MARKET POWER AND COMPETITIVE ANALYSIS OF CHINA'S SOYBEAN IMPORT MARKET

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1 Unversty of Kentucky UKnowledge Unversty of Kentucky Doctoral Dssertatons Graduate School 2006 MARKET POWER AND COMPETITIVE ANALYSIS OF INA'S SOYBEAN IMPORT MARKET Baohu Song Unversty of Kentucky, Clck here to let us know how access to ths document benefts you. Recommended Ctaton Song, Baohu, "MARKET POWER AND COMPETITIVE ANALYSIS OF INA'S SOYBEAN IMPORT MARKET" (2006). Unversty of Kentucky Doctoral Dssertatons Ths Dssertaton s brought to you for free and open access by the Graduate School at UKnowledge. It has been accepted for ncluson n Unversty of Kentucky Doctoral Dssertatons by an authorzed admnstrator of UKnowledge. For more nformaton, please contact UKnowledge@lsv.uky.edu.

2 ABSTRACT OF DISSERTATION Baohu Song The Graduate School Unversty of Kentucky 2006

3 MARKET POWER AND COMPETITIVE ANALYSIS OF INA S SOYBEAN IMPORT MARKET ABSTRACT OF DISSERTATION A dssertaton submtted n partal fulfllment of the requrements for the degree of Doctor of Phlosophy n the College of Agrculture at the Unversty of Kentucky By Baohu Song Lexngton, Kentucky Drector: Dr. Mary A. Marchant, Professor of Agrcultural Economcs Lexngton, Kentucky 2006 Copyrght Baohu Song 2006

4 ABSTRACT OF DISSERTATION MARKET POWER AND COMPETITIVE ANALYSIS OF INA S SOYBEAN IMPORT MARKET Globally, Chna s the number one soybean mporter, and the Unted States, Brazl, and Argentna are the top three soybean exporters. Ths research, based on the reverse resdual demand model, developed and estmated a two-country partal equlbrum trade model to test who has stronger market power n the Chnese soybean mport market. Ths two-country partal equlbrum trade model ncorporates the U.S. resdual soybean supply for Chna, the Chnese resdual demand for U.S. soybeans, and the equlbrum condton, where the U.S. resdual soybean supply equals the Chnese resdual soybean demand. Data used n ths research are monthly data from January 1999 to February 2005, 74 observatons. Emprcal results ndcated that Chnese soybean mporters have stronger market power relatve to U.S. soybean exporters. Ths research also conducted the compettve analyss of the Chnese soybean mport market by examnng both annual and monthly data of Chnese soybean mports from the U.S. and South Amerca (Brazl and Argentna). Results mpled that the U.S. and South Amerca are seasonal complementary soybean supplers for Chna. Possble reasons nclude: 1) seasonal dfference--the U.S. and South Amerca have opposng growng seasons,.e., dfferent tme perods to supply soybeans to markets; and 2) stronger market power of Chnese soybean mporters Chna s strategc choce, dversfyng ther soybean supplers and reducng prce ncrease rsk, made the U.S. and South Amerca complementary soybean supplers to Chna. Addtonally, ths research compared the soybean export costs to Chna for the three countres. Results showed that Brazl has the greatest advantage for producton costs, followed by Argentna and the U.S.; the U.S. has the greatest advantage for nternal and nternatonal transportaton and marketng costs, followed by Argentna and Brazl. In aggregate, the total soybean export costs for Brazl were the lowest and the export costs for Argentna were the hghest, wth U.S. costs between them.

5 In terms of polcy mplcatons for the U.S. soybean ndustry facng strong competton from South Amerca, we cannot expect that U.S. market share n the Chnese soybean mport market can be expanded much. Wth the development of nfrastructure n Brazl and Argentna, the U.S. advantage wll become less and less. Therefore, f the U.S. soybean ndustry wants to keep ts current poston n the Chnese soybean mport market, some governmental polcy supports are stll necessary. KEYWORDS: Chnese Soybean Import Market, Compettve Analyss, Market Power, Two-Country Partal Equlbrum Trade Model, Soybean Polces Baohu Song May 15, 2006

6 MARKET POWER AND COMPETITIVE ANALYSIS OF INA S SOYBEAN IMPORT MARKET By Baohu Song Mary A. Marchant Drector of Dssertaton Davd Freshwater Drector of Graduate Studes

7 RULES FOR THE USE OF DISSERTATIONS Unpublshed dssertatons submtted for the Doctor s degree and deposted n the Unversty of Kentucky Lbrary are as a rule open for nspecton, but are used only wth due regard to the rghts of the authors. Bblographcal references may be noted, but quotatons or summares of parts may be publshed only wth permsson of the author, and wth the usual scholarly acknowledgments. Extensve copyng or publcaton of the dssertaton n whole or n part also requres the consent of the Dean of the Graduate School of the Unversty of Kentucky. A lbrary that borrows ths dssertaton for use by ts patrons s expected to secure the sgnature of each user. Name Date

8 DISSERTATION Baohu Song The Graduate School Unversty of Kentucky 2006

9 MARKET POWER AND COMPETITIVE ANALYSIS OF INA S SOYBEAN IMPORT MARKET DISSERTATION A dssertaton submtted n partal fulfllment of the requrements for the degree of Doctor of Phlosophy n the College of Agrculture at the Unversty of Kentucky By Baohu Song Lexngton, Kentucky Drector: Dr. Mary A. Marchant, Professor of Agrcultural Economcs Lexngton, Kentucky 2006 Copyrght Baohu Song 2006

10 ACKNOWLEDGMENTS I would lke to express my great grattude and sncere apprecaton to Dr. Mary Marchant for her nvaluable contrbuton and drecton. Her academc gudance, dedcaton, and extreme patence made possble the successful completon of ths dssertaton. Her knowledge, nsghtful comments and hgh standards were nstrumental n helpng develop my research and mprovng my wrtng sklls. Next, I wsh to express my deepest apprecaton to the members of my dssertaton commttee, Dr. Mchael R. Reed, Dr. Mukhtar Al, Dr. Legh J. Maynard, and Dr. Glenn Blomqust for ther nvaluable comments, crtques, and advse that enrched ths dssertaton. Ths dssertaton would not have been feasble wthout the fnancal support from the graduate school and Dr. Marchant. The Dssertaton Enhancement Award I won from the graduate school and partal fnancal support by Dr. Marchant enabled me to go to Chna and collect ndspensable data for ths research. Wthout ther support, ths research cannot be done! I would lke to gve my sncere thanks to Dr. Robbns, our department Char. He generously supported my trps to many professonal meetngs lke Amercan Agrcultural Economcs Assocate annual meetngs, Southern Agrcultural Economcs Assocaton annual meetngs, and other professonal meetngs to present my research results. Wthout the department support, my research could not have been well recognzed n our professon. In addton, I also thank all the staff members n our department, ther full support and servces guaranteed my research went smoothly and successfully. Fnally, my thanks and apprecaton to my wfe Shuang Xu for her love, understandng, and treless support durng those busy days! Under God s mercy and grace, we are studyng n the same department, sharng the same offce, enjoyng hs love together. All the honors and prase belong to God, our savor!

