6;31 7130'1- 0' University Free State 11\\1\\ IIIII'1\\\ IIIII\3\1141"3Ill00"Il0l 0\\I0ll7"I3ll716\\\0' 5IIIII1\\1' '1111\\1'1 'Ill 1\\1 Universiteit Vrystaat ECONOMIC IMPUCATIONS OF TIRADE LIBERALiSATION ON THE SOUTH AFRICAN RED MEAT INDUSTRY by ANDRÉ JOOSTE Submitted in partial fulfilment of the requirement for the degree PhD in the Department of Agricultural Economics Faculty of Natural and Agricultural Sciences University of the Free State Bloemfontein May 2001 6 - DEC 2001 U-OVS-S-AS-OL !lB_L_..O_T_EE..K.- Acknowledgements The undertaking of a dissertation of this nature would not have been possible without the assistance, guidance and support by a number of people. Many individuals provided inputs in various aspects of this study. I give my thanks to all who have been involved, several of whom I must mention by name. First of all I wish to thank my promoter, Professor Herman van Schalkwyk, who is also a valued friend, for affording me the opportunity to write this dissertation. More specifically, I would like to thank him for his guidance, his valuable and practical inputs, as well as his perseverance during the completion of this study, providing me with the courage and confidence I needed. He also devoted generous amounts of his valuable time to read the first drafts of this study. I would also like to thank my co-promoter, Dr Martin van Lampe, Institute of Agricultural Policy at the University of Bonn, for his guidance and assistance in developing the methodological framework used in this study. He shared his thorough technical knowledge and resources with me freely, and also edited several parts of this study. I have also benefited greatly from the guidance and support of Dr Wolfgang Britz, Institute of Agricultural Policy at the University of Bonn. His initial input, advice and instruction provided the basis for the completion of this study, without which this study wouldn't have been possible. I am also greatly indebted to the personnel of the Chair in International Agricultural Marketing and Development at the University of the Free State. More specifically Daan Louw, who took over my lecturing responsibilities and in the process had to be away from home for extended periods. Harm du Plessis for his encouragement, Frances Geldenhuys for her technical editing and Lorinda Rust for general editing. Also a word of thanks to the members of the Project Evaluation Committee of the Red Meat Research and Development Trust (RMRDT) for their inputs. Acknowledgements On a more personal note I wish to extend my gratitude to my parents, who have provided me with the best of everything at times they could not really afford to do so. Your continued encouragement and support will always serve as an example to me. My heartfelt thanks go to my wife Estelle for her moral support, motivation and perseverance during the completion of this study. I will forever be indebted to her and my son, Ruan, who had to be satisfied with very little of my time the past few years. For all their sacrifice I dedicate this dissertation to them. I also wish to thank my parents-in-law and long time friends for their interest and encouragement during the completion of this study. The financial assistance of the National Research Foundation (NRF): Social Sciences and Humanities towards this research is hereby acknowledged. Opinions expressed and conclusions arrived at, are those of the author and are not necessarily to be attributed to the NRF. Finally, to the Almighty, for the strength and wisdom to complete this study. André Jooste Bloemfontein May 2001 ii ECONOMIC IMPLICATIONS OF TRADE LIBERALISATION ON THE SOUTH AFRICAN RED MEAT INDUSTRY by ANDRÉJOOSTE Degree: PhD Department: Agricultural Economics Promoter: Professor H.O. van Schalkwyk Co-promoter: Doctor M. von Lampe ABSTRACT Successful agricultural trade relations have to a large extent become a function of how well countries are able to measure the possible impact of increased trade liberalisation. Many studies worldwide have attempted to gauge the impact of agricultural trade liberalisation on world production, consumption, trade and prices by means of mathematical programming models. Given the importance of the red meat sector in South Africa's agricultural economy, it is of the utmost importance that the red meat industry understands the implications and consequences of trade liberalisation. Such knowledge would enable this industry to pro-actively provide input to Government on the possible 'effects of trade liberalisation on the domestic red meat industry, that could be used in multi- or bilateral trade agreements. Furthermore, the industry would be in a position to identify threats and opportunities and make the necessary strategic decisions. In South Africa many studies have investigated various different issues of economic importance pertaining to the red meat industry. None of them have attempted to investigate the impact of trade liberalisation within the mathematical programming framework. This study employs a spatial partial equilibrium model embedded in the iii Abstract mathematical programming framework to analyse the possible effects of a reduction of tariffs, increases in world prices of red meat, changes in the exchange rate, the abolishment of the Lomé Convention and changes in population size. The model includes two-stage spatially separated markets for red meat products in South Africa that encompass behavioural parameters to gauge the impact of exogenous changes related to trade liberalisation. In the case where all tariffs on red meat imports are abolished, changes in prices of red meat products will be substantial. Producer prices for cattle, sheep and pigs will decline by 21.11 per cent, 13.90 per cent and 11.99 per cent, respectively. Beef, sheep meat and pork prices will, on average, decline by 27.88 per cent, 28.56 per cent and 13.16 per cent, respectively. Demand will increase substantially for all three meat types. From a welfare point of view consumers will experience welfare increases. Producers, on the other hand, will experience a drop in welfare. In monetary terms the welfare gains by consumers are greater than the welfare losses by producers, which constitutes a net welfare gain to society. Furthermore, the red meat industry in South Africa should carefully consider preferential access granted to third countries under FTA's. Preferential access could easily lead to a reduction in the marginal tariff rate which, in turn, would result in lower domestic prices of red meat. In the case where the world price increases more than 10 per cent for beef, 18 per cent for mutton and 6 per cent for pork, zero imports would result. The losses in welfare to consumers are greater than the gains in welfare by producers. The impact of a 40 per cent depreciation in the exchange rate is very similar to the situation when world prices are assumed to increase, whilst the effect of a possible abolishment of Lomé on the South African beef market would be minimal. Finally, an increase in the population size combined with an increase in world prices will only partly offset the impact of a total reduction in tariffs. Also, increases in demand due to lower prices will largely be met by higher imports. iv EKONOMIESE IMPLIKASIES VAN HANDELSLIBERALISERING OP DIE SUID-AFRIKAANSE ROOIVLEISBEDRYF deur ANDRÉJOOSTE Graad: PhD Departement: Landbou-ekonomie Promotor: Professor H.D. van Schalkwyk Mede-promotor: Doktor M. von Lampe SAMEVATTING Suksesvolle handelsverhoudinge het tot 'n groot mate 'n funksie geword van hoe goed lande die moontlike impak van verdere handelsliberalisering kan bepaal. Verskeie studies wêreldwyd het probeer om die impak van landbouhandelsliberalisering op produksie, verbruik, handel en pryse deur middel van wiskundige programmeringsmodelle te bepaal. Gegewe die belangrikheid van die rooivleissektor in Suid-Afrika is dit van uiterste belang dat hierdie bedryf die implikasies en gevolge van handelsliberalisering verstaan. Dit sal die bedryf in staat stelom proaktief insette aan die regering oor die moontlike impak van handelsliberalisering op die plaaslike rooivleisbedryf te lewer. Dit kan dan weer gebruik word in multi- of bilaterale onderhandelinge met betrekking tot handel. Die bedryf salook in 'n posisie wees om gevare en geleenthede te indentifiseer en daarvolgens die nodige strategiese besluite te kan neem. Daar is reeds baie navorsing gedoen oor verskillende aspekte van ekonomiese relevansie vir die rooivleisbedryf in Suid-Afrika. Nie een van hierdie studies het gepoog om die impak van handelsliberalisering binne die raamwerk van wiskundige programmering te bepaal nie. Hierdie studie maak gebruik van 'n gedeeltelike v Samevatting ruimtelike ewewigsmodel wat ondervang word deur die wiskundige programmerings raamwerk om die moontlike effek van 'n verlaging in tariewe, verhogings in die wêreldprys van rooivleis, veranderinge in die wisselkoers, die uitfasering van die Lomé Konvensie en veranderinge in die grootte van die bevolking, te bepaal. Die model bestaan uit twee ruimtelike onderskeibare markte vir rooivleisprodukte in Suid-Afrika wat ondervang word deur gedragsparameters om die impak van eksogene veranderinge wat verband hou met handelsliberalisering te bepaal. lndien alle tariewe op die invoere van rooivleis verwyder word, sal die impak op pryse substansieël wees. Produsentepryse vir beeste, skape en varke sal onderskeidelik met 21.11 persent, 13.90 persent en 11.99 persent daal. Die pryse van bees-, skaap- en varkvleis sal onderskeidelik met 27.88 persent, 28.56 persent en 13.16 persent daal. Die vraag na hierdie produkte sal egter substansieël toeneem. Uit 'n welvaart oogpunt sal verbruikers 'n verhoging in welvaart ervaar, terwyl die welvaart van produsente sal afneem. In monetêre terme is die verhoging in welvaart van verbruikers groter as die verlies aan welvaart deur produsente, wat 'n netto styging in welvaart vir die gemeenskap impliseer. Daar moet ook besin word oor toegewings aan derde lande ) wanneer dit kom by vryehandelsooreenkomste, omrede dit maklik kan lei tot 'n verlaging in die marginale tariefkoers, wat weer sal lei tot verlagings in pryse van rooivleis op die plaaslike mark. In die geval van wêreldpryse vir bees-, skaap- en varkvleis wat met onderskeidelik 10 persent, 18 persent en 6 persent styg, sal geen rooivleis meer ingevoer word nie. Die verlies aan welvaart vir verbruikers is groter as die verhoging in welvaart vir produsente. Die impak van 'n 40 persent depresiasie van die wisselkoers sal 'n soortgelyke situasie tot gevolg hê, soos die geval wanneer aangeneem word dat wêreldpryse styg. Die uitfasering van Lomé sal 'n minimale impak op die beesvleisbedryf in Suid-Afrika hê. Laastens, indien die impak van 'n styging in die grootte van die bevolking gekombineer word met 'n styging in wêreldpryse, sal dit slegs gedeeltelik die effek van 'n totale uitfasering van tariewe teenwerk. Verder sal verhoogde vraag as gevolg van laer pryse grootliks deur invoere aangevul word. vi TABLE OF CONTENTS Page Acknowledgements i Abstract iii Samevatting v Table of contents vit List of tables xl! List of figures xv List of abbreviation xvii CHAPTER 1 INTRODUCTION 1.1 Background 1 1.2 Motivation 3 1.3 Problem statement 5 1.4 Objectives 6 1.5 Methodology and data used 7 1.6 Outline of the study 9 CHAPTER2 THE INTERNATIONAL RED MEAT TRADE ARENA 2.1 Introduction 10 2.2 Production, consumption and trade in red meat.. 11 . 2.2.1 The beef sector 11 2.2.2 The pork sector 16 2.2.3 The sheep meat sector 22 , 2.3 I The WTO and agriculture 28 vii Table of contents 2.3.1 The Uruguay Round of GATI negotiations 30 ,2.3.2 Impact of the Uruguay Round on red meat prices 33 2.3.3 The overall impact of and lessons learned from liberalisation 38 2.3.3.1 Did the Uruguay Round deliver? 38 2.3.3.2 Positive consequences of the Uruguay Round 39 2.3.4 Issues of importance in preparing for new WTO negotiations 41 2.3.5 The WTO and meat trade 47 2.3.5.1 Export subsidies 47 2.3.5.2 Market access 48 2.3.5.3 Other issues pertaining to meat trade ,. 49 2.4 The European Union and its Common Agricultural Policy 52 2.4.1 CAP and the red meat sector 55 2.4.2 The impact of Agenda 2000 62 2.5 The Lomé Convention 64 .2.6 Conclusions 68 . CHAPTER3 OVERVIEW OF THE SOUTH AFRICAN RED MEAT SECTOR 3.1 Introduction 70 3.2 Production of red meat in South Africa 72 3.3 Consumption of red meat in South Africa 76 3.4 Imports and prices of red meat 81 3.5 Trade in red meat products by SACU 88 3.6 Conclusion 103 viii Table of contents CHAPTER4 DEVELOPMENT OF A SPATIAL PARTIAL EQUILIBRIUM MODEL FOR THE SOUTH AFRICAN RED MEAT INDUSTRY 4.1 Introduction 105 4.2 Justification of the mathematical programming approach to trade modelling 105 4.2.1 The scope of equilibrium trade models 109 4.2.2 The nature of spatial equilibrium models 112 4.2.3 Selected world trade models 115 4.2.4 Summary 126 4.3 Model specification 127 4.3.1 Product specification and regional delineation 127 4.3.2 Data specification 131 4.3.3 Supply and demand of livestock 131 4.3.4 Supply and demand of meat.. 133 4.3.5 Prices for livestock and meat 134 4.3.6 Specification of the demand and supply equations 137 4.3.7 Determination of the slope variables and constant parameters 140 4.4 The mathematical model.. 142 4.5 Model characteristics 144 4.6 Summary 145 CHAPTER 5 VALIDATION OF THE SPATIAL PARTIAL EQUILIBRIUM MODEL 5.1 Introduction 147 5.2 The validation procedure 147 5.3 Validation results 149 ix Table of contents 5.4 Conclusion 158 CHAPTERS THE IMPACT OF LIBERALISATION ON THE RED MEAT INDUSTRY 6.1 Introduction 159 6.2 Justification of existing tariffs applicable to red meat imports 160 6.3 The impact of a total reduction in tariffs 165 6.3.1 Theoretical principles of applying tariffs 165 6.3.2 The impact of zero tariffs 168 6.4 The impact of an increase in the world price of red meat commodities 174 6.5 The impact of a depreciation of the exchange rate on the South African red meat industry 180 6.6 The impact of the abolishment of Lomé on the South African beef industry 183 6.7 An alternative tariff regime for red meat in South Africa 183 6.8 The impact of changes in the population on the red meat industry 184 6.9 Conclusions 190 CHAPTER 7 CONCLUSIONS AND RECOMMENDATIONS 7.1 Introduction 192 7.2 Major conclusions drawn from this study 192 7.2.1 International red meat trade 192 7.2.2 Impact of the Uruguay Round on red meat 194 7.2.3 Issues of importance in preparing for new WTO negotiations........................................................................... 195 x Table of contents 7.2.4 The European Union and its Common Agricultural policy 197 . 7.2.5 Trade in red meat products by SACU 198 ·7.2.6 The impact of a total reduction in tariffs 200 . 7.2.7 The impact of a world price increase in red meat commodities 202 7.2.8 The impact of a depreciation of the exchange rate on the South African red meat industry 204 . 7.2.9 The impact of the abolishment of Lomé on the South African beef industry 204 . 7.2.10 An alternative tariff regime for red meat in South Africa 205 . 7.2.11 The impact of population and income growth on the red meat industry 205 7.3 Policy recommendations 206 7.4 Recommendations for further studies 215 REFERENCES 217 APPENDIX A 236 . APPENDIX B 246 APPENDIX C 259 APPENDIX D 264 xi LIST OF TABLES Page Table 2.1: Major net exporters and importers of cattle and beef 13 Table 2.2: World exports of bovine meat products (1999) 14 Table 2.3: World imports of bovine meat products (1999) 15 Table 2.4: Major net exporters and importers of pork 19 Table 2.5: World exports of pork products (1999) 20 Table 2.6: World imports of pork products (1999) 21 Table 2.7: Major net exporters and importers of sheep and sheep meat.. 25 Table 2.8: World exports of lamb and sheep products (1999) 25 Table 2.9: World imports of lamb and sheep products (1999) 26 Table 2.10: The principles of the 1947 Act.. 28 Table 2.11: Main differences between GAn and the WTO 30 Table 2.12: Features of the negotiating process concerning the AoA. 32 Table 2.13: Projected international price changes (1987/89) and actual prices (1994 - 1996) (WFM model) 34 Table 2.14: Estimated changes in word market prices for bovine and sheep meat estimated with different world trade models 35 Table 2.15: Different estimates of the impact of liberalisation by industrialised countries on world beef prices by 2000 (percentage change) 36 Table 2.16: Impact of liberalisation in both industrialised and developing countries on beef prices by 2000 (percentage change) 37 Table 2.17: Impact of liberalisation on different red meat products by 2000 (percentage change) 37 Table 2.18: Reductions in beef support prices (EUR per ton) 56 Table 2.19: Special and slaughter premiums for beef (Agenda 2000) 58 Table 2.20: Level of support payments for a European farmer producing a 550kg steer for slaughter 60 Table 2.21: Outlook for beef balance in 2005 under Agenda 2000 63 Table 2.22: Outlook for pork meat balance in 2005 under Agenda 2000 64 xii List of tables Table 2.23: EU beef imports (tons) from ACP states (1994 - 1998) 68 Table 3.1: Real per capita expenditure on red meat in South Africa 85 Table 3.2 Imports of bovine meat products from overseas 98 Table 3.3: Exports of selected bovine meat products from SACU 101 Table 3.4: Imports of swine meat products from overseas 103 Table 3.5: Exports of selected swine products from SACU 105 Table 3.6: Imports of sheep meat products from overseas 106 Table 3.7: Exports of selected sheep products from SACU 107 Table 4.1: Product coverage by the WFM 122 Table 4.2: Regional coverage of the ClS 126 Table 4.3: Products and product groups included in the WATSIM 128 Table 5.1: Validation of cattle supply and demand 155 Table 5.2: Validation of beef supply and demand 156 Table 5.3: Validation of cattle and beef prices 156 Table 5.4: Validation of sheep supply and demand 159 Table 5.5: Validation of sheep meat supply and demand 159 Table 5.6: Validation of sheep and sheep meat prices 160 Table 5.7: Validation of pig supply and demand 162 Table 5.8: Validation of pork supply and demand 162 Table 5.9: Validation of pig and pork prices 163 Table 6.1: Current RSA tariff regime on imports of red meat products 166 Table 6.2: International comparison of PSEs (1998) (percentage) 167 Table 6.3: PSEs for red meat in South Africa (1996 -1998) (percentage) 168 Table 6.4: Red meat PSEs for selected countries in the world (1996 - 1998) 169 Table 6.5: The impact of zero tariffs on the cattle industry 175 Table 6.6: The impact of zero tariffs on the beef industry 176 Table 6.7: The impact of zero tariffs on the sheep industry 176 Table 6.8: The impact of zero tariffs on the sheep meat industry 177 Table 6.9: The impact of zero tariffs on the pig industry 178 Table 6.10: The impact of zero tariffs on the pork industry 178 Table 6.11: Change in welfare as a result of a total reduction in tariffs 179 xiii list of tables Table 6.12: The impact of a 10 per cent increase in the world price of beef on the cattle sub-sector 182 Table 6.13: The impact of a 10 per cent increase in the world price of beef on the beef sub-sector 182 Table 6.14: The impact of a 18 per cent increase in the world price of sheep meat on the sheep sub-sector 183 Table 6.15: The impact of a 18 per cent increase in the world price of sheep meat on the sheep meat sub-sector 184 Table 6.16: The impact of a 6 per cent increase in the world price of pork on the pig sub-sector 184 Table 6.17: The impact of a 6 per cent increase in the world price of pork on the pig sub-sector 185 Table 6.18: Change in welfare as a result of an increase in world prices for red meat. 186 Table 6.19: The impact of a 40 per cent depreciation of the exchange rate 188 Table 6.20: Impact of the abolishment of Lomé on the South African beef industry 190 Table 6.21: Fixed tariffs for the South African red meat industry 191 Table 6.22: Population projections for 2004 and 2009 197 Table 6.23: Growth in real per capita income 198 Table 6.24: Income elasticities for red meat for different population groups (1990) 198 Table 6.25: Impact of population growth on the red meat industry (2004) 200 Table 6.26: The impact of different per capita income growth scenarios on the red meat industry 200 Table 6.27: Combined effect of a change in population, reduction in tariffs and an increase in the world price of red meats.................. 197 Table 7.1: Importance of economic and non-economic factors in meat demand 222 xiv LIST OF FIGURES Page Figure 1.1 Evolution of the trade environment.. 1 Figure 2.1: World beef and veal production (1961 - 2000) 11 Figure 2.2: US price for beef in carcass equivalents (US$) 12 Figure 2.3: World pork production (1961 - 2000) 17 Figure 2.4: Barrow and gilt price in the US (US$) 19 Figure 2.5: World sheep meat production (1977 - 2000) 22 Figure 2.6: New Zealand lamb and ewe prices (US$) 24 Figure 2.7: Evolution of the CAP 53 Figure 3.1: The South African cattle herd and slaughtering (1975 - 2000) 73 Figure 3.2: The South African pig herd and slaughtering (1976 - 1999) 74 Figure 3.3: The South African sheep flock and slaughtering (1975 - 1999) 75 Figure 3.4: Relation between real per capita disposable income and the per capita consumption of beef (1973 - 2000) 77 Figure 3.5: Relation between real per capita disposable income and the per capita consumption of pork (1973 - 2000) 78 Figure 3.6: Relation between real per capita disposable income and the per capita consumption of sheep meat (1973 - 2000) 79 Figure 3.7: The relation between beef imports and the domestic Class A price (Jan 95 - Dec 00) 82 Figure 3.8: The relation between the real average auction price of beef and per capita consumption of beef (1970 - 2000) 83 Figure 3.9: The relation between the nominal porker price and pork imports (Jan 95 - Dec 00) 84 Figure 3.10: The relation between the real average auction price of pork and per capita consumption of pork (1970 - 2000) 85 Figure 3.11: The relation between the nominal sheep meat price and sheep meat imports (Jan 95 - DecOO) 87 Figure 3.12: The relation between the real average auction price of sheep meat and per capita consumption of sheep meat (1970 - 2000) ....... 87 xv List of figures Figure 3.13: Growth of national demand and international supply of meat products to SACU 89 Figure 3.14: Growth of national supply and international demand for exported meat products from SACU 91 Figure 3.15: Competition between suppliers to SACU for the selected import product in 1999 (Product: 020230 Bovine cuts boneless, frozen) 95 Figure 3.16: Competitiveness of suppliers to South Africa for the selected import product in 1999 (Product: 020329 Swine cuts, frozen nes) 99 Figure 4.1: A geometrical diagram representing a two region trading regime 114 Figure 4.2: The influence of transfer cost on regional pricing 115 Figure 5.1: Net trans-shipment of cattle in the base run (1996) 151 Figure 5.2: Net trans-shipment of beef in the base run (1996) 152 Figure 5.3: Net trans-shipment of sheep in the base run (1996) 154 Figure 5.4: Net trans-shipment of sheep meat in the base run (1996) 155 Figure 5.6: Net trans-shipment of pigs in the base run (1996) 157 Figure 5.7: Net trans-shipment of pork in the base run (1996) 158 Figure 6.1: Effects of an import tariff: A small nation case 166 Figure 6.2: Population projection, 1995 - 2050 185 xvi LIST OF ABBREVIATIONS ACP African, Caribbean and Pacific countries CAP Common Agricultural Policy CGE Computational General Equilibrium CIF Cost insurance and freight ClS Country-Link System CMO Common market organisation CSE Consumer Subsidy Equivalent Cwe Carcass weight equivalent DME Developing Market Economy ERS Economic Research Service of the USDA EU European Union EAGGF European Agricultural Guarantee and Guidance Fund FAPRI Food and Agricultural Policy Research Institute FOB Freight on board FSU Former Soviet Union FTA Free Trade Agreement GAMS General Algebraic Modelling System GATT General Agreement on Tariffs and Trade IME Industrial Market Economy Kg Kilogram lFA less Favoured Areas MERCOSUR Southern Common Market xvii MFN Most Favoured Nation Mio Million Nes Not elsewhere specified OECD Organisation for Economic Cooperation and Development PSA Private Storage Aid scheme PSE Producer Support Estimate (previously Producer Subsidy Equivalent) SA South Africa SADC Southern African Development Community SAMIC South African Meat Industry Company SPE Spatial partial equilibrium SPS Sanitary and phyto-sanitary measures SSA Sub-Saharan Africa SWOPSIM Static World Policy Simulation Model TBT Technical Barriers to Trade TRIPS Agreement on Trade Related Aspects of Intellectual Property Rights TRQ Tariff Rate Quota US United States USDA United States Department of Agriculture WFM World Food Model WATSIM World Agricultural Trade Simulation Model WTO World Trade Organisation xviii CHAPTER 1 ~NTRODUCTION Indeed, models basically play the same role in economics as in fashion. They provide an articulated frame on which to show off your material to advantage, ... a useful role, but fraught with the dangers that the designer may get carried away by his personal inclination for the model, while the customer may forget that the model is more streamlined than reality. - J.H. Dréze (1984) 1.1 Background The international trade environment has changed remarkably since the 18th century when the mercantilist philosophy was promoted widely amongst merchants, bankers and governments. The father of economics as science, Adam Smith, disagreed with this philosophy and stated that voluntary trade is only possible if there are mutual gains for trading partners. David Ricardo went further with his Law of Comparative Advantage (Chacholaides, 1990). The modern explanation of trade between countries is embedded in the thinking of people like Porter (1998), namely, competitive advantage. Moreover, the evolution of the trade environment could be explained more easily by Figure 1.1. Figure 1.1: Evolution of the trade environment • Political economy dependence _. independence _. interdependence • Markets mercantilists _. 'free market' _. 'free trade blocs' • Enterprises production _. marketing _. organisation • Strategies stability _. competition _. globalisation Source: Cordon, 2000. 1 Introduction A large part of the zo" century was characterised by many countries breaking their dependence from colonialism. The so-called mainstay of these countries was that they could rely on their own resources and governance to ensure success in many respects. It was, however, realised, even by successful economies, that a country could not only rely on its own resources to face the challenges of international competition. Hence the movement towards interdependence on government and company level during the late zo" century into the 21st century (Cordon, 2000). With respect to the latter the cotton and fibre industry serves as good example. Cotton produced in Egypt finds its way to South America where it is processed (spun) and exported to Italy for the manufacture of designer clothes. Advertising campaigns for the same clothes, on the other hand, originate in the United States. As was already mentioned the marketing environment has also undergone drastic changes. Mercantilism, which resulted in several wars, was followed by the ideology of free trade amongst countries. Even though the free market resembles the ultimate form of trade, its working still remains an enigma to many practitioners of this ideology. In essence the world was not ready to fully acknowledge and implement a fully free market regime (Cordon, 2000). Instead, countries opted for a subtle marketing regime, namely free trade blocs, of which there are various examples. Enterprises also had to change their approach to world trade. Production was once considered the cornerstone of the marketing chain. However, consumers soon became much more sophisticated, and hence the emphasis moved towards marketing. However, it was soon realised that marketing was not enough, i.e. many enterprises lacked the ability to coordinate what consumers demanded and what was actually produced. Moreover, many companies lacked the ability to source the products they needed to market successfully (Porter, 1998). This resulted in much more emphasis being put on the organisation of the value chain. It is thus no' wonder that the international trade environment has seen multi-national companies excelling with regard to size, profits and market share. 2 Introduction After World War II governments all over the world felt the need for stability (USDA, 1994). This resulted in the establishment of various international institutions, including the General Agreement on Tariffs and Trade (GATT), later transformed into the World Trade Organisation (WTO). A stable environment was seen to be the ideal opportunity to promote trade between countries. However, it was soon realised that in order to improve welfare through trade, products need to be competitive in markets outside domestic boundaries. Specialisation, technological innovation, structural change, etc. all accompanied the move towards becoming more competitive (Porter, 1998). These changes were, however, to a large extent localised in certain parts of the world. Third world countries, in particular, could not keep up with their more industrialised trading partners. Growth in the information technology sector, however, quickly changed this situation (Cordon, 2000). For example, it is today possible for anyone with access to a computer and Internet to source information on any aspect of technology, trade opportunities, trade partners, etc. from anywhere in the world. Communication advanced to such a degree that deals could be clinched without the contracting parties having to meet each other. This, together with factors already mentioned, resulted in the globalised trade environment as we know it today. It should be clear that the trade environment has changed considerably, especially during the past few decades. South Africa's re-entry into the global village after the democratic elections was fast and uncompromising. Domestic enterprises had to adapt quickly from an environment that was inwardly orientated to one that is part and parcel of the international trade arena. This exercised pressure on institutions that survived the legacies of a regulated environment, and also on market structures designed to cater for a controlled trade regime. 1.2 Motivation The red meat sub-sector is and will probably remain the dominant agricultural sub- sector in South Africa. It is, however, a fact that various factors will have an influence on the competitiveness and structure of the red meat industry in years to come. The 3 Introduction rapidly changing economic and policy environment, as discussed above, and the possible influence of these variables, should be of major importance to role players in the red meat industry. The reason for this is the fact that the move towards deregulation coupled with liberalisation, as well as the economic welfare of South Africa, will not only influence the competitiveness of the red meat industry, but will also present challenges to industry role players regarding adjustment to the new marketing environment. Studies by, amongst others, Lubbe (1991, 1992a, 1992b) and Nieuwoudt (1985) provide ample proof to this effect. The deregulation process coupled with the liberalisation of international markets also forced this industry to reorganise its operational structures, of which the formation of the South African Meat Industry Company (SAMIC) is a good example, to address issues of mutual importance. Of particular importance in the globalised world economy is the extent to which the red meat industry in South Africa will be affected when, for instance, tariffs are reduced or when red meat is included in regional free trade agreements. The importance lies in the fact that, on the one hand, there is a general move towards more liberalised markets whereby production and trade are supposed to be a function of the competitiveness of countries. On the other hand, policies in existence in countries like Japan, the US and the EU are still responsible for distorted production and trade patterns. Hence, from a South African red meat industry point of view, the question is what the possible impact will be if further liberalisation on the red meat industry takes place, e.g. what will happen if tariffs on red meat imports are reduced, or what will be the impact of a further liberalisation of the world market on the domestic red meat industry. In order to measure the impact of such changes, appropriate economic modelling tools are needed. The fact of the matter is, however, that South African agriculture is lagging far behind in developments in this area compared to other countries such as the US, the EU and Australia. Therefore, in order to fill this gap, a modelling tool to measure the impact of further liberalisation on the red meat industry in South Africa is needed. Not only are producers, agri-business and consumers dependent on information about the possible results of further liberalisation in order to position themselves strategically, but 4 Introduction policy makers need this information to guide policy, to negotiate trade agreements and to create an environment for the improvement of the general welfare of a nation. Furthermore, the ability to measure the impact of external shocks in a scientifically correct manner becomes even more important if one considers that linear interpolations and extrapolations could easily lead to erroneous conclusions (Jooste, Aliber and Van Schalkwyk, 1998). 1.3 Problemstatement Many researchers have investigated issues of agricultural economic relevance in the red meat industry. These issues encompass studies related to the estimation of price inter- relationships in the South African meat industry (Van Heerden, Van Zyl and Viviers, 1989), estimation of demand elasticities and flexibilities, cross price elasticities and demand prospects (Du Toit, 1982; Nieuwoudt, 1985; Hancock, Nieuwoudt and Lyne, 1984, Bowmaker and Nieuwoudt, 1990; Nieuwoudt, 1998a and b), and the marketing and distribution of livestock and livestock products in developing areas and informal settlements (Nkosi and Kirsten, 1992; DBSA, 1992; Karaan and Myburgh, 1992; Van Rooyen and Jooste, 1997a and b). Other issues investigated ranged from studies on the importance of the red meat industry and analysis related to price cycles (Laubscher, 1982; Lubbe, 1989; Lubbe, 1990), evaluation of the red meat marketing scheme and regulations associated with it (Eales, 1979; Nieuwoudt, 1985; Lubbe, 1991; Lubbe, 1992a; Lubbe, 1992b; Venter, 1996) to issues specifically relating to international trade of red meat. These latter issues include research relating to the impact of the EU-SA FTA on the demand for meat in South Africa (Badurally-Adam and Darroch, 1997), the possible effect of a reduction of tariffs in the red meat industry (Jooste, 1996; Jooste and Van Schalkwyk, 1996a; Jooste, Aliber and Van Schalkwyk, 1998), trade preferences of specifically beef (Jooste and Van Schalkwyk, 1996b) and the impact of the EU export policy on the South African beef market (Nieuwoudt, 1997; Koester and Lay, 1998). None of the research mentioned above, however, endeavoured to quantify the effects of trade-related issues, or demand and supply shift factors from a mathematical 5 Introduction programming point of view that falls within the spatial partial equilibrium (SPE) framework. By using this methodology the effects of trade-related shocks, such as a reduction in tariffs on red meat imports, could be quantified. In other words, answers could be provided on aspects related to (i) changes in the net price in each domestic region; (ii) changes in the quantity of exports or imports for each domestic region; (iii) which regions export, import or do neither; and (iv) the volume and direction of trade between each possible pair of regions. Given the above problem statement and provided that one is able to construct a SPE model, it would be possible to simulate the outcome of various different scenarios relating to trade aspects, as well as demand and supply shift factors on prices, production, consumption and trade flows between different regions. Such a model could be used by policy makers, agri-business and producers to address a wide range of issues. 1.4 Objectives The primary objective of this study is to quantify the possible impact of liberalisation and market parameters on beef, mutton and pork in order to provide future policy and management guidelines to enhance the red meat industry's competitive position. A better understanding of the effects of liberalisation and other market variables will prove to be useful in the formulation and implementation of policies that affect the red meat industry in South Africa. In order to achieve the primary objective several secondary objectives will have to be met: • Investigate the international and domestic red meat markets in order to provide information on production, consumption and trade trends. Furthermore, this also involves identifying possible market opportunities for trade in red meat products by South Africa, and whether these opportunities are being utilised. 6 Introduction • Determine the impact of tariff liberalisation on the red meat industry in South Africa. This also involves determining a different tariff regime that will uphold the status quo. Other issues pertaining to improved market access will also be investigated, e.g. the abolishment of the Lomé Convention. In addition, the effect of a more liberalised red meat market on the South African red meat industry will be investigated. • Determine the impact of socio-economic factors, such as population growth and income shifts on issues related to supply, demand and prices of livestock and red meat products in South Africa. 1.5 Methodology and data used This study is concerned with the development of a SPE model, which may be used to solve for spatial equilibrium prices, consumption, production and geographical flows from a multi-commodity point of view, provided that linear functions are acceptable approximations of regional demand and supply functions. In other words, a trade simulation model that encompasses the interaction between supply and demand activities on various levels will be used to quantify the effects of different policy regimes and/or marketing scenarios on red meat trade. The model is based on the Takayama and Judge (1971) approach to modelling trade between spatially separated markets. In fact, this approach or variations thereof is probably the most widely used amongst agricultural economists worldwide to quantify the effects of different policies on different industries (Halbrendt, Jundong, Aull-Hyde and Webb, 1995; Yavuz, Zulauf, Schnitkey and Miranda, 1996). The underlying assumptions of this modelling approach are that (i) there are two or more regions trading a homogeneous good, (ii) each region constitutes a single and distinct market, (iii) the regions of each possible pair of regions are separated but not isolated by a transport cost per physical unit which is independent of volume, (iv) there are no legal restrictions limiting the actions of the profit-seeking traders in each region and (v) for 7 Introduction each region the functions which relate local production and local use to local price are known, and consequently, the magnitude of difference which will be exported or imported at each local price is also known. It is of particular importance to note that this modelling approach assumes homogeneous goods, which entails that consumers regard goods as perfect substitutes for each other. In reality, however, the situation is much more complex, and hence would require a much more complex modelling framework that requires data currently unavailable in South Africa. For example, dropping the homogeneity assumption would require the implementation of the Armington approach. The Armington approach requires information on the substitutability of products from a consumer's point of view. Hence, in order to use the Armington approach, substitution elasticities need to be calculated. This entails a complex study on its own, especially if one considers the changes in factors that affect consumers' purchasing decisions (Bansback, 1995) coupled with the paucity of data. For this reason it was decided that the Armington approach falls beyond the scope of this study. Nevertheless, by adopting the above methodological framework for the red meat industry different policy scenarios under different climatic and socio-economic conditions on a macro-level can be simulated. This will provide the necessary management information for improving strategic management and influencing policy makers. The data needs for such a model is extensive. Data needs include, amongst others, regional supply and demand data, transport costs between regions, behavioural parameters (elasticities), as well as domestic and international prices. Due consideration should also be given to the consistency of the data used. Furthermore, it is important to provide a holistic view of the international and domestic red meat industries. Hence, trend information will also be used to describe patterns in terms of production, consumption, prices and trade. 8 Introduction 1.6 Outline of the study Chapter 2 presents a discussion of issues that relate to the international red meat industry. More specifically, an overview of production, consumption and trade is given. Chapter 3 contains a profile of the domestic red meat industry. Specific emphasis is placed on red meat trade and opportunities that exist internationally. In Chapter 4 a spatial partial equilibrium model is developed to model red meat trade in South Africa. In addition, justification for using this type of model is provided. Models are merely abstractions of reality, and hence it is impossible to capture all the specifics prevalent in the red meat industry. However, the aim is to develop a modelling tool that represents reality as closely as possible. In Chapter 5 the model developed in Chapter 4 is validated in terms of how well it represents reality. In Chapter 6 different scenarios relating to trade liberalisation are simulated. Finally, Chapter 7 will provide overall conclusions and recommendations. 9 CHAPTER 2 THE !NTERNAT!ONAl RED MEAT TRADE ARENA 2.1 Introduction As mentioned in Chapter 1 the subject matter of this study relates to the impact of trade liberalisation on the South African red meat industry. However, in order to understand this issue properly a holistic overview of the international trade environment and the factors influencing it is necessary. This chapter provides an overview of the international red meat market in terms of production, consumption and trade. This includes information on the major role players, as well as the intensity and growth in trade of red meat products internationally. Trends in production, consumption and trade of red meat products will undoubtedly be influenced by the worldwide trend towards globalisation. In this respect the move towards greater liberalisation under the auspices of the World Trade Organisation (WTO) and reforms of the EU's Common Agricultural Policy (CAP) will probably have the most significant effect. It is for this reason that this chapter will also focus on issues related to the WTO and the CAP. This does not mean that other issues, such as trade integration between various economies in the world, are considered of lesser importance. To the contrary, such issues are considered to be as important, but cognisance should be taken of the fact that a wealth of information, that could not possibly be included in a study such as this, exists. For example, it would not be viable to discuss all the issues relating to the liberalisation process under the auspices of the WTO. For this reason it was attempted to cite as much literature relating to trade issues that could be used for further reference as possible, without going into unnecessary detail. 10 The international red meat trade arena 2.2 Production, consumption and trade in red meat 2.2.1 The beef sector • Production According to Figure 2.1 world beef and veal production reached a maximum in 1990 with production at 51 365 thousand tons, after which it averaged 48 159 thousand tons per annum. Annual growth from 1961 to 1990 was 2.4 per cent. Annual growth between 1991 and 2000 was, however, negative at -0.43 per cent. 60000 50000 40000 ê oo;; 30000 c: o I- 20000 10000 0 (") 90 70 1.0 1.0 1.0 eo c.o c.o f'-.. f'-.. f'-.. 00 00 00 0) 0) 0) 0 0 0 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0 0 0 0 -.... ).. 0....).. .0...).. 0....).. .0...).. 0....).. 0....).. .0...).. 0....).. 0....).. 0....).. .0...).. 0....).. .0...).. 0....).. 0 0 0N N N -c.--o --c.--o -c-.--o --c.--o --c.--o -c-.--o -c-.--o -c-.--o --eo-- -c-.--o -c-.--o -e-o-- -c-.--o --c.--o -c-.--o --c.--o -c-.o eo1.0 0) ...... 1.0 0) ...... 1.0 0) ...... 1.0 0) ...... 1.0 0) ...... -1.-0 0----) Weeks 1- US price: Carcass equivalent 1 Figure: 2.2: US price for beef in carcass equivalents (US$) Source: Agrimark Trends, 2000. 12 The international red meat trade arena It is clear from Figure 2.2 that the price of beef has experienced a downward trend from 1995 to 1999, whereafter it rebounded to levels seen in late 1997. During the latter part of 2000, however, prices started to drop again. o Trade Table 2.1 shows the major net exporters and importers of cattle and beef in the world. Note that although the US is the largest producer of beef in the world it remains a net importer of beef. Table 21 ° MOaror net expo rters andO tmpo rters 0f cattlean db eef Net exporters Net importers Australia Japan Canada USA Brazil Middle East/North Africa EU FSU New Zealand Other Far East Argentina South Korea India South Africa Uruguay Mexico CEEC's Source: IMS-GIRA, 2000. Table 2.2 shows the exports of selected bovine meat products in the world (see Appendix A for a detailed list of exporting countries of the different bovine meat products). World exports of bovine carcasses and half carcasses (fresh or chilled) was valued at just over a million dollars in 1999 with 314 027 tons being exported (see Table 2.2). From 1995 to 1999 the value of exports decreased by 4 per cent, whilst the quantity exported remained the same. The major performer among the top 15 exporters in this market is Spain, showing considerable growth in terms of the value and quantity exported (see Appendix A). Ireland, Canada and Austria also performed well over the period 1995 to 1999. 13 The international red meat trade arena Table 2.2: World exports of bovine meat products (1999) Exports Value exported in Quantity exported Annual growth in Annual growth in 1999, in US$ in 1999 (tons) value between quantity between thousand 1995 - 1999 % 1995 - 1999 % Product 020110 (Bovine carcasses and half carcasses fresh or chilled) v~.2!!2../!.!1l~.:J.t~~,./1/.D"/.I/.8"/I/l/2~.!H~1..~/...v4V'/H/,.!.D'xn'/.n"/.N/g,.~.1i2.l1d/.q/A;:áf7.;.p;lw/...vIN/.u/H.(&l"'4vj41..w.D/a.~/6/.#.J~~~P/.I/Ih9"'/H'~/.1/"''''/4;~~~.o; Product 020120 (Bovine cuts bone in fresh or chilled) v~~1~~;/~~~fr~7~~i~;/~~;;~~~~i;;~/1~;;~~~7~ff;dr"L~'N>8.~~"':'~d.~/n.~~w,",l~/p.~/.Vh"w/;!~~'~~~I/~ ~!~~r%~~¥f6/7~~~f~;~;!~;;;;;;~~h~fl;:;~~;;;;f;l;;;,)~w",,~~,.~',"K'&"Q.M~4<"Lp'-WM,~/.r/.V{q~/8/~'~;"">V/~~ '~!~~~;/~i~¥fg(~~~i;;l~~t;~~';i;~;:f;;;;~rJ.2~».".,.>,"Y~~'l.w4,,/,.vm:12~,,L,,~,~~,~"/'.~v~, '$"~';~!.~'~YN.,q"~a.",Jp, World estimation 4 564 609 2162012 -2 0 Source: ITC calculations based on COMTRADE statistics, 2000, Table 2.2 shows that for bovine cuts (bone in, fresh or chilled) annual growth in the value and quantity exported was negative. Exports from Eastern European countries, such as Poland and the Czech Republic have, however, exceeded that of all other countries in terms of value and quantity exported. The US has also shown positive annual growth, but trails distantly behind Poland and the Czech Republic. Bovine carcasses and half carcasses (frozen) experienced negative growth in terms of value and quantity exported, even though some of the major' exporters, such as the US, Spain, Belgium and Lithuania have improved their position. Bovine cuts (boneless frozen) are the most prominent in terms of quantity exported, but experienced negative growth in the value of exports between 1995 and 1999 (see Table 2.2). Australia, the largest exporter of this product, however, experienced positive growth in both value and quantity exported. Similarly, Brazil and Uruguay performed well over the stated period, but for Argentina the opposite applies (see Appendix A). According to Table 2.2 only bovine cuts (boneless, fresh or chilled) experienced growth in both the value and the quantity exported. The US, the largest exporter of this product, saw growth in quantity exported, but experienced stagnant growth in value exported. The second largest exporting country, namely Australia, experienced negative growth in the value exported, even though the quantity exported increased. Countries performing well in terms of both value and quantity exported include, amongst others, 14 The international red meat trade arena Canada, Germany, Brazil, Uruguay, Italy, Spain, Mexico, Panama and Paraguay (see Appendix A). Table 2.3 shows the imports of selected bovine meat products in the world (see Appendix B for a detailed list of importing countries for the different bovine meat products). The trends in imports (value and quantity) for the different products shown in Table 2.3 are similar to that shown for exports in Table 2.2. Table 2.3: World imports of bovine meat products (1999) Imports Value exported in Quantity exported Annual growth in Annual growth in 1999, in US$ in 1999 value between quantity between thousand (tons) 1995 - 1999 % 1995- 1999 % I Product 020110 (Bovine carcasses and half carcasses fresh or chilledl ~7~;~~f*i~f¥*ê~';;~i;d'~~l;~~~vr;,Jf;;;h·>~;~~~fbr.,,_LN'.w"~w_;:~Q.,,,w.,.r.~"'J?J,r/~~/~M/.Y/P/I/A~"~ CX> CX> CX> CX> Ol Ol Ol Ol OlOl Ol Ol Ol Ol » Ol c» Ol Ol Ol Ol Ol.,-- .,-- .,-- .,-- .,-- .,- .,-- .,-- .,-- .,-- .,-- .c,»-- .O,--l O.,--l .O,-l .,- Year D Canada Mexico DUS D Brazil I • EU 15 D Eastern Europe .USSR D China• Japan Taiwan D Philippines • Other Figure 2.3: World pork production (1961 - 2000) Mean: 623 716 thousand tons Standard deviation: 330900 thousand tons Source: ERS, 2000. Figure 2.3 also shows the net production breakdown for selected countries in the world. China produces nearly half of the world's pig meat, followed distantly by the EU and the US. • Consumption Demand for pork in general is expected to increase. The rate of growth will, however, differ between countries. In developed countries pork growth is expected to slow down due to increased competition from poultry and moderate economic growth (European Commission,2000b). 17 The international red meat trade arena Price Figure 2.4 shows the barrow and gilt price in the US. Prices were under severe pressure during late 1998 and early 1999. The main reason for this was an oversupply on the market. Certain market observers in the US blamed this state of affairs on a lack of processing space. This was due to over-expansion by pork producers following discussions and decisions on moratoriums and additional rules and regulations (N.C. Pork Council, 1998). In addition to this the industry in the US and Canada was also plagued by strikes and closure of processing plants. Increases in productivity and efficiency also played its part to aggravate the oversupply. Hurt (1998) supports the notion that a lack of packer capacity contributed to the problems in the US pork industry, but he also states that high retail prices delayed increases in the volume of pork consumption. According to O'Doherty (1998) the situation in the EU was as bad. Producers in the EU, as in the US and Canada, faced severe financial problems. The main reason was an oversupply of pig meat on the EU market. Overproduction in Europe was exacerbated by the virtual closure of export markets to Russia, Japan and the rest of Asia due to the financial crisis experienced by these countries at the time. 18 The international red meat trade arena 80 70 60 -J 500~ 40CJ) ::J 30 20 10 0 L{) L{) CD CD I'- I'- co co (j) (j) 0 0 (j) (j) (j) (j) (j) (j) (j) c» (j) (j) 0 0 (j) (j) (j) (j)..- .. (j) (j) (j) (j) (j) (j) 0 0-.. --e.-.' -.-. .-..-. -...-. .-..-. .-..-. .-..-. .-..-. .-..-. N-.. N-.. 0 0 0 0 0 0 0 0 0 0 0 0 N-...-. N-.. N-...-. N-.. N.-..-. N-.. -N.. N-.. N- N N..- ...-. -.. -.... N-.. I'- I'- I'- I'- I'- - I'- Weeks 1- US Barrow and Gilt price 1 Figure 2.4: Barrow and gilt price in the US (US$) Source: Agrimark Trends, 2000. • Trade Table 2.4 shows the major net exporters and importers of pork in the world. Even though China is the largest producer of pig meat it still remains a net importer of this product. The same is true for the US as a major pig meat producing country. Table 24 M·ajor net exporters and·rrnpo rters 0f por k Net exporters Net importers EU FSU Canada Japan Brazil South Korea CEEC's US Mexico China Taiwan Source: IMS-GIRA, 2000. 19 The international red meat trade arena Table 2.5 shows exports of selected pork products of the world (see Appendix A for a detailed list of exporting countries for the different pork products). All the pork products have shown growth in quantities exported from 1995 to 1999. The largest growth was reported for swine carcasses and half carcasses (frozen). The major contributors to this growth are situated mainly on the European continent, namely Germany, France, Spain, the Netherlands, Hungary, Finland and Norway. Germany accounts for about 34 per cent of world exports, followed by Poland with 19.39 per cent; the respective share of exports of other countries is less than 10 per cent. Poland experienced only moderate growth in quantity exported compared to the mentioned countries. The Ukraine and China recorded negative growth in terms of value and quantity exported. Table 2.5: World exports of pork products (1999) Exports Value exported in Quantity exported Annual growth in Annual growth in 1999, in US$ in 1999 value between quantity between thousand (tons) 1995 -1999 % 1995-1999 % Product 020311 (Swine carcasses and half carcasses fresh or chilled) '~;f:;;[/Ë~6¥fi7~~~;H;~.r.~;fi!~;~;;g"~;r,d;;-t~;~b~r;;~~f;;:h;~~hi";dr~1.~~%V/_'/d/~ ~~~151/!!1l!!};;I2~~:1~w/~~/1/22~p~~~~~~j~H/8/.H/~/H2~i/l!~/D/~HhY/l/.H/.H~/4'~/~'~~{«~/Ar.~~w/nj/I/AW'1«w,.~;~g~'/.6/,H/H/I/I.~ Product 020321-{Swine carcasses and half carcasses frozen) z~~1~!~1i!!}!!!t2~~1;D;w40K/.6~~~/2~/Q.~~;m;gL~/6/H7#/~/~~~~2_'/D/I/1/6/1~d!w.~~~/6.~~4~/A/6/'~{N/3,J(8.{8/8.",v.~~.'ml~I/.I/N/J/I/4/A Product 020322 (Hams shoulders and cuts thereof of swine bone in, frozen) ~/~~~~/;:/~!!};lt~n/~1W-4Y-~A~Á7.~~~.4?,2r~/u;~D'/~w/-p.L/.l7/.l!WN/N73/~~~1~A;Q"/"/P/~l~/.w49'/U.;.v.«;i~~9.~..v/.D.~W/I.~j/H/H/8/N.W.~:tYj~/,q/.Al'/4/N/'/I.{M Product 020329 (Swine cuts frozen nes*) World estimation 33..77 848 1 760419 -1 12 * nes = not elsewhere specified Source: ITC calculations based on COMTRADE statistics, 2000. Note that for carcasses and half carcasses (fresh or chilled), hams, shoulders and cuts thereof (bone in, fresh or chilled) and swine cuts (frozen) growth in value from 1995 to 1999 was negative, even though the quantity exported had been positive (see Table 2.5). This translates into a lower per unit value of these products over the mentioned period and is probably a result of increased competition between exporters. Table 2.6 shows the imports of pork products for the world (see Appendix B for a detailed list of importing countries for the different pork products). The quantity imported of pork products increased from 1995 to 1999. However, in terms of the value 20 The international red meat trade arena of imports only hams, shoulders and cuts thereof (bone in, frozen) experienced positive growth. Swine carcasses and half carcasses (fresh or chilled) experienced the largest drop in value of imports, probably fuelled by the drop in the value of imports by Germany, Italy and Greece; these three countries account for nearly 92 per cent of world imports of this product. Only Germany experienced a decline in the quantity imported from 1995 to 1999 (1%). Other countries that experienced considerable growth in the value and quantity of imports, although their shares of world imports are relatively small, were Mexico, Belgium, Switzerland, Romania, Slovakia, the Czech Republic and Lithuania. Table 2.6: World imports of pork products (1999' Imports Value exported in Quantity exported Annual growth in Annual growth in 1999, in US$ in 1999 value between quantity between thousand (tons) 1995 -1999 % 1995-1999 % Product 020311 (Swine carcasses and half carcasses fresh or chilled) ,Y;Lc;~51'/.!!~~.:.!l..2-~.8""J'/.""/.'-",,;!P'/.O:~~~~/~1/g,whCJ"/.D'/j./I/.D'7.D7I/l/~~/~~2.D'Xt77I'/.6/.o"/1,w/I/47/4I"4&%D'/;1!/.6/D.1"/.'/AI"/8,'J.w/D/H/.D/I/'/..D"47"'"iMr/AI"/D"/.á'/".vM".u; Product 020312 (Hams, shoulders and cuts thereof of swine bone in fresh or chilled) ~~2.~~/!!1!~;].2-~/H;1$;~:.vb7/1/~~2Á7~~~a7hVhFJ{6/6/..wD.14'~~r./~!!/H/6a1'/.ar/!/D.~:.v/D7.'/6/""~4/H/H/..v.~D'X9"/P;j/d/O/8a7/I/D/..v/4'~,/..vh"18/,,./4; Producl020321 (Swine carcasses and half carcasses, frozen) r~.2.~5!,./!!:/~~2J!2~/R/lw/.6.;u'("""/6~i~H/~~£./..e/A/4~/H!8hT/n/4'/D/~/~/!/22~""'/.C"/..6"'4SI"/4/!/.D'/.8."'H/44.?'::W.W;"~.o::{4VXU...t~'V//4/WN"/'A.aW:bJ""'/P/..!P'/.4""~H/..v/H/,CJ"'/.4"';~7.6,: Product 020322 (Hams shoulders and cuts thereof of swine bone in, frozen) v~!!