiptment Machinary and Equipments Manufacturers nec Brazil 0 0 0 31 0 0 10 56 0 6 0 15 5 0 0 0 0 7 30 38 47 0 0 100 32 165 20 15 13 15 11 14 15 15 19 15 15 59 15 5 15 15 Source: GTAP Database China 0 0 0 48 30 0 11 34 0 29 0 17 25 14 35 0 0 8 30 40 64 30 0 0 35 84 18 14 14 15 14 15 15 14 17 15 15 16 14 3 14 13 Russia 0 0 0 38 30 0 0 0 30 20 0 15 23 0 28 10 0 11 0 0 0 0 0 0 0 156 15 15 12 15 15 15 14 15 20 15 15 15 8 10 15 15 South Africa 0 0 0 41 0 0 10 53 0 4 0 15 5 30 41 0 0 11 30 30 65 34 0 100 35 114 16 15 13 15 7 14 15 15 20 15 15 16 11 8 15 15 19 ASEAN 43 0 0 34 30 0 10 63 20 10 0 11 5 28 36 10 0 6 23 27 99 40 55 29 40 78 15 15 13 14 12 14 16 15 19 15 14 18 11 2 13 15 USA 80 0 50 36 30 0 10 42 30 12 0 15 11 29 27 0 0 14 30 70 49 39 0 99 44 117 15 15 13 15 13 15 15 15 19 15 15 17 8 2 13 15 EU­25 5 0 5 44 16 0 13 27 8 3 0 15 11 26 15 0 0 15 18 39 73 37 57 50 39 137 16 15 14 15 14 15 15 15 19 15 15 31 8 4 14 15 Rest of World 28 0 19 36 51 0 10 37 0 1 0 15 6 8 35 10 10 10 15 24 48 30 33 36 33 58 15 9 10 10 13 11 13 15 19 15 15 22 13 2 14 15 Total 156 0 74 308 187 0 75 310 89 85 0 118 92 135 216 30 10 81 175 268 443 210 146 414 257 908 130 113 103 114 99 113 117 118 153 120 119 193 89 37 114 118 Appendix Table 2: Level of Protection Faced by India in other Regions in GTAP database rTMS Paddy, Rice Wheat Cereal Grain nec Vegetable, Fruits Oilseeds Sugarcane, Sugar Beet Plant Based Fiber Crop Nec Cattle,sheep, goat, horse Animal Product Nec Raw Milk Wool, Silk-Worm Forestry Fishing Coal Oil Gas Mineral Nec Meat: Cattle, Sheep, Goats, Horse Meat Products Nec Vegetable Oils And Fats Dairy Products Processed Rice Sugar Food Product Nec Beverages And Tobacco Products Textiles Wearing Apparel Leather Products Wood Products Paper Products, Publishing Pertoleum, Coal Product Chemical Rubber Plastic Mineral Products Nec Ferrous Metal Metal Nec Metal Products Motor Vechicle Parts Transport Equip Electronic Equiptment Machinary and Equipments Manufacturers nec Brazil 0 0 0 11 5 0 0 13 0 2 0 0 8 8 0 0 0 6 0 17 11 0 16 0 11 22 16 20 12 14 13 0 8 12 12 10 18 17 16 14 13 16 China 0 0 0 5 5 0 0 8 0 9 0 0 12 9 0 0 0 0 18 0 7 9 0 0 12 41 7 19 9 6 7 5 9 11 5 8 10 15 11 2 7 11 Russia 0 0 0 6 5 0 5 5 0 6 0 0 8 7 0 0 0 5 14 0 5 8 10 0 13 49 15 20 11 17 11 5 10 15 6 5 11 7 9 8 7 16 South Africa 0 0 3 4 9 0 4 8 0 1 0 0 1 0 0 0 0 0 20 0 9 9 0 12 4 29 21 39 12 17 5 3 3 5 4 2 10 19 0 6 3 4 Source: GTAP Database 20 ASEAN 5 2 0 1 4 0 2 12 0 3 0 0 4 13 1 0 2 2 4 11 3 2 1 13 15 92 10 10 4 6 5 3 3 8 4 3 7 23 2 2 3 1 USA 5 3 1 0 24 0 1 2 0 1 0 2 0 0 0 0 0 0 5 2 3 7 2 6 2 11 7 11 6 0 0 1 2 1 0 0 0 0 0 0 0 0 EU-25 59 7 20 1 0 0 0 2 10 5 0 0 1 3 0 0 0 0 254 18 2 20 109 34 7 20 7 9 3 0 0 0 1 1 0 2 0 4 1 1 0 0 Rest of World 53 5 13 11 55 0 3 12 9 3 0 9 14 7 11 0 14 1 11 11 4 18 19 28 8 69 10 12 7 8 11 8 7 11 10 4 12 15 14 8 7 2 Total 122 16 38 40 107 0 15 62 19 30 0 12 47 48 12 1 16 14 326 59 44 74 157 93 71 331 94 139 65 68 51 25 43 64 41 33 68 100 53 41 42 49 Appendix Table 3: Sector-wise Changes in Industrial Output qo Paddy Wheat Cereal grain Veg. Fruits Oil seeds Sugarcane Plant fiber Crop n.e.c. Cattle sheep Animal product Raw milk Wool silk Meat cattle