11 TABLE OF CONTENTS ACKNOWLEDGMENTS.... LIST OF TABLES v LIST OF FIGURES...v APTER ONE INTRODUCTION.1 Background..1 Objectves of Research 3 Organzaton of the Dssertaton.5 APTER TWO OUTLOOK OF THE WORLD SOYBEAN INDUSTRY.7 Leadng Global Soybean Producng Countres.7 Leadng Global Soybean Consumers 9 Leadng Global Soybean Exporters. 11 Leadng Global Soybean Importers. 13 Summary 14 APTER THREE SOYBEAN POLICY REVIEW.17 Soybean Polces n the Unted States 17 U.S. Soybean Polces..17 U.S. Botech Polces.23 Brazlan Soybean Polces 25 Brazlan Agrcultural Polces...25 Brazlan Botech Polces 29 Argentnean Soybean Polces...30 Argentnean Agrcultural Polces..30 Argentnean Botech Polces.. 32 Chnese Botech Polces and Soybean Trade.. 33 Chna s Stuaton and Outlook...33 Chnese Botech Polces and Trade Impacts...35 APTER FOUR LITERATURE REVIEW The Lerner Index Prcng to Market Model...41 Resdual Demand Elastcty Model 44 Revew of World Soybean Market Studes.. 50 The FAPRI/CARD Internatonal Olseed Model 50 The ERS/Penn State Trade Model.. 53 v

12 APTER FIVE THEORETICAL MODEL Introducton Modfcaton of the Lerner Index from the Exporters Perspectve Modfcaton of the Lerner Index from the Importers Perspectve Chna s Inverse Resdual Soybean Demand Model...64 Exportng Country s Inverse Resdual Soybean Supply Model The Two-Country Partal Equlbrum Trade Model.. 67 APTER SIX VARIALBE IDENTIFICATION 69 Chna s Inverse Resdual Soybean Demand Model 69 Exportng Country s Inverse Resdual Soybean Supply Model 72 Two-Country Partal Equlbrum Trade Model. 73 APTER SEVEN EMPIRICAL ESTIMATION AND INTERPRETATION. 76 Introducton..76 Data Descrpton.76 Specfcaton Test 82 Heteroskedastcty Test..83 Autocorrelaton Test...84 Multcollnearty Test Emprcal Estmaton and Interpretaton APTER EIGHT COMPETITIVE ANAYSIS OF INA S SOYBEAN IMPORT MARKET...92 The U.S., Brazl, and Argentna n the Chnese Soybean Import Market.92 Are the U.S. and South Amerca Substtutve Soybean Supplers for Chna?...95 The U.S. and South Amerca Are Seasonal Complementary Soybean Supplers for Chna Compettveness Comparson among the U.S., Brazl, and Argentna n the Chnese Soybean Import Market Summary APTER NINE CONCLUSIONS Summary and Conclusons Polcy Implcatons Future Research REFERENCES VITA. 118 v

13 LIST OF TABLES Table 1. Man U.S. Botech Varetes (Percent of Planted Acreage).23 Table 2. Summary Results of Resdual (Inverse) Demand Elastctes.49 Table 3. Commodty and Country Coverage of the FAPRI/CARD Internatonal Olseed Model.51 Table 4. Country and Commodty Coverage of the ERS/Penn State Trade Model..54 Table 5. Varables and Ther Sources.77 Table 6. Whte s Test Results for Heteroskedastcty.83 Table 7. Test Results for Autocorrelaton 85 Table 8. Correlaton between Independent Varables for the Chnese Inverse Resdual Demand for U.S. Soybeans.. 86 Table 9. Correlaton between Independent Varables for the U.S. Inverse Resdual Soybean Supply for Chna.87 Table 10. Estmaton Results of the Two-country Partal Equlbrum Model.89 Table 11. Summary of the Estmaton Results...91 Table 12. Soybean Export Costs of the U.S., Brazl, and Argentna..104 v

14 LIST OF FIGURES Fgure 1. The Top Fve Agrcultural Commodtes n the World (Harvested Area) 1 Fgure 2. Internatonal Trade Ratos for the Top Fve Agrcultural Commodtes..2 Fgure 3. Global Harvested Area for Soybeans.7 Fgure 4. Leadng Global Soybean Producng Countres.8 Fgure 5. Leadng Global Soybean Consumers.9 Fgure 6. Comparson of Soybean Usage Dstrbuton..10 Fgure 7. Leadng Global Soybean Exporters 12 Fgure 8. Export Shares of Top Soybean Exporters n the World Soybean Market 12 Fgure 9. Leadng Global Soybean Importers.14 Fgure 10. The Global Soybean Market 15 Fgure 11. Comparson of Planted Acres for U.S. Soybeans, Corn, and Wheat.18 Fgure 12. U.S. Net Expendtures on the Soybean Industry..19 Fgure 13. U.S. Loan Rate for Soybeans 21 Fgure 14. U.S. Soybean Producton, Consumpton, Exports, and Stocks 22 Fgure 15. Brazlan Soybean Producton, Consumpton, Exports, and Stocks 29 Fgure 16. Argentnean Soybean Producton, Consumpton, Exports, and Stocks 32 Fgure 17. Chnese Soybean Producton, Consumpton, Imports, and Exports.34 Fgure 18. Chnese Net Imports of Soybeans..35 Fgure 19. Hstory of Chna s Botech Regulatons 37 Fgure 20. Exchange Rate between Chnese Yuan (RMB) and U.S. Dollars.44 Fgure 21. Chna s Resdual Demand for Country s Soybeans.57 Fgure 22. Exportng Country s Resdual Soybean Supply for Chna 61 Fgure 23. Chnese Personal Dsposable Income: Annual and Monthly 79 Fgure 24. U.S. Personal Dsposable Income: Annual and Monthly.81 Fgure 25. Soybean Surplus n Man Soybean Exportng Countres 93 Fgure 26. Soybean Shortage n Man Soybean Importng Countres.. 93 Fgure 27. Chnese Soybean Import Market 95 Fgure 28. Chnese Soybean Imports from the U.S. and South Amerca.96 Fgure 29. Chnese Soybean Import Prces from the U.S., Brazl, and Argentna.97 Fgure 30. Chna s Soybean Imports from the U.S. and Soybean Stocks n SA...98 v