~;;/Ër~*;;I~;r~;~~~;~i~u~;~r~/;/~.~,..7/#!."/,-2~"~,j,~LV/7n.~,w,~oru,P/.J&~Ww'I~/.dL';/81~u'_N'''/.~/6/~ World estimation 3 876 824 1627452 -7 6 Source: ITC calculations based on COMTRADE statistics, 2000. The Russian Federation, Spain, China and Taiwan were the main importing countries that stimulated growth in the value and quantity imported of hams, shoulders and cuts thereof (bone in, frozen). The decline in the value of imports of swine cuts (frozen), the most important imported pork product, is largely attributed to negative growth in the value of imports in Japan and Germany. Together these two countries accounted for 57.45 per cent of world imports of this product. 21 The international red meat trade arena 2.2.3 The sheep meat sector • Production Figure 2.5 shows the production of sheep meat for the world. Production averaged 500 mio tons from 1988 to 1996. However, since 1997 production increased again on an annual basis. Given past trends this growth could be expected to level out within the next few years. 600000 500000 ~ 400000 oo ~ 300000 co I- 200000 100000 o Ol ..- (") LO Ol ..-r-- LO OlCX) CX) CX) CX) Ol Ol Ol O..-l Ol Ol O..-l .O.-l Ol O..-l Ol Year o Argentina III EU15 0 Eastern Europe oUSSR IIIMiddle East and North Africa 0 China .India o Australia • New Zealand IIIOther Figure 2.5: World sheep meat production (1977 - 2000) Mean: 325 568 thousand tons Standard deviation: 185860 thousand tons Source: ERS, 2000. Figure 2.5 also shows the net production breakdown of sheep meat for selected countries. On a single country basis the largest sheep producer in the world is China, followed by India. On a regional basis the Middle East/North Africa and the EU, produces 17 per cent and 6 per cent of the world's total sheep meat respectively. 22 The international red meat trade arena Consumption According to Cordon (2000) the consumption of sheep meat is basically determined by the degree of presence and the tradition of sheep rearing. Barnard (2000) states that over the past 40 years, the global sheep meat industry has been singularly unsuccessful in competing for space on consumers' plate, with a decline in per capita consumption of 0.6 per cent per annum. For example, in 1999 the amount of sheep meat consumed worldwide was only one-fifth the amount of beef consumed, only one- sixth the amount of poultry consumed, and only one-eighth of the amount of pork consumed. Consumption of, for example, lamb has fallen by 37 per cent in Australia, 22 per cent in the US and the United Kingdom between 1980 and the late 1990's, whilst per capita consumption in New Zealand experienced a drop of 57 per cent since the mid 1980's (Barnard, 2000). He attributes the decline in consumption primarily to the fact that sheep meat is the most expensive meat world-wide and that sheep meat prices have increased at a faster rate than that of other meats. • Price The decline in sheep meat consumption has also placed pressure on sheep meat prices. Figure 2.6 shows that after prices of lamb and ewes rebounded in late 1996 it remained relatively high throughout 1997, whereafter it declined again to stabilise around US$1.50 per kg lambs weighing 15 kg. The price of lamb weighing 21 kg stabilised just below US$1.50 per kg since 1998. For ewes the price stabilised at nearly half the level of what it was in 1997. 23 The international red meat trade arena 2.50 2.00 -~Cl 1.50~en ::;:) 1.00 0.50 - 0.00 I.!) I.!) ID ID I'- I'- CX) CX) 0) 0) 0 0 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0 0 -0...)- 0-) -0) -0) 0) 0) 0) 0) 0) 0)..- -...- ...- .-..- ...- --...- .--..- -...- -...- 0 0 ~ N ~ ID ID ID ID ID ID ID -..- r:::: ..- r:::: ~..- ~I'- ...- I'- .~..- r:::: .-.- ~ Weeks -- NZ lamb (15kg, 7-12mm fat) -- NZ lamb (21kg, 7-12mm fat) -- NZ ewe (21kg) Figure 2.6: New Zealand lamb and ewe prices (US$) Source: Agrimark Trends, 2000. • Trade Table 2.7 shows the major exporters and importers of sheep meat in the world. Considering Figure 2.5, note that the major sheep meat producers are also major net importers of this product (China, EU, Middle East/North Africa). Although China is the largest sheep meat producer, New Zealand, Australia and Britain are the major players in terms of world trade, exporting approximately 87 per cent of the world's sheep meat. The EU is the third largest exporter of lamb with Britain, Ireland, Spain and France being the major exporters. The EU is, however, a net importer of lamb and mutton. Out of the eight major mutton importing countries (importing ± 80% of the world mutton), five are in Europe (± 65%). The economic welfare of the European consumer therefore plays a major role in world mutton trade trends (IMS-GIRA, 2000). Australia and New Zealand contributes the largest share to world exports. In 2000 these two countries accounted for nearly 75 per cent of world exports, i.e. 33.7 per cent and 40.6 per cent respectively (IMS- GIRA, 2000). 24 The international red meat trade arena Table 27. . Ma' ior net expo rters and'tmpo rters 0f shsep and sehep meat Net exporters Net importers New Zealand EU Australia Middle East/North Africa East Africa Other Far East CEEC's US South America South Africa Japan/South Korea FSU Source: IMS-GIRA, 2000. Table 2.8 shows the exports of selected lamb and sheep products for the world (see Appendix A for a detailed list of exporting countries for the different lamb and sheep products). Table 2.8: World exports of lamb and sheep products (1999) Exports Value exported in Quantity exported Annual growth in Annual growth in 1999, in US$ in 1999 value between quantity between thousand (tons) 1995 -1999 % 1995-1999 % Product 0204101Lamb carcasses and half carcasses, fresh or chilled) ~.2!~A"~.!t~!]/~~u/.l/l/.l7/&~/.;;.v.~~~.../..../.J. ""'/D4V.49'/6M1'Ai7~/..v/.Q/d/ ..../.6..7•9•''/.,41'; Product 020442 (Sheep cuts, bone in, frozen) World estimation 652000 328226 2 7 Source: ITC calculations based on COMTRADE statistics, 2000. 26 The international red meat trade arena Similar to exports of lamb and sheep products, lamb carcasses and half carcasses (fresh or chilled) and sheep carcasses and half carcasses (frozen) did not perform well over the period 1995 to 1999. In terms of the former, France, with a share of 66.13 per cent of world imports reduced its imports by 1 per cent, whilst the value of imports declined by 5 per cent. Other EU countries that experienced a negative growth in either the value of imports, the quantity imported or both include Italy, Belgium, Germany, Portugal, the United Kingdom, the Netherlands and Spain. These countries contributed 22.74 per cent to world imports of this product. As far as sheep carcasses and half carcasses (frozen) are concerned negative growth in value and quantity imported was fuelled by Korea, Malaysia, Oman, Taiwan, the Russian Federation, Jamaica and the US. Growth in the value and quantity of imports of the world's largest importer of this product could not negate the negative overall growth (see Appendix B). Growth in respect of the value and quantity of sheep cuts imported (bone in, fresh or chilled) can be attributed to the fact that the top 17 importers of this products experienced positive growth in both value and quantity imported, with the exception of Germany, which experienced marginal negative growth in the value of imports. Four countries dominate the imports of this product, namely the US, France, United Kingdom and Belgium with respective market shares of 26.52 per cent, 15.02 per cent, 12.66 per cent and 11.63 per cent (see Appendix B). Sheep cuts (bone in, frozen) also experienced positive growth with regard to value and quantity imported (see Table 2.9). The overall situation is, however, not as positive as is the case with sheep cuts (bone in, fresh or chilled). The major importer of this product, namely the United Kingdom, only experienced a 4 per cent growth in the quantity imported, but zero growth in the value imported. Growth in the value and quantity imported by the US, the second largest importer with less than half the market share of the United Kingdom, exceeded that of the United Kingdom. 27 The international red meat trade arena 2.3 The WTO and agriculture The General Agreement on Tariffs and Trade (GATT), the forerunner of what is today known as the WTO, was established in Geneva in 1947. Its basic aim was to liberalise world trade and to place it on a secure basis, thereby contributing to economic growth and development (USDA, 1994), or stated otherwise, it has aimed to create a framework that would regulate international trade and stimulate international commerce (FAO, 1998b). Without too much deliberation about the GAIT, it is nevertheless necessary to take into account the most important elements of the GAIT as set out in the 1947 Act (see Table 2.10). Table 21.0 . The ormcm. Ies 0fth e 1947 Act Most This entails that each contracting party to the GATT is required to provide all other Favoured contracting parties with the same conditions of trade at the most favourable terms it Nation (MFN) extends, i.e. each contracting party is required to treat all contracting parties in thesame wav that it treats its "most favoured nation". The benefits of any bilateral agreements between contracting parties, regarding tariff Reciprocity reductions and market access, are extended simultaneously to all contracting parties.The principle of reciprocity relates to the requirement to reciprocate the treatment provided by other contractino parties. Fundamental to a transparent system of trade is the need to harmonise the system of Transparency import protection, so that barriers to trade can then be reduced through the process ofnegotiation. The GATT therefore limited the use of quotas, except in specific conditions widelv used bv adriculture. Tariff When GATT was established tariffs were the main form of trade protection, andnegotiations in the early years focused primarily upon tariff reduction. The text of the reduction 1947 GATT sets out the oblioations of the contractlno parties in this reoard. Source: FAO, 1998b. Since 1947 various so-called GAIT negotiating Rounds were held to further expand and develop the "rules" that were laid down initially. In total eight Rounds were held, but agriculture was largely excluded from seven of them mainly due to opinions that agriculture was a unique sector of the economy, that, for reasons of national food security, could not be treated like other sectors. Agriculture was also exempted from some important GAIT rules (FAO, 1998b): • Agriculture was allowed to make use of quantitative import restrictions, whilst it was banned for all other commodities, providing that domestic production 28 The international red meat trade arena of the commodity in question was also subject to certain restrictions, or to domestic price stabilisation or price support policies. The use of agricultural export subsidies was explicitly permitted, conditional upon the observance of "equitable" market shares; but "equitable" was difficult to define and agricultural subsidies proliferated. • Other mechanisms for protecting agriculture, variable import levies and domestic subsidies, were not covered explicitly by the GATT, and provided additional loopholes for agricultural policy makers wishing to protect the agricultural sector. It was only during the last Round, the Uruguay Round, that agriculture was put firmly on the negotiating table. The reasons for doing so were due mainly to issues related to comparative advantages, world market instabilities and the effects of protectionism. This Round also paved the way for establishing the WTO. Although the establishment of the WTO was not foreseen when talks began in the Uruguay Round in 1986 it was increasingly realised that an institutional framework enabling greater clarification and enforcement of all the procedures and commitments under the GATT was needed. Hence, the importance of the WTO lies in its consolidation of all the Agreements and arrangements of the GATT both for 1947 and 1994, under a single umbrella. In other words, the WTO provides the common institutional framework for the conduct of trade relations among its members in matters relating to the agreements contained in the Final Act of the Uruguay Round (FAO, 1998b). The main differences between the GATT and the WTO are summarised in Table 2.11 29 The international red meat trade arena Table 2.11: Main differences between GATT and the WTO GATT WTO GAn is a set of rules, a multilateral agreement, with no institutional foundation and with only a small associated secretariat, which has its origins in the The WTO is a permanent institution with its own attempt to establish and International Organisation secretariat. in the 1940's. GAn was applied on a "provisional basis". The WTO commitments are full and permanent. GAn rules applied to trade in merchandise goods. The WTO also covers trade in services and thetrade-related aspects of intellectual property. While GAnwas a multilateral instrument by the The agreements which constitute the WTO are 1980's, many new arrangements of plurilateral and almost all multilateral and thus involve commitments therefore selective nature had been added. for the entire membership. The WTO dispute settlement system is faster, more The old GAndispute settlement system was automatic and thus less susceptible to blockages. susceptible to blockages. The implementation of WTO dispute findings will also be more easily assured. Source: NDA, 1997. Given the above background the terms GATT and WTO will be used interchangeably since multilateral trade negotiations underpinning the rules governed by the WTO took place under the auspices of the GATT. 2.3.1 The Uruguay Round of GATT negotiations According to the FAO (1998b), the Uruguay Round was launched in 1986 by the Punta del Este Declaration, in which the negotiating objectives of the Round were laid down. The objectives are summarised by Van Zyl and Kirsten (1992): • Improvement of market access through the reduction of import barriers; • increased discipline regarding the use of all subsidies and other measures affecting trade; • compensation of trading partners for any damage incurred as a result of changes in trade barriers; and • settlement of trade disputes through negotiations by using GATT codes of conduct as guidelines. 30 The international red meat trade arena The process of negotiating the Agreement on Agriculture (AoA) has not been plain sailing all the way. It was characterised by fierce negotiations by the main actors, namely the US, the EU, the Cairns group and developing countries outside the Cairns group. Although the latter two groups played an important role during negotiations, the discussions were dominated by the differences between the US and the EU. The inability to resolve differences between them also resulted in the final agreement being reached much later than planned. The main features of the negotiating process are shown in Table 2.12. Pearce (1996) states that the principle components of the AoA focussed on domestic support, market access restrictions and export subsidies. Table 2.12 does not show the specific commitments as they relate to these components, but they are reported widely by amongst others, GAn (1994); USDA (1994); Pearce (1996); FAO (1998b). Nevertheless, mention is made of specific commitments in the text to follow as they relate to the impact of liberalisation. It should be clear from the above discussion that negotiations regarding the AoA were mostly dominated by the US and the EU. This is no wonder if one takes into account that, although developing countries had very clear intentions to bargain for lower subsidies and improved access to developed country markets, developing countries still felt the desperate need to protect their own interests. It would appear that in the end the latter weighed heavier than the former. Ingco and Townsend (1998) state that the negotiating efforts of developing countries were concentrated on obtaining preferential treatment regarding market access to industrial country markets and exemptions from many GAn rules. Special and differential treatment was the yardstick for judging their links to the multilateral trade rules. Furthermore, the motivation for several developing countries to take part in the negotiations was mainly to safeguard old preferences or obtain compensation for potential adverse effects from higher food prices on their import bills. In other words, one could argue that developing countries were not really at the negotiating table to attend to issues pertaining to liberalisation worldwide and in their own countries, but rather to ensure that they still receive beneficial treatment on the grounds of being developing countries or least developed countries. 31 The international red meat trade arena Table 2.12: Features of the negotiating process concernina the AoA US and its Cairns group allies: All trade-distorting domestic and export subsidies Initial should be phased out, and all import protection should be converted to tariffs, which position should be reduced sharply. (1990) EU and its allies: There should be an arrangement to reduce aggregate spending on domestic and export subsidies and some limits on border orotection. December It was thought that the Uruguay Round would be concluded during this meeting, but 1990 developing country members of the Cairns group rejected the EU's position. This ministerial situation resulted in the realisation by the EU that CAP reforms are unavoidable and led meeting to major reforms in the CAP in 1991. At the end of 1991 negotiations were still stalled on key issues in agriculture and other sectors. The Dunkei Text was put on the table as a benchmark for remaining negotiations. It called for immediate tariffication, the establishment of market access requirements, and a reduction in subsidies in terms of spending and volumes subsidised. The Dunkei It also established a framework for substantial different treatment for developing Text (1991) countries. The publication of the Dunkei Text resulted in the focus of agricultural groupsshifting to what the proposed agreement would require in terms of changes in policy and levels of protection. Japan, Korea, France and Germany expressed their dissatisfaction with the Dunkei Text. France even went as far as to threaten to block EU approval of the Uruguay Round if changes were not made to bring it more in line with the reformed CAP. The US and the Cairns crouos endorsed the Dunkei Text. Further In 1992 it was established that the EU's reformed oilseed policy still violated GATT, tensions resulting in the US threatening to retaliate against EU products if the situation was not (1992) rectified. The Blair house agreement dealt with all the outstanding issues between the US and the EU in the Dunkei Text and also contained an agreement to end the US-EU impasse over oilseed policy. It did not deal with issues directly affecting developing countries. It is The Blair commonly seen that the Blair House agreement went the way of the EU relating to House reductions in the volume of subsidised exports, aggregation of minimum-access agreement requirements and budgetary subsidy cuts that would take place on an aggregate basis. (1992) EU compensation payments and US deficiency payments would also be exempt fromreduction. This agreement also included a "cease fire" that entailed that GATT complaints on certain issues could not be filed for the duration of the implementation period of six years if the country in question was complying with its Uruguay Round commitments. This was pushed mainlv bv the EU. The new US administration that took office in January 1993 raised several issues about parts of the Blair House agreement that led another 12 months of high-level negotiations. Amendments The first amendment relates to the base period chosen for the reduction of export to the Blair subsidies which effectively causes the EU and the US to subsidise significantly more House products during the implementation period than would otherwise have been the case. agreement (1993) The second amendment relates to allowing a few countries to postpone tariffication ofsome products by agreeing to minimum import levels higher than those required under tariffication. This benefited mainlv the rice industries of Jaoan and Korea. It consists of two parts. One is a set of general commitments spelling out the new GATT The final rules and the second is a series of schedules setting out the individual nations' Uruguay commitments in terms of the level of tariffs declared when non-tariff controls are Round converted to tariffs; tariff reductions on a line-by-line- basis; minimum access concessions agreement and related details; the level of base-year spending, the volume of export subsidies, and (1994) the schedule of reductions on a yearly basis; the aggregate level of trade-distorting domestic supports in the base period' and the level of final commitments for reduction. Source: Hathawayand Ingco, 1996. 32 The international red meat trade arena Ingco and Townsend (1998) furthermore argue that had developing countries been at the negotiating table for the right reasons, i.e. finding ways and means to take advantage of the liberalisation process, they would in any case have received differential treatment. Hathaway and Ingco (1996) state that while many aspects of the modalities in the originalDunkel Text were the subject of keen attention and negotiation that led to changes, the portions relating to differential treatment for developing countries remained undiscussed and untouched even though developing countries won differential treatment in several regards. For example, their obligations regarding tariff reduction could be as low as two-thirds of that of industrial countries, many programmes regarded as export subsidies for industrial countries are not regarded as such for developing countries, and developing nations could even escape tariff reductions on a large number of products if they chose to do so. Ingco and Townsend (1998) are of the opinion that by resisting liberalisation and the opportunity to anchor domestic reform in an international framework, a region such as Sub-Saharan Africa (SSA) has foregone the opportunity to reap substantial gains from the Uruguay Round. This is reinforced by a study conducted on the possible impact of the Uruguay Round on developing countries by Brandáo and Martin (1993). They mention that it seems that developing countries could expect to achieve small welfare gains if the Dunkei package were implemented by the developed countries alone and the developing countries choose not to participate in the liberalisation process. Larger gains would be realised if developing countries choose to participate wholeheartedly in the world trading system by undertaking agricultural reforms of their own. 2.3.2 Impact of the Uruguay Round on red meat prices It should be clear from the previous section that trade liberalisation under the auspices of the WTO definitely has an effect on world production, trade patterns, prices of agricultural products, as well as the general welfare of countries. Several studies have attempted to quantify these effects by using different modelling frameworks, some of which were discussed earlier. In this section different studies using different approaches to model the impact of liberalisation on the red meat industry will be cited. It is, however, also important 33 The international red meat trade arena to take note of the fact that results from such studies may differ considerably from what actually happens in reality. According to Pearce (1996) the combination of declining grain stocks, shifting production patterns, major economic changes in transition economies, plus major policy changes in the EU and the US, not to mention the uncertainties regarding Chinese trade policy, makes any forecasts of the future behaviour of international agricultural markets extremely hazardous. One can add to this the uncertainties regarding the impact of international markets on changing consumption patterns in newly industrialised countries, and the even greater unknowns provided by the combined threats of global warming, biodiversity loss and population growth. Trying to isolate the separate effects of the AoA from the implications of these events is a very difficult task to accomplish. The difficulty of achieving this end is illustrated by comparing results between projected changes in international prices for selected commodities and the actual price trends since the Uruguay Agreement was signed (see Table 2.13). It is clear that the actual market prices determined by supply and demand factors could overshadow the possible impacts of the AoA. Table 2.13: Projected international price changes (1987/89) and actual prices (1994 - 1996) (WFM model) Products Uruguay Round effect* Actual** Percentace chance from benchmark to end date Bovine meat 8 6a Sheep meat 10 _1b a - EU export Unit value (1994-95), • D -Iamb. New Zealand wholesale prices london * Impact on prices due to the implementation of commitments reached in the AoA during the Uruguay Round. ** What actually happened in terms of prices in the world market. Source: Pearce, 1996. Taking into account the fact that the estimated effect and the actual effect of liberalisation on prices can differ considerably, the rest of this section will be devoted to studies measuring the impact of the AoA. 34 The international red meat trade arena Table 2.14 shows the results of different models that estimate changes in world market prices for selected red meat products as a result of liberalisation. The models used mainly considered the main elements of the AoA. The differences in the projections of different models can be attributed to different assumptions related to base periods used, transmission elasticities, whether they used a general or partial equilibrium framework, etc. For instance, the RUNS I model used 1982-83 (Iow protection) as base period, the RUNS III used 1991-93 (high protection) as base period, whilst the WFM used 1987-89 as base period. Nevertheless, there is sufficient agreement in the results to suggest that the overall trends may be viewed with a degree of confidence. Table 2.14 shows that all the models predict increases in market prices for bovine and sheep meat. Table 2.14: Estimated changes in word market prices for bovine and sheep meat estimated with different world trade models Products WFM I ATPSM I I ATPSM II I RUNS I I RUNS III Percentaae chanae from benchmark to end of immementation_period i.e.2000 Bovinemeat 8.0 10.1 5.3 0.2 1.4 Sheep meat 9.9 l 10.2 I 5.5 _I 0.2 1 1.4 WFM = World Food Model; ATSM = Agricultural Trade Policy Simulation Model; RUNS = Rural Urban North- South model. Source: Pearce, 1996. Another approach to modelling trade liberalisation involves considering the producer subsidy equivalent (PSE) and consumer subsidy equivalent (CSE). This approach encompasses a wider range of issues than only those related to the AoA. Table 2.15 shows the impact of liberalisation on world beef prices when removing producer and consumer subsidies as measured by PSE's and CSE's. A common feature of all the studies shown in Table 2.15 is an expected increase in the prices of beef if industrialised countries liberalise their agricultural policies. The results of the study conducted by Zietz and Valdés (1990) is somewhat more modest than the results of other studies shown in Table 2.15. The reason for these differences lie in the application of different base or reference periods in the different studies and the fact that predictions are very sensitive to values attached to PSE's and CSE's, which can vary considerably over time. 35 The international red meat trade arena The studies done by Tyers and Anderson (1987) serve as good examples to show the influence of different policy assumptions on results of such models. If protection levels of 1980 to 1982 are used Tyers and Anderson (1987) estimated the increase in red meat prices to be 21 per cent, but when the projected protection levels for 1988 are used, the estimated price increases amount to 43 per cent. Hence, when evaluating results from studies concerned with the impact of liberalisation one has to take into account the assumptions used regarding policies that will have an impact on agriculture, i.e. over and above those only pertaining to the AoA. Table 2.15: Different estimates of the impact of liberalisation by industrialised countries on world beef prices bv 2000 (percentage change) Base Percentage reduction in PSE's and~uthors year CSE's in industrialised countries 10% 50% 100% Zietz and Valdés (1990) 81-83 0.9 4.9 10.5 Parikh, Fischer, Frohberg and Gulbransen (1988) * 17 !ryers and Anderson (1987) 80-82 21 Tyers and Anderson (1987) 88 43 lZietz and Valdés (1986) 78-81 17.4 Frohberg, Fischer and Parikh (1990)** 81 17 * Econometric model of the International Institute for Applied Systems Analysis (IIASA) ** Estimated relative price change of bovine and ovine products to non-agricultural prices using a CGE The studies cited above only considered the impact of liberalisation on the beef industry in industrialised countries. Table 2.16 shows the impact of a combination of agricultural liberalisation in industrialised and developing countries. Zietz and Valdés (1990) expect beef prices to increase moderately by 2.9 per cent if only developing countries liberalise their agricultural policies. Parikh et al (1988), on the other hand expect beef prices to drop by 3 per cent. The reason for this discrepancy is the fact that the latter authors only considered tariff and quota liberalisation, whilst the former authors considered total PSE's and CSE's. What these results indicate is that developing countries should consider their liberalisation strategies carefully, i.e. liberalising only certain policies could result in sub-optimal effects in the industry being liberalised. 36 The international red meat trade arena Table 2.16: Impact of liberalisation on beef prices by 2000 in both industrialised and develonlna countries (nercentaae chanae !Authors Base year Developing countries All countries jzietz and Valdés (1990) 81-83 2.9 13.3 Parikh et al (1988) * -3 11 Tyers and Anderson (1987) 88 13 * Econometric model of the International Institute for Applied Systems Analysis (IIASA) Table 2.16 furthermore shows that when the combined effect of liberalisation and total liberalisation in industrialised countries is also taken into account, world beef prices are expected to increase by between 11 and 13 per cent. In contrast to the studies cited above Table 2.17 shows the relative impact of liberalisation on all the different red meat products considered in this study for both Developing Market Economies (OME) and Industrialised Market Economies (IME). Table 2.17: Impact of liberalisation on different red meat products by 2000 (percentaae chance) (Base vear = 1986) !Authors Beef and veal Pork Multon and lamb IME I OME IMEr I OME IME I OME IKrisoff et al (1990) 16-17* 7** 12-14* I 8** 25-30* I 21*· * Liberalisation in industrialised market economies (IME) under different scenarios pertaming to aggregate incomes. ** Liberalisation also in developing market economies (OME) with respect to exchange rates to reflect estimated free market levels. It is clear from Table 2.17 that if DME's realign their exchange rates to estimated free markets levels, increases in world prices are considerably less than when only IME's liberalise their agricultural policies. Krissoff, Sullivan and Wainio (1990) state that the smaller world price increases reflect the significant overvaluation of national currencies by governments in the developing world. The simultaneous effect of liberalisation of agricultural markets in IME's and a devaluation of currencies in OME's should result in a considerable rise in domestic prices of agricultural commodities in DME's which should encourage further production and less consumption. Thus, with expanded world production and contracted world consumption there is less pressure on world prices to increase as a result of increased excess demand in the IME's. 37 '----------- J The international red meat trade arena 2.3.3 The overall impact of and lessons learned from liberalisation Goldin, Knudsen and Van der Mensbrugghe (1993) estimated worldwide benefits due to liberalisation in the order of US$190 billion with tariff reductions in the order of 30 per cent. About US$70 billion of this total would accrue to non-OECD countries. The total gains would increase to US$430 billion with full agricultural reform, with the gain for non-OECD countries in the order of US$180 billion. With the levels of tariffication agreed in the Uruguay Round agreement, the gains are much smaller, particularly for those agricultural exporters who do not subsidise their agricultural activities. From a Sub-Saharan Africa (SSA) point of view, studies by Harrison, Rutherford and Tarr (1995) and Hertel, Masters and Elbehri (1997) show losses amounting to 0.24 per cent and 0.13 per cent of the SSA's base GDP respectively in the year 2005 as a result of the reforms under the Uruguay Round. Harrison et al (1995) concluded that there exists a large potential for improvement, or even reversal, of the situation through domestic policy reforms which are stated to be necessary for taking advantage of the new trading opportunities opened up by the Uruguay Agreement. The OECD (1998a) and Gulbransen (1995), while also recording welfare losses as a result of the implementation of the AaA, support the view of Harrison et al (1995). 2.3.3.1 Did the Uruguay Round deliver? It should be noted that although the OECD (1998a) acknowledges that the disciplines introduced by the Uruguay Round agreement were a step forward in the process of incorporating of agriculture into multilateral trade negotiations, they state that the results of tariffication were far below the expectations of the developing countries. Those developing countries that export agricultural commodities without subsidies, and which were largely powerless to influence the course of the negotiations in agriculture, did not see much improvement in market access for their products. 38 The international red meat trade arena This view is also supported by Ingco and Townsend (1998) who mention that several studies that have attempted to measure the impact of the Uruguay Round on agriculture have indicated their concerns about the high cost of complying with the new obligations set out in the new Act and the limits these may put on developing strategies, whilst others raised concerns about the potential market losses due to the erosion in the value of preferential exports, as overall cuts in tariffs will reduce the value of the preferences. Sharma, Konandreas and Greenfield (1998) state that the AaA is expected to cause beneficial effects for aggregate world income, as inefficiencies in production and trade will be removed gradually, but it is generally agreed that the impact on global trade would be fairly small over the implementation period, reflecting the limited extent of the reforms achieved. According to Tangermann (1996) the rules under which the new commitments were established under the AaA were relatively clear-cut. However, the way in which they were implemented when it came to inserting numbers in the schedules differed significantly from case to case. Not surprisingly, there was a tendency to build some slack into schedule commitments. Also the base period chosen for defining the starting point of the new commitments was relatively "generous". As a result, many of the new commitments turn out not to bind current policies very much, or not at all, with the important exception of the constraints on the quantities of subsidised exports. As a consequence, the AaA may change market conditions in the immediate future less than might have been expected from an agreement which was negotiated with so much effort, and which established disciplines which go far beyond past GATT rules for agriculture. 2.3.3.2 Positive consequences of the Uruguay Round From the above discussion one could easily be misled into thinking that the Uruguay Round negotiations were a waste of time and money. However, several important lessons are to be learned, especially by developing countries, in view of the next round of 39 The international red meat trade arena negotiations. Tangermann (1996) mentions that while GAn rules on agricultural trade were vague and weak in the past, governments now have to observe clearly defined constraints when making agricultural policy and trade decisions. He goes further by stating that all participating countries now have schedule commitments in quantitative terms which define what they can and cannot do, in areas of market access, export competition and domestic support. The agreement should be judged in comparison with the state of affairs in agricultural trade before the Uruguay Round began, e.g. GAn Article XVI:3, that was supposed to constrain export subsidies in the era before the Uruguay Round was powerless. Hathaway and Ingco (1996) share his optimism by stating that despite the substantial retreat by the advocates of liberalisation, the Uruguay Round agreement on agriculture appears to hold great promise. Cognisance is taken of the fact that some of the binding powers laid down during the Uruguay Round may be weak, but the essence is that new rules have been laid down to which role players must adhere in future. The efficiency of the application of these rules will depend mainly on the outcome of the next Round of negotiations. Also, the fact that countries have agreed to lower their tariffs to the committed bound rates, although they may be high in some cases, means that they come closer to within-quota tariffs under tariff rate quotas (TRQ), hence TRQs could loose much of their significance. Tangermann (1996) furthermore states that the existence of the new WTO disciplines for agriculture have already began to impact on the process of agricultural policy-making in many countries, e.g. the EU and the US, make . explicit reference to their WTO commitments in their efforts to reform their respective agricultural sector policies. It was also stated that the failure of many developing countries to reform their domestic agricultural sectors to meet WTO rules was the main cause for the new rules not having any significant impact in terms of welfare gains; in fact it was shown that the developing world will probably suffer welfare losses. According to Gulbransen (1995), welfare loss could be reduced substantially if the exogenous price changes are transferred to domestic markets of the food importing countries and markets are allowed to act. Hertel et al (1997) concluded in their study that losses due to the AoA could be reversed if (i) freight costs on exports are reduced to the level of other developing countries, and (ii) yield rates were to grow at the same rate as that in South Asia. This 40 The international red meat trade arena conclusion clearly illustrates the importance of a well-functioning and efficient transport system and the importance of technological innovation and transmission. Hence, provided that these countries learned from the past, reform their agricultural sectors to be more in line with the WTO rules and address other structural inefficiencies, the impact of the WTO could be expected to be much more significant (hopefully in a positive sense) in the years to come. 2.3.4 Issues of importance in preparing for new WTO negotiations From the above discussion it is clear that many issues that is contained in the AoA as it stands today need to be revisited. Furthermore, since the signing of the AoA, several changes have taken place in the world's trade structure, e.g. the ongoing integration of economies and accompanying agricultural policy reforms, which provide an environment for further trade liberalisation. Miner (2001) states that the expansion of regional trade agreements and EU enlargement negotiations add urgency to the multilateral negotiating process. Furthermore, issues such as the anticipated expiry of the Peace Clause in 2003, export subsidies, other forms of export competition, unfair pricing practices, and dumping require urgent attention. • Article 20 Ingco and Townsend (1998) and Miner (2001) state that the issues that will dictate the agenda for negotiations, and that are embedded in Article 20, are the following: Experience of implementing the reduction commitments under the AoA; the effects of these commitments on world trade in agriculture; non-trade concerns; special and differential treatment for developing country members of the WTO and the objectives of establishing a fair and 41 The international red meat trade arena market-orientated trading system and other objectives mentioned in the preamble of the agreement; and further commitments necessary for achieving the objectives of the AoA. According to Ingco and Townsend (1998) Article 20 of the AoA mandates countries to work towards "substantial progressive reductions in protection in agriculture" and adoption of least-trade distortionary policies. Article 20 also provides for the negotiations involving further commitments which may be necessary to achieve long-term liberalisation objectives, i.e. the agricultural negotiating mandate will incorporate commitments for further liberalisation of restrictions under market access, domestic support and export subsidies, and will also cover topies that go beyond reductions in support and trade barriers, such as strengthened rules and disciplines (Ingco and Townsend, 1998). With regard to the latter Valdés and Zietz (1987) suggest that in order to give the AoA a lasting eminence, present rules and disciplines on subsidies and quantitative restrictions need to be strengthened. • The Peace Clause According to Sharma, Greenfield and Konandreas (1998) and Miner (2001) Article 13, the so-called Peace Clause, is the most important article that requiring negotiation. As was stated in Table 2.12, the Blair House agreement included a cease-fire that entailed that GATI complaints on certain issues could not be filed for the duration of the implementation period if the country in question was complying with its Uruguay Round commitments (Hathaway and Ingco, 1996). Sharma et al (1998) state that the importance of the Peace Clause lies in the fact that it prevents members from challenging export subsidies, Green and blue box, and de minimus payments. Green box policies are not deemed to have a major effect on production and trade, and include a variety of direct payment schemes that subsidise farmers' incomes in a manner that is deemed not to influence production decisions. It also includes 42 The international red meat trade arena assistance programs, e.g. producer retirement programmes, resource retirement programmes, environmental protection programmes, regional assistance programmes, certain types of investment aid and general services that provide, for example, research, training and extension, marketing information and certain types of rural infrastructure. Blue box policies, also exempted from aggregate measure of support (AMS) commitments 1, include the compensatory payments and land set- aside schemes of the EU's CAP and the deficiency payment scheme of the US. Such direct payments under production-limiting programmes are exempted from AMS reduction if (i) such payments are based on fixed area and yields or (ii) such payments are made on 85 per cent or less of the base level of production or livestock payments are made on a fixed number of heads. The de minimis exemptions allows any support for a particular commodity (or non-specific support) to be excluded from the total AMS calculation if that support is not greater than a given threshold level, i.e. where the value of total domestic support for a particular commodity is not greater than 5 per cent (10 per cent for developing countries) of the total value of production of that product, then that support need not be included in the calculation of the current total AMS, which means that it will not have to be reduced (FAO, 1998b). Hence, the de minimis provision offers policy makers additional room to manoeuvre (Pearce, 1996). He also states that it is important to note that the de minimis provisions are specified in relation to total production, not to total marketed production. Thus, in countries where a substantial percentage of total production is retained on the farm, the protection of marketed production that subsidies need to exceed before AMS commitments come into effect, will be considerably higher than 5 per cent. Given the above it is clear that most of the subsidies that are allowed under the AaA could become subject to challenge in the Disputes Settlement Mechanisms of the WTO if a member can show injury. According to Sharma et al (1998), countries 1 The AMS commitments require a 20 per cent (13.3 per cent for developing countries) reduction in the Base Total AMS (base period 1986 - 1988) starting in 1995 and lasting for six years for developed countries and 10 years for developing countries. The AMS applies to all domestic policies that are considered to have a significant effect on the volume of production. 43 The international red meat trade arena that rely on these subsidies would have a strong interest in negotiating an extension of Article 13, whilst countries that may be harmed by such subsidies would have a strong interest in insisting on the termination thereof. The Cairns Group can be expected to have a strong stance in this regard. During the 18th Cairns Group ministerial meeting it was clearly stated that all trade-distorting subsidies must be eliminated and that market access must be improved substantially so that agricultural trade can proceed on the basis of market forces. The Cairns Group are also of the opinion that in many cases agricultural subsidies and access restrictions have stimulated farm practises that are harmful to the environment, and hence reform of these policies could contribute to the development of environmentally sustainable agriculture (C.airns Group, 1998). Miner (2001) suggests that if Article 13 is not extended or replaced, domestic support measures and export subsidies could be challenged under countervail legislation, or for nullification or impairment of benefits, whether or not they meet the existing commitments. This would place many agricultural exports from the major subsidising countries at risk to be challenged, a situation that would be particularly difficult not only for the EU, but also for the United States, Canada and a number of other countries. Since the Peace Clause is due to disappear in the year that a new US Farm Bill is due, which is also a crucial time in the EU enlargement exercise, there will be strong pressures on the key negotiating countries to reach agreement on agriculture in the WTO by that time. • Tariff Rate Quotas Another issue that is deemed very important is the rules on Tariff Rate Quota (TRQ) administration and allocation (Inego and Townsend, 1998). A TRQ is the volume of imports that is permitted to enter a country at below the normal tariff rate. TRQs relate to the minimum access commitments of countries, which entail that exporters of tarrified products should be allowed to supply at least 3 per cent of the domestic consumption at the beginning of the implementation period, 44 The international red meat trade arena rising to 5 per cent at the end of the implementation period in 2004 at reduced tariff rates. Tangermann (1996) states that some people are of the opinion that minimum access may be the only real improvement to market access. He disagrees, since there are no guarantees that the TRas will serve this purpose, and hence that they will affect the actual trade flows and constrain policies of the importing countries. Also it should be remembered that there is no commitment regarding imports, but only a commitment to charge no more than the specified reduced rates of tariffs specified, i.e. whether products could be exported under the TRas will depend on whether these reduced tariffs are still prohibitive or not. Incgo and Townsend (1998) mention that the establishment of the new TRas created interest groups which promise to uphold inter-governmental restrictions on trade through licensing procedures and other administrative arrangements. The FAO (1998b) states that there is also uncertainty surrounding the procedures for allocating minimum access quotas, i.e. the recipients of licences to import at in- quota tariff rates will benefit from economic rents, and therefore countries have an interest in allocating these licenses to domestic traders rather than foreign traders even though this may not be entirely consistent with most favoured nation (MFN) principles. Incgo and Townsend (1998) add by stating that traders in turn will have an incentive to lobby for the continuation of the high levels of applied and bound tariffs. They are of the opinion that the challenge for the next Round in this area is to prevent the TRas from interfering more than is necessary in the competitive development of trade. Tangermann (1996) and the FAO (1998b) suggest auctioning licences under minimum access TRas. Ingco and Townsend (1998) state that auctioning, however, also has disadvantages, i.e. if the TRas were auctioned to the exporter, the effects would be similar to the system of tariffs that the quota was designed to avoid. This is because the exporter would tend to bid up the size of the tariff for the right to make more profit in the import market. It should be clear that, although only a few issues that require urgent attention during follow-up negotiations on agriculture were mentioned and discussed, there is still a lot to 45 The international red meat trade arena be done as far as liberalisation of trade is concerned. The answers to pressing questions are far from clear, which is alarming, as world trade is not going to remain static until such answers are found. From a developing country point of view, matters are even more worrying, especially considering that some developing countries, especially least developed countries, have been facing difficulties regarding lack of trained personnel to fully appreciate the implications of the provisions of the AaA and its implementation in practice (Ingco and Townsend, 1998). These economies are also experiencing difficulties in adapting ongoing domestic agricultural policies to the new rules, which will exacerbate their future positions. Sharma et al (1998) mention the following problems that confront developing countries in their efforts to keep pace with their commitments and ongoing negotiations: The inadequate administrativellegal capacity to meet the requirements of WTO membership, including preparation of notifications, defending interests of national agriculture in the WTO, assessing the impact on agriculture of policy changes agreed upon at the WTO, and developing systems of plant variety protection, as requested by the Agreement on Trade Related Aspects of Intellectual Property Rights (TRIPS). The insufficient national policy formulation capacity in agriculture, forestry, and fisheries sectors and the inadequate analytical capacity to assess the impact of policy changes being proposed at the WTO. The limited scientific, administrative and infrastructure capability to deal with food standards, plant and animal health inspection services and quality assurance requirements of developing countries' imports. The lack of plant variety protection and the necessity to develop such protection rapidly, by patents or sui generis legislation, or mixture of both, by all WTO members, including developing countries with no prior experience. The lack of capacity to prepare and negotiate in Rounds, including eventually the preparation/revision of national schedules of commitments to the WTO, requiring additional skills and a forward-looking capacity in their ministries. 46 The international red meat trade arena Apart from the issues mentioned, Miner (2001) states that a myriad of newer issues and non-trade concerns have become linked to the trade agenda, whether or not they belong there. Most are legitimate issues, but they are also complex, sensitive and emotional ones, without easy or obvious solutions. A surprising number of these emerging issues are related to the food business and many are being raised in relation to agricultural trade negotiations, no doubt for both substantive and tactical reasons. In addition to issues already identified in the AaA, including food security, food safety and quality, environmental concerns, resource conservation and rural development, WTO members have raised such desperate issues as animal welfare, biotechnology, species preservation, safeguarding the landscape, poverty reduction and preservation of rural culture. Governments are under growing pressure to address these issues either directly or in trade talks (Miner, 2001). 2.3.5 The WTO and meat trade Kerr (2001) states it has become abundantly clear over the last few years that the WTO cannot be relied upon to solve all the issues in livestock trade. He is of the opinion that building private relationships is increasingly important for solving issues with common interest among role players in the market. Nevertheless, some of the most pressing issues relating to meat trade involve better access to foreign markets. The ban by the EU on beef production by using hormones provides a good example of the problems being experienced in this field. New issues such as animal welfare and biotechnology are also emerging. Old issues that remain on the trade agenda and that have to be dealt with include dumping, export subsidies and technical barriers to trade (Kerr, 2001). 2.3.5.1 Export subsidies As far as export subsidies are concerned, Kerr (2001) states that while ongoing reform of the European Union's CAP has reduced the degree of export support required for the 47 The international red meat trade arena beef industry, considerable latitude for using of export subsidies remains. While the United States and the Cairns Group have proposed that export subsidies be removed completely, it seems unlikely that the EU will agree. A likely compromise is that there will be further reductions in export subsidies. Obtaining commitments on the basis of individual commodities rather than allowing for averaging subsidy reductions across a range of commodities would reduce the EU's ability to disrupt international meat markets during a domestic market downturn (Kerr, 2001). 2.3.5.2 Market access Market access issues are also likely to be important during the negotiations. As mentioned previously, liberalisation of tariff quotas and their administration could become major points of contention during negotiations. From a meat trade point of view the issues surrounding tariff quotas are likely to involve some other dimensions as well. Kerr (2001) states that allowing disease-free subnational zones in the WTO has made it possible for some South American countries, particularly Argentina, to begin shipping foot-and-mouth-free chilled beef to markets that have traditionally been closed to their products. Total quotas were, however, set prior to the entry of the South American countries into the fresh beef trade, and it is expected that they will have considerable export capacity in place in the near future. Hence, they will favour expansion of the quota portion of the existing tariff quotas, to reflect the new international reality. Failing that, given their likely cost advantage, they may also wish to have the over-quota tariff reduced. The smaller the market access they are able to obtain elsewhere through expansions in tariff quotas, the more cost competitive they will become in the over- quota market. Negotiations on liberalisation of tariff quotas, namely reductions in within- quota tariffs, over-quota tariffs, and the quota quantity, thus need to be conducted carefully because they will be subject to the dynamics of the international beef market (Gainsford and Kerr, 2001). One way of distributing quotas more equitably is moving to market-based allocation mechanisms, such as auctions. The question that arises is how fair such allocations 48 ~------------------------------------------------------------------------- The international red meat trade arena will be. For example, Kerr (2001) mentions that the US would be able to secure large proportions of some countries' beef or pork markets due to their economic power rather than their inherent competitiveness. However, one should keep in mind that the WTO's preference for tariffs over quantitative restrictions as border instruments, arose in part because tariffs ensure that the low-cost country will become the import supplier. This is particularly important when major changes are taking place, such as the entry of South American countries into the international chilled beef market. Thus, the ability of the US to secure market access through their size rather than their inherent competitiveness, raises questions over the "fairness" of quota allocation, and will definitely result in some heated debate during trade negotiations. As far as pork is concerned, Canada has proposed zero-for-zero reductions in tariffs for trade in pork products. The level of protection for pork in the EU is, compared to many agricultural products, relatively low. It seems unlikely, however, that Japan would be interested in opening its market completely and, hence, it may not be possible to achieve an agreement (Kerr, 2001). Furthermore, while China is not yet a member of the WTO, if the agricultural negotiations are sufficiently protracted it may well have acceded prior to a new agreement being reached. China has shown little indication that it wishes to liberalise its pork market, although, in its accession agreement, it has promised to place its pork import regime on a "scientific basis" and to reduce its tariffs from 20 to 12 percent (Kerr, 2000). These concessions were wrested from a China that is desperate to join the WTO. Once it has obtained membership, further liberalisation in agriculture, particularly for meat products, is likely to become very difficult to achieve. 