SWP769 The Costs of Protectionism to Developing Countries An Analysis for Selected Agricultural Products Joachim Zietz Alberto Valdes G= ii . 4 WORLD BANK STAFF WORKING PAPERS Number 769 SERIES ON INTERNATIONAL CAPITAL AND ECONOMIC DEVELOPMENT Number I WORLD BANK STAFF WORKING PAPERS Number 769 SERIES ON INTERNATIONAL CAPITAL AND ECONOMIC DEVELOPMENT Number 1 The Costs of Protectionism to Developing Countries An Analysis for Selected Agricultural Products Joachim Zietz Alberto Valdes INTERNATIONAL MOINETARY FUND JOINT LIBRARY NOV 2 ,1986 !NTrLNATIONAL BAN- FOR r. -CO3NSTRUCTION AND Dl E'." 'EN, WASHINGTON. D.C ZO40 1 The World Bank Washington, D.C., U.S.A. Copyright ©) 1986 The International Bank for Reconstruction and Development/THE WORLD BANK 1818 H Street, N.W. Washington, D.C. 20433, U.S.A. All rights reserved Manufactured in the United States of America First printing January 1986 This is a working document published informally by the World Bank. 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Joachim Zietz is with the Institute of World Economics (Kiel, Federal Republic of Germany) and was assistant professor of economics at the University of Baltimore when the report was written; Alberto Vald6s is director of the Intemational Food Trade and Food Security Program at the International Food Policy Research Institute (Washington, D.C.); both are consultants to the World Bank. Library of Congress Cataloging-in-Publication Data Zietz, Joachim, 1953- The costs of protectionism to developing countries. (World Bank staff working papers ; no. 769. Series on international capital and economic development ; no. 1) Bibliography: p. 1. Produce trade--Covernment policy. 2. Tariff on farm produce. 3. Free trade and protection. 4. Produce trade--Developing countries. 5. Balance of trade-- Developing countries. I. ValdeSs, Alberto, 1935- II. Title. III. Series: World Bank staff working papers ; no. 769. IV. Series: World Bank staff working papers. Series on international capital and economic development ; no. 1. HD9000.6.Z54 1985 382'.41'091724 85-29421 ISBN 0-8213-0680-4 FOREWORD This paper is one in a special series of World Bank Staff Working Papers on international capital and economic development. Prepared as background papers for World Development Report 1985, the series provides more detailed treatment and documentation of the issues dealt with In the Report. The papers cover a range of topics including a historical perspective on international capital and economic development; the effects of policies in industrial and developing countries on international capital flows, external debt, and economic development; and the role of official assistance, commercial bank lending, securities markets, and private direct investment in developing countries. Several studies of individual developing countries are also included in the series. The background papers draw on a large number of published and unpublished studies of individual researchers, on World Bank policy analysis and research, and on reports of other organ- izations working on these issues. The papers are the work of individuals and the views and interpretations expressed in them do not necessarily coincide with the views and interpretations of the Report itself. I hope these detailed studies will supplement World Development Report 1985 in furthering understanding of the relationship between international capital and economic develop- ment. A complete list of the papers appears on the overleaf. Francis X. Cola9o Staff Director World Development Report 1985 Papers in the Series Aliber, Robert. Financial Intermediation and the External Debt Crisis Batista, Paulo Noguiera, Jr. International Financial Flows to Brazil Since the Late 19609: An Analysis of Debt Expansion and Current Payments Problems Blanchard, Olivier, and Lawrence H. Summers. Perspectives on High Real Interest Rates Throughout the World Codippily, Hilarian M.A. Ethiopia: International Financial Flows, 1967-83 Dornbusch, Rudiger. The Effects of OECD Macroeconomic Policies on Non-oil Developing Countries: A Review Fishlow, Albert. Capital Markets During the 19th Century and the Interwar Period: Lessons from the Past Hooper, Peter. The International Repercussions of the U.S. Budget Deficit Ibrahim, Tigani E. Kenya: Use of External Resources, 1963-1983 Ishiyama, Yoshihide, and Keiko Atsumi. Capital Outflows from Japan to Developing Countries Iqbal, Farrukh. Korea's Debt Accumulation, Use, and Management Strategies Johnson, John H. The Role of International Finance in Argentine Development, 1965-84 Lessard, Donald. International Financing for Developing Countries: The Unfulfilled Promise Llewellyn, David. International Financial Intermediation and the Role of Banks in Balance of Payments Financing Martone, Celso L. Macroeconomic Policies, Debt Accumulation, and Adjustment in Brazil, 1965-84 Muller, Patrice, and Robert Price. Public Sector Indebtedness and Long-Term Interest Rates O'Brien, Richard, and John Calverley. Private Banks and Developing Countries Pant, Chandrashekar. Yugoslavia: Economic Development and External Capital, 1970-1984 Rybezynski, T. M. Internationalization of Financial Arrangements and the Developing Countries: The Evolving Relationship Sachs, Jeffrey, and Warwick McKibbin. Macroeconomic Policies in OECD Countries and External Adjustment in Developing Countries Saini, Krishan G. Capital Market Innovations and Financial Flows to Developing Countries Sherbiny, Naiem A. Arab Financial Institutions and Developing Countries Swoboda, Alexander, and Hans Genberg. The Stages in the Balance of Payments Hypothesis Revisited Weigel, Dale, and Robert R. Miller. Foreign Direct Investment in Economic Development Wyplosz, Charles. International Aspects of the Policy Mix in Six OECD Countries Zietz, Joachim, and Alberto Vald6s. The Costs of Protectionism to Developing Countries: An Analysis for Selected Agricultural Products - iv - ABSTRACT The purpose of this study is to quantify the welfare and foreign exchange costs that arise in developing countries as a result of the protectionist policies pursued by developed countries with respect to many agricultural products. A detailed analysis is presented for four key commodities: sugar, beef, wheat, and maize. For each commodity, the potential gains to developing countries from a complete removal of tariff and nontariff barriers in developed countries are analyzed within the framework of a comparative-static world market equilibrium model. The study considers fifty-eight developing countries as well as seventeen developed countries. For each country and commodity, a consistent set of data on domestic production, consumption, exports, and imports is taken from the Preliminary Food Balance Sheets of the Food and Agriculture Organization (FAO) of the United Nations. The figures are averages for the years 1979 to 1981. The world market price for each commodity equals the average deflated world export unit value for the same years. For each commodity, the world market price is linked to the export and import unit values of developing countries. Domestic price elasticities of demand and supply are taken from previous studies. For each developed country and commodity, ad valorem tariff and nontariff trade barriers are derived from a comparison of domestic wholesale prices and t\he corresponding import unit values. \ The model is simulated for a variety of alternative assumptions regarding the domestic supply elasticities of developing and developed countries. Accordingly, the predicted costs of protectionism vary somewhat. However, the results seem to suggest that a switch to free trade in wheat and maize would lead to a net welfare loss to developing countries as a group, although a number of them could expect considerable increases in foreign exchange earnings. In contrast, free trade in sugar and beef is likely to greatly benefit developing countries. For both commodities together, the model predicts welfare gains between US$250 million and more than US$1.5 billion (1980) per year, depending on the underlying assumptions. The corresponding increases in foreign exchange could be anywhere from US$6.6 billion to more than US$12 billion. For beef alone, foreign exchange earnings can be expected to increase by more than 500 percent; most of this would go to the countries of Latin America. Trade liberalization in sugar would favor Asia and Latin America about equally. ACKNOWLEDGEMENTS We are indebted to Ron Duncan for extensive comments on an earlier draft. TABLE OF CONTENTS Page 1. Introduction ................................................................ l 2. The Theoretical Model ............... . 2 2.1 Developed Countries ................. .... 3 2.2 Treatment of the European Community .. 6 2.3 Developing Countries ....... .. . 7 2.3.1 The General Case ................. . 8 2.3.2 The Special Case of ACP Countries .......................... 10 2.4 Countries Classified as Rest-of-the-World ...... ............ . 11 2.5 Solution of the Model . . . 13 2.6 Effects of Trade Liberalization on Developing Countries ........... 13 2.6.1 The Ceneral Case ....................... . 14 2.6.2 Some Special Cases ......................................... 16 3. Data . . ....... . ........................................................ 19 3.1 Quantities and Prices ............................. . 19 3.2 Demand and Supply Elasticities . .. 21 3.3 Protection Levels . . ............................................... 25 3.3.1 Sugar ..................................................... 26 3.3.2 Beef and Veal .......... .................................... 29 3.3.3 Wheat ...................................................... 31 3.3.4 Maize ............................................................. 32 4. Results ..... ............................................................. 33 5. Conclusion ..............................52 Footnotes .o o.o.oo...o...... oo - ..... o o .- - ................ ooo .....o........ o55 References .... . ............. ............... ......... ... .. . .58 Appendix A: Input Data by Commodity and Country. .......... o- ..... 61 Appendix B: Individual Country Results by Commodity . ... . 74 - vii - - viii - TABLES Table 1: Effect of Trade Liberalization on World Price and Export Quantity, Trade Values and Welfare of Developing Countries Table 2: Sensitivity Analysis for Sugar--1983 Protection Levels Table 3: Absolute and Relative Size of Foreign Exchange Gains of Developing Countries Table 4: Export Market Shares before and after Trade Liberalization Table 5: Countries Most Affected by Trade Liberalization Table 6: Effect of Trade Liberalization on Low-Income Countries Table 7: Regional Impact of Trade Liberalization on Developing Countries--Sugar, 1979-81 Protection Levels Table 8: Regional Impact of Trade Liberalization on Developing Countries--Beef Table 9: Regional Impact of Trade Liberalization on Developing Countries--Wheat Table 10: Regional Impact of Trade Liberalization on Developing Countries--Maize 1. Introduction This study seeks to identify some of the welfare and foreign exchange costs that developing countries must bear when developed countries follow a policy of protectionism in the agricultural sector. The analysis is limited to four commodities: sugar, beef and veal, wheat, and maize. These four commodities are selected for somewhat different reasons. Sugar and beef are included mainly because previous research (see, for example, Valdes and Zietz 1980) has shown that trade liberalization in these commodities would likely be of the greatest benefit to developing countries. Wheat and maize are included for a different reason. For some time now, a number of countries, particularly large developed country exporters such as the United States and Australia, have been keenly interested in the removal of trade barriers for cereals. It is not clear, however, whether trade liberalization in cereals would also be beneficial to developing countries, since most of them are net importers and thus would be worse off with any increase in the world price that is likely to result from trade liberalization. This study attempts to shed some light on the relative gains of developed country exporters and developing countries as a whole for two of the most widely traded cereals, wheat and maize. The potential gains from trade liberalization are analyzed within the framework of a single-commodity world market equilibrium model. The hypothetical case of a complete absence of tariffs and other nontariff trade barriers in developed countries is compared with the current situation, which is characterized by the existence of such impediments to trade. The model employed for the analysis is of the partial equilibrium type. Interdependen- cies among the four commodity markets under consideration are not explicitly - 2 - modeled through the use of cross-price elasticities (see, for example, Anderson and Tyers 1983). Rather, we follow the procedure that we employed in a previous study (Valdes and Zietz 1980) and take interdependencies into account implicitly by adjusting the own-price elasticities appropriately where this seems necessary. 2. The Theoretical Model A separate world market model is constructed for each of the four commodities being analyzed. Each world market model is solved iteratively by searching for a value of the increase in the world market price that achieves postliberalization equilibruim. Compared with the closed-form solution that we used in an earlier study (Valdes and Zietz 1980), the iterative method allows us to simplify the computational treatment of trade reversals of countries from a net-exporting to a net-importing position, or vice versa. The model distinguishes among four categories of countries, developed countries outside the European Community, the members of the European Community, developing countries, and those countries not considered on an individual basis. Since the study seeks to identify the costs to developing countries of trade protectionism in developed countries and the European Community, only the developed and European Community countries are assumed to remove their trade barriers. The level of protectionism in all other countries is held constant. The countries within each category are assumed to react according to the same behavioral postulates, although different parameter values are used in each case. The behavioral postulates for each set of countries are described next. -3- 2.1 Developed Countries In the preliberalization situation, the domestic commodity price (p0) prevailing in a particular developed country can be related to the world market price prior to trade liberalization, pwo, by the equation po = pwo r (1 + tO) (1 + m), where r is the market exchange rate, tO the ad valorem equivalent of a particular country's tariff and nontariff barriers, and m is a margin that incorporates insurance, freight, and marketing costs. A tariff reduction by all developed countries is assumed to change each country's domestic price to P1 = pw1 r (1 + tl) (1 + m), where pw1 is the world market price after the joint tariff reduction in all developed countries and tl the postliberalization tariff level for a particular developed country. The exchange rate, r, and the marketing margin, m, are assumed to be unaffected by the changes induced by trade liberalization. For developed countries, this assumption seems to be justified, given the relatively small share of the four agricultural products under study in the total value of trade for most countries. When the domestic price before and after trade liberalization (po and P1, respectively) is examined for each developed country, the percentage change in domestic price (ph) resulting from trade liberalization,l/ (p1 - P )/po, can be calculated as ph = (1 + pwh) [1 + dt/(l + tO)] - 1, where pwh is defined as the percentage change in world price that is due to the combined effect of trade liberalization in developed countries, ( pw1-pw0)/pwO , and where dt is the difference between the post- -4 - liberalization and the preliberalization tariff levels, tI-tO. For the case of a complete elimination of tariffs, t1=0, the last expression reduces to ph = (1 + pwh)/(l + tO) - 1. When the price faced by consumers is substantially below the government subsidized producer price, ph is calculated separately for consumption and production by using the appropriate protection level for each. Civen the percentage change in domestic price, ph, consumption, and production in each developed country are assumed to change according to the equations (1) dC = C0 [(1 + ph) Cp _ 1] (2) dQ = Q0 [( + ph)QP - 1] where d stands for change and where £Z indicates the own-price elasticity of z.2/ Once the changes in domestic production and consumption are determined, the postliberalization levels of net exports (XI) and net imports (MI) can be derived from the equation sets (3) and (4), respectively: -5 X1 = (X + dQ - dC) if ( ..)