Meat product Veg edible oil dariy Processed rice Sugar Food pronec beverages T. Agriculture forestry fishing coal oil gas Mineral nec textiles Wear apparel Leather prod Wood prod paper Petro coal Chemical & rubber Minerprodn Ferrous Metal nec Metal produ Motor vechic Transport eq Electro equi Machinery Manufacturers NonAgricultural electricity Gas manufacture water construction trade Transport nes sea Air transport communication Financial ser insurance business recreation Pub admin dwelling Services India Brazil 0.16 0.13 0.13 0.03 0.07 -1.65 0.25 0.12 0.07 0.39 0.26 -0.37 -0.42 10.81 -0.68 0.24 0.2 -4.42 0.3 -4.46 -0.169 0.03 0.19 -0.13 -0.1 0.44 0.79 0.01 2.58 4.3 0.34 -0.32 0.32 -0.07 -4.39 -0.19 -0.46 5.04 2.94 -0.1 -0.75 0.42 0.68 0.03 0.19 0.4 1.16 3.78 -0.04 -0.14 6.02 0.26 3.81 1.014 0.09 -0.19 -0.33 -0.3 -0.2 -0.06 -4.71 -3.89 6.42 -1.11 -0.04 -0.22 0.79 -0.69 0.62 0.34 1.28 0.35 0.64 -0.71 -0.45 0.76 1.61 0.31 -1.08 -2.27 -0.81 1.23 -1.1 -2.04 -1.57 -1.21 0.560 -0.749 0.35 0.25 0.24 0.79 0.34 0.35 0.23 0.32 0.11 0.2 0.16 0.05 0.28 0.27 0.25 0.367 -0.29 -0.34 -0.08 1.68 0.25 0.16 -0.72 -0.12 -0.06 -0.08 0.12 -0.06 0.18 0.28 0.11 0.317 China 0.16 -0.02 0.14 0.18 -1.51 0.39 1.47 0.25 0.18 0.15 0.25 1.06 -0.28 -0.16 -1.96 0.16 0.1 -0.51 -0.2 0.14 -0.001 -0.35 0.05 0.1 -0.22 0.14 -0.14 2 2.7 0.8 -0.13 -0.13 0.1 Russia South Africa -1.68 -0.03 0.43 0.47 -0.21 -1.62 -1.66 6.02 -0.3 -0.01 0.15 -1 -0.3 -3.06 0.35 -0.01 -4.12 -1.61 2.77 0.09 0.230 3.06 0.14 0.08 -0.07 0.1 0.04 -4.82 -12.06 -3.2 -0.79 1.28 0.65 -1.13 -0.41 -0.07 0.3 -0.54 0.51 0.23 -0.59 -0.3 -2.02 0.06 17.71 -0.5 -3.85 -0.57 0.1 4.07 1.23 -0.07 0.22 -0.105 0.62 -0.01 0.03 -0.11 0.47 0.23 -8.62 -14.35 -12.18 -0.37 0.21 0.07 0.13 3.94 0.33 -0.08 -0.41 0.28 -0.08 0.41 -0.11 0.07 -0.03 -0.41 0.86 0.2 0.82 -0.04 12.89 -0.14 0.75 -1.39 0.252 0.16 0.06 0.17 0.39 0.14 0.07 0.11 -0.09 0.2 0.17 -0.01 0.19 0.16 0.21 0.21 0.214 ASEAN USA EU_25 0.2 0.29 0.03 0.04 -1.34 -0.01 0.17 0.17 -0.02 0 -0.02 0.42 -0.03 -0.03 0.2 -0.02 -0.02 -0.01 -0.03 -0.03 -0.016 0.02 -0.01 0.03 0.04 0.24 0.01 0 0.04 -0.25 0 -0.02 -0.04 0.82 -0.1 -0.03 -0.05 -0.12 0.54 1.18 7.37 0.24 1.39 1.61 0.29 0.94 1.72 -0.04 0.09 0.05 -0.08 -0.04 -0.1 0.12 0.07 -0.04 0.01 0.07 0.12 0.01 -0.02 -0.04 -0.01 0.02 0.02 -0.05 0.04 0.08 -0.04 -0.05 -0.06 0.01 -0.01 -0.05 -0.02 0.02 -0.24 -0.03 -0.04 -0.08 0.05 0.04 -0.11 0.569 0.200 -0.005 -0.002 -0.042 -0.034 0.49 0.17 0.27 0.36 0.26 0.18 -0.08 -0.11 0.09 0.38 -0.06 0.07 0.21 0.27 0.23 0.259 0.91 0.2 0.23 2.35 -0.53 0.01 0.24 -0.19 0.09 0.09 0.09 0.31 0.23 0.5 0.21 0.289 -0.04 -0.01 -0.03 -0.13 -0.02 0.04 0.07 0.03 0 -0.03 0.02 0.02 -0.03 -0.06 -0.05 -0.029 -0.02 -0.02 -0.03 -0.05 -0.03 -0.02 0.02 -0.02 -0.03 -0.03 -0.03 -0.03 -0.04 -0.03 -0.02 -0.031 -0.03 0 -0.04 -0.07 -0.04 0 0.1 -0.02 -0.03 -0.03 -0.02 -0.03 -0.04 -0.05 -0.04 -0.039 -0.05 -0.03 -0.03 -0.06 -0.03 -0.01 0.08 0 -0.03 -0.03 -0.02 -0.03 -0.03 -0.04 -0.02 -0.033 Source: Simulation Result 21 0.09 0 0.02 0 0.55 -0.03 -0.03 0.07 0 -0.01 -0.04 0.13 0.13 0.07 0.17 -0.04 0.01 0 -0.05 -0.05 -0.006 0.09 -0.02 0.07 0.08 0.28 0.05 -0.2 -0.25 -0.32 0.01 -0.02 -0.05 Rest of World -0.02 0.12 -0.03 0.03 -0.43 