15 Fgure 31. Chna s Soybean Imports from SA and Soybean Stocks n the U.S...99 Fgure 32. U.S. Soybean Stocks. 100 Fgure 33. Brazlan Soybean Stocks Fgure 34. Average Monthly Soybean Exports from the U.S. and South Amerca (Brazl and Argentna) to Chna ( ) v

16 APTER ONE INTRODUCTION Background From a global perspectve, soybeans are among the top fve agrcultural commodtes n harvested area wheat, rce, corn, soybeans, and barley. As shown n Fgure 1, n 2004 the harvested area for soybeans reached 92 mllon hectares, rankng fourth (FAO, 2005). Among these fve commodtes, the nternatonal trade rato (export volume dvded by producton) for soybeans was hghest, followed by wheat, barley, corn, and rce. Fgure 2 shows that after 2000, about 30% of soybeans were traded on the world market (FAO, 2005). Ths fact mples that nternatonal trade for soybeans s crucal for and of nterest to both soybean exportng and mportng countres Mllon Hectares Wheat Rce Corn Soybeans Barley Fgure 1. The Top Fve Agrcultural Commodtes n the World (Harvested Area) Source: FAOSTAT-Agrculture,

17 % Soybeans Wheat Barley Corn Rce Fgure 2. Global Internatonal Trade Ratos for the Top Fve Agrcultural Commodtes Source: FAOSTAT-Agrculture, From a producton perspectve, the U.S., Brazl, Argentna, and Chna are the top four soybean producers n the world. The sum of soybean producton from these four countres accounted for 90% of the world total n 2004, wth the U.S. at 39%, Brazl at 25%, Argentna at 18%, and Chna at 8% (USDA-FAS, 2006b). In addton, the U.S., Brazl, and Argentna were also the top three global soybean exporters, and the sum of soybean exports from these three countres accounted for 92% of the world total n 2004, wth the U.S. at 46%, Brazl at 32%, and Argentna at 15%. From an mport perspectve, the top four soybean mportng countres are Chna, the European Unon (EU), Japan, and Mexco. The sum of soybean mports from these 2

18 four countres accounted for 76% of the world total, wth Chna at 40%, the EU at 24%, Japan at 7%, and Mexco at 6% n The U.S. leads the world n soybean producton, consumpton, and exports. However, n the last decade, soybean ndustres n Brazl and Argentna developed very quckly and became strong compettors for the U.S. n the world soybean market. Excess supply of soybeans from the U.S., Brazl, and Argentna ncreased quckly n recent years. To deal wth ths soybean surplus, Chnese soybean mport market became a prmary consderaton. Although Chna s a large soybean producer, Chna s also the number one soybean mporter n the world. Excess soybean demand by Chna skyrocketed n the last decade. Wth 1.3 bllon people, rapd economc growth, and rapd development of the lvestock ndustry, the Chnese soybean demand s expected to contnue to ncrease, as a man source of food ol for human consumpton and feed for lvestock. In contrast, excess soybean demand by other man soybean mporters, ncludng the EU, Japan, and Mexco, have been qute stable. Therefore, Chna wll contnue to play a key role n the world soybean market. Objectves of Research Gven the above facts, the Chnese soybean mport market can be characterzed as ether monopsony, whereby Chnese soybean mporters have stronger market power relatve to soybean exporters, ncludng the U.S., Brazl, and Argentna, or olgopoly, whereby these three soybean exporters have stronger market power relatve to Chnese soybean mporters. Knowng who has stronger market power s of nterest to both soybean exportng countres and soybean mportng countres, especally the Unted 3

19 States snce soybeans are the Unted States number one bulk export commodty. Although the U.S. s currently the leader of the global soybean ndustry, the rapd development of Brazlan and Argentnean soybean ndustres s threatenng ths leadng poston. To enhance compettveness of the U.S. soybean ndustry and to expand U.S. market share n the Chnese soybean mport market, knowng the market poston and compettve status of these three man soybean supplers for Chna s crucal for the U.S. soybean ndustry to make producton and marketng decsons, and for U.S. polcymakers to formulate soybean polces. As the former secretary of the U.S. Department of Agrculture (USDA), Ann Veneman (2003), sad "One of the key objectves set forth n the Department s new strategc plan s the expanson of nternatonal marketng opportuntes. As the strategc plan and our earler revew of the U.S. food and agrcultural system n the 21st century make clear, expandng markets s crtcal to the long-term health and prosperty of Amercan agrculture. Wth 96 percent of the world s populaton lvng outsde the Unted States, future growth n demand for food and agrcultural products wll occur prmarly n overseas markets (Veneman, 2003). The objectves of ths research nclude (1) To provde a global outlook of the soybean ndustry; (2) To revew soybean polces and ther mpacts on soybean producton, exportaton, and mportaton for soybean exportng and mportng countres; (3) To develop a two-country partal equlbrum trade model and apply ths model to test market power for the Chnese soybean mport market; 4

20 (4) To analyze the compettve structure of these top three soybean supplers the Unted States, Brazl, and Argentna n the Chnese soybean mport market. Organzaton of the Dssertaton Ths dssertaton s dvded nto nne chapters. Chapter one ntroduces the background, objectves, and organzaton of ths dssertaton. Chapter two provdes an outlook of the global soybean ndustry. In ths chapter, abundant data and fgures draw a clear pcture of the world soybean ndustry, ncludng the leadng soybean producng and consumng countres along wth exportng and mportng countres. Chapter three revews soybean polces and ther mpacts on soybean producton and exports from the U.S., Brazl, and Argentna, as well as ther botech polces and mpacts on soybean exports nto Chna. Chapter four revews the lterature, ncludng the Lerner Index, whch s a prmary concept to measure market power, the prce to market model (PTM), whch focuses on the mpacts of the exchange rates on mport prces, and the resdual demand elastcty model, whch was commonly used n the lterature to emprcally test market power. Fnally, a revew of research on the soybean ndustry ncludes the Internatonal Olseed Model developed by the Food and Agrcultural Polcy Research Insttute (FAPRI) n the Center for Agrcultural and Rural Development (CARD), and the U.S. Department of Agrculture, Economc Research Servce (USDA-ERS)/Penn State Trade Model. Chapters fve, sx, and seven develop and estmate the model, ncludng dervaton of the theoretcal model (Chapter fve), varable dentfcaton (Chapter sx), and emprcal estmaton and nterpretaton (Chapter seven). Based on the results from 5

21 Chapter seven, Chapter eght conducts addtonal compettve analyss of the Chnese soybean mport market. The last chapter, Chapter nne, s dscusson and conclusons. 6