>0 and XO > 0 (3) X1 = -(Mo + dC - dQ) if (..) < 0 and Mo > 0 ml = 0 if ( ..) >Oand Mo > 0 Ml = (Mo + dC - dQ) if (...) > 0 and Mo > 0 (4) Ml = -(X0 + dQ - dC) if (...) < 0 and X0 > 0 ml = O if ( ..)> Oand X0 > 0. A few points should be mentioned concerning equation sets (3) and (4). First, although the new levels of exports and imports are calculated solely on the basis of domestic demand and supply elasticities, the determining equations do imply particular levels of the export-supply and import-demand elasticitites. For example, the first equation in equation set (3) easily derives from the familiar expression K1 = X0 (1 + cX ph) if one replaces the export supply elasticity, £Xp with its well-known excess demand expression, Exp =Qp(Q/X) - (C/X). Multiplying out and substituting dC for (C £C ph) and'dQ for (Q0 £Q ph) results in the first equation of (3).- - 6 - Second, both sets of equations, (3) and (4), explicitly allow for a trade reversal of developed countries. Countries that are net importers in the preliberalization state can become net exporters if the world price increase exceeds the preliberalization tariff. Similarly, net-exporting countries can become net importers if the tariff equivalent is sufficiently large relative to the increase in world price. Third, both sets of equations implicitly assume that any stock changes that take place in the base period carry over to the new equilibrium position without change. To put it differently, stock changes are assumed to be constant in absolute terms and unaffected by trade liberalization. 2.2. Treatment of the European Community Postliberalization export and import levels for European community countries are calculated as they would be for any other developed country. Hence, the description of the preceding section applies in full. The reason for treating the European Community separately is the assumption that it affects the world market only as a net trading entity, similar to a large country with several regions or states. To incorporate such an effect, the sum of the net imports of all European Community members is subtracted from the sum of net exports to arrive at European Community net exports. Consequently, postliberalization net exports of the European Community are given by EC X1 = (£ X - £ ) if (..) > 0 xC otherwise. - 7 - where subscripts i and j stand for European Community countries that are net importers and net exporters, respectively, after trade liberalization. Postliberalization net imports of the European Community as a unit can be written as EC M1 = ( M - E x if (..) > O I 1 ii ij EC Ml = 0 otherwise. As already noted, M1 and Xi are calculated for each member country of the European Community as described by equations (1) to (4). 2.3 Developing Countries Developing countries are expected to benefit from trade liberalization in developed countries through a combination of two effects: the world price increase associated with trade liberalization and the potential increase in the quanity of their net exports to developing countries. The increase in the world price will benefit net exporting developing countries independently of whether they increase their export quantity or not. However, this general rule does not apply in the case of the ACP countries--that is, those Afric,an, Carribean, and Pacific countries that have, for certain commodities, preferential access to the market of the European Community under a quota system. In selling on the high-price European market, they effectively capture monopoly rents, which would be lost if trade were liberalized. Hence trade liberalization could mean a net loss to ACP countries. The same reasoning applies to developing countries that have preferential access to the U.S. market. -8- Net importing developing countries will always be hurt by trade liberalization unless they turn into net exporters. Even then, trade liberalization produces an increase in welfare for the country as a whole only if the lops in consumer surplus is less than the increase in producer surplus. The quantitative effects of trade liberalization on developing countries largely depend on the extent to which the world price increase is transmitted to domestic producers and consumers. Studies on trade liberalization commonly assume that the protection of the domestic market from the world price remains the same in nonliberalizing countries. For fixed exchange rates, this implies that the world price increase resulting from trade liberalization in developed countries is transmitted in full to the domestic market of developing countries. The internal price, in other words, changes by the same percentage as the world market price. A potential problem with this line of reasoning is the precondition of an exchange rate that is unaffected by the export and import changes induced by trade liberalization. Although this may be quite plausible for developed countries, it may be somewhat unrealistic for developing countries that rely heavily on any one of the commodities under study for most of their export earnings. There does not seem to be an easy way out of this problem, however, other than changing the basic setup of the partial equilibrium model used in this study. 2.3.1 The General Case For each developing country, the response of consumption and production to an increase in the world price can be caLcuLated by means of equations (1) and (2), respectively, but replacing ph and with pwh. Post- liberalization exports for developing countries are then given by the equations _ 9 _ X1 = XO + dQ - dC if XO > 0 X1 = -(M0 + dC - dQ) if (..) < O and M0 > ° X= 0 otherwise. Postliberalization net import levels are derived as M1 = (MO + dC - dQ) if (..) > O m1 0 otherwise. As in the case of developed countries, the above equations allow for the possibility that developing countries may turn from a net importing position to net exporting position. Unlike the developed countries, however, the developing countries outside the ACP-country group that are net exporters prior to trade liberalization will always remain exporters. Calculating export and import levels according to the response of consumption and production assumes that each developing country has the capacity to export readily any excess supply or import in case of excess demand. For certain countries without an adequate infrastructure necessary for foreign trade, this assumption may be considered overly optimistic. As an alternative, postliberalization export and import levels could be calculated from empirically observed trade elasticities. Postliberalization imports would be - 10 - Ml = M (1 + e pwh) if e pwh>-1 1 0 Mpw mpw m = 0 otherwise, where e is the import-demand elasticity. The corresponding equations Mpw for exports would be X1 = X0 (1 + eX pwh) if XO > 0 XI = -Mo (1 + eM pwh) if EMph pwh < -1, where X denotes the export-supply elasticity. 2.3.2. The Special Case of ACP-Countries ACP countries currently sell part of their exports to the European Community at a price substantially above that realized by non-ACP exporters. Hence, for these countries, a removal of all European community trade barriers would imply a price change that is different from pwh. The relevant percentage change in price for ACP-country i, pwhi, is given by I - x x x pwhi = (f pw 1 Pod)/poi if f pw0 < I pwhi = pwh otherwise, x where Poi is the preliberalization export unit value of country i; ; is defined as the average regional value of 4i, which is given by the ratio of preliberalization export unit value and world price. i Poi tW To relate pwhi to pwh, the first equation can be rewritten as pwh. = (0/4i) (1 + pwh) - 1. The if statement attached to the determining equation of pwhi implies that ACP countries are treated differently from other developing countries only if their preliberalization export unit value exceeds the average export unit value of other exporters in the region. This implies that a particular ACP country actually has to sell more than just a small fraction of its exports under a preferential quota system to receive special treatment in this study. For the calculation of the changes in consumption and production, pwh' simply replaces ph in equations (1) and (2), respectively. Given dC and dQ, the postliberalization levels of exports and imports of ACP countries are derived as described in the preceding section. The ACP countries could however, experience a trade reversal from a net-exporting to a net-importing status. In that sense, the behavior of ACP countries resembles that of developed countries. 2.4. Countries Classified as Rest-of-the-World The category of countries classified as rest-of-the-world consists of the centrally planned economies and small developing countries with less than 5 million inhabitants. For this category of countries, the post- liberalization level of exports is derived as a weighted average of the export level for the group of centrally planned economies (CPE) and the group of small developing countries (SDC) as - 12- X1i = w XOPE (1 + EX pwh) + (1-w) XSDC (1 + eSDC pwh), 0 Xpw where w is the preliberalization share of the centrally planned economies in the net exports of the countries categorized as rest-of-the-world. Similarly, for postliberalization imports, ROW CPE CPE M z M (l+Mpw pwh) + (1-z) MSDC (1 + £ DC pwh), 0 Mpw where z is the preliberalization share of centrally planned economies in the net imports of the rest-of-the-world countries. Both the composite import- demand and export-supply elasticities of the centrally planned economies are determined empirically. The corresponding elasticities for the small developing countries are calculated as a weighted average of the trade elasticitites of those developing countries that are explicitly considered in the study and that have no more than 8 million inhabitants. The trade elasticitites for the developing countries included in the study are derived using the well-known excess demand elasticity formulas EMpw = ECp (C/M) - eQp(Q/M) Xpw e (Q/X) - e (C/X) X Qp Cp - 13 - for import demand and export supply, respectively. If one assumes that the domestic price elasticities of consumption and production are the same for a given country and commodity, the above equations reduce to EMp = (c +Q)/M Mpw Cp EXp E (c +Q)/X. Xpw Qp From the last two equations one can easily see the rationale for including only developing countries with less than 8 million inhabitants in the calculation of the weighted trade elasticities of the smaller developing countries. If large developing countries were included, the weighted trade elasticities would likely be inflated because for large developing countries the value of C+Q is generally quite large compared with M. 2.5. Solution of the Model The model is solved iteratively by searching for a value of the world price increase, pwh, that achieves postliberalization equilibrium in the world market. Such an equilibruim is realized if the following equation holds DC LDC + ROW EC 1i j l j 1 1 MDC + m MLDC ROW MEC Mlk m% Im + MI +MI 2.6 Effects of Trade Liberalization on Developing Countries For a given world price increase and corresponding quantities of postliberalization exports and imports, one can derive the foreign exchange - 14 - and welfare implications of trade liberalization for developing countries, as described in the following sections. 2.6.1. The General Case The change in export revenue of exporting country i and in import costs of country j is dVX. = (Xli pw1 - Xoi PwO i dVM = (M j pw- moi P O j respectively, where pwI represents the world price after trade liberalization. For developing country j,O. is defined as .j = j P o As noted earlier, *i equals the ratio of the export unit value of developing country i to the world price in the preliberalization period. For developing countries that incur a trade reversal owing to the increase in world price--that is, countries that turn from a net importer to a net exporter--the term dVM equals the negative of the preliberalization import bill. Similarly, dVX equals the new level of export revenue after trade liberalization. Since a preliberalization export unit value does not exist for countries incurring a trade reversal, the regional average 0 substitutes for *i. Hence, the increase in export revenue for developing country i that incurs a trade reversal is given by dVXi = Xi P - 15 - The welfare gain of trade liberalization to developing country exporter i can be approximated by dWXi = 0.5 (pwI - pw0) (Xoi + X i) *i Similarly, for importing developing country j, one can approximate the welfare loss incurred by the world price increase owing to trade liberalization as dWM. = 0.5 (pw1 - pwO) (Moi +Mi) ei. Finally, for developing country i with a trade reversal from a net- importing to a net-exporting status, the change in welfare is derived by the equations dWX. = 0.5 [(f pw1 Pxi ) xi- (pi P- ) M0], dWM. =0 T where P is the price at which a trade reversal would occur in terms of T import unit values; pXi is the corresponding price in terms of export unit values. The latter is related to the former by the relation Pxi = Pi (pw0 0 /Poi where f is defined as in section 2.3.2. For each country i, the - 16 - determining equation of pT is found by setting domestic production, eQp cCp Ap , equal to domestic consumption, Bp and solving for p. To do so, we need values of the constants A and B. For each country, they are found by the equations A = Q / pM cQP p 0 and B = C /pM £Cp, respectively. Both equations are based on the somewhat unrealistic assumption that a country's import unit value for a particular commodity, p0, is equal to the domestic market price. Given the lack of detailed country data and the tentative nature of the trade reversal calculations, this approximation does not seem to be unreasonable. According to the above assumptions, pT is determined for each developing country by the equation p = exp Qln (C pM Cp) - In (Q p) - EC ) Cp Clearly, in the case of a trade reversal, dWX can be positive or negative, depending on whether the welfare gain to producers outweighs the welfare loss to consumers. 2.6.2 Some Special Cases The first special case to be considered is that of ACP countries. For ACP country i, which remains a net exporter in the postliberalization period, the change in welfare is derived by the following two equations - 17 - dWX 0.5 (o pw1 - 4ipwo) (Xoi + X i) dWM. = 0 1 For ACP country j, which incurs a trade reversal from a net-exporting to a net-importing status, the change in welfare is calculated as dWM. = 0.5 [(pM; - Opwl) M.j - (Poj - pT) x0;] dWX. = 0, where pT is derived by the general formula given in the last section except J X M T T that, for each j, pO is substituted for P0. Pmj gives p. in terms of T import unit values. It is related to pj by the equation T T PMj =Pj (pwo 5/po which can also be written as T T - PMj P;(o A second special case derives frome some price distortions introduced into the beef market by Australian export behavior.4/ Since Australian exporters of beef earn quota rights to the U.S. market by selling beef to developing countries under world market level, many importing developing countries outside Latin American can buy beef at artificially low prices. - 18 - Trade liberalization is likely to eliminate these rents and force developing countries to buy at world market prices. To incorporate this additional loss of rents among developing countries that import beef we must modify the determining equations of dVM and dMW somewhat. Also, some changes have to be made for ACP countries that are subject to a trade reversal from a net exporting to a net importing status. For country j outside of the ACP group of countries and Latin America, the change in the import bill is calculated as dVM =Mj pw - oj Poj if pw0 > Poj holds.5/ If this last condition is not satisfied for country j, it is assumed that the country does not benefit from sales of Australian beef below the world market price in the preliberalization period. As a consequence, the change in its import bill is derived as for the general case discussed in the previous section. Similarly, the change in welfare of developing country beef importer k is dWM = 0-.5 (pw, - p M) (M + M) k 1 Ok Ok lk M if pwO > Pok* Again, if the condition does not hold, the corresponding equations of the preceding section apply. The change in welfare of ACP countries that incur a trade reversal from a net exporting to a net importing status is given by the equation described at the beginning of this section, except that the term OpwI now reduces to just pw1. Also, the calculation of pM; simplifies to T T /X) pMj= p. (pw00p) J p.0 - 19 - 3. Data Four commodities are analyzed: total sugar measured in raw equivalents,61 (FAO Trade Yearbook classification number 061), beef and veal (FAO Trade number 011.1), wheat and wheat flour measured in wheat equivalents, and maize (FAO Trade number 044). The study explicitly incorporates all market-economy developing countries with a 1980 population level of more than 5 million; the total is fifty-eight countries. The geographical distribution is as follows: twenty- one countries are from the sub-Saharan region, twelve from Asia, twelve from North Africa and the Middle East, and thirteen from Latin America. Seventeen market-economy developed countries are considered. All are members of the Organisation for Economic Co-operation and Development (OECD). All the remaining countries of the world--that is, small market economy, developing countries as well as centrally planned countries--are lumped together in a category identified as rest of the world. 