2.3.5.3 Other issues pertaining to meat trade Other major issues pertaining to meat trade that actually fall outside the AoA are (1) dumping, (2) sanitary measures, and (3) technical barriers to trade. 49 The international red meat trade arena ~ Anti-dumping As far as dumping is concerned, several role players in the meat industry have already expressed their dissatisfaction with the "selling below cost" definition (Kerr, 2001; NCBA, 2000). Canada and the National Cattlemen's Beef Association (NCBA) in the US are of the opinion that the definition must be removed as sole criterion for the imposition of anti-dumping duties. Kerr (2001) states that while the intent of this definition relates to predatory pricing, the definition cannot be used in isolation. The reason for this is that the livestock industry worldwide is characterised by production cycles, i.e. when a production cycle is at a low point, prices tend to be high and vice versa. Hence, it is argued that claims with respect to dumping are being made at times when prices are forced downwards by economic and natural factors. In other words, cyclical patterns could result in producers making a loss (prices received are lower than production costs), and for this reason it is argued that if such producers sell their produce internationally at the same prices it should not be regarded as dumping. However, the issue is not that simple to diffuse. Producers in countries such as the US and the EU receive various types of green box payments, as discussed above. Such payments could easily make up the deficit between the price and the production cost, although the payments may not have been introduced for this purpose. The result is that producers may not feel the pressures of the market that much, or not at all. Many other producers worldwide do not have this safety net at their disposal (Kerr, 2001). Also, one should remember that consumption patterns of different products differ between different countries, which could cause products that are seen as by-products in one country to be highly sought after in another country. But the country that has surpluses of the "by-product" could easily use price discrimination to get rid of the product, or stated alternatively sell the product at well below international market prices, whilst the average returns in terms of a commodity package could still be above production costs (NCBA, 2000). It should be clear that the issue of dumping has no simple solution, but given that it would most probably be tabled for renegotiation, it is the responsibility of countries that could be affected most by changes in dumping rules 50 The international red meat trade arena to take action in advance and make sure that they are in a strong negotiating position (Kerr, 2001). • Sanitary measures As mentioned previously, the EU's position on hormone-fed beef has already had serious implications with respect to trade as it relates to market access. This case, however, also has implications for the implementation and adherence to Sanitary and Phyto-Sanitary (SPS) measures as spelled out in the AoA, namely that to ensure a scientific basis for trade barriers relating to human, animal, and plant health. According to Kerr (2001), one of the new agreement's first tests was the long-standing beef hormone dispute between the EU on the one side and Canada and the United States on the other. The EU prohibits the use of beef hormones domestically and also the import of beef products produced using these growth promoters. With the SPS in place, as well as the new arbitration-based dispute settlement system, Canada and the United States challenged the EU ban. The EU lost the case. According to Kerr and Perdikis (1995) the EU based its case largely on technicalities because it was clear that its ban did not have a solid scientific basis. The EU, however, decided not to comply with the WTO dispute panel ruling and, instead, chose to accept retaliation, as is its right (Kerr and Perdikis, 1995). Kerr (2001) states that, while it is possible to accept retaliation and breach WTO commitments legally, these occurrences are rare and usually indicate that the political consensus that underlies the WTO has broken down. When this happens it usually signals that renegotiation at the WTO is necessary. The EU has made it clear that it wishes to renegotiate the SPS to include consumers' concerns. The hormone case proves that the SPS is working as intended - to prevent the capricious use of extreme health regulations to protect producers. Applying the SPS is important for the future functioning of trade in red meat products (Kerr and Hobbs, 2000). 51 1\'UOJiII The international red meat trade arena e Technical Barriers to Trade In respect of Technical Barriers to Trade (TBT) issues relating to requirements in some countries that all meat sold through commercial channels should carry domestic labels raises questions about the aims, functioning and application of TBTs. Kerr (2001) is of the opinion that TBTs need to be strengthened if the red meat industry is to be better protected from regulations such as country-of-origin labelling requirements. Currently, technical barriers must have a legitimate purpose. Further, the TBT states that the "costs of implementing the standard must be proportional to the purpose of the standard". The intent of this statement is ensuring that the benefits received from the standard by consumers should not exceed the costs to exporters of implementing the standard. The point to be made is that the South African red meat industry must note that such issues will probably be put forward for negotiations, and hence a proactive stance must be taken in this regard. Such a "simple" issue may have wide-ranging repercussions in the red meat industry, especially if the combined effect of the issues discussed above is not in South Africa's favour. 2.4 The European Union and its Common Agricultural Policy Three issues necessitate a comprehensive discussion of the EU and its agricultural policy. Firstly, various authors already cited clearly indicated the possible impact of the EU's agricultural policy on agricultural markets worldwide. Secondly, the EU is South Africa's largest trading partner, hence a study such as this would be incomplete without due cognisance of new developments as far as the agricultural policy of the EU is concerned. Thirdly, the EU is the largest import source of beef to South Africa. The EU-SA FTA, however, falls beyond the scope of this study as trade in red meat was put on the reserve list by both countries, and as such falls within the MFN principle of the WTO. The Common Agricultural Policy (CAP) of the EU that was first developed in the early 1960's has been the source for much discussion and conflict amongst agricultural 52 The international red meat trade arena producers worldwide; also in the EU itself (Corbett, 2000). It can also be regarded as one of the most controversial agricultural policies in existence today. The objective of the CAP, to encourage and support increased agricultural production in the EU, was attained to such a degree that by 1990 the EU was self-sufficient in most of the commodities being produced there. In fact, by the early 1990's, the EU started to experience problems with excessive supplies of agricultural commodities (Corbett, 2000). This, apart from the pressures exerted on the EU by the international community to reform the CAP, was one of the main reasons for major reforms to the CAP since the early 1990's (Hathaway and Ingco, 1996). It was accepted that the costs associated with the CAP could not be sustained indefinitely (see Atkin, 1993 for a discussion on costs associated with the CAP). The latest reforms to the CAP are embedded in the so-called Agenda 2000. Figure 2.7 shows the evolution of the CAP reform. 1992 1998 1999 First major Agenda 2000 Revised Agenda revisions developed 2000 proposal to CAP ~~ to European..... Parliament li60 19iO ~2000 •••••r + .. I Iof " 1962 Late1980!t March 1999 2000 Implementation General agreement that Agricultural Council Agenda 2000 of the CAP reform to CAP is needed reach, by qualified Reforms take majority, political effect agreement on revised Agenda 2000 proposal Figure 2.7: Evolution of the CAP Source: Reich, 1999. Several factors, internal and external to the EU, served as catalysts for the recent reforms to the CAP as entrenched in Agenda 2000. According to the European Commission (1999) the major external factors include growing world demand for food, further moves towards a more liberal global trading environment, and the challenge of the European 53 The international red meat trade arena Union's eastward enlargement. According to Reich (1999) the enlargement of the EU placed, and is still placing, increasing pressure on the budget needed to fund the CAP, in fact the CAP now takes the bulk of the EU budget. There also exist imbalances between the extent to which countries fund the EU budget and the amount of CAP support they receive. Furthermore Eastern European countries currently seeking EU accession have large agricultural sectors, and supporting them to current CAP levels would be beyond the EU budget. As was mentioned previously, the EU also recognises the need to liberalise world agriculture under the auspices of the WTO further. Thus, the reforms undertaken can also be seen as an effort of the European Commission to prepare the EU agricultural sector for greater liberalisation (Reich, 1999). From an internal point of view there are four broad factors that need to be addressed. Firstly, there is the very real risk of a return to market imbalances in some sectors. Secondly, the Treaty of Amsterdam, which came into force on May 1, 1999, makes it the responsibility of Community lawmakers to integrate environmental concerns into all legislation. Thirdly, the CAP needs to rise to the challenge of greater consumer interest in food safety, quality and animal welfare. Lastly, the CAP must adapt and respond to the need for further decentralisation, greater transparency and simpler rules (European Commission, 1999). In an effort to address these four factors three key priorities were identified, namely (European Commission, 1999): • to ensure the competitiveness of the European Union agricultural sector both on the Community market and on growing export markets; • to promote ways of farming that contribute to the maintenance and enhancement of rural development and landscapes; • to contribute to sustaining the livelihood of farmers while promoting the economic development of the wider rural economy. According to Reich (1999) it would appear that the major emphasis of Agenda 2000 is the protection of farmers' livelihoods, rather than implementing policies that encourage increased production efficiencies and environmental protection. To what extent such an 54 The international red meat trade arena allegation is valid is difficult to measure at this stage, but time and the new Round of agricultural negotiations will surely provide answers. According to the European Commission (1999), Agenda 2000 resulted in several new regulations, and restricts the agricultural budget to an average of EUR 38 billion annually for market policy (including veterinary and plant health measures) and EUR 4.3 billion for rural development measures. The new regulations which will come into force (with the exception of milk) from the year 2000 onwards, concern the arable crop, beef, milk and wine sectors, the new rural development framework, the horizontal rules for direct support schemes and the financing of the CAP. 2.4.1 CAP and the red meat sector The beef and veal sector is the second largest production sector in the EU, accounting for around 10 per cent of total agricultural production (after dairy with a share of 18% in 1998) (European Community, 2000a). Hence, it is understandable that the beef sector was high on the agenda for further liberalisation and will be the main point of discussion in this section, although reference will also be made to pork and sheep meat. Rodriguez (2000) supports the idea that further liberalisation of the beef sector is needed, even though there was a 15 per cent price reduction for beef since 1992, to align EU beef prices with world prices. EU price support is facilitated by an intervention scheme that involves purchasing beef to maintain market prices above certain levels. The benchmark for intervention is the so-called intervention price that effectively places a floor under domestic wholesale prices. Intervention into the market is triggered when the market price in the EU falls to 80 per cent of the intervention price. This price was set at EUR 3 475 per ton for the first six months of 2000. This is also the basis for further reductions as stipulated in Agenda 2000. More specifically, Agenda 2000 introduced a 20 per cent reduction in the level of price support in three equal steps with EUR 3 475 per ton as basis (see Table 2.18). The change in the intervention scheme also involves a change from intervention purchasing by government to an EU-funded 55 The international red meat trade arena Private Storage Aid (PSA) scheme for beef that is currently being used by the EU's pork industry. Table 2.18: Reductions in beef support prices (EUR per ton) Year Intervention price Safety Net Trigger Basic Price Trigger price 1999/2000 3475 2085 2780 2000/2001 3242 1 910 2001/2002 3013 1735 2002/2003 2224 2291 Source: Adapted from Reich, 2000. Table 2.18 shows that the intervention price will be replaced by a basic price for storage, fixed at EUR 2 224 per ton during 2002/2003. The basic price serves as proxy for triggering the PSA scheme, i.e. when the market price falls below 103 per cent of the basic price for beef (EUR 2 291 per ton) the PSA scheme will come into play. According to Reich (2000) the PSA scheme effectively acts as an incentive scheme since certified storage vendors can receive payments from the EU for the storage of commodities for the agreed length of time. She argues that this essentially maintains the market price at EUR 2 291 per ton, because if the price falls to this level, the PSA scheme is triggered. It should be noted that from July 1, 2002 producers may also benefit from a "safety net" intervention system. Reich (2000) states that the EU always had a "safety net" system in place, which was triggered when market prices fell below 60 per cent of the intervention price. Agenda 2000 stipulates that the level for the "safety net" trigger price should be reduced to 25 per cent, i.e. when the average market price for bulls or steers in a Member State (or region thereof) is less than EUR 1 560 per ton for two consecutive weeks, buying-in tenders will be organised in the respective Member State by the Commission through the Management Committee procedure (European Commission, 2000a). Rodriguez (2000) suggests that it is evident that reducing EU prices will take time and that, at the end, there will still be a significant difference between the Community prices and those of other world producers. According to the European Commission (1997), 56 The international red meat trade arena with an average support level of 80 per cent of the intervention price, i.e. a price of around EUR 2 780 per ton, the EU price would still be nearly about 20 to 25 per cent higher than the projected US price after 2000 (depending on the US$-EUR exchange rate) and 30 per cent or more higher than other major exporters. Rodriguez (2000) also mentions that since early 1995 beef subsidies have dropped on numerous occasions. In 2000 subsidies were less than half what were in 1995. The total annual expenditure on beef subsidies has been reduced by 66 per cent compared to the case before the WTO agreement was accepted. He also mentions that in the swine sector the amounts exported without subsidies are now more important than the subsidised pork. Over and above the reforms to the price support system for beef, Agenda 2000 also involves support to beef farmers through direct payment to offset income reductions resulting from reform in the price support system. Direct payments take several forms, and include special premiums, slaughter premiums, extensification premiums and deseasonalisation premiums. Table 2.19 shows the special and slaughter premiums as embedded in Agenda 2000. The former entails an annual premium granted per calender year and per holding within the limits of regional ceilings for not more than 90 animals. The latter involves that farmers receive premiums if they provide proof that animals are slaughtered or exported to a third country, and were owned by the farmer for at least 2 months. 57 The international red meat trade arena Table 2.19: Special and slaughter premiums for beef (Agenda 2000) Type of premium Type of animal 1999 2000 2001 2002 EUR per head Special premium Bulls 135 160 185 210 payments" Steers 108.7 122 136 150 Suckler cow 144.9 163 182 200 Slaughter prerniurn'" Bulls 0 27 53 80 Steers 0 27 53 80 Dairy cows 0 27 53 80 Suckler cows 0 27 53 80 Heifers 0 27 53 80 Calves 0 17 33.. 50 • This premium IS paid only once In the hfetlme of bulls older than 9 months or at a minimum carcass weight of 185 kg. This premium is also paid only once in the lifetime of a suckler cow, but twice in the lifetime of steers (9 months and 21 months) •• Bulls, steers, dairy cows, suckler cows and heifers eligible for this premium should be older than 8 months. Calves qualify if they are older than 1 month but younger than 7 months and less than 160 in carcass weight (kg). Source: Reich, 2000; European Commission, 2000a. Reich (2000) also mentions that Agenda 2000 affords what is called national envelopes for each member state, to supplement direct payments made for male and female bovine animals and provide extra flexibility when making direct payment. Agenda 2000, in an effort to promote environmental sustainability, also entails an extensification premium. This involves farmers qualifying for special premiums receiving an additional premium of EUR 100 per premium granted, provided that the stocking density on their holdings per calender year did not exceed 1.4 livestock units per hectare. However, Member States may decide to grant the "extensification" payment as follows (European Commission, 2000a): • In respect of the calendar years 2000 and 2001 an amount of: EUR 33 for a stocking density of 1.6 livestock units per hectare or more, and less than or equal to 2.0 livestock units per hectare; EUR 66 for a stocking density of less than 1.6 livestock units per hectare. • In respect of the calendar year 2002 and the subsequent years an amount of: EUR 40 for a stocking density of 1.4 livestock units per hectare or more, and less than or equal to 1.8 livestock units per hectare; 58 The international red meat trade arena EUR 80 for a stocking density of less than 1.4 livestock units per hectare. The qualification criteria are rendered more rigorous by taking account of all the adult cattle actually present on the farm as well as sheep on which premia are claimed. The number of hectares considered is limited to temporary and permanent pasture and all the other forage areas, except arable crops (European Commission, 2000a). The "deseasonalisation" premium aims to encourage slaughtering out of the traditional slaughter season, in order to reduce surges in supply at particular times of the year, as well as to reduce the pressure on prices. The premiums are available in Member States, where steers slaughtered in a given year account for more than 60 per cent of total number of male animals slaughtered and where more than 35 per cent of the slaughtering takes place between September 1 and November 30. The premium levels function on a sliding scale depending on the time of slaughter (from EUR 72.45 for animals slaughtered in the first 15 weeks of the year, to EUR 18.11 for animals slaughtered between the 22nd and 23rd weeks of the year). (European Commission, 2000a). In order to illustrate the situation from a South African point of view it is useful to apply the various support measures to an actual production situation to and convert the values to South African Rand (EUR1 = R7.14). Table 2.20 shows the situation before Agenda 2000, and for two different situations after the implementation of Agenda 2000. In Situation 1 it is assumed that a beef producer receives the highest extensification and deseasonalisation premiums possible under Agenda 2000. In Situation 2 it is assumed that no extensification premium is payable, whilst the beef producer receives the lowest deseasonalisation premium payable. Comparing Situation 1 with the original situation it is clear that the EU beef farmer will secure a higher price than was the case before the implementation of Agenda 2000. In Situation 2 the EU beef farmer is worse off than was the case before the implementation of Agenda 2000. At present Situation 2 is more likely, due to the fact that beef farmers in the EU could experience some problems 59 The international red meat trade arena with respect to extensification (Reich, 2000). Most notable in Table 2.20 is the extremely high returns to the EU farmer in Rand denominated terms, even in the case before the implementation of Agenda 2000. At the time of writing this document the South African producer (carcass) price ranged between R7.50 per kg and RB.50 per kg; this was far below the producer price EU beef producers receive, as is shown in Table 2.20. Table 2.20: Level of support payments for a European farmer producing a 550 kg steer for sIauglhter Support measures Original situation Situation 1 Situation 2 EUR Rand EUR Rand EUR Rand per head equivalents per head equivalents per head equivalents per head per head per head EUR1 = R7.14 Price support 1 529.00 10917.06 1260.00 8996.40 1 260.00 8996.40 Special premium 217.40 1 552.24 300.00 2142.00 300.00 2142.00 Slaughter premium 0.00 0.00 80.00 571.20 80.00 571.20 Extensification premium 0.00 0.00 100.00 714.00 0.00 0.00 Deseasonalisation premium 0.00 0.00 72.45 517.29 18.11 129.31 Total 1 746.40 12469.29 1 812.45 12940.89 1 658.11 11 838.91 Price per kg 3.18 22.67 3.30 23.53 3.01 21.53 Although the sheep and goat industry is not directly affected by Agenda 2000, this sector seems to be indirectly influenced by two elements of it. There is, firstly, the expected lower price for the other types of meat and, secondly, the higher cattle premiums combined with the density factors and the new rules on extensification (European Commission, 2000b). Regarding the first aspect, there is a risk that sheep/goat prices could come under pressure due to increased competition caused by the probability of falling prices for the other types of meat. This is especially true for beef, for which the price cut of 20 per cent in three years is substantial, but also pig meat and poultry prices which are expected to decrease to some extent due to expected lower cereal prices. Ashworth (2000) states that sheep and goat meat production in the EU has declined since 1990 partly due to the reform of the Common Market Organisation (CMO) in 60 The international red meat trade arena 1992. However, according to the European Commission (2000b), more recent declines in sheep and goat numbers can probably be attributed to reforms in the beef industry under Agenda 2000. In other words, the anticipated increase in cattle premiums and the new rules on extensification could have provided an incentive for mixed farms (cattle/sheep) to switch from sheep/goat to cattle, as the density factors for animals have to be respected. The magnitude of this impact is, however, extremely difficult to quantify since it depends mostly on individual circumstances on a given farm. A variety of elements may influence such an adjustment, for instance the number of available premium rights, farm size in ha, individual constraints concerning the density factor farmer preferences regarding the type of farming, expected price, and market developments. The decision to switch from a headage to area payments for sheep and goat farmers within less favoured areas (LFA) could also have resulted in de-stocking. Ashworth (2000) states that at present sheep and goat meat production is the least significant of the livestock enterprises commonly found in the EU, accounting for only 3 per cent of meat production by volume. However, in terms of the total agricultural output of the EU, sheep and goat meat production accounted for around ECU 4 bn in 1997. Hence, although it only accounted for 2 per cent of the total value of agricultural production, sheep meat and goat meat producers receive a disproportionately high level of support. For example, in 1997 they received 3.5 per cent (ECU 1.4 bn) of the total European Agricultural Guarantee and Guidance Fund (EAGGF) expenditure. This compares with 1.2 per cent on pig meat, 16.3 per cent on beef and 7.7 per cent on milk. The EU Court of Auditors (CEC, 1995) estimated that, in 1992, each kilo of sheep meat received 1.7 ECU of support; more than three times the support paid per kilo of beef. By 1997 this gap had narrowed, but it is estimated that support per kilo of r:neat is 50 per cent greater in the sheep and goat sector at ECU 1.3 per kilo of meat than the beef sector. 61 The international red meat trade arena 2.4.2 The impact of Agenda 2000 The European Commission (2000c) summarises the results of three separate studies conducted to estimate the impact of the Agenda 2000 CAP reform in the year 2005 with reference to a status quo policy situation. The status quo situation corresponds with a policy scenario based on the continuation of the 1992 CAP reforms. However, it should be noted that the status quo scenarios vary substantially across studies, mainly with regard to medium-term developments on world agricultural markets and key policy (e.g. compulsory set-aside rate) as well as economic variables (e.g. €I$ exchange rate). Therefore, for comparative purposes, the simulation results are presented in the form of deviations from the reference scenario. This enables the depiction of the likely impact of Agenda 2000 on the economy while reducing (though not avoiding) any potential bias generated by the models and the starting point, when both status quo scenario and Agenda 2000 situations are compared in terms of absolute levels. Furthermore, results should not be interpreted as changes relative to the current (unreformed) situation (European Commission, 2000c). The separate studies were carried out by the University of Bonn using the SPEUEU- MFSS model, the Food and Agricultural Policy Research Institute (Fapri) and the Centre for World Food Studies of the University of Amsterdam, using the CAPMAT model of the EU agricultural sector. The European Commission (2000c) states that the various policy changes to be implemented in the beef sector are expected to have countervailing effects. On the one hand, the reduction of the current support prices, the removal of the current intervention system and its replacement by a private storage scheme and a new "safety net" intervention system, the adjustment in the suckler cow ceilings and the eligibility of heifers for suckler cow premium (to a maximum of 20%) should exert downward pressure on supply. On the other hand, the increase in the existing direct payments and the introduction of the slaughter premium, combined with lower feed costs and higher milk quotas, should support production. Table 2.21 shows the estimated impact of the 62 The international red meat trade arena Agenda 2000 CAP reform in the year 2005 with reference to a status quo policy situation. Overall, the three studies foresee that the former elements would outweigh the latter, resulting in a small decline in beef production compared to the status quo scenario. Beef consumption would benefit from the fall in domestic prices. However, it is expected that after a short-term increase in absolute value supported by lower prices, beef consumption would resume its long-term decline from 2003 onwards (European Commission, 2000c). Assuming constant stock levels, higher internal demand combined with lower supply levels would strongly diminish exportable surplus. Table 2.21: Outlook for beef balance in 2005 under Agenda 2000 Agenda 2000 Simulation in Status 2005 quo SPEUEU-scenario MFSS Fapri -1* Fapri - 11* CAPMAT Production 100 99.9 97.8 99.5 98.6 Consumption 100 101.8 102.8 103.1 106.4 Net exports 100 37.8 92.1 17.5** Ending stocks 100 0 19 100 Producerprice 100 80 87.9 87.1 80 * The study by FAPRI consists of two quantitative analyses. The first one was conducted by the FAPRI unit at the University of Missouri (Fapri - I) using an experimental version of an EU model, whereas the second analysis was carried out in the FAPRI unit at the University of Iowa (Fapri - II) using their set of models of major world agricultural markets. *. Gross exportable surplus. Source: European Commission, 2000. The European Commission (2000c) also states that policy changes in the beef and arable crop sectors are expected to have an impact on the pork sectors (See Table 2.22). Lower feed prices are expected to favour production of white meat whereas more competitive beef prices should exert pressure on white meat consumption and, in turn, on domestic prices and production levels. The degree to which lower feed prices and more competitive beef prices will impact on the pork sector differs across studies, which provides diverging results. On the one hand, the Fapri-Missouri and the SPELlEU- MFSS model expects pork consumption to suffer as a result of cheaper beef, with declines ranging between -0.3 per cent and -1.2 per cent. Lower consumption levels would exert pressure on market prices for outweighing the impact of lower feed prices, and generating a slight fall in pork production of roughly the same magnitude. 63 The international red meat trade arena Conversely, the feed cost reduction effect dominates in the Fapri-Iowa and CAPMAT model, with a modest rise projected for pork production, ranging between 0.1 per cent and 0.6 per cent. Consumption would also develop accordingly, although the CAPMAT model foresees some adjustments between internal and external demand (European Commission, 2000c). Table 2.22: Outlook for pork meat balance in 2005 under Agenda 2000 Status Agenda 2000Simulation in 2005 quo SPEUEU-scenario MFSS Fapri -1* Fapri -11* CAPMAT Production 100 99.7 99.5 100.3 100.1 Consumption 100 99.7 99.4 100.3 100.4 Net exports 100 100.7 97 Producer price 100 93.3 96.8 95.4 95.6 * Fapn -I = Fapn Mlssoun; Fapn -II = Fapn Iowa. Source: European Commission, 2000. The decline in the price of pork due to Agenda 2000 also varies across studies, but the general direction of prices compared to the status quo scenario is downwards. The SPEUEU model shows the largest drop in pork prices (-6.7%), whilst a much more modest drop (-3.2%) is predicted by the Fapri - Missouri model (European Commission, 2000c). 2.5 The Lomé Convention The EU offered South Africa a qualified membership of the Lomé Convention, which came into force following the approval of the ACP/EU Council in April 1997, and after the ratification of the Lomé IV in May 1998. It should be noted that, although several articles within the framework of the Convention are applicable to South Africa, special protocols on bananas, rum, beef and veal, sugar, coal and steel products were not afforded to South Africa. However, the protocol on beef is applicable to several of South Africa's neighbouring countries and could have an influence on the South African red meat industry. This justifies a short discussion on the Lomé Convention (Corbett, 2000). 64 The international red meat trade arena Davenport, Hewland and Koning (1995) state that an investigation into Lomé IV by a GATT working group concluded that the Convention is in breach of GATT rules. This conclusion is based on the fact that the Convention is non-reciprocal and that it discriminated between developing countries. The EU and the African-Caribbean-Pacific (ACP) countries sought a waiver, which was granted until the year 2000. At a meeting held in Brussels, Belgium, from 2 to 3 February 2000, the EU and ACP states concluded a new agreement, an extension of the Lomé Convention that regulates development cooperation and trade relations between the two regions. According to Buhera (2000), one of the major agreements entered into is the determination of an eight-year transition period during which new negotiations on trade and economic arrangements with the EU are to be negotiated and concluded. This transition will run from 1 March 2000 to 31 December 2007, during which period market access into the EU will continue under current arrangements. A further 12 years was agreed upon as the implementation period. In addition, 13.5 billion euros were made available under the extended Environment Development Fund (EDF) to assist development efforts of ACP countries for the period 2000 to 2005. This assistance would be used to support and promote efforts of ACP countries, which include poverty reduction, private sector development and reform of ACP economies and gradual integration of ACP countries into the global economy. Other assistance relate to relieving the debt positions of ACP countries. Among other issues discussed at the Brussels meeting were the level of aid to ACP nations, good governance, corruption, market access for countries not classified as least developed and the duration of the new convention (Buhera, 2000). The outcome of the talks was generally favourable for the ACP countries and a number of important agreements were reached. In order for this arrangement to be compatible with World Trade Organisation (WTO) rules and regulations, the EU is expected to request for a waiver to continue with the current trade preferences. Internal arrangements are being made to ensure continuity of trade flows from ACP to EU (Buhera, 2000). 65 The international red meat trade arena The implications of these agreements for the ACP countries are that they will continue to benefit from the current trade preferences without disruptions during the eight-year preparatory period. Duty-free items and those on concessionary duty will continue to benefit during the transition period. The more favourable preferential terms granted to the ACP countries for accessing the Common European Market is seen to be more important than the financial development assistance covered by the agreement (Buhera, 2000). The new agreement also involves the strengthening of political relations between the ACP and EU states. In addition, due cognisance was also taken of the fact that the parties concerned are expected to take part in the negotiations and implementation of agreements leading to further multilateral and bilateral trade liberalisation. At the same time recognition was given to the fact that this wider process of liberalisation could lead to a deterioration in the relatively competitive position of the ACP States, which would threaten their development efforts. In the light of this, the EU and the ACP countries agreed to examine all necessary measures in order to maintain the competitive position of the ACP countries on the Community market during the preparatory period. This examination may include, inter alia, calendar requirements, rules of origin, sanitary and phytosanitary measures and implementation of specific measures addressing supply side constraints in the ACP countries. The objective will be to offer ACP countries opportunities to exploit their existing and potential comparative advantage on the Community market. Bearing in mind their commitment to cooperation in the WTO, the Parties agree that this examination will also take into account any extension within the WTO of the trade advantages which may be offered by member countries to developing countries (Buhera, 2000). For Botswana, Mauritius, Namibia, Swaziland and Zimbabwe, the current quotas on beef and sugar will stay in place. More specifically, Declaration XXVI of the final agreement states that the EU undertakes to ensure that the beneficiaries of the Protocol on beef and veal in ACP countries derive full benefits from it (European Commission, 2000d). To this end, the EU committed itself to enact appropriate rules and procedures in a timely fashion. The EU also committed itself to implementing the protocol, so that 66 The international red meat trade arena ACP States can market their beef and veal without undue restrictions throughout the year. At present ACP states that qualify for preferential beef quotas can market their beef to the EU at reduced costs in terms of tariffs and duties, e.g. an exporter in South Africa who wants to export beef to the EU will be liable to pay 12.8% plus 303.4 EUR per 100 kg, but an exporter in Botswana will pay 0% plus 24.2 EUR per 100 kg as far as the preferential quota is concerned (TARIC, 2001). Apart from only providing preferential access to ACP countries for their beef and veal, the EU also declared its willingness to assist the ACP beef and veal exporters in improving their competitiveness through, inter alia, addressing supply-side constraints, in accordance with the development strategies set out in this Agreement and within the context of National and Regional Indicative Programmes. Table 2.23 shows historical trends in EU imports of boneless beef from ACP countries free of customs duties and at a reduced rate of the EU import tariff. It is clear that in most years the mentioned countries were not able to fulfil their quotas, except Zimbabwe that exported well over its quotas in 1994 and 1995. It should also be noted that if any ACP country is not able to supply its annual quota, a decision may be taken to devide the quantities between the other states concerned, up to a limit of 30 000 tons, for the same or following year. The other interesting trend to note is that in total the quotas exported to the EU declined continuously from 1994. This can be attributed to, amongst other reasons, the stringent health regulations applied by the EU, e.g. the stringent animal health rules of the EU have on several occasions led to the suspension of beef exports, in particular from Botswana and Swaziland. Zimbabwe has also experienced problems with health regulations applicable to beef exports to the EU (CAP- monitor, 1995). 67 The international red meat trade arena Table 2.23: EU beef imports (tons' from ACP states (1994 - 1998) Year Total Botswana Namibia Madagascar Swaziland Zimbabwe Allocated quota 52100 18916 13000 7579 3363 9100 1994 42484 12425 11 087 2087 642 16242 1995 41146 16521 12369 4024 720 10512 1996 31 298 11 511 9770 1 753 533 7753 1997 25181 10670 6026 435 225 7825 1998 26302 11 859 8292 15 149 5986 Source: Bruwer, 2000. 2.6 Conclusions This chapter discussed a wide range of issues important to the red meat industry internationally, which will also cascade down to the domestic red meat industry. It should be clear that it is difficult to highlight specific issues without also referring to related issues, i.e. the process of policy reform and trade liberalisation in the international red meat market are interlinked to such an extent that they are mutually influential. Nevertheless, it is clear that liberalisation and policy reform will lead to higher international prices for red meat. The worrying factor, however, is that the speed of this process differs considerably between countries, which raises the question whether it is beneficial to all countries. Another issue of importance is the fact that estimations on the effect of liberalisation to a large extent ignores the risks associated with changing climate patterns and consumer preferences. Hence, when evaluating estimates that relate to trade liberalisation, one should be aware of the fact that other factors, such as climate, may have a greater influence on how markets behave. Furthermore, it is clear that the Uruguay Round has set the table for further liberalisation efforts, but that role players have also become more "devious" in their approach to trade liberalisation. Imbedded in the AaA are also various opportunities for rent-seeking that may defy the purpose of further negotiation on liberalisation. The 68 The international red meat trade arena case of TRas serves as good example. Also, several new issues have come to the fore and may prove even more difficult to reach agreement on than the issues tabled during the Uruguay Round. These issues relate to product identification, food safety, etc. It is thus important to take cognisance of these issues when preparing for further negotiations on trade liberalisation. Of particular importance is the stance of developing countries towards trade liberalisation. It is clear that these countries could reap substantial benefits from trade liberalisation, but the question remains whether the economies of these countries are geared to participate fully in a more liberalised trade environment. In other words, one must ask whether the supply chain, institutional environment and infrastructure in developing countries have been adapted to enhance their favourable participation in a more open market environment. The answer to this question warrants a debate on its own, but of significance to South Africa is the fact that all neighbouring countries fall within either the developing or least developed country classification. In other words, the state of openness of the economies of these countries and to what extent they are able to benefit from a more open market environment will definitely have an influence on, not only South Africa's trade relations internationally, but also the economy. This is especially important from a Southern African Development Community (SADC) perspective. 69 CHAPTER 3 OVERVIEW OF THE SOUTH AFRICAN RED MEAT SECTOR 3.1 Introduction The South African red meat industry was, and will in the future remain, one of the most important agricultural sub-sectors in South Africa. This can be attributed largely to natural circumstances. For example, approximately 70 per cent of South Africa's total area of 1.2 million km2 is only suitable for livestock production. Furthermore, the red meat industry evolved from a highly regulated environment to one that is totally deregulated today. Various policies, such as the distinction between controlled and uncontrolled areas, compulsory levies payable by producers, restrictions on the creation of abattoirs, the compulsory auctioning of carcasses according to grade and mass in controlled areas, supply control via permits and quotas, the setting of floor prices and the floor price removal scheme, etc. characterised the red meat industry before deregulation commenced in the early 1990's (Jooste, 1996). The final nail in the coffin of the regulated red meat market dispensation came in 1997, when all control boards were abolished. Since then the red meat industry has experienced several structural changes, e.g. an increasing number of animals being raised in feedlots and the mushrooming of abattoirs in the previously uncontrolled areas. Also, informal trade in red meat increased tremendously (Schutte, 2000). In terms of SACU the red meat industry is also very important, especially for Namibia and Botswana. Schneider (1992) reports that 90 per cent of the 690 000 square kilometres of land used for agriculture in Namibia is utilised for extensive livestock farming (i.e. cattle ranching, 48%; mixed cattle and small stock ranching, 14,5%, and small stock ranching, 37,5%). Beef processing in Botswana accounts for around 80 per cent of agricultural output. Nevertheless, although Botswana's climate and soil renders it suitable for large scale ranching water shortages bring about that only 20 per cent of the land area can be grazed by stock (The Economist Intelligence Unit, 1995). According to 70 Overview of the South African red meat industry Fourie (1972), the soil in the largest part of Botswana is also unsuitable to arable agriculture. In addition the livestock industries in Southern Africa is highly dualistic. For example, in Zimbabwe the commercial sector comprises between 25 to 30 per cent of the Zimbabwean cattle herd, whilst it contributes about 80 per cent of total beef production (Takavarasha, Mafurirano, Zitsanza and Mfote, 1997; The Economist Intelligence Unit, 1996). Mupotola-Sibongo, Kadhikua and Sakaria (1997) reports that the communal and commercial herds are approximately equal in Namibia, whereas nearly 90 per cent of cattle marketed at livestock auctions originate from the commercial sector. They also state that productivity in the communal sector is low. Similar situations are reported for South Africa, Botswana and Zambia by Jooste, Van Schalkwyk, Bekker and Lourens (1997), Fidzani, Makepe and Tlhalefang (1997) and Kafuli and Maweie (1997), respectively. In general the commercial sectors are characterised by capital intensity, livestock fattening, proper land tenure, availability of infrastructure, etc., whilst the smali- scale sector is characterised by low offtake rates, overgrazing, lack of tenure, and use of livestock for several purposes over and above that of marketing (e.g. draft power, security or store of wealth, provision of manure, etc.). Given the size of the small-scale or communal livestock sectors in Southern Africa it can, and should, play a much more important role in contributing significantly to the improvement of welfare. However, the emergence of these sectors will be determined largely by factors such as accessibility to markets, opportunities to trade, as well as price and policy variables (especially tariffs). The reason for also mentioning other Southern African countries is the fact that the problems experienced by these countries with regard to their red meat sectors are to a large extent similar to the situation in South Africa. Thus, even though this chapter specifically discusses the South African red meat industry, it may provide insight into issues of common interest. This chapter will focus mainly on the trade of red meat products. However, trade is derived from production and consumption in different regions, and hence brief mention will also be afforded to these two issues. 71 Overview of the South African red meat industry 3.2 Production of red meat in South Africa The beef sector Figure 3.1 shows the South African cattle herd and the number of animals slaughtered annually since 1973. The commercial cattle herd comprises approximately 65 per cent of the total cattle herd. This means that approximately 35 per cent of all cattle in South Africa are owned by non-commercial farmers. Sixty-eight per cent of the commercial herd comprises female animals, of which the majority is for meat production. The composition of the national herd is not expected to change significantly in future. The main feature depicted in Figure 3.1 is the cyclical trend in herd numbers. Lubbe (1990) states that the cyclical behaviour of beef supply is attributable largely to cyclical behaviour of female slaughterings. The main contributor to this phenomenon is climatic conditions. The correlation between national herd numbers and the three-year moving average of rainfall was estimated at 0,62 by the Sunnyside Group (1991). Lubbe (1990) investigated the decomposition of price time series components of the red meat industry. He states that the combined effect of rainfall, the variation in production capacity and price expectations produce an environment for relatively stable prices. Furthermore, livestock expansion and liquidation processes are fueled by the rainfall cycle and rainfall expectations. Lubbe (1990) concluded that agricultural policy and farmers' strategies could be more effective if the existence and nature of price and rainfall cycles are known. 72 Overview of the South African red meat industry 14000 3300 3100 13500 2900 0-0 .0.... ê -0.0.... 13000 2700 -(/j 2500 Cl .C;:: '0 '- 12500 2300 ~Q) 2100 J:::t Cl 1900 ~:::J12000 1700 en 11500 1500 ~~~~~~r~o~mroor~Nor~~o~oiolrlor~oooromoOo~Nro~o~o~ill~oomo ~m~m~m~m~m~m~m~m~m~~m~m~m~m~m~m~m~m~m~~m~m~m~m~mmmo mmmmmmmmmmo N Year 1 Cattle herd numbers-+- Numberof cattle slaughtered 1 Figure 3.1: The South African cattle herd and slaughtering (1975 - 2000) Source: Agrimark Trends, 2000; NDA, 2000. Since the deregulation process started in the red meat industry in 1992 there has been a marked increase in the number of cattle slaughtered in previously non-controlled areas. Before deregulation the slaughtering of red meat was demarcated into controlled and uncontrolled areas. In other words, red meat producers in the uncontrolled areas were not allowed to slaughter animals in uncontrolled areas and then sell the meat in controlled areas. They were, however, allowed to transport the live animals to the controlled areas for slaughtering, after which the meat could be sold there. According to Venter (1996) this means that the beef industry has moved to a marketing system aimed at reducing the direct and indirect costs of marketing (direct costs include transport and other transaction costs, as well as social costs, whilst indirect costs include issues such as weight loss and deaths). The result of this state of affairs is that direct marketing and the number of animals slaughtered in primary production areas has increased at the expense of carcass auctions in large metropolis. Venter (1996) also states that this phenomenon is not unique to South Africa, and cites Tomek and Robinson (1990) who described a similar situation in the US. 73 Overview of the South African red meat industry • The pork sector Figure 3.2 shows the relation between the number of commercial pigs slaughtered and the domestic pig herd. The growth in terms of the pig herd and the number of animals slaughtered can be attributed largely to big investments in this industry, e.g. computerised feeding and environmental maintenance equipment, better disease control by improving the housing environment, etc., that contributed to improved production circumstances and efficiency. 1700 2200 1600 2000 - o ê 1500 o 0 1800 z, 0 1/1 0.-... 1400 Cl1600 c'c".C.. 1300 .S! CII J: 1200 1400 '§,:s 1'0 1100 1200 en 1000 1000 m~~oomO~N~mm~m~m~mrmomrmomo ~o~m~ommrmomomo ormoO~mmmrmo No~o~mmmr ~ mo m mo ~oomommmmmmmmmm ~~~~~~~~~~~~~~~~~~~~~~~m~ Year 1-4- Pork herd ~ Number of pigs slaughtered 1 Figure 3.2: The South African pig herd and slaughtering (1976 - 1999) Source: Agrimark Trends, 2000; NDA, 2000. • The sheep industry Figure 3.3 shows the South African sheep flock and the number of sheep slaughtered. Sheep numbers started to drop quite drastically during the mid 1980's, mainly due to a collapse of the wool industry, but recovered well up to 1990, whereafter it dropped again and stabilised at around 29 mio animals. Similarly, sheep meat production dropped to an all-time low in the mid 1990's. The main reasons for this phenomenon can be traced back to the following: 74 Overview of the South African red meat industry • Severe drought in the early nineties; • escalation of stock theft; and • the breakdown of vermin control. 36000 10000 35000 9000 34000 ê00 g 33000 8000 z, ~ 32000 7000 II) cCl ~ u 31000 6000 "t: ...Sl0 30000 cu, 5000 Ol 29000 :::Jnl 28000 4000 (/) 27000 3000 Year I-+- Sheep flock -+- Number of sheep slaughtered I Figure 3.3: The South African sheep flock and slaughtering (1975 - 1999) Source: Agrimark Trends, 2000. Since the deregulation process started in 1985, a healthy informal market has been created, with its own distribution network. Today approximately 1,6 mio sheep are marketed in the informal market, growing at approximately 2 per cent per annum. For example, Karaan and Myburgh (1992) report that the marketing of sheep in the Western Cape Townships has grown tremendously and has developed its own marketing distribution system. However, this system is not without problems, e.g. there are sporadic shortages of sheep, a relatively low degree of competition, high risk and concerns about health and hygiene hazards. Despite these problems it appears as if the entrepreneurs in this market segment are able to exploit the opportunities that exist. In fact, there are important lessons to be learned from the study by Karaan and Myburgh (1992), e.g. sheep that used to grade badly in the formal marketing channels are highly sought after in the townships. They state that it is ironic that low graded sheep meat attain much higher prices than the better graded sheep/carcasses at the 75 Overview of the South African red meat industry auctions, but that retailing to the consumers takes place at cheaper prices than formal prices on average. This can be attributed to lower cost of distribution and lower opportunity cost of their labour, whilst at the same time these entrepreneurs succeed to provide constant form, place, time and possession utilities that consumers in this market segment need. 3.2 Consumption of red meat in South Africa • The beef sector The per capita consumption of beef has come under increased pressure since the early 1990's. This can be attributed mainly to a decreasing or stagnating per capita disposable income and the price advantage that poultry has over beef. Figure 3.4 shows the relation between real per capita disposable income and the per capita consumption of beef. It is clear that per capita disposable income and beef consumption are very closely linked. This is emphasised by the fact that beef has a high income-elasticity of demand (Nieuwoudt, 1998). Nieuwoudt (1998) suggests that the expected racial mix of the South African population has important implications for food demand. This entails, for example, that with the Black population growth rate being higher than those of the other groups, the average per capita food consumption of all groups taken together may decline over time even although the per capita growth rate of each group may be increasing. The reason for this phenomenon, as suggested by Nieuwoudt (1998), is that the group with the highest population growth often has the lowest per capita demand consumption of livestock products. 76 Overview of the South African red meat industry 9800 26 9600 24 9400 22 20 S "rC::: 9200 c.. CIS 18 CIS() 0:: 9000 16 -Cl~ 8800 14 8600 12 8400 10 Year I _._ Per capita disposable income ~ Per capita consumption of beef I Figure 3.4: Relation between real per capita disposable income and the per capita consumption of beef (1973 - 2000) Source: SARB, 2000; NDA, 2000; own calculations. Nieuwoudt (1998), by considering (i) population growth rate, (ii) income elasticity, (iii) economic growth rate and (iv) urbanisation, estimated the demand for various livestock products under different economic growth scenarios until 2020/2021 (for a detailed description of the analytical framework see Nieuwoudt (1998)). Taking a short-term view the expected increase in the demand for beef under a 3 per cent growth in the economy and low income scenarios could range between 12 and 25 per cent for 2000/2001 with 1995 as basis. Estimations for a 5 per cent economic growth rate were also made, but given the state of the world economy, and specifically the South African economy, such a growth rate is not foreseen. In fact, even when taking an optimistic view, a 3 per cent growth rate in the economy over the next few years is unlikely. Given this assumption, per capita demand for beef is expected to remain relatively constant or even decline in the foreseeable future. 77 Overview of the South African red meat industry • The pork sector The per capita consumption of pork has been moving sideways over the last couple of decades. This is contrary to the trend with regard to the per capita beef and mutton consumption. As is the case worldwide, pork and poultry serve primarily as substitutes for beef consumption. In certain instances pork is regarded as the other white meat. Although a misconception, it proves to be to the benefit of pork producers. Figure 3.5 shows the relation between real per capita disposable income and the per capita consumption of pork. 9800 3.80 9600 3.60 9400 3.403.20 S "cC 9200 : 3.00 'iita ta a:::: 9000 2.80 -a, 8800 2.60 ~2.40 8600 2.20 8400 2.00 Year I _._ Per capita disposable income ~ Per capita consumption of pork I Figure 3.5: Relation between real per capita disposable income and the per capita consumption of pork (1973 - 2000) Source: SARB, 2000; NDA, 2000. Nieuwoudt (1998) states the income elasticity of pork is relatively low compared to other red meat products. This entails that when per capita disposable income increases consumers will purchase, in relative terms, more other red meat products, and vice versa. Nieuwoudt (1998) expects that under a 3 per cent growth in the economy and low income scenarios, the demand for pork will increase between 8 and 12 per cent for 2000/2001 with 1995 as basis. Compared to growth in demand for other meats reported in 78 Overview of the South African red meat industry Nieuwoudt's study, this expected increase is relatively low. The reason is that pork is consumed mainly by whites, who under an income growth scenario of 3 per cent will have the lowest increase in per capita income. • The sheep sector South Africa is only able to supply approximately 80 per cent of the local demand for sheep meat. Shortages in the domestic market are supplemented by imports, mostly from Namibia (live animals) and Australia. As with the other red meats, especially beef, sheep meat consumption is highly sensitive to changes in per capita income. Figure 3.6 illustrates the correlation between per capita consumption of sheep meat and the per capita income of people in South Africa. According to Nieuwoudt (1998), the expected increase in the demand for sheep meat under a 3 per cent growth in the economy and low income scenarios could range between 12 and 25 per cent for 2000/2001 with 1995 as basis. 