22 APTER TWO OUTLOOK OF THE WORLD SOYBEAN INDUSTRY Leadng Global Soybean Producers Global harvested area for soybeans ncreased steadly from 26 mllon hectares (63 mllon acres) n 1964 to 92 mllon hectares (226 mllon acres) n 2004 (Fgure 3; FAO, 2005). Durng ths perod ( ), the average annual growth rate of the global harvested area for soybeans was 3% Mllon Hectares Fgure 3. Global Harvested Area for Soybeans Source: FAOSTAT-Agrculture, Among global soybean producers, the top four countres are the U.S., Brazl, Argentna, and Chna, as shown n Fgure 4. In 2005, soybean output from these four countres reached 200 mllon metrc tons, accountng for 90% of the global total (USDA- FAS, 2006b). Among them, the U.S. led the world n soybean producton wth an output 7

23 of 84 mllon metrc tons n Brazlan soybean output reached 57 mllon metrc tons, about 76% of U.S. producton, and ranked second n the world. Argentna produced 41 mllon metrc tons of soybeans and Chna only produced 18 mllon metrc tons. Mllon Metrc Tons U.S. Brazl Argentna Chna Others Fgure 4. Leadng Global Soybean Producng Countres Source: USDA-FAS, 2006b. Fgure 4 also ndcates that the growth of soybean producton was qute stable for the U.S., Chna, and other countres. In the last four decades, the average annual growth rates of soybean producton n the U.S. and Chna were 5% and 3%, respectvely. In contrast, soybean producton n Brazl and Argentna ncreased dramatcally n recent years. From 1964 to 2005, the average annual growth rates of soybean producton n Brazl and Argentna were 14% and 27%, respectvely (USDA-FAS, 2006b). From these trends shown n fgure 4, t s reasonable to expect that wthn a few years Brazl may surpass the U.S. and become the largest soybean producer n the world, f Brazl contnues ts current growth rate. In contrast, the growth rate of Argentnean soybean 8

24 producton s even hgher than that of Brazl, and Argentna has also become a strong compettor for the U.S. n the world soybean market. Leadng Global Soybean Consumers Leadng global soybean consumng countres (or economc groups) nclude the U.S., Chna, Brazl, Argentna, and the EU-25. Fgure 5 compares soybean consumpton among these leadng soybean consumng countres (USDA-FAS, 2006b). The U.S. s the number one soybean consumer n the world. In 2005, U.S. soybean consumpton reached 51 mllon metrc tons, accountng for 61% of U.S. soybean output. Brazl, rankng second n soybean consumpton, consumed 31 mllon metrc tons n 2005, accountng for 57% of ts producton. Argentna s soybean consumpton reached 31 mllon metrc tons n 2005, accountng for 76% of ts producton. In contrast, Chna s soybean consumpton was 45 mllon metrc tons n 2005, whle Chna s soybean producton was only 18 mllon metrc tons, resultng n a 27 mllon metrc tons shortage. Mllon Metrc Tons US Chna Brazl Argentna EU-25 Fgure 5. Leadng Global Soybean Consumers Source: USDA-FAS, 2006b. 9

25 Soybeans compose a sgnfcant part of the human det, especally for Asan countres. Soybeans were orgnally cultvated n Chna and later spread across Asa. Tradtonal soybean products nclude fermented products such as Indonesan tempeh and Japanese mso, and nonfermented products such as tofu, sauce, curd, beverage, and powder. Soybeans can be processed nto soyol and soymeal. Soyol s wdely consumed around the world as food ol, especally n Chna, whle soymeal s used for anmal feed. Fgure 6 llustrates the soybean usage dstrbuton of the world and the leadng soybean consumng countres n Globally, only 6% of soybeans were used drectly for food, and 86% of soybeans were crushed nto meal for feed and ol for food or ndustral usage n 2004 (USDA-FAS, 2006b). Thus, Chna s domestc consumpton has a greater proporton of soybeans used as food, e.g., tofu, sauce, curd, beverage, and powder. Mllon Metrc Tons Crush Food Feed, Seed, Waste, and Others World U.S. Chna Brazl Argentna EU-25 Fgure 6. Comparson of Soybean Usage Dstrbuton Source: USDA-FAS, 2006b. 10

26 In the U.S., over 60% of soybeans were consumed domestcally. Of ths, 8% were waste or used as seed, and 92% were crushed nto soyol and soymeal n 2005, whereas 83% of soymeal was manufactured nto feed and 17% of soymeal was exported. For soyol, 92% of t was used for food and only 8% exported (USDA-FAS, 2006b). Brazl, Argentna, and the EU followed a smlar pattern to the Unted States. In contrast, Chna followed a dfferent pattern for soybean consumpton. In 2005, Chnese soybean consumpton totaled 38 mllon metrc tons, of whch 21%, or 8 mllon metrc tons, was used drectly for food, and 74%, or 28 mllon metrc tons, were crushed nto soyol for food and soymeal for feed (USDA-FAS, 2006b). Leadng Global Soybean Exporters The top three soybean exporters n the world nclude the U.S., Brazl, and Argentna. Fgure 7 shows that Brazl s soybean exports reached 25 mllon metrc tons n 2005, surpassng the U.S., and Brazl became the number one soybean exporter n the world. The U.S. exported 24 mllon metrc tons of soybeans, a 3 mllon metrc tons fall compared to Brazl s soybean exports ncreased dramatcally n the last decade from 4 mllon metrc tons n 1995 to 25 mllon metrc tons n 2005, an over 500% ncrease. Soybean exports from Argentna also ncreased n recent years, and reached 10 mllon metrc tons n Brazl and Argentna became strong compettors for the U.S. n the world soybean market. 11

27 Mllon Metrc Tons U.S. Brazl Argentna Others Fgure 7. Leadng Global Soybean Exporters Source: USDA-FAS, 2006b. 100% 80% 8% 16% 60% 39% 40% 20% 37% 0% U.S. Brazl Argentna Others Fgure 8. Export Shares of Top Soybean Exporters n the World Soybean Market Source: USDA-FAS, 2006b. 12