3.1 Quantities and Prices Data on domestic production (Q0), consumption (CO), exports (X0), and imports (MO) are taken from the Preliminary Food Balance Sheets of the Food and Agriculture Organization of the United Nations. The figures are averages for the years 1979 to 1981. X0 and Mo are net exports and net imports, respectively. Consumption is calculated as a residual: O QO XO + M - - dSTO - 20 - where X' and M' are gross exports and imports, respectively, and where dST represents stock changes. A listing of production, consumption, net export and net import data by commodity and country is provided in appendix A. The preliberalization world market price (pw0) equals the average deflated world export unit value for the years 1979 to 1981. It is calculated by dividing the value of world exports by the quantity of world exports for each year and deflating the resulting values by the world wholesale price index as published in the IMF International Financial Statistics. The price index has 1980 as its base year. Value and quantity of world exports are from the FAO Trade Yearbook. The value of pwo for sugar is derived by excluding Cuba and the principal ACP exporters of sugar7/ from the value and quantity of world exports. Cuba is excluded from the calculations because it is exporting most of its sugar to the Soviet Union at prices far in excess of those found in the free market. A similar argument can be made for the ACP countries, which are selling under a preferential quota system on the high-price European market. Because detailed country data on sugar exports are lacking for 1983, the same method could not be used for that year. Instead, the world price of sugar for 1983 was set equal to its 1979-81 average, multipled by the factor 0.54. The latter factor can be found by dividing the average deflated export unit value of Brazil, the Dominican Republic, and the Philippines for 1979 to 1981, as quoted in IMF International Financial Statistics (Yearbook 1984), into the corresponding average for 1983. The prices used for the term pw0 throughout the study are as follows: - 21 - Prices Commodity 1979-81 1983 Total sugar 396.7 214.2 Beef and veal 2513.7 Wheat and flour 186.6 Maize 145.6 All prices are expressed in 1980 U.S. dollars per metric ton. For each commodity and developing country, unit values of trade (pX and pO ) are calculated as simple averages of the deflated unit values of the years 1979 to 1981. The raw data come from the 1981 FAO Trade Yearbook. Average regional unit trade values are substituted whenever a country's trade value was judged unreliable because of a very small level of trade. Lack of data made it necessary to construct the 1983 export and import unit values of sugar from their average 1979-81 levels. This was accomplished by multiplying the average 1979-81 levels by the factor 0.54, the derivation of which is described above. 3.2 Demand and Supply Elasticities Values for domestic demand and supply elasticitites are taken from the following sources: Askari and Cummings (1976), Caspari et al. (1980), Koester and Schmitz (1982), Stern et al. (1976), Tyers (1982), Tyers and Anderson (1983), and Valdes (1975). The demand elasticities for sugar are from Stern et al. (1976, pp. 336-37), except for Ireland, Italy, and the United Kingdom. The domestic demand elasticities for these countries are from Caspari et al. (1980, pp. 56 76, and 105, respectively). For countries not mentioned in either Stern et - 22 - al. (1976) or Caspari et al. (1980), the demand elasticities are assumed to be 0.4. This elasticity value corresponds to the one reported in Stern et al. (1976, pp. 354-57) for developing countries. For the benchmark run, the supply elasticity of sugar is set equal to 0.6 for all countries. This value is somewhat below the unitary elasticity used by Koester and Schmitz (1982) for countries outside the European Community. A lower elasticity is used here to account for possible interdependencies in production between sugar and the other commodities considered in this study.8/ Also, the more conservative elasticity value reflects the relatively high degree of uncertainty regarding the supply response of sugar. The uncertainty results from an unusual scarcity of econometric evidence. To check on the sensitivity of the results with respect to the assumed elasticity of 0.6, the model was also run with three alternative elasticity assumptions. The first alternative model simulation uses a supply elasticity of 0.06 rather than 0.6 for all European Community countries. This reflects the possibility that sugar production in the European Community may change very little if trade is liberalized in grains and sugar at the same time. Farmers could very well switch from the production of grains, which is afforded generally higher protection levels than sugar, to the production of sugar. A second alternative model run is based on the opposite assumption that sugar production in developed countries would react very sharply to an elimination of trade barriers. To incorporate this assumption, the supply elasticity of all European Community countries is raised tenfold to 6.0. A supply elasticity of 4.0 is assumed for all other developed countries with significant protection levels, which include all producers with the exception of Australia. For a third alternative model run, the supply elasticity of all developing countries is doubled from 0.6 to - 23 - 1.2. The higher supply elasticity is meant to incorporate the possibility that a removal of all trade barriers in developed countries could effectively eliminate the consequences of what may be called export perssimism of developing countries.- The prospect of assured free access to the market of developed countries could, in other words, spark considerable investments in the sugar industry. For beef and veal, the domestic demand elasticities of Argentina, Brazil, Chile, Colombia, and Venezuela are adapted from Valdes (1975). An elasticity of 0.5 is used for these countries. This is somewhat below the values reported by Valdes. The domestic demand elasticity of New Zealand is from Stern et al. (1976, pp. 354-57). The corresponding values for the members of the European Community are taken from Caspari et al. (1980, p. 124). The supply elasticities for Argentina, Brazil, Chile, Colombia, and Venezuela are adapted from Valdes (1975), whose estimates are close to 1.50. Thus the value of 1.0 used in this study is rather conservative. The supply elasticities for the Netherlands and West Cermany are from Stern et al. (1976, pp. 354-57). Both the demand and the supply elasticities for ruminant meat reported in Tyers (1982) are used for Australia, Canada, Indonesia, Korea, Malaysia, the Philippines, and the United States. The corresponding elasticities for Japan are from Tyers and Anderson (1983), as is the supply elasticity for all member countries of the European Community except Germany and the Netherlands. For all countries for which none of the consulted studies gave an estimate, the domestic demand and supply elasticities are set equal to 0.4, except in the case of the Latin American countries. On the basis of Valdes's (1975) study of the beef sector in South America, which showed a rather high supply response, it was decided to use 0.6 as the default supply elasticity for Latin American countries. - 24 - For an alternative run of the beef model, the somewhat more conservation value of 0.4 is substituted for the supply elasticity of all European Community countries and Japan. This is done to incorporate the uncertainty regarding the supply response of beef if tariff barriers are eliminated in grains at the same time. Two sets of elasticities are used for wheat and maize. The elasticities entering the benchmark runs of the model are described first. The domestic demand and supply elasticities for wheat and coarse grains listed in Tyers (1982) are used for Australia, Canada, Indonesia, Korea, Malaysia, the Philippines, Thailand, and the United States. The Australian elasticities are also employed for New Zealand. The coarse grains elasticities are substituted for the maize elasticities needed in the study. The wheat elasticities for Bangladesh and India as well as the maize elasticities for Pakistan also come from Tyers (1982). The wheat and coarse grain elasticities for Japan and the European Community are taken from Tyers and Anderson (1983). The supply elasticities of maize for India and Syria are from Askari and Cummings (1976). India's elasticity of 0.7 is at the lower end of a whole range of estimates presented by Askari and Cummings. For all countries not mentioned explicitly, the domestic demand and supply elasticities are set equal to 0.4 for both wheat and maize. These values correspond roughly to those reported in Stern et al. (1976, pp. 354-57) for both developed and developing countries. To check on the sensitivity of the model results with respect to the choice of the domestic supply elasticities, we used a second set of elasticities for both wheat and maize. It differs from the one just described with regard to the default values of the supply elasticity of developing countries. For both wheat and maize, the default value of 0.4 used in the benchmark runs is doubled to 0.8. - 25 - The calculation of postliberalization export and import levels of the rest-of-the-world countries requires a value for the share of the centrally planned economies in the net exports and net imports of the countries of this category. These market shares are derived from the export and import data reported in the FAO Preliminary Food Balance Sheets. All Eastern European countries as well as the Soviet Union are classified as centrally planned economies. Their share of rest-of-the-world net exports is 0, 0.25, 0.54, and 0 for sugar, beef, wheat, and maize, respectively. Their share of rest-of- the-world net imports is calculated as 0.58, 0.37, 0.43 and 0.53, respectively, for the same commodities. The import-demand elasticities reported for the Soviet Union in Tyers (1982) are assumed to represent the corresponding elasticities for the centrally planned economies as a whole. This assumption seems justified given the overwhelming share of the Soviet Union in the imports of the centrally planned economies. The elasticity values are -1.0, -0.27, and -0.46 for wheat, maize, and beef, respectively. The unit elasticity for wheat corresponds exactly to the estimate by Carson et al. (1984) for their preferred model. The import-demand elasticity for sugar was set to -1.0. The rationale for this rather low elasticity is that the Soviet Union receives most its sugar under long-term contracts from Cuba. Hence, changes in the world market price probably do not greatly influence its imports. The export-supply elasticities of the centrally planned economies for beef and wheat are set to 1.0. Since their export share for sugar and maize is set at zero, no assumption regarding the corresponding export-supply elasticities is needed. 3.3. Protection Levels Ad valorem tariff equivalents of tariff and nontariff trade barriers are derived from a comparison of domestic wholesale prices and the - 26 - corresponding import unit values or border prices for each trade liberalizing country and commodity.-0/ The calculations are based on the nominal protection coefficient (NPC), 1+tO, which is defined as the ratio of the domestic to the c.i.f. or border price, with both prices expressed in the same currency units. Wherever necessary, a distinction is made between the protection afforded to producers and the level of protection relevant to consumers. The derivation of the protection levels is described by commodity. The members of the European Community are treated separately from the other developed countries included in the study. 3.3.1. Sugar The basic protection level of the European Community is derived by dividing the threshold price of raw sugar by its c.i.f. Rotterdam price for each year from 1979 to 1981 and taking a simple average. The threshold prices for raw sugar are from the Agricultural Yearbook (1983) and the c.i.f. Rotterdam prices from Agricultural Prices (June 1984). The NPCs for the marketing years 1978-79 to 1980-81 are 2.8, 1.36, and 0.9, respectively, which gives an average of 1.69. Given the average protection level for the European Community, individual country protection levels are derived by multiplying the average nominal protection rate (NPR), NPC-1, by an index of relative prices within the European Community. This index is based on the selling prices of sugar beet of standard quality measured in ECU as reported in Agricultural Price Statistics 1983 (Table 1085). An average price for 1979 to 1981 was calculated for each country.!!/ The average found for Italy, the country with the highest sugar beet price, was set equal to one. All other average prices were divided by the Italian average to find the remaining index numbers. Italy's price level was set to 1.0 in deriving the index to incorporate the fact that a part of the NPR for the European Community'as a whole is clearly - 27 - redundant for those of its members that export sugar. As pointed out by Koester (1982, p. 15) for the case of grains, exports from a country imply that its internal price is about equal to the intervention price. But the latter was about 17 percent below the threshold price for the years 1979 to 1983. A lowering of the threshold price within that percentage range cannot be expected to induce imports to sugar-exporting countries. From this derives the partial redundancy of the threshold price. The basic procedure described above was also used for the derivation of the 1983 protection levels. Since no domestic prices were available at the time of the calculations, however, the 1983 prices in local currency were calculated from the 1975 prices using the Index of Producer Prices for sugar beet quoted above. The equivalent prices in ECU were found by applying the exchange rates (green rates) listed in the Official Journal of the European Community (L 132, May 21, 1983).121 NPCs for non-European Community countries were drived, in general, by dividing the raw sugar equivalent of the producer price of sugar beet as reported in FAO Producer Prices by the import unit values for total sugar as derived from the FAO Trade Yearbook for 1981. The raw sugar equivalent of the beet price was estimated by the FAO method of multiplying the beet price by 10. The local currency prices given in the FAO printout were converted into U.S. dollars using the market exchange rates published in OECD Economic Outlook (1984, p. 19). These computations were carried out for each of the years 1979 to 1981. The NPC used in the study is a simple average of those three values. Some adjustments to the above procedure were needed for certain countries. For sugar-exporting countries, the import unit value of a neighboring importing country was substituted. This was done for Austria and - 28 - Australia. The Swiss import unit value was substituted for the Austrian value and the Oceania value for Australia's. For Australia, the FAO printout also contained a price quotation for raw sugar. This was used instead of the sugar beet price. For the United States, the New York raw sugar price listed in Business Statistic 1982 (U.S. Department of Commerce 1983, p. 100) was taken as the representative domestic price. In the case of countries for which the producer price of raw sugar is far in excess of the wholesale price of refined sugar as published in the Sugar Yearbook of the International Sugar Organization, a separate NPC was calculated for refined sugar The corresponding NPR value replaces tO in equation (1). For Norway and Switzerland, the wholesale price of refined sugar from the Sugar Yearbook was divided by the import unit value of refined sugar from the FAO Trade Yearbook for 1981. The average of the 1978 and 1981 values was used for tO in (1). The corresponding number for Canada was derived in the same way, except that the average import unit value of Norway and Switzerland substituted for Canada's which was considered unusable. Lack of data presented some probLems in deriving meaningful NPCs for the non-European Community countries for the year 1983. One exception is the United States. To find its NPC, we divided the New York raw sugar spot price (c.i.f., duty/fee paid, contract #12) by the spot raw sugar world price of the International Sugar Agreement. Both numbers are from the Commodity Yearbook (Commodity Research Bureau April 1984). For all otheV non-European Community countries, the 1978 NPC value-3/ was adjusted by a factor reflecting the increase of the world price of raw sugar from 1978 to 1983 (8.14 percent) and the hypothesized increase in the domestic price over its 1978 value. On the basis of the development of beet producer prices in the FAO Producer Prices printout, a 10 percent increase was hypothesized for the domestic sugar price - 29 - in Austria, Sweden, and Switzerland. A 25 percent increase was assumed for Japan and Canada. All percentage increases are likely to be on the conservative side. The procedure described earlier for deriving the NPR value faced by consumers in Norway, Switzerland, and Canada was applied in an analogous way for 1983. Since no data were available for that year, the calculations were done for 1978, a year with a world price of raw sugar somewhat below the one for 1983 in nominal terms. No adjustment factor was applied to correct for the differences in domestic and international prices of refined sugar between 1978 and 1983 owing to the lack of a perceptible trend in domestic wholesale prices and the unavailability of an import unit value for refined sugar. 