9800 8.00 9600 7.00 9400 6.00 J'S "e0 9200 Q. ca 5.00 rJ 0::: 9000 -Cl 8800 4.00 ~ 8600 3.00 8400 , 2.00 ~~~~~~~~~~o~o~moOo~ooNo~o~o~o~o~oooomooO~oN~~~~~oomo ~m~m~m~m~~m~m~m~~m~mm oooooommmmmmmmmmo ~~~m~m~m~~m~m~m~m~~m~m~m~~mNmmmmmmo Year l--- Per capita disposable income ---+- Per capita consumption of sheep meat I Figure 3.6: Relation between real per capita disposable income and the per capita consumption of sheep meat (1973 - 2000) Source: SARB, 2000; NDA, 2000. 79 Overview of the South African red meat industry • Per capita expenditure on red meat Table 3.1 shows the real per capita expenditure on red meats for 1993 and 1999. The methodology followed to calculate the real per capita expenditure on red meats is similar to that used by Nieuwoudt (1998). Nieuwoudt (1998) used a system of two equations to estimate rural and urban per capita expenditure per population group (see Nieuwoudt 1998 for the methodology used). Expenditure data per population group and per product were obtained from Martins (1994) and Martins (1999). The assumption underlying the calculation of the real per capita expenditure on red meats is that there is . no growth in the size of the rural black population. Table 3.1 shows that real per capita expenditure for beef, pork and sheep meat has declined since 1993. The largest decline in per capita expenditure was experienced by beef, followed by sheep meat and then pork. In terms of the total population per capita, expenditure on beef is still the highest. On a per capita expenditure basis whites spend the most on beef, followed by blacks in urban areas, but it is important to note that the real per capita expenditure by both has declined considerably between 1993 and 1999. In the case of sheep meat, Asians spend the most, followed by whites and then coloureds. Also note the decline in real per capita expenditure by especially whites and Asians. Real per capita expenditure on pork is dominated by whites, followed distantly by the other population groups. Interesting to note is the increase in the per capita expenditure of blacks in rural areas in terms of all three red meats. This could probably be attributed to increases in real income from a very low base. Table 31. .. ReaI per capita expen d"Iture on red meat lIn Sou th Af·rlca Beef Sheep meat Pork Population group Rand per capita (1993 = base period) 1993 1999 1993 1999 1993 1999 ~sians 179.73 115.47 396.20 280.80 17.81 25.14 Blacks (urban) 223.00 136.45 65.48 53.12 18.25 19.95 Blacks (rural) 53.57 71.85 15.73 27.97 4.38 10.51 Coloureds 203.55 105.58 158.19 144.69 33.45 29.23 Whites 540.30 325.34 303.56 245.00 139.91 120.04 !rota I population 187.53 127.38 91.29 77.33 29.35 27.74 80 Overview of the South African red meat industry 3.4 Imports and prices of red meat o The beef sector Beef imports from overseas saw a substantial increase since 1994, averaging more than 40 000 tons annually up to 1998. Since 1998 beef imports have ranged between 15 000 and 20 000 tons annually. The decline in beef imports since 1998 is attributed firstly to the establishment of Agri Inspec, who are responsible for policing agricultural imports from overseas, and secondly due to the sharp drop in EU intervention stocks. One of the biggest problems experienced by the red meat industry was the underinvoicing of imported red meat, incorrect classification of meat by importers and poor inspection of containers. The establishment of Agri Inspec rectified this problem to a large extent. This emphasises the importance of proper policing of imports. Figure 3.7 shows a close relation between domestic prices and imports during the period 1994 to 1998. This trend is still visible after 1998, but to a smaller extent. Imports exert pressure on domestic prices to fall back to lower levels. Another important factor that will have an influence on the competitiveness of domestic producers is the depreciation of the rand. Another issue of importance is that, although the EU was traditionally the major exporter of beef to South Africa, imports from countries such as Uruguay and Argentina may also pose a threat to South African producers. The reason for this is the decline in the exchange rate of these countries against the South African Rand, making it much more profitable for them to export beef to South Africa. 81 Overview of the South African red meat industry 1,000 8000 950 7000 - 900 6000~- -Ol 850 5000~ -g800 4000 ~ Cl) c 0 ';: a, 750 3000 e- 700 2000 650 1000 600 0 I _._ Nominal beef price (Class A) ~ Beef imports from overseas I Figure 3.7: The relation between beef imports and the domestic Class A price (Jan 95 - Dec 00) Source: SAMie, 2000. Figure 3.8 shows the relation between the beef producer price and per capita consumption of beef. It is important to note that the real producer prices and per capita consumption of beef are, too a large degree, mirror images of each other. What is, however, of concern is the general downward trend in both variables shown in Figure 3.8. The reasons for this is, firstly, the pressure on per capita disposable income which render consumers unable to react to more favourable prices, secondly, the beef to poultry price ratio that favours poultry and, thirdly, the influence of non-economic factors such as product consistency and quality, food safety, health and nutrition concerns, and conven ience. 82 Overview of the South African red meat industry 1350 26 1250 24 ra - 1150 22 "-iira-~Cl 1050 20 .C.J.~ 950 18 Q)c.. Q) .C;J: 850 16 E o, ~ 750 14 Cl0 650 12 :i: 550 10 ~O~~~N~~~~~~~~~~~o~oomoOo~N~~mmmmmmmmmmmmmmooo ~o~o~oooooomoOo~No~o~oo~~o~oommommmommmmmmo ~~~~~~~~~~~~~~~~~~~~m~m~~m~m~m~~m~m~m~Nmmmmmmmmo Year 1 Real beef price -+- Per capita consumption of beef 1 Figure 3.8: The relation between the real average auction price of beef and per capita consumption of beef (1970 - 2000) Source: NDA, 2000; Agrimark Trends, 2000. • The pork sector As was stated, pork imports from overseas increased substantially once the deregulation process commenced in 1994. Figure 3.9 shows the relation between domestic pork prices and imports. This serves as a measure of the influence of imported pork on domestic pork prices. It is shown that whenever domestic prices increase, imports tend to increase. This has important implications for domestic pork producers, since any expected increases in domestic pork prices will be dampened by increased imports. A factor that does, however, count in the favour of domestic pork producers is the weak rand, though low international prices may erode this advantage. 83 Overview of the South African red meat industry 1,050 3000 950 2500 -- 850 2000 êCl.li:: -.0...~ 750 1500 ~ u< (I) Sheep cuts, boneless, "0 Bovine edible offal, frozen nes_ .~o... -5 s: Bovine tongues, edible offal, ~ Cl , ,/" Sheep carcasses and half ëU ::l C • C <{ ,_ Poultry, domestic, • whole, fresh or chilled ~ Bubble scale = ~ US$ 10 millions and half carcasses, frozen Annual growth of imports of SACU between 1995-1999, %1 Figure 3.13: Growth of national demand and international supply of meat products to SACU Source: ITC calculations based on COMTRADE statistics, 2000, 89 Overview of the South African red meat industry The left-hand side of the diagonal line can be interpreted in a similar fashion. For example, growth in imports of bovine cuts (fresh or chilled) is growing at a slower rate than world exports of this product, or imports of this product experienced negative growth domestically, whilst the world market experienced positive growth. Figure 3.14 depicts the situation for exports. The interpretation of the data depicted in Figure 3.14 is similar to that of Figure 3.13. Note that Figure 3.14 has been divided into 4 different quadrants. The first quadrant shows the products that can be classified as underachievers in the world market, i.e. international demand (imports) for these products has been growing at above-average rates, whilst exports from SACU have either declined or have grown less dynamically than world trade. This implies that SACU has been losing international market share as far as these products are concerned. Furthermore, the fact that these products are classified as underachievers signals that export opportunities do exist. In order to take advantage of this opportunity the domestic industry needs to identify destination markets, solve problems within the domestic supply chain and become involved in active trade promotion programmes. Each of these factors encompasses a complex set of issues that need to be investigated, but falls beyond the scope of this study. The second quadrant designated for products classified as champions is empty. This state of affairs is alarming as any country should ultimately strive towards concentrating its products in this quadrant. Products referred to as champions are those products of which exports are growing faster than world trade in general, i.e. the country succeeded in outperforming world market growth to such an extent its share in world imports increased. Underachievers have the potential to move to this quadrant provided that the troubling issues mentioned are addressed. Also, this quadrant is seen as a measure of international competitiveness. 90 10 Underachievers cuts, bone In, fresh or chilled Hams, shoulders and cuts ther,f, of swine, • Champions 'if!. ai "<, Bovine edible offal, 2.5 C1I C..1I.;.,. C1I Bovine cuts boneless, fresh or chilled C1I r::: Ol tt 1 I I I I I I' 'I I I I' ~ ..c 0......... chilled- • ~ Bovine livers, ecroteionar, Bovine cuts bone in, frozen oc. Bovine cuts boneless, frozen .E •- Il"C Bovine edible offal, frozen \ Hams, shoulders and cuts thereof, of swine ~ nes bone in, fresh or chilled.o... Lamb carcasses and half -5 s: carcasses, fresh or chilled - Swine carcasses and half carcasses, frozen ~ carcasses and half carcasses, fresh or chilled Ol Swine cuts, frozen 'iii nes Bovine cuts bone In, fresh or chilled ::J r::: Swine cuts, fresh or chilled, nes / e ~ .D "0 Dynamic suppliers under-represented ~ Ol> :E .B Ul t o 0- X United States of America Ol> -Ul Dynamic suppliers-Ocl> speelalleed In the countryc: o::I .o... Ol> 5 c: t 111 0- I I I t I I Growth of total world exports Canada Non-dynamic 8uppllero speclall •• d In the country United Kingdom Ireland Non-dynamie suppliers under-represented Zimbabwe Annual growth of SACUs imports from the partner countries between 1995-1999, % Figure 3.16: Competition between suppliers to SACU for the selected import product in 1999 (Product: 020329 Swine cuts, frozen nes) Source: ITC calculations based on COMTRADE statistics, 2000. 99 Overview of the South African red meat industry Table 3.5 shows exports of selected pork products. The performance in terms of the value exported was mixed. Swine hams, shoulders and cuts thereof (bone in, fresh or chilled) and swine cuts (fresh or chilled, nes) recorded significant growth, 45 per cent and 82 per cent respectively. What makes it even more significant is the fact that the world has experienced negative growth in these two products. As far as the other products are concerned, SACU experienced larger declines in the value exported than the rest of the world. This may be an indication that SACU has been targeting the wrong markets, but conversely it may also indicate that SACU is more price competitive on a unit-value basis than most other countries and could secure niche markets provided that export promotion is directed as such and the supply chain allows for it. Table 35. .Expo rtsto se ltedc e swme pro ductst rom SACU Product Value Quantity Unit Annual growth in value Annual growth in value HS 1999 in 1999 value between 1995-1999, % of world imports rev. US$ (ton) between 1995-1999, thousand % Swine carcasses and 20311 half carcasses, fresh or 71 198 0.4 -12 -11 chilled Hams, shoulders and 20312 cuts thereof, of swine 41 6 6.8 45 -3 bone in fresh or chilled 20319 Swine cuts, fresh orchilled nes 651 1261 0.5 82 -7 20321 Swine carcasses and half carcasses frozen 383 363 1.1 Na -5 Hams, shoulders and 20322 cuts thereof, of swine, 60 23 2.6 -16 4 [bone in frozen 20329 Swine cuts frozen nes 1481 934 1.6 -26 -7 Source: ITC calculations based on COMTRADE statistics, 2000. • Sheep meat trade Table 3.6 shows the imports of selected sheep meat products. On average SACU has seen considerable growth in imports of sheep meat products. The largest growth was recorded by sheep cuts (bone in, frozen), with an increase in value and quantity imported of 23 per cent and 53 per cent, respectively. This growth was fuelled by increases in imports from both Australia and New Zealand, with the latter increasing its 100 Overview of the South African red meat industry exports to SACU by 129 per cent from 1995 to 1999. Australia, however, remains the largest import origin for this product, with a SACU market share of 90.19 per cent. New Zealand has a market share of only 9.04 per cent, but given its export growth to SACU one could expect this share to increase over time. Table 36 . Impo rts of sehep mea t pro ductsf rom overseas HS rev. Product Value 1999 Quantity Unit Annual growth Annual growth Annual growth in US$ 1999 value in value in quantity in value of thousand between 1995- between 1995- world exports 1999, % 1999, % between 1995- 1999 % 20422 ~heep cuts, bone in,fresh or chilled 62 91 0.7 -22 -16 13 Lamb carcasses and 20430 half carcasses, 287 564 0.5 -12 13 -18 rozen Sheep carcasses 20441 and half carcasses, 624 1449 0.4 -36 -21 -9 rozen 20442 Sheep cuts, bone in,rozen 14958 35106 0.4 23 53 2 20443 Sheep cuts,boneless frozen 922 1633 0.6 3 17 -4 Source: ITC calculations based on COMTRADE statistics, 2000. Table 3.7 shows the exports of sheep meat products by SACU. It is clear that SACU exported very small quantities of sheep meat products in 1999. The value of sheep meat products exported showed a decline from 1995 to 1999, with the exception of sheep cuts (bone in, fresh or chilled), which remained constant. Of some concern may be the fact that sheep cuts (bone in, frozen) show a drop in the value of exports, whilst the world in general experienced positive growth. It may indicate that opportunities exist, but have not been exploited to their potential. The same can be said with respect to sheep cuts (bone in, fresh or chilled). The other side of the coin, however, is that export prices of SACU cuts may have been forced to become more in line with that in the world market. 101 Overview of the South African red meat industry Table 37. Expo rtsto seIectdehseep productst rom SACU Product Value 1999 Quantity Unit Annual growth in value Annual growth in value HS in US$ 1999 value between 1995-1999, % of world imports rev. thousand between 1995-1999, % Lamb carcasses and 20410 half carcasses, fresh 10 2 5.0 -9 -5 brchilled 20422 pheep cuts, bone in,fresh or chilled 39 14 2.8 0 10 ~heep carcasses 20441 and half carcasses, 24 11 2.2 Na -9 rozen 20442 Sheep cuts, bone in,rozen 226 48 4.7 -5 2 Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. The latter is probably also true regarding sheep cuts (bone in, frozen), since the calculated unit value of world exports is US$1.83 per kg whilst the unit value for SACU exports of this product amounts to US$4.70 per kg (the unit value for world imports of this product in 1999 was US$1.98 per kg). With respect to sheep cuts (bone in, fresh or chilled) the world export price amounts to US$3.59 per kg, whilst the SACU price is US$2.8 per kg (the unit value for world imports of this product in 1999 was US$5 per kg). Hence the former argument that opportunities on the world market have not been fully exploited probably applies for this product. Nevertheless, one should take into account that SACU is a net importer of sheep meat products. One could argue that SACU should increase exports of those products for which the returns on the world market is better than on the domestic market, and import lower-priced shortages. For instance, SACU exported sheep cuts (bone in, fresh or chilled) at a unit value of US$2.8 per kg, while the import price for the same product was US$0.4 per kg. The fact of the matter is, however, that to exploit such opportunities fully, exporters have to take account of the following: The needs and preferences of consumers in other markets; 102 Overview of the South African red meat industry quality of the exported product; continuity of supply; proper supply chain functioning; and regulations pertaining to health, food safety and trade. The above factors are by no means the only factors that need to be accounted for, but they surely encompass some of the most important issues. Furthermore, these factors can't be isolated from each other, i.e. they are inter-related. For example, suppose that a product adheres to quality standards and regulations and is price competitive, but there is supply chain and continuity problems. It would be remarkable if such a product can be exported successfully according to its full potential. Furthermore, successful exports are as much the responsibility of a particular industry/individual/company as it is the responsibility of government. 3.4 Conclusion It is quite clear from this chapter that the red meat industry in South Africa has undergone some drastic economic and structural changes in recent years. It is also clear that much remains to be done. It was shown that there are definite export opportunities to exploit, but that this would entail some adjustments in the red meat supply chain. In this regard one only has to mention the fact that although a large number of animals is kept by the non-commercial sector, they contribute very little to output. This state of affairs needs urgent attention. For example, this sector can contribute significantly to improved continuity of red meat which is currently a problem as far as exports are concerned. One could also argue that it would contribute to greater price stability; a luxury in "free" market system. One might ask why so much emphasis is placed on the international market and opportunities that exist for exports. The answer to this a question is quite simple. Being able to export and to increase one's market share internationally implicitly also relates to one's competitiveness. This in turn means that concerns about imports from other 103 Overview of the South African red meat industry countries could receive less prominence and the industry could use scare human and capital resources to serve the industry more efficiently. Such a task cannot, however, not be accomplished by the industry itself. The active involvement of government is of the utmost importance. This entails that government should actively pursue issues that relate to disease prevention (not control), animal welfare, traceability, stock theft and trade. Finally, it would appear that new role players are targeting the South African market as export destination. In this regard Uruguay is most prominent in the beef market since it has not only increased exports to South Africa, but has shown considerable export growth internationally. Cognisance should also be taken of countries that are not yet prominent on the South African red meat market, but that have shown export growth on the international market. In this regard Australia, in terms of beef, and the US, in terms of pork, are important role players. 104 CHAPTER4 DEVELOPMENT OF A SPATIAL PARTIAL EQUILIBRIUM MODEllFOR THE SOUTH AFRICAN RED MEAT INDUSTRY 4.1 Introduction In this chapter a spatial partial equilibrium model is developed to measure the impact of trade-related issues and demand and supply shift factors on the South African red meat industry. The model considers the effects of different tariff regimes, changes in the exchange rate, population and per capita income, as well as supply shocks on prices, consumption, production and the optimal flow of red meat products between different regions. The method of approximation and procedure is based largely on that followed by Takayama and Judge (1971) in their approximation of mathematical programming models applicable to the analysis of spatial price and allocation problems. The first part of this chapter will provide justification for the modelling approach used, and it will be followed by a discussion on selected models currently being used internationally. This is followed by a discussion on the product specification, regional delineation and data used to develop the model. The latter part of this chapter will be used to develop a quasi- welfare maximisation model. 4.2 Justification of the mathematical programming approach to trade modelling During the last century mathematical programming methods pertaining to specifically equilibrium analysis was embedded firmly in agricultural sciences. Methodological advances in this field were enormous. According to Takayama and Judge, (1971) there were several pioneers in the field of developing a modelling framework where production and allocation of commodities is permitted, e.g. Koopmans (1949 and 1951), Dantzig (1951), Enke (1951), Samuelson (1952), McKenzie (1954), Marschak (1955), Judge (1965) and others. The work concluded by these pioneers, whether directly or 105 Development of a spatial partial equilibrium model for the South African red meat industry indirectly, is still in use today. Models were improved by applying more of the economic theory, as well as institutional and economic reality. The modelling of consumer demand, market equilibrium in both product and factor markets, risk and risk aversion, and the role of instruments of economic policy, received much attention and substantial advances were made in these areas. The ability to model decisions of the farming household also improved (HazeIl and Norton, 1986). According to Hazell and Norton (1986), the cumulative effect of these advances has been to provide a tool of analysis that is much more adaptable to different situations and it presents a potentially more realistic portrayal of agricultural reality. The question might, however, rightfully be asked why mathematics should be used as vehicle to derive answers sometimes quite obvious to observers in the field of 'economics. In this regard it should be remembered that mathematical economics is merely an approach to economic analysis. Chiang (1984) supports this by stating that it should not, and does not differ from the non-mathematical approach to economic analysis in any fundamental way. He goes further by stating that the major difference between "mathematical economics" and "literary economics" lies principally in the fact that, in the former, the assumptions and conclusions are stated in mathematical symbols rather than words, and in equations rather than sentences. The main advantages for going beyond the geometric approach of economic modelling lie in the' following (Chiang, 1984): • The "language" used in the mathematical approach is more concise and precise. • There exists a wealth of mathematical theorems. • Mathematical programming forces the analyst to state explicitly all assumptions as a prerequisite to the use of the mathematical theorems. • Mathematical programming allows the analyst to treat the general n-variable case. 106 Development of a spatial partial equilibrium model for the South African red meat industry Given the above, observers of research in this field could rightfully ask why the analyst uses mathematical programming instead of econometrics. Chiang (1984) states that the latter refers almost exclusively to the study of empirical data by statistical methods of estimation and hypothesis testing, whereas the application of mathematics to the purely theoretical aspects of economic analysis has come to be referred to as mathematical economics. He concludes that econometrics and mathematical economics are coordinate terms instead of being subordinate to each other. Arfini and Paris (1995) are of the opinion that econometric analysis, powerful as it might be, is impractical in dealing with agricultural development issues, since adequate data are extremely difficult to obtain. In most cases the agricultural scenario is indeed quite fragmentary, being made up of a productive and organisational pattern that is typical of, .and heavily affects the farmers' environment, in addition to leading to oversimplifications that make it virtually impossible for the models to thoroughly and comprehensively interpret the existing phenomena. According to them a sound alternative to econometric analysis is provided by mathematical programming which, while requiring a limited amount of information, can nevertheless handle the analysis of economic issues through a two-stage approach, namely estimate (or calibration) and forecasting. The normative character of mathematical programming has often been the reason for criticism directed at this way of conducting economic analysis, which is in sharp contrast to the positive nature of econometric models. Arfini and Paris (1995) reply to this criticism is that if the degree of specialisation associated with the optimisation of a goal does make LP models normative in character, it is equally true that mathematical programming is not designed solely to solve maximisation and minimisation problems. For instance, no normative qualification can be applied to models intended to identify equilibrium conditions. McCarl and Spreen (2000) mention that mathematical programming analysis generally has a comparative advantage of the problem, and not in algorithm development procedures. Consequently, the problem analyst should be thoroughly informed on the 107 Development of a spatial partial equilibrium model for the South African red meat industry topics of the problem formulation, results interpretation and model use, but in large part can treat the solution processes as a "black box". Another issue of which cognisance should be taken is that in the field of economic research one often hears that economic models do not portray reality, or that it is an unrealistic representation of reality. Sydsaeter and Hammond (1995) mention that one would, for example, never be able to consider all the factors that influence such a complex phenomenon as inflation since the outcome would be a hopelessly complicated theory. A model that intends to explain a phenomenon like inflation is at best only an approximate representation of reality (Sydseater and Hammond, 1995). Chiang (1984) goes further, and states that the epithet "unrealistic" cannot be used in criticising economic theory in general, whether or not the approach is mathematical. According to Sydseater and Hammond (1995) theory is, by its very nature, an abstraction from the real world, since it is a device for singling out only the most essential factors and relationships so that we can study the crux of the problem at hand, free from the many complications that exist in the actual world. Finally, Hazell and Norton (1986) state that models provide the link between economic theory and data, on the one hand, and practical appreciations of problems and policy orientations, on the other. Models are imperfect abstractions, but by virtue of their logical consistent framework they provide the analyst and policy-maker with valuable economic representations of the real world and a laboratory for testing ideas and policy proposals (HazeIl and Norton, 1986). When modelling trade policy, one should therefore try to develop a reasonable, though stylised representation of complex policy, demand, and production relationships (Francious, 1999). The trade-off is between keeping the model workable, and keeping it realistic enough to actually be useful. Given the aforementioned discussion it should be clear that the analyst is to decide which tool is most suitable for the problem to be researched, and would provide answers that are realistic and easy to interpret. The decision regarding the most suitable tool is also influenced by issues relating to the availability of data, the sultabllity of data and the underlying assumptions to be used. Hence, given that this study 108 Development of a spatial partial equilibrium model for the South African red meat industry endeavours to investigate the implications of trade liberalisation on the red meat industry that could provide information on trade flows and price changes on a regional basis, and that data on transport costs, demand and supply on a regional basis are available, the mathematical programming approach to economic analysis was deemed most appropriate. Developing a mathematical programming model also allows for investigating broader issues than merely those relating too trade liberalisation, for example the impact of population growth and income changes. 4.2.1 The scope of equilibrium trade models According to Francious (1999), when building computational trade models, decisions have to be made whether to work in partial or general equilibrium, working with a single or multi-country model, and/or working with a single or multi-product model. Although partial equilibrium models have known limitations, for example it suppresses interactions between commodities that are actually linked together by substitution and competition (Houck, 1992), they offer some unbeatable advantages. Partial equilibrium models, by definition, do not take into account many of the factors emphasised in general equilibrium theory, but by focussing on a very limited set of factors, such as few price and policy variables and limited sectoral linkages, applied partial equilibrium models allow for a relatively rapid and transparent analysis of a wide range of policy issues. According to Houck (1992) most real-world policy interventions are targeted at specific commodity problems, and hence partial equilibrium analysis is the most useful approach to assessing direct and immediate economic impacts even though one should not ignore the broader and more diffuse results of policy decisions. In many cases it may be difficult to justify devoting otherwise scarce resources to more complex and less transparent models, when they may yield only marginal extensions of the basic insights drawn from simpler approaches (Francious, 1999). There are, however, questions for which answers can only be provided by larger multi- sector models. These are generally known as Computational General Equilibrium 109 Development of a spatial partial equilibrium model for the South African red meat industry (CGE) models, and capture linkages between different sectors in an economy by modelling firm's use of factors and intermediate inputs. CGE models, for example, allows for explicit assessment of many liberalisation commitments and their welfare impacts simultaneously. It is thus understandable that Hertel (1993) found sizable discrepancies between the results derived from SPE and CGE models used to predict the changes in the global pattern of food sales due to reform of the Common Agricultural Policy (CAP). Hertel (1993) also mentions that it is the "accounting", as opposed to behavioural equations in an applied general equilibrium model, that provides its general equilibrium nature. Francious (1999) states that the complexity of CGE models, combined with their data requirements, limits their applicability. In this regard, the aggregation problem is of special concern since, by necessity, sectors and regions are left out of CGE assessments by a data construction process that buries them in aggregates. It is important to note that the data focus of a particular model can bias the results. For example, an aggregated structure may prove to be useful for assessing the impact of liberalisation on an economy or even different sectors in an economy, but is much less useful when assessing the effect of liberalisation on specific industries at a disaggregated level (Francious, 1999). Furthermore, Hertel (1993) is of the opinion that a general equilibrium framework should not preclude selective partial equilibrium analysis since many problems are best addressed in the partial equilibrium framework. It is thus clear that both SPE and CGE models have their own special place when it comes to modelling trade and policy reform issues. The choice of a modelling framework should be influenced by the specific problem at hand, the answers that are needed, the availability of data, the time required to derive answers, the sector or regional focus of the model and the representation of trade. For instance, the policy questions at hand (like the impact on a particular country or sector) are likely to guide the focus of particular modelling efforts. Francious (1999) states that the regional and sectoral structure of the model determines which effects are caught by the model. He uses the following illustration: the aggregation structure can 110 Development of a spatial partial equilibrium model for the South African red meat industry be compared to maskevidden (the Norwegian word for the weave of a fish net). In casting a narrow-meshed net on agricultural products and a wide-meshed net on industry, one can expect to catch the agricultural effects but miss the industrial effects, and vice versa. Computer software, data, and time constraints, along with the disadvantages of overly complex models (which tend to become "black boxes"), simply prohibit one from casting a fine-meshed net everywhere. Another important aspect of model structure that follows from the specification of competition between imports and domestic goods relates to the modelling of trade flows as net or gross flows. Homogeneous goods models are consistent with basic trade theory, and are also consistent with the assumption that primary agricultural goods are commodities. However, this assumption is also inconsistent with the reality of two-way trade within product categories. The way in which this is handled theoretically can affect the qualitative nature of modelling results (Francious, 1999). He mentions that the Armington approach explains two-way trade by assuming that products within the same product category, but originating in different nations, are imperfect substitutes (the so-called "Armington" assumption). Models with Armington specifications yield smaller trade and output effects than models with homogeneous goods. The implied adjustment costs of trade liberalisation are hence much greater in homogenous goods models than in Armington models (Francious, 1999). The Armington approach to trade modelling is obviously superior than homogeneous goods models, as it allows for endogenously determined two-way trade that will provide the policymaker or producer with product specific information. However, cognisance should be taken of the fact that the Armington approach also requires more specific information that relates to the substitutability of different products. Hence, in cases where such information is not available or could not be estimated due to time and cost limitations, the homogeneous goods models are the next-best alternative. 111 Development of a spatial partial equilibrium model for the South African red meat industry 4.2.2 The nature of spatial equilibrium models Krishnaiah (1995) states that a spatial model is a theoretical construction having space as one of its components. Spatial equilibrium models characterise several economic activities: the regional locations of production, the regional levels of consumption and the relative level of prices, as well as the formulation of the equilibrium situation pertaining to a particular sector or economy. In a sector or economy where demands, supplies and transport costs are known for each geographical area, the model could be used to determine the optimum set of prices and geographical flows. Given two or more locations, the demand and supply functions for a given product in terms of its market price at that location, and unit transport costs for carrying the product between these regions, spatial equilibrium models provide competitive equilibrium prices in each location, and the level of imports and exports. These models include formulations commonly called activity analysis models, inter-regional competition models, transportation models, spatial equilibrium models, plant location models and simulation models (Krishnaiah, 1995). More specifically, Krishnaiah (1995) states that equilibrium models reflect specifications that permit economic forces over sectors and space to act in unison to determine the optimum price and allocation outcomes. A great variety of situations can be handled by these specifications. In an economy where demands, supplies, and transport costs are known for each geographical area, the spatial equilibrium model could be used to determine the optimum set of geographical flows and prices. Alternatively, if the prices and the demands for the final commodities are assumed known, along with the primary commodity endowments, technical conditions of production, and transport costs for each geographical area, the spatial equilibrium model could be used to determine the competitive spatial price and allocation scheme. Factors such as trade agreements, import tariffs, export subsidies, import quotas, or ad valorem tariffs can be handled in spatial equilibrium models by introducing additional restrictions or modifying the data used. In addition, the gains to society through inter-regional trade, such as producers' 112 Development of a spatial partial equilibrium model for the South African red meat industry and consumers' surplus, can be effectively assessed through partial equilibrium models (Krishnaiah, 1995). The general principles involved in developing inter-regional trade models can be illustrated with the aid of diagrams (geometric approach) showing aggregate supply and demand functions for two regions and one homogeneous product (see Figure 4.1). Consider a situation where a state of autarky exists, i.e. there is no trade between the two regions. If this is the case-demand and supply in Region A will be in equilibrium at point 9, whilst demand and supply in Region B will be in equilibrium at point h. Suppose the state of autarky is relaxed, i.e. there are no barriers to trade between the two regions, and that the international price Pi is available to both sellers and buyers, and is higher than the price in Region A and lower than the price in Region B. Since the international price is higher in Region A, production will be stimulated since producers would wish to take advantage of this situation (point b), i.e. they will divert their supplies to the market where they receive better prices. Conversely, consumers in Region A will demand less of the product (point a) since lower supply in the domestic market will result in higher prices. The result is that Region A will become an exporter of the product concerned. This tendency to export when international prices are above domestic prices is depicted by the excess supply curve, in this case the function ESA shown on the right-hand side of the vertical price line of the graph in the centre in Figure 4.1. Note that should the international price be equal to the domestic price, there will be no excess supply (point 9 = point k). The situation for Region B is different from that of Region A. The international price Pi is lower than the domestic price, resulting in consumers in Region B demanding more of the particular product (point f), whilst producers in Region B would reduce production at this price level (point e). The net effect is a shortage of the product in Region B. This situation is depicted by the excess demand curve (EOs). Where the international price is equal to the domestic price, excess demand will be zero, i.e. where point i is equal to point h. Note that ab represents exports from Region A and ef represents imports to Region B, where ab=ef=cd. Another feature of Figure 4.1 is that trade expands to a level where prices 113 Development of a spatial partial equilibrium model for the South African red meat industry are equalised in both regions. The assumption underlying this is that transportation and other transfer costs are ignored. Region A Region B p p p X -------- ~------------------ g 0A °imports-A o °exports-A °exports-B °imports-B Figure 4.1: A geometrical diagram representing a two region-trading regime Source: Houck, 1992. The gains from trade resulting from the shifts in the initial equilibrium situation are also depicted in Figure 4.1. A rise in prices in Region A will result in producers gaining areas X + Y, but consumers on the other hand will lose area X. On the other hand, consumers in Region B will benefit areas Z and V, but producers will lose area Z. The sum of areas Y and V is defined as the net social payoff or net welfare. The objective of spatial equilibrium modelling is to maximise these surpluses. As mentioned before, the influence of transportation and other transfer costs are ignored in Figure 4.1. However, in reality, account should be taken of these costs. Figure 4.2 depicts a situation where transfer costs are taken into account when two regions trade with each other. Transfer costs are depicted by mn in Figure 4.2. This entails that the domestic prices in Regions A and B in equilibrium will differ by this amount. Note that in Figure 4.1 the prices were the same in both regions, whereas the situation with transfer cost results in 114 Development of a spatial partial equilibrium model for the South African red meat industry a lower price in Region A (PA) and a higher price in Region B (Pe). The price differential is equal to mn (PA + mn = Pe). Equilibrium in a situation where transfer costs play a role is located at that point (trade volume) where the difference in the price between two regions is exactly equal to the price differential. In Figure 4.2 this is equal to Oq1. Also note that should the situation arise where the transfer costs are equal or greater than gh, no trade will take place between the two regions. o Qimports-A Qexports-A Qexports-B Qimports-B Figure 4.2: The influence of transfer cost on regional pricing Source: Houck, 1992. 4.2.3 Selected world trade models This section focuses on partial equilibrium modelling efforts undertaken internationally. Only a few of the most prominent models used are highlighted by referring to their basic aims, general characteristics, the regions and commodities they cover, as well as their strengths and weaknesses. It should be understood that there are many more equilibrium modelling efforts in development or currently being used than the models cited below. Not all of them are within the partial equilibrium framework. Probably the 115 Development of a spatial partial equilibrium model for the South African red meat industry best known of these models are the CGE GTAP model and the econometrically based FAPRI model. • World Food Model According to the FAO (1998a), the World Food Model (WFM) is an interactive, dynamic, price equilibrium multi-commodity trade model. It is interactive in that it allows for the simultaneous determination of supply, demand, trade, stock levels and prices for all the commodities covered. The dynamic nature of the model stems from the fact that it allows for the outcome of one year or a sequence of years to influence the outcome of future years. According to Von Lampe (1999) this enables the model to capture the adjustment paths of the market after the introduction of certain shocks. It is a price equilibrium model, as all commodity prices are determined at the level where world supply is equal to world demand and all variables are determined simultaneously. Although sources and destinations of trade flows are not identified by the WFM, it is solved for world market clearing prices by equating the sum of gross imports and the sum of gross exports (FAO, 1998a). In principle, the WFM was not designed to simulate policy, but rather concentrated on making projections of the world food situation. However, modifications were made to the WFM to simulate the impact of trade liberalisation scenarios, more specifically the impact of the Uruguay Round commitments (FAO, 1998a, De Nigris, 1999). It covers only measurable Uruguay Round commitments that encompass bound tariffs and their reductions, minimum access and limits on subsidised exports. It is furthermore important to note that the WFM is basically a determinist model, i.e. it does not contain stochastic elements. In essence, the approach followed aims to examine the impact of production shocks on world price stability in order to verify if tariffication and reduction of tariffs have the expected effect (De Nigris, 1999). The WFM includes 13 food commodities, i.e. five cereals, four meat markets, one each for milk, butter, oilseeds and fats, and oil meals. Table 4.1 shows the commodity coverage of the WFM. 116 Development of a spatial partial equilibrium model for the South African red meat industry Table 41 . Produc t coverage blY the WFM Product DescriDtion Wheat Wheat in primary product equivalent Maize Maize in primary product equivalent Sorghum and millet Serahum and millet in primary product equivalent Coarse grains others Coarse qrains nes in primary product equivalent Rice Rice in milled rice equivalent Bovine meat Bovine meat measured in carcass weiaht Pig meat Pia meat measured in carcass weiaht Sheep/coat meat Meat from sheep and coats measured in carcass weiaht Poultry meat Poultrv meat measured in carcass weiaht Milk Milk in primary product weiaht Butter Butter Oilseeds and fats Oilseeds and fats measured in oil equivalent Oilmeals Oilmeals cakes measured in oreduet weloht Source: FAO, 1998a. The model covers 146 countries or country groups. The 15 member countries of the EU are grouped together (the EU15 group). Developing countries are covered in detail, with 112 countries and country groups defined. The disaggregation of the countries in transition is also fairly detailed - with 23 countries and groups representing Eastern Europe and the former USSR. The current version of the WFM is used to project to the year 2005, the model uses 1993-95 as the base period. Lagged data are also needed as some equations contain 2-period lagged variables. In order to smooth the base data itself, and thus avoid unusual movements during the early years of the projections, the model uses three-year averages for each year of the base period, i.e. 1991-1993 average for 1992,1992-1994 average for 1993 and 1993-1995 average for 1994. Thus, model solutions are assumed to reflect the average or normal situation. Intra-trade is excluded for the EU15 (FAO, 1998a) Due to the unavailability of domestic producer and consumer prices for all the countries/commodities covered, prices are normalised by setting the base year prices equal to unity. It is also not possible to account explicitly for domestic price wedges between border, producer and consumer levels. Elasticities and parameters used in the equations are mainly from estimates made by the Food and Agricultural Organisation 117 Development of a spatial partial equilibrium model for the South African red meat industry (FAO), supplemented by the elasticity data bases of the United States Department of Agriculture's (USDA) SWOPSIM model and the Organisation for Economic Cooperation and Development's (OECD) MTM model (De Nigris, 1999). These parameters are held constant when projections are made with the WFM. • AGLlNK model The AGLlNK model that was developed by the OECD in close co-operation with OECD member countries is basically a dynamic supply-demand model of world agriculture. The main focus of the model is to provide information on the potential influence of agricultural policy on agricultural markets in the medium term. One of the main strengths of the AGLlNK model is that the model structure closely represents the agricultural situation in member countries. Hence, it has the ability to capture interaction between commodities and between countries since it not only provides indications of directional flows/impact, but also information on the magnitude of these impacts (OECD, 1998). More specifically, the following key factors or assumptions are embedded in the AGLlNK model (OECD, 1998a): World markets for agricultural commodities are competitive, i.e. buyers and sellers do not behave as if they have market power. Market prices are also determined through global supply and demand. Domestically produced and traded commodities are viewed to be perfect substitutes by buyers and sellers. Importers do also not distinguish commodities by country of origin. The model is partial equilibrium in nature and includes major OECD agricultural commodity markets with respect to supply, demand and prices. The products included are wheat, coarse grains, oilseeds, oilseed meals and oils, dairy 118 Development of a spatial partial equilibrium model for the South African red meat industry products, milk, meats and eggs. As far as non-agricultural markets are concerned, they are treated exogenously and feedback to the macro-economy is not accounted for. This may be considered as a weakness of the model with respect to countries where agriculture plays a significant part of the domestic economy. Rice, sheep meat, fish and wool are either not modelled, at all or incompletely modelled which may affect the interpretation of model properties. The model consists of complete modules for seven OECD countries/regions. That is Australia, Canada, EU15, Japan, Mexico, New Zealand and the US. The model also takes account of one non-OECD country, namely Argentina, and also one non-OECD region, namely the Rest of the World. The scope and nature of the linkages between OECD and non-OECD modules depends on the specific commodity. For example, in the case of cereals, oilseeds and dairy products the non-OECD regions interact separately with OECD-7 countries. However when it comes to beef and pork, markets are segmented, e.g. beef is segmented into the foot and mouth disease free areas, the Mercosur countries and the EU, whereas beef is not included in the Rest of the World component. Market determination of equilibrium prices for most commodities is simulated. This entails that prices on markets must adjust to equate total demand exactly, including carry-over, to total supply, including carry-in based on specific reference prices. The functional relationships linking supply and demand to prices are in most cases linear in the logarithms of the variables, and the equation coefficients used are partial elasticities. Von Lampe (1999) states that a major shortcoming of the AGLlNK model is its inflexibility and inability to differentiate current regional aggregates embedded in the model further, namely the rest of the OECD and the Rest of the World. He states that in aggregating important developing countries such as China, India and the African Rim 119 Development of a spatial partial equilibrium model for the South African red meat industry within a single region makes it difficult to reflect the impact of the considerable changes in those regions on the world market. Another shortcoming is the absence of important food crops in many southern hemisphere countries and in Asia, since the substitution of these products in favour of higher-quality food cannot be modelled. • The Country-link System The Country-Link System (ClS) of the Economic Research Service (ERS) of the USDA is used to conduct global supply, demand and trade projections in general, whilst different scenarios, such as the Asian crisis, could also be modelled. It also allows for individual country analyses. It is a decentralised system that is linked to expertise based in different regions. Regional models are then linked to each other to form a complete system capable of simultaneous multi-commodity, multi-region solutions within the partial equilibrium framework over the medium and long term. Another distinguishing feature of the ClS is that it has the capability to analyse bilateral trade flows with the Armington facility (landes, 1998). The ClS covers wheat, rice, corn, barley, sorghum, other coarse grains, beef and veal, pork, poultry, eggs, soybeans, rapeseed, sunflower seed, other seeds, cotton and sugar. The countries and regions covered are shown in Table 4.2. The major strengths of the ClS can be summarised as follows: Established linkages to regional and commodity expertise exist, supported by an appropriate software interface, since analysts in different countries do not use the same software for model construction. The country and commodity coverage is broad. It exhibits multi-commodity and multi-region consistency through a simultaneous solution framework. 120 Development of a spatial partial equilibrium model for the South African red meat industry The model can be adapted with relative speed as far as "non-model" approaches are concerned. Table 42 . Reglona coverage 0fth e els Regions Countries Australia Bangladesh New Zealand China Other Asia Hong Kong Pakistan Asia and Oceania India Philippines Indonesia South Korea Japan Taiwan Malaysia Thailand Mvanmar_(RI) Vietnam Argentina Caribbean Western Hemisphere Brazil MexicoCanada Other South America Central America United States Algeria Egypt Sub-Saharan Africa Africa and Middle East Iran South Africa Iraq Tunisia Morocco Turkey Saudi Arabia West Africa-10 (CT) Czech Republic Other Western Europe EU-15 Poland Europe Hungary Russia Other Central Europe Slovak Republic Other FSU Ukraine Source: Landes, 1998. The elS, however, also has some weaknesses, namely: The non-standardised modelling formats slows the process of linking models and theoretical consistency cannot always be enforced in all models. A lack of regional expertise exists in some areas, whilst some models are also poorly maintained. Some key areas are not modelled endogenously. It is not suitable for short-term forecasting. 121 Development of a spatial partial equilibrium model for the South African red meat industry According to Van lampe (1999) the Country-Link system, in addition to including several policy measures such as tariffs, quotas, etc., also considers a number of other exogenous variables, i.e. changes in population, income and exchange rates, etc. He also regards the absence of a number of products, such as pulses and various starchy products that are particularly important for developing countries, as a minor disadvantage of the ClS. • World Agricultural Trade Simulation Model Few of the models that have been developed to project agricultural world market developments due to changes caused by, for example, the Uruguay Round and CAP reforms, are suitable for calculations beyond six to ten years, whilst those models that are capable of longer-term projections lack the ability to reflect the political environment for these market developments properly. The World Agricultural Trade Simulation Model (WATSIM) developed at the University of Bonn in 1999 attempts to fill this gap (Von lampe, 1999). According to Von lampe (1999) the WATSIM includes a broad set of policy measures that influence domestic and world markets by altering price, production, demand and trade quantities. The model focuses mainly on those key factors that will influence supply and demand prospects, for example, socio-economic and natural variables that have a direct impact on supply and demand, urbanisation, changes in real per capita income, etc. The main characteristics of the WATSIM model are as follows (Van lampe, 1999): It is partial equilibrium in nature. In other words, the WATSIM does not account endogenously for the linkages between other sectors and the agricultural sector, nor does it account for the interrelationship with macro- economic conditions. Information and data on the macro-economic environment are, however, introduced exogenously. 