0.07 0.06 0.09 0.02 0.02 0 0.01 0.13 0.09 -1.21 0.02 -0.04 0.09 -0.06 -0.08 -0.103 -0.27 -0.03 0.12 0.05 0.29 0.02 -0.3 -0.07 -0.39 0.22 -0.04 -0.06 0 0.09 0 -0.02 -0.41 -0.05 -0.02 0.05 -0.02 0.01 -0.03 0.29 0 0.09 -0.1 -0.02 -0.01 -0.06 -0.06 -0.04 0.002 -0.01 -0.02 0.08 0.05 0.26 -0.04 -0.17 -0.1 -0.74 0.03 -0.03 -0.06 Appendix Table 4: Demand for Unskilled Labour qfe[UnSkLab**] Paddy wheat Cereal grain Veg. fruits oilseeds sugarcane Plant fiber Crop nec Cattle sheep Animal product Raw milk Wool silk Meat cattle Meat product Veg edible oil dariy Processed rice Sugar Food pronec beverages T. Agriculture forestry fishing coal oil gas Mineral nec textiles Wear apparel Leather prod Wood prod paper Petro coal Chemical & rubber Minerprodn Ferrous Metal nec Metal produ Motor vechic Transport eq Electro equi Machinery Manufacturers Non-Agricultural electricity Gas manufacture water construction trade Transport nes sea Air transport communication Financial ser insurance business recreation Pub admin dwelling Services India 0.22 0.18 0.19 0.08 0.12 -1.75 0.32 0.17 0.12 0.47 0.33 -0.36 0.01 11.12 -0.25 0.62 0.36 -4.03 0.68 -4.05 0.085 0.09 0.34 -0.12 -0.06 0.74 0.97 0.21 2.77 4.78 0.6 0.09 0.91 1.41 1.21 0.97 1.81 0.94 1.05 -0.47 0.06 1.37 2.03 0.814 0.89 0.66 0.64 1 1.04 0.75 0.64 0.73 0.73 0.78 0.73 0.34 0.57 0.4 1 0.782 Brazil 0.14 -4.31 0.03 -0.25 5.43 3.27 0.12 -0.55 0.65 0.93 0.25 0.42 0.79 1.56 4.26 0.42 0.27 6.23 0.64 4.16 1.380 0.17 -0.24 -0.51 -0.45 -0.28 -0.04 -4.27 -3.83 6.73 -0.84 0.12 0.22 -0.23 0.75 -0.55 -1.75 -0.62 1.75 -0.81 -1.51 -1.17 -0.89 -0.504 0.05 0 0.25 2.33 0.43 0.32 -0.56 0.04 0.42 0.05 0.29 0.32 0.19 0.28 0.85 0.438 China 0.23 0.04 0.21 0.25 -1.54 0.47 1.61 0.32 0.25 0.21 0.33 1.18 -0.06 0.01 -1.78 0.35 0.36 -0.31 -0.02 0.4 0.195 -0.39 0.1 0.2 -0.31 0.83 -0.14 2.2 2.89 1 0.08 0.07 0.33 0.36 0.5 0.11 -0.21 0.47 0.14 0.55 0.15 0.25 0.24 0.414 0.46 0.27 0.37 0.57 0.36 0.36 0.43 0.29 0.52 0.47 0.25 0.42 0.3 0.31 0.54 0.418 Russia -1.66 0.08 0.56 0.6 -0.11 -1.6 -1.64 6.49 -0.2 0.1 0.27 -0.94 0.22 -2.63 0.82 0.44 -3.59 -1.19 3.21 0.54 0.522 3.65 0.34 0.17 0.01 0.29 0.13 -4.76 -11.67 -3.11 -0.63 1.85 1.33 4.32 -0.14 1.37 0.76 1.01 0.27 12.94 0.2 0.93 -1.21 0.770 0.98 0.41 0.47 0.88 1.24 0.78 0.54 0.47 0.47 0.64 0.45 0.63 0.56 0.4 1.05 0.695 Source: Simulation Result 22 South Africa -1.03 -0.29 0.06 0.45 -0.42 0.66 0.37 -0.47 -0.17 -1.94 0.19 18.41 -0.06 -3.49 0.08 0.55 4.9 2.12 0.45 0.97 0.316 0.92 0.1 0.2 -0.05 1.07 0.35 -8.28 -14.16 -11.74 0.04 0.76 1 1.61 1.19 1.9 8.53 0.66 2.1 2.04 0.9 1.5 2.73 0.072 1.75 0.98 0.9 2.96 0.34 0.95 1.23 0.72 1.04 0.85 0.85 1.16 0.53 0.71 1.5 0.858 ASEAN -0.04 0.11 -0.05 0.01 -0.5 0.05 0.05 0.08 0 0 -0.02 -0.01 0.09 0.06 -1.25 -0.01 -0.08 0.05 -0.1 -0.12 -0.143 -0.31 -0.05 0.16 0.06 0.41 0.01 -0.34 -0.11 -0.43 0.18 -0.08 -0.11 -0.14 -0.08 0.04 0.01 -0.12 -0.08 -0.14 0.08 0.04 -0.08 -0.055 -0.1 -0.07 -0.09 -0.16 -0.07 -0.01 0.01 -0.03 -0.05 -0.08 -0.03 -0.01 -0.06 -0.07 -0.12 -0.070 USA 0.18 0.29 0.01 0.02 -1.44 -0.03 0.16 0.16 -0.05 -0.03 -0.04 0.42 -0.04 -0.03 0.18 -0.03 -0.04 -0.02 -0.05 -0.05 -0.053 0.02 -0.02 0.04 0.06 0.37 0.01 -0.01 0.03 -0.26 0 -0.03 -0.06 -0.05 0 