3.3.2. Beef and Veal NPCs for all countries were derived by dividing the U.S. import unit value for beef from the FAO Trade Yearbook for 1981 into the domestic wholesale price of beef. The NPCs found for the years 1979 to 1981 were averaged to arrive at the value of (1+tO) for equations (1) and (2). The choice of the U.S. import unit value as the border price for all developed countries derives from an effort to match domestic wholesale and border prices of meat of approximately the same quality. Import unit values of beef vary greatly from country to country, depending on the quality of beef imported. For example, countries that import mainly high-quality boneless beef, such as Japan4/ , have a rather high import unit value. However, the domestic wholesale beef prices, which are available, refer in general to carcass weight beef. They are considerably below the corresponding prices of lean, boneless beef. Hence, calculations of NPCs based on individual country import unit values or a world market price of boneless beefl5/ are likely to underestimate the true protection level in many cases. The U.S. import unit value was - 30 - chosen as the denominator in the NPC calculations for the benchmark runs because it is believed to be representative of the quality of beef for which domestic prices could be obtained. It should be noted, however, that it is by far not the lowest import unit value for the developed countries under consideration. At the same time, it is well above other unit import values that may be considered useful for the NPC calculcations. These include the import unit values of most countries of the Middle East or of the Soviet Union. For the calculations of NPCs for the European Community countries, the dollar price was converted into ECU using the exchange rates given in the Yearbook of Agricultural Statistics of the European Community. The domestic wholesale prices are from Agricultural Price Statistics 1983 (table 2045). The prices refer to good-quality carcass meat of heavy cattle. Since no prices were quoted for Ireland, the United Kingdom prices were used as a substitute. For most other countries, NPCs were computed on the basis of the producer prices given in the FAO Producer Prices printout. Again, the domestic currency prices were converted to U.S. dollars at the market exchange rates quoted in OECD Economic Outlook (1984). For Austria, Canada, the United States, and Japan, NPCs were calculated using domestic beef prices taken from original government statistics. In the case of Austria, the beef price is from the 1982 Taetigkeitsbericht of the Ministry of Agriculture and Forestry. It refers to the average price of half animals, carcass weight, of steers, oxen, and calves on all "Richtmaerkte." The Canadian Prices are the Ontario wholesale prices for dressed A-1 steer carcass beef weighing 500 to 700 pounds, as quoted in the Livestock Market Review. The U.S. price is taken from Business Statistics 1982 and refers to the wholesale price of 600- to - 31 - 700-pound fresh steer carcasses. The domestic Japanese prices are from The Meat Statistics in Japan (January 1984, table 15) and refer to the wholesale carcass price of first-grade steer beef. Again, all domestic currency prices are converted to U.S. dollars using the exchange rates in OECD Economic Outlook (1984). As it turns out, the average NPRs calculated from the original data sources are very close to the ones that can be derived using the prices given in the FAO Producer Prices printout. 3.3.3. Wheat For the European Community, the NPR values were taken from Koester (1982). NPRs for individual European Community countries were derived by multiplying their average NPR value for the years 1979 to 1981 by an index reflecting the wholesale price differences among its members. The wholesale prices of soft wheat from Agricultural Price Statistics 1983 (table 1045) measured in ECU were used for the construction of the index. No wholesale prices are quoted for the United Kingdom and Ireland. The producer prices for soft wheat from Agricultural Price Statistics 1983 (table 1005) were taken as a substitute. To make them comparable with wholesale prices, we multiplied them by the average ratio of wholesale-to-producer prices for those countries for which both prices were available. The adjustment factor is 1.07 for 1979 and 1980, and 1.06 for 1981. Given wholesale prices for all European Community countries, the above-mentioned index was constructed by setting the wholesale price of Germany equal to 1.0. The reason for doing this is similar to that given for the sugar protection levels.16/ For all non-European Community countries, with the exception of Australia and Japan, NPRs were calculated for each year from 1979 to 1981 by dividing the U.S. dollar producer prices given in the World Wheat Statistics (1982) by the respective import unit values from the FAO Trade Yearbook. The - 32 - producer prices for Australia come from the Australia Yearbook. The producer prices for Japan are the government purchasing prices taken from the 58th Statistical Yearbook (1981-82, appendix 1). The import unit values of Switzerland and Norway were substituted for the ones of Austria and Sweden, respectively. Japan's import unit value was used for both Australia and New Zealand. Information in Austria's Statistisches Handbuch on the years 1980 and 1981 indicates that the wholesale price of wheat was below the producer price by approximately 13 percent in those years. -Using this information we calculated a separate NPR value for consumers. Similarly, the 58th Statistical Yearbook of the Japanese Ministry of Agriculture quotes a government selling price for wheat far below the corresponding purchase price. Again, a consumer-specific NPR was calculated along the principles outlined above. 3.3.4. Maize The NPR value for the European Community over the years 1979 to 1981 is a simple average of the annual estimates presented in Koester (1982, p. 15). As in the case of wheat, an index was constructed on the basis of information on the wholesale prices in individual European Community countries. The wholesale prices are from Agricultural Price Statistics 1983 (table 1060). The prices for the United Kingdom, Ireland, and Denmark are estimates from FAO Producer Prices. The local currency prices were converted to ECU using the implicit conversion rate for soft wheat in table 1005 of Agricultural Price Statistics, 1978-81. The resulting prices were adjusted for each year by the average ratio of producer to wholesale prices for Germany, France, and Italy, as derived from Agricultural Price Statistics (tables 1035 and 1060). Since no FAQ prices are available for Ireland for the 33 - years 1980 and 1981, it was assumed that the ratio of Ireland's average 1979- 81 price to the average United Kingdom price over the same time period equals the ratio of the two countries' 1979 prices. For non-European Community countries, NPCs were derived from the FAO Producer Prices, converted to U.S. dollars at the exchange rates given in OECD Economic Outlook (1984), and the appropriate import unit values. For Austria, the FAO producer prices could be checked against those published by the Ministry of Agriculture in its Lagebericht 1982. The two series are the same. Norway's import unit value was used as the denominator in the NPC calculations for Norway, Austria, Sweden, and Switzerland. 4. Results Table 1 provides an overview of the effects on developing countries-7/ of a complete removal of trade barriers for sugar, beef, wheat, and maize as they prevailed in developed countries during 1979 to 1981. It also gives the model's predictions of the changes in the world market price and in world exports. World exports are defined as the sum of the net exports of all exporting countries. Several results are presented for each of the four commodities analyzed in this study. Differences among the results are solely due to differences in the assumed supply elasticities. For each commodity, superscript 1 indicates the use of the benchmark elasticities as they can be found in appendix A. For beef, wheat, and maize, superscript 2 identifies the alternative elasticity assumptions described in the data section.-8/ The alternative elasticity assumptions for sugar are as follows: - 34 - Table 1. Effect of Trade Liberalization on World Price and Export Quantity, Trade Values and Welfare of Developing Countries Absolute Change in Developing Country Percentage Change in (billions of 1980 U.S. dollars) World World Foreign Welfare Import Net Price Exports Exchange (Exporters Bill Welfare Earnings only) Sugarl 16.7 12.4 2.75 0.60 -0.33 0.08 Sugar2 13.6 10.4 2.19 0.46 -0.31 0.03 Sugar 29.4 31.3 5.11 1.25 -0.42 0.39 Sugar4 12.9 16.8 3.04 0.49 -0.48 0.09 Beef' 18.5 167.7 5.10 0.54 -0.33 0.32 Beef2 16.2 143.2 4.38 0.43 -0.28 0.22 Wheat' 12.7 10.2 1.17 0.13 -0.35 -0.66 Wheat2 11.5 10.5 1.37 0.13 -0.58 -0.58 Maize1 11.7 35.6 0.61 0.14 -0.57 -0.07 Maize2 10.8 35.3 0.84 0.14 -0.74 -0.04 Note: Superscripts refer to various assumptions with respect to the supply elasticities. Details are given in the text. World exports are defined as the sum of net exports of all net exporting countries. - 35 - Sugar2 -Supply elasticity of all European Community members set at 0.06 Sugar3 -Supply elasticity of all European Community members set at 6 and supply elasticity of all other developed countries except Australia set at 4. Sugar4 -Supply elasticity of all developing countries doubled to 1.2 the world price increases predicted by the model are roughly between 10 and 30 percent. For sugar and beef, they are somewhat larger than for the two cereals included in the study, in part because of the more widespread use of trade protectionism for the former commodities. The case of sugar demonstrates that the calculated increase in the world price is quite sensitive to the underlying domestic supply elasticities. The world price is predicted to rise most if the trade liberalizing countries are assumed to have a very high price elasticity of supply. If instead the domestic supply elasticities of all developing countries are doubled to 1.2, the world price rises by only 13 percent, rather than by almost 30 percent. Reducing the domestic supply elasticities of both the European Community countries and Japan for the case of beef also has a noticeable impact on the reported results. On the other hand, doubling the domestic supply elasticities of developing countries for wheat and maize does not have a significant effect on the world market. This is largely due to the fact that most developing countries are importers of grain. The share of developing countries in world exports is a mere 6 percent for wheat and 12 percent for maize for the years 1979 to 1981. The third column of table 1 presents the changes in foreign exchange earnings of developing countries. For the benchmark elasticity runs of the - 36 - model,-9/ an increase of approximately US$10 billion per year is predicted for the total of the four commodities. This value is expressed in 1980 dollars. Hence, the equivalent figure in 1984 dollars would exceed 14 billion. As expected, the change in welfare of developing country exporters is only a fraction of the foreign exchange increase, thereby reflecting the domestic resource cost of increased production. Its ratio to the change in foreign exchange earnings varies between 0.1 and 0.25 because of different implicit export-supply elasticities among commodities. For all four commodities, the predicted increase in world price results in an absolute decrease in the value of developing country imports. This reaction implies an elastic import demand for developing countries as a whole. The reduction in the import bill, although equivalent to a saving of foreign exchange, causes a welfare loss to developing countries, as is evident from the low values of the net welfare change in the last column of table 1.2°/ Taking developing country exporters and importers together, trade liberalization in wheat and maize would actually cause a net welfare loss to these countries as a group. Beef is the commodity for which the difference between gross and net welfare changes is smallest, both in absolute and percentage terms, the reason being that developing countries as a group import less than 20 percent of all beef entering world trade. On the other hand, they import more than 40 percent of all wheat in the preliberalization period. Table 2 reports how the results for sugar change if the calculations are based on 1983 prices and protection levels. The percentage changes in the world price are more than twice as large as those reported in table 1. For the most part the percentage changes in world exports are more than three times larger than those of table 1. Considerably larger numbers also result for foreign exchange earnings and welfare increases. In interpreting table 2, however, it should be remembered that, for many countries outside the European - 37 - Community, the lack of adequate data made the derivation of the 1983 protection -levels even less straightforward than for the period 1979-81. Table 2 Sensitivity Analysis for Sugar--1983 Protection Levels Absolute change in developing country (billions of 1980 U.S. dollars) Percentage change in Foreign Welfare Import Net World World exchange (exporters bill welfare price exports earnings only) Sugarl 39.7 45 4.15 1.06 -0.28 0.46 Sugar2 33.1 36 3.38 0.82 -0.24 0.30 Sugar3 64.5 75 7.39 2.13 -0.35 1.27 Sugar4 29.2 56 4.61 0.86 -0.43 0.44 Note: Superscripts refer to various assumptions with respect to the supply elasticities. Details are given in the text. World exports are defined as the sum of net exports of all net exporting countries. Similarly, all 1983 export and import unit values had to be derived from their 1979-81 levels by means of some conversion factor. Possibly the most important qualification of the 1983 results for sugar has to do with the use of 1979-81 quantities owing to the lack of consistent data for 1983. Finally, one may ask whether the large 1983 protection levels were an unusual occurrence or whether they are more likely to represent historical and future developments of the sugar market than the 1979-81 protection levels. Future developments are not considered here. Historically, however, the year 1983 seems to have been somewhat unusual. The 1983 sugar price2i' was the lowest in real terms since 1948, except for the years 1965 to 1968. For many countries, this also means that, excluding the latter part of the 1960s, protection levels were at a record high in 1983. The nominal protection - 38 - coefficient for the European Community22/ may illustrate this point. For the years 1973-74 to 1982-83, the coefficient has developed as follows: Year 1973-74 75 76 77 78 79 80 81 82 83 l+tO 0.8 0.5 1.1 2.0 2.6 2.8 1.4 0.9 1.8 2.8 In the light of the historical record of sugar prices and protection levels, it seems that the 1983 results for sugar have to be regarded as an upper limit on the costs that trade protectionism imposes on developing countries. As already mentioned, the study includes only developing countries with a minimum of 5 million inhabitants in the base period. Many large sugar producers, however, can be found among those countries that are excluded from this study because of size. It also happens that most of these producers are exporting a considerable portion of their production under a preferential quota system to the European Community. Among this group of ACP countries are such large sugar producers as Mauritius, Guyana, Fiji, Swaziland, Jamaica, and Trinidad. A removal of all trade barriers would eliminate their monopoly rents, which they currently derive from selling their exports to the European Community at internal European Community prices. From data for 1978-79, Schmitz and Koester (1981) estimate that the foreign exchange equivalent of the monopoly rent for the six countries mentioned above is about US$380 million.23- Given similar protection levels of the European Community for 1978-79 and 1983, this figure gives some indication of the likely overestimate of the foreign exchange gains of developing countries for the year 1983. The figure for the average of 1979-81 should be somewhat smaller as a result of the smaller differences between internal European Community prices and the world market price for that time period. Of the countries included in the - 39 - study, several also belong to the ACP group--namely, Kenya, Madagascar, Tanzania, Uganda, and India. However, none of them is actually treated as an ACP country along the lines discussed in the theoretical section.