28 The export shares n the world soybean market for Brazl, the U.S., and Argentna were 39%, 37%, and 16%, respectvely (USDA-FAS, 2006b) n The sum of soybean exports from these three countres accounted for 92% of the global total. The trends for market shares and the structural changes n the world soybean market are shown n fgure 8. The U.S. soybean export share n the world market has been decreasng, especally n the last decade. In 1995, the U.S. soybean export share was 73%, but fell to 37% n 2005, a 36% market share loss n the world soybean market. In contrast, Brazlan market share n the world soybean market ncreased from 11% n 1995 to 39% n 2005, ganng 28% more wthn 10 years. Argentna also competes wth the U.S. n the world soybean market, and Argentnean market share ncreased from 6% n 1995 to 16% n Leadng Global Soybean Importers The leadng global soybean mporters nclude Chna, the EU-25, Japan, and Mexco as shown n fgure 4. Chna s soybean mports skyrocketed n the last decade from 0.8 mllon metrc tons n 1994 to 27 mllon metrc tons n 2005, an almost 27-fold ncrease, whle soybean mports nto the EU, Japan, and Mexco remaned qute stable. In 2005, Chna s soybean mports accounted for 41% of the world total (USDA-FAS, 2006b). Recall that Chna produced 18 mllon metrc tons and ts acreage annual growth rate was 3%. Thus soybean mports play an mportant role for Chnese consumers. The EU-25 mported 14 mllon metrc tons of soybeans n 2005, whch was 22% of global soybean mports. Soybean mports for Japan and Mexco were 4 mllon metrc tons each. Japanese and Mexcan soybean mport shares were each only about 6% of the world total. 13

29 Mllon Metrc Tons Chna EU-25 Japan Mexco Others Fgure 9. Leadng Global Soybean Importers Source: USDA-FAS, 2006b. Summary In summary, the leadng global soybean producers are the U.S., Brazl, Argentna, and Chna. The leadng global soybean consumers are the U.S., Brazl, Chna, Argentna, and the EU-25. The leadng global soybean exporters nclude the U.S., Brazl, and Argentna, and the leadng global soybean mporters are Chna, the EU-25, Japan, and Mexco, as shown n Fgure

30 Soybean Exporters Soybean Importers The U.S. Chna EU-25 Brazl Japan Argentna Mexco Fgure 10. The Global Soybean Market The growth of soybean producton n the U.S. and Chna was qute steady, wth an annual growth rate of 5% and 3%, respectvely, n the last four decades. In contrast, the annual growth rate of the soybean ndustres n Brazl and Argentna were 15% and 28%, respectvely, durng the same perod. However, soybean consumpton n the U.S., Brazl, and Argentna dd not ncrease as much as ther producton. Therefore, soybean exports became an mportant channel for the U.S., Brazl, and Argentna to deal wth ther soybean surplus. Soybean exports from Brazl and Argentna ncreased rapdly n recent years and became man compettors n the world soybean market. On the other hand, the man global soybean mporters, ncludng the EU, Japan, and Mexco dd not ncrease ther soybean mports much n the past. In contrast, for Chna, as the number soybean mporter, Chnese soybean mports skyrocketed n the last 15

31 decade and became the prmary soybean mport market n the world, attractng more attenton from top soybean exporters, ncludng the U.S., Brazl, and Argentna. 16

32 APTER THREE SOYBEAN POLICY REVIEW Soybean Polces n the Unted States U.S. Soybean Polces Globally, the U.S. s the number one soybean producer, consumer, and exporter. Natonally, U.S. soybean producton value reached $24 bllon n 2004, rankng second among all agrcultural bulk commodtes behnd corn (USDA-NASS, 2005). Compared wth two other man commodtes, corn and wheat, the planted area for soybeans has contnuously ncreased n the Unted States, whereas the planted areas for corn and wheat have been ether relatvely stable or declned (Fgure 11). From these trends shown n Fgure 11, t s reasonable to expect that soybeans wll surpass corn and become the number one (from a planted area perspectve) agrcultural bulk commodty n the Unted States, assumng that the U.S. does not make sgnfcant changes n current agrcultural polces. Behnd the leadng poston for the U.S. soybean ndustry both natonally and nternatonally, the support polces for soybeans from the U.S. government played a very mportant role. The U.S. soybean subsdy program, nsttuted n 1941, was a commodty loan program, whch supported soybean market prces. Under ths program, producers used ther soybeans as collateral for government loans. Dependng on the market prce level, farmers chose to ether default on these non-recourse loans, keepng ther loan and forfetng soybean ownershp to the U.S. Department of Agrculture (USDA), or farmers 17

33 could sell ther soybeans and repay ther loans plus nterest (Westcott and Prce, 1999, 2001) Corn Mllon Acres Wheat Soybeans Corn Wheat Soybeans Fgure 11. Comparson of Planted Acres for U.S. Soybeans, Corn, and Wheat Source: USDA-NASS, The marketng loan program began n the md-1980s and supported farmers ncomes. Under ths program, farmers could operate as descrbed above. Alternatvely, marketng loan provsons also allowed repayment of soybean loans at less than the orgnal loan rate when soybean market prces fell (USDA-FSA, 2005a). Instead, government ncentves encouraged farmers to retan ownershp and sell ther soybeans on the market at a prce lower than the loan rate, rather than default on ther loans and forfet ownershp to the USDA (Westcott and Prce, 1999, 2001). Under these government programs, U.S. government payments to soybean farmers ncreased rapdly, especally n the past decade. For example, net government expendtures totaled only $5 mllon n 1990 and ncreased to over $3 bllon n 2001 as 18

34 shown n Fgure 12 (USDA-FSA, 2005b). Because both domestc and nternatonal soybean prces recovered from very low to a hgher level, the net government expendtures for soybeans dropped sgnfcantly n 2003 and Mllon Dollars Fgure 12. U.S. Net Expendtures on the Soybean Industry Source: USDA-FSA, 2005b. Recent U.S. soybean polces nclude both drect government and counter-cyclcal payments (CCP), both of whch began wth the 2002 Farm Bll and extend through A descrpton of the calculaton of each follows. The formula for drect government payments for soybeans s (1) Drect payments = Base acreage x Program yeld x 85% x Drect payment rate In regards to varable defntons, the USDA, Farm Servce Agency (USDA-FSA) defnes base acreage from farmers one tme choce of the followng optons. Ths choce extends through 2007: 19

35 to use 2002 Producton Flexblty Contract (PFC) acreage to establsh CCP base acres; to use 2002 PFC acreage and add olseed base hstory for the crop years (three optons were avalable under ths scenaro that allowed flexblty between olseed base acres and other crop base acres); and to calculate all base acres usng the farm s planted and approved prevented planted hstory from (USDA-FSA, 2003). The program yeld for the above drect government payments s obtaned by multplyng the 1998 through 2001 average yeld for soybeans tmes the hstorc yeld rato, whch s the rato that results from dvdng the natonal average yeld for soybeans, ; by the natonal average yeld, The drect payment rate (DPR), set by the USDA, equals $0.44/bushel of soybeans n the 2002 Farm Bll. Drect payments relate only to planted acreage, regardless of the crop planted. In contrast, the formula for counter-cyclcal payments s more complcated than that for drect government payments. Counter-cyclcal payments are nfluenced not only by base acreage and program yeld, but also by soybean market prces (also referred to as marketng year average (MYA) prce n the followng formula). The formula for counter-cyclcal payments (CCP) can be expressed as follows: (2) Counter-cyclcal payment = Base acreage 85% Program yeld CCP rate (3) CCP rate = Max {0, (Target prce Effectve prce)} (4) Effectve prce = Max {MYA prce, Loan rate} + Drect payment rate (DPR) The base acreage n equaton (2) s defned above. For program yeld n equaton (2), farmers can use one of the followng two methods: 20