0.06 0.11 0 -0.03 -0.04 -0.02 0.01 0.01 -0.007 -0.05 -0.05 -0.04 -0.06 -0.04 -0.03 0 -0.04 -0.05 -0.04 -0.03 -0.03 -0.05 -0.04 -0.06 -0.042 EU_25 0.1 0.01 0.03 0.01 0.57 -0.03 -0.03 0.07 0.01 0 -0.04 0.14 0.11 0.04 0.15 -0.06 -0.02 -0.02 -0.07 -0.09 -0.009 0.1 -0.05 0.12 0.11 0.4 0.05 -0.22 -0.27 -0.35 -0.01 -0.05 -0.09 -0.07 -0.08 0.02 0.06 -0.06 -0.07 -0.08 -0.01 -0.03 -0.07 -0.063 -0.07 -0.04 -0.07 -0.1 -0.08 -0.04 0.06 -0.06 -0.06 -0.05 -0.04 -0.07 -0.07 -0.06 -0.1 -0.069 Rest of World 0 0.09 -0.01 -0.03 -0.43 -0.06 -0.02 0.04 -0.02 0 -0.04 0.3 -0.02 0.07 -0.13 -0.05 -0.05 -0.08 -0.08 -0.07 -0.032 -0.02 -0.04 0.13 0.07 0.41 -0.05 -0.19 -0.12 -0.76 0 -0.05 -0.1 -0.15 -0.05 0 -0.27 -0.05 -0.07 -0.1 0.03 0.02 -0.13 -0.059 -0.09 -0.06 -0.07 -0.08 -0.06 -0.04 0.05 -0.02 -0.06 -0.06 -0.04 -0.06 -0.06 -0.05 -0.07 -0.055 Appendix Table 5: Demand for Skilled Labour qfe[SkLab**] Paddy wheat Cereal grain Veg. fruits oilseeds sugarcane Plant fiber Crop nec Cattle sheep Animal product Raw milk Wool silk Meat cattle Meat product Veg edible oil dariy Processed rice Sugar Food pronec beverages T. Agriculture forestry fishing coal oil gas Mineral nec textiles Wear apparel Leather prod Wood prod paper Petro coal Chemical & rubber Minerprodn Ferrous Metal nec Metal produ Motor vechic Transport eq Electro equi Machinery Manufacturers Non­Agricultural electricity Gas manufacture water construction trade Transport nes sea Air transport communication Financial ser insurance business recreation Pub admin dwelling Services India 0.22 0.18 0.19 0.08 0.12 ‐1.75 0.32 0.17 0.12 0.47 0.33 ‐0.36 0.01 11.12 ‐0.25 0.62 0.36 ‐4.03 0.68 ‐4.05 0.229 0.09 0.34 ‐0.12 ‐0.06 0.74 0.97 0.21 2.77 4.78 0.6 0.09 0.91 1.41 1.21 0.97 1.81 0.94 1.05 ‐0.47 0.06 1.37 2.03 0.870 0.89 0.66 0.64 1.00 1.04 0.75 0.64 0.73 0.73 0.78 0.73 0.34 0.57 0.4 1.00 0.573 Brazil 0.14 ‐4.31 0.03 ‐0.25 5.43 3.27 0.12 ‐0.55 0.65 0.93 0.25 0.42 0.79 1.56 4.26 0.42 0.27 6.23 0.64 4.16 1.706 0.17 ‐0.24 ‐0.51 ‐0.45 ‐0.28 ‐0.04 ‐4.27 ‐3.83 6.73 ‐0.84 0.12 0.22 ‐0.23 0.75 ‐0.55 ‐1.75 ‐0.62 1.75 ‐0.81 ‐1.51 ‐1.17 ‐0.89 ­0.508 0.05 0 0.25 2.33 0.43 0.32 ‐0.56 0.04 0.42 0.05 0.29 0.32 0.19 0.28 0.85 0.307 Source: Simulation Result China 0.23 0.04 0.21 0.25 ‐1.54 0.47 1.61 0.32 0.25 0.21 0.33 1.18 ‐0.06 0.01 ‐1.78 0.35 0.36 ‐0.31 ‐0.02 0.4 0.094 ‐0.39 0.1 0.2 ‐0.31 0.83 ‐0.14 2.2 2.89 1 0.08 0.07 0.33 0.36 0.5 0.11 ‐0.21 0.47 0.14 0.55 0.15 0.25 0.24 0.456 0.46 0.27 0.37 0.57 0.36 0.36 0.43 0.29 0.52 0.47 0.25 0.42 0.3 0.31 0.54 0.364 Russia ‐1.66 0.08 0.56 0.6 ‐0.11 ‐1.6 ‐1.64 6.49 ‐0.2 0.1 0.27 ‐0.94 0.22 ‐2.63 0.82 0.44 ‐3.59 ‐1.19 3.21 0.54 1.113 3.65 0.34 0.17 0.01 0.29 0.13 ‐4.76 ‐11.67 ‐3.11 ‐0.63 1.85 1.33 4.32 ‐0.14 1.37 0.76 1.01 0.27 12.94 0.2 0.93 ‐1.21 0.911 0.98 0.41 0.47 0.88 1.24 0.78 0.54 0.47 0.47 0.64 0.45 0.63 0.56 0.4 1.05 0.507 23 South Africa ‐1.03 ‐0.29 0.06 0.45 ‐0.42 0.66 0.37 ‐0.47 ‐0.17 ‐1.94 0.19 18.41 ‐0.06 ‐3.49 0.08 0.55 4.9 2.12 0.45 0.97 0.443 0.92 0.1 0.2 ‐0.05 1.07 0.35 ‐8.28 ‐14.16 ‐11.74 0.04 0.76 1 1.61 1.19 1.9 8.53 0.66 2.1 2.04 0.9 1.5 2.73 0.430 1.75 0.98 0.9 2.96 0.34 0.95 1.23 0.72 1.04 0.85 0.85 1.16 0.53 0.71 1.50 0.794 ASEAN ‐0.04 0.11 ‐0.05 0.01 ‐0.5 0.05 0.05 0.08 0 0 ‐0.02 ‐0.01 0.09 0.06 ‐1.25 ‐0.01 ‐0.08 0.05 ‐0.1 ‐0.12 ­0.341 ‐0.31 ‐0.05 0.16 0.06 0.41 0.01 ‐0.34 ‐0.11 ‐0.43 0.18 ‐0.08 ‐0.11 ‐0.14 ‐0.08 0.04 0.01 ‐0.12 ‐0.08 ‐0.14 0.08 0.04 ‐0.08 ­0.041 ‐0.1 ‐0.07 ‐0.09 ‐0.16 ‐0.07 ‐0.01 0.01 ‐0.03 ‐0.05 ‐0.08 ‐0.03 ‐0.01 ‐0.06 ‐0.07 ‐0.12 ­0.064 USA 0.18 0.29 0.01 0.02 ‐1.44 ‐0.03 0.16 0.16 ‐0.05 ‐0.03 ‐0.04 0.42 ‐0.04 ‐0.03 0.18 ‐0.03 ‐0.04 ‐0.02 ‐0.05 ‐0.05 ­0.047 0.02 ‐0.02 0.04 0.06 0.37 0.01 ‐0.01 0.03 ‐0.26 0 ‐0.03 ‐0.06 ‐0.05 0 0.06 0.11 0 ‐0.03 ‐0.04 ‐0.02 0.01 0.01 ­0.009 ‐0.05 ‐0.05 ‐0.04 ‐0.06 ‐0.04 ‐0.03 0 ‐0.04 ‐0.05 ‐0.04 ‐0.03 ‐0.03 ‐0.05 ‐0.04 ‐0.06 ­0.039 EU_25 0.1 0.01 0.03 0.01 0.57 ‐0.03 ‐0.03 0.07 0.01 0 ‐0.04 0.14 0.11 0.04 0.15 ‐0.06 ‐0.02 ‐0.02 ‐0.07 ‐0.09 ­0.035 0.1 ‐0.05 0.12 0.11 0.4 0.05 ‐0.22 ‐0.27 ‐0.35 ‐0.01 ‐0.05 ‐0.09 ‐0.07 ‐0.08 0.02 0.06 ‐0.06 ‐0.07 ‐0.08 ‐0.01 ‐0.03 ‐0.07 ­0.055 ‐0.07 ‐0.04 ‐0.07 ‐0.1 ‐0.08 ‐0.04 0.06 ‐0.06 ‐0.06 ‐0.05 ‐0.04 ‐0.07 ‐0.07 ‐0.06 ‐0.10 ­0.067 Rest of World 0 0.09 ‐0.01 ‐0.03 ‐0.43 ‐0.06 ‐0.02 0.04 ‐0.02 0 ‐0.04 0.3 ‐0.02 0.07 ‐0.13 ‐0.05 ‐0.05 ‐0.08 ‐0.08 ‐0.07 ­0.058 ‐0.02 ‐0.04 0.13 0.07 0.41 ‐0.05 ‐0.19 ‐0.12 ‐0.76 0 ‐0.05 ‐0.1 ‐0.15 ‐0.05 0 ‐0.27 ‐0.05 ‐0.07 ‐0.1 0.03 0.02 ‐0.13 ­0.050 ‐0.09 ‐0.06 ‐0.07 ‐0.08 ‐0.06 ‐0.04 0.05 ‐0.02 ‐0.06 ‐0.06 ‐0.04 ‐0.06 ‐0.06 ‐0.05 ‐0.07 ­0.053 Appendix Table 6: Sector-wise Changes in Exports qxw Paddy Wheat Cereal grain Veg. Fruits Oil seeds Sugarcane Plant fiber Crop n.e.c. Cattle sheep Animal product Raw milk Wool silk Meat cattle Meat product Veg edible oil dariy Processed rice Sugar Food pronec beverages T. Agriculture forestry fishing coal oil gas Mineral nec textiles Wear apparel Leather prod Wood prod paper Petro coal Chemical & rubber Minerprodn Ferrous Metal nec Metal produ Motor vechic Transport eq Electro equi Machinery Manufacturers Non-Agricultural electricity Gas manufacture water construction trade Transport nes sea Air transport communication Financial ser insurance business recreation Pub admin dwelling Services India Brazil -0.81 -0.86 -0.43 0.36 2.65 5.13 10.58 4.38 -0.49 -0.26 9.71 10.46 -1.41 15.85 2.96 -0.86 0.72 4.9 2.51 2.14 1.642 0.9 -1.18 1.25 -0.69 -22.01 1.02 4.7 3.33 8.5 -0.03 1.76 0.66 6.53 0.9 2.56 11.19 3.38 2.82 3.91 5.16 6.14 3.31 21.865 0.46 -1.36 -1.32 -0.35 -1.14 -0.39 -0.07 -0.4 -1.43 -1.56 -1.42 -0.22 -0.22 -0.31 0.14 -3.375 -6.59 -6.02 -2.76 -2.76 7.22 -3.85 3.9 -3.94 -4.96 -1.91 1.86 1.58 0.18 1.93 8.27 -5.54 -1.43 10.52 -0.33 35.55 3.049 -0.84 -0.95 0.02 1.13 2.27 0.06 4.6 3.58 14.17 -2.63 0.05 -0.85 -0.32 -1.7 -0.92 -2.02 -1.67 2.62 -2.55 1.64 -1.42 -2.19 0.707 -3.35 -3.82 -3.56 -3.35 -2.64 -1.54 -0.95 -1.43 -3.35 -2.84 -2.77 -3.3 -2.4 -2.45 0.11 -7.337 China Russia -3.99 -2.86 -0.95 1.28 0.47 -0.54 2.61 1.68 -1.56 -0.26 6.14 6.65 4.66 -0.11 1.74 -0.14 0.44 -0.76 0.37 0 0.334 2.26 -0.61 -0.36 0.91 0.38 0.33 3.35 3.63 2.03 -0.3 -0.26 1.16 1.89 1.14 -0.18 0.98 0.89 -0.12 1.99 0 0.57 0.58 19.656 -0.89 -0.69 -2.08 -0.86 -1.16 -1.18 -0.26 -0.58 -1.64 -1.81 -1.4 -1.3 -1.13 -1.2 0.6 -6.290 -0.71 -3.1 -1.17 13.74 2.37 2.65 0.08 9.75 -0.83 1.62 7.49 13.52 7.6 0.43 -0.59 -1.33 0.28 1.93 14.75 -0.28 -0.356 7.14 -1.27 -0.42 -0.7 -2.7 -0.02 4.63 3.92 11.44 -0.92 5.06 0.84 8.59 -0.64 0.95 0.64 9.99 -0.29 22.17 5.75 6.23 0.89 1.964 -1.92 -0.84 -1.04 -0.98 -1.65 -0.57 -0.45 -0.67 -0.96 -0.79 -1.26 -1.36 -0.79 -0.41 0.14 -1.292 Source: Simulation Result 24 South Africa -1.43 -1.14 -0.48 0.66 -0.21 2.77 1.09 0.6 -0.4 0.68 11.11 32.12 1.72 1.48 2.24 -0.71 4.92 5.89 0.65 0.02 0.533 9.22 0.09 -0.58 -0.18 -22.03 0.19 9.85 8.41 11.12 -0.42 2.4 0.12 4.4 -0.25 1.57 7.6 0.95 3.68 2.29 -0.02 1.16 15.62 10.963 -0.46 -1.58 -1.52 -0.51 -0.88 -0.71 -0.28 -0.46 -0.99 -1.53 -1.51 -1.34 -0.31 0.07 0.21 -0.586 ASEAN 0.94 0.47 0.18 0.12 0.3 -0.25 0.4 0.21 0.18 0.13 0.12 1.22 0.28 0.74 -1.8 0.14 -0.12 0.3 -0.15 -0.42 -0.268 -2.2 0.1 0.19 0.02 0.55 0.05 -0.71 -0.13 -0.56 0.27 -0.09 -0.15 -0.17 -0.01 0.05 0.03 -0.2 -0.06 -0.25 0.12 0.08 -0.1 -0.019 0.13 0.34 0.29 0.1 0.2 0.22 0.13 0.08 0.15 0.13 0.14 0.1 0.08 0.07 -0.04 1.438 USA EU_25 0.48 0.39 0.13 0.16 -3.22 0.21 0.53 0.37 0.22 0.22 -0.07 0.69 -0.34 -0.19 0.78 0.16 -0.04 0.42 -0.23 -0.02 -0.151 0.26 0.04 0.7 0.16 1.32 0.02 -0.21 0 -1.51 0.08 0.02 -0.01 -0.12 0.1 0.15 0.13 0.05 0.02 -0.13 -0.19 0.07 -0.22 -0.381 0.31 0.37 0.12 0.14 0.11 0.12 0.16 0.03 0.07 0.04 0.08 0.03 0.02 0.06 -0.02 1.104 0.21 0.06 0.1 0.01 1.16 -0.2 0.05 0.14 0 0.03 -0.34 0.17 0.36 0.17 0.38 -0.01 0 0.13 -0.07 -0.07 0.046 0.38 0 0.3 0.09 0.41 0.14 -0.39 -1.16 -0.8 0.05 0.02 -0.07 -0.05 -0.08 0.08 0.11 -0.1 -0.05 -0.1 0 0 -0.15 -0.545 0.15 0.25 0.12 0.05 0.12 0.19 0.12 0 0.04 0.03 0.06 0.07 0.04 0.02 -0.04 1.348 Rest of World 1.66 0.3 0.12 -0.06 -1.43 -0.36 0.11 0.05 0.01 0.09 -0.31 1.34 -0.12 -0.29 -0.45 0.08 -0.09 -0.76 -0.25 -0.06 0.044 -0.6 0.04 0.1 0.08 0.56 0.02 -0.4 -0.39 -2.03 0.1 -0.07 -0.12 -0.29 -0.01 -0.01 -0.53 -0.09 -0.06 -0.16 0.07 0.07 -0.45 -0.252 0.07 0.2 0.12 0.12 0.17 0.18 0.13 0.05 0.03 0.04 0.05 0.02 0.02 0.02 -0.03 0.523 Appendix Table 7: Sector-wise Changes in Imports qim Paddy Wheat Cereal grain Veg. Fruits Oil seeds Sugarcane Plant fiber Crop n.e.c. Cattle sheep Animal product Raw milk Wool silk Meat cattle Meat product Veg edible oil dariy Processed rice Sugar Food pronec beverages T. Agriculture forestry fishing coal oil gas Mineral nec textiles Wear apparel Leather prod Wood prod paper Petro coal Chemical & rubber Minerprodn Ferrous Metal nec Metal produ Motor vechic Transport eq Electro equi Machinery Manufacturers Non-Agricultural electricity Gas manufacture water construction trade Transport nes sea Air transport communication Financial ser insurance business recreation Pub admin dwelling Services 54.73 9.9 0.76 2.79 4.37 5.93 5.08 17.67 1.93 6.99 29.51 11.75 19.29 4.81 2.91 1.91 22.54 91.02 5.84 67.46 3.039 2 4.44 1.62 0.43 15.9 0.82 23.22 16.57 11.11 3.1 3.18 1.42 6.7 0.72 1.97 3.39 7.78 12.61 1.87 5.73 3.22 2.68 18.12 1.97 5.06 6.15 5.35 4.06 2.84 6.47 2.76 1.89 1.069 4 1.16 -0.41 0.55 -0.56 -0.62 24.89 115.25 50.89 4.07 2.58 1.21 48 1.32 0.81 2.14 2.13 7.63 3.04 5.66 0.97 0.84 8.12 4.35 3.81 23.71 2.58 0.85 1.58 0.75 6.79 0.84 1.745 7.12 0.87 1.51 0.52 11.86 0.58 3.01 1.21 9.64 1.97 1.76 0.98 8.76 2.41 0.66 1.37 6.49 2.11 -0.04 0.96 0.36 0.69 2.68 6.43 4.2 4.74 1.61 1.12 2.26 4.66 2.3 0.45 2.171 5.53 1.42 