-24 The quota for Kenya, Madagascar, and India is rather small when compared to total exports. Hence their export unit values are not significantly affected for the years 1979-81. Tanzania and Uganda, however, were actually importers rather than exporters of sugar in the base period. When we compare the results in tables 1 and 2 with the findings of other studies, several problems arise. First, commodity definitions often differ. Kirmani, Molajoni, and Mayer (1984), for example, use broad aggregates such as meat or cereals rather than specific commodities such as beef or wheat. Similarly, Anderson and Tyers (1983) study coarse grains rather than maize and ruminant meat instead of beef. Valdes and Zietz (1980) distinguish between raw sugar and refined sugar, whereas the current study is confined to total sugar in raw equivalents. Second, few studies use the same base period. The study of Valdes and Zietz (1980) is based on 1975-77 averages, as is the work by Koester (1982); Anderson and Tyers (1983) take 1980 as their reference year; and the current study utilizes an average of the years 1979-81, as do Kirmani, Molajoni, and Mayer (1984). Third, the calculation of protection levels generally differs among studies. Rather large differences of protection levels are reported by Kirmani, Molajoni, and Mayer (1984, table 1), for example, for a number of surveyed studies. Finally, the methodology employed for a study of trade liberalization can be different enough to make comparisons of results rather meaningless.25/ In the light of the above problems, most of the following comparisons have to be viewed with caution. - 40 - The long-run steady-state results reported by Anderson and Tyers (1983) are similar in spirit to the comparative static results of this study. Furthermore, they choose 1980 as their base year, which is very close to the average of the years 1979-81 utilized in the current study. They report world price increases for ruminant meat, wheat, and coarse grains of 24, 20, and 16 percent, respectively. These are somewhat larger than the price increases given in table 1 for beef, wheat, and maize, the commodities that match the more aggregate commodity groups chosen by Anderson and Tyers. Almost identical numbers are generated for the projected increase in world exports, however. Anderson and Tyers report export increases of 3.9, 7.5, and 24.4 million tons for ruminant meat, wheat, and coarse grains, respectively. The corresponding figures from the current study are 3.7, 8.2, and 25.4 million tons if the benchmark elasticity results are taken. In a recent study for FAO, Tangermann (1980) constructs a model of the world beef market. According to his calculations, a complete removal of trade barriers would result in a world price increase of 47 percent, a value considerably above those reported in table 1. In addition, Tangermann estimates that world exports would increase by 300 percent, which is about twice the size of the values found in this study. One reason for the very large percent changes predicted by Tangermann is his assumption that trade barriers are not only removed in OECD countries but also in certain developing countries with high protection levels, such as the Republic of Korea. In comparing the current results with those of Valdes and Zietz (1980), one has to keep in mind that the 1980 study is based on data for the years 1975-77. In any case, the projected increases in developing country export earnings from trade liberalization in sugar are quite similar in the two studies--around 3 billion in 1980 U.S. dollars.2' The increase in - 41 - developing country export earnings calculated for beef, however, are from six to seven times greater in the present study than they are in the 1980 study, making beef rather than sugar the most promising candidate for trade liberalization. The differences for wheat and maize are less pronounced than for beef. Even so, the current figures for the benchmark elasticity runs are still in the order of two to five times the 1980 results for maize and wheat, respectively. Koester (1982) also utilizes the methodology and basic data base of Valdes and Zietz (1980), but concentrates on the analysis of cereals. Assuming a complete removal of trade barriers in the European Community, Koester predicts an increase in the world price of wheat and maize of 9.6 and 2.2 percent, respectively. Both percentage increases are below those of table 1. However, they are based on the assumption that trade barriers are removed only in the European Community. Koester finds, as we do (see the last column of table 1), that trade liberalization in cereals as a whole results in a net welfare loss to developing countries, although their foreign exchange earnings increase by more than US$1 billion. Two recent studies, Koester and Schmitz (1982) and Roberts (1982), analyze the effects of trade liberalization in sugar. In contrast to this study, they examine the impact of the sugar policy only on the European Community. When they take into account the income transfers derived from preferential access to the high-price European Community market under its Sugar Protocol, Koester and Schmitz conclude that a removal of European Community trade barriers would actually result in a net loss to the ACP countries. In contrast, Roberts calculates that developing countries could expect an increase in welfare of between US$370 million and US$570 million compared with a loss to the ACP countries under the Sugar Protocol of around - 42 - US$170 million. Unfortunately, Robert's results cannot be directly compared to the figures reported in this study because of different assumptions regarding the scope of trade liberalization. Table 3 analyzes the relative significance to developing countries of the foreign exchange earnings reported in table 1. Column (2) relates the absolute increase in export earnings to their preliberalization levels. For all commodities, the percentage changes are quite substantial, especially for beef. Column (3) shows how developing countries would benefit from trade liberalization relative to developed countries. For sugar, almost all of the potential gains of trade liberalization go to the developing countries. The only developed country also benefitting from trade liberalization in sugar is Australia. All other developed countries lose because most have high current levels of protection. Trade liberalization in beef and veal, however, increases export earnings about equally for developed country exporters and the developing countries. Among the developed countries, Australia and the United States have by far the most to gain from trade liberalization in beef. The distribution of benefits among developed and developing countries for the two cereals is very different. Most of the increase in foreign exchange earnings goes to the large developed country exporters--the United States, Canada, and Australia. Columns (4) and (5) of table 3 compare the potential foreign exchange gains of developing countries to the inflow of official development aid. For sugar and beef together, the potential increase in developing country export earnings amounts to one-quarter of total average OECD aid for the year 1979 to 1981 if the calculations are based on the most conservative assumptions. The percentage rises to almost 50 percent if one assumes a strong supply response of developed countries. If developing country export earnings are related to - 43 - Table 3 Absolute and Relative Size of Foreign Exchange Gains of Developing Countries Developing country foreign Foreign Exchange Exchange gains as percentage of Absolute Percentage Gains by Average Official 1979-81 increase change developed 1979-81 aid to cereals (billions of countries OECD aid agriculture imports Commodity U.S. dollars) (1) (2) (3) (4) (5) (6) Sugarl 2.75 103 n.a. 11 25 17 Sugar2 2.19 83 n.a. 9 20 14 Sugar3 5.11 192 n.a. 20 47 32 4 Sugar 3.04 115 n.a. 12 28 19 Sugar831 4.15 289 n.a. 16 38 26 Sugar832 3.38 236 n.a. 13 31 21 Sugar833 7.39 516 n.a. 29 67 46 Sugar834 4.61 322 n.a. 18 42 29 Beefl 5.10 533 82 20 46 32 Beef2 4.38 458 85 17 40 27 Wheat 1 1.17 146 32 5 11 7 Maize 0.61 52 13 2 6 4 Note: Superscripts refer to various assumptions with respect to the supply elasticities. Details are given in the text. Sugar83 stands for the results based on 1983 protection levels. Developed countries in column (3) exclude the European Community. The average development aid of OECD countries used in column (4) is from the World Development Report 1983, p. 182. Official aid to agriculture in column (5) refers to total official 1980 aid commitments, not disbursements, to Food and Agriculture. The raw data are from OECD, 1983, p. 138. The average 1979-81 cereal import bill in column (6) is from FAO Trade Yearbook. It refers to imports of market economy developing countries. The individual year figures are deflated by the world wholesale price index from the International Monetary Fund, International Financial Statistics; n.a. indicates that the share going to developed countries is negligible. - 44 - total 1980 aid commitments to food and agriculture, one can find values ranging from 60 to almost 120 percent, depending on the assumptions. Even though the ratios in both column (4) and (5) seem quite high, they are likely to be underestimated because the foreign exchange earnings of the fifty-eight developing countries included in the present study are compared with the development aid going to all developing countries. A similar argument applies to column (6), which relates the predicted change in the foreign exchange earnings of the developing countries under consideration to the cereal import bill of developing countries classified as market economies by FAQ. Table 4 presents export market shares before and after trade liberalization for all model runs based on benchmark elasticity assumptions. The figures support the earlier conclusion that developing countries as a whole benefit from trade liberalization in sugar and beef. Their share of world exports increases substantially for both commodities, whereas the share going to developed countries outside the European Community drops. Table 4 also highlights the dominance of developed country exporters in the market for cereals. According to the model simulations, this dominance is likely to increase through trade liberalization. An interesting result is the elimination of the European Community as a net exporter for all of the commodities under study. The considerable increases in the export earnings of developing countries reported in tables 1 through 3 do not imply that all these countries share equally in absolute or relative terms in the gains from trade liberalization. This fact is supported by table 5, which lists the countries most affected in absolute terms. From this table, we see that, in absolute terms, the potential gains associated with trade liberalization are heavily - 45 - Table 4 Export Market Share before and after Trade Liberalization Percentage Share of World Exports Developing Developed European Rest of the Commodity countries countries community world (excl. EC) Sugar before 33 10 12 45 after 49 9 0 42 Sugar83 before 33 10 12 45 after 57 9 0 34 Beef before 19 56 7 18 after 39 53 0 8 Wheat before 6 82 9 3 after 11 86 0 3 Maize before 12 83 0 5 after 12 84 0 4 Note: World exports refer to the sum of net exports of all net exporting countries. Results are reported for the benchmark elasticity runs of the model. Sugar83 denotes the results for 1983 protection levels. - 46 - concentrated among a few developing countries. For the commodities under study, Argentina, Brazil, and India seem to benefit by far the most in absolute terms. A more detailed analyis of table 5 reveals that the three- country concentration ratio of foreign exchange gains varies considerably among commodities. For sugar and maize, about two-thirds of the total change in developing country export earnings accrues to three countries. For beef, this share rises to more than three-quarters, and for wheat to 95 percent. Despite the large gains to only a few countries, many smaller developing countries can also expect substantial increases in foreign exchange. For many of them, the relative changes are substantially greater than they are for the large countries of table 5. Moreover, a considerable number of countries only turn into exporters as a result of trade liberalization. (For more details on these last points, the interested reader is referred to appendix B, which provides individual country results for all model runs based on benchmark elasticity assumptions.) Another way to break down the results of this study is presented in table 6, which analyzes the potential impact of trade liberalization on the group of low-income countries. For the purposes of this study, low-income countries are those developing countries with a 1981 per capita gross national product of US$400 or less, according to the World Development Report 1983. Of the developing countries included in this study, twenty-two are categorized as low-income countries. According to column (2), low-income countries as a group suffer a welfare loss from trade liberalization in cereals. This conclusion is similar to the one derived for all developing countries in table 1. Column (3) of table 6 expresses the foreign exchange gains of low-income countries as a percentage of the gains of all fifty-eight developing - 47 - Table 5 Countries Most Affected by Trade Liberalization (millions of 1980 U.S. dollars) Change in Foreign Countries Exchange Net Countries Loss in Gaining Earnings Welfare Losing Net Welfare Sugar India 988 90 Nigeria 63 Brazil 617 177 Korea, Rep. of 56 Philippines 201 83 Iraq 42 Sugar83 India 1,263 202 Nigeria 77 Brazil 863 280 Korea, Rep. of 70 Philippines 275 120 Iraq 52 Beef Argentina 2,233 311 Egypt 91 Brazil 1,370 97 Iran 29 Colombia 404 37 Saudi Arabia 20 Wheat India 602 11 Egypt 115 Turkey 304 26 Brazil 106 Argentina 208 98 Algeria 67 Maize Argentina 175 97 Korea, Rep. of 46 India 118 7 Mexico 38 Brazil 71 -9 Venezuela 20 Note: The results refer to the benchmark elasticity runs of the model. - 48 - countries. The most notable result is probably the low percentage of foreign exchange gains from beef that accrue to low-income countries. Trade liberalization in beef, in other words, is mainly in the interest of middle- or high-income developing countries, particularly those of Latin America. At the same time, the gains to developing countries from free trade in sugar are quite considerable. A comparison of columns (3) and (4) shows that India is the low-income country with by far the largest potential gains. The share of foreign exchange gains going to the group of low-income countries apart from India seems rather low. But again, one has to consider that, for a small developing country, even a negligible share of total benefits may translate into a substantial amount of foreign exchange, in