122 Development of a spatial partial equilibrium model for the South African red meat industry It is multi-regional with multi-products. The multi-regional with multi-product approach entails that the interaction between different regions and different products are captured simultaneously if different scenarios are modelled. The model comprises 15 regions and regional aggregates. Table 4.3 shows the products included. The WATSIM model distinguishes between 29 products and 3 product groups. Table 43 .. Products and pro duc t arOUDSmc Iuded' In th e WATSIM Products Wheat Other vegetable oils Barley Soybean cake Corn Other cereals Sunflower cakeRape cake Rice Starchy products Other oil cakesBeef and veal Sugar Pig meat Pulses Other meat Soybeans Sunflower seed PoultryEggs Rape seed Milk Other oilseeds Cheese Soybean oil Butter and cream Sunflower oil Skimmed milk products Raoe oil Product arcuns Fruits Other crops for technical use, e.g. tobacco, Vegetables rubber and fibre croos Source: Von Lampe, 1999. It is deterministic in nature. In other words, uncertainty and risk associated with, for example variability in weather conditions, are not accounted for. Average conditions are assumed for particular target years. Endogenous changes in stock levels are furthermore only accounted for when stock levels react to politically determined prices and when limited export possibilities exist. Private stocks are assumed to be zero but could be included exogenously. It is non-spatial. The WATSIM model does not account for trade flows or bilateral exchanges of products, whilst traded commodities are assumed perfect substitutes in that no differentiation can be made between the imports and exports of a region's foreign trade regime. 123 Development of a spatial partial equilibrium model for the South African red meat industry It is synthetic. The behavioural parameters, i.e. income elasticities and price elasticities of demand and supply are not estimated endogenously in the model, but are sourced from literature and other models. Use of supply and demand shift factors. Demand and supply shift factors entail those natural and macroeconomic variables that could influence demand and supply, and hence prices over the long terms for example growth in population and changes in per capita income. The WATSIM model does, however, also have some weaknesses. Firstly, due do the lack of data on agricultural policies in many developing countries, changes in policies of these countries cannot be simulated, and hence it is assumed that price incentives from the world market to domestic producers in such countries are transmitted fully. Secondly, issues such as market access commitments and import tariffs applicable to net-exporting regions are not properly represented in the model. Thirdly, although not a weakness, but rather an area for refinement, is the fact that some statistics, such as the impact of urbanisation on consumption patterns, were assumed to be the same in regions where such information does not exist (Von Lampe, 1999). According to Henriehsmeyer, Von Lampe, and Moellmann (2001) further improvements have been made to the WATSIM model since 1999. The WATSIM model now incorporates gross imports and exports by making use of a modified Armington approach, whilst it also addresses the issue of tariff rate quotas and limits on subsidised exports. • The USDA WTO project The SWOPSIM model is possibly the best known partial equilibrium model developed by the Economic Research Service (ERS) of the USDA. This model is spreadsheet based, using medium-term elasticities to analyse world agricultural market development using PSE's and CSE's. The ERS also endeavoured to develop country-specific 124 Development of a spatial partial equilibrium model for the South African red meat industry spreadsheet-based models using specific policy instruments for simulation purposes. However, in light of the new developments as far as liberalisation and the WTO are concerned, the ERS started to design a new modelling framework with the aim of analysing trade liberalisation options under the new WTO negotiations (ERS, 1999). It is a non-spatial partial equilibrium model that is policy specific, e.g. tariff rate quotas (TRQ's) and subsidies are some of the policy parameters embedded in the new model. It uses both long and short-term elasticities and assumes that goods are largely homogeneous. The model is built around three different market levels, namely (ERS, 1999): Single-market level: The single-market level entails trade in raw products that includes demand for food, demand for feed and other products, inventory demand, area planted and supply, as well as price equations. Products falling into this category are corn, other coarse grains, rice, sugar, high fructose corn sweetener, tropical oils and wheat. Trade in processed products pertaining to meat is also modelled at single-market level and entails demand, animal inventory, supply and price equations. Meat products in this category include beef and veal, pork and poultry. Two-market levels: The two-market level involves both raw and processed products, with the emphasis on oilseeds, and entails demand for oil and meal, seed area and production, crushing and price equations. Products in this category are soybeans, soybean oil, soybean meal, other oilseeds, other oilseed oil and other oilseed meal. Three-market levels: The emphasis is on processed products that entail final product demand and imports, supply of milk, use of fat and non-fat solids and price equations. Products in this category include butter, cheese and skim milk powder. 125 Development of a spatial partial equilibrium model for the South African red meat industry 4.2.4 Summary The models discussed above are by no means the only models used internationally to model issues pertaining to food security, changes in domestic policies and trade liberalisation. Nevertheless, the characteristics discussed are represented to a lesser or greater extent in most models used today. Important to note is that the model structure is dependent on what modellers wish to quantify. For example, a model aimed at quantifying the effect of policy issues on food security will have a different structure than a model designed to quantify liberalisation issues on trade. This is not to say that a model developed to quantify the effects of policy issues on food security would not be able to provide information on the impact of such issues on trade, but that detail pertaining to trade issues would be much less specific, and vice versa. In fact, many models, including some of the models mentioned, have been adapted, so that they are more versatile, i.e. amendments were made in terms of model structure. A further distinction between the models discussed is the differences in terms of commodity and regional coverage, time frame for projections and inclusion of non- agricultural demand and supply shift factors. Hence, one would expect predictions to differ between these models. This does not mean that one is better than the other, but rather that results of such predictions should be interpreted bearing in mind the original aim of the modelling exercise. One area of concern with respect to the models discussed above is the fact that sub- Saharan Africa, and more specifically southern Africa, is under-represented in the sense that there is a lack of data and information pertaining to technical and economic issues related to agriculture. This concern is not meant as criticism towards the modellers of the mentioned models, but towards government agendes responsible for gathering and disseminating of such information in the respective countries. As mentioned, the main issues covered by these models relate to food security, changes in domestic policies and liberalisation, which is again associated with the welfare situation in southern African countries. It is therefore difficult to understand why so little has 126 Development of a spatial partial equilibrium model for the South African red meat industry been done to improve the information basis that could, in its turn, assist modellers in quantifying the effect of, for example, liberalisation, which could in turn be used as tool during trade negotiations. A further problem associated with this state of affairs is that results generated by these models are used for planning and policy design purposes, which could lead to poorly directed policy initiatives. It is thus no wonder that developing countries are discontented regarding the conclusion of trade negotiations. The fact of the matter is that the responsibility of a country to ensure it is in a good negotiating position lies within the country and not with modellers or other governments. However, from an international point of view it would be to the benefit of both developed and developing countries if policies initiated in developing countries should lead to improvements in welfare. Hence, the idea that much more emphasis should be placed on improving developing countries' information systems could be considered, i.e. directing a portion of development funds towards the development of internationally comparable information systems. 4.3 Model specification The previous section discussed models currently being used internationally to model the effects of trade liberalisation, issues relating to food security and socio-economic variables, such as population growth. In the section that follows a SPE model for the South African red meat industry will be developed. This entails, amongst other factors, a discussion of the products, regions, and supply and demand data used, as well as the specification of the model parameters and variables. 4.3.1 Product specification and regional delineation Two different product categories are specified in the model, namely primary products and secondary products. The primary products category is further divided into three sub- categories, namely cattle, sheep and pigs. Similarly, the secondary products group is divided into three sub-categories, namely beef, mutton and pork. Products from different regions are assumed to be perfect substitutes, and consequently buyers are assumed to 127 Development of a spatial partial equilibrium model for the South African red meat industry be indifferent as to the sources of supply. Armington (1969) states that this assumption implies - leaving aside any factors that lead buyers to spend more on a given item than necessary - that elasticities of substitution between different supplies are infinite and that the corresponding price ratios are constant. According to Tomek and Robinson (1990) this assumption is often unrealistic. Armington (1969) suggests an approach to trade modelling that entails a general theory of demand for products that are distinguished not only by their kind, but also by their place of production (generally known as the Armington approach). Products are distinguished from one another in the sense that they are assumed to be imperfect substitutes in demand. In other words, not only is each good different from any other good, but each good is also assumed to be differentiated according to the suppliers' area of residence from a buyers' viewpoint. For example, buyers may view fruit produced in Chile as different from fruit produced in Brazil. Nevertheless, although cognisance is taken of the Armington approach, paucity of relevant data and information pertaining to elasticities of substitution resulted in reverting to the more general assumption of perfect substitution among products of the same kind. Within this framework let: i,j denote all commodities; i,j = 1,2, ..., n. where i = j ip,jp denote all primary commodities (Cattle, sheep and pigs); ip, jp = 1,2, ..., n. where ip and jp c i is,js denote all final commodities (Beef, mutton and pork); is, js = 1,2, ..., n. where is and js c i The model consists of 12 regions among which livestock and meat are shipped. Eleven are classified as domestic regions and one as a foreign region. Domestic regions are the Western Cape, Eastern Cape, KwaZulu-Natal, Northern Cape, North West, Free State, Gauteng, Mpumalanga and Northern Province. Namibia and Botswana are also 128 Development of a spatial partial equilibrium model for the South African red meat industry regarded as domestic regions. Foreign regions consist of a Rest-of-the-World component. In addition three transit points, namely Cape Town Harbour, Port Elizabeth Harbour and Durban Harbour, are included. Note that it is also assumed that all three transit points have the infrastructure for the importation of meat products. The regions are denoted as follows: r,r1 denote all regions; r, r1 = 1,2, "., 13. rd denote all domestic regions; rd = 1,2, .'" 9. where rd c r rfn denote all foreign regions; rfn = 1. where rfn c r Production is assumed to originate at a single location in each region (except in the transit regions). Likewise, consumption and processing is assumed to occur at a specific location. Within the current modelling framework, production, consumption and processing are assumed to take place at the same location and correspond to that used by Jooste (1996). This convention was also adopted by Wallace and Judge (1959), Bawden (1966), Commer (1991), Halbrendt et a', (1995) and Yavuz et a', (1996). According to Tomek and Robinson (1990) this assumption may cause derived prices of products to not correspond closely to observed prices. He states that such discrepancies may be attributable to errors in data, the rigid assumptions underlying SPE's, or the failure to take account of special trading relationships and/or "irrational" preferences among buyers and sellers. A specific problem encountered in this study was that the price differentials between regions with respect to the producer price of livestock hardly ever corresponded to associated observed transport costs. In this regard it is important to note that price differences between any two regions (or markets) that trade with each other will merely equal transfer costs (Tomek and Robinson, 1990; Takayama and Judge, 1971; Halbrendt et a', 1995; Caves and Jones, 1985). Mathematically this is expressed as follows: pj - Pjl ~ TCr ,rl ,jwhere pj denotes the demand price of commodity i in region r, Pjl denotes supply price of commodity i in 129 Development of a spatial partial equilibrium model for the South African red meat industry region r1 and TCr ,rl ,i denotes the transport cost of commodity i between region rand r1. The discrepancies in observed prices and associated transport cost are caused by several factors, namely (i) observed prices are reported as regional averages which includes "just-across-regional-border-trade" and trade over long distances and (ii) that transport costs were only calculated to correspond with the central locations identified in each region. With respect to the latter, sample data pertaining to the transport cost of livestock and meat were obtained from Hestony Transport (2000), Nel (2000), Durr (2000) and Milton (2000). Road transport cost for live animals was assumed to be fixed per animal per kilometer, but different according to the type of animal transported as a result of truck capacity utilisation. Road transport rates of meat between all the market and supply source points were not available, and hence a similar model previously used by Wallace and Judge (1959) and Jooste (1996) was used to reflect road transport rates for meat. / This model is reflected by the following functional relationship: TGij = f31Mij + f32 vAIIij + e; where TGij represents the cost in rand of shipping a ton of meat from point i to pointj; My· is the kilometers between i and j; f31 and f32 are unknown parameters to be estimated and e is an unobservable random error. This functional form was postulated in the belief that transport rates are an increasing function of kilometers but should increase at a decreasing rate. In order to overcome the discrepancies between observed and estimated transport costs, transport costs were adjusted to reflect observed price differentials between different regions. One could argue that due to the fact that prices are reported as regional averages it would be more justifiable to adjust prices instead of observed transport costs, but due to a lack of data and a justifiable methodological framework to adjust prices, this could not be done. Also, such intervention would defy the objective of the study since it is the impact of liberalisation on prices that is to be measured, and not on transport cost. 130 Development of a spatial partial equilibrium model for the South African red meat industry 4.3.2 Data specification Data on demand, supply and prices of livestock and meat on a regional basis presented several problems. The reason for this is fourfold, namely (i) information that is important for planning purposes, such as slaughter statistics is, since the demise of the Meat Board of South Africa, no longer gathered, (ii) most information gathered since 1997 was only done on a national basis, (iii) the red meat industry has not yet fully restructured its information gathering and dissemination structures and (vi) industry role players are reluctant to provide information within the "free market" environment as they consider it a possible threat to their own existence. Hence, 1996 was the last year that official statistics spanning 12 months of importance for this study was published. This, coupled with the fact that the full force of deregulation and liberalisation caught up with the red meat industry in 1996, resulted in this year being used as base year in the model. 4.3.3 Supply and demand of livestock In order to model the supply of livestock in South Africa, data are needed on the size of the national herd and off-take rates of animals per region, i.e. the herd size multiplied by the off-take rate equals supply. Thus, in order to determine regional supply of livestock, information is needed on regional herd numbers and off-take rates. However, although information on regional herd numbers was sourced from the NDA (2000) and Meat Boards (1997) there exists a paucity of data as far as regional off-take rates are concerned. In order to overcome this problem, commercial and non-commercial off-take rates were calculated on a national basis. It was then assumed that the commercial off-take rate would be the same for all commercial herds, whilst the non-commercial off-take rate, will be the same for all non-commercial herds. In order to calculate the national commercial off-take rate live imports from other countries, such as Namibia, were subtracted from the reported total commercial slaughterings. Cognisance should furthermore be taken of the fact that the ratio between commercial and non-commercial herds differs between regions. The implication of this is that regional off-take rates will be different, i.e. a region with a 131 Development of a spatial partial equilibrium model for the South African red meat industry large commercial herd compared to the non-commercial herd, will have a higher off-take rate than a region where the commercial herd is relatively small compared to the non- commercial herd. To account for this, weighted off-take rates were calculated, which was then used to calculate regional supply of livestock. In terms of the demand for livestock, regional commercial slaughter statistics were sourced from the Meat Board (1997). In order to derive regional slaughter numbers for the non-commercial sector, the national non-commercial sector off-take rate was calculated and multiplied by the non-commercial sectors' herd numbers in the respective regions. Herd numbers on a regional basis for the non-commercial sector were obtained from the NDA (2000), whereas slaughter numbers for this sector were only available on a national basis from the same source. The total number of animals slaughtered in South Africa per region was calculated by adding commercial and non-commercial slaughter numbers. From a modelling point of view exogenous/original demand and supply of livestock is represented as follows: denotes the given quantity demanded of a primary commodity ip in region r. sup r = HrdSiz rx 0r where: sar" denotes the given quantity supplied of a primary commodity ip inr region r. HrdSizr denotes the amount of the primary product ip that could be utilised for further processing in domestic region r. 132 Development of a spatial partial equilibrium model for the South African red meat industry denotes the rate (constant proportion at all output levels) at which a primary commodity ip is made available for further processing in region r. 4.3.4 Supply and demand of meat The supply of meat on a regional basis for all domestic regions was calculated on the basis of a conversion factor associated with each primary product sub-category. For example, conversion ratios used to convert cattle, sheep and pigs into meat were 175, 17 and 60, respectively. For example, this implies that one head of cattle will produce 175 kg of meat. The other conversion ratios could be interpreted in the same manner. It should already be clear that there is a direct relation between the number of cattle slaughtered and the supply of meat on a regional basis. Demand for meat was more cumbersome to calculate. Since meat demand per province was not available it had to be calculated. This was done by calculating the proportional demand for different red meats per region so that the total demand equates to total availability in the base year. The procedure followed entails the calculation of total regional spending by using the real per capita expenditure on different red meats per population group as discussed in Chapter 3, i.e. per capita spending per population group was multiplied by the number of people per population group per region to derive total weighted spending per region. It was then assumed that the proportional spending per region is equal to the proportional consumption per region in such a manner that it equates to the total availability in the base year. Due to a paucity of data it is assumed that the calculated spending on red meat products in 1993 is a good approximation of spending in the base year. Although this approach may result in rough estimates of regional demand for different types of red meat, it is still a better approximation of regional demand than applying the national per capita consumption uniformly over all regions. In other words, by multiplying the national per capita consumption estimate by regional population without taking cognisance of the fact that different population groups have 133 Development of a spatial partial equilibrium model for the South African red meat industry different consumption patterns will grossly over or under-estimate regional consumption. From a modelling point of view exogenous/original demand and supply of meat is represented as follows: DEM~ denotes the given quantity demanded of a secondary commodity is in region r. stir: = CONV)P,iS x DEMt where: denotes the given quantity supplied of a secondary commodity is in region r. denotes the rate (constant proportion at all output levels) at which a primary commodity ip is converted, per unit, into a final commodity is in region r. DEMr denotes the given quantity demanded of a primary commodity ip in region r. 4.3.5 Prices for livestock and meat Prices for livestock per region were determined by multiplying the producer price received per kg by the carcass mass and then adding income from offal (cattle, sheep and pigs) and hides (only cattle and sheep). The income from offal and hides is not necessarily realised by the farmer since it is common for abattoirs to take ownership of these products as payment for the service they provide. It is furthermore important to take cognisance of the fact that the market for offal and hides is not modelled in this study, and hence market developments in these markets are not accounted for in terms of livestock prices. Hide and offal returns are merely handled as constants. Nevertheless, it is important that returns on hides and offal are considered for in the determination of cattle prices, in order 134 Development of a spatial partial equilibrium model for the South African red meat industry to portray a more realistic picture. Offal and hide prices, regional producer prices and regional wholesale prices for meat were sourced from the Meat Board (1997). The wholesale price was selected, since this price includes, amongst others, processing costs and reflects the efficiency of the industry. Hayes, Green, Jensen and Erbach (1991) as cited by Jooste (1996) also regard the price of wholesale cuts as most useful for measuring of the protection level afforded to different livestock industries. They warned against the use of average prices for determining protection levels, since a country or region imports certain cuts and exports simultaneously. However, as prices pertaining to individual cuts were not available on a regional basis, average prices had to be used to investigate the impact of tariffs and changes in the exchange rate on the livestock industry as a whole. The argument by Hayes et al (1991) cannot be discarded completely for the SACU region due to political, economical, geographical and topographical differences across country borders, and it was therefore decided to use the average wholesale prices pertaining to Namibia and Botswana to reflect their own situations. From a modelling point of view exogenous/original livestock and meat prices in domestic regions is represented as follows: BASPRD1d denotes the base price of a primary commodity ip in region rd. BASPRD~d denotes the base price of a secondary commodity is in region rd. The tariff protection method was used to calculate world prices for the different secondary sub-category products. According to Bradfield (1987), tariff protection rates are an indication of the percentage deviation of domestic prices from international prices. The derivation of the world prices, using the tariff protection method, is denoted as follows: Wp = o, / (1 + Tpr) 135 Development of a spatial partial equilibrium model for the South African red meat industry where: Wp = World price; Op = Domestic price; and Tpr = Tariff protection rate. The assumption underlying this method is that ad valorem duties represent the deviation between the domestic price and the world price. The derived world price was also adjusted for cost insurance and freight (cif) costs. From a modelling point of view exogenous/original meat prices that enter through the transit regions are represented as follows: BASPRdifn = BASPRn;~w+CIFCSTis where: BASPRD~n denotes the base price of secondary commodity is in region rfn (in this case the transit regions). BASPRD~w denotes the base price of secondary commodity is in region row (in this case the rest of the world). CIFCSTis denotes the cif cost associated with secondary commodity is. It is further important to note that the meat price of the rest of the world is subject to import tariffs. The import tariffs are calculated on an ad valorem basis on the free-on-board (fob) price of the imported product. The import tariff is then added to the price differential between domestic and international prices. From a modelling point of view tariffs are represented as follows: 136 Development of a spatial partial equilibrium model for the South African red meat industry TARlFF~ow,rfn= BASPR4/n x PA VTR.Bf./n+PSPTR.Bf./n where: TARlFF~w,rfn denotes the tariff applied on imports of the secondary commodity is from region rfn. BASPRD*n denotes the fob rest of the world price for secondary commodity is PAVTRIiifn denotes the ad valorem tariff applicable to commodity is originating from region rfn. PSPTRIiifr, denotes the specific tariff applicable to commodity is originating from region rfn. Note that parameter PSPTRB*n is zero in the base year, since no specific tariffs are currently applied to the imports of red meat. However, such a scenario would be entertained at a later stage. 4.3.6 Specification of the demand and supply equations Each region has primary commodity supply, conversion and secondary commodity demand functions. Given the above mentioned problem statement, prices are expressed as a function of the quantities in the different functional relations, and are referred to as the quantity formulation. The formulation of the supply and demand functions is specified in this manner to comply with the Takayama and Judge (1971) approach to calculating the net quasi-welfare function. Elasticities of demand and supply were derived from Nieuwoudt (1998), whilst unknown elasticities at primary production and intermediate level were estimated by means of the methodology suggested by NicholIs (1941). Given the above clarification, the supply, demand and conversion functions used in the model are specified as follows: 137 Development of a spatial partial equilibrium model for the South African red meat industry Supply function where: ppr denotes the endogenous producer price of primary commodity jp in region r. aipr and pipr denotes the intercept and slope coefficients respectively for the supply function of primary commodity jp in region r. denotes the endogenous quantity supplied of the primary commodity jp in region r. The set of quantity-dependent regional supply relations may be written in matrix form as: PPI al PI QSI PP2 a2 P2 QS2 Pqs == = + PPn an or more compactly Pqs = X +OQS (X = intercept and 0 = slope). The underlying assumption of the above specification is that the actual supply quantity QSr is to be greater than or equal to the effective supply from region r to all other regions. . n . Mathematically this is expressed as follows: QSf ~ "IQS;rl . rl ' Demand function PD ris = isr + (JJ riSQD irs where: PD~ denotes the endogenous consumer price of secondary commodity is in region r. 138 Development of a spatial partial equilibrium model for the South African red meat industry denotes the intercept and slope coefficients respectively for the demand function of secondary commodity is in region r. denotes the endogenous quantity demanded of the secondary commodity is in region r. The set of quantity-dependent regional demand relations may be written in matrix form as: pd, AI lVl QDI pd2 A2 lV2 QD2 Pqd == = + pd; An or more compactly Pqd = V + ;QD (v = intercept and ; = slope). The underlying assumption of the above specification is that the actual demand QS;s is less than or equal to the quantity shipped from all the supply regions. Mathematically this is expressed as . Ln .follows: QD;s s QD;i r . rl ' Conversion function The conversion functions denote the intermediate industry, i.e. the demand for livestock and the supply of meat. The matrix for the conversion functions is different from the above functions insofar as it represents prices for final products and prices for live animals. It also contains both commodity groups, i.e. the demand side contains only live animals and the supply side only meat. The conversion functions are denoted as follows: Ppirp = rirp +V ipriPQc r where: denotes the endogenous producer price of primary commodity ip in region r. 139 Development of a spatial partial equilibrium model for the South African red meat industry PD~ denotes the endogenous consumer price of secondary commodity is in region r. denotes the intercepts respectively for the demand and supply functions of primary and secondary commodities in the processing sector in region r. denotes the slope coefficients respectively for the demand and supply functions of the primary and secondary commodities in the processing sector in region r. denotes the endogenous quantity demanded of the primary product for conversion into secondary commodities in region r. denotes the en'dogenous quantity supplied of the secondary commodity in region r. 4.3.7 Determination of the slope variables and constant parameters As mentioned before, supply and demand functions were specified in a way that they comply with the Takayama and Judge (1971) approach to calculating the net quasi- welfare function. This has certain implications for behavioural parameter specification. The reason for this is that demand and supply elasticities are derived with quantity expressed as a function of prices, and are referred to as the price formulation. According to Tomek and Robinson (1990) this means that if a demand function is written Q = f(P), then the slope of the function is BQ / BP, and the price elasticity at a point (Q, P) is Gp = (BQ/BP)(P/Q». In other words, the slope coefficients of price in the supply and demand equations are computed from the elasticities pertaining to final demand and supply of primary and secondary commodities in region r by means of the following simple algorithm: 140 Development of a spatial partial equilibrium model for the South African red meat industry where: denotes the slope coefficient of price in the demand and supply functions of commodity i in region r. denotes the elasticity of supply (demand) of commodity i in region r. q~ denotes the quantity supplied (demand) of commodity i in region r. p~ denotes the supply (demand) price of commodity i region r However, if P = f(Q), then the slope of the function is ap IaQ, and the price elasticity is ep = [1I(ap I aQ) fp IQ). Hence the slope of the inverse demand and supply functions can be calculated easily using the following notation: where: denotes the slope of the inverse demand and supply functions of commodity i in region r. denotes the slope of the ordinary demand and supply functions of commodity i in region r. Given the slope coefficients, the intercept terms (ar, A,~ and (};onv) are computed as follows: aipr = BASP RDirp - pipr SUpipr (}cronv = BASP RDconv _ Vconvr r cosv=r : 141 Development of a spatial partial equilibrium model for the South African red meat industry 4.4 The mathematical model The model contains two stages. The first is a production stage, where farmers supply livestock to processors who, in turn, manufacture meat. The second is a processing stage where processors supply meat to wholesalers for further sale. Given the aforementioned parameter specification, the quasi-welfare function to be optimised is measured as producers' surplus and consumers' surplus minus transport cost and tariffs. The concave quadratic function is derived as follows: W (Qvisr r' OSirP,QCi)r=fqd;s(;_is _r.,nDiS)dQD iS _fqs;s(aiSqd r ~. r r qso r +piPrQSipr)dQSiSo r where: denotes the welfare function dependent on demand quantity QV;s, supply quantity Qsr and quantity converted QC;. qdo and qd;s denotes the change in welfare from a pre- to post-trade equilibrium in the demand function. qso and qs;s denotes the change in welfare from a pre- to post-trade equilibrium in the supply function. qco and qc, denotes the change in welfare from a pre- to post-trade equilibrium in the conversion function. The integration operation above captures the consumer and producer surplus in each of the specified regions, and hence qualifies as a regional welfare function that must be maximised. Thus, this integral function would yield the following non-linear quasi-welfare function: 142 Development of a spatial partial equilibrium model for the South African red meat industry W (QDiS OSiPQCi) = k + ;_isQDiS _ _2!_liJiS(QDiS)2 _ aiPQSis _ _!_piP (QSiP)2r r' r, r r r r r r r 2 r r _ eiQci _ _!_ vi (QCi2 )2r r r r where: k denotes the constant of integration and can be dropped from the above equation. The community quasi-welfare function over all n regions is derived by taking the sum of the welfare function that results in the total quasi-welfare function: W (QDiS .os»QCi) = Ï, [;_isQDiS - _!_liJiS(QDiS)2 - aip QSis - _!_ pip (QSiP)2 , i=1 2 2 - ei oe' - _!_vi (QCi)2] 2 Until now the equation W (QDis ,OSiP, QCi) has not taken into account the transport cost associated with the trans-shipment of primary and secondary commodities between different regions. Takayama and Judge (1971) state that since transport costs are determined exogenously, it represents a negative benefit to the society. Hence, transport cost needs to be deducted from the total quasi-welfare function as follows: W (QDiS .osr QCi) = [Ï, AisQDis _ _!_liJiS(QDis)2 _ aip QSis _ _!_ pip (QSip)2, ~ 2 2 _ ei oe' __!_vi (Qcï)2] - Ï Xi te' 2 r,rl=1 where: denotes the variable quantity of a commodity i, shipped between regions. denotes the transport cost of commodity i, shipped between regions. 143 Development of a spatial partial equilibrium model for the South African red meat industry As stated previously, imports of red meat in South Africa are regulated by means of import tariffs which will have an effect on the welfare situation within a particular country or region. Hence, it is important to take into account the tariff regime applied to meat imports in the welfare calculation. According to Takayama and Judge (1971) the presence of a tariff implies that when the flow from region r to r1 of commodity i is positive, the differential between the market demand price and the market supply price, P; - P;l ' must be exactly equal to the transportation cost plus the import tariff, i.e. P; - P;l = TC r,rl ,i + Tariff; ,rl . Hence the function to be maximised becomes: W (QDiS,OSiPQCi)=[Ï, ;_isQDiS, ~ _.!2.(()is(QD iS)2 _aiPQSiS _.!2.pi P(QSiP)2 -o'oc' _.!.vi(QCi)2]_ Ï, Xi x (TCi +Tariffi) 2 r,rl=l where: Tariffi denotes the tariff applied on imported commodity i. Since the condition for SPE's is that the quantity demanded and supplied should be equal to each other in order to attain a market equilibrium price, the following market clearing equation was specified: QS; +QC; + "LX;l,r = QD; + "LX;,rl rl rl 4.5 Modelcharacteristics The main characteristics of the model is as follows: Spatial partial equilibrium in nature: The model only considers one sub- sector of South African agriculture, namely the red meat sector. Account is not given of the linkages with other agricultural sub-sectors, nor with the rest of the economy. Issues such as changes in per capita income could, however, be 144 Development of a spatial partial equilibrium model for the South African red meat industry introduced exogenously. Furthermore, the model reflects trade through endogenously determined trans-shipments of the respective commodities between different regions. Multi-region, muiti-product in nature: The model comprises nine different provinces of South Africa, three external regions and three transit points. Three livestock and three red meat products are included. It is, however, important to note that it is assumed that consumers do not distinguish between commodities imported from other regions and those produced within the domestic region. Deterministic: Risk and uncertainty associated with, for example, weather changes, are not taken into account. Hence, average conditions are assumed with respect to different simulations. Shocks associated with, for example, increased livestock supply during drought periods, can however be introduced exogenously. Synthetic: Behavioural parameters, i.e. different elasticities, are not estimated endogenously within the model, but are soureed from literature. 4.6 Summary There are currently several multi-commodity, multi-region agricultural trade models in use internationally for measuring the impact of issues related to trade liberalisation, food security, etc. Most of these models have the ability to do forecasts over the medium term, whereas the WATSIM model was designed specifically to go beyond the medium term. None of these models, however, provide specific information on the red meat industry in South Africa. Furthermore, although the red meat industry in South Africa was researched extensively in terms of its structure, economic behavioural parameters, etc., limited research has been conducted from a mathematical programming point of view that encompasses a partial spatial equilibrium model, focussing specifically on the red meat industry. 145 Development of a spatial partial equilibrium model for the South African red meat industry The model developed in this chapter aims to maximise a quasi-welfare function to optimise producers' surplus and consumers' surplus minus transport cost and tariffs, using GAMS. The main characteristics of the model are that it is spatial partial equilibrium, multi-region and multi-product, deterministic and synthetic in nature. The model is for the exclusive use of modelling changes in trade policy and selected demand and supply shift factors on the market for red meat products in South Africa. The model is not suitable for reaching conclusions about resource use on farm level, nor is it suitable for deriving answers on market variables over the short run. Assumptions underlying the model can be summarised as follows: (i) production, processing and consumption takes place at the same location in each region, (ii) average prices are used for each region, (iii) price differences between any two regions (or markets) that trade with each other will merely equal transfer costs, (iv) surplus regions will first meet own demand before trading, and deficit regions supply their own demand before importing, (v) homogeneous products are traded, and (vi) conversion and off-take rates are constant over time. These assumptions have implications for the results generated by the model, e.g. just- across-the-border-trade will not be captured, which entails that all trade in reality will not be shown. Also, there is good reason to believe that behavioural parameters have changed from those estimated during the period of regulation of the red meat industry. In other words, the current model may not reflect the current status of economic behaviour, but will nonetheless provide plausible orders of change in important variables. Lastly, the homogeneous product assumption entails perfect substitution between products, which in reality is not the case. However, due to a paucity of data, the Armington approach to trade modelling could not be used. This is not to say that the homogeneous product assumption will result in unrealistic results, but rather that there is room for improvement in the current modelling framework. 146 CHAPTER 5 VALIDATION OF THE SPATIAL PARTIAL !EQUILIBRIUM MODEL 5.1 Introduction In Chapter 4 a spatial partial equilibrium model for the red meat industry was developed. This model is solved using the quadratic programming procedure in the General Algebraic Modelling System (GAMS). It is presumed that the commodity markets represented by the data are in a static SPE state. This assumption becomes credible if there exists a spatial welfare maximisation model which, when solved, attains an SPE state with optimal values that closely match the existing production, consumption, and price data. The aim of this chapter is therefore to investigate the extent to which the developed model matches the data discussed in Chapter 4. 5.2 The validation procedure According to Hazel and Norton (1986) validation of a model encompasses four different issues, namely a numerical report of a model's fidelity to the historical data set, improvements of the model as a consequence of imperfect validation, a qualitative judgement on how reliable the model is for the stated purposes, and a conclusion regarding the kinds of uses that it should not be used for. The validation procedure followed in this study involved a comparison between observed supply, demand for and prices of livestock and red meat products and the values as calculated in the base run. The model was first solved only with respect to minimum cost transport flows across regions to, firstly, check the consistency of observed transport costs given observed prices in different regions, and secondly to check the validity of net trans-shipment quantities. This implies that demand and supply quantities in each region were fixed to the observed values. 147 Validation of the spatial partial equilibrium model In respect of the consistency check the results indicated that observed transport costs did not conform to the theoretical principle that the price in a deficit region will be equal to the price in a surplus region plus transport/transaction costs. The reason could be, firstly, that there may exist discrepancies in the observed prices as reported by the Meat Board (1997), and secondly that quoted transport costs between regions may not be the same as the actual transport costs incurred. This again emphasises the importance of accurate and timely information on market variables, such as prices (see Louw, Jooste, Van Schalkwyk, and Frick (2000) and Jooste and Groenewald (2000) for a comprehensive discussion on this issue). This problem was solved by recalculating the transport costs so that it conformed to the theoretical principles mentioned in Chapter 4. This allowed for checking of the validity of net trans-shipment of products, between regions. From a qualitative judgement point of view the model generated a realistic picture of net trans-shipment of the different products taking into account that just- across-the-border trade will not be reflected. These trade flows were then used to re- calculate the prices in different regions. However, to check the accuracy of the model as far as it simulates actual demand, supply and prices, the solution space of the SPE model could not be restricted, i.e. demand and supply quantities, as well as prices in each region cannot be fixed to the observed values. Thus, for the base run the upper and lower bounds of supply were set by multiplying actual supply by 100 and 0.01, respectively. The same was done with respect to demand. Hence, allowing the model to derive an optimal solution independent of specific restrictions, will provide insight in how accurate the model simulates reality. In other words, the better the situation is simulated in the base period, the more reliable the model, but it is, however, important to take note of the fact that it is unlikely for any model to capture all real-world effects. This is also echoed by Yavuz et al (1996) and Miranda (2000). In this respect it is important to note that the model used is synthetic in nature (see Chapter 4). Thus, given that pre-defined elasticities are used to calibrate the inverse supply and demand functions, there is no need for further calibration on observed 148 Validation of the spatial partial equilibrium model values. Stated alternatively, the construction of the inverse supply and demand functions is a kind of model calibration, since it assures that, given unchanged conditions, the original values are repeated. 5.3 Validation results Tables 5.1 and 5.2 compare the actual data with the results of the base run for cattle and beef. It is clear that the base run yielded exactly the same supply and demand values as the actual/observed supply and demand of cattle and beef in the different regions of South Africa. With respect to cattle, the Western Cape, Northern Cape, Mpumalanga, Gauteng and the North West are regarded as deficit regions for cattle, i.e. more cattle are demanded than actually supplied. Shortages of cattle in these regions are supplemented from surplus South African regions and from Namibia. As far as beef is concerned', the Western Cape, Eastern Cape, KwaZulu-Natal, Northern Province and Gauteng are deficit regions. Shortages are supplemented from other South African surplus regions, Namibia, Botswana and the rest-of-the-world. Table 5.1..Valrd afIon 0 f ca ttle supply an dd ernan d Region Cattle supply (number) Cattle demand (number) Surplus/deficit Observed Base run Observed Base run Western caoe 82407 82407 146647 146647 -64240 Northern Caoe 80437 80437 123686 123686 -43249 Free State 363323 363323 214892 214892 148431 Eastern Cape 337208 337208 263475 263475 73733 Kwazulu-Natal 406158 406158 363961 363961 42197 MpumalanQa 230499 230499 273306 273306 -42807 Northern Province 170197 170197 137180 137180 33017 Gautenq 44642 44642 447720 447720 -403078 North West 257878 257878 281008 281008 -23130 Ilml.2orts*:Namibia (number) I 279126 I * Equal to actual imports in 1996. 149 Validation of the spatial partial equilibrium model Table 52...ValI"datlIon 0fb eef SUPPlY andd ernand Region Beef supply (ton) Beef demand (ton) Surplus/deficit Observed Base run Observed Base run Western Cane 25663 25663 63445 63445 -37782 Northern Cape 21645 21645 11917 11917 9728 Free State 37606 37606 34075 34075 3531 Eastern Cape 46108 46108 50208 50208 -4100 Kwazulu-Natal 63693 63693 69826 69826 -6133 MQumalanaa 47829 47829 48620 48620 -791 Northern Province 24007 24006 22297 22297 1709 Gautena 78351 78351 125265 125265 -46914 North West 49176 49176 28920 28920 20256 Imports": Namibia (ton) 9589 Botswana (ton) 3842 Rest-of-the-World (ton) 47064 *Equal to actual imports In 1996 Table 5.3 shows the deviation between the actual prices and those that resulted from the base run for cattle and beef respectively. The base run cattle prices deviated relatively little from the observed cattle prices. The deviation in beef prices was greater than those of cattle prices. The discrepancies between the observed and base run prices can be attributed to the fact that observed prices and reported transport costs are not consistent. This can also be traced back partly to the spatial assumptions of regional spot markets. Note should also be taken that other transaction costs related to, for example administration, negotiations, etc. are also excluded, and will probably never be captured. Table 5.3: Validation of cattle and beef prices Region Cattle price (Rlkg) Beef price (Rlkg) Observed Base run Deviation Observed Base run Deviation !western Cape 7.70 7.70 0.00% 14.22 12.77 -10.20% Northern Cape 7.50 7.50 0.00% 11.49 12.67 10.28% Free State 7.35 7.49 1.92% 11.72 12.69 8.23% Eastern Cape 7.20 7.35 2.08% 12.62 12.79 1.35% Kwazulu-Natal 7.47 7.45 -0.24% 12.98 12.77 -1.65% Mpumalanaa 7.74 7.69 -0.70% 11.70 12.78 9.24% Northern Province 7.40 7.61 2.83% 11.85 12.70 7.18% Gautena 8.10 7.65 -5.61% 12.80 12.80 0.00% North West 7.60 7.59 -0.12% 11.50 12.74 10.77% 150 Validation of the spatial partial equilibrium model Figure 5.1 and 5.2 show the net trans-shipment of cattle and beef among different regions in South Africa that correspond with the surpluses and deficits identified. NAMIBIA Wndhoek BOTSWANA 0· SOUTH PE HarbaJr N Cape TO\M1 Harbour A Figure 5.1: Net trans-shipment of cattle in the base run (1996) 151 Validation of the spatial partial equilibrium model NAMIBIA Wndhrek BOTSWANA IJ SOUTH PE Harbrur N Cape TOWl Hartour A Figure 5.2: Net trans-shipment of beef in the base run (1996) In Tables 5.4 and 5.5 the observed versus base-run results pertaining to the supply and demand of sheep and sheep meat is shown. As was the case for cattle and beef, the base-run results conformed to the observed demand and supply. With respect to sheep, the Western Cape, Northern Cape, KwaZulu-Natal, Gauteng and the North West are deficit regions. These shortages are supplemented from surplus South African regions, whilst all non-South African sheep are imported from Namibia. As far as sheep meat is concerned, the KwaZulu-Natal, Mpumalanga, Northern Province, Gauteng and North West are deficit regions. For the base-year scenario all sheep meat imports to 152 Validation of the spatial partial equilibrium model satisfy domestic demand, over and above those from surplus South African regions, originated from the rest-of-the-world. Table 54o 0 Va IOI dafIon 0 f sehep supply an dd eman d Region Sheep supply (number) Sheep demand (number) Surplus/deficit Observed Base run Observed Base run Western Cape 523956 523956 1297722 1297722 -773766 Northern Cape 1184503 1184503 1585265 1585265 -400762 Free State 924448 924448 584044 584044 340404 Eastern Cape 1050895 1050895 889929 889929 160966 'Kwazulu-Natal 152274 152274 204434 204434 -52160 Mpumalanga 296189 296189 141310 141310 154879 Northern Province 25328 25328 22435 22435 2893 Gautena 16638 16638 237639 237639 -221001 North West 106514 106514 145736 145736 -39222 moorts": Namibia (number) 827769 *Equal to actual Imports In 1996 Table 55 0o 0 Va rId a tlIon 0 f sehep mea t SUppl yan dd ernan d Region Sheep meat supply (ton) Sheep meat demand (ton) Surplus/deficit Observed Base run Observed Base run Western Cape 22061 22061 21365 21365 696 Northern Cane 26950 26950 3739 3739 23211 Free State 9929 9929 7638 7638 2291 Eastern Cape 15129 15129 11495 11495 3634 Kwazulu-Natal 3475 3475 22571 22571 -19096 Mpumalanga 2402 2402 9510 9510 -7108 Northern Province 381 381 4084 4084 -3703 Gautena 4040 4040 30523 30523 -26483 North West 2478 2478 6233 6233 -3755 imports": Rest-of-the-World (ton) 30313 *Equal to actual imports In 1996 Table 5.6 shows the deviation in observed sheep and sheep meat prices and those obtained from the base run. The absolute difference between model derived and actual sheep prices varies from 0 to 5.45 per cent. The largest deviation occurred in Gauteng, followed by Mpumalanga. For sheep meat the largest deviation occurred in the Northern Cape followed by KwaZulu-Natal. Except for the Northern Cape, the deviations are relatively small, and were expected given the model specifications. 153 Validation of the spatial partial equilibrium model Table 5.6. Valrd atlIon 0f sheeQ_and shee_Qm_eat prices Region Sheep price (Rlkg) Sheep meat price (Rlkg) Observed Base run Deviation Observed Base run Deviation Western Cape 11.76 11.76 0.00% 16.59 16.61 0.13% Northern Cape 11.12 11.00 -1.06% 14.25 16.75 17.55% Free State 10.76 10.71 -0.55% 16.24 16.77 3.23% Eastern Ca_pe 10.41 10.35 -0.56% 16.80 16.69 -0.68% Kwazulu-Natal 12.06 11.59 -3.90% 17.77 16.77 -5.62% MpumalanQa 11.12 10.65 -4.23% 16.25 16.88 3.87% Northern Province 11.00 10.71 -2.67% 16.30 16.88 3.55% Gautenq 11.88 11.24 -5.45% 16.88 16.88 0.00% North West 11.18 11.06 -1.05% 16.75 16.84 0.56% Figures 5.3 and 5.4 show the net trans-shipment of sheep and sheep meat as determined in the base run among different regions in South Africa, as well as imports. NAMIBIA Windhoek BOTSWANA LJ PE Harbour N Cape Town Harbour A Figure 5.3: Net trans-shipment of sheep in the base run (1996) 154 Validation of the spatial partial equilibrium model NAMIBIA Wndhoék SOTSWANA LJ PE Harbrur N Cape TOW1 Hartour A Figure 5.4: Net trans-shipment of sheep meat in the base run (1996) Tables 5.7 and 5.8 compare between observed supply and demand of pigs and pork in different regions and supply and demand computed in the base run. Similar to the other red meats discussed, the estimated supply and demand figures conform to the observed supply and demand figures. Deficits regarding pigs exist in KwaZulu-Natal and Gauteng. Observed data suggest that no pigs are imported to South Africa. As far as pork is concerned, the Western Cape, Northern Cape, Free Sate, Eastern Cape, Mpumalanga and North West are all deficit regions. Pork demand in these 155 Validation of the spatial partial equilibrium model regions is supplemented by exports from surplus South African regions and imports from the rest-of-the-world. Table 57.. Valrd atl.on 0f pi.g supply andd ernan d Region Pig supply (number) Pig demand (number) Surplus/deficit Observed Base run Observed Base run Western Caoe 334475 334475 334475 334475 0 Northern Cape 29666 29666 25883 25883 3783 Free State 250451 250451 157838 157838 92613 Eastern Cape 159419 159419 153328 153328 6091 Kwazulu-Natal 331256 331256 372461 372461 -41205 MDUmalanqa 296974 296974 70614 70614 226360 Northern Province 182505 182505 134162 134162 48343 Gautenq 296355 296355 757763 757763 -461408 North West 263320 263320 137897 137897 125423 Table 5.8..Vall.dation 0f por k supply andd ernand Region Pork supply (ton) Pork demand (ton) Surplus/deficit Observed Base run Observed Base run Western Caoe 20069 20069 25251 25251 -5182 Northern Cape 1553 1553 4222 4222 -2669 Free State 9470 9470 10334 10334 -864 Eastern Cape 9200 9200 13739 13739 -4539 Kwazulu-Natal 22348 22348 18570 18570 3778 Mpumalanga 4237 4237 12197 12197 -7960 Northern Province 8050 8050 4938 4938 3112 Gautenq 45466 45466 41937 41937 3529 North West 8274 8274 8388 8388 -114 Imports*: Rest-of-the-world 10910 *Equal to actual Imports In 1996 The deviation between observed prices for pigs and pork and those obtained in the base run is shown in Table 5.9. For pigs the largest deviation occurred in the Northern Cape, followed by the North West. In general, however, deviations between observed and base run prices are relatively small. The largest difference in terms of pork prices occurred in the Eastern Cape and KwaZulu-Natal. Nevertheless deviations between observed and base-run prices are relatively small. 156 Validation of the spatial partial equilibrium model Table 59...VarId afIon 0f pi.g and por k prices Region Pigs price (R/kg) Pork meat price (R/kg) Observed Base run Deviation Observed Base run Deviation Western Ca_pe 6.20 6.02 -2.96% 10.80 10.38 -3.87% Northern Caoe 5.95 5.52 -7.28% 10.53 10.49 -0.41% Free State 5.80 5.63 -2.87% 10.20 10.46 2.51% Eastern Cape 5.37 5.43 1.24% 11.00 10.40 -5.43% Kwazulu-Natal 6.03 6.03 0.00% 10.93 10.31 -5.65% Mpumalanga 5.53 5.60 1.20% 10.51 10.51 0.00% Northern Province 5.62 5.63 0.30% 10.50 10.40 -0.91% Gauteng 6.20 6.02 -2.96% 10.40 10.40 0.01% North West 5.65 5.83 3.24% 10.47 10.46 -0.08% Figures 5.6 and 5.7 show the net trans-shipment of pigs and pork among different regions in South Africa as calculated during the base run. NAMIBIA Windhoek BOTSWANA CJ Harbour N Cape Town Harbour A Figure 5.6: Net trans-shipment of pigs in the base run (1996) 157 Validation of the spatial partial equilibrium model NAMIBIA Windhoek o BOTSWANA SOUTH PE Harboor N Cape To'Ml Harbour A Figure 5.7: Net trans-shipment of pork in the base run (1996) 5.4 Conclusion With respect to demand and supply of livestock and different red meat products, the base run yielded observed values. However, the validation process did not yield exactly the same prices for the different products as the observed prices. This was expected, given the above mentioned assumptions underlying the model. Nevertheless, the deviations are relatively small and hence one can conclude that the model would predict the impact of, for example policy changes, with a high degree of accuracy. 