1.07 1.81 2.89 0.54 1.04 9.51 4.63 2.01 1.7 1.72 0.14 0.23 0.41 0.42 0.18 3.83 0.39 1.41 -0.07 1.46 10.26 -2.3 10.91 45.2 2.23 1.68 0.72 0.96 3.08 0.94 1.703 2.49 0.37 1.2 0.07 14.59 1.63 16.65 109.37 43.3 4.66 1.1 2.68 -1.51 -0.15 -0.27 -0.36 -1.11 0.03 -0.24 -0.5 -0.15 -0.17 -0.38 -0.54 -0.76 -1.09 -0.76 -0.1 -0.11 -0.17 -0.12 -0.08 -0.215 -0.07 -0.12 -0.08 -0.13 0.14 -0.07 -0.31 -0.34 -0.34 -0.13 -0.09 -0.04 -0.63 -0.12 -0.07 -0.14 -1.04 -0.04 -0.25 -0.45 -0.13 -0.24 -0.37 -0.14 -0.13 -0.55 -0.39 -0.15 -0.05 -0.2 -0.13 -0.06 -0.125 -0.06 -0.05 -0.34 -0.08 -0.28 -0.05 -0.14 -0.15 -0.14 -0.21 -0.14 -0.12 -0.09 -0.07 -0.1 -0.04 -0.45 0.1 -0.15 -0.3 0.04 -0.07 -0.16 -0.09 -0.47 -0.24 -0.32 -0.05 -0.05 -0.1 -0.08 -0.06 -0.113 -0.44 -0.05 -0.14 -0.07 -0.14 -0.06 -0.16 -0.18 -0.16 -0.09 -0.08 -0.06 Rest of World -0.22 -0.12 -0.08 -0.09 -0.24 0.01 -0.18 -0.34 -0.06 -0.18 -0.22 -0.54 -0.43 -0.52 -0.19 -0.08 -0.07 -0.5 -0.09 -0.07 -0.150 -0.52 -0.14 -0.12 -0.12 -0.11 -0.11 -0.2 -0.3 -0.17 -0.13 -0.12 -0.07 4.15 2.47 1.34 2.03 1.49 -0.12 -0.12 -0.07 -0.08 2.15 3.7 2.13 11.26 4.65 5.6 2.71 2.7 4.26 2.913 1.600 0.600 1.140 1.010 0.990 0.460 0.340 0.360 0.210 0.910 0.590 0.400 0.460 0.320 0.140 0.517 6.45 7.42 3.21 10.52 2.54 4.29 5.14 5.68 34.05 5.122 1.120 1.450 1.540 3.510 1.570 0.940 0.400 0.650 0.680 1.420 1.400 1.810 0.970 1.260 0.110 1.318 1.2 1.99 1.75 1.47 1.25 2.24 0.37 0.96 10.98 1.209 1.620 0.390 1.250 0.550 0.720 0.790 0.730 0.530 1.040 1.110 0.740 0.860 0.800 0.850 0.600 0.761 3.67 1.96 5.34 3.59 0.62 1.71 1.72 1.29 8.59 2.386 1.890 1.010 0.810 0.880 1.090 0.810 0.570 0.620 0.590 0.790 0.640 0.850 0.630 0.510 0.140 0.796 4.97 2.18 4.91 5.98 2.24 1.42 2.33 2.68 8.15 5.624 1.940 0.840 0.010 2.720 0.680 0.540 0.370 0.250 0.600 0.660 0.900 1.010 0.390 0.520 0.210 0.680 -0.15 -0.07 -0.02 -0.12 -0.09 -0.13 0.04 -0.06 -0.16 -0.065 -0.100 -0.290 -0.170 -0.150 -0.140 -0.030 -0.010 -0.050 -0.110 -0.100 -0.040 -0.030 -0.080 -0.070 -0.040 -0.065 -0.24 -0.25 -0.22 -0.26 -0.07 -0.22 -0.17 -0.18 -0.24 -0.151 -0.190 -0.350 -0.130 -0.090 -0.070 -0.080 -0.110 -0.050 -0.080 -0.060 -0.050 -0.050 -0.060 -0.060 -0.020 -0.063 -0.1 -0.07 -0.1 -0.1 -0.07 -0.09 -0.1 -0.09 -0.21 -0.090 -0.100 -0.250 -0.130 -0.110 -0.120 -0.060 -0.020 -0.060 -0.070 -0.050 -0.060 -0.080 -0.070 -0.080 -0.040 -0.075 -0.16 -0.15 -0.22 -0.12 -0.07 -0.07 -0.1 -0.08 -0.16 -0.112 -0.060 -0.280 -0.110 -0.090 -0.090 -0.060 0.030 -0.060 -0.060 -0.050 -0.050 -0.050 -0.050 -0.050 -0.030 -0.052 India Brazil China South Africa Russia Source: Simulation Result 25 ASEAN USA EU_25 Appendix Table 8: Trade balance in Million US $ India Paddy wheat Cereal grain Veg. fruits oilseeds sugarcane Plant fiber Crop nec Cattle sheep Animal product Raw milk Wool silk Meat cattle Meat product Veg edible oil dariy Processed rice Sugar Food pronec beverages T. Agriculture forestry fishing coal oil gas Mineral nec textiles Wear apparel Leather prod Wood prod paper Petro coal Chemical & rubber Minerprodn Ferrous Metal nec Metal produ Motor vechic Transport eq Electro equi Machinery Manufacturers NonAgricultural electricity Gas manufacture water construction trade Transport nes sea Air transport