both absolute and relative terms. (See appendix B for individual cases.) Table 6. Effect of Trade Liberalization on Low-Income Countries Change Col. (1) as (millions of 1980 U.S. dollars) Percentage of Col. (3) Change in Foreign Developing without Change in welfare of Exchange Net Country India import bill importers Earnings Welfare Total (percent) (US$ million) (USS million) (1) (2) (3) (4) (5) (6) Sugar 1,129 54 41.1 8.0 -39 -55 Sugar83 1,598 192 38.5 11.6 -25 -62 Beef 38 2 0.7 0.7 -13 -2 Wheat 651 -65 55.8 8.6 -346 -71 Maize 167 -4 27.6 10.1 -38 -11 Note: The results refer to the benchmark elasticity runs of the model. - 49 - Tables 7 to 10 provide a regional account of the impact of trade liberalization on developing countries. Only the results for the benchmark elasticity runs of the model are reported. A change to higher domestic supply elasticities does not appreciably affect the regional impact.27/ For sugar (table 7), Asia and Latin America share about equally in the potential gains of trade liberalization. Sub-Saharan Africa and North Africa and the Middle East, in particular, are net losers with respect to welfare. For beef, the potential gains are almost exclusively concentrated in Latin America, at least in absolute terms. All other regions suffer net welfare losses, although they are rather small in the case of sub-Saharan Africa. The latter region can increase its foreign exchange earnings by a rather substantial percentage. The same also applies to North Africa, the Middle East, and Asia. Trade liberalization in wheat leads to welfare losses in all four regions. Most of the foreign exchange earnings accrue to Asia, particularly to India. Wheat is also the only commodity of the four analyzed in which North Africa and the Middle East could expect to share more than just marginally in the foreign exchange gains of trade liberalization. The individual country results provided in appendix B, however, reveal that essentially all of the gains go to one country, Turkey. In the case of trade liberalization in maize, only Latin America could expect to register net welfare gains. For sub-Saharan Africa, however, the model predicts a large percentage increase in foreign exchange earnings. - 50 - Table 7 Regional Impact of Trade Liberalization on Developing Countries-- Sugar, 1979-81 Protection Levels Change Foreign Distribution of exchange Net change in foreign Change in foreign Change in Region earnings welfare exchange earnings exchange earnings import bill (millions of 1980 US dollars) (percent) (percent) (USS millions) Sub-Saharan Africa 142 -43 5.2 79 25 North Africa Middle East 70 -248 2.5 n.a. -86 Asia 1,379 80 50.2 166 -62 Latin America 1,157 288 42.1 70 -206 Total 2,748 77 100.0 103 -330 Note: N.A. indicates that preliberalization exports are zero or negligible. The results refer to the benchmark elasticity assumptions. Table 8 Regional Impact of Trade Liberalization on Developing Countries--Beef Change Foreign Distribution of exchange Net change in foreign Change in foreign Change in Region earnings welfare exchange earnings exchange earnings import bill (millions of 1980 US dollars) (percent) (percent) (US$ millions) Sub-Saharan Africa 99 -9 1.9 217 -86 North Africa Middle East 131 -162 2.6 n.a. -27 Asia 173 -19 3.4 n.a. -105 Latin America 4,693 506 92.1 517 -107 Total 5,095 317 100.0 533 -325 Note: N.A. indicates that preliberalization exports are zero or negligible. The results refer to the benchmark elasticity assumptions. - 51 - Table 9 Regional Impact of Trade Liberalization on Developing Countries--Wheat Change Foreign Distribution of exchange Net Change in Foreign Change in foreign Change in Region earnings welfare Exchange Earnings exchange earnings Import Bill (millions of 1980 US dollars) (percent) (percent) (US$ millions) Sub-Saharan Africa 4 -71 0.3 n.a 23 North Africa Middle East 345 -325 29.6 453 -89 Asia 611 -127 52.4 n.a. -288 Latin America 208 -132 17.8 29 3 Total 1,167 -656 100.0 146 -351 Note: N.A. indicates that preliberalization exports are zero or negligible. The results refer to the benchmark elasticity assumptions. Table 10 Regional Impact of Trade Liberalization on Developing Countries--Maize Change Foreign Distribution of exchange Net change in foreign Change in foreign Change in Region earnings welfare exchange earnings exchange earnings import bill (millions of 1980 US dollars) (percent) (percent) (US$ millions) Sub-Saharan Africa 90 -18 14.9 412 -139 North Africa Middle East 18 -63 3.0 n.a. -15 Asia 234 -5 38.6 68 2 Latin America 263 19 43.4 33 -420 Total 606 -67 100.0 52 -572 Note: N.A. indicates that preliberalization exports are zero or negligible. The results refer to the benchmark elasticity assumptions. - 52 - 5. Conclusion This study has analyzed the potential benefits to developing countries of trade liberalization in beef and sugar as well as the two cereals wheat and maize. The results seem to support the conclusion that trade liberalization in cereals would likely lead to a net welfare loss to developing countries as a whole, although a number of these countries could expect considerable percentage increases in foreign exchange earnings. This conclusion applies in particular to the case of wheat. According to results obtained with the model, most of the gains of trade liberalization in cereals would accrue to the large developed country exporters, namely, the United States, Canada, and Australia, at the expense of the members of the European Community. In contrast to the case of cereals, trade liberalization in sugar and beef would probably be of benefit to the developing countries. For both commodities together, a complete removal of tariff barriers could result in net welfare gains of US$250 million to more than US$1.5 billion per year, depending on the underlying assumptions.28- The corresponding increase in foreign exchange earnings could be anywhere from US$6.6 billion to more than US$12 billion per year, again depending on the assumptions regarding supply elasticities and protection levels.29/ For just two commodities, these numbers are very large, not only in absolute terms but also when compared with the preliberalization export earnings of developing countries or the flow of development aid to these countries. Trade liberalization in sugar benefits developing countries almost exclusively. Only a fraction of the total increase in export earnings is - 53 - expected to be captured by developed country exporters. This is somewhat different for beef, for which total benefits, if measured in terms of foreign exchange, are split about equally among developed and developing countries. As for the regional distribution of benefits, both Latin America and Asia could expect about half of total developing country foreign exchange increases resulting from trade liberalization in sugar. Latin America has the most to gain from a removal of tariffs on beef. It would capture 92 percent of the foreign exchange gains going to developing countries. The countries of North Africa and the Middle East are likely to suffer a net welfare loss from trade liberalization in both sugar and beef. Sub-Saharan Africa could expect to realize substantial percentage increases in foreign exchange earnings from all commodities except wheat. Overall, the predicted gains to developing countries from trade liberalization in beef and sugar are quite substantial. They certainly do not support some recent pessimistic appraisals of the effects of trade liberalization in temperate-zone agricultural products (Matthew 1984). To put the reported results in the proper perspective, one must remember that these results have to be interpreted as static gains or losses. Some rudimentary efforts have been made to capture at least part of what may be called dynamic gains through the use of larger supply elasticities for developing countries in alternative model runs. It is unlikely, however, that all of the potential benefits of trade liberlization to developing countries are captured by these model simulations. As pointed out by Valdes and Zietz (1980), "permanently reducing trade barriers would lead the [developing countries] to develop new export products, including the expansion of their own processing operations. In addition, it would probably encourage [developing countries] to concentrate more resources on increasing agricultural production." Trade liberalization - 54 - is, in other words, likely to break the current climate of "export pessimism" that inhibits the adoption of export-oriented policies in the agricultural sector. As a result, the overall development performance of many developing countries could be expected to improve perceptively. - 55 - Footnotes 1/ For constant r and m, ph is negative; that is, the domestic price decreases if the ratio of post- to preliberalization world price is smaller than (1+tO)/(l+tl), or in case of a complete elimination of tariffs, if the world price increase, pwh, is smaller than the preliberalization tariff, tO. 2/ Here, as in all other cases, domestic demand-and-supply elasticities are assumed to be constant. Equations (1) and (2) then give the exact changes in C and Q, even for large variations in p. 3/ The expressions in parentheses are the small change equivalents of equations (1) and (2) in the text. 4/ The authors thank Ron Duncan of the World Bank for pointing out this special case. 5/ The determining equation for dVM implies that developing countries are forced to import at the world market price in the postliberalization period, irrespective of possible differences in transportation costs, quality differences, and the like. This simplifying assumption is likely to overestimate the losses that would be incurred by developing countries if inexpensive Australian beef exports were discontinued. 6/ This category includes all types of raw sugar and refined sugar. 7/ The following ACP countries are excluded from the calculation of the world export unit value: Barbados, Fiji, Guyana, Jamaica, Mauritius, and Trinidad and Tobago. 8/ The larger the set of commodities incorporated in a study, the greater is the possibility of interdependencies among commodities. In a partial equilibrium setting it is thus advisable to adjust the own-elasticities downward. In an earlier study, (Valdes and Zietz 1980), we considered ninety- nine rather than just four commodities. In keeping-with the above logic, a supply elasticity of 0.4 was used, a value below or more conservative than the one employed in the current study. 9/ See also Peterson (1979) for a strong argument in favor of an aggregate supply elasticity around 1.2 for developing countries. 10/ The world price, pwO, is not used to calculate protection levels because it does not allow for differences in transport costs or the composition of imports from country to country. The latter is particularly relevant because the commodity definitions used in this study are quite broad. 11/ Here, as in all other cases, the Belgian price is taken to represent the price for the table entry Belgium/Luxembourg in the Appendix. Since no beet prices are reported for Denmark for the years 1979 to 1981, the beet prices in Krona were derived from the 1975 price using the producer price index for sugar beet as reported in European Community Agricultural Price Indices - 56 - (January 1984). The Krona prices were converted into ECU using the implicit conversion rate for crystallized sugar (Agricultural Price Statistics 1983, table 1540). 12/ The 1983 protection levels for the European Community as well as those for all other developed countries are presented in appendix B. 13/ Its calculation corresponds to the one described above, except that the import unit value of Sweden was used for Austria, Sweden itself, and Switzerland. The 1978 import unit value of Switzerland was judged an unreliable indicator of the border price of total sugar. Switzerland imports refined sugar almost exclusively. This caused the import unit value for total sugar to be biased upward considerably for 1978, quite unlike the years 1978 to 1981. 14/ See Saxon and Anderson (1982, table 8) for historical evidence. Imports are restricted to boneless beef to minimize the danger of importing the hoof and mouth disease. 15/ Such as U.S imported beef, frozen, boneless, 90 percent visible lean, f.o.b. port of entry as quoted for example in Singh (1983, p. 86). 16/ What is referred to is the partial redundancy of the official threshold price for wheat exporters. 17/ Unless otherwise noted, developing countries refers to the fifty-eight countries included in the study. 18/ For beef, the supply elasticities of all European Community countries and Japan are reduced to 0.4. For wheat and maize, the default supply elasticities of all developing countries is doubled to 0.8. 19/ They are identified by superscript 1. 20/ The change in net welfare is calculated as the difference between the welfare increases enjoyed by developing country exporters and the welfare losses incurred by developing country importers. 21/ The following refers to the sugar price of the International Sugar Organization as quoted, for example, by Singh (1983). 22/ It is calculated as the ratio of the European Community threshold price* of raw sugar to its c.i.f. Rotterdam price. 23/ The figures are taken from the authors' table 14 and are converted into 1980 U.S dollars using the 1978 $/ECU exchange rate and the world wholesale price index from the International Financial Statistics. 24/ In the case of beef, only two countries, Kenya and Madagascar, met the conditions explained in the theoretical section that call for special treatment of ACP countries. 25/ See, for example, the study by Fischer and Frohberg (1984). - 57 - 26/ This takes into account the different assumptions regarding the percentage reduction in tariffs between the two studies. 27/ Neither does the replacement of 1979-81 prices and protection levels by 1983 values for the case of sugar. 28/ All value terms are expressed in 1980 U.S. dollars. 29/ It should be pointed out that larger numbers than those reported can be obtained if certain model assumption are combined, such as very large supply elasticities and protection levels of developed countries with very elastic supply responses of developing countries. - 58, - References Anderson, K., and R. Tyers. 1983. "European Community's Grain and Meat Policies and U.S. Retaliation: Effects on International Prices, Trade and Welfare." Australian National University, Canberra, October. Askari, H., and J.T. Cummings. 1976. Agricultural Supply Response: A Survey of the Econometric Evidence. New York: Praeger. Carson, Richard T., Alan Love, and Fabien Keller-Griesmar. 1984. "The Soviet Grain Import Decision As A Short Term Control Problem." Paper read at the American Agricultural Economics Association Annual Summer Meeting, Cornell University, August. Caspari, Conrad, Donald LacLaren, and Georgina Hobhouse. 1980. Supply and Demand Elasticities for Farm Products in the Member Countries of the European Community. (Under the direction of Edmund Neville-Rolfe, Bureau Europeen de Recheres, Brussels, Belgium.) USDA: International Economics Division; Economics, Statistics, and Cooperative Service, January. Fischer, Guenther, and Klaus Frohberg. 1984. "The Differential Impact on Trade Liberalization in Agricultural Products on Developing and Industrialized Countries." Paper read at the 4th European Congress of Agricultural Economists, Kiel. Kirmani, N., P. Molajoni, and T. Mayer. 1984. "Effects of Increased Market Access on Selected Developing Countries' Export Earnings: An Illustrative Exercise." Washington, D.C.: International Monetary Fund, August 24. Koester, U. 1982. Policy Options for the Grain Economy of the European Community: Implications for Developing Countries. Research Report no. 35. Washington, D.C.: International Food Policy Research Institute. Koester, U., and P.M. Schmitz. 1982. "The EC Sugar Market Policy and Developing Countries." European Review of Agricultural Economics 9 (2): pp. 183-204. Matthews, Alan. 1984. "The CAP and the Less Developed Countries: A Review of the Evidence." Paper read at the 4th European Congress of Agricultural Economists, Kiel. Peterson, Willis L. 1979. "International Farm Prices and the Social Cost of Cheap Food Policies." American Journal of Agricultural Economic 62(1) (February): 12-21. Roberts, I.M. 1982. "EEC Sugar Support Policies and World Market Prices: A Comparative Static Analysis". Australian Bureau of Agricultural Economics Working Paper no. 82-13, Canberra. Saxon, E., and K. Anderson. 1982. "Japanese Agricultural Protection in Historical Perspective." Pacific Economic Paper no. 82-13 Canberra: Australia-Japan Research Centre. - 59 - Schmitz, P.M., and U. Koester. 