158 CHAPTER 6 THE IMPACT OF LIBERALISATION ON THE RED MEAT ~NDUSrRY 6.1 Introduction South Africa has clearly demonstrated its commitment to "reform" its agricultural sector in recent years. This was mainly achieved through two processes, namely deregulation and liberalisation. According to Vink (1993) the deregulation of agriculture in South Africa started as early as the late 1970's. when the financial sector was extensively liberalised following the publication of the De Kock Commission report. Since then various reforms relating to deregulation have taken place (Brand, Cristodoulou, Van Rooyen and Vink, 1992; Kassier, 1992; LAPC, 1993; Jooste and Van Zyl, 1999) that culminating in the abolishment of the agricultural control boards in 1997. One could argue that this process actually "prepared" South African agriculture for the process of liberalisation that commenced in 1995. In actual fact the main thrust towards deregulation coincided with the start of the liberalisation process. This has exerted considerable pressure on the South African agriculture to adapt to the emergence of a new marketing environment, resulting in several structural changes regarding industry organisation, agribusiness and producer level (Jooste, Van Schalkwyk, Viljoen, Meyer and Kassier, 2001). This chapter will focus on issues that relate to the liberalisation process. Of particular importance is the issue of tariff liberalisation as discussed in Chapter 2. In addition, the possible impact of increases in world market prices for red meats due to liberalisation or a devaluation of the exchange rate will be investigated. The possible impact of the abolishment of Lomé will also be investigated. 159 The impact of liberalisation on the red meat industry 6.2 Justification of existing tariffs applicable to red meat imports Table 6.1 shows South Africa's commitment with regard to scaling down tariffs on red meat as stipulated in its country schedule under the WTO. Table 6.1 Current RSA tariff regime on Imports of red meat products Tariff Description of product Base Bound Applied Line Rate Rate Tariff % % % 02.01 Meat of Bovine Carcasses, Fresh or Chilled: 0201.10 -Carcasses and half carcasses 115 69 40% 0201.20 -Other cuts with bone in 115 69 40% 0201.30 -Boneless 400 160 40% 02.02 Meat of Bovine Animals, Frozen: 0202.10 -Carcasses and half carcasses 115 69 40% 0202.20 -Other cuts with bone in 115 69 40% 0202.30 -Boneless 400 160 40% 02.03 Meat of Swine, Fresh, Chilled or Frozen: 0203.1 -Fresh or chilled: 0203.11 =Carcasses and half carcasses 50 37 15% 0203.12 =Hams, shoulders and cuts thereof, with bone in 50 37 15% 0203.19 =Other 0203.19.10 - Rib 50 37 free 0203.19.90 -Other 50 37 15% 0203.2 -Frozen: 0203.21 =Carcasses and half carcasses 50 37 15% 0203.22 =Hams, shoulders and cuts thereof, with bone in 50 37 15% 0203.29 =Other 0203.29.10 -Rib 50 37 free 0203.29.90 -Other 50 37 15% 02.04 Meat of Sheep or Goats, Fresh, Chilled or Frozen: 0204.10 -Carcasses and half-carcasses of lamb, fresh or chilled 190 95 40% 0204.2 -Other meat of sheep, fresh or chilled: 0204.21 =Carcasses and half carcasses 190 95 40% 0204.22 =Other cuts with bone in 110 66 40% 0204.23 =Boneless 110 66 40% 0204.30 -Carcasses and half-carcasses of lamb, frozen 190 95 40% 0204.4 -Other meat of sheep, frozen 0204.41 =Carcasses and half carcasses 190 95 40% 0204.42 =Other cuts with bone in 110 66 40% 0204.43 =Boneless 110 66 40% 0204.50 -Meat of coats 150 82 40% In terms of the Marrakech Agreement the actual rate of duty should be phased down from a level which does not exceed the base rate to a level which does not exceed the bound rate within the specified period. Source: NDA, 2000. 160 The impact of liberalisation on the red meat industry It is clear that South Africa is well within its WTO commitments. The question can, however, rightfully be asked whether tariffs on red meat imports are justifiable. The answer to this question is provided by Van Schalkwyk, Van Zyl and Jooste (1995). They regard the South African agricultural producer to be entitled to protection against the negative effects of price distorting aid measures of foreign countries on their produce prices and sales. The validity of this argument is clearly demonstrated when one compares the Producer Support Estimate (PSE) of different countries are compared. From Table 6.2 it is clear that South Africa can be regarded as one of the least subsidised countries in the world. Only New Zealand had a lower PSE than South Africa in 1998. Table 6.2: International comparison of PSE's (1998) (percentage) !country I PSE for 1998 I New Zealand 0.80 South Africa 2.70 Australia 6.80 Hungary 11.80 Canada 16.10 Mexico 16.70 Czech Republic 17.50 USA 21.60 EU 45.30 ~apan 63.20 Iceland 68.90 Source: Kirsten, Tregurtha, Gouse and Twai, 2000. The argument made by Van Schalkwyk et al (1995), is also of particular importance to the South African red meat industry, especially if one takes into account the direct and indirect support afforded to, for example beef producers in the EU (see Chapter 2), South Africa's largest trading partner when it comes to red meat trade. Table 6.3 shows the PSE's for the South African red meat industry as calculated by Kirsten et al (2000). They mention that government expenditure had a limited influence on the PSE results and it is expected that the percentage PSE per commodity will vary according to the market price support, which could be influenced by tariffs. In other words, the high PSE's shown for beef and sheep meat is largely due to the current tariff 161 The impact of liberalisation on the red meat industry dispensation for these two commodities. However, Kirsten et al (2000) make a very important observation in that variations in the world reference price plays an extremely important role in PSE calculations. For example, the PSE for beef and veal shown in Table 6.3 was calculated by using the average price (or unit value) of low-quality meat imports from the EU. If the reference price is changed to EU FOB prices (good-quality beef) the 1998 PSE changes to -61.73 per cent from +21.20 per cent. Similarly, using the international world unit value for sheep cuts (bone in, frozen) the PSE changes to +19.18 per cent from +49.28 per cent. Table 6.3: PSE's for red meat in South Africa (1996 -1998) (percentage) Product 1996 1997 1998 Beef and Veal 10.77 13.64 21.20 Pork -27.43 -11.99 -0.03 Sheep meat 47.66 40.36 49.28 Source: Kirsten et al, 2000. Table 6.4 shows the PSE for red meat in selected OECD countries. Beef and sheep producers in the EU receive the highest subsidies as measured by the PSE, followed distantly by the US, Australia and New Zealand. EU pork producers, on the other hand, are not afforded the same luxuries. In fact Table 6.4 shows that, of the three red meats, pork is the least subsidised in the world with recorded PSE's of lower than 10 per cent since 1996. On average Canada recorded the highest PSE's for pork. From Table 6.4 it is evident that New Zealand is the least subsidised country as far as all three commodities are concerned. 162 The impact of liberalisation on the red meat industry Table 6.4: Red meat PSE's for selected countries in the world (1996 -1998) Country 1996 1997 1998 Beef EU 43 55.4 61.7 Australia 5.5 4.1 3.7 US 2.8 3 3.9 New Zealand 1.3 1 0.9 Sheep EU 66.4 63.9 64.7 Australia 4.6 3.8 3.5 US 4 4.2 3.9 New Zealand 0.3 0.3 0.4 Pork EU 1 1.8 7.8 Australia 3.1 3.3 3.2 US 3.1 3.4 3.3 New Zealand 2.3 2.2 2.3 Canada 7 4.6 6 Source: OECD, 1998b. It should be clear from the above that, taking into account the sensitivity of PSE's to changes in the reference price used, the PSE's for beef and pork compares very favourably with that recorded for the major overseas producers of these commodities, and hence the level of tariffs could be justified. On the other hand, the PSE's calculated for sheep meat do not compare very favourably with countries like Australia and New Zealand, South Africa's major trading partners as far as sheep meat is concerned. These two countries could argue that the 40 per cent tariff applicable to sheep meat imports is too high. However, one should consider the following factors: • The MFN principle does not allow countries to discriminate against each other on the basis of tariffs, i.e. South Africa is not allowed to lower sheep meat tariffs only for Australia or New Zealand. A reduction in tariffs will have to apply all other countries, which will increase import competition considerably. • When considering reductions in tariffs, one should also consider the impact on related industries. The reason for this is the strong cross-price effects evident in the red meat industry. In other words, a drop in tariffs for sheep meat will also have a considerable influence on the beef and pork industries, which can't 163 The impact of liberalisation on the red meat industry be justified on the basis that the PSE's for these two red meats compare favourably as far as the countries that are shown in Table 5.4 are concerned. • Since the democratic elections in 1994 Government has redirected its efforts in the agricultural sector to place much more emphasis on the developing agricultural sector as this sector was largely neglected previously. Regarding sheep, between 11 and 12 per cent of the total herd belongs to small-scale or emerging farmers. Of these farmers, 84 per cent reside in the Eastern Cape. In other words, a reduction in tariffs will greatly diminish efforts by Government to enhance sheep production among small-scale and emerging farmers, especially in the Eastern Cape. Added to this are the recent successes achieved in the wool industry as far as small-scale and emerging farmers are concerned (Moore, 2001). A reduction in tariffs will undoubtedly also have a negative impact on the developmental efforts in the wool industry since sales of sheep supplement the income obtained from wool. • The fact that South Africa is part of the SACU and the SADC should also be considered. A reduction in sheep meat tariffs will have wide ranging repercussions in the southern African region as a whole, especially for Namibia. It is clear from the above that tariffs on sheep meat imports can't merely be reduced on the basis that the PSE for the sheep industry does not compare favourably. In fact, these issues also hold for the beef and pork subsectors, even though their PSE's are favourable. A wide range of issues need to be considered. Van Schalkwyk et al (1995) also mention that the consumer may rightfully claim that food should be as cheap as possible, which implies that it may also be imported if this is cheaper than the locally produced product. The availability of affordable food within a policy of food security is also a priority of the current government. The question may therefore rightfully be asked about the extent to which the interests of producers and consumers differ or coincide. According to Van Schalkwyk et al (1995), the objectives of consumers and of producers are, viewed over the longer term, not necessarily opposed to each other, but may be 164 The impact of liberalisation on the red meat industry identical. This view must be seen in the light of factors influencing local producers' competitiveness vis-a-vis imported commodities, as well as how these factors are likely to vary in future. Van Schalkwyk et al (1995) regard the two main factors that will undoubtedly influence local competitiveness of local producers vis-a-vis imported products to be the world price of that product and the exchange rate (the impact of both of these factors will be quantified in this chapter). They pointed out that, in the medium to long term, it is in the consumer's interest to have locally produced products available because it will probably be competitive with imported products in the long term in view of the expected trend in world prices and exchange rates. In Chapter 2 the possible impact of liberalisation on world red meat prices was discussed. Several studies have shown that red meat prices are expected to increase considerably due to liberalisation. In other words, large-scale imports at lower prices could destroy current production capacity to such an extent that the red meat industry may not be able to meet demand in the near future when competitiveness has recovered. This entails that concentration on only a short-term view will not be in the interest of neither consumers nor producers of red meat. Several issues were discussed above that need to be quantified, e.g. the impact of a reduction in tariffs, an increase in the world price of red meat and the possible effect of a depreciation in the exchange rate. In addition, the possible impact of changes in population combined with a reduction in tariffs will also be quantified. This will be done in the following sections using the model developed in Chapter 4. 6.3 The impact of a total reduction in tariffs 6.3.1 Theoretical principles of applying tariffs The discussion in Chapter 2 only considered a trade regime where price formation takes place in the absence of any trade distortion measures such as tariffs, quotas, etc. This assumption is somewhat unrealistic, since the measures that distort trade are widely applied all over the world. The discussion of the theoretical concept underpinning trade in a world characterised by such measures will be restricted to a 165 The impact of liberalisation on the red meat industry small country case. This entails that the share of a small country in world imports, which is typically the case of the South African livestock sector, will affect the level of world supply negligible. In other words, meat imports from South Africa will not have any significant impact on world supplies of meat and, hence not on world prices. This situation is depicted in Figure 6.1. The small nation characteristic is reflected by the horizontal excess supply function for the rest-of-the-world, ES(R). If no trade distortion measures are applied by country A, the international and domestic price in country A will be equal to P1. At price P1 production in and imports to country A will equate to ab and be, respectively. This brings total consumption in country A to ac. Note that the intersection of the excess demand curve, EO, and the excess supply curve, ES(R), represent total imports into country A, i.e. bc is equal to df. Small Country Rest-of-the-world P P P2 g D ED ED* Q Qm Figure 6.1: Effects of an import tariff: A small nation case Source: Houck, 1992. However, suppose the government in country A decides to restrict imports from the rest of the world by means of a specific tariff, T. The effect of this restriction is that the per unit price of the product will increase, more specifically P1 + T = P2. In line with micro- economic theory, demand for the product in country A will decrease (ac to gj), whilst supply will increase (ab to gh). The level of imports in country A will also decline from bc to hj. The reason for these changes can be traced back to a displacement of the excess demand curve, EO, to a new position represented by the tariff-burdened excess 166 The impact of liberalisation on the red meat industry demand curve, EO·. The result is a reduction in imports of ef (df - de). Lower imports cause domestic prices in country A to increase along the original excess demand curve, EO. Thus, the result of the specific tariff is that domestic consumers in country A have to face higher priced (P2) imports ("international price") and will hence reduce their consumption of the product. Producers in country A will take advantage of the increase in price and start to produce more of the product. The above discussion focussed mainly on the shifts in demand, supply and prices as a result of the imposition of a tariff. Cognisance should, however, also be taken of the resulting welfare effects, i.e. the changes in consumer and producer surplus. The total change in welfare is represented by area agjc. As the discussion becomes clearer it will be evident that that there are losers and winners as a result of imposing a tariff. Producers will gain area aghb, which could be translated as an increase in producer surplus. The area mhjn that is taken away from consumers is transferred to the government in the form of tariff revenues. On the other hand, the area Ibhm lost by consumers goes to sellers of variable inputs. In other words, for producers to be able to expand production by hb, they will need to purchase additional variable inputs. These additional resources needed to expand production will not be available to other sectors, which constitute an opportunity cost, and hence area bhm can be considered as a deadweight loss. For this reason area bhm represents a decline in production efficiency. Area jnc is not redistributed to anyone in the economy and is also regarded as a deadweight loss, since it represents a real income loss to consumers. The above discussion may give the impression wrongly that trade distortion measures such as tariffs are all bad. However, there may be good reasons for imposing tariffs, or other trade restrictions, on imported goods. Houck (1992) mentions the following reasons why countries impose trade restrictions: • Protection of a new industry; • to protect national security; • to protect national health; 167 The impact of liberalisation on the red meat industry • protection against unfair foreign trade policy; ct to protect domestic programs; ct to protect balance of payments; • improvement of international terms of trade; ct to provide revenue; and • protection against painful economic adjustment. Although not all of the above reasons apply to the South African red meat industry, constructive and valid arguments have already been made in Section 6.2 regarding protection against unfair foreign trade policy, protection of domestic programs and protection against painful economic adjustment. 6.3.2 The impactof zerotariffs The impact of zero tariffs on red meat imports is derived by comparing the base-run situation discussed in Chapter 4 with a situation where all tariffs have been reduced to zero. Table 6.5 shows the impact of zero tariffs on the cattle subsector in different provinces in South Africa. In total, cattle numbers will reduce by 6.03 per cent or 118 989. The number of cattle slaughtered will reduce by 6.75 per cent or 151 931 animals. Producer prices will decline by 21.11 per cent or R1,60 per kg. The Eastern Cape and KwaZulu- Natal will experience the greatest fall in prices. The reason for mentioning this is that in these two provinces the number of cattle in the hands of small-scale or emerging farmers exceeds that of commercial farmers. Hence, efforts to commercialise the small-scale cattle industry should obviously start in these provinces, but any such efforts will be seriously hampered by zero tariffs. 168 The impact of liberalisation on the red meat industry Table 65T.h e i.rnpac t 0f zero ta·nft son the cattlein. dusttry Region Cattle supply (number) Cattle demand (number) Producer price R/kg) Base run Scenario Change Base run Scenario Change Base run Scenario change Western Cape 82407 78253 -5.04% 146647 136307 -7.05% 7.70 6.10 -20.72% NorthernCape 80437 75362 -6.31% 123686 115696 -6.46% 7.50 5.90 -21.27% FreeState 363323 341072 -6.12% 214892 201502 -6.23% 7.49 5.90 .-21.30% EasternCajl_e 337208 318171 -5.65% 263475 244539 -7.19% 7.35 5.75 -21.71% Kwazulu-Natal 406158 381942 -5.96% 363961 337926 -7.15% 7.45 5.85 -21.42% Mpumalanga 230499 216274 -6.17% 273306 255474 -6.52% 7.69 6.09 -20.76% Northern Province 170197 159919 -6.04% 137180 128873 -6.06% 7.61 6.01 -20.97% Gauteng 44642 41958 -6.01% 447720 417618 -6.72% 7.65 6.05 -20.87% NorthWest 257878 240809 -6.62% 281008 262009 -6.76% 7.59 6.00 -21.02% [rotaI 1972749 1853760 -6.03% 2251875 2099944 -6.75% 7.56 5.96 -21.11% Deviation -118989 -151931 -1.60 Table 6.6 shows the impact of a zero tariff scenario on the beef subsector in South Africa. Beef prices will, on average, decline by 27.88 per cent, whilst beef supply will decline by 8.11 per cent. Conversely, demand will increase substantially as a result of lower beef prices. The combined effect of a reduction in beef supply domestically and an increase in beef demand entails a drastic increase in imports. Table 66.Th e .impac t 0f zero tar!·ffs on the beef lIndusttrv Region Beef supply (tonl Beef demand (ton) Beef price (R/kg) Base run Scenario change Base run Scenario Change Base run Scenario change 'Nestern Cape 25663 23503 -8.42% 63445 85183 34.26% 12.77 9.12 -28.55% NorthernCape 21645 19954 -7.81% 11917 15862 33.10% 12.67 9.18 -27.59% FreeState 37606 34759 -7.57% 34075 45187 32.61% 12.69 9.24 -27.17% EasternCape 46108 42151 -8.58% 50208 67381 34.20% 12.79 9.15 -28.50% Kwazulu-Natal 63693 58253 -8.54% 69826 93757 34.27% 12.77 9.12 -28.56% Mpumalanga 47829 44067 -7.87% 48620 64739 33.15% 12.78 9.25 -27.63% Northern Province 24006 22235 -7.38% 22297 29500 32.30% 12.70 9.28 -26.92% Gauteng 78351 72023 -8.08% 125265 167214 33.49% 12.80 9.23 -27.91% NorthWest 49176 45183 -8.12% 28920 38651 33.65% 12.74 9.17 -28.04% Total 394077 362128 -8.11% 454573 607474 33.64% 12.74 9.19 -27.88% Deviation -31949 152901 -3.55 Table 6.7 shows the impact of a zero tariff scenario on the sheep subsector. 169 The impact of liberalisation on the red meat industry Table 67, Th e t'rnpac t 0f zero tar!'ffs on the sehep ,Industry Region Sheep supply (number) Sheep demand (number) Producer price (R/kg) Base run Scenario change Base run Scenario change Base run Scenario change Western Cape 523956 498423 -4.87% 1297722 1232018 -5.06% 11.76 10.24 -13.00% Northern Cape 1184503 1113382 -6.00% 1585265 1498747 -5.46% 11.00 9.47 -13.90% Free State 924448 877864 -5.04% 584044 552386 -5.42% 10.71 9.18 -14.29% Eastern Cape 1050895 999062 -4.93% 889929 841838 -5.40% 10.35 8.82 -14.77% Kwazulu-Natal 152274 144756 -4.94% 204434 193514 -5.34% 11.59 10.06 -13.20% Mpumalanga 296189 280462 -5.31% 141310 133532 -5.50% 10.65 9.12 -14.36% Northern Province 25328 24021 -5.16% 22435 21203 -5.49% 10.71 9.18 -14.29% Gauteng 16638 15775 -5.19% 237639 224831 -5.39% 11.24 9.71 -13.61% North West 106514 101166 -5.02% 145736 137822 -5.43% 11.06 9.53 -13.83% Total 4280745 4054911 -5.28% 5108514 4835891 -5.34% 11.01 9.48 -13.90% Deviation -225834 -272623 -1.53 The supply of sheep and the number of sheep slaughtered are expected to decrease by 5.28 per cent and 5.34 per cent, respectively. On average sheep prices are expected to drop by 13.90 per cent, with the largest decline in the Eastern Cape where, as stated previously, the number of sheep that reside in the hands of small-scale farmers are the largest. The results therefore provide proof for the argument made in Section 5.2 that a reduction in tariffs could seriously impede on development efforts in the sheep industry. Table 6.8 shows the impact of a total reduction of tariffs on the sheep meat subsector. Demand will increase substantially. This, combined with a decline in sheep meat supply, would result in an increase in sheep meat imports. The reason for this state of affairs could be traced back to the fact that, on average, sheep meat prices will decline by 28.56 per cent as a result of the removal of the tariff. 170 The impact of liberalisation on the red meat industry Table 68T.h e .impac t 0f zero tan·ffs on the sehep meat·Indus ttry Region Sheep meat supply (ton) Sheep meat demand (ton) Sheep meat price (R/kg) Base run Scenario change Base run Scenario Change Base run Scenario change ~estern Cape 22061 20825 -5.60% 21365 32951 54.23% 16.61 11.95 -28.09% Northern Cape 26950 25325 -6.03% 3739 5820 55.66% 16.75 11.92 -28.84% Free State 9929 9334 -5.99% 7638 11838 54.99% 16.77 11.99 -28.49% Eastern Cape 15129 14224 -5.98% 11495 17770 54.59% 16.69 11.97 -28.28% Kwazulu-Natal 3475 3270 -5.90% 22571 35120 55.60% 16.77 11.94 -28.80% Mpumalanga 2402 2256 -6.08% 9510 14764 55.25% 16.88 12.05 -28.62% Northern Province 381 358 -6.04% 4084 6340 55.24% 16.88 12.05 -28.62% Gauteng 4040 3799 -5.97% 30523 47385 55.24% 16.88 12.05 -28.62% North West 2478 2329 -6.01% 6233 9683 55.35% 16.84 12.01 -28.68% Total 86845 81720 -5.90% 117158 181671 55.06% 16.79 11.99 -28.56% Deviation -5125 64513 -4.79 Table 6.9 and 6.10 show the impact of a reduction of tariffs on the pig and pork industries, respectively. The number of pigs demanded for slaughter is expected to decrease by 4.64 per cent on average. The supply of pigs will decline with the same percentage. Pig prices will drop by 11.99 per cent on average or RO.69 per kg. Pork prices will decrease by 13.16 per cent as a result of a zero tariff on pork imports. This will, in turn, stimulate domestic demand for pork, but depress the supply of pork, resulting in increased imports of pork. Table 69. .. The impact 0f zero tar!·ffs on theplg.. Industtry Region Pig supply (number) Pig demand (number) Producer price R/kg) Base run Scenario Change Base run Scenario Change Base run Scenario Change Western Cape 334475 318787 -4.69% 334475 318787 -4.69% 6.02 5.28 -12.19% Northern Cape 29666 27941 -5.81% 25883 24628 -4.85% 5.52 4.83 -12.39% Free State 250451 238315 -4.85% 157838 150241 -4.81% 5.63 4.95 -12.13% Eastern Cape 159419 152613 -4.27% 153328 145355 -5.20% 5.43 4.75 -12.58% Kwazulu-Natal 331256 316260 -4.53% 372461 355566 -4.54% 6.03 5.35 -11.33% Mpumalanga 296974 283222 -4.63% 70614 67006 -5.11% 5.60 4.92 -12.20% Northern Province 182505 173882 -4.72% 134162 127279 -5.13% 5.63 4.95 -12.13% Gauteng 296355 282902 -4.54% 757763 724594 -4.38% 6.02 5.33 -11.36% North West 263320 250994 -4.68% 137897 131462 -4.67% 5.83 5.15 -11.71% Total 2144421 2044916 -4.64% 2144421 2044918 -4.64% 5.75 5.06 -11.99% Deviation -99505 -99503 -0.69 171 The impact of liberalisation on the red meat industry Table 610 The r"mpac t 0f zero tariOffs on th e por k"Industtrv Region Pork supply (ton) Pork demand (ton) Pork price (Rlkg) Base run Scenario Change Base run Scenario change Base run Scenario change !WesternCape 20069 18961 -5.52% 25251 31598 25.14% 10.38 8.98 -13.51% NorthernCape 1553 1465 -5.67% 4222 5243 24.18% 10.49 9.12 -13.01% FreeState 9470 8937 -5.63% 10334 12840 24.25% 10.46 9.09 -13.04% EasternCape 9200 8644 -6.04% 13739 17185 25.08% 10.40 9.00 -13.49% Kwazulu-Natal 22348 21157 -5.33% 18570 23048 24.11% 10.31 8.98 -12.97% Mpumalanga 4237 3985 -5.95% 12197 15226 24.83% 10.51 9.11 -13.35% Northern Province 8050 7570 -5.96% 4938 6176 25.07% 10.40 9.00 -13.49% Gauteng 45466 43121 -5.16% 41937 51823 23.57% 10.40 9.08 -12.67% NorthWest 8274 7822 -5.46% 8388 10404 24.03% 10.46 9.11 -12.92% Total 128667 121662 -5.44% 139576 173543 24.34% 10.42 9.05 -13.16% Deviation -7005 33967 -1.37 Table 6.11 shows the welfare implications of a total reduction of tariffs on the red meat industry. It is clear that consumers will experience considerable welfare increases. The largest gains will be accrued by Gauteng, KwaZulu-Natal, the Western Cape and the Eastern Cape. In total, welfare gains by consumers due to a total reduction of tariffs will amount to R2 829 mio. This translates into a 0.49 per cent increase in the real gross national income, which is very low. In respect of real disposable income, a total reduction of tariffs would add a mere 0.75 per cent. However, cognisance should be taken of the fact that a considerable proportion of the gains by consumers are merely a transfer from the national treasury to consumers. This transfer is represented by area mhjn in Figure6.1. Table 6.11 furthermore shows that producers will experience a drop in welfare if tariffs are reduced. The provinces that will experience the largest decline in producer welfare are the Free State, KwaZulu-Natal and the Eastern Cape. This is to be expected since these provinces contribute the largest proportion to livestock production. The total loss in producer welfare would amount to R868 mio. The loss in producer welfare amounts to 2.71 per cent of real gross farm income and 10.72 per cent of real net farm income, which is substantial. It is clear that a reduction of tariffs in the red meat industry would result in net welfare gains to society which are relatively small, but that the impact on the agricultural sector would be substantial. Nevertheless note should be taken that the above results do not 172 The impact of liberalisation on the red meat industry provide an overall insight into welfare gains or losses. The wider economic implications can only be investigated by a much more complicated model within the CGE framework, that falls beyond the scope of this study. Table 611 .. Change In we Ifare as a resu It of a t0taI reduction in tar! fts Region Consumer surplus Producer surplus Total monetatv chanae (Million rand) !western Cape 438 -56 Northern Cape 78 -59 Free State 199 -157 Eastern Caoe 305 -148 Kwazulu-Natal 465 -156 Mpumalanga 278 -98 Northern Province 122 -66 Gautena 772 -28 North West 172 -101 South Africa 2829 -868 The results discussed above clearly show the impact of a zero tariff situation on the domestic red meat sector. Not only will such a situation depress prices, but it will substantially reduce red meat production in South Africa, which could lead to income and job losses in the red meat industry. As mentioned in Section 6.2, the efforts by Government to commercialise or to improve the livelihoods of small-scale or emerging farmers could be hampered. Another issue of importance that relates to the results shown in this section is that South Africa clearly demonstrated its willingness to participate in FTA's, of which the SADC and EU-SA FTA's are the most recent examples. Government also made its intentions to negotiate a FTA with the MERCOSUR countries clear. The question that arises is what will be the impact if a decision is made to grant red meat imports preferential access under such agreements. Depending on the specific agreement, it could result in a two-tier situation. Firstly, if a portion of red meat imports is allowed to enter South Africa at' lower tariffs it would in principle have no or a very small impact on prices and quantities demanded and supplied. The reason for this is the fact that the marginal import tariff remains unchanged. In other words, only if the last ton of imports 173 The impact of liberalisation on the red meat industry enters South Africa at a lower tariff than formally applied there would be significant changes in prices and quantities. Secondly, within a FTA situation this could transpire easily. For instance, should South Africa allow MERCOSUR to export beef to South Africa at lower or no tariffs, it could mean that prices and quantities demanded and supplied will change from the status quo situation if MERCOSUR are in a position to fully meet South Africa's import requirements. This is not a far fetched scenario if one considers the increase in imports from these countries over the last two years. Should they, for example, only meet three-quarters of the import demand, the rest could easily be supplied by other countries with whom South Africa also has FTA's, such as the SADC and the EU - in the latter case agreements duty free or lower duties on, for instance, beef imports, must still be negotiated since it was put on the reserve list when the EU-SA FTA was concluded in 2000. Should South Africa grant the MERCOSUR countries preferential access to the South African red meat market, one can expect the EU to press hard for the same preferential access during the next round of negotiations. Given the powerful negotiating position of the EU it would be very difficult not to grant the EU the same preferential access. Hence, South Africa should carefully consider its tariff "strategy" when granting preferential access to its red meat market since preferential access to too many trade partners could result in a lower marginal tariff that will affect the red meat industry negatively. 6.4 The impact of an increasein theworld price of redmeatcommodities In Chapter 2 various studies were cited that indicated that world red meat prices are expected to increase due to the world-wide liberalisation of policies applied to the red meat sector. In this section the possible impact of such increases on the South African red meat sector will be quantified under the assumption that the price transmission from the rest of the world takes on the same magnitude as that between regions within South Africa. This may be a rigorous assumption but due to a paucity of data this assumption will have to suffice. 174 The impact of liberalisation on the red meat industry It should be noted that the price increases projected in the studies cited in Chapter 2 for beef, sheep meat and pork are higher than the price increase used. The reason for this is he fact that simulations of different price increases showed that a price increase above 10 per cent for beef, 18 per cent for mutton and 6 per cent for pork will result in zero imports, thus stabilising the domestic market through domestic demand and supply forces. Also note that the price increases are over and above the tariff that is applied. Table 6.12 shows the impact of a 10 per cent increase in the world price of beef on the cattle subsector. Producer prices will, on average, increase by 4.81 per cent. There will also be an increase in the number of cattle supplied and the number of cattle slaughtered. The increase in the number of cattle slaughtered can be derived from the fact that higher beef prices in the secondary industry create an incentive to supply more beef from domestic sources. This in turn creates a higher demand for slaughtered animals. Table 6.12: The impact of a 10 per cent increase in the world price of beef on the cattle subsector Region Cattle supply (number) Cattle demand (number) Producer price Rlkg) Base run Scenario change Base run Scenario change Base run Scenario change Western Cape 82407 83357 1.15% 146647 149860 2.19% 7.70 8.06 4.72% Northern Cape 80437 81598 1.44% 123686 125860 1.76% 7.50 7.86 4.85% Free State 363323 368412 1.40% 214892 218469 1.66% 7.49 7.85 4.85% Eastern Cape 337208 341562 1.29% 263475 266580 1.18% 7.35 7.71 4.95% Kwazulu-Natal 406158 411696 1.36% 363961 368892 1.35% 7.45 7.81 4.88% Mpumalanga 230499 233752 1.41% 273306 276205 1.06% 7.69 8.05 4.73% Northern Province 170197 172547 1.38% 137180 139206 1.48% 7.61 7.97 4.78% Gauteng 44642 45256 1.38% 447720 454292 1.47% 7.65 8.01 4.76% North West 257878 261782 1.51% 281008 285156 1.48% 7.59 7.95 4.79% Total 1972749 1999962 1.38% 2251875 2284520 1.45% 7.56 7.92 4.81% Deviation 27213 32645 0.36 The impact of a 10 per cent increase in the world price for beef on the South African beef subsector is shown in Table 6.13. Beef prices will increase by 6.35 per cent on average, whilst the demand for beef will drop by 7.59 per cent. Supply of beef will, on average, increase by 1.76 per cent. 175 The impact of liberalisation on the red meat industry Table 6.13: The impact of a 10 per cent increase in the world price of beef on the beef sub-sector Region Beef supply ~ton) Beef demand (ton) Beef price (R/kg) Base run Scenario change Base run Scenario change Base run Scenario change !western Cape 25663 26314 2.54% 63445 57724 -9.02% 12.77 13.73 7.52% NorthernCape 21645 22096 2.08% 11917 10947 -8.14% 12.67 13.53 6.79% FreeState 37606 38352 1.98% 34075 31369 -7.94% 12.69 13.53 6.62% EasternCape 46108 46787 1.47% 50208 46748 -6.89% 12.79 13.53 5.75% Kwazulu-Natal 63693 64749 1.66% 69826 64749 -7.27% 12.77 13.54 6.06% Mpumalanga 47829 48472 1.34% 48620 45362 -6.70% 12.78 13.50 5.59% Northern Province 24006 24435 1.79% 22297 20608 -7.58% 12.70 13.50 6.31% Gauteng 78351 79741 1.77% 125265 115850 -7.52% 12.80 13.60 6.27% NorthWest 49176 50053 1.78% 28920 26736 -7.55% 12.74 13.54 6.30% !Total 394077 400999 1.76% 454573 420093 -7.59% 12.74 13.55 6.35% Deviation 6922 -34480 0.81 Table 6.14 shows the impact of a 18 per cent increase in the world price of sheep meat on the sheep sub-sector. Sheep supply and the number of sheep slaughtered are expected to increase by 2.18 per cent and 2.19 per cent, respectively. Producer prices for sheep will, on average, increase by 5.88 per cent. Table 6.14: The impact of a 18 per cent increase in the world price of sheep meat on tehs heep su b-sec tor Sheep supply (number) Sheep demand (number) Producer price R/kg)Region Base run Scenario change Base run Scenario change Base run Scenario change WesternCape 523956 534484 2.01% 1297722 1325277 2.12% 11.76 12.41 5.50% NorthernCape 1184503 1213828 2.48% 1585265 1619650 2.17% 11.00 11.65 5.88% FreeState 924448 943656 2.08% 584044 596978 2.21% 10.71 11.35 6.04% EasternCape 1050895 1072267 2.03% 889929 909993 2.25% 10.35 11.00 6.25% Kwazulu-Natal 152274 155374 2.04% 204434 209286 2.37% 11.59 12.24 5.58% Mpumalanga 296189 302674 2.19% 141310 144539 2.29% 10.65 11.29 6.08% Northern Province 25328 25867 2.13% 22435 22925 2.18% 10.71 11.35 6.04% Gauteng 16638 16994 2.14% 237639 242729 2.14% 11.24 11.88 5.76% NorthWest 106514 108719 2.07% 145736 148881 2.16% 11.06 11.71 5.85% Total 4280745 4373863 2.18% 5108514 5220258 2.19% 11.01 11.65 5.88% Deviation 93118 111744 0.65 Table 6.15 shows the impact of a 18 per cent increase in the world sheep meat price on the domestic sheep meat sub-sector. This would result in an overall price increase of 11.74 per cent for the domestic market for sheep meat. Demand is expected to decline 176 The impact of liberalisation on the red meat industry substantially (-22.79%) as a result of the price increase. Supply of sheep meat will increase marginally by 2.42 per cent. This is due to the fact that only a marginal increase in domestic supply is needed to meet domestic demand. Note that exports are not modelled and therefore the increase in domestic supply on both sheep and sheep meat could be under-estimated. This applies only, if South Africa has access to markets overseas in order to take advantage of the increase in world prices for sheep meat. This again emphasised the importance of export markets, even though the country as a whole may be a net importer of sheep meat. In fact, this also holds for the other two red meats. Table 6.15: The impact of a 18 per cent increase in the world price of sheep meat on the sehep meat sub-sector Region Sheep meat supply (ton) Sheep meat demand (ton) Sheep meat price (Rlkg) Base run Scenario change Base run Scenario change Base run Scenario change ~estern Cape 22061 22580 2.35% 21365 16535 -22.61% 16.61 18.56 11.71% Northern Cape 26950 27596 2.40% 3739 2901 -22.41% 16.75 18.70 11.61% Free State 9929 10172 2.45% 7638 5916 -22.55% 16.77 18.72 11.68% Eastern Cape 15129 15506 2.49% 11495 8888 -22.68% 16.69 18.65 11.75% Kwazulu-Natal 3475 3566 2.62% 22571 17130 -24.11% 16.77 18.87 12.49% Mpumalanga 2402 2463 2.54% 9510 7334 -22.88% 16.88 18.88 11.85% Northern Province 381 391 2.62% 4084 3176 -22.23% 16.88 18.82 11.52% Gauteng 4040 4136 2.38% 30523 23738 -22.23% 16.88 18.82 11.52% North West 2478 2537 2.38% 6233 4844 -22.28% 16.84 18.79 11.54% Total 86845 88947 2.42% 117158 90462 -22.79% 16.79 18.76 11.74% Deviation 2102 -26696 1.97 Table 6.16 shows the impact of a 6 per cent increase in the world price of pork on the domestic pig sub-sector. Pig prices will, on average, increase by 3.16 percent. Pig supply and the number of pigs slaughtered will both increase by 1.20 per cent for the country as a whole. The increase in the number of pigs slaughtered is attributable to the supply response in the secondary industry as a result of higher pork prices. 177 The impact of liberalisation on the red meat industry Table 6.16: The impact of a 6 per cent increase in the world price of pork on the pig su b-sector Region Pig supply (number) Pig demand (number) Pig price (Rlkg) Base run Scenario change Base run Scenario Change Base run Scenario change Western Cape 334475 340835 1.90% 334475 340835 1.90% 6.02 6.32 4.99% Northern Cape 29666 30064 1.34% 25883 26194 1.20% 5.52 5.68 3.02% Free State 250451 253252 1.12% 157838 159773 1.23% 5.63 5.80 2.96% Eastern Cape 159419 160990 0.99% 153328 156765 2.24% 5.43 5.60 3.07% Kwazulu-Natal 331256 334717 1.04% 372461 376946 1.20% 6.03 6.20 2.76% Mpumalanga 296974 300148 1.07% 70614 71228 0.87% 5.60 5.77 2.98% Northern Province 182505 184495 1.09% 134162 135334 0.87% 5.63 5.80 2.96% Gauteng 296355 299460 1.05% 757763 764217 0.85% 6.02 6.18 2.77% North West 263320 266165 1.08% 137897 138835 0.68% 5.83 6.00 2.86% !Total 2144421 2170126 1.20% 2144421 2170127 1.20% 5.75 5.93 3.16% Deviation 25705 25706 0.18 Table 6.17 shows the impact of a 6 per cent increase in world pork price on the domestic pork sub-sector. As was expected domestic demand will, on average, decrease (-6.47%) as a result of an overall increase in domestic pork prices (3.33%) due to an increase in the international pork price. Higher domestic pork prices will also cause supply to increase, even though there is a decline in demand. The end result is lower imports of pork meat. Table 6.17: The impact of a 6 per cent increase in the world price of pork on the por k sub-sector Region Pork supply (ton) Pork demand ton) Pork price (RI~g) Base run Scenario change Base run Scenario Change Base run Scenario change !western Cape 20069 20518 2.24% 25251 22677 -10.19% 10.38 10.95 5.48% Northern Cape 1553 1575 1.42% 4222 3978 -5.78% 10.49 10.81 3.11% Free State 9470 9605 1.43% 10334 9728 -5.86% 10.46 10.79 3.16% Eastern Cape 9200 9429 2.49% 13739 12609 -8.22% 10.40 10.86 4.42% Kwazulu-Natal 22348 22659 1.39% 18570 17465 -5.95% 10.31 10.64 3.20% Mpumalanga 4237 4281 1.04% 12197 11586 -5.01% 10.51 10.79 2.69% Northern 8050 8134 1.04% 4938 4688 -5.06% 10.40 10.69 2.72%Province Gauteng 45466 45931 1.02% 41937 39817 -5.06% 10.40 10.68 2.72% North West 8274 8344 0.85% 8388 8002 -4.60% 10.46 10.72 2.48% Total 128667 130476 1.41% 139576 130550 -6.47% 10.42 10.77 3.33%_11 Deviation 1809 -9026 0.35 178 The impact of liberalisation on the red meat industry Table 6.18 shows the welfare implications in South Africa of an increase in world prices of red meat. The losses in welfare to consumers are greater than the gains in welfare by producers. If the loss in consumer welfare is related to real disposable income it would amount to 0.16 per cent. However, if the gains by producers are related to net farm income it constitutes a gain of 2.84 per cent. What is important to note is that an increase in prices would result in net welfare losses to society. However, as was stated in the previous section, an exact estimate of welfare losses or gains would require a much more complex model. Table 6.18: Change in welfare as a result of an increase in world prices for red meat on Consumer surplus Producer surplus Total monetary chanae (Million rand) Western Cape -109 18 Northern CaDe -18 20 Free State -44 42 Eastern Cape -62 40 Kwazulu-Natal -100 38 MDumalanaa -54 25 Northern Province -26 16 Gautena -161 7 North West -35 25 South Africa -607 230 The above discussion shows that an increase in the world price for red meat will definitely favour the South African red meat industry. Cognisance should, however, be taken of the following: - The analysis was restricted to the assumption of homogeneous commodities. In other words, commodities were assumed to be perfect substitutes in the sense that consumers regard the imported commodity as exactly the same as the domestically produced commodity. In reality the situation is much more complex, and for this reason it would be unrealistic to conclude that an increase in world prices to the levels investigated will lead to a total displacement of imports by domestic produce. In any case, minimum market access requirements as stipulated under the WTO require that countries still 179 The impact of liberalisation on the red meat industry import the amount of a commodity that was stipulated in its country schedule submitted during the Uruguay Round. - The model used in this study does not account for the possibility of exports of red meat products by South Africa. The implication is that the model does not allow domestic producers to take advantage of higher world prices through increased exports. In other words, supply of beef, sheep meat and pork is restricted to such levels that will balance the domestic market. Thus, should export be introduced, one might see a higher supply response than indicated at present. On the other hand, this would depend on the extent to which the red meat industry is currently geared for exports. In Chapter 3 it was shown that export opportunities do exist for red meat exports by South Africa, but that these opportunities have not yet been utilised. This could be an indication that the South African red meat industry is at present not geared for exports, an issue that should receive serious attention if the red meat industry wishes to take advantage of opportunities in a liberalised trade environment. Having said this, the results provided in this section may not have under-estimated the supply response as one might expect, but this situation may change as the industry re-orientates itself to be more export orientated. 6.5 The impact of a depreciation of the exchange rate on the South African red meat industry The South African Rand has performed dismally against most major international currencies during the past decade. This was the result of various factors, internationally and domestically. Although it falls beyond the scope of this study to investigate the reasons for the Rand's poor performance, some factors that had an influence include, amongst others, perceptions of investors, monetary controls and interventions by the Reserve Bank, the political climate, the performance of other currencies on the international market, etc. (Jooste, Van Schalkwyk, Geldenhuys, and Van Den Berg, 2000). From 1985 to 2001 the Rand depreciated by 307 per cent against the US Dollar, of this 123 per cent were since the beginning of 1996. The same trend was evident with 180 --------------------------------------------------------------------------~ The impact of liberalisation on the red meat industry respect the AUS$ and the £. Sëdersten and Reed (1994) state that a devaluing of the exchange rate changes the prices of domestically produced traded goods relative to the prices of the same goods produced in other countries. That is, it reduces the relative prices of the devaluing country's goods and of its import competing goods, which will, in time, increase the volume of exports and decrease the volume of exports. Apart from the fact that changes in the exchange rate influence the world price at which commodities, such as red meat, are imported or exported, it also has an influence on the price of inputs used in the production process. Hence, the price of tradable inputs must also be adjusted with the exchange rate in order to gauge the effect of exchange rate changes fully, but this falls beyond the scope of this study. In order to measure the impact of depreciation of the exchange rate on the South African red meat industry, a depreciation of 40 per cent of the Rand against the US$ was assumed. The results are shown in Table 6.19. The results are very similar to those in Tables 6.12 to 6.17, mainly due to the fact that a depreciation of the Rand results in higher prices for imported red meat. Table 619 Th e 0Impact 0f a 40 percen td enreciOaf Ion 0fth e exchange rate Primary Base run Scenario Change Base run Scenario Change Base run Scenario Change industry Supply (number) Demand (number) Price (RIkSI) Cattle 1972749 2000105 1.39% 2251875 2284653 1.46% 7.56 7.93 4.87% Sheep 4280745 4375510 2.21% 5108514 5222230 2.23% 11.01 11.65 5.88% Pigs 2144421 2170311 1.21% 2144421 2170310 1.21% 5.75 5.93 3.16% Secondary industry Supply (tons) Demand (ton) Price (Rlkg) Beef 394077 401026 1.76% 454573 419920 -7.62% 12.74 13.56 6.39% Sheep meat 86845 88983 2.46% 117158 89996 -23.18% 16.79 18.79 11.95% Pork 128667 130490 1.42% 139576 130487 -6.51% 10.42 10.77 3.35% It should be noted that the 40 per cent depreciation in the Rand is not transmitted in full to the domestic red meat industry. The reason for this is the fact that the imports would effectively be reduced to zero since it becomes more expensive than domestically produced red meat. Price behaviour is then solely determined by domestic supply and demand factors, e.g. demand decreases for red meat due to an increase in prices, but 181 The impact of liberalisation on the red meat industry suppliers respond positively to the price increase. The dynamics in supply and demand on the domestic market would then determine the new equilibrium price. As was stated previously this may be a oversimplification of the market situation if international prices increase, whether it is due to liberalisation or a devaluation of the Rand against other currencies. The reason is that the current model does not make provision for exports. In reality one would expect exports to increase if world market prices become more favourable, but as stated previously, this is not expected over the short run since South Africa is not fully geared for exports. It is furthermore important to note that although competitiveness improves with a depreciation of the exchange rate, this does not imply improved efficiency on farm level. Thus, the increase in competitiveness is exogenous in nature and out of the producer's control. Relying entirely on exogenous factors for competitiveness it is a recipe for failure. Producers and agribusiness must look beyond the borders of their own industries when evaluating the influence of changes in the exchange rate. When the exchange rate depreciates it also influences the rest of the economy. Continued depreciation of the exchange rate will eventually exert pressure on the inflation rate to increase, which in turn will exert upward pressure on interest rates. Higher interest rates culminates in lower expenditure on food as income has to be directed to higher debt repayment. This will eventually lead to a slack in economic growth. Thus, a depreciation in the exchange rate may be favourable over the short term, but in the long term will lead to a decline in economic growth. As a simple example, the consumption of red meat is very closely related to consumers' per capita income, which is again closely related to the economic growth rate. Thus, should the economic growth rate be negatively affected by a continued depreciation in the exchange rate, consumers' per capita income will also be negatively influenced. This will lead to lower demand for red meat. It should be clear from this discussion that competitiveness gained by a depreciating exchange rate may not be sustainable over the long run. 182 The impact of liberalisation on the red meat industry 6.6 The impact of the abolishment of Lomé on the South African beef industry The Lomé Convention and the benefits it holds for ACP countries, and particularly other southern African countries in respect of beef, were discussed in Chapter 2. In this section a scenario whereby Namibia and Botswana are no longer afforded their preferential access to the EU market is tested in order to determine the impact on the South African beef industry. The underlying assumption of this scenario is that both these countries decide to export their surplus beef (Lomé quotas) to South Africa over the short run, i.e. processing of beef still resides in the countries mentioned whilst they investigate other markets for exports. Table 6.20 shows the results. Table 62.0 : Imoac t 0f th ea b0uIShmen t 0f Lomeon the Sou th Af'rlcan beef'Industry Primary Base runlscenarlo] change Base runlScenariol change Base runlêcenarlo] change industry Supply (numbers) Demand (numbers) Price (Rlkg) Cattle 1972749 11971620 I -0.06% 2251875 I 2252596 I 0.03% 7.56 I 7.54 I -0.18% Secondary industry Supply (tons) Demand (ton) Price (Rlkg) Beef 394077 I 393829 I 0.02% 454573 1 456953 I 0.11 % 12.74 -r 12.73 I -0.15% It is clear that the effect on the South African market is minimal. Prices of beef and cattle reduce by less than 0.5 per cent. It should also be noted that these two countries could export beef free of tariffs to South Africa. Thus, increased imports from these two countries will not have any effect on the marginal tariff level at the levels used in this scenario, and hence the relatively small effect on domestic beef prices. 6.7 An alternative tariff regime for red meat in South Africa It is commonly known that the red meat industry has been experiencing problems with respect to fraudulently invoiced imports to avoid ad valorem tariffs. It was for this reason that the red meat industry applied for a fixed tariff on red meat imports. The question that arises is what should the level of the fixed tariff be in order to maintain the status quo. The model developed in Chapter 4 could be used to provide answers to this 183 The impact of liberalisation on the red meat industry question. By introducing fixed tariffs and through an iterative procedure calibrate the model to reflect the status quo situation the fixed tariffs were determined. The results are shown in Table 6.21. Table 6,21 F"Ixed tan'ffs for the 5outh Afrr'can red meat'Industrv Commodity Fixed tariff equivalent (RIton) Beef 3470 Sheep 4700 Pork 1355 6,8 The impact of changes in the population on the red meat industry In this section the impact of population growth until 2004 on the red meat industry is investigated. A combination of population growth and a reduction in tariffs are also quantified. Due cognisance is also taken of the possible impact of HIV/AIDS on population growth. The reason for using specifically 2004 is that a recent study by Balyamujura, Jooste, Van Schalkwyk, Geldenhuys, Crew, Carstens, Bopape and Modiselle (2000) estimated the divergence between population growth rates from a "With HIV/AIDS" and "Without HIV/AIDS" point of view. In addition, the impact of an increase in per capita income is also considered. Cognisance should be taken of the fact that this section only uses total population figures, i.e. no distinction is made between different population groups. The reason for this is that there is little data available regarding the divergence between population growth rates per population group from a "With HIV/AIDS" and "Without HIV/AIDS" point of view. The average population growth rate in South Africa is expected to continue declining over the coming decades. The growth rate of the African population has decreased from 2,45 per cent in 1990/91 to an estimated 1,65 per cent in 2000/2001, while that of the total population has dropped from 2,13 per cent to 1,43 per cent over the corresponding period (CIAMD, 2000). The fact of the matter is however that population will continue to grow in the future, which will put increasing pressure on natural resources to fulfil in humans desire to meet at least their minimum nutritional requirements. 184 ~-------------------------------------------------------------------------~ The impact of liberalisation on the red meat industry The impact of HIV/AIDS is of particular importance when one considers further population trends. According to Van Aardt, Van Tonder and Sadie (2000)\ the South African population will number between 46 to 70 million in 2020 (see Figure 6.2), depending on the impact of AIDS, declining fertility rates and migration. Fractlle 100.0 0.975 90.0 80.0 0.8 e- ~ 70.0 0.6g Median c 60.0 0.4.~ Ri 0.2 :; 50.0 e, a0. 40.0 0.025 30.0 20.0 10.0 0.0 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Year Figure 6.2: Population projection, 1995 - 2050 Source: Van Aardt ef al, 2000. It is also important to note that the impact of HIV/AIDS is not restricted to the individual infected. The impact of HIV/AIDS is much broader in that it has demographic, economic, social and developmental consequences. However, considering all these issues falls beyond the scope of this study, but is discussed comprehensively by Balyamujura et al (2000). I Van Aardt, Van Tonder, and Sadie (1999) performed a long-term projection for the South African population from 1996 onwards. Demographers would question the usefulness of such an exercise due to the vast number of uncertainties regarding key aspects such as: the true size and age distribution of the South African population in 1996; the magnitude and future impact that AIDS will have, and the number of immigrants and emigrants (migration). Hence, although not meant to produce accurate projections, the demographic model used in Van Aardt's research can produce useful plausible orders of magnitude as well as clear population trends. 