36 93.5 percent of the average yeld; or the drect payment yeld (PFC yeld) plus 70 percent of the dfference between the average and the drect payment yeld (USDA-FSA, 2003). The counter-cyclcal payment rate (CCP rate) n equaton (2) s related to both the target prce and the effectve prce, determned n equaton (3). The target prce s set by the USDA. The effectve prce s affected by the market year average (MYA) prce, the loan rate (see Fgure 13), and the drect payment rate n equaton (4) Dollars/Bushel Fgure 13. U.S. Loan Rate for Soybeans Source: USDA-FSA, 2005a. Counter-cyclcal payments are closely related to soybean market prces (MYA prces) through these three equatons (2, 3, and 4). If soybean market prces (MYA prces) are hgher than the natonal loan rate, then the effectve prce n equaton (4) s the MYA prce plus the drect payment rate ($0.44/bushel). If not, the effectve prce equals the loan rate plus the drect payment rate (DPR) n equaton (4). For the target prce n equaton (3), the 2002 Farm Bll sets t at $5.80/bushel through When the target 21

37 prce s hgher than the effectve prce, the dfference between the target prce ($5.80/bushel) and the effectve prce s the CCP rate n equatons (2) and (3). Otherwse the CCP rate s zero,.e., f the target prce s less than the effectve prce. Fnal countercyclcal payments equal 85% of the base acreage multpled by the program yeld and the CCP rate, determned n equaton (3). If the market prce (MYA prce) exceeds the loan rate n equaton (4), so that the sum of the MYA prce and the DPR,.e., the effectve prce, s greater than the target prce n equaton (3), the CCP rate equals zero and countercyclcal payments wll not occur. Wth these supportve polces, the U.S. soybean ndustry has developed steadly. Fgure 14 shows U.S. soybean producton, consumpton, exports, and stocks. U.S. soybeans stocks have been qute stable n the past, and U.S. soybean producton, consumpton, and exports have been ncreased steadly Mllon Metrc Tons Producton Consumpton Exports Stocks Fgure 14. U.S. Soybean Producton, Consumpton, Exports, and Stocks Source: USDA-FAS, PS&D, 2006b. 22

38 U.S. Botech Polces The U.S. leads the world n agrcultural botechnology research, adopton, commercalzaton, and exports of botech products. The man U.S. botech varetes nclude soybeans, cotton, and corn. Wth the expectaton of lower producton costs, hgher yelds, and reduced herbcde use, U.S. farmers adopted botech commodtes mmedately after they were avalable n 1996 (USDA-ERS, 2004). From 1996 to 2004, U.S. botech commodtes expanded dramatcally. For example, n 2005, 87% of soybeans, 79% of cotton, and 52% of corn planted n the Unted States were botech varetes as shown n Table 1 (USDA-ERS, 2005a). Table 1. Man U.S. Botech Varetes (Percent of Planted Acreage) Commodty Soybeans 54% 68% 75% 81% 85% 87% Cotton % Corn % Source: USDA-ERS, 2005a. In the U.S., the U.S. Department of Agrculture, the Envronmental Protecton Agency (EPA), and the Food and Drug Admnstraton (FDA) are jontly responsble for the regulaton of botech food commodtes. Each of these three agences has a dfferent focus regardng the regulaton of botech food commodtes: the USDA s prmarly responsble for determnng whether a new product s safe to grow or not; the EPA s n charge of the revews of the potental mpact on the envronment mposed by any botech commodtes; and the FDA s focused on protectng consumers and has fnal authorty to declare whether a product s safe to eat or not (UF-FEI, 2005). 23

39 Before the commercalzaton of any botech commodtes, feld testng s requred as a mandated part of the approval process. In 2001, there were about 13,000 multple ste feld tests n the Unted States. In 1993, the FDA announced that botech foods dd not requre any specal regulaton, as they were not nherently dangerous. Snce the FDA approved the frst botech commodty -- the Flavr savr tomato -- n 1994, the USDA has approved more than 50 botech commodtes for plantng, ncludng corn, tomatoes, soybeans, cotton, potatoes, rapeseed (canola), squash, beets, papaya, rce, flax, and chcory (UF-FEI, 2005). Currently the EU, Chna and Japan, requre that any food products contanng botech contents should be labeled (Marchant, Fang, and Song, 2002). However, the U.S. does not requre mandatory labelng for all botech food products. At the 1997 Codex 3.1 food labelng meetng, the U.S. delegate expressed U.S. stance on botech products as "Because foods derved from plants developed through dfferent methods of breedng do not dffer n any unform manner, under Unted States laws and polces, the falure to dentfy a plant breedng process s not tself consdered to be an omsson of a materal fact of the type that would cause the food to be msbranded. Thus, the Unted States beleves that, as a class, foods obtaned through botechnology do not warrant any mandatory labelng wth regard to the method by whch they were obtaned." "The Unted States beleves that, f consumers wsh to have access to nformaton on foods obtaned through botechnology, manufacturers ought to provde such nformaton on a voluntary bass" (OCA, 2005). 3.1 The Codex Almentarus Commsson s a Unted Natons body responsble for mplementaton of the Food and Agrculture Organzaton/World Health Organzaton Jont food Standards Program. Ths program was establshed to develop nternatonal food standards n the nterests of enhancng consumer protecton and ensurng far nternatonal trade n food products. Codex Almentarus s a Latn term meanng a code of law governng foods. 24