1981. "Der Einfluss der EG-Zuckerpolitik auf die Entwicklungslaender." Working Paper no. 42, Institut fuer Agrarpolitik und Marktlehre, Universitaet Kiel, June. Singh, Shamsher. 1983. Sub-Saharan Agriculture, Synthesis and Trade Prospects. World Bank Staff Working Paper no. 608, Washington, D.C. Stern, R.M., J. Francis and B. Schumacher. 1976. Price Elasticities in International Trade. An Annotated Bibliography. New York: Macmillan. v. Tangermann, Stefan. 1980. "Protectionism in the Livestock Sector." Rome: Food and Agriculture Organization of the United Nations. Tyers, Rod. 1982. "Effects on Asean of Food Trade Liberalisation in Industrial Countries." Paper read at the Second Western Pacific Food Trade Workshop, Jakarta, August. Tyers, Rod, and K. Anderson. 1983. "Price, Trade and Welfare Effects of Agricultural Protection: the Case of East Asia." Australian National University, Canberra, September. Valdes, Alberto. 1975. "Algunos Aspectos Economicos de la Industria Ganadera en America Tropical." In CIAT, "El Potencial para la Produccion de Ganado de Carne en America Tropical." Cali: International Center for Tropical Agriculture, Series CS-10, November. Valdes, Alberto, and Joachim Zietz. 1980. Agricultural Protection in OECD Countries: Its Cost to Less-Developed Countries. Research Report 21 Washington, D.C.: International Food Policy Research Institute. Other Statistical Sources Agriculture Canada. Livestock Market Review. Ottawa, various years. Australia Yearbook. Bundesministerium fuer Land-und Forstwirtschaft. 1982. Taetigkeitsbericht 1982. Bern. . 1982. Lagebericht 1982. Bern. Commodity Research Bureau. 1984. Commodity Yearbook Statistical Abstract Service, Vol. 21, No. 3, April. European Community. Yearbook of Agricultural Statistics, 1978-81. Luxembourg: Statistical Office of the European Community. . Agricultural Price Statistics, 1983. Luxembourg: Statistical Office of the European Community. _ 1983. Official Journal of the European Communities. L132, vol. 26, 21. May. - 60 - . 1984. EC Agricultural Price Indices (Output and Input), Index of Producer Prices of Agricultural Products. Luxembourg: Statistical Office of the European Community, 1. . 1984. Agricultural Prices, 6. Food and Agriculture Organization. Trade Yearbook, Rome: various issues. . 1984. Preliminary Food Balance Sheets, 1979-81. Rome: computer printout. . 1983. Producer Prices, 1968-1982. Rome: computer printout. International Monetary Fund. 1984. International Financial Statistics. Washington, D.C. International Sugar Organization. Sugar Yearbook. London: various issues. International Wheat Council. 1982. World Wheat Statistics. London. Ministry of Agriculture, Forestry and Fisheries. 1984. The Meat Statistics in Japan. Livestock Bureau, Tokyo, January. . 1981-82. The 58th Statistical Yearbook of Ministry of Agriculture, Forestry and Fisheries. Statistics and Information Department, Tokyo. New Zealand Yearbook. Organisation for Economic Co-operation and Development. 1984. OECD Economic Outlook, Historical Statistics, 1960-82. Paris: OECD. _ 1983. Development Co-operation, Effects and Policies of the Members of the Development Assistance Committee, 1983 Review. Paris: OECD. Statistics Canada. Cereals and Oilseeds Review. Ottawa, various years. Statistisches Handbuch fuer die Rupublik Oesterreich. 1983. U.S. Department of Commerce, Bureau of Economic Analysis. 1983. Business Statistics 1982. Washington, D.C.: Government Printing Office, November. World Bank. 1983. World Development Report, 1983. Washington, D.C. - 61 - Appendix A Input Data by Commodity and Country In the following pages we present the raw data, by commodity, for the calculations described in the theoretical section.30/ The notation corresponds to that used elsewhere in the study. X0 stands for net exports, MO for net imports, QO for production, CO for consumption. The subscript 0 indicates pre-liberalization levels.31/ All four quantity variables are averages for the years 1979 to 1981. The dimension is thousands of metric tons. Blanks appear for countries that were neither importing nor exporting in the base period. It is assumed that trade liberalization would not change this situation. Economically, this can be rationalized by assuming that domestic demand and supply elasticities are the same in absolute terms. The latter are denoted by eC,p and eQ,p, respectively. For developed countries, the nominal rate of protection (tO) is given whenever it exceeds zero. For some developed countries two values are presented for tO. The first one is the nominal protection rate relevant to producers indicating the percentage rate by which the domestic producer price exceeds the world market price. The second tO-value gives the percentage rate by which the domestic wholesale price exceeds the world market price. 30/ The export and import unit values for each country and commodity are not listed because they can be easily obtained from the 1981 FAO Trade Yearbook. 31/ No subscripts or superscripts are used in the following listings. - 62 - SUGAR XO MO QO CO eQ,p eC,p SUB-SAHARAN AFRICA Angola 66 33 99 0.60 -0.40 Barkina Faso Cameroon 1 61 60 0.60 -0.40 Ethopia 9 165 158 0.60 -0.40 Ghana 39 4 43 0.60 -0.40 Guinea 7 20 27 0.60 -0.40 Ivory Coast 18 101 78 0.60 -0.40 Kenya 43 386 344 0.60 -0.40 Madagascar 19 115 94 0.60 -0.40 Malawi 94 141 49 0.60 -0.40 Mozambique 82 189 126 0.60 -0.40 Niger 15 18 -0.40 Nigeria 732 42 774 0.60 -0.40 Rwanda 4 3 8 0.60 -0.40 Senegal 39 46 83 0.60 -0.40 Tanzania 6 129 135 0.60 -0.40 Uganda 29 5 50 0.60 -0.40 Voltahas Zaire 8 52 66 0.60 -0.40 Zambia 1 105 104 0.60 -0.40 Zimbabwe 205 353 177 0.60 -0.40 SUBTOTAL 428 1,013 1,965 2,531 ASIA Bangladesh 38 133 180 0.60 -0.40 Burma Hong Kong 103 104 -0.40 India 288 5,385 6,028 0.60 -1.75 Indonesia 528 1,271 1,679 0.60 -0.40 Korea, Rep. of 718 718 -0.40 Malaysia 421 60 486 0.60 -0.40 Nepal 9 17 28 0.60 -0.40 Pakistan 65 679 819 0.60 -1.75 Philippines 1,381 2,360 1,256 0.60 -0.60 Sri Lanka 251 25 252 0.60 -0.40 Thailand 892 1,534 631 0.60 -0.40 SUBTOTAL 2,561 2,133 11,464 12,181 - 63 - XO MO QO Co eQ,p eC,p NORTH AFRICA/ MIDDLE EAST Afghanistan 80 7 85 0.60 -0.40 Algeria 557 8 582 0.60 -0.60 Egypt 474 663 1,177 0.60 -0.40 Iran IR 634 452 1,264 0.60 -0.80 Iraq 589 32 504 0.60 -0.40 Morocco 310 364 678 0.60 -0.40 Saudi Arabia 294 234 -0.40 Sudan 240 175 446 0.60 -0.40 Syria 212 34 272 0.60 -0.40 Tunisia 161 6 164 0.60 -0.40 Turkey 84 1,194 1,155 0.60 -0.70 Yemen AR 99 82 0.60 -0.40 SUBTOTAL 0 3,734 2,935 6,643 LATIN AMERICA Argentina 524 1,584 1,077 0.60 -0.40 Bolivia 84 270 179 0.60 -0.40 Brazil 2,424 7,989 6,249 0.60 -0.40 Chile 242 139 424 0.60 -0.50 Colombia 231 1,192 960 0.60 -0.40 Dominican Rep. 878 1,107 202 0.60 -0.40 Ecuado 61 357 322 0.60 -0.40 El Salvador 70 210 148 0.60 -0.40 Guatelmala 184 408 245 0.60 -0.40 Haiti 8 55 67 0.60 -0.40 Mexico 274 2,810 2,950 0.60 -0.40 Peru 78 580 573 0.60 -0.60 Venezuela 376 339 700 0.60 -0.42 SUBTOTAL 4,534 900 17,040 14,096 Developing Country Total 7,523 7,780 33,404 35,451 - 64 - XO MO QO Co tO eQ,p eC,p DEVELOPED COUNTRIES Australia 2,201 3,242 763 0.06 0.60 -0.39 Austria 90 450 380 0.65 0.60 -0.42 Canada 830 118 1,008 1.22/.22 0.60 -0.30 Japan 2,128 779 3,000 1.31 0.60 -1.00 New Zealand 147 161 -0.40 Norway 183 189 0.0/.25 -0.40 Sweden 9 350 368 0.17 0.60 -0.32 Switzerland 154 120 283 1.88/.79 0.60 -0.31 United States 3,673 5,345 9,372 0.28 0.60 -0.25 SUBTOTAL 2,291 7,124 10,404 15,524 EUROPEAN COMMUNITY Belgium/ Luxemboug 581 994 382 0.54 0.60 -0.27 Denmark 228 493 243 0.56 0.60 -0.24 France 2,269 4,720 2,188 0.48 0.60 -0.30 Germany 855 3,261 2,402 0.59 0.60 -0.34 Ireland 18 178 189 0.67 0.60 -0.34 Italy 59 1,956 1,989 0.69 0.60 -0.85 Netherlands 216 1,000 767 0.60 0.60 -0.37 United Kingdom 1,259 1,215 2,474 0.67 0.60 -0.47 SUBTOTAL 4,167 1,318 13,817 10,634 MOEC 0 XOWLD 23,121 XOROW 10,458 XOEC 2,849 MOROW 8,831 - 65 - BEEF AND VEAL XO MO QO Co eQ,p eC,p SUB-SAHARAN AFRICA Angola 9 50 59 0.40 -0.40 Burkina Faso 1 29 28 0.40 -0.40 Cameroon 1 50 49 0.40 -0.40 Ethopia Ghana 3 11 14 0.40 -0.40 Guinea Ivory Coast 11 45 56 0.40 -0.40 Kenya 1 183 182 0.40 -0.40 Madagascar 4 124 117 0.40 -0.40 Malawi Mali Mozambique 2 36 38 0.40 -0.40 Niger 1 37 38 0.40 -0.40 Nigeria 22 250 272 0.40 -0.40 Rwanda Senegal Tanzania Uganda Zaire 1 22 23 0.40 -0.40 Zambia Zimbabwe 17 82 65 0.40 -0.40 SUBTOTAL 25 48 919 941 ASIA Bangladesh Burma Hong Kong 22 33 55 0.40 -0.40 India Indonesia 1 130 131 1.00 -1.40 Korea, Rep. of 37 118 155 0.50 -1.00 Malaysia 9 10 19 0.38 -1.30 Nepal Pakistan Philippines 6 77 83 0.50 -0.49 Sri Lanka Thailand SUBTOTAL 0 75 368 443 - 66 - XO MO QO CO eQ,p eC,p NORTH AFRICA MIDDLE EAST Afghanistan Algeria 19 44 63 0.40 -0.40 Egypt 69 129 198 0.40 -0.40 Iran IR 48 171 219 0.40 -0.40 Iraq 13 52 65 0.40 -0.40 Morocco 4 106 110 0.40 -0.40 Saudi Arabia 45 20 65 0.40 -0.40 Sudan Syria 7 28 35 0.40 -0.40 Tunisia 6 27 33 0.40 -0.40 Turkey 1 229 228 0.40 -0.40 Yemen AR 1 13 14 0.40 -0.40 SUBTOTAL 1 212 819 1,030 LATIN AMERICA Argentina 348 2,964 2,643 1.00 -0.50 Bolivia Brazil 52 2,103 2,155 1.00 -0.50 Chile 6 171 177 1.00 -0.50 Colombia 16 607 591 1.00 -0.50 Dominican Rep. 2 49 47 0.60 -0.40 Ecuador El Salvador 2 29 27 0.60 -0.40 Guatemala 16 83 67 0.60 -0.40 Haiti 1 25 24 0.60 -0.40 Mexico 10 600 590 0.60 -0.40 Peru 5 87 92 0.60 -0.40 Venezuela 7 358 365 1.00 -0.50 SUBTOTAL 395 70 7,076 6,778 Developing Country Total 421 405 9,182 9,192 - 67 - XO MO QO Co tO eQ,p eC,p DEVELOPED COUNTRIES Australia 876 1,683 807 0.35 -1.16 Austria 7 199 192 0.29 0.40 -0.40 Canada 13 978 995 0.09 0.40 -0.40 Japan 143 430 573 3.05 0.80 -1.20 New Zealand 330 502 182 0.06 0.40 -0.56 Norway 8 73 81 0.99 0.40 -0.40 Sweden 4 156 152 0.55 0.40 -0.40 Switzerland 12 161 173 1.33 0.40 -0.40 United States 747 10,092 10,871 0.50 -0.80 SUBTOTAL 1,217 933 14,274 14,026 EUROPEAN COMMUNITY Belgium/Luxembourg 24 306 282 0.66 1.02 -1.70 Denmark 166 246 71 0.34 1.02 -1.10 France 54 1,832 1,741 0.48 1.02 -0.41 Germany 130 1,498 1,368 0.54 0.68 -0.37 Ireland 284 384 101 0.38 1.02 -0.56 Italy 316 1,121 1,437 0.60 1.02 -0.62 Netherlands 126 420 294 0.50 0.62 -1.09 United Kingdom 326 1,063 1,421 0.38 1.02 -1.24 SUBTOTAL 784 642 6,870 6,715 MOEC 0 XOWLD 2,179 XOROW 399 XOEC 142 MOROW 841 - 68 - WHEAT XO MO QO Co eQ,p eC,p SUB-SAHARAN AFRICA Angola 176 10 173 0.40 -0.40 Burkina Faso 30 30 -0.40 Cameroon 107 2 109 0.40 -0.40 Ethopia 256 543 799 0.40 -0.40 Ghana 131 138 -0.40 Guinea 42 42 -0.40 Ivory Coast 183 189 -0.40 Kenya 39 212 279 0.40 -0.40 Madagascar 57 57 -0.40 Malawi 16 1 17 0.40 -0.40 Mali 24 2 26 0.40 -0.40 Mozambique 164 5 169 0.40 -0.40 Niger 33 2 34 0.40 -0.40 Nigeria 1,187 24 1,344 0.40 -0.40 Senegal 107 117 -0.40 Tanzania 46 71 137 0.40 -0.40 Uganda 6 10 16 0.40 -0.40 Rwanda 7 3 10 -0.40 Zaire 176 5 175 0.40 -0.40 Zambia 137 9 148 0.40 -0.40 Zimbabwe 1 174 195 0.40 -0.40 SUBTOTAL 1 2,924 1,073 4,204 ASIA Bangladesh 1,145 803 1,835 0.67 -0.40 Burma 13 83 96 0.40 -0.40 Hong Kong 91 123 214 0.40 -0.40 India 500 34,550 36,383 0.41 -0.40 Indonesia 1,244 1,244 -1.20 Korea, Rep. of 1,853 64 1,917 0.45 -0.36 Malaysia 487 489 -0.10 Nepal 6 444 450 0.40 -0.40 Pakistan 1,046 10,686 11,289 0.40 -0.40 Philippines 779 779 -0.40 Sri Lanka 673 673 -0.40 Thailand 173 173 -0.66 SUBTOTAL 0 8,010 46,753 55,542 - 69 - XO MO QO CO eQ,p eC,p NORTH AFRICA MIDDLE EAST Afghanistan 77 2,804 2,911 0.40 -0.40 Algeria 2,509 1,296 3,670 0.40 -0.40 Egypt 5,234 1,864 6,991 0.40 -0.40 Iran IR 1,118 6,155 7,286 0.40 -0.40 Iraq 1,698 1,297 2,172 0.40 -0.40 Morocco 1,847 1,500 3,457 0.40 -0.40 Saudi Arabia 777 164 816 0.40 -0.40 Sudan 233 206 439 0.40 -0.40 Syria 389 1,882 1,805 0.40 -0.40 Tunisia 632 837 1,371 0.40 -0.40 Turkey 477 17,041 17,298 0.40 -0.40 Yemen AR 413 58 461 0.40 -0.40 SUBTOTAL 477 14,927 35,104 48,677 LATIN AMERICA Argentina 4,230 7,927 4,596 0.40 -0.40 Bolivia 310 65 368 0.40 -0.40 Brazil 4,259 2,613 6,529 0.40 -0.40 Chile 954 882 1,876 0.40 -0.40 Colombia 437 50 499 0.40 -0.40 Dominican Rep. 166 161 -0.40 Ecuador 242 34 245 0.40 -0.40 El Salvador 105 111 -0.40 Guatemala 115 49 206 0.40 -0.40 Haiti 171 172 -0.40 Mexico 1,015 2,749 3,784 0.40 -0.40 Peru 780 99 932 0.40 -0.40 Venezuela 790 800 -0.40 SUBTOTAL 4,230 9,344 14,468 20,279 Developing Country Total 4,708 35,205 97,398 128,702 - 70 - XO HO QO Co tO eQ,p eC,p DEVELOPED COUNTRIES Australia 10,853 14,472 2,968 0.88 -0.15 Austria 177 1,025 826 .27/.11 0.40 -0.40 Canada 15,458 20,430 5,278 0.53 -0.18 Japan 5,647 570 6,045 2.79/.27 0.60 -0.60 New Zealand 43 323 370 0.88 -0.15 Norway 370 64 431 0.90 0.40 -0.40 Sweden 348 1,097 785 0.12 0.40 -0.40 Switzerland 358 410 752 1.76 0.40 -0.40 United States 39,126 66,290 21,669 0.80 -0.21 SUBTOTAL 65,962 6,418 104,681 39,124 EUROPEAN COMMUNITY Belgium/Luxembourg 303 949 1,273 0.45 0.90 -0.50 Denmark 143 692 495 0.41 0.90 -0.50 France 11,120 22,028 10,766 0.44 0.90 -0.50 Germany 38 8,107 7,935 0.50 0.90 -0.50 Ireland 260 245 495 0.38 0.90 -0.50 Italy 1,475 8,988 10,809 0.48 0.90 -0.50 Netherlands 534 867 1,474 0.45 0.90 -0.50 United Kingdom 1,186 8,115 8,919 0.45 0.90 -0.50 SUBTOTAL 11,301 3,758 49,991 42,166 MOEC 0 XOWLD 80,308 XOROW 2,095 XOEC 7,543 MOROW 39,971 - 71 - MAIZE XO MO QO CO eQ,p eC,p SUB-SAHARAN AFRICA Angola 113 303 412 0.40 -0.40 Burkina Faso 13 111 133 0.40 -0.40 Cameroon 8 409 417 0.40 -0.40 Ethopia 13 1,125 1,164 0.40 -0.40 Ghana 43 380 423 0.40 -0.40 Guinea 3 52 55 0.40 -0.40 Ivory Coast 19 280 299 0.40 -0.40 Kenya 87 1,785 1,979 0.40 -0.40 Madagascar 1 122 121 0.40 -0.40 Malawi 22 1,164 1,264 0.40 -0.40 Mali 13 66 79 0.40 -0.40 Mozambique 136 275 411 0.40 -0.40 Niger 1 9 11 0.40 -0.40 Nigeria 167 1,543 1,710 0.40 -0.40 Rwanda Senegal 19 60 81 0.40 -0.40 Tanzania 136 800 969 0.40 -0.40 Uganda 17 360 419 0.40 -0.40 Zaire 216 570 736 0.40 -0.40 Zambia 183 941 1,237 0.40 -0.40 Zimbabwe 127 1,834 1,493 0.40 -0.40 SUBTOTAL 128 1,209 12,189 13,413 ASIA Bangladesh Burma 16 123 107 0.40 -0.40 Hong Kong 17 268 285 0.40 -0.40 India 9 6,440 6,389 0.70 -0.35 Indonesia 31 3,844 3,830 0.22 -0.35 Korea, Rep. of 2,710 149 2,859 0.28 -0.22 Malaysia 433 8 441 0.65 -0.35 Nepal Pakistan 3 917 920 0.19 -0.35 Philippines 179 3,211 3,390 0.40 -0.35 Sri Lanka 1 22 23 0.40 -0.40 Thailand 2,270 3,103 410 0.22 -0.50 SUBTOTAL 2,286 3,383 18,085 18,654 -72 - XO -MO QO Co eQ,p eC,p NORTH AFRICA MIDDLE EAST Afghanistan Algeria 185 1 178 0.40 -0.40 Egypt 909 3,159 4,110 0.40 -0.40 Iran IR 738 56 794 0.40 -0.40 Iraq 158 93 251 0.40 -0.40 Morocco 133 245 421 0.40 -0.40 Saudi Arabia 622 3 625 0.40 -0.40 Sudan Syria 157 43 180 0.69 -0.40 Tunisia 187 187 0.40 -0.40 Turkey 3 1,263 1,260 0.40 -0.40 Yemen AR 6 82 88 0.40 -0.40 SUBTOTAL 3 3,095 4,945 8,094 LATIN AMERICA Argentina 6,186 9,333 3,533 0.40 -0.40 Bolivia 2 422 391 0.40 -0.40 Brazil 1,324 19,259 20,583 0.40 -0.40 Chile 316 471 744 0.40 -0.40 Colombia 111 868 959 0.40 -0.40 Dominican Rep. 149 38 186 0.40 -0.40 Ecuador El Salvador 1 517 523 0.40 -0.40 Guatemala 65 947 1,020 0.40 -0.40 Haiti 13 179 187 0.40 -0.40 Mexico 2,532 11,967 13,633 0.40 -0.40 Peru 223 554 777 0.40 -0.40 Venezuela 883 654 1,571 0.40 -0.40 SUBTOTAL 6,186 5,619 45,209 44,107 Developing Countries Total 8,601 13,306 80,428 84,268 - 73 - XO MO QO co to eQ,p eC,p DEVELOPED COUNTRIES Australia 25 164 145 0.60 -0.15 Austria 32 1,338 1,336 0.28 0.40 -0.40 Canada 487 5,901 6,303 0.68 -0.40 Japan 12,610 4 12,614 3.49 0.60 -0.60 New Zealand 38 162 120 0.60 -0.15 Norway 68 68 0.86 -0.40 Sweden 112 122 0.38 -0.40 Switzerland 290 120 410 2.23 0.40 -0.40 United States 59,296 192,924 127,392 0.75 -0.40 SUBTOTAL 59,359 13,599 200,613 148,510 EUROPEAN COMMUNITY Belgium/Luxembourg 2,611 38 1,305 0.73 0.91 -0.80 Denmark 336 340 0.58 -0.80 France 2,410 9,576 6,775 0.62 0.91 -0.80 Germany 1,961 748 2,963 0.76 0.91 -0.80 Ireland 198 198 0.60 -0.80 Italy 2,894 6,950 9,484 0.64 0.91 -0.80 Netherlands 2,337 2 2,128 0.69 0.91 -0.80 United Kingdom 2,804 1 2,805 0.70 0.91 -0.80 SUBTOTAL 2,410 13,141 16,955 25,998 MOEC 10,731 XOWLD 71,471 XOROW 3,442 XOEC 0 MOROW 36,545 - 74 - Appendix B Individual Country Results by Commodity The following listings contain detailed country results for all model runs with benchmark elasticities. The column headings correspond to the respective equations in the theoretical section. For developed countries outside the European Community and the members of the community, the change in consumption (DC), the change in production (DQ), and the postliberalization levels of exports (X1) and imports (Ml) are given. The column TRVIM provides the postliberalization level of imports of a country with a trade reversal from an exporting to an importing status. Similarly, TRVEX gives the post- liberalization level of exports of'a country with a trade reversal from a net- importing to a net-exporting status. MIEC represents the postliberalization import level of the,.EurQpean community as trading