185 The impact of liberalisation on the red meat industry Using the ASSA 600 model, Balyamujura et al (2000) estimated the possible impact of HIV/AIDS on population growth rates for 2004 (see Table 6.22). Continuing the present HIV/AIDS infection rate, South Africa's population would be 48.5 million in 2004. From a "Without HIV/AIDS" point of view the population would have been 50.5 million people. This translates into a 4.96 per cent difference in the growth of the population. This difference in population growth rates was used in this study to reflect the impact of HIV/AIDS on the consumption of red meat in South Africa for 2004. Since 1996 is used as base year, population growth had to be calculated from 1996 to 2004. In this regard population estimates by Van Aardt et al (2000) was used. According to them, the population growth rate between 1996 and 2004 would be 12.7 per cent. Table 62.2 Popu Iaf Ion proj_.ecrlons for 2004 and 2009 Description 2004 Without AIDS With AIDS Population 50533912 48450876 Population with HIV/AIDS - 7901 546 Normal Death 353836 341 762 AIDS Death - 609810 Total Death 353836 951 572 New InfectionIYear - 756754 New AIDS Sick - 748713 Cumulative AIDS Death - 2715075 Birth Rate 230% 229% Death Rate 070% 1 96% Dependency Ratio 576% 59 1% Source: Balyamujura et a', 2000. As mentioned, the possible changes of per capita income on the red meat industry will also be investigated. Van den Berg (1996) as cited by Nieuwoudt (1998) shows that under a scenario of total income growth of 3 per cent and 5 per cent, the per capita incomes of various population groups are expected to increase (see Table 6.23). Nieuwoudt (1998) also cited McGrath (1996) and Spies (1996) with respect to changes in real per capita income growth under different scenarios. It was, however, decided to use the estimates by Van den Berg (1996) since it distinguishes between the different population groups, i.e. his estimates indicate different increases in real per capita income for all the different population groups. This is important since consumption patterns differ between different population groups, and hence different population 186 The impact of liberalisation on the red meat industry groups will also use increases in per capita income in different ways when purchasing food (red meat). Table 620 3 Grow th In rea per camOta 00 Income Population group Growth in real per capita income 5 per cent 3 per cent 1per cent Asians 3.3 2.0 1.0 Blacks 6.1 3.7 -1.5 Coloureds 4.1 2.7 1.5 Whites 1.4 0.1 -0.3 Source: Van den Berg, 1996 as cited by Nieuwoudt, 1998. Nieuwoudt (1998) however, expressed his doubts regarding whether a high-growth scenario of 5 per cent would result in such high increases in real per capita income as estimated by Van den Berg. But for the sake of consistency it was nevertheless decided to make use of Van den Berg's estimates. Nieuwoudt (1998) also states that a high-income scenario would probably overestimate demand since income elasticities will generally decline with high per capita income growth. Thus, even though this study investigates the impact of a high-income growth situation, the result of such a scenario must be interpreted with caution. The income elasticity of red meat in respect of the demand for different red meat products by different population groups is an important factor when predicting the response of consumers when their income changes. Table 6.24 shows the income elasticities for different red meats as estimated by Nieuwoudt (1990). Table 624 00 0 Income elasticities for red meat for dOIff erent population groups 1990 Product Metropolitan Rural Blacks Asians Blacks Coloureds Whites Beef 0.65 1.04 0.70 0.34 1.33 Pork 0.40 0.00 0.60 0.32 0.25 Muttonand aoat meat 1.65 1.30 0.65 0.23 1.52 Source: NIeuwoudt, 1990. 187 The impact of liberalisation on the red meat industry Note should be taken of the low income elasticities of pork for blacks. The implication of this is that a very small proportion of increases in the per capita income of blacks will be used to purchase additional pork on a per capita basis. Since this study only accounts for total population it was necessary to derive aggregated (weighted) income elasticities for the different red meats. This was done by using the ratio between total expenditure per product group and the expenditure per population group. The calculated aggregated income elasticities for beef, pork and sheep meat are 0.77,0.28 and 0.79 respectively, and was used in this study. Table 6.25 shows the impact of population growth on the red meat industry. As stated, two different population growth rates were used in order to gauge the possible impact of HIV/AIDS. In the "Without HIV/AIDS" scenario demand for beef, sheep meat and pork will increase with 12.01 per cent, 12.22 per cent, and 11.92 per cent respectively. In the "With HIV/AIDS" scenario demand will only increase by 7.19 per cent, 7.31 per cent and 7.28 per cent for beef, sheep meat and pork, respectively. It should also be noted that the increase in demand for the different red meat products is only met marginally by increases in domestic supply. Most of the increase in demand is met by overseas imports. Similar results were found by Nieuwoudt (1998). Also, prices of red meat on the domestic market only show marginal increases. The reason for this state of affairs is the fact that red meats have relatively low supply elasticities as a result of biological production attributes and are hence not able to respond to increases in demand as rapidly as one might want too. Furthermore, cognisance should be taken of the fact that domestic prices are also a function of international prices, i.e. any expected increase in domestic prices due to an increase in demand will be dampened by the level of international prices. This also results in supply increases not being as high as what one might expect, since prices for red meat on the domestic market only increase marginally. 188 The impact of liberalisation on the red meat industry Table 6.25: Impact of population growth on the red meat industry (2004) Product Base run Scenario Change Base run Scenario Change Base run Scenario Change Supply (tons) Demand (ton) Price (R/kg) Growth in _j)_opulation of without AIDS (12.7%) Beef 394077 394720 0.16% 454573 509150 12.01% 12.74 12.83 0.64% Sheep meat 86845 86887 0.05% 117158 131474 12.22% 16.79 16.81 0.15% Pork 128667 128894 0.18% 139576 156213 11.92% 10.42 10.45 0.28% Growth in population with AIDS (7.74%) Beef 394077 394591 0.13% 454573 487272 7.19% 12.74 12.81 0.48% Sheep meat 86845 86883 0.04% 117158 125728 7.31% 16.79 16.81 0.13% Pork 128667 128803 0.11% 139576 149742 7.28% 10.42 10.45 0.21% Table 6.26 shows the impact of an increase in per capita income on the red meat industry. Demand increases are as expected. Note that the increase in pork consumption is lower than the increases in demand for beef and sheep meat. This can be attributed mainly to the fact that the aggregated income elasticity is considerably lower for pork than it is for the other two red meats for reasons already explained. As was the case in the population growth scenario there is limited supply response domestically and therefore the increases in demand is met mainly by imports. Prices also change marginally, if at all, due to the fact that most of the demand increase is met by imports. Table 6.26: The impact of different per capita income growth scenarios on the red meat Ilndustry Base run Scenario Base run Scenario Change Base run ScenarioProduct Supply (tons) Demand (tons) Price (R/kg) Growth in income of 3.18 percent Beef 394077 394521 454573 463636 1.99% 12.74 12.80 Sheep meat 86845 86847 117158 120081 2.49% 16.79 16.79 Pork 128667 128675 139576 140780 0.86% 10.42 10.43 Growth in income of 5.35 percent Beef 394077 394575 454573 470975 3.61% 12.74 12.81 Sheep meat 86845 86859 117158 121900 4.05% 16.79 16.79 Pork 128667 128707 139576 141480 1.36% 10.42 10.43 Table 6.27 shows a combination of different scenarios, namely an increase in population, a reduction in tariffs and an increase in the world price, as discussed previously. It is clear that an increase in population and the world price will soften the 189 The impact of liberalisation on the red meat industry impact of a total reduction in tariffs. However, it should be noted that the impact of a zero tariff regime is still significant. Table 6.27: Combined effect of a change in population, reduction in tariffs and an Increase I.n th ewor Id price 0f red meats Product Base run Scenario change Base run Scenario change Base run Scenario change Supply (Number/ton) Demand (Number/ton) Price (Rlkg) Growth in population of 7.74% with AIDS, total reduction in tariffs and increase in world price Cattle 1972749 1886095 -4.39% 2251875 2140582 -4.94% 7.56 6.39 -15.40% Beef 394077 370691 -5.93% 454573 610146 34.22% 12.74 10.15 -20.32% Sheep 4280745 4154858 -2.94% 5108514 4955801 -2.99% 11.01 10.12 -8.02% Sheep meat 86845 83976 -3.30% 117158 165238 41.04% 16.79 14.09 -16.05% Pigs 2144421 2086706 -2.69% 2144421 2086706 -2.69% 5.75 5.34 -7.03% Pork 128667 124602 -3.16% 139576 171678 23.00% 10.42 9.62 -7.70% Growth in population of 12.7% without AIDS, total reduction in tariffs and increase in world price Cattle 1972749 1886343 -4.38% 2251875 2140463 -4.95% 7.56 6.40 -15.34% Beef 394077 370678 -5.94% 454573 638088 40.37% 12.74 10.16 -20.30% Sheep 4280745 4155032 -2.94% 5108514 4956011 -2.99% 11.01 10.12 -8.02% Sheep meat 86845 83978 -3.30% 117158 172790 47.48% 16.79 14.09 -16.03% Pigs 2144421 2086727 -2.69% 2144421 2086727 -2.69% 5.75 5.34 -7.03% Pork 128667 124604 -3.16% 139576 179574 28.66% 10.42 9.62 -7.70% 6.9 Conclusions This chapter investigated the possible impact of liberalisation on the red meat industry in South Africa. The results obtained in this chapter can be summarised as follows: • Reducing tariffs on red meat imports to zero will lead to a substantial drop in red meat prices, which also has implications for production and processing of red meat products. Welfare gains by consumers due to a total reduction of tariffs will amount to R2 829 mio, whilst the total loss in producer welfare would amount to R868 mio. However, cognisance should be taken of the fact that a significant proportion of the gains by consumers are merely a transfer from the national treasury. Finally, the red meat industry should consider its tariff strategy carefully when it comes to granting preferential access to other countries, since it could ultimately lead to a reduction in the marginal tariff, to the detriment of local producers. 190 The impact of liberalisation on the red meat industry • Increases in the world price of red meat due to liberalisation or a depreciation of the exchange rate will benefit the South African red meat industry. However, the red meat industry should not rely merely on external factors to make it more competitive internationally. What is needed is a consumer- export orientated strategy backed by a well-functioning supply chain to take advantage of marketing opportunities, both domestically and internationally. • The abolishment of the Lomé Convention will not have any severe repercussions for the beef sub-sector in South Africa. • Growth in population is a more important determinant of growth in demand for red meats than growth in per capita income is, or at least this will hold over the short to medium term. Secondly, increases in demand are met mainly by overseas imports due to the inherently slow supply response of the industry over the short to medium term. However, an important issue of which cognisance should be taken is that off-take rates in the developing sector are very low, i.e. should the developing sector be in a position to increase its off-take rate it could take advantage of the increase in demand. Hence, given the expected increases in the demand for red meat in South Africa, government and the private sector should seriously consider additional programmes and initiatives to improve productivity (off-take) in the developing red meat industry. This would greatly enhance welfare in rural areas, especially in the Eastern Cape and KwaZulu-Natal. This could, however, not be done in isolation. The red meat industry needs to consider the efficiency of the red meat value chain and ways to improve the image of red meat amongst consumers. • Finally, the combined effect of an increase in population size and world prices will not be sufficient to offset the negative effects on the red meat industry of a total reduction of tariffs. 191 CHAPTER 7 CONCLUSIONS AND RECOMMENDATIONS 7.1 lntroductlon Trade liberalisation has become a common phrase in the vocabulary of role players involved in the agricultural sector. This is not surprising if one considers the important implications of trade liberalisation, and the consequences for agriculture in South Africa. This is no different for the red meat industry in South Africa. It is therefore of the utmost importance that the possible impact of liberalisation is quantified in order to provide answers to pressing questions, such as what will be the impact of further tariff liberalisation, what will happen to international prices of red meat and what will be the impact on the domestic red meat industry, etc. This study concerned itself with investigating such issues. The methodological approach adopted relates to the spatial partial equilibrium framework used by Takayama and Judge (1971). The rest of this chapter will summarise the conclusions drawn from this study, after which recommendations will be made. The last part of this chapter will highlight issues for further study. 7.2 Major conclusions drawn from this study 7.2.1 International red meat trade • Bovine meat From 1995 to 1999 the value of exports of bovine carcasses and half carcasses (fresh or chilled) decreased by 4 per cent, whilst the quantity exported remained the same. For bovine cuts (bone in, fresh or chilled) and bovine carcasses and half carcasses (frozen) annual growth in the value and quantity exported was negative from 1995 to 1999. Bovine cuts (boneless frozen), which are the most prominent bovine 192 Conclusions and recommendations meat product in terms of quantity exported, also experienced negative growth in the value of exports between 1995 and 1999. Only bovine cuts (boneless, fresh or chilled) saw growth in both the value and the quantity exported. Imports of bovine carcasses and half carcasses (fresh or chilled) in the world showed no growth, whilst the value of imports declined by 6 per cent between 1995 and 1999. The value and quantity of bovine cuts (bone in, fresh or chilled) and bovine carcasses .and half carcasses (frozen) declined from 1995 to 1999. Conversely, imports of bovine cuts (boneless, fresh or chilled) saw positive growth in terms of both value and quantity. In terms of bovine cuts (boneless, frozen), the value of imports dropped, whilst the quantity imported improved. • Pork All the pork products have shown growth in quantities exported from 1995 to 1999. The largest growth was reported for swine carcasses and half carcasses (frozen). In terms of the value exported, carcasses and half carcasses (fresh or chilled), hams, shoulders and cuts thereof (bone in, fresh or chilled) and swine cuts (frozen) experienced negative growth from 1995 to 1999, even though the quantity exported was positive. This translates into a lower per unit value of these products over the mentioned period and is probably a result of increased competition between exporters. World imports of pork products increased from 1995 to 1999. However, in terms of the value of imports, only hams, shoulders and cuts thereof (bone in, frozen) experienced positive growth. Swine carcasses and half carcasses (fresh or chilled) experienced the largest drop in value of imports. The decline in the value of imports of swine cuts (frozen), the most important imported pork product, is largely attributed to negative growth in the value of imports in Japan and Germany; together they account for 57.45 per cent of world imports of this product. 193 Conclusions and recommendations • Sheep meat Exports of lamb carcasses and half carcasses (fresh or chilled) and sheep carcasses and half carcasses (frozen) experienced negative growth in terms of value and quantity exported from 1995 to 1999. Sheep cuts (bone in, fresh or chilled) and sheep cuts (bone in, frozen) both experienced growth in value and quantity exported between 1995 and 1999. This growth can be attributed mainly to the export performance of New Zealand and Australia. World imports of lamb and sheep products, lamb carcasses and half carcasses (fresh or chilled) and sheep carcasses and half carcasses (frozen) did not perform well over the period 1995 to 1999. As far as sheep carcasses and half carcasses (frozen) are concerned, negative growth in value and quantity imported was fuelled by Korea, Malaysia, Oman, Taiwan, the Russian Federation, Jamaica and the US. Growth in respect of the value of imports and quantity imported of sheep cuts (bone in, fresh or chilled) can be attributed to the fact that the top 17 importers of this product experienced positive growth in both value and quantity imported. Sheep cuts (bone in, frozen) also experienced positive growth in value and quantity imported. 7.2.2 Impact of the Uruguay Round on red meat prices It should be noted that under the auspices of the WTO, liberalisation would affect world production, trade patterns, prices of agricultural products, as well as the general welfare of countries. Several studies have attempted to quantify the affects of trade liberalisation on world production, trade patterns and prices of red meat products by using different modelling frameworks. Although the models cited in this study differ in terms of assumptions used and manner in which liberalisation is simulated, they all predict an increase in world prices of red meat. It is expected that sheep meat will show the most notable increases in prices, followed by pork and beef. An important aspect that came to light is that when only industrialised countries liberalise trade, increases in red meat prices will be lower than when both industrialised and developing countries liberalise trade. 194 Conclusions and recommendations 7.2.3 Issues of importance in preparing for new WTO negotiations a) Issues such as export subsidies, other forms of export competition, unfair pricing practices, and dumping require urgent attention. In this respect Article 20 is of particular importance. Article 20 provides for the negotiations to involve further commitments which would be necessary to achieve long-term liberalisation objectives, i.e. the agricultural negotiating mandate will incorporate commitments for further liberalisation of restrictions under market access, domestic support and export subsidies, and will also cover topies that go beyond reductions in support and trade barriers, such as strengthened rules and disciplines. b) The Peace Clause also requires urgent reconsideration. The importance of the Peace Clause lies in the fact that it stops members from bringing challenges against export subsidies, green and blue box, and de minimus payments. Removal of the Peace Clause would mean that most of the subsidies that are allowable in the AoA could become subject to challenge in the Disputes Settlement Mechanisms of the WTO if a member can show injury. Hence, countries that rely on these subsidies would have a strong interest in negotiating an extension of Article 13, whilst countries that may be harmed by such subsidies would have a strong interest in insisting on the termination thereof. Another issue that is deemed very important is the rules on Tariff Rate Quotas (TRQ) administration and allocation. The reason for this is as follows: There are no guarantees that the TRQs will lead to real improvements of market access, and hence that they will affect the actual trade flows and constrain policies of the importing countries. This is so since there is no commitment to imports, but only a commitment to charge no more than the specified reduced rates of tariffs specified, i.e. whether products could be 195 Conclusions and recommendations exported under the TRas will depend on whether these reduced tariffs are still prohibitive or not. New TRas created interest groups which promise to apply inter- governmental restrictions on trade through licensing procedures and other administrative arrangements. There is uncertainty surrounding the procedures for allocating minimum access quotas, i.e. the recipients of licences to import at in-quota tariff rates will benefit from economic rents, and therefore countries have an interest in allocating these licenses to domestic traders rather than foreign traders even though this may not be entirely consistent with most favoured nation (MFN) principles. These problems could largely be resolved by auctioning licences under minimum access TRas. However, auctioning also has disadvantages, i.e. if the TRas were auctioned to the exporter, the effects would be similar to the system of tariffs that the quota was designed to avoid. This is because the exporter would tend to bid up the size of the tariff for the right to make more profit in the import market. It is clear that the issues surrounding TRas will not be solved easily, and for this reason it is of the utmost importance that countries are well prepared when the issue comes to table during negotiations. c) It is furthermore important to take cognisance of the fact that various newer issues and non-trade concerns have become linked to the trade agenda. Many of these issues are connected to the food business and many are being raised in relation to agricultural trade negotiations, no doubt for both substantive and tactical reasons. In addition to those already identified in the AoA, including food security, food safety and quality, environmental concerns, resource conservation and rural development, WTO members have raised disparate 196 Conclusions and recommendations issues such as animal welfare, biotechnology, species preservation, safeguarding the landscape, poverty reduction and preservation of rural culture. The emergence of these issues will put much more pressure on the negotiating process, which in turn means that countries will have to be well prepared for the next round of negotiations. This entails that industries, such as the red meat industry in South Africa, will have to act pro-actively in terms of understanding these issues, implementing strategies that embed the concerns surrounding these issues and making sure that cognisance is taken by government of such strategies, and how they are implemented. Apart from the issues mentioned above, due attention should also be given to the following: Inadequate administrative/legal capacity. Insufficient national policy formulation capacity. Limited scientific, administrative and infrastructure capability. The lack of capacity to prepare and negotiate in rounds. Although not all of the above may be applicable to South Africa, it is nevertheless the responsibility of the red meat industry to remind government that they are accountable when it comes to these issues. 7.2.4 The European Union and its Common Agricultural Policy Three issues necessitated the inclusion of the EU and its agricultural policy in this study. Firstly, due to the possible impact of the EU's agricultural policy on agricultural markets worldwide. Secondly, the EU is South Africa's largest trading partner. Thirdly, the EU is the largest import source of beef to South Africa. Of red meat the beef and veal sector is the most important in the EU. It is the second largest production sector in the EU, accounting for around 10 per cent of total agricultural production. Therefore it is understandable that much emphasis is put on the 197 Conclusions and recommendations beef and veal sector in the EU, especially when it comes to reforming policies pertaining to this sector. This study elaborated extensively on the reforms being implemented under Agenda 2000. It was also shown that despite the policy reforms EU beef producers are still heavily "supported". Nevertheless, several studies have shown that prices of beef and pork are destined to drop due to the Agenda 2000 reforms. However, it is suggested that prices will still be higher than prevailing world market prices for the same products. 7.2.5 Trade in red meat products by SACU • Beef From 1995 to 1999 SAGU experienced negative growth in the imports of bovine cuts (boneless, fresh or chilled) and bovine cuts (boneless, frozen), but positive growth in bovine cuts (bone in, frozen). In terms of bovine cuts (bone in, frozen), Uruguay was the most important importer in 1999 with an import value of US$709 thousand and more than a thousand tons. The drop in imports of bovine cuts (boneless, frozen) can be attributed largely to the fact that imports from SACU's most important import origin, namely Ireland, have declined by 17 per cent. The import trends in respect of Zimbabwe and Uruguay are especially important in the light of the SAOG FTA and the envisaged FTA with the MERGOSUR countries, of which Uruguay is a member. As far as Zimbabwe is concerned one could expect further growth in exports with the implementation of the SAOG FTA. With respect to Uruguay, a FTA with MERGOSUR could result in Uruguay becoming a much more important role player to contend with, depending on the specific trade arrangements embedded in such a FTA. This would not only put the South African beef industry under pressure, but also other SAOG members such as Namibia, Botswana and Zimbabwe. This becomes even more important in the light of the fact that Uruguay is regarded as a dynamic supplier internationally of this product. 198 Conclusions and recommendations Furthermore, note should also be taken of Australia, which is regarded as a dynamic supplier of this product in the world market. As present Australia is not taking advantage of its position to gain market share in South Africa, but this situation could change relatively quickly if one takes into account Australia's global market share. As far as exports are concerned, only in two instances have the value of exports increased from 1995 to 1999, namely bovine cuts (bone in, fresh or chilled) and bovine cuts (bone in, frozen). Conversely, bovine cuts (boneless, frozen) and bovine cuts (boneless, fresh or chilled) have experienced considerable negative growth in value exported from 1995 to 1999. In contrast the world has seen positive growth in terms of the latter product, and only a 2 per cent decline in growth in the former product. • Pork Imports of swine cuts (fresh or chilled, nes) have grown in terms of both value and quantity imported, whereas the value of world exports of this product declined. This may be an indication that SACU is a more lucrative market to export to than most other countries in the world. The value and quantity of imports of swine hams, shoulders and cuts thereof (bone in, frozen) have decreased significantly from 1996 to 1999. There was also considerable growth in the imports of swine cuts (frozen, nes) into SACU, although the value of imports decreased. The combined effect of the decline in the value of imports and the increase in quantity imported may be an indication that competition for the SACU market is increasing. Countries of major importance that currently export to SACU include Australia, Spain, Germany, Brazil, Austria and the US, even thought their market shares may be relatively small in SACU. The reason for this is that they are regarded as dynamic suppliers that are currently under-represented in SACU. They owe their dynamic status to the fact they were able to show positive growth in exports of swine cuts (frozen nes) internationally from 1995 to 1999. The performance in terms of the value exported was mixed. Swine hams, shoulders and cuts thereof (bone in, fresh or chilled) and swine cuts (fresh or chilled, nes) 199 Conclusions and recommendations recorded significant growth, 45 per cent and 82 per cent respectively. What makes it even more significant is the fact that the world has experienced negative growth in the value of exports of these two products. As far as swine carcasses and half carcasses (fresh or chilled), hams, shoulders and cuts thereof (of swine, bone in, frozen) and swine cuts (frozen nes) are concerned, South Africa experienced larger declines in the value exported than the rest of the world. This may be an indication that SACU has been targeting the wrong markets, but conversely it may also indicate that SACU is more price competitive on a unit value basis than most other countries and could secure niche markets provided that export promotion is directed as such and the supply chain allows for it. • Sheep meat On average SACU has experienced considerable growth in imports of sheep meat products. The largest growth was recorded by sheep cuts (bone in, frozen) with an increase in value and quantity imported of 23 per cent and 53 per cent, respectively. Very little sheep meat was exported in 1999. The value of sheep meat products exported showed a decline from 1995 to 1999, with the exception of sheep cuts (bone . in, fresh or chilled), which remained constant. Of some concern may be the fact that sheep cuts (bone in, frozen) and sheep cuts (bone in, fresh or chilled) show a drop in the value of exports, whilst the world in general experienced positive growth. It may indicate that opportunities exist, but have not been exploited to their potential. The other side of the coin, however, is that export prices of SACU cuts may have been forced to become more in line with that in the world market. 7.2.6 The impact of a total reduction in tariffs The question frequently heard is what will be the impact if a decision is made to grant red meat imports preferential access under such agreements. Depending on the specific agreement it could result in a two-tier situation. Firstly, if a portion of red meat 200 Conclusions and recommendations imports is allowed to enter South Africa at lower tariffs it would in principle have no or very little impact on prices and quantities demanded and supplied. The reason for this stems from the fact that the marginal import tariff is unchanged. Within a FTA situation the marginal tariff could change easily. For instance, should South Africa allow MERCOSUR to export beef to South Africa at lower or no tariffs it could mean that prices and quantities demanded and supplied will change from the status quo situation if MERCOSUR are in a position to fully meet South Africa's import requirements. This is not a far-fetched scenario if one consider the increase in imports from these countries over the last two years. South Africa should carefully consider its tariff "strategy" when granting preferential access to its red meat market, since preferential access to too many trade partners could result in a lower marginal tariff that will affect the red meat industry negatively. In the case where all tariffs on red meat imports are abolished, changes in prices of red meat products will be substantial. This will also result in changes in the production and consumption of red meat products. Cattle and livestock: In total cattle numbers will reduce by 6.03 per cent or 118 989. The number of cattle slaughtered will reduce by 6.75 per cent or 151 931 animals. Producer prices will decline by 21.11 per cent or R1,60 per kg. Beef prices will on average decline by 27.88 per cent, whilst beef supply will decline by 8.11 per cent. Conversely, demand will increase by 33.64 per cent as a result of lower beef prices. The combined effect of a reduction in beef supply domestically and an increase in beef demand entails a drastic increase in imports. Sheep and sheep meat: The supply of sheep and the number of sheep slaughtered are expected to decrease by 5.28 per cent and 5.34 per cent, respectively. On average sheep prices are expected to drop by 13.90 per cent. Demand for sheep meat will increase substantially. This, combined with a decline in sheep meat supply, would 201 Conclusions and recommendations result in an increase in sheep meat imports. The reason for this state of affairs could be traced back to the fact that, on average, sheep meat prices will decline by 28.56 per cent as a result of the removal of the tariff. Pigs and pork: The number of pigs demanded for slaughter is expected to decrease by 4.64 per cent on average. The supply of pigs will decline by the same percentage. Pig prices will drop by 11.99 per cent on average. Pork prices will decrease by 13.16 per cent as a result of a zero tariff on pork imports. This will in turn stimulate domestic demand for pork, but depress the supply of pork, resulting in increased imports of pork. Welfare implications: Consumers will experience considerable welfare increases. Producers, on the other hand, will experience a drop in welfare. In monetary terms the welfare gains by consumers are by far greater than the welfare losses by producers. Improved welfare for consumers will add 0.75 per cent to total real disposable income. However, cognisance should be taken of the fact that a significant proportion of the gains by consumers are merely a transfer from the national treasury. The loss in producer welfare amounts to 2.71 per cent of real gross farm income or 10.72 per cent of real net farm income, which is substantial. The fact of the matter is that if tariffs are reduced it would result in net welfare gains to society, but to the detriment of the agricultural sector. Hence, given the strategic importance of this sector, government should consider support arrangements, for example, direct payments, should be reduced. 7.2.7 The impact of a world price increase in red meat commodities Price increases showed that a price increase above 10 per cent for beef, 18 per cent for mutton and 6 per cent for pork would result in zero imports, thus stabilising the domestic market through domestic demand and supply forces. However, cognisance should be taken of the fact that tariffs as currently applied remain in place. 202 '------------------------------------------' Conclusions and recommendations Cattle and beef: Producer prices for cattle farmers will on average increase by 4.81 per cent if international prices rise to 10 per cent. There will also be an increase in the number of cattle supplied (1.38%) and the number of cattle slaughtered (1.45%). The increase in the number of cattle slaughtered can be derived from the fact that higher beef prices in the secondary industry create an incentive to supply more beef from domestic sources. This in turn creates a higher demand for slaughter animals. Beef prices will increase by 6.35 per cent on average, whilst the demand for beef will drop by 7.59 per cent. Supply of beef will, on average, increase by 1.76 per cent. Sheep and sheep meat: Sheep supply and the number of sheep slaughtered is expected to increase by 2.18 per cent and 2.19 per cent, respectively. Producer prices for sheep will on average increase with 5.88 per cent. An 18 per cent increase in the world sheep meat would result in an overall price increase of 11.74 per cent on the domestic market for sheep meat. Demand is expected to decline substantially (-22.79%) as a result of the price increase. Supply of sheep meat will increase marginally by 2.42 per cent. This is due to the fact that only a marginal increase in domestic supply is needed to meet domestic demand. Pig and pork: Pig prices will on average increase by 3.16 percent. Pig supply and the number of pigs slaughtered will both increase by 1.20 per cent for the country as a whole. The increase in the number of pigs slaughtered is attributable to the supply response in the secondary industry as a result of higher pork prices. Demand for pork will on average decrease (-6.47%) as a result of an overall increase in domestic pork prices (3.33%), which is, in turn, due to an increase in the international pork price. Higher domestic pork prices will also cause supply to increase, even though there is a decline in demand. Welfare implications: The losses in welfare to consumers are greater than the gains in welfare by producers. If the loss in consumer welfare is related to real disposable income it would amount to 0.16 per cent. However, if the gains by producers are related to net farm income it constitutes a gain of 2.84 per cent. 203 Conclusions and recommendations 7.2.8 The impact of a depreciation of the exchange rate on the South African red meat industry In order to measure the impact of depreciation of the exchange rate on the South African red meat industry, a depreciation of 40 per cent of the Rand against the US$ was assumed. The results are very similar to the situation when world prices are assumed to increase. The depreciation in the Rand is not transmitted in full to the domestic red meat industry. The reason for this is that the imports would effectively be reduced to zero since it becomes more expensive than domestically produced red meat. Price behaviour is then solely determined by domestic supply and demand factors, e.g. demand decreases for red meat due an increase in prices, but suppliers respond positively to the price increase. The dynamics in supply and demand on the domestic market would then determine the new equilibrium price. The results obtained may, however, represent an oversimplification of the market situation if international prices increase, whether it is due to liberalisation or a devaluation of the Rand against other currencies. The reason is that the current model does not make provision for exports. In reality one would expect exports to increase if world market prices become more favourable but, as stated previously, this is not expected over the short run since South Africa is not fully geared for exports. 7.2.9 The impact of the abolishment of Lomé on the South African beef industry The effect on the South African market is minimal. Prices of beef and cattle reduce by less than 0.5 per cent. It should also be noted that these two countries could export beef to South Africa free of tariffs. Thus, increased imports from these two countries will not have any effect on the marginal tariff level at the levels used in this scenario, and hence the relatively small effect on domestic beef prices. 204 Conclusions and recommendations 7.2.10 An alternative tariff regime for red meat in South Africa It is common knowledge that the red meat industry has been experiencing problems with respect to fraudulently invoiced imports aimed at avoiding ad valorem tariffs. In order to avoid these problems an alternative tariff regime, such as fixed tariffs, may be employed. In order to maintain the status quo, fixed tariffs on beef, sheep meat and pork were calculated at R3.47/kg, R4.70 and R1.35/kg, respectively. 7.2.11 The impact of population and income growth on the red meat industry The impact of population growth on the red meat industry was considered from a "Without HIV/AIDS" and "With HIV/AIDS" point of view. In the "Without HIV/AIDS" scenario, demand for beef, sheep meat and pork will increase by 12.01 per cent, 12.22 per cent, and 11.92 per cent, respectively. In the "With HIV/AIDS" scenario, demand will only increase by 7.19 per cent, 7.31 per cent and 7.28 per cent for beef, sheep meat and pork, respectively. It should also be noted that the increase in demand for the different red meat products is only met marginally by increases in domestic supply. Most of the increase in demand is met by overseas imports. Also, prices of red meat on the domestic market only show marginal increases. Demand for red meat will also increase as a result of an increase in per capita income. The increase in pork consumption is, however, lower than the increases in demand for beef and sheep meat. This can be attributed mainly to the fact that the weighted aggregated income elasticity is considerably lower for pork than for the other two red meats. There is also limited supply response domestically and therefore the increases in demand are met mainly by imports. Prices also change marginally, if at all, due to the fact most of the demand increase is met by imports. Finally, the increase in population combined with an increase in world prices will only partly offset the impact of a total reduction in tariffs. 205 Conclusions and recommendations 7.3 Policy recommendations a) South Africa has clearly demonstrated its willingness to participate in FTA's. The question that arises is what impact this would have on the red meat industry in South Africa should domestic red meat products be included in such agreements, i.e. red meat products are afforded preferential tariffs, if any, under an FTA. In this regard it is important to take into account the export capacity of the country or countries with which such agreements are negotiated. The reason for this is that if South Africa negotiates, for example, an FTA with Mercosur under which red meat is awarded preferential status and these countries can export all domestically demanded red meat at preferential rates, it would mean that the marginal tariff will decline to the preferential tariffs, if any, agreed upon. This will result in a drop in domestic prices of red meat to approximately the difference between the marginal tariff and the preferential tariff, if any tariff is applied. In other words, if one assumes that under an FTA with Mercosur countries they are allowed to import red meat at zero tariffs and they have the ability to supply the domestic deficit in total, the price effect would be similar to a zero tariff scenario despite the fact that tariffs are still applied to all other third parties. The same situation would apply for red meat imported from SAOG, i.e. if the domestic red meat deficit is met in total by imports from SAOG, domestic prices will become a function of the landed price of imports from these countries. The implication of this is that the red meat industry in South Africa should carefully consider granting preferential access to third countries under FTA's. Preferential access could easily lead to a reduction in the marginal tariff rate, which in turn would result in lower domestic prices of red meat. This would in turn have an impact on the supply of primary products and the profitability of red meat production. Also, it will have follow-on effects on the animal feed industry, which in turn will have an impact on the field crop sector. 206 Conclusions and recommendations b) The study clearly demonstrated that reductions in tariffs would have the most severe impact on the coastal regions of South Africa. From a development point of view, the significance of this is that the Eastern Cape and KwaZulu-Natal Provinces are known to have the largest number of cattle and sheep in the developing sector. It is also known that much effort is afforded by government and industry organisations to improve the welfare of such farmers through training and better market access, and to ensure the sustainability of scarce resources. This also entails greater pressure on these farmers to produce the right quality animal, to apply proper animals and veldt management practices, etc. in an effort to take full advantage of the market and to ensure sustainability. Obviously prices received by these farmers will be very important since such income is, in its turn, used for other purposes, amongst others, improvement of household food security. Thus, should a reduction in tariffs lead to lower prices, incentives to apply proper marketing and farm management practices by these farmers will be greatly diminished. It will also. mean that investment in human capital could be wasted. In addition to the above, the study has shown that improvements in efficiency in the developing sector could benefit the whole industry. For example, under a status quo situation increased demand due to growth in population and per capita income will be met largely by increased imports. In other words, the domestic red meat industry will loose market share to overseas producers. However, if the developing sector lives up to the challenge to improve efficiency, this sector could largely offset increased imports. However, increased off-take rates will lead to a drop in cattle prices on the domestic market, but this would only happen if export opportunities are not developed and exploited (exports will bediscussed in more detail later). Thus, initiatives to improve the participation of the developing sector in red meat markets should not take place in isolation. In other words, initiatives aimed at strategic issues in the red meat industry, such as increased efficiency and exploitation of export opportunities, should be done in tandem to ensure the most beneficial outcome. 207 Conclusions and recommendations c) This study has clearly shown that export opportunities for red meat products by SACU, and by implication also South Africa, do exist. In fact, growing markets currently being exported to are not optimised to its fullest potential. Exploitation of such opportunities becomes even more important in the light of expected world price increases due to liberalisation. Several reasons for this could be provided, e.g. stringent SPS requirements, issues related to food safety and other NTB's. Nevertheless, the question could rightfully be asked whether the red meat supply chain is structured and/or functioning efficiently. The reason for this is that issues related to SPS measures and food safety could be linked directly and indirectly to the supply chain. For example, one can only ask how many abattoirs in South Africa are export certified. The ITC (2000) also attribute the inability of countries to exploit export opportunities to inefficiencies in supply chains, i.e. the fact that export opportunities are not fully utilised cannot entirely be blamed on SPS measures and NTB's. Thus, the red meat industry in South Africa should seriously consider investigating the red meat supply chain in an all-encompassing manner. This would imply priorities being assigned to specific strategic issues, e.g. improvement of food safety and the image of red meat in the eye of the beholder - the consumer; greater continuity coupled with producer education, increased productivity in the commercial and developing sector, as well as output industry; addressing issues gaining importance in the international trade arena and assessing government's role in the red meat industry. In essence very basic questions need to answered - what is important for the red meat industry to survive in the globalised environment, how will such issues be addressed and who will be responsible. In the light of the SACU and SADC agreements much of what has been said also applies to South Africa's neighbours. Thus, one should consider joint efforts to address joint problems that could lead to mutually beneficial outcomes. This section does not imply that nothing has been done in terms of the issues discussed. In fact, at present many initiatives called for in this section are under 208 Conclusions and recommendations way in the red meat industry in South Africa. This section merely provides reasons for much more urgency in terms of these initiatives. d) Although this study has not specifically focussed on the consumers of red meat products, most of the issues related to trade are directly linked to the consumer, e.g. the reaction of consumers to changes in prices, food safety issues, etc. Hence, it is of the utmost importance that the consumer environment is taken into account when strategies or policies are designed. As stated elegantly by Adam Smith - "Consumption is the sole end and purpose of all production". Surely, this quote holds more truth today than ever before. It is for this reason that this section will elaborate in more detail on the factors that mayor could influence the demand for red meat. Consumers will only consume those goods and products that fulfil their specific demand requirements. The globalisation process broadened consumers' demand space, and hence created the opportunity for countries to take advantage of trade opportunities. This, however, entails that producers' should understand the factors that affect consumers' demand behaviour and that producers adjust accordingly. Degado (2000) mentions that, unlike the supply-led Green Revolution, the "Livestock Revolution" is driven by demand. From the early 1970's to the mid- 1990's, the volume of meat consumed in developing countries increased by almost three times as much as it did in developed countries. Developing-world consumption grew at an even faster rate in the second half of this period, with Asia in the lead. According to HowelIs (2000) consumers world-wide are becoming more demanding regarding what they want, and this is clearly evident from the switch from "quantity" to "quality" issues. The form in which consumption is taking place is changing; this is expressed in a number of ways, for example: The increased interest in food safety; greater concern for environmental and animal welfare issues; 209 Conclusions and recommendations increased importance of eating quality; and the greater role of food service. Huston (2000) is of the opinion that the market for meat is typically considered in terms of production and per capita consumption. He questions if this is the most meaningful measure of the world's beef (meat) market, and states that a more useful measure is demand. According to him demand is perhaps the most misunderstood term in the beef (meat) business; it is often translated into simply per capita consumption, price or profitability. Its nature is, however, much more complex in that it encompasses the interaction between what is offered in the market place and the price consumers are willing to pay. Beef (meat) demand increases if (1) more beef (meat) is sold at the same price, or (2) the same amount of beef (meat) is sold at a higher price. Huston (2000) elaborates by stating that there are several forces at work in the market place that undermine beef (meat) demand: Perceptions that beef (meat) is old-fashioned and boring with questionable safety. Consumers thinking that beef (meat) is too difficult and time-consuming to prepare. Questions surrounding meat's healthfulness, specifically concerns about fat and cholesterol. Prices being too high for some consumers to justify its purchase, leading than to select a product that they perceive as a better value. Price and disposable income issues will always be a barrier to some people. Duffy (1999) and Huston (2000) state that there has been no shortage of analysis on the factors influencing the demand by consumers for meat in general. The issue at hand, however, is the fact that the simple relationship of price and consumption no longer applies (Duffy, 1999). Huston (2000) goes further and calls into question the ability of price movements alone to explain problems with 210 Conclusions and recommendations meat demand. Duffy (1999) identifies two broad classifications for factors that influence the demand for meat, namely: Economic These factors include income and price. In other words, consumers will generally increase their consumption of meat when real income increases, whilst consumption falls when price relative to other meats rises. Non-economic These factors include issues pertaining to health and safety, convenience, quality, animal welfare and the environment. Bansback (1995) attempted to identify the influence of price, income and other factors (non-economic in nature) on the demand for meat in the EU. The results of his analysis are shown in Table 7.1. The results show that for the period 1955 to 1979, price and income factors accounted for a higher proportion of the explanation of changes in meat consumption than the period 1975 to 1994. Bansback (1995) concludes that non price/income factors are becoming more important and that traditional forms of demand analysis by economists are now less satisfactory than in the past. Also, industry efforts, such as promotion programmes, quality assurance measures, new product development and product quality improvement, can influence consumption. In other words, both companies and meat organisations may be in unique positions to affect consumption trends. Table 7.1: Importance of economic and non-economic factors in meat demand Product 1955 -1979 1975 -1994 Economic Non-Economic Economic Non-Economic Beef 95 5 68 32 Pig meat 98 2 55 45 Sheep meat 84 16 58 42 Source: Bansback, 1995. 211 Conclusions and recommendations Huston (1999) adds to the above by stating that the primary demand drivers for red meat in the US are: Product consistency and quality; food safety; health and nutrition concerns; and convenience. For example, by focussing only on these factors since 1998 the US beef industry were able to stabilise beef demand. In fact, demand averaged 5.2 per cent higher in the first half of 2000 than the first half of 1999. Consumer spending also increased about $2 billion. Similar initiatives are under way in countries such as Australia, New Zealand and Canada (Huston, 2000). It would thus appear that if the meat industry neglects to properly take account of all the factors that influence meat demand, it will be to their own detriment. Smith (1999) adds to this by stating that to accomplish the goal of producing the right kinds of beef, pork and lamb, producers and packers have to learn to differentiate between customers and consumers. For producers and packers to be both customer- driven and consumer-driven, the reward/punishment system must be directed toward sellers meeting the needs of buyers (customers) while simultaneously satisfying the desires of end-users (consumers). More specifically Smith (1999) states: "Seedstock producers can be successful if they sell breeding animals, to their customers, that are lean, muscular, fertile, prolific and/or heavy milkers. Feeder-animal producers can please their customers if the animals are lean, muscular, healthy, disease-free and grow rapidly and efficiently. Those who finish animals for slaughter can please their customers (packers) if the animals have high dressing percentages, are disease- free and defect-free, and yield carcasses that are of high quality/cutability. Those who harvest animals and sell carcasses/cuts to supermarkets and/or food-service customers can succeed if their products are lean, muscular, economically priced, 212 Conclusions and recommendations properly packaged and of high quality/palatability. Principals in each of those sectors must constantly remind themselves though that satisfying their customers (those to whom they sell animals or products) is not enough-in the end they must also please consumers (those who eat the meat). " Taking into account the above discussion, Quinn (1999) is of the opinion that the meat industry world-wide is living in the past, instead of looking to the future. He states that the past is one of managed markets, with largely captive customers and endlessly rising demand. The future is one in which the customer calls the shots, and the businesses that succeed will be those who recognise this fact and who act on it. This is echoed by Smith (1999), who states that to be "consumer- driven" means that beef, pork and lamb producers can no longer just produce what they (individually or collectively) think is best (or easiest, or most economical, etc.) and expect the world to come begging for more; rather, it means that at each critical juncture in the beef, pork and lamb production sequences, consideration must be given to what the consumer wants and is willing to buy. Finally, Smith (1999) and Quinn (1999) summarise the factors that need to be accounted for in order to turn around the depressed state of red meat demand. These are: Properties which influence consumer demand for processed (prepared) beef, pork and lamb products include: (a) Novelty (new and different, changed in form, modernised, with added value) (b) Quality (taste, tenderness, physical attractiveness, storage stability); (c) Simplicity (quick, fast, time-saving, uncomplicated); (d) Convenience (easy to prepare, easy to serve, easy to clean-up after); (e) Safety (bacteriologically safe, chemically safe), and 213 Conclusions and recommendations (f) Consistency (sameness in appearance from purchase to purchase, sameness in performance from preparation to preparation, sameness in palatability from eating experience to eating experience). Properties that influence consumer demand for fresh (unprocessed/unprepared) beef, pork and lamb include: (a) Quality (taste, tenderness, physical attractiveness, storage stability) ; (b) Consistency (sameness in appearance from purchase to purchase, sameness in palatability from eating experience to eating experience); (c) Safety (bacteriologically safe, chemically safe), and; (d) Caring Attitude (by producers, about the environment and animal welfare). In conclusion it can be stated that research pertaining to consumer orientated production should increasingly receive more attention. This is not only important from a South African point of view, but also from an international point of view. Inroads into the international market is only attainable if consumers' tastes and preferences on this market is properly understood. Then, and only then, would it be worthwhile to promote South African products internationally. In other words, there is a need to determine whether South African red meat products appeal to consumers abroad, and also domestically. This can only be done through proper market research that encompasses issues such as product characteristics, form and place utilities of consumers, food safety requirements, etc. Neglecting to achieve this end will be to the detriment of all parties playing an active role in the red meat industry, e.g. research pertaining to veterinary issues will mean a waste of valuable research resources in a declining industry. Recognising consumers as the sole end and purpose of all production will have the opposite result. 214 Conclusions and recommendations This would, however, not mean that the "battle" has been won. As mentioned, the red meat supply chain also needs to be considered. In this regard one can also mention the fact that although a large number of animals is kept by the non- commercial sector, they contribute very little to output. This state of affairs needs urgent attention. For example, this sector can contribute significantly to improved continuity of red meat, which is currently a problem as far as exports are concerned. Finally, one might wonder why so much emphasis is placed on the international market and opportunities that exist for exports. The answer to this question is quite simple. Being able to export and to increase one's market share internationally implicitly also relates to one's competitiveness. This in its turn means that concerns about imports from other countries could receive less prominence and the industry could use scare human and capital resources to serve the industry more efficiently. Such a task could, however, not be accomplished by the industry itself. The active involvement of government is of the utmost importance. This entails that government should actively pursue issues that relate to disease prevention (not control), animal welfare, traceability, stock theft and trade. 7.4 Recommendations for further studies Further research on the following aspects is necessary: a) Application of the Armington approach on trade modelling in the red meat industry: It is commonly known that the quality of products vary considerably between different sources. This is no exception in the red meat industry. Thus, a country will, for instance, export good quality red meat and import lower quality red meat. Such trade characteristics are best handled by the Armington approach. Within the current modelling framework only imports are handled 215 Conclusions and recommendations endogenously. The Armington approach would allow for handling both imports and exports endogenously. b) Re-estimation of behavioural parameters: Most of the empirical work relating to supply and demand elasticities in South Africa was completed before the process of liberalisation and deregulation. The importance is that SPE models rely heavily on these parameters for result estimations. Thus, in order to have more accurate predictions on how markets react to external shocks, one would have to estimate behavioural parameters that reflect the marketing environment after deregulation. In addition, the inclusion of cross-price effects must also be considered. In fact, this is one of the most important shortcomings of the present analysis. c) Expansion of current modelling framework to include more products: It is common knowledge that poultry is the most important substitute for red meat products, in particular beef and sheep meat. The present analysis, however, excludes poultry. Thus, in order to properly measure the impact of external shocks on the red meat industry, the inclusion of poultry is necessary. Furthermore, the red meat industry also has strong linkages to the animal feed sector. This entails that changes in the feed sector will also influence the red meat sector and vice versa. Inclusion of this sector in the modelling framework used in this study would provide a much better understanding of the red meat trade environment. Also it would provide important information regarding the red meat value chain. d) Expansion of current modelling framework to include other southern African countries: This is particularly important in the light of the SAOG agreement. Furthermore, very little information is also available on the extent of red meat trade in this region. 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OECD and The World Bank, Paris and Washington DC. 235 Appendix A: World exports of different red meat products Table A.1: IExports of products 020110 (Bovine carcasses and half carcasses, fresh or chllled) Value Quantity Annual growth Annual growth Share in Exporters exported in exported Quantity in value 1995 - in quantity world1999, in US$ thousand in 1999 unit 1999, % 1995-1999, % exports,% World estimation 1,047,813 314,027 Tons -4 0 100 Netherlands 305,861 65,068 Tons -2 0 29.19 France 205,345 57,733 Tons -13 -9 19.60 Soain 160,699 52,136 Tons 40 48 15.34 Belgium 124,351 35,669 Tons -11 -6 11.87 Germany 66,618 30,477 Tons -7 4 6.36 Ireland 41,503 17,365 Tons 15 24 3.96 Canada 27,394 6,918 Tons 12 8 2.61 United States of 27,219 10,194 Tons -9 -2 2.60 America Denmark 24,695 7,820 Tons -13 -7 2.36 Austria 24,411 9,604 Tons 16 27 2.33 Italy 14,016 6,482 Tons -29 -21 1.34 Nlcaraoua 6,665 3,458 Tons -18 -17 0.64 IArg_entina 3,367 2,583 Tons -30 -34 0.32 Colombia 2,200 997 Tons 6 10 0.21 Uruquav 2,192 1,682 Tons Na Na 0.21 Note: Only countries with an export value of more than US$10 000 000 or more than a 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table A.2: Exports of products 020120 (Bovine cuts bone in, fresh or chilled) Value exported in Quantity Quantity Annual growth Annual growth Share in Exporters 1999, in US$ exported unit in value 1995- in quantity world thousand in 1999 1999, % 1995-1999, % exports, % World estimation 2,604,564 836,976 Tons -6 -4 100 Germany 506,772 154,774 Tons -4 1 19.46 France 460,431 136,679 Tons -6 -3 17.68 Netherlands 431,384 111,354 Tons -6 -4 16.56 Ireland 245,125 52,164 Tons 5 2 9.41 Canada 210,037 87,762 Tons -1 -6 8.06 Austria 136,655 45,613 Tons -1 7 5.25 Denmark 118,435 42,047 Tons -8 -4 4.55 United States of America 114,411 34,717 Tons 13 19 4.39 Spain 97,020 43,694 Tons 1 9 3.72 Belolurn 86,497 24,681 Tons -16 -11 3.32 236 Table A.2: Continues Value exported in Quantity Quantity Annual growth Annual growth Share in Exporters world1999, in US$ exported unit in value 1995- in quantity exports, thousand in 1999 1999, % 1995-1999, % % Italy 80,704 38,581 Tons 6 14 3.10 Uruguay 22,528 19,441 Tons 10 10 0.86 \Australia 18,186 8,169 Tons -7 7 0.70 Hencarv 16,840 6,961 Tons 3 3 0.65 Poland 13,969 8,016 Tons 175 212 0.54 Paraquav 11,058 9,036 Tons 8 Na 0.42 Slovenia 10,275 3,373 Tons 4 15 0.39 Croatia 4,367 900 Tons -17 -14 0.17 Finland 3,949 1,284 Tons -18 -25 0.15 New Zealand 2,507 890 Tons -14 -13 0.10 Czech Republic 2,002 961 Tons 45 52 0.08 SACU 1,840 730 Tons 2 Na 0.07 ~rgentina 1,723 1,342 Tons -52 -56 0.07 IBosnia and 1,540 513 Tons 23 31 0.06 Herzeqovina United Kincdom 1 192 254 Tons -79 -80 0.05 Mexico 899 260 Tons Na Na 0.03 Norway 865 1,008 Tons Na Na 0.03 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table A.3: Exports of products 020130 (Bovine cuts boneless. fresh or chilled ) Value Quantity Exporters exported in exported Quantity Annual growth Annual growth 1999, in US$ unit in value 1995- in quantity Share in world in 1999 1999, % 1995-1999, % exports, % thousand World estimation 5,117,632 1,265,272 Tons 2 8 100 United States of 1,276,390 326,008 Tons 0 9 24.94 IIAmerica l\Australia 811,370 241,023 Tons -5 1 15.85 Canada 705,830 237,563 Tons 54 47 13.79 Netherlands 514,506 104,359 Tons 1 5 10.05 Ireland 481,880 51,473 Tons -2 -10 9.42 l\Argentina 348,323 73,631 Tons -1 2 6.81 France 195,832 45,348 Tons -7 -3 3.83 Germany 151,784 29,205 Tons 10 13 2.97 Brazil 117,422 31,083 Tons 24 45 2.29 Denmark 96,726 17,452 Tons -1 3 1.89 Belolurn 92,576 18,765 Tons 5 9 1.81 Uruguay 88,101 23,047 Tons 22 37 1.72 New Zealand 72,462 17,212 Tons 1 8 1.42 Izimbabwe 24,721 5,405 Tons -13 -4 0.48 United Kingdom 24,184 3,926 Tons -45 -46 0.47 237 Table A.3: Continues Value Quantity Annual growth Annual growth Exporters exported in Quantity1999, in US$ exported unit in value 1995- in quantity Share in world in 1999 1999, % 1995-1999, % exports, %thousand Nicaragua 20,997 8,037 Tons 1 2 0.41 Italy 14,499 3,810 Tons 40 39 0.28 Costa Rica 12,834 4,712 Tons -11 -12 0.25 Panama 11,772 3,929 Tons 34 33 0.23 Paraguay 11,713 5,253 Tons 19 0.23 Finland 8,630 1,741 Tons 24 39 0.17 Austria 8,009 2,637 Tons -1 7 0.16 Spain 7,503 4,408 Tons 37 67 0.15 Mexico 5,172 626 Tons 38 20 0.10 JaQ_an 3,945 47 Tons 15 17 0.08 Sweden 1,978 579 Tons -13 1 0.04 Guatemala 1,775 753 Tons -13 -22 0.03 Hungary 1,352 334 Tons 0.03 ~rea Nes 1,106 248 Tons -28 -27 0.02 SACU 949 1,276 Tons -59 0.02 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table A.4: Exports of products 020210 (Bovine carcasses and half carcasses, frozen) Value exported in Quantity Quantity Annual growth Annual growth Share in Exporters 1999, in US$ exportedin 1999 unit in value 1995- in quantity world 1999, % 1995-1999, % exports, % thousand World estimation 209637 173003 Tons -15 -10 100 Ukraine 139701 125535 Tons -14 -9 66.64 Australia 16441 12042 Tons -27 -22 7.84 United States of America 15,460 4,761 Tons 25 24 7.37 Lithuania 9,461 9,182 Tons 15 22 4.51 Belarus 5,509 4,473 Tons Na Na 2.63 Moldova 4,948 4,737 Tons Na Na 2.36 Kazakstan 4,081 3,561 Tons -34 -31 1.95 Ireland 2,872 517 Tons Na Na 1.37 Spain 2,511 970 Tons 299 315 1.20 Belgium 2,424 956 Tons 42 63 1.16 Mongolia 2,299 3,174 Tons 28 60 1.10 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. 238 Table A.5: Ex aorts of products 020230 iBovine cuts boneless frozen) Value exported in Quantity Quantity Annual growth in Annual growth Share in Exporters 1999, in US$ exported unit value 1995-1999 , in quantity world exports, thousand in 1999 % 1995-1999, % % World estimation 4,564,609 2,162,012 Tons -2 0 100 Australia 1,038,776 609,323 Tons 6 7 22.76 United States of America 1,024,026 341,088 Tons -1 5 22.43 New Zealand 543,431 285,442 Tons -4 -1 11.91 Ireland 388,675 116,264 Tons -4 -15 8.51 Brazil 326,145 119,471 Tons 24 38 7.15 Uruguay 202,114 97,698 Tons 8 12 4.43 ~rgentina 169,537 81,096 Tons -15 -13 3.71 Netherlands 139,798 61,385 Tons 1 1 3.06 Germany 123,219 83,192 Tons -7 -1 2.70 Italy 89,880 45,343 Tons 5 18 1.97 India 80,250 70,305 Tons -6 -2 1.76 France 73,747 47,606 Tons -22 -20 1.62 Canada 62,982 32,994 Tons 13 11 1.38 Spain 59,011 36,363 Tons 4 20 1.29 Denmark 37,559 18,113 Tons -10 -9 0.82 Belgium 32,271 13,536 Tons -20 -25 0.71 China 24,837 18,472 Tons -1 4 0.54 Ukraine 17,450 11,561 Tons -15 -8 0.38 Costa Rica 14,525 8,933 Tons -17 -16 0.32 Nicaragua 14,109 8,116 Tons -9 -8 0.31 United Arab Emirates 10,121 7,197 Tons 35 26 0.22 Poland 9,831 5,174 Tons 4 33 0.22 Paraguay 9,596 4,165 Tons -21 0.21 6_ustria 8,998 9,215 Tons 8 27 0.20 Moldova 6,094 4,605 Tons 0.13 Greece 5,335 1,703 Tons -6 -9 0.12 Zimbabwe 4,629 2,560 Tons -22 -8 0.10 Georgia 4,603 1,928 Tons 0.10 Area Nes 4,411 1,962 Tons 0 9 0.10 Hungary 4,287 1,906 Tons 0.09 United Kingdom 4,048 1,023 Tons -60 -66 0.09 Mexico 3,759 1,896 Tons -7 -4 0.08 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. 239 Table A.6: Exports of product 020311 (Swine carcasses and half carcasses, fresh or chilled) Value exported in Quantity Quantity Annual growth Annual growth Share in Exporters 1999, in US$ exported in unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % exports, % World estimation 987595 729130 Tons -9 4 100 Belgium 223,452 171,246 Tons -14 1 22.63 Netherlands 188,690 144,678 Tons -18 -5 19.11 France 107,868 73,333 Tons -15 -3 10.92 United States of America 80,124 29,571 Tons 54 41 8.11 Spain 79,154 62,858 Tons 5 23 8.01 Denmark 57,188 51,207 Tons -7 10 5.79 Germany 50,503 39,152 Tons 5 26 5.11 United Kingdom 46673 46946 Tons -17 0 4.73 Australia 35,788 15,044 Tons 209 236 3.62 Austria 34,054 25,568 Tons 16 37 3.45 Canada 20,773 12,334 Tons -1 2 2.10 Ireland 13,567 11,257 Tons -12 -1 1.37 HungalY_ 12,499 12,186 Tons 24 43 1.27 Sweden 8,116 7,374 Tons 9 31 0.82 Belarus 4,979 3,565 Tons Na Na 0.50 Finland 4,196 3,542 Tons -13 6 0.42 Czech Republic 3,761 4,060 Tons 458 635 0.38 Italy 3,177 2,460 Tons -11 2 0.32 Estonia 2,666 2,048 Tons 579 Na 0.27 Poland 2,117 3,474 Tons -28 -16 0.21 Norway 1,704 2,082 Tons 148 201 0.17 Portugal 1,177 1,152 Tons 16 34 0.12 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table A.7: Exports of product 020312 (Hams, shoulders and cuts thereof, of swine bone in. fresh or chilled Value Quantity Annual growth Annual growth Share in Exporters exported in Quantity 1999, in US$ exported in unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % exports, % !world estimation 1695543 1 084145 Tons -3 7 100 Netherlands 504106 358749 Tons -10 3 29.73 Denmark 425436 251653 Tons -4 7 25.09 Germany 145578 94865 Tons 5 17 8.59 Belgium 143859 99744 Tons -7 6 8.48 France 100689 61 811 Tons -11 -1 5.94 UnitedStates of lAmerica 96,250 38,558 Tons 36 39 5.68 Spain 95568 58404 Tons 13 27 5.64 Canada 84717 62901 Tons -4 4 5.00 240 Table A.7: Continues Value exported in Quantity Quantity Annual growth Annual growth Share in Exporters world 1999, in US$ exported in unit in value 1995- in quantity1999 1999, % 1995-1999, % exports,thousand % Austria 33,889 21,892 Tons 13 27 2.00 Ireland 20,476 7,683 Tons 2 7 1.21 Hun_g_é!ry 13260 7946 Tons 33 46 0.78 talv 12231 4887 Tons 53 43 0.72 Sweden 9,953 6,012 Tons 32 52 0.59 UnitedKingdom 6644 6,955 Tons -29 -10 0.39 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITe calculations based on eOMTRADE statistics, 2000. Table A.8: Exports of product 020321 (Swine carcasses and half carcasses, frozen) Value exported in Quantity Share in Exporters exported in Quantity Annual growth Annual growth 1999, in US$ unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % exports, % World estimation 278966 305256 Tons 3 15 100 Germany 94865 96425 Tons 47 71 34.01 Poland 54092 81 398 Tons 2 15 19.39 France 24402 29792 Tons 31 60 8.75 UnitedStatesof America 16,143 7,828 Tons 6 11 5.79 Spain 15145 10481 Tons 49 66 5.43 China 11 581 9284 Tons -29 -25 4.15 Vietnam 9128 5369 Tons 33 38 3.27 Ukraine 6298 '6283 Tons -27 -18 2.26 Moldova 6180 6352 Tons Na Na 2.22 Netherlands 5090 7213 Tons 29 64 1.82 Hungary 4860 5571 Tons 53 99 1.74 Belarus 4227 3968 Tons Na Na 1.52 Finland 4069 5196 Tons 102 135 1.46 Norway 3384 6147 Tons 91 152 1.21 Ireland 3002 1 228 Tons 11 20 1.08 Austria 2920 5126 Tons 74 117 1.05 Kazakstan 2461 2160 Tons 27 39 0.88 Belgium 1994 4057 Tons -26 9 0.71 Sweden 1 817 2930 Tons 286 388 0.65 Romania 1750 2855 Tons -53 -46 0.63 Denmark 1 155 1 738 Tons 41 80 0.41 Italy 1066 1 103 Tons 13 35 0.38 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITe calculations based on eOMTRADE statistics, 2000. 241 Table A.9: Exports of product 020322 (Hams, shoulders and cuts thereof, of swine, bone in frozen) Value Quantity Annual Annual growth Share in Exporters exported in Quantity growth in 1999, in US$ exported in unit value 1995- in quantity world thousand 1999 1999, % 1995-1999, % exports, % World estimation 328072 236572 Tons 0 12 100 USA 112111 45709 Tons -1 2 34.17 Hungary 35209 19574 Tons 36 38 10.73 Denmark 27396 26729 Tons -8 8 8.35 France 25844 38364 Tons 9 48 7.88 Netherlands 23401 24788 Tons -9 10 7.13 Canada 21044 16263 Tons 11 19 6.41 Belgium 15784 13997 Tons -15 2 4.81 Spain 15075 10776 Tons -3 14 4.60 Germany 11 119 8142 Tons 31 54 3.39 Mexico 7993 3654 Tons 193 143 2.44 Ireland 7074 4246 Tons -9 -1 2.16 United Kingdom 5193 6726 Tons -22 -5 1.58 Italy , 4478 2350 Tons 33 59 1.36 Sweden 3581 2523 Tons 70 99 1.09 ~ustria 2265 3009 Tons 57 115 0.69 China 1 588 1 379 Tons -29 -25 0.48 Kazakstan 1435 1287 Tons 134 173 0.44 Korea 1 319 663 Tons 50 106 0.40 Brazil 1042 2086 Tons -19 8 0.32 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table A.10: Exports of product 020329 (Swine cuts, frozen nes) Value Quantity Annual growth Annual growth Share in Exporters exported in Quantity1999, in US$ exported in unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % exports, % [\II.I_oreldstimation 3377 848 1 760419 Tons -1 12 100 Denmark 1 156719 469032 Tons -5 7 34.24 France 262416 171 950 Tons 5 22 7.77 Canada 260794 142658 Tons -1 10 7.72 USA 259592 133568 Tons 7 15 7.69 Korea 223141 67803 Tons 30 55 6.61 Netherlands 188436 126 121 Tons -9 7 5.58 Germany 120047 93677 Tons 12 31 3.55 Belgium 115282 76886 Tons -15 -1 3.41 Brazil 113679 73292 Tons 9 23 3.37 Sp_ain 109981 85238 Tons 15 39 3.26 Mexico 99429 29935 Tons 27 40 2.94 Hungary 90794 46049 Tons -3 2 2.69 242 Table A.10: Continues Value exported in Quantity Annual growth Annual growth Share inExporters 1999, in US$ exported in Quantity in value 1995- in quantity world thousand 1999 unit 1999, % 1995-1999, % exports, % UnitedKingdom 89292 61 948 Tons -10 8 2.64 Ireland 72042 25906 Tons -11 -1 2.13 China 53335 42262 Tons -21 -18 1.58 Italy 31 518 27534 Tons 4 34 0.93 Australia 29636 11 022 Tons 15 34 0.88 Austria 28408 29811 Tons 37 66 0.84 Chile 20846 5587 Tons 51 40 0.62 Sweden 20445 14711 Tons -6 10 0.61 Finland 13361 9575 Tons 18 28 0.40 [AreaNes 2092 1463 Tons -28 -25 0.06 Portugal 2077 2232 Tons 0 21 0.06 CzechRepublic 2009 1 042 Tons 54 70 0.06 SACU 1 481 934 Tons -26 0.04 Slovenia 1 392 1 135 Tons 110 149 0.04 Poland 1271 2558 Tons 14 32 0.04 Norway 1246 2233 Tons 72 118 0.04 Greece 1175 548 Tons -2 1 0.03 Cyprus 1 096 790 Tons 43 63 0.03 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table A.11: Exports of product 020410 (Lamb carcasses and half carcasses, fresh or chilled) Value Quantity Annual growth Annual growth Share in Exporters exported in Quantity in value 1995- in quantity world 1999, in US$ exported in unit 1995-1999, % exports, thousand 1999 1999, % % World estimation 505353 115595 Tons -6 -10 100 UnitedKingdom 257031 80999 Tons -12 -10 50.86 Ireland 154917 7918 Tons 1 -27 30.66 I Spain 22500 5166 Tons 17 21 4.45 Bulgaria 18370 4677 Tons 24 26 3.64 France 11 641 2794 Tons -5 3 2.30 [Australia 11 334 5328 Tons -5 -3 2.24 !Turkey 5417 1276 Tons 23 19 1.07 NewZealand 5063 2235 Tons -3 0 1.00 Netherlands 4374 1094 Tons -5 1 0.87 Hungary 2923 638 Tons 9 16 0.58 Italy 2909 644 Tons 155 185 0.58 Belgium 2811 662 Tons 15 16 0.56 Uruguay 1254 849 Tons 0.25 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. 243 Table A.12: Exports of product 020422 (Sheep cuts bone in fresh or chilled) Value Quantity Annual growth Annual growth Share in Exporters exported in 1999, in US$ exported in Quantity unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % exports, % !Worldestimation 285381 79457 Tons 13 17 100 NewZealand 115507 27133 Tons 14 20 40.47 !Australia 107431 38903 Tons 18 19 37.64 Belgium 17396 3203 Tons 31 25 6.10 UnitedKinqdom 16775 3953 Tons -6 -1 5.88 France 13592 2123 Tons 11 19 4.76 Ireland 9894 2935 Tons -1 4 3.47 Netherlands 1464 199 Tons 94 84 0.51 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table A.13: Exports of product 020441 (Sheep carcasses and half carcasses, frozen) Value Quantity Share in Exporters exported in exported in Quantity Annual growth Annual growth unit in value 1995-1999, in US$ in quantity world 1999 1999, % 1995-1999, % exports,thousand % World estimation 38369 40852 Tons -9 -8 100 !Australia 22782 23909 Tons 2 6 59.38 NewZealand 9544 12504 Tons -26 -23 24.87 India 1 110 461 Tons -10 -13 2.89 Chile 1074 1055 Tons 24 23 2.80 Moldova 1 041 1 088 Tons Na Na 2.71 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table A.14: Exports of product 020442 (Sheep cuts, bone in, frozen) Value Annual growth Annual growth Share in Exporters exported in Quantity Quantity world 1999, in US$ exported in unit in value 1995- in quantity 1999 1999, % 1995-1999, % exports,thousand % ~orld estimation 619357 337399 Tons 2 7 100 NewZealand 412700 192613 Tons 0 4 66.63 Australia 140968 122501 Tons 7 13 22.76 Belgium 21 919 5250 Tons 4 5 3.54 Uruguay 9451 5465 Tons 30 18 1.53 United Kingdom 7130 2165 Tons -5 0 1.15 ~ermany 4356 1083 Tons 20 24 0.70 Chile 3474 1681 Tons 32 39 0.56 Korea 3015 1 060 Tons 323 329 0.49 USA 2479 1275 Tons -6 1 0.40 reland 2011 781 Tons 36 27 0.32 244 Table A.14: Continues Value Quantity Annual growth Annual growth Share in Exporters exported in Quantity 1999, in US$ exported in unit in value 1995- in quantity world exports, thousand 1999 1999, % 1995-1999, % % Spain 1792 754 Tons 6 11 0.29 Italy 1 771 498 Tons -10 -10 0.29 Netherlands 1 519 256 Tons 33 27 0.25 France 1490 453 Tons -19 -1 0.24 Canada 1409 218 Tons 15 15 0.23 Iceland 1 065 243 Tons -7 -14 0.17 Note: Only countries with an export value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. 245 Appendix B: World imports of different red meat products Table B.1: Imports of products 020110 (Bovine carcasses and half carcasses, fresh or chilled) Value Share in Importers imported in Quantity Quantity Annual growth Annual growthimported in value 1995- in quantity world1999, in US$ thousand in 1999 unit 1999, % 1995-1999, % imports,% World estimation 1,002,113 369,480 Tons -6 0 100 Italy 456,160 115,460 Tons 1 5 45.52 France 140,683 49,855 Tons -13 -7 14.04 Netherlands 98,945 48,440 Tons -8 5 9.87 Portugal 94,632 29,945 Tons 6 12 9.44 Greece 41,857 63,064 Tons -8 33 4.18 Germany 38,382 10,389 Tons -30 -27 3.83 United States of 27,226 6,881 Tons 12~merica 8 2.72 Belgium 18,860 5,939 Tons 11 20 1.88 United Kingdom 15,549 6,397 Tons 24 29 1.55 ~ustria 11,870 3,551 Tons 1 9 1.18 Spain 11,793 2,471 Tons -24 -23 1.18 Mexico 11,222 6,457 Tons 109 110 1.12 Brazil 7,075 6,260 Tons -37 -40 0.71 El Salvador 3,637 1,961 Tons -27 -41 0.36 ~Igeria 3,629 1,999 Tons Na Na 0.36 Chile 2,921 1,983 Tons 108 113 0.29 IT"unisia 2,288 1,393 Tons -14 -9 0.23 Argentina 2,247 1,647 Tons 661 602 0.22 Note: Only countries with an import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table B.2: Imports of products 020120 (Bovine cuts bone in, fresh or chilled) Value imported in Quantity Quantity Annual growth Annual growth Share in world Importers 1999, in US$ imported unit in value 1995- in quantity1999, % 1995-1999, % imports, % thousand in 1999 World estimation 2,366,702 776,640 Tons -7 -3 100 Italy 796,616 200,504 Tons -2 1 33.66 France 434,553 156,651 Tons -14 -8 18.36 Greece 228,236 74,980 Tons -6 -1 9.64 United States of 207,885 86,736 Tons -1 -6 8.78 ~merica Denmark 120,467 38,233 Tons 2 8 5.09 Spain 108,320 18,402 Tons 0 1 4.58 246 Table B.2: Continues Value imported in Quantity Quantity Annual growth Annual growth Share in worldImporters 1999, in US$ imported unit in value 1995- in quantity thousand in 1999 1999, % 1995-1999, % imports, % Netherlands 86,470 30,706 Tons 2 12 3.65 Germany 85,798 30,099 Tons -21 -19 3.63 PortUB_al 59,156 17,868 Tons -14 -10 2.50 United Kingdom 59,062 26,067 Tons -6 19 2.50 Mexico 38,978 27,098 Tons 48 58 1.65 Belgium 17,799 5,451 Tons -16 -11 0.75 Brazil 16,835 14,670 Tons -3 -4 0.71 Canada 15,799 4,392 Tons -8 -6 0.67 Macedonia 10,695 5,994 Tons 24 25 0.45 fA.ustria 9,959 3,321 Tons -5 2 0.42 Switzerland 9,090 1,310 Tons 23 20 0.38 Japan 9,078 2,015 Tons -24 -21 0.38 Russian Federation 7,865 9,123 Tons -13 -27 0.33 ~rgentina 7,583 5,840 Tons 34 26 0.32 fA,ndorra 4,783 1,374 Tons -1 0 0.20 Finland 2,986 1,743 Tons -9 14 0.13 Czech Republic 2,858 2,832 Tons 19 15 0.12 Sweden 2,714 928 Tons -27 -27 0.11 Croatia 2,582 948 Tons -12 -16 0.11 Bosnia and Herzegovina 1,597 1,163 Tons -20 -14 0.07 Note: Only countries with an Import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table B.3: Im oorts of products 020130 (Bovine cuts boneless fresh or chilled) Value Quantity Quantity Annual growth Annual growth Share in Importers imported in1999, in US$ imported in unit in value 1995- in quantity world1999, % 1995-1999, % imports, % thousand 1999 World estimation 5,346,718 1,365,689 Tons 2 10 100 Japan 1,604,539 331,965 Tons -8 -2 30.01 United States of America 755,327 244,376 Tons 46 40 14.13 Mexico 486,695 202,353 Tons 64 68 9.10 Germany 440,816 81,119 Tons -8 -3 8.24 United Kingdom 311,832 65,456 Tons 1 6 5.83 France 307,441 63,293 Tons -6 -2 5.75 Canada 212,522 67,405 Tons -7 -6 3.97 Netherlands 194,984 45,468 Tons 4 14 3.65 Italy 159,685 27,542 Tons 6 10 2.99 Spain 144,498 33,478 Tons 19 33 2.70 Chile 126,888 56,737 Tons 12 15 2.37 247 Table B.3: Continues Value Importers imported in Quantity Quantity Annual growth Annual growth Share in 1999, in US$ imported in unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % imports, % Denmark 87,255 18,720 Tons -2 2 1.63 Sweden 77,764 19,289 Tons 11 27 1.45 Belgium 74,702 13,288 Tons 4 9 1.40 Austria 35,799 4,900 Tons 8 11 0.67 Switzerland 33,745 3,257 Tons 0 0 0.63 Greece 32,716 12,966 Tons 2 14 0.61 Portugal 30,903 6,407 Tons 6 11 0.58 Brazil 26,412 6,826 Tons 9 11 0.49 Taiwan 23,546 6,193 Tons 13 21 0.44 Hong Kong 17,681 2,447 Tons -2 6 0.33 Finland 15,416 4,394 Tons 2 18 0.29 El Salvador 15,331 4,973 Tons 19 -1 0.29 Saudi Arabia 14,996 6,807 Tons -9 2 0.28 Lebanon 14,678 5,086 Tons 9 9 0.27 Singapore 12,487 1,888 Tons -3 3 0.23 French Polynesia 8,570 2,189 Tons 1 12 0.16 United Arab Emirates 7,783 2,869 Tons 5 8 0.15 Dominican Republic 7,318 2,130 Tons 68 165 0.14 Korea 6845 1836 Tons 128 249 0.13 !Argentina 4,346 1,812 Tons 59 61 0.08 Bermuda 3,952 613 Tons 3 5 0.07 !Australia 3,923 1,104 Tons -23 -22 0.07 Note: Only countries with an Import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. 248 Table B.4: Imports of products 020210 (Bovine carcasses and half carcasses, frozen) Value imported in Quantity Quantity Annual growth in Annual growth Share inImporters 1999, in US$ imported in unit value 1995-1999, in quantity world thousand 1999 % 1995-1999, % imports, % V'II_orldestimation 199,633 163,094 Tons -14 -10 100 Russian Federation 153,837 139,406 Tons -21 -14 85.48 Netherlands 16,244 8,538 Tons 12 24 5.24 Portugal 10,202 3,219 Tons 40 53 1.97 Egypt 6,783 4,087 Tons 122 127 2.51 Uzbekistan 2,819 3,042 Tons Na Na 1.87 Italy 1,866 449 Tons -6 -5 0.28 France 1,497 676 Tons 19 31 0.41 Note: Only countries with an import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table B.5: Imports of products 020230_(Bovine cuts boneless, frozen) Value imported in Quantity Quantity Annual growth in Annual growth in Share inImporters 1999, in US$ imported in unit value 1995- quantity 1995- world thousand 1999 1999, % 1999, % imports, % World estimation 4,494,507 2,182,725 Tons -2 2 100 United States of 1,031,987 541,944 Tons 5 6 22.96 fA.merica Japan 810,638 338,057 Tons -5 5 18.04 Russian Federation 228,727 198,142 Tons -1 8 5.09 Korea 220,894 83,166 Tons -10 -4 4.91 Egypt 215,332 132,922 Tons 6 4 4.79 Canada 186,221 104,925 Tons 1 5 4.14 Taiwan 140,707 55,548 Tons -2 4 3.13 Italy 117,541 37,092 Tons 5 12 2.62 Israel 112,563 48,798 Tons 4 -1 2.50 Hone Kono 101131 37269 Tons -1 3 2.25 Spain 99,118 26,527 Tons -2 2 2.21 Germany 97,067 29,499 Tons '-14 -8 2.16 United Kingdom 93,349 41,191 Tons -17 -10 2.08 Malaysia 80,182 66,092 Tons -4 3 1.78 Netherlands 63,583 16,347 Tons -11 -10 1.41 Iran 60,168 25,272 Tons Na Na 1.34 France 59,934 21,527 Tons -1 6 1.33 Philippines 46,794 40,132 Tons 4 11 1.04 Mexico 46,094 29,623 Tons 20 33 1.03 Greece 42,797 23,580 Tons -15 -1 0.95 Sweden 42,288 10,886 Tons 0 12 0.94 Saudi Arabia 39,361 7,100 Tons -8 -33 0.88 249 Table B.5: Continues Value imported in Quantity Annual growth in Annual growth in Share inImporters 1999, in US$ imported in Quantity value 1995- quantity 1995- world thousand 1999 unit 1999, % 1999, % imports, % Portugal 32,642 8,200 Tons 12 21 0.73 ~Igeria 30,955 16,005 Tons -3 -5 0.69 Belgium 30,737 8,609 Tons 6 7 0.68 Chile 30,407 20,787 Tons -4 0 0.68 Singapore 28,279 12,096 Tons -10 -2 0.63 Indonesia 26,692 14,705 Tons -22 -22 0.59 Denmark 23,019 5,707 Tons 8 13 0.51 Brazil 20,228 7,529 Tons -29 -35 0.45 Malta 19,625 6,919 Tons 3 3 0.44 United Arab Emirates 14,838 5,160 Tons -3 -8 0.33 Bulgaria 12,014 10,596 Tons 0 5 0.27 Switzerland 11,921 3,231 Tons -3 -2 0.27 Cyprus 11,703 1,852 Tons 1 1 0.26 Finland 10,626 2,983 Tons 9 18 0.24 Oman 9,482 5,553 Tons -12 -17 0.21 SACU 8,913 14,439 Tons -37 -30 0.20 Bosnia and Herzegovina 8,688 5,376 Tons 7 10 0.19 ~ustria 8,630 2,810 Tons -17 -17 0.19 Norway 8,540 2,230 Tons 12 20 0.19 ~rmenia 8,024 7,715 Tons Na Na 0.18 Ireland 7,927 3,754 Tons -8 -5 0.18 ~ngola 7,911 4,112 Tons 8 11 0.18 French Polynesia 7793 3853 Tons -1 5 0.17 Kuwait 7,448 3,644 Tons 4 0 0.17 Mauritius 7,423 4,832 Tons -13 -13 0.17 Dominican Republic 7,026 4,085 Tons 274 365 0.16 Trinidad and Tobago 6,860 Na Na 17 Na 0.15 Croatia 6,551 3,853 Tons -13 -7 0.15 China 5,383 3,851 Tons 13 9 0.12 Ghana 5,046 4,172 Tons Na Na 0.11 Lebanon 5,000 1,944 Tons -8 -15 0.11 Jordan 4,910 2,991 Tons 49 54 0.11 Argentina 4,788 2,539 Tons 40 43 0.11 Bahrain 4,632 1,641 Tons 10 8 0.10 Romania 4,357 2,232 Tons 16 17 0.10 New Zealand 4,144 2,178 Tons -19 -19 0.09 Guatemala 3,960 2,463 Tons 124 135 0.09 Peru 3,950 2,010 Tons -10 -8 0.09 Netherlands fAntilles 3,894 1,627 Tons 29 42 0.09 !Venezuela 3,793 2,144 Tons 56 54 0.08 Barbados 3,779 1,388 Tons Na Na 0.08 250 Table B.5: Continues Value imported in Quantity Quantity Annual growth in Annual growth in Share inImporters 1999, in US$ imported in unit value 1995- quantity 1995- world thousand 1999 1999, % 1999, % imports, % El Salvador 3,743 1,470 Tons 191 158 0.08 Area Nes 3,719 1,468 Tons -21 -13 0.08 Macedonia 3496 2318 Tons 44 55 0.08 Greenland 3,406 563 Tons 4 6 0.08 Cuba 3,288 1,228 Tons 70 116 0.07 Papua New Guinea 3,263 3,338 Tons -30 -26 0.07 Comoros 3,127 2,354 Tons -2 -6 0.07 Bahamas 2,859 1,055 Tons 11 32 0.06 Tunisia 2,808 1,013 Tons -9 -10 0.06 Slovakia 2,804 1,888 Tons -7 0 0.06 Thailand 2,790 1,276 Tons 2 5 0.06 Gabon 2,457 2,073 Tons -21 -21 0.05 Note: Only countries with an import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table B.6: Imports of product 020311(Swine carcasses and half carcasses, fresh or chilled) Value imported in Quantity Share in Importers imported in Quantity Annual growth Annual growth 1999, in US$ unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % imports, % World estimation 893821 733686 Tons -11 4 100 Germany 357750 302440 Tons -16 -1 40.02 Italv 159220 105165 Tons -10 3 17.81 Greece 125840 133025 Tons -6 17 14.08 Singapore 36038 15108 Tons Na Na 4.03 Mexico 34232 30217 Tons 74 85 3.83 Portugal 27719 20723 Tons -7 6 3.10 Austria 26841 20569 Tons -12 4 3.00 United States of 11,206 Tons -1 America 19,339 1 2.16 France 15057 13971 Tons -25 -9 1.68 Belqium 12322 12199 Tons 26 55 1.38 Switzerland 10012 7355 Tons 15 34 1.12 Romania 9755 7582 Tons 273 266 1.09 Russian Federation 9,614 12,028 Tons -20 -15 1.08 Jnited Kingdom 7447 6594 Tons -18 -2 0.83 Slovenia 5940 5346 Tons -17 -5 0.66 Slovakia 4903 5126 Tons 119 143 0.55 Netherlands 4326 3817 Tons -18 -5 0.48 Estonia 4 111 3212 Tons 70 Na 0.46 Sweden 3719 2015 Tons -1 8 0.42 251 Table B.6: Continues Ireland 3154 1 417 Tons 21 30 0.35 Czech Republic 2376 2919 Tons 133 147 0.27 Poland 1795 2233 Tons Na Na 0.20 Lithuania 1747 1 194 Tons 271 292 0.20 Macedonia 1 504 1 168 Tons 70 96 0.17 Note: Only countries with an Import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table B.7: Imports of product 020312 (Hams, shoulders and cuts thereof, of swine bone in, fresh or chilled) Value imported in Quantity Quantity Annual growth Annual growth Share in Importers 1999, in US$ imported in unit in value 1995- in quantity world 1999 1999, % 1995-1999, % imports,thousand % World estimation 1 650859 1 097217 Tons -3 9 100 Italy 738756 481 609 Tons -4 8 44.75 France 242586 151 149 Tons -7 6 14.69 Germany 206802 149732 Tons -9 3 12.53 UnitedKingdom 124290 72114 Tons 12 22 7.53 USA 81 521 61099 Tons -5 3 4.94 Spain 56053 31949 Tons 32 40 3.40 Mexico 42555 54283 Tons 76 92 2.58 Austria 31362 15227 Tons 16 20 1.90 Portugal 30330 20901 Tons 5 21 1.84 Belgium 23573 14149 Tons -1 5 1.43 Sweden 14282 4924 Tons 23 30 0.87 Greece 10713 9708 Tons -1 18 0.65 Poland 8640 6868 Tons -22 -12 0.52 Ireland 5568 2211 Tons 5 11 0.34 Finland 5402 2529 Tons 17 34 0.33 Canada 5310 3926 Tons 34 45 0.32 Slovenia 5075 2707 Tons -6 2 0.31 Netherlands 4998 3753 Tons -23 -9 0.30 Croatia 1686 1 004 Tons -13 -9 0.10 Lithuania 1390 819 Tons 0.08 Denmark 1 312 472 Tons 66 64 0.08 ~aiwan 1247 951 Tons 0.08 Note: Only countries with an import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. 252 Table B.8: Imports of product 020319 (Swine cuts, fresh or chilled_,_nes) Value imported in Quantity Quantity Annual growth Annual growth Share in Importers 1999, in US$ imported in unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % imports, % World estimation 2350140 984220 Tons -7 5 100 Japan 828868 171 724 Tons -10 -1 35.27 Germany 449221 218847 Tons -12 -1 19.11 USA 210761 116325 Tons 4 14 8.97 France 159824 101 204 Tons -6 8 6.80 UnitedKinadom 123924 57177 Tons -7 3 5.27 Italy 99122 49813 Tons -7 4 4.22 Netherlands 75317 50397 Tons 1 19 3.20 Sweden 53607 11414 Tons 3 14 2.28 !Austria 45716 22208 Tons 4 14 1.95 Belaium 40520 25331 Tons -16 -3 1.72 Greece 35957 29317 Tons -1 20 1.53 Portuaal 30063 18813 Tons 13 28 1.28 Canada 29881 16680 Tons 12 9 1.27 Denmark 24742 13762 Tons 5 24 1.05 Finland 20624 6494 Tons -1 8 0.88 Mexico 20382 15581 Tons 38 32 0.87 Poland 19521 14762 Tons 18 29 0.83 Ireland 16659 5049 Tons 42 36 0.71 Switzerland 11 088 3073 Tons 107 123 0.47 CzechRepublic 7383 6932 Tons 32 37 0.31 HonaKona 6501 2096 Tons 244 219 0.28 Spain 6249 3231 Tons -23 -7 0.27 Hunaarv 5089 5804 Tons -20 -9 0.22 Slovakia 2877 3095 Tons 66 75 0.12 Korea 2701 851 Tons 105 114 0.11 Bosniaand Herzeaovina 2,640 1,355 Tons 77 86 0.11 Araentina 1 861 938 Tons 39 62 0.08 Slovenia 1770 967 Tons -19 -13 0.08 RussianFederation 1 383 1 394 Tons -46 -47 0.06 Andorra 1299 581 Tons -19 -10 0.06 Sinaaoore 1066 297 Tons 56 180 0.05 Note: Only countries with an import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. 253 Table B.9: Imports of product 020321 (Swine carcasses and half carcasses, frozen) Value Quantity Annual growth Annual growth Share in Importers imported in 1999, in US$ imported in Quantity unit in value 1995- in quantity world 1999 1999, % 1995-1999, % imports,thousand % World estimation 243920 251 064 Tons -5 8 100 RussianFederation 172 987 199143 Tons -9 9 70.92 HongKong 18917 9867 Tons 21 29 7.76 UnitedKinadom 7522 3593 Tons -7 7 3.08 Belarus 5084 4285 Tons Na Na 2.08 Sweden 3617 1374 Tons 248 317 1.48 Romania 3514 2669 Tons 68 65 1.44 Sinqapore 2917 1468 Tons -14 -8 1.20 Korea 2411 1649 Tons Na Na 0.99 Ukraine 2364 3865 Tons 16 35 0.97 Latvia 1882 2779 Tons -7 3 0.77 Portuaal 1 825 1 163 Tons 7 18 0.75 Philippines 1 708 1 848 Tons Na Na 0.70 rraiwan 1488 1 091 Tons 21 29 0.61 Germany 1 348 538 Tons 32 26 0.55 Spain 1 342 1 112 Tons -6 -1 0.55 Greece 1 314 482 Tons 11 16 0.54 Norwav 1290 1 150 Tons 666 908 0.53 Estonia 1260 1394 Tons -12 Na 0.52 Italy 1 188 801 Tons -16 -7 0.49 Poland 1052 1244 Tons Na Na 0.43 Note: Only countrres with an Import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table B.10: Imports of product 020322 (Hams, shoulders and cuts thereof, of swine bone in. frozen) Value imported in Quantity Quantity Annual growth Annual growth Share in Importers 1999, in US$ imported in unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % imports, % World estimation 286553 254687 Tons 4 20 100 RussianFederation 62778 67133 Tons 27 35 21.91 Spain 45602 34173 Tons 26 39 15.91 Italv 22280 13487 Tons -19 -10 7.78 France 20651 11244 Tons -13 -3 7.21 China 19583 48106 Tons 210 290 6.83 USA 18454 7977 Tons 7 9 6.44 Talwan 12147 7731 Tons 81 103 4.24 Portuqal 8443 5592 Tons -10 3 2.95 HonaKona 8088 8945 Tons -12 5 2.82 Germany 7837 5383 Tons -11 3 2.73 Mexico 6003 7462 Tons 25 32 2.09 254 Table 8.10: Continues Value Quantity Annual growth Annual growth Share in Importers imported in 1999, in US$ imported in Quantity unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % imports, % UnitedKingdom 5267 2766 Tons -3 -20 1.84 Poland 3666 2711 Tons 11 18 1.28 Finland 3630 1 514 Tons 37 57 1.27 Panama 3428 2466 Tons 283 326 1.20 NewZealand 3212 1 875 Tons 21 38 1.12 Belgium 2770 1440 Tons 19 25 0.97 Netherlands 2723 2335 Tons -5 20 0.95 Austria 2235 1410 Tons 40 54 0.78 Japan 2226 466 Tons -17 -10 0.78 Ireland 2035 893 Tons 20 28 0.71 Cuba 1 765 1267 Tons 2 17 0.62 Trinidad 1460 0 No Quantity 17 0.51 Philiooines 1414 1 540 Tons 11 33 0.49 Canada 1223 724 Tons 17 22 0.43 Denmark 1 013 1270 Tons 12 17 0.35 Note: Only countrres with an Import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITe calculations based on eOMTRADE statistics, 2000. Table 8.11: Im~orts of product 020329 (Swine cuts frozen nes) Value imported in Quantity Annual growth Annual growth Share in Importers 1999, in imported in Quantityunit in value 1995- in quantity world US$ 1999 1999, % 1995-1999, % imports, thousand % World estimation 3876824 1 627452 Tons -7 6 100 Japan 2031 092 427513 Tons -10 -2 52.39 Korea Reo. of Korea 212615 121 601 Tons 14 32 5.48 Germany 196159 101 654 Tons -15 -4 5.06 USA 180608 69625 Tons 4 6 4.66 RussianFederation 160306 164021 Tons -3 13 4.13 HonoKono (SARC) 144293 112385 Tons 13 23 3.72 Italy 103950 57710 Tons -17 -6 2.68 France 78685 51295 Tons -15 -2 2.03 UnitedKinodom 70386 59986 Tons -11 5 1.82 ~rgentina 58605 34349 Tons 10 25 1.51 Canada 47384 17450 Tons 25 31 1.22 ~ustralia 43828 22112 Tons 32 44 1.13 Spain 37998 16777 Tons -12 -3 0.98 Greece 33901 18252 Tons -10 -4 0.87 Taiwan 33660 31 139 Tons 48 58 0.87 Denmark 32904 18485 Tons 1 16 0.85 Note: Only countrres with an Import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITe calculations based on eOMTRADE statistics, 2000. 255 Table 8.12: Imports of product 020410 (Lamb carcasses and half carcasses, fresh or chilled) Value imported in Quantity Quantity Annual growth Annual growth Share in Importers 1999, in US$ imported in unit in value 1995- in quantity world imports, thousand 1999 1999, % 1995-1999, % % !Worldestimation 552984 191 523 Tons -5 0 100 France 365696 116 122 Tons -5 -1 66.13 Italy 42079 10715 Tons -3 2 7.61 Belaium 36773 10159 Tons -4 -1 6.65 Greece 24116 22835 Tons 16 50 4.36 Germany 13469 4234 Tons -16 -12 2.44 Portugal 12884 4077 Tons -6 2 2.33 Spain 12569 3827 Tons -19 -16 2.27 SaudiArabia 8797 2706 Tons 9 4 1.59 UnitedArab Emirates 6,992 3,424 Tons -4 -1 1.26 UnitedKingdom 6277 5630 Tons -15 -9 1.14 USA 5782 2008 Tons 69 78 1.05 Switzerland 3137 749 Tons -19 -17 0.57 lArgentina 1839 1 242 Tons 2 6 0.33 Croatia 1742 415 Tons -19 -21 0.32 Netherlands 1679 468 Tons -3 2 0.30 Austria 1 046 272 Tons -34 -33 0.19 Andorra 1 018 213 Tons 9 13 0.18 Note: Only countries with an import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. Table 8.13: Imports of product 020422 (Sheeo cuts bone in. fresh or chilled) Importers Value Quantity Quantity Annual growth Annual growth Share in imported in imported in unit in value 1995- in quantity world 1999, in US$ 1999 1999, % 1995-1999, % imports, thousand % World estimation 291 077 58203 Tons 10 13 100 USA 77183 12250 Tons 31 34 26.52 France 43707 11 163 Tons 2 10 15.02 UnitedKinadom 36853 7664 Tons 9 7 12.66 Belgium 33838 5625 Tons 9 22 11.63 Switzerland 15641 1700 Tons 4 4 5.37 Germany 14997 2317 Tons -3 2 5.15 Canada 14401 3710 Tons 5 7 4.95 !Japan 8675 826 Tons 0 4 2.98 Italy 8042 1228 Tons 7 9 2.76 Netherlands 7617 747 Tons 10 4 2.62 Denmark 5581 713 Tons 149 118 1.92 !Austria 4587 353 Tons 30 23 1.58 SaudiArabia 4257 1924 Tons 10 8 1.46 HoneKono 1832 195 Tons 15 11 0.63 256 Table 8.13: Continues Importers Value Quantity Quantity Annual growth Annual growth Share in imported in imported in unit in value 1995- in quantity world 1999, in US$ 1999 1999, % 1995-1999, % imports, thousand % UnitedArab Fmirates 1,731 946 Tons 23 28 0.59 Taiwan 1 521 1 216 Tons 16 10 0.52 Sinaapore 1488 395 Tons 12 28 0.51 Note: Only countries with an Import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITe calculations based on eOMTRADE statistics, 2000. Table 8.14: Imports of product 020441 (Sheep carcasses and half carcasses, frozen) Importers Value Quantity Quantity Annual growth Annual growth Share in imported in imported in unit in value 1995- in quantity world 1999, in US$ 1999 1999, % 1995-1999, % imports, thousand % ~orld estimation 41 216 41 163 Tons -9 -4 100 Mexico 9226 10738 Tons 5 17 22.38 Korea 3883 4434 Tons -19 -17 9.42 Malaysia 3875 3407 Tons -4 0 9.40 Oman 2962 1885 Tons -3 5 7.19 Taiwan 2872 3649 Tons -5 -3 6.97 Sinaapore 2625 2297 Tons 1 7 6.37 Portugal 1884 770 Tons 17 22 4.57 RussianFederation 1441 1 522 Tons -25 -28 3.50 SaudiArabia 1 395 1557 Tons 1 3 3.38 Jamaica 1 153 1 525 Tons -12 -8 2.80 JSA 1 007 740 Tons -34 -33 2.44 Note: Only countries with an Import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITe calculations based on eOMTRADE statistics, 2000. Table 8.15: Imports of product 020442 (Sheep cuts bone in, frozen) Value imported Quantity Quantity Annual growth Annual growth Share in Importers in 1999, in US$ imported in unit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % imports,% World estimation 652000 328226 Tons 2 7 100 UnitedKinadom 164786 57021 Tons 0 4 25.27 USA 77 481 23492 Tons 12 11 11.88 Germany 56181 15821 Tons -4 -2 8.62 France 52275 17105 Tons -1 5 8.02 Belgium 28057 5962 Tons 5 3 4.30 Mexico 21663 23141 Tons 24 32 3.32 PapuaNew Guinea 19,062 26,688 Tons -10 -6 2.92 SaudiArabia 17465 15719 Tons 13 18 2.68 257 Table 8.15: Continues Value imported Quantity Annual growth Annual growth Share in Importers in 1999, in US$ imported in Quantityunit in value 1995- in quantity world thousand 1999 1999, % 1995-1999, % imports,% Canada 15947 6232 Tons 6 4 2.45 SACU 14958 35106 Tons 23 53 2.29 Soain 14713 4721 Tons 1 4 2.26 Uapan 13166 6518 Tons -9 -4 2.02 Italv 13059 4519 Tons 0 3 2.00 Greece 9403 4443 Tons 9 16 1.44 Netherlands 9165 2033 Tons -3 -6 1.41 Fiii 8911 10020 Tons 0 4 1.37 ~ordan 7925 6359 Tons -1 1 1.22 Taiwan 7839 4200 Tons 32 46 1.20 Note: Only countries with an Import value of more than US$10 000 000 or more than 1000 tons are included. Na - not available Source: ITC calculations based on COMTRADE statistics, 2000. 258 Appendix C: Trade in selected red meat products by SACU ~ ~~ , ~~ Exporters Imported Share in Imported Quantity Unit Import trend Import trend Ranking of Share of Total export value SACU's quantity unit value in value in quantity partner partner growth in value of 1999 in imports, 1999 1995-1999, 1995-1999, countries in countries in partner countries US$ % %,p.a. %, p.a. world world exports, 1995-99, %, p.a. thousand exports % Uruauav 709 63 1,187 Tons 0.6 na na 10 2 22 ~ustralia 366 33 642 Tons 0.6 -15 -3 4 10 2 ~imbabwe 37 3 28 Tons 1.3 nr nr 49 nr nr Na - not available Nr - not reported * - SACU ranks so" in world imports of this product Source: ITC calculations based on COMTRADE statistics, 2000. Iaore \J."': Imlaorts OT proauct u"'u"'~u (tsovme CUts noneress, rrozenj: Exporters Imported Share in Imported Quantity Unit Import trend Import trend Ranking of Share of Total export value 1999 SACU's quantity unit value in value in quantity partner partner growth in value of in US$ imports, 1999 1995-1999, 1995-1999, countries countries in partner countries thousand % %,p.a. %,p.a. in world world exports, 1995-99, %, p.a. exports %- Ireland 5,014 56.25 9,373 Tons 0.5 -30 -17 4 9 -4 Zimbabwe 1,724 19.34 1,159 Tons 1.5 87 105 27 0 -22 Belgium 1,348 15.12 2,760 Tons 0.5 -12 0 16 1 -20 Australia 299 3.35 465 Tons 0.6 -6 12 1 23 6 Argentina 216 2.42 221 Tons 1.0 -65 -67 7 4 -15 Uruguay 122 1.37 140 Tons 0.9 26 46 6 4 8 United Kingdom 78 0.88 150 Tons 0.5 -82 -80 31 0 -60 Iran 72 0.81 98 Tons 0.7 -47 -40 67 0 Na Denmark 28 0.31 48 Tons 0.6 15 1 -10 Germany 10 0.1_1_ 24 Tons 0.4 -57 -41 9 3 -7 NA - not available * - SACU ranks 38th in world imports in this product ** - rounded Source: ITC calculations based on COMTRADE statistics, 2000. 259 - ---_ - - - - - - -_ - - - - -- - - - - - -- -- - - - - - - -- - - - - - - - _- -- - - - - - - - - - - - Exporters Imported Share in Imported Quantity Unit Import trend in Import trend Ranking of Share of Total export I value 1999 SACU's quantity unit value value 1995- in quantity partner partner growth in value; in US$ imports, % 1999 1999, %, p.a. 1995-1999, countries in countries in of partner I thousand %, p.a. world exports world countries 1995-1 exports, 99, %, p.a. 0/0** France 5,999 53.31 5,386 Tons 1.1 13 64 2 8 5 Hungary 1,582 14.06 1,485 Tons 1.1 -16 13 12 3 -3 Belgium 1,344 11.94 1,832 Tons 0.7 -2 52 8 3 -15 United Kingdom 1,104 9.81 1,481 Tons 0.7 -22 13 13 3 -10 Brazil 434 3.86 322 Tons 1.3 Na Na 9 3 9 Spain 357 3.17 325 Tons 1.1 Na Na 10 3 15 Canada 123 1.09 265 Tons 0.5 -57 -11 3 8 -1 ~imbabwe 111 0.99 62 Tons 1.8 -28 -27 37 0 -12 Ireland 91 0.81 141 Tons 0.6 34 111 14 2 -11 United States of 42 0.37 48 Tons 0.9 -28 19 4 8 7 ~merica Germany 22 0.20 24 Tons 0.9 Na Na 7 4 12 fA-ustria 17 0.15 13 Tons 1.3 Na Na 18 1 37 fA-ustralia 16 0.14 17 Tons 0.9 Na Na 17 1 15 t-,Hger 11 0.10 25 Tons 0.4 Na Na 58 0 Na --- NA - not available * - SACU ranks so" in world imports in this product ** - rounded Source: ITC calculations based on COMTRADE statistics, 2000. 260 Exporters Imported Share in Imported Quantity Unit Import trend Import trend Ranking of Share of Total export value 1999 SACU's quantity unit value in value in quantity partner partner growth in value in US$ imports, % 1999 1995-1999, 1995-1999, countries in countries in of partner thousand %,p.a. %,p.a. world exports world countries 1995- exports, 99,%, p.a. 0/0** ~ustralia 13,491 90.19 31,702 Tons 0.4 20 51 2 23 7 New Zealand 1,352 9.04 3,118 Tons 0.4 83 129 1 67 0 United Kingdom 45 0.30 127 Tons 0.4 Na Na 5 1 -5 , Ireland 35 0.24 68 Tons 0.5 Na Na 10 0 36 NA - not available * - SACU ranks io" in world imports in this product ** - rounded Source: ITC calculations based on COMTRADE statistics, 2000. Table C.S: Exports of product 020220 (Bovine cuts bone in, frozen)* Exported Share in Export trend Export trend Ranking of Share ofvalue Exported partner partner Total import : Importers 1999 in SACU'sexports, quantity Quantity Unit in value in quantity growth in value of' 1999 unit value 1995-1999, 1995-1999, countries in countries in US$ % %, p.a. %, p.a. world r,vorld imports, partner countries thousand imports %* 1995-99,%, p.a. I Mozambique 858 12.55 582 Tons 1.5 77 Na 35 0 77 Angola 455 6.66 160 Tons 2.8 42 Na 41 0 13 Portugal 374 5.47 71 Tons 5.3 Na Na 20 0 3 Italy 298 4.36 53 Tons 5.6 Na Na 4 4 79 Belgium 247 3.61 47 Tons 5.3 21 Na 24 0 22 Gabon 188 2.76 62 Tons 3.0 Na Na 43 0 -2 France 122 1.78 16 Tons 7.6 Na Na 19 1 -12 Hong Kong (SARC) 89 1.30 29 Tons 3.1 124 Na 6 3 -3 Seychelles 87 1.27 23 Tons 3.8 39 Na 68 0 52 Congo 85 1.24 26 Tons 3.3 39 Na 85 0 18 Malaysia 79 1.16 16 Tons 4.9 122 Na 15 1 -12 Cóte d'lvoire 61 0.89 16 Tons 3.8 99 Na 64 0 12 Tanzania 60 0.88 16 Tons 3.8 50 Na 128 0 261 Table C.S: Continues Exported value Share in Exported Export trend Export trend Ranking of Share of partner partner Total import Importers 1999 in SACU'sexports, quantity Quantity Unit in value in quantity unit value 1995-1999, 1995-1999, countries in countries in growth in value of US$ 1999 partner countries thousand % %, p.a. %,p.a. world r.vorld imports, imports %* 1995-99, %, p.a. Mauritius 56 0.82 22 Tons 2.5 Na Na 97 0 -45 German_y 49 0.72 9 Tons 5.4 Na Na 10 2 20 Netherlands 49 0.72 7 Tons 7.0 Na Na 37 0 -30 Democratic Republic of the 41 0.60 13 Tons 3.2 76 Na 93 0 76 Congo Ghana 23 0.34 4 Tons 5.8 16 Na 69 0 ~apan 22 0.32 3 Tons 7.3 Na Na 3 4 -13 fur!g~Qre 18 0.26 3 Tons 6.0 63 Na 23 0 -18- NA - not available * - SACU ranks 13th in world exports in this product ** - rounded Source: !TC calculations based on COMTRADE statistics, 2000. 1ante c.s: t:.x pons or proauct U:;lU:;l3U (tsovme cuts eoneiees, rrczenr Exported Share of value Share in Ranking of Total import I SACU's Exported Quantity Unit Export trend Export trend partner partner growth in value I Importers 1999 in quantity unit value in value 1995- in quantity 1995-1999, countries in countries in world of partner US$ exports,% 1999 1999, %, p.a. %,p.a. world imports, countries 1995-1housand imports %** 99, %, p.a. Kuwait 469 27.27 144 Tons 3.3 Na Na 46 0 4 I MozambiQue 324 18.84 208 Tons 1.6 -44 Na 119 0 -44 I Comoros 195 11.34 71 Tons 2.7 47 Na 70 0 -2 Libyan Arab 164 9.53 59 Tons 2.8 Na Na 94 0 -37 Jamahiriya lAngala 142 8.26 53 Tons 2.7 -7 Na 44 0 8 United Arab 96 5.58 26 Tons 3.7 Na Na 32 0 -3 Emirates IGermany 67 3.90 12 Tons 5.6 -78 Na 12 2 -14 IBelgium 64 3.72 __ 1J _ Tons 3.8 -58 Na 25 1 6- 262 Table C.6: Continues Ranking of Share ofExported value Share in Exported Export trend Export trend partner partner Total import SACU's Quantity Unit in quantity countries in growth in valueImporters 1999 in exports, quantity unit value in value 1995- 1995-1999, countries inUS$ 1999 1999, %, p.a. world world of partner % %, p.a. imports, countries 1995-housand imports 0/0** 99, %, p.a. Nigeria 58 3.37 7 Tons 8.3 Na Na 146 0 172 Netherlands 44 2.56 22 Tons 2.0 Na Na 15 1 -11 United Kingdom 26 1.51 40 Tons 0.7 Na Na 13 2 -17 Norway 19 1.10 55 Tons 0.3 -62 Na 41 0 12 France 12 0.70 33 Tons 0.4 Na Na 17 1 -1 Democratic Republic of the 11 0.64 32 Tons 0.3 6 Na 105 0 -42 Congo NA - not available * - SACU ranks 36th in world exports in this product ** - rounded Source: ITC calculations based on COMTRADE statistics, 2000. Importers Exported Share in Exported Quantity Unit Export trend Export trend Ranking of Share of Total import value 1999 SACU's quantity unit value in value in quantity partner partner growth in value in US$ exports, 1999 1995-1999, 1995-1999, countries in countries in of partner thousand % %,p.a. %, p.a. world imports world countries 1995- imports, 99, %, p.a. 0/0** Singapore 978 66.00 660 Tons 1.5 -19 Na 22 1 12 New Zealand 215 14.52 120 Tons 1.8 64 Na 24 0 19 Hong Kong 97 Tons 1.5 -28 Na 6 4 13 I(SARC) 141 9.52 Angola 86 5.81 32 Tons 2.7 -1 Na 53 0 38 Mozambique 22 1.49 11 Tons 2.0 38 Na 137 0 38 Mauritius 11 0.74 3 Tons 3.7 48 Na 94 0 59 NA - not available * - SACU ranks zs" in world exports in this product Source: ITC calculations based on COMTRADE statistics, 2000. 263 Appendix D Comparison of trade statistics reported by the iTe and the Department of Customs and Excise Import and exports statistics reported in Chapter 3 were soureed from the ITC, who base their import and export statisties on the COMTRADE database. SACU did not report trade statistics to the COMTRADE database until 1999. In other words, the trade statistics reported for SACU were obtained from the exporting or importing country that does report to the COMTRADE database. Hence, it may be possible that certain exports or imports are not accounted for by the ITC. Tables 0.1 to 0.4 compare trade data for 1998 by the ITC and the Department of Customs and Excise in South Africa for selected bovine meat products imported and exported by SACU in order to point out the discrepancies in data between the two sources. It is believed that the same discrepancies will hold for the other products. Table 0.1 compares import statistics for bovine cuts (boneless, fresh or chilled; HS code 020130). According to the ITC, Ireland, Australia and the Netherlands reported that they exported this product to SACU. Conversely, C&E statistics suggest that only the Netherlands exported this product to SACU. Zimbabwe is also reported to have exported this product to SACU, but is not captured by the ITC since Zimbabwe does not formally report trade statistics to the COMTRADE database. Due to these discrepancies one would expect the total imports reported by the two sources to differ, but not to the magnitude presented in Table 0.1. Also noteworthy is the large difference in the unit value of imports of the Netherlands reported by the ITC and the C&E, respectively. 264 Table 0.1: Comparison of import statistics reported by ITC and the Department of Customs and Excise on bovine cuts (boneless, fresh or chilled; HS code 020130) ITC statistics Customs and Excise(C&E) statistics Exporters to Unit value Unit value SACU Imported Imported Imported Imported (ITC) (Rlkg) (C&E) (Rlkg) value 1998 in quantity value 1998 in quantity Rand (000) 1998 (ton) Rand (000) 1998 (ton) Total 4839 622 2200 222 1.18 9.90 Ireland 3971 514 Nr Nr 7.72 Nr Australia 614 104 Nr Nr 5.90 Nr Netherlands 254 4 208 4.51 63.60 46.01 Zimbabwe Nr Nr 1993 217.7 Nr 9.15 NR - Not recorded Source: ITC, 2000; NDA, 2000. Table D.2 compares the export statistics of bovine cuts (boneless, fresh or chilled; HS code 020130). According to the ITC total exports of this product amounted to 13 932 tons, but the C&E quotes a figure of 6 285 tons to the same destinations, except for Hong Kong for which no data is reported by the C&E. Taking into account the additional 13 countries to which this product was exported to according to the C&E, the quantity exported is still 4 553 tons less that the amount reported by the ITC (Total exports to all destinations amounted to 9379 tons according to the C&E). The large discrepancies in terms of the value and quantity exported on a country basis should also be noted. Probably most significant are the large differences in the unit value of exports. The average unit value reported by the ITC is R32.37 per kg, whilst that of the C&E amounts to R8 per kg. Economic logic would suggest that the former is a much better portrayal of reality since exporters would rarely go through all the trouble of exporting a product at lower prices than they could realise on the domestic market given that South Africa is a net importer of bovine meat products. The small deviations in the unit values reported by the ITC augments this line of thinking. 265 Table 0.2: Comparison of exports statistics reported by ITC and the Department of Customs and Excise on bovine cuts (boneless, fresh or chilled; HS code 020130) ITC statistics Customs and Excise(C&E) statistics Unit value Unit ValueImporters from Exported Exported Export value Exported . (ITC) (C&E)SACU value 1998 in quantity 1998 in Rand quantity in (Rlkg) (Rlkg) Rand (000) 1998(ton) (000) 1998 (ton) ITotal 450943 13932 50288 6285 32.37 8.00 United Kingdom 320159 10026 17084 4155 31.93 4.11 IGermany 54498 1633 3297 719 33.37 4.58 France 37952 1223 137 32 31.03 4.28 Norway 29093 847 29746 1377 34.35 21.60 Switzerland 9118 200 4 0.24 45.59 18.59 Hong_Kong 82 2 Nr Nr 41.48 Nr Malaysia 38 1 17 0.51 38.71 34.46 Note - Only countries on which the ITC reports export statistics are included in the table for comparison purposes. C&E list an additional 13 countries to which SACU exported. Source: ITC, 2000; NDA, 2000. Table 0.3 compares the imports of bovine cuts (boneless, frozen; HS code 020230). Although the differences in terms of the total imports of this product is not as large as those reported in Table 0.1 discrepancies on the basis of individual country for countries reported by both the ITC and the C&E, are still considerable. Also, it should be noted that the unit value of imports of this products as reported by the ITC is higher than that reported by the C&E. This may be indicative of the common belief that importers make themselves guilty of under-invoicing of imports in order to lower their burden in terms of customs duties. 266 Table 0.3: Comparison of import statistics reported by ITC and the Department of Customs and Excise on bovine cuts (boneless, frozen; HS code 020230) ITC statistics Customs and excise(C&E) statistics Exporters Unit value Unit valueImported Imported Importedquantity Imported quantity (ITC) (Rlkg) (C&E) (Rlkg)value 1998 in 1998 value 1998 inRand (000) (tons) Rand (000) 1998 (tons) Total 99568 15195 53578 12951 6.55 4.14 Ireland 49687 7384 26909 7279 6.73 3.70 fA,ustralia 26444 4512 11495 2645 5.86 4.35 Belgium 9672 1565 9028 1941 6.18 4.65 New Zealand 4253 633 617 123 6.72 5.01 US 3578 372 Nr Nr 9.62 Nr ~rgentina 3196 393 699 185 8.13 3.78 Uruguay 1410 193 744 156 7.31 4.76 France 382 62 364 78 6.15 4.68 Norway 371 18 Nr Nr 20.58 Nr Portugal 315 24 Nr Nr 13.13 Nr Germany 133 12 57 23 11.06 2.49 Canada 111 25 92 24 4.42 3.88 Botswana Nr Nr 39 18 Nr 2.15 United Kingdom Nr Nr 76 15 Nr 5.23 India Nr Nr 22 6 Nr 3.63 Iran Nr Nr 506 125 Nr 4.06 Ukraine Nr Nr 56 15 Nr 3.68 Zimbabwe Nr Nr 2872 317 Nr 9.06 Source: ITC, 2000; NDA, 2000. Table 0.4 compares the exports of bovine cuts (boneless, frozen; HS code 020230). For all countries included, in other words also the 16 countries not reported in Table 0.4, the C&E reports total exports at 8 662 tons. This is 2 465 tons lower than the exports reported by the ITC in Table 0.4. Also notable is the large difference in the total value of export, as well as on an individual country basis. As was the case in Table 0.2, the unit value of exports also shows large discrepancies. It is difficult to anticipate why exporters will export this product at a lower unit price than could be realised on the domestic market, especially if it is known that exports of this product is usually of exceptional quality. 267 Table 0.4: Comparison of exports statistics reported by ITC and the Department of Customs and Excise on bovine cuts (boneless, frozen; HS code 020230) ITC statistics Customs and excise(C&E) statistics Unit value Exporters Exported Exported Exported Exported (ITC) Unit value value 1998 in quantity value 1998 in quantity (Rlkg) (C&E) (Rlkg) Rand 1998 Rand 1998 thousand (tons) thousand (tons) Total 170556 11127 31681 7882 15.33 4.02 Germany 48039 2963 4618 1891 16.21 2.44 Greece 38931 3095 5005 2349 12.58 2.13 United Kingdom 31394 2067 2977 1484 15.19 2.01 Norway 26577 1248 18533 2001 21.30 9.26 Netherlands 10059 737 393 148 13.65 2.65 Belgium 8372 617 151 5 13.57 26.24 France 7012 375 Nr Nr 18.70 Nr Hong Kong 171 25 1.8 0.05 6.86 34.17 Note - Only countries on which the ITC reports export statistics are included in the table for comparison purposes. C&E list an additional16 countries to which SACU exported. Source: ITC, 2000; NDA, 2000. In the light of the above discussion it should be understandable why this study rather uses the ITC statistics to report on trade rather than the official Customs and Excise data. Koester and Loy (1996) also questioned the reliability of the information on trade provided by the Department of Customs and Excise in South Africa due to factors such as rent seeking by importers and exporters. It is, however, not suggested that the ITC statistics are entirely correct, but rather that it provides a more reliable picture of imports and exports for those countries that are reported jointly by the ITC and the C&E. It also places question marks over the C&E data reported for countries not covered by the ITC. This state of affairs is not satisfactory and should receive serious attention, especially if one considers that strategic marketing decisions based on wrong information in a globalised world could be catastrophic. 268