40 Brazlan Soybean Polces Brazlan Agrcultural Polces Brazl has the largest economy n South Amerca and the eghth-largest economy n the world, wth a GDP of $635 bllon n real terms (2000=100) n 2004 (USDA-ERS, 2006). Brazl s endowed wth vast agrcultural resources. Brazl s agrcultural area manly ncludes two regons the temperate south and tropcal center-west. In the south, wth temperate clmate, hgher ranfall, better sols, greater technology and nput use, adequate nfrastructure, and more experenced farmers, make Brazlan south ts man gran, olseed, and export commodtes producton area (Flaskerud, 2003). Brazlan agrculture s well dversfed, and the country s largely self-suffcent n food. Agrculture accounts for 8% of the country's GDP, and employs about onequarter of the labor force n more than 6 mllon agrcultural busnesses. Brazl s the world's largest producer of sugarcane and coffee, and a net exporter of cocoa, soybeans, orange juce, tobacco, forest products, and other tropcal fruts and nuts. Besdes crop producton, Brazlan lvestock producton s also very mportant n many sectons of the country. On a value bass, producton s 60% feld crops and 40% lvestock (Wkmeda Foundaton, 2005). Rapd urbanzaton and ncome growth caused great demand for both cookng ol and meat products. To meet domestc demand for meat products, the poultry, pork, and dary ndustres developed quckly (Wllams and Thompson, 1984). As a result, feed demand ncreased dramatcally as well. Along wth the ncreased demand for cookng ol, the demand for soybeans skyrocketed. Ths ncreased domestc demand along wth 25

41 hgher world soybean prces n the late 1990s, as well as government support polces, encouraged rapd expanson of soybean producton n Brazl. Pror to the 1990s, Brazl experenced an unstable macroeconomc envronment, ncludng hypernflaton, a heavy external debt burden, hgh nterest rates, and perods of severe currency overvaluaton. Brazl also mposed an mport tax on agrcultural nputs and export tax on agrcultural products. These polces dstorted domestc agrcultural producton (Peng, 2002; Schnepf, et al., 2001; Vctor, Marchant, and Isnka, 1995). In general, Brazl s agrculture suffered much due to ts unstable macroeconomc envronment and unfavorable agrcultural polces. However, Brazl s soybean ndustry was a specal case, whch has been expandng. The reasons can be summarzed as follows: 1. The Brazlan government consdered soybeans as a strategc product for the government from both the standpont of technologcal advancement and the volume of fnancal resources perspectve. From the 1960s to the 1980s, the soybean ndustry contrbuted greatly to Brazl s economy, at least from the followng perspectves: (1) savng foregn exchange, (2) ncreasng foregn exchange earnngs, (3) mprovng the natonal det, (4) stmulatng ndustral development, (5) holdng down food prce ncreases, and (6) terrtoral occupaton. (Warnken, 1999). 2. The Brazlan soybean ndustry benefted from ts mport-substtuton strategy. After World War II, the Brazlan Government mplemented an mport-substtuton strategy to stmulate the domestc economy and to reduce external debts. Under the mport-substtuton strategy, the agrcultural sector lost ther ncentve to export and put 26

42 more pressure on Brazl s lmted foregn exchange reserves. To compensate for the shortage of foregn exchange, Brazl s government gave the soybean ndustry specal treatment to expand exports and ncrease foregn exchange (Schnepf, et al., 2001). 3. The government support polcy played a key role n the Brazlan soybean boom. The Brazlan government s supportve programs ncluded the government acquston program and the Natonal Rural Credt System (Warnken, 1999). Under the government acquston program, the Brazlan government set a mnmum prce level for soybeans and, f the market prce was below the mnmum prce, the government would purchase soybeans from farmers at the mnmum prce. Ths program frst began n 1975, and dd not play an mportant role n the 1970s and early 1980s. In the late 1980s ths program dd protect Brazlan soybean farmers from low domestc soybean prces. Brazl s Natonal Rural Credt System (NRCS) ncluded three components: producton credt, nvestment credt, and marketng loan credt (Warnken, 1999). Among these three components, producton credt was the largest one. The government provded soybean farmers credt for ther producton of soybeans wth negatve nterest rates (the nflaton rate was hgher than the loan nterest rate) for most of the years from 1970 to In the late 1970s and the early 1980s, about 50% of Brazlan soybean producton used government loans and producton credts averaged about one-thrd of the total value of soybean output. In contrast, nvestment credt provded farmers and cooperatves funds for ther nvestments on nfrastructure mprovements, such as correcton of sol acdty, sol conservaton, rural electrfcaton, and purchase of agrcultural machnery, rrgaton 27

43 equpment, and transportaton vehcles (Warnken, 1999). Investment credt was also subsdzed by a negatve nterest rate smlar to producton credt. The marketng loan program prmarly helped soybean cooperatves and processors for soybean storage and transportaton, as well as processng. The government provded loans to cooperatves or processors for up to sx months wth a negatve nterest rate. Snce the md-1990s, the Brazlan government changed ts agrcultural polces and tred to elmnate ts mnmum prce nterventon and government buffer stock gradually (USDA-ERS, 2002). At the same tme, the Brazlan government used Federal taxes n addton to an array of state taxes on agrcultural exports. Currently, although Brazlan subsdy programs stll exst, they do not play as mportant a role as they dd before. Wth all of these support programs, Brazl has been a net exporter of soybeans (see Fgure 15), and a strong compettor for the U.S. n the nternatonal soybean market. In 2005, soybean producton n Brazl totaled 57 mllon metrc tons, accountng for 25% of the world total (USDA-FAS, 2006b). However, Brazlan domestc demand for soybeans dd not ncrease as fast as producton. Therefore, the Brazlan government used soybean exports to reduce ts domestc soybean surplus. In 2005, Brazlan soybean exports reached 22 mllon metrc tons, an ncrease of 18 mllon metrc tons, compared wth 4 mllon metrc tons of soybean exports n 1994, and became the second largest soybean exporter n the world soybean market, competng wth the U.S. and Argentna. One nterestng observaton s that Brazlan soybean stock changes. Pror to 1999, Brazlan soybeans stocks were very low. However, after 1999, Brazlan soybean stocks ncreased dramatcally from less than1 mllon metrc tons n 1999 to 17 mllon metrc 28

44 tons n Ths huge soybean stock ncrease mples that Brazlan soybean storage capacty has been mproved greatly. In addton, ths mproved nfrastructure may ncrease Brazl s compettveness n the nternatonal market. From another perspectve, Brazl also needs to boost ther soybean exports to avod contnuous ncrease of ther soybean stockple Mllon Metrc Tons Producton Consumpton Exports Stocks Fgure 15. Brazlan Soybean Producton, Consumpton, Exports, and Stocks Source: USDA-FAS, PS&D, 2006b. Brazlan Botech Polces For botech polces n Brazl, the Brazlan Government nvested heavly n botech research and development n the early 2000s wth estmated $15 mllon per year snce 2001 (James, 2004). However, adopton and commercalzaton of botech commodtes were not allowed before Although the Government banned botech agrcultural producton n Brazl, llegal growng of botech commodtes, manly botech soybeans, was qute common n Brazl before Fnally, the Brazlan Government 29