entity, XlEC the corresponding export, level. For the-sugar results based on 1983 protection levels, the corresponding levels of tO are added in a separate column. All quantities are in thousands of metric tons. For developing countries, the following results are presented: the change in welfare of exporters and-countries with a trade reversal from a net- importing to a net-exporting status (DWX), the change in foreign exchange earnings (DVX), the preliberalization level of foreign exchange earnings (VXO), the percentage change in foreign exchange earnings (percentage change VX), the change in the import'bill'(DVM),' and the change in welfare of net- importing developing countries'or APC countries that experience a trade - 75 - reversal from a net-exporting-to a net-importing status (DWM). All, numbers except the percentage changes are expressed i-n thousands of 1980 U.S. dollars; "na" indicates that the country was a net importer in the preliberalization period, and "Low Inc." sums the respective column over all low-income c6untries as defined in the data sectiofn.. The low-income category for;Latin America consists solely of Haiti and thus has not been separated in the listings. - 76 -, Sugar DEVELOPED DC DQ TRVIM TRVEX Xi Ml COUNTRIES Australia -28 193 0 0 2422 0 Austria 59 -84 54 0 0 54 Canada 214 -38 0 0 0 1082 Japan 2937 -262 0 0 0 5327 New Zealand -10 0 0 0 0 137 Norway 5 0 0 0 0 188 Sweden 0 -O O 0 0 10 Switzerland 40 -50 0 0 0 244 United States 245 -288 0 0 0 4206 SUBTOTAL 3464 -529 54 0 2422 11249 EUROPEAN DC DQ TRVIM TRVEX Xi Ml COMMUNITY Belgium/Luxembourg 30 -152 0 0 399 0 Denmark 18 -79 0 0 132 0 France 162 -627 0 0 1481 0 Germany 266 -552 0 0 37 0 Ireland 24 -34 41 0 0 41 Italy 735 -390 0 0 0 1184 Netherlands 95 -172 51 0 0 51 United Kingdom 454 -235 0 0 0 1948 SUBTOTAL 1783 -2241 92 0 2048 3224 MlEC 1175 XlEC 0 - 77 - DWX DVX VXO %change DVM DWM SUB-SAHARA VX AFRICA Angola 0 0 0 0 176 -4991 Burkina Faso 0 0 0 0 0 0 Cameroon 319 4012 0 na -401 0 Ethopia 1022 8787 2527 348 0 0 Ghana 0 0 0 0 1430 -2934 Guinea 0 0 0 0 -1597 -466 Ivory Coast 1835 8661 7821 111 0 0 Kenya 5472 34084 19522 175 0 0 Madagascar 2020 10051 8373 120 0 0 Malawi 8102 16642 44507 37 0 0 Mali 0 0 0 0 -196 -2083 Mozambique 6711 18585 34651 54 0 0 Niger 0 0 0 0 708 -1372 Nigeria 0 0 0 0 33668 -62704 Rwanda 0 0 0 0 -145 -379 Senegal 0 0 0 0 -2476 -3147 Tanzania 291 6886 0 na -2796 0 Uganda 0 0 0 0 375 -2185 Zaire -504 477 0 na -3593 0 Zambia 552 7265 0 na -336 0 Zimbabwe 11845 27006 63835 42 0 0 SUBTOTAL 37,663 142,455 181,235 79 24,816 -80,262 Low Income 17,640 61,427 90,058 68 -5,814 -9,419 DWX DVX VXO %change DVM DWM vx ASIA Bangladesh 0 0 0 0 -7465 -1529 Burma 0 0 0 0 0 0 Hong Kong 0 0 0 0 4296 -7217 India 89737 987807 122239 808 0 0 Indonesia 0 0 0 0 -86256 -34579 Korea Rep. of 0 0 0 0 33848 -56476 Malaysia 0 0 0 0 11609 -26492 Nepal 0 0 0 0 -1077 -554 Pakistan 1768 79280 0 na -26267 0 Philippines 82804 200648 440788 46 0 0 Sri Lanka 0 0 0 0 8917 -16804 Thailand 49719 110847 269114 41 0 0 SUBTOTAL 224,029 1,378,582 832,141 166 -62,395 -143,651 Low Income 91,506 1,067,087 122,239 873 -25,892 -18,887 - 78 - DWX DVX VxO Zchange DVM DWM NORTH AFRICA VX MIDDEL EAST Afghanistan 0 0 0 0 3443 -6693 Algeria 0 0 0 0 13160 -36454 Egypt 0 0 0 0 -34141 -29612 Iran IR 0 0 0 0 -51368 -39555 Iraq 0 0 0 0 26253 -42172 Morocco 0 0 0 0 -16901 -20815 Saudi Arabia 0 0 0 0 20766 -30399 Sudan 0 0 0 0 -5904 -19671 Syria 0 0 0 0 4391 -11828 Tunisia 0 0 0 0 5507 -9720 Turkey 6457 69718 0 na -56293 0 Yemen AR 0 0 0 0 5385 -8039 SUBTOTAL 6,457 69,718 0 0 -85,702 -254,958 Low Income 0 0 0 0 -2,461 -26,364 DWX DVX VXO Zchange DVM DWM LATIN VX AMERICA Argentina 42066 136153 208141 65 0 0 Bolivia .5714 19076 .28006 68 0 0 Brazil 176986 617219 855240 72 0 0 Chile 0 0 0 0 -5677 -17182 Colombia 20967 95140 91155 104 0 0 Dominican Rep. 58732 107321 328798 33 0 0 Ecuador .5452 27135 22596 120 0- 0 El Salvador 5107 16559 25255 66 0 0 Guatemala 12263 32718 63895 51 0 0 Haiti -490 561 0 na -4383 0 Mexico -940 72359 0 na -183810 0 Peru 5188 32564 18390 177 0 0 Venezuela 0 0 0 0 -12334 -25813 SUBTOTAL 31,045 1,156,805 1,641,476 70 -206,204 -42,995 TOTAL 599,193 2,747,560 2,654,852 103 -329,485 -521,866 Low Income 108,656 1,129,075 212,296 532 -38,550 -54,671 - 79 - Sugar 1983 Protection Levels DEVELOPED DC DQ TRVIM TRVEX Xi Ml tO COUNTRIES Australia -93 719 0 0 3014 0 0.0 Austria 115 -141 166 0 0 166 1.62 Canada 118 -23 *0 0 0 971 1.02/.17 Japan 5420 -360 0 0 0 7908 2.92 New Zealand -20 0 0 0 0 127 0.0 Norway -7 0 0 0 0 176 0.0/.27 Sweden 43 <-65 0 O 0 "11'7 0.97 Switzerland 29 -65 0 0 0 248 4.07/.92 United States 1793 -1672 0 0 0 7138 1.61 SUBTOTAL 7399 -1607 166 0 3014 16852- EUROPEAN DC DQ TRVIM TRVEX Xl Mi tO COMMUNITY Belgium/Luxembourg 54 -253 0 0 274 0 1.28 Denmark 39 -153 0 0 37 0 1.59 France 389 -1318 0 0 562 0 1.41. Germany 584 -1.041 770 0 0 77.0: 1.65 Ireland 55 -65 102 0 0 -102 1.96 Italy 1636 -676 0 0 0 2371 1.83 Netherlands 224 -340 348 0 0 348 1.79 United Kingdom 1059 -444 . .0 '0. .0. 2762. 1.98 SUBTOTAL 4040 -4288 1219 0 872 6352 MIEC 5479 XIEC 0 - 80 - DWX DVX VXO %change DVM DWM SUB-SAHARA vx AFRICA Angola 0 0 0 0 -353 -5842 Burkina Faso 0 0 0 0 0 0 Cameroon 1670 11280 0 na -217 0 Ethopia 2237 12481 1365 915 0 0 Ghana 0 0 0 0 1696 -3593 Guinea -346 459 0 na -2020 0 Ivory Coast 3172 12217 4223 289 0 0 Kenya 10437 48242 10542 458 0 0 Madagascar 3552 14182 4521 314 0 0 Malawi 11429 22893 24034 95 0 0 Mali 0 0 0 0 -538 -2406 Mozambique 10032 25810 18711 138 0 0 Niger 0 0 0 0 859 -1686 Nigeria 0 0 0 0 40710 -77145 Rwanda 0 0 0 0 -251 -425 Senegal 0 0 0 0 -3940 -3376 Tanzania 2752 22239 0 na -1510 0 Uganda 0 0 0 0 315 -2599 Zaire 42 6638 0 na -1940 0 Zambia 2890 19873 0 na -182 0 Zimbabwe 17021 37267 34471 108 0 0 SUBTOTAL 64,888 233,582 97,867 239 32,631 (97,072) Low Income 29,698 104,703 48,631 215 (3,387) (10,709) DWX DVX VXO %change DVM DWM vx ASIA Bangladesh -1163 6818 0 na -7179 0 Burma 0 0 0 0 0 0 Hong Kong 0 0 0 0 5292 -8929 India 201769 1262834 66009 1913 0 0 Indonesia 0 0 0 0 -128293 -30026 Korea Rep. of 0 0 0 0 41723 -69901 Malaysia 0 0 0 0 13458 -32283 Nepal 0 0 0 0 -1607 -519 Pakistan 23866 217842 0 na -14184 0 Philippines 120098 275381 238026 116 0 0 Sri Lanka 0 0 0 0 10704 -20654 Thailand 71182 153049 145322 105 0 0 SUBTOTAL 415,752 1,915,924 449,356 426 (80,086) (162,313) Low Income 224,472 1,487,494 66,009 2,253 (12,266) (21,173) - 81 - DWX DVX VXO %change DVM DWM NORTH AFRICA VX MIDDLE EAST Afghanistan 0 0 0 0 4123 -8216 Algeria 0 0 0 0 15702 -44262 Egypt 0 0 0 0 -52483 -30493 Iran IR 0 0 0 0 -71782 -40982 Iraq 0 0 0 0 32275 -52273 Morocco 0 0 0 0 -26765 -22270 Saudi Arabia 0 0 0 0 25903 -37899 Sudan 0 0 0 0 -10764 -22256 Syria 0 0 0 0 4917 -14326 Tunisia 0 0 0 0 6718 -11991 Turkey 19439 126180 0 na -30398 0 Yemen AR 0 0 0 0 6706 -10011 SUBTOTAL 19,439 126,180 0 na (95,849) (294,979) Low Income 0 0 0 0 (6,641) (30,472) DWX DVX VXO %change DVM DWM LATIN VX AMERICA Argentina 65258 190234 112396 169 0 0 Bolivia 8936 26694 15123 177 0 0 Brazil 279673 862881 461829 187 0 0 Chile 0 0 0 0 -9654 -19447 Colombia 35774 133979 49224 272 0 0 Dominican Rep. 81281 146934 177551 83 0 0 Ecuador 9579 38224 12202 313 0 0 El Salvador 7924 23126 13638 170 0 0 Guatemala 18190 45421 34503 132 0 0 Haiti 137 6187 0 na -2367 0 Mexico 41384 353250 0 na -99258 0 Peru 9815 45328 9930 456 0 0 Venezuela 0 0 0 0 -20725 -28656 SUBTOTAL 557,953 1,872,259 886,397 211 -132,003 -48,104 TOTAL 1,058,031 4,147,945 1,433,620 289 (275,307) (602,468) Low Income 254,306 1,598,385 114,640 1,394 (24,661) (62,353) - 82 - Beef DEVELOPED DC DQ TRVIM TRVEX Xi Ml COUNTRIES Australia -144 103 0 0 1123 0 Austria 7 -7 6 0 0 6 Canada -65 69 0 121 121 0 Japan 1932 -269 0 0 0 2345 New Zealand -11 23 0 0 364 0 Norway 19 -14 0 0 0 40 Sweden 17 -16 29 0 0 29 Switzerland 54 -38 0 0 0 104 United States -1377 892 0 1512 1512 0 SUBTOTAL 432 742 36 1632 3119 2524 EUROPEAN DC DQ TRVIM TRVEX xi Ml COMMUNITY Belgium/Luxembourg 219 -89 284 0 0 284 Denmark 10 -29 0 0 127 0 France 166 -372 485 0 0 485 Germany 138 -245 253 0 0 253 Ireland 9 -55 0 0 220 0 Italy 295 -296 0 0 0 907 Netherlands 86 -57 18 0 0 18 United Kingdom 296 -153 0 0 0 776 SUBTOTAL 1220 -1298 1039 0 346 2721 MlEC 2375 XIEC 0 - 83 - DWX DVX VXO %change DVM DWM SUB-SAHARA VX AFRICA Angola 0 0 0 0 -15289 -3925 Burkina Faso 1031 9074 1905 476 0 0 Cameroon 1169 11833 1455 813 0 0 Ethopia 0 0 0 0 0 0 Ghana 0 0 0 0 -5013 -1380 Guinea 0 0 0 0 0 0 Ivory Coast 0 0 0 0 -5648 -10114 Kenya 0 -3075 3075 -100 17152 -1143 Madagascar 0 -10764 10764 -100 0 -377 Malawi 0 0 0 0 0 0 Mali 0 0 0 0 0 0 Mozambique 301 8964 0 na -3788 0 Niger 742 12150 0 na -1796 0 Nigeria -2634 39681 0 na -69467 0 Rwanda 0 0 0 0 0 0 Senegal 0 0 0 0 0 0 Tanzania 0 0 0 0 0 0 Uganda 0 0 0 0 0 0 Zaire 255 6096 0 na -2530 0 Zambia 0 0 0 0 0 0 Zimbabwe 6774 25006 28372 88 0 0 SUBTOTAL 7,638 98,965 45,571 217 -86,378 -16,939 Low Income 2,329 25,520 12,669 201 -13,126 -1,757 DWX DVX VXO %change DVM DWM vx ASIA Bangladesh 0 0 0 0 0 0 Burma 0 0 0 0 0 0 Hong Kong 0 0 0 0 -8787 -10478 India 0 0 0 0 0 0 Indonesia 11531 150741 0 na -2570 0 Korea Rep. of 0 0 0 0 -78691 -12910 Malaysia 0 0 0 0 -2939 -7708 Nepal 0 0 0 0 0 0 Pakistan 0 0 0 0 0 0 Philippines 509 22062 0 na -12075 0 Sri Lanka 0 0 0 0 0 0 Thailand 0 0 0 0 0 0 SUBTOTAL 12,041 172,803 0 na -105,061 -31,096 Low Income 0 0 0 0 0 0 - 84 - DWX DVX VXO %change DVM DWM NORTH AFRICA VX MIDDLE EAST Afghanistan 0 0 0 0 0 0 Algeria 0 0 0 0 -8173 -10768 Egypt 0 0 0 0 43188 -91371 Iran IR 0 0 0 0 -38005 -29299 Iraq 0 0 0 0 -9524 -9744 Morocco 1665 31650 0 na -7050 0 Saudi Arabia 0 0 0 0 4053 -19704 Sudan 0 0 0 0 0 0 Syria 0 0 0 0 -5351 -5092 Tunisia 0 0 0 0 -4172 -5228 Turkey 7972 96645 2621 3687 0 0 Yemen AR -0 2464 0 na -1876 0 SUBTOTAL 9,636 130,759 2,621 4,989 -26,910 -171,207 Low Income 0 0 0 0 0 0 DWX DVX VXO %change DVM DWM LATIN Vx AMERICA Argentina 310724 2232872 804410 278 0 0 Bolivia 0 0 0 0 0 0 Brazil 96608 1370004 0 na -71232 0 Chile 7137 107033 0 na -12659 0 Colombia 37133 403534 33556 1203 0 0 Dominican Rep. 3748 37114 5042 736 0 0 Ecuador 0 0 0 0 0 0 El Salvador 1923 14423 4701 307 0 0 Guatemala 11030 49299 42272 117 0 0 Haiti 1326 11996 2302 521 0 0 Mexico 18406 200858 16252 1236 0 0 Peru 1261 27691 0 na -7775 0 Venezuela 17114 237783 0 na -15149 0 SUBTOTAL 506,411 4,692,608 908,536 517 -106,815 0 TOTAL 535,726 5,095,136 956,728 533 -325,165 -219,242 Low Income 3,655 37,515 14,971 251 -13,126 -1,757 - 85 - Wheat DEVELOPED DC DQ TRVIM TRVEX Xi Ml COUNTRIES Australia -53 1602 0 0 12508 0 Austria 41 -48 0 0 89 0 Canada -112 1334 0 0 16904 0 Japan 6472 -295 0 0 0 12413 New Zealand -3 18 0 0 0 22 Norway 100 -12 0 0 0 482 Sweden -2 3 0 0 353 0 Switzerland 324 -123 0 0 0 806 United States -536 6640 0 0 46302 0 SUBTOTAL 6230 9118 0 0 76155 13723 EUROPEAN DC DQ TRVIM TRVEX Xi Ml COMMUNITY Belgium/Luxembourg 171 -193 0 0 0 667 Denmark 59 -126 42 0 0 42 France 1405 -4364 0 0 5351 0 Germany 1220 -1841 3023 0 0 3023 Ireland 53 -41 0 0 0 354 Italy 1579 -1956 0 0 0 5010 Netherlands 198 -176 0 0 0 908 United Kingdom 1199 -1648 0 0 0 4033 SUBTOTAL 5884 -10345 3065 0 5351 14037 MiEC 8686 XlEC 0 - 86 - DWX DVX VXO %change DVM DWM SUB-SAHARA VX AFRICA Angola 0 0 0 0 2763 -4745 Burkina Faso 0 0 0 0 544. -908 Cameroon 0 0 0 0 1728 -2959 Ethopia 0 0 0 0 -6137 -4421 Ghana 0 0 0 0 2200 -3809 Guinea 0 0 0 0 525 -876 Ivory Coast 0 0 0 0 2806 -4787 Kenya 0 0 0 0 -6050 -979 Madagascar 0 0 0 0 1081 -1803 Malawi 0 0 0 0 282 -516 Mali 0 0 0 0 381 -719 Mozambique 0 0 0 0 2323 -4047 Niger 0 0 0 0 516 -920 Nigeria 0 0 0 0 14830 -27644 Rwanda 0 0 0 0 81 -351 Senegal 0 0 0 0 1573 -2803 Tanzania 0 0 0 0 -1252 -1235 Uganda 0 0 0 0 -165 -179 Zaire 0 0 0 0 3050 -5172 Zambia 0 0 0 0 1474 -2739 Zimbabwe 259 4158 208 1995 0 0 SUBTOTAL 259 4,158 208 1,995 22,552 -71,611 Low Income 0 0 0 0 3,429 -24,955 DWX DVX VXO %change DVM DWM vX ASIA Bangladesh 0 0 0 0 -3695 -18846 Burma 0 0 0 0 -1486 -206 Hong Kong 0 0 0 0 -1296 -2104 India 11176 602427 0 na -145618 0 Indonesia 0 0 0 0 -3465 -17380 Korea Rep. of 0 0 0 0 27366 -44849 Malaysia 0 0 0 0 10866 -12081 Nepal 357 7547 0 na -1329 0 Pakistan -6744 529 0 na -190275 0 Philippines 0 0 0 0 10290 -17161 Sri Lanka 0 0 0 0 9279 -15476 Thailand 0 0 0 0 1353 -3986 SUBTOTAL 4,788 610,502 0 na -288,010 -132,089 Low Income 4,788 610,502 0 na -333,124 -34,529 - 87 - DWX DVX VXO %change DVM DWM NORTH AFRICA VX MIDDLE EAST Afghanistan 970 40275 0 na -18283 0 Algeria 0 0 0 0 11934 -67165 Egypt 0 0 0 0 34951 -115029 Iran IR 0 0 0 0 -102769 -17915 Iraq 0 0 0 0 6587 -45430 Morocco 0 0 0 0 -5512 -40160 Saudi Arabia 0 0 0 0 13485 -27658 Sudan 0 0 0 0 -1102 -6241 Syria 0 0 0 0 -25070 -6410 Tunisia 0 0 0 0 -7972 -15407 Turkey 26218 304330 76101 400 0 0 Yemen AR 0 0 0 0 5159 -10509 SUBTOTAL 27,188 344,606 76,101 453 -88,592 -351,925 Low Income 970 40,275 0 na -19,384 -6,241 DWX DVX VXO %change DVM DWM LATIN VX AMERICA Argentina 98149 207519 723014 29 0 0 Bolivia 0 0 0 0 2549 -5912 Brazil 0 0 0 0 10926 -105710 Chile 0 0 0 0 -5316 -22858 Colombia 0 0 0 0 4825 -9815 Dominican Rep. 0 0 0 0 2205 -3603 Ecuador 0 0 0 0 5326 -9976 El Salvador 0 0 0 0 1623 -2817 Guatemala 0 0 0 0 234 -3062 Haiti 0 0 0 0 3075 -5150 Mexico 0 0 0 0 -43498 -21394 Peru 0 0 0 0 8386 -18071 Venezuela 0 0 0 0 13086 -22014 SUBTOTAL 98,149 207,519 723,014 29 3,420 -230,381 TOTAL 130,384 1,166,784 799,323 146 -350,630 -786,006 Low Income 5,758 650,777 0 na -346,004 -70,874 - 88 - Maize DEVELOPED DC DQ TRVIM TRVEX Xi Ml COUNTRIES Australia -2 11 0 0 39 0 Austria 75 -71 0 0 0 178 Canada -273 461 0 247 247 0 Japan 16452 -2 0 0 0 29064 New Zealand -2 11 0 0 51 0 Norway 15 0 0 0 0 83 Sweden 11 0 0 0 0 123 Switzerland 131 -29 0 0 0 450 United States -5513 16685 0 0 81494 0 SUBTOTAL 10893 17066 0 247 81830 29898 EUROPEAN DC DQ TRVIM TRVEX Xi Ml COMMUNITY Belgium/Luxembourg 547 -12 0 0 0 3170 Denmark 95 0 0 0 0 431 France 2347 -2749 2686 0 0 2686 Germany 1300 -253 0 0 0 3514 Ireland 66 0 0 0 0 264 Italy 3412 -1944 0 0 0 8250 Netherlands 836 -1 0 0 0 3173 United Kingdom 1120 -0 0 0 0 3925 SUBTOTAL 9723 -4960 2686 0 0 25413 MlEC 25413 XlEC 0 - 89 - DWX DVX VXO Zchange DVM DWM SUB-SARARA VI AF'RICA Angola 0 0 0 0 -3453 -1784 Burkina Faso 0 0 0 0 -1880 -159 Cameroon 202 5356 0 na -1608 0 Ethopia 504 16561 0 na -1846 0 Ghana 0 0 0 0 -5924 -505 Guinea -19 325 0 na -705 0 Ivory Coast -146 1239 0 na -3827 0 Kenya -1256 14895 0 na -16247 0 Madagascar 122 1980 163 1213 0 0 Malawi -187 16016 0 na -4557 0 Mali 0 0 0 0 -1287 -262 Mozambique 0 0 0 0 -3197 -2531 Niger 0 0 0 0 -175 -13 Nigeria 0 0 0 0 -49248 -3882 Rwanda 0 0 0 0 0 0 Senegal 0 0 0 0 -902 -355 Tanzania 0 0 0 0 -14258 -2265 Uganda -370 3268 0 na -2259 0 Zaire 0 0 0 0 -9713 -5436 Zambia 0 0 0 0 -17502 -3214 Zimbabwe 4029 30829 21791 141 0 0 SUBTOTAL 2,878 90,470 21,955 412 -138,588 -20,408 Low Income 49 38,150 163 23,370 -45,800 -11,173 DWX DVI VxO %change DVM DWM VI ASIA Bangladesh 0 0 0 0 0 0 Burma 320 1719 2075 83 0 0 Hong Kong -90 1174 0 na -2743 0 India 6607 118427 0 na -1916 0 Indonesia 1842 32931 0 na -7536 0 Korea Rep. of 0 0 0 0 34854 -46382 Malaysia 0 0 0 0 5371 -8523 Nepal 0 0 0 0 0 0 Pakistan 400 8096 0 na -525 0 Philippines -658 14955 0 na -25040 0 Sri Lanka -0 156 0 na -149 0 Thailand 41059 56839 343640 17 0 0 SUBTOTAL 49,479 234,297 345,715 68 2,315 -54,905 Low Income 7,327 128,398 2,075 6,187 -2,590 0 - 90 - DWX DVX VXO %change DVM DWM NORTH AFRICA VX MIDDLE EAST Afghanistan 0 0 0 0 0 0 Algeria 0 0 0 0 2320 -3786 Egypt 0 0 0 0 -36899 -12821 Iran IR 0 0 0 0 8560 -15973 Iraq 0. 0 0 0 305 -3254 Morocco 0 0 0 0 -2877 -2319 Saudi Arabia 0 0 0 0 11197 -18799 Sudan 0 0 0 0 0 0 Syria 0 0 0 0 1071 -3239 Tunisia 0 0 0 0 2005 -3344 Turkey 963 17509 420 4169 0 0 Yemen AR -48 247 0 na -1104 0 SUBTOTAL 915 17,755 420 4,227 -15,422 -63,535 Low Income 0 0 0 0 0 0 DWX DVX VXO %change DVM DWM LATIN VX AMERICA Argentina 97078 175129. 793250 22 0 0 Bolivia 537 5531 0 na -318 0 Brazil -8770 71206 0 na -226931 0 Chile 0 0 0 0 -3489 -5176 Colombia 0 0 0 0 -11654 -1246 Dominican Rep. 0 0 0 0 828 -2143 Ecuador 0 0 0 0 0 0 El Salvador 345 7321 0 na -142 0 Guatemala -482 3574 0 na -10653 0 Haiti -41 519 0 na -1977 0 Mexico 0 0 0 0 -158736 -37731 Peru 0 0 0 0 .-6192 -3553 Venezuela 0 0 0 0 -1167 -19932 SUBTOTAL 88,668 263,279 793,250 33 -420,432 -69,781 TOTAL 141,940 605,801 1,161,339 52 -572,126 -208,630 Low Income 7,336 167,066 2,238 7464 -50,368 -11,173 I I I I I The World Bank Headquarters European Office Tokyo Office 1818 H Street, N.W. 66. avenue d'Ina Kokusai Building Washington, D.C. 20433, U.S.A. 75116 Paris, France 1-1 Marunouchi 3-chome Telephone: (202) 477-1234 Telephone: (1) 47.23.54.21 Chiyoda-ku, Tokyo 100, Japan Telex: WUI 64145 WORLDBANK Telex: 842-620628 Telephone: (03) 214-5001 RCA 248423 WORLDBK Telex: 781-26838 Cable Address: INTBAFRAD WASHINGTONDC ISSN 0253-2115/ISBN 0-8213-0680-4