communication Financial ser insurance business recreation Pub admin dwelling Services Brazil China Russia South Africa ASEAN USA EU_25 Rest of World -1.2 -3.6 -0.6 -31.3 8.4 0.4 13.0 -0.6 -0.1 -5.2 -0.1 -22.8 -7.3 1.0 -80.7 -1.7 8.6 -299.8 38.9 -283.8 -668.6 -10.7 -1.3 -29.0 -119.7 -0.5 1.5 -162.5 175.6 162.8 -10.0 -49.0 -10.2 163.3 -6.2 -23.8 -15.9 -23.5 460.1 0.0 17.5 -114.7 -0.9 -4.4 -0.2 0.2 32.7 130.4 385.1 -10.8 -4.1 346.4 -9.2 292.6 1451.2 -0.5 -0.9 3.2 -6.1 0.7 61.0 -332.4 -323.2 318.9 -87.0 -1.7 -58.5 -422.4 -7.7 -20.4 -4.3 25.8 -191.2 -0.2 -74.6 4.8 -1.6 -12.6 -0.7 -38.3 -26.1 -71.9 -114.1 -4.1 1.6 -2.0 -257.6 -2.2 -797.0 -194.7 -5.1 -7.2 -177.6 0.5 -114.3 1087.9 1984.7 298.7 -96.3 -200.9 -42.1 -304.9 -0.2 -22.0 -2.3 -22.1 -3.7 0.0 0.2 -12.8 -0.1 0.3 1.4 0.3 -62.9 -102.0 -12.1 -16.2 -3.9 -64.1 364.7 -7.2 35.4 203.3 -2.2 -12.2 -284.0 -419.6 2.0 -24.4 -506.4 -54.8 -61.0 90.4 171.7 984.8 0.0 -0.8 -0.9 15.7 -0.1 0.1 0.5 -3.7 0.0 -0.3 -0.1 31.3 -11.1 -84.2 -9.8 -2.5 -1.0 15.5 -13.7 -0.5 -65.8 7.5 0.3 -9.1 -7.3 0.0 3.0 -210.9 -860.9 -237.6 -32.0 18.8 -8.2 121.6 2.9 2.9 1.2 5.9 17.5 0.0 3.8 10.9 0.5 1.7 0.0 0.1 3.8 12.2 -213.8 3.7 -8.0 4.6 -24.2 -6.8 -180.9 -33.5 0.9 13.5 27.2 81.5 0.9 -70.2 -19.1 -51.8 34.5 -2.4 -16.6 -58.0 3.2 22.1 4.6 18.9 -246.7 0.0 18.7 29.6 1.9 5.5 0.1 0.2 0.9 -4.2 26.3 5.7 -0.8 2.1 -12.9 7.0 -117.8 3.6 1.5 20.3 31.3 7.3 -0.4 17.7 76.6 -9.4 96.7 29.9 13.3 -52.9 0.7 5.7 4.9 11.0 25.0 -0.1 2.0 56.4 -1.1 4.4 -0.2 0.7 59.2 61.6 61.1 8.0 0.5 8.5 -11.4 -20.0 276.9 24.0 4.1 3.4 -55.1 -91.6 30.5 -183.1 -464.4 -216.7 87.6 74.8 -12.6 -37.4 8.6 39.7 14.5 -8.3 -84.4 -0.1 12.5 31.9 1.4 10.8 -0.3 25.9 13.6 56.7 -36.1 18.3 6.1 -23.8 -84.2 0.2 3.0 -10.8 4.3 16.5 597.5 425.5 7.2 -230.8 -157.8 -256.9 89.3 25.4 -47.6 -563.7 -4.8 -36.0 -67.7 -52.5 -14.1 -151.8 -148.2 -72.3 302.5 -134.5 -60.2 -75.3 -118.2 -135.0 191.1 -247.4 -415.9 -766.7 -180.4 -2656.9 109.1 -395.1 -232.0 159.0 -211.3 86.7 -140.4 -388.8 -30.4 1185.6 -86.4 144.8 58.8 10.2 -57.1 428.7 -114.2 27.8 -153.5 346.6 -38.0 87.7 668.8 -52.3 -41.7 -16.5 -96.9 -164.2 114.3 -753.9 3.3 4.9 1.1 -3.3 9.7 3.1 127.6 72.1 -5.1 120.2 39.7 54.8 63.1 73.1 172.1 -27.7 73.0 405.9 56.5 1146.1 -7.6 126.1 117.6 -21.2 -11.8 -25.6 277.4 313.2 23.3 -45.0 42.3 66.7 -494.5 13.5 -44.8 -53.2 430.0 532.4 -137.0 253.6 -1.18 0 -0.15 -8.44 -11.45 -9.48 -6.87 -2.05 -12.72 -24.03 -10.71 -47.14 -2.82 -5 0 -142.04 -19.51 -0.31 -0.62 -1.77 -35.12 -19.89 -19.17 -16.08 -8.7 -19.4 -16.76 -231.11 -12.42 -39.01 0 -439.87 -4.74 -0.95 -2.09 -17.17 -315.42 -124.74 -0.88 -30.11 -20.93 -19.35 -37.59 -134.65 -50.97 -69.66 0 -829.25 -17.89 -16.61 -0.67 -38.6 -38.21 -60.73 -11.13 -26.56 -9.23 -12.42 -8.82 -101.24 -15.29 -16.07 0 -373.47 -9.88 -0.01 -0.59 -0.85 -15.03 -13.29 -1.54 -6.18 -3.36 -6.11 -7.67 -11.35 -4.97 -3.27 0 -84.1 0.18 2.04 0.32 4.74 30.66 34.19 18.05 9.87 4.49 6.04 4.96 26.1 7.41 5.29 0 154.34 5.79 2.05 0.58 5.73 27.91 59.27 16.1 18.87 8.42 7.43 22.86 35.48 3.35 37.55 0 251.39 35.75 6.48 1.91 31.35 173.03 263.43 143.05 34.93 30.21 49.7 31.87 374.56 51.25 47.19 0 1274.71 11.46 7.32 1.31 25.01 183.55 195.39 106.48 51.12 11.82 18.1 21.85 89.06 24.44 42.96 0 789.87 Source: Simulation Result 26