45 offcally approved plantng of botech soybeans n The approval was temporary, pendng the passage of a botech bll that wll provde a permanent framework for evaluatng and approvng botech commodtes n Brazl (James, 2005). In 2005, Brazl experenced the largest ncrease n botech soybean adopton relatve to total producton of soybeans, wth 9.4 mllon hectares of botech varetes compared wth 5 mllon n Argentnean Soybean Polces Argentnean Agrcultural Polces Argentna s the second largest country n South Amerca and the eghth largest n the world. Argentna has a wealth of natural resources and a good clmate, whch gves Argentna a natural advantage n agrcultural producton. From the early 1950s, Argentna was already a major corn and wheat producer but dd not produce much soybeans. Smlar to Brazl, Argentnean agrculture suffered due to hgh nflaton, an often overvalued exchange rate, and a heavy external debt burden. Although the Argentnean Government undertook a seres of programs to stablze ts macroeconomc condtons durng the 1960s, 1970s, and 1980s, ther macroeconomc envronment had not mproved (Peng, 2002; Schnepf, et al. 2001). In addton, the Argentnean Government adopted an mport substtuton strategy, whch further dampened ther agrcultural ndustry. Under ths mport substtuton strategy, the Argentnean Government tred to control and reduce mports by settng hgh tarffs and quanttatve restrctons (quotas), export taxes, and manpulated exchange rates. Pror to 1977, Argentnean mport tarffs on fertlzers and agrcultural chemcals were 60 and 65 30

46 percent. Export taxes on grans and olseeds were ntally set at 18 percent n 1982, and vared each year. As a result, Argentnean farmers had to use ther neffcent, overprced domestc nputs, and sold ther agrcultural products domestcally at lower prces. In 1991, Argentna enacted economc reforms movng toward a free market economy. Schnepf, et al. (2001) summarzed the man reform polces related to agrculture n Argentna as follows: The elmnaton of all export taxes on major gran and processed olseed products n 1991, except for the 3.5-percent tax on unprocessed olseed exports. The elmnaton of all quanttatve restrctons on mported agrcultural nputs. The reducton of tarffs on mported agrcultural nputs to a range not to exceed 15 percent of CIF (cost, nsurance, and freght) value, although an addtonal 10-percent tax was leved on most mported agrcultural nputs. The exempton from tarffs and taxes of agrcultural nputs classfed as captal goods.e., those whose economc lfe extends beyond one producton cycle such as embryos, certfed seed, and trucks. The elmnaton of several government commodty agences that held export monopoles for ther respectve commodtes (e.g., the Natonal Gran Board, the Natonal Meat Board, and smlar agences for sugar and tobacco). The ntaton of prvatzaton n the marketng and transportaton nfrastructure, ncludng state-owned gran elevators, port facltes, and ralroads. These favorable polces along wth hgh nternatonal prces for soybeans greatly spurred Argentnean soybean producton. In 2005, soybean output n Argentna reached 41 mllon metrc tons, accountng for 18% of world soybean producton, rankng thrd globally behnd the U.S. at 38% and Brazl at 25% (USDA-FAS, 2006b). However, soybean consumpton n Argentna dd not grow as quckly as soybean producton (Fgure 31

47 16). The Argentnean populaton s small and stable and the lvestock ndustry s also relatvely small. In addton, the cattle ndustry n Argentna s predomnantly grass-fed; thus soymeal demand s lmted. As a result, the nternatonal market was Argentna s prmary choce to deal wth ts soybean surplus. Argentnean soybean exports ncreased dramatcally from 2.6 mllon metrc tons n 1994 to 10 mllon metrc tons n 2005, whch accounted for 16% of world soybean exports (USDA-FAS, 2006b) Mllon Metrc Tons Producton Consumpton Exports Stocks Fgure 16. Argentnean Soybean Producton, Consumpton, Exports, and Stocks Source: USDA-FAS, 2006b. Argentnean Botech Polces For Argentna s botech polces, Argentna conducted feld trals for botech soybeans as early as 1986, and began to grow botech soybeans commercally n Followng ts ntroducton, botech soybeans expanded dramatcally n Argentna. In 2005, almost the entre natonal planted area for soybeans was botech varetes, leadng the world n botech soybean adopton and commercalzaton (James, 2005). 32

48 Wth abundant arable land and quck adopton of new technology, Argentna s a strong compettor n the nternatonal soybean market. However, one dsadvantage for the Argentnean soybean ndustry s that s Argentna s pervasve polcy nterventon that ultmately promoted other sectors of the economy at the expense of agrculture. For example, although ts export tax was elmnated n 1991, n March 2002 a 13.5 percent export tax was mposed on soybeans and a 10 percent tax on most other prmary agrcultural products (Torgerson, 2002). Then n Aprl 2002, export taxes were rased to 20 percent for many agrcultural products, ncludng soybeans, wheat, feed grans, and vegetable ols and soymeal. Soybeans were stll assessed a 3.5 percent surcharge, makng the export tax 23.5 percent for soybeans Ths recently re-mposed export tax dampened the soybean ndustry n Argentna and weakened ther advantage n the nternatonal soybean market. Chnese Botech Polces and Soybean Trade Chna s Stuaton and Outlook Wth a populaton of 1.3 bllon and an annual GDP growth rate of more than 8% n the past decade, Chna s not only a large producer of agrcultural commodtes, but also a large consumer of agrcultural commodtes ncludng soybeans. In 2004, Chna produced 31% of world rce, 27% of rapeseed, 19% of corn, 27% of cotton, 16% of wheat, and 9% of soybeans (FAO, 2005). Chna s also a large player n nternatonal gran and olseed markets, exportng almost four mllon metrc tons of corn and mportng 27 mllon metrc tons of soybeans n 2005 (USDA-FAS, 2006b). 33

49 In the past, Chna was also a major soybean exporter n the world market. However, recently, demand for soybeans n Chna ncreased dramatcally resultng n Chna becomng a net mporter n the late 1990s from a net exporter n the 1980s. Fgures 17 and 18 show the change of Chna s status n the soybean world market (USDA-FAS, 2006b). The man soybean supplers for Chna nclude the U.S., Brazl, and Argentna. Snce 85% of U.S. soybeans, 22% of Brazlan soybeans, and 98% of Argentnean soybeans were botech varetes n 2004, any changes n Chna s botech polces may have a sgnfcant mpact on Chna s soybean trade. Mllon Metrc Tons Producton Consumpton Imports Exports Fgure 17. Chnese Soybean Producton, Consumpton, Imports, and Exports Source: USDA-FAS, 2006b. 34

50 Mllon Metrc Tons Fgure 18. Chnese Net Imports of Soybeans Source: USDA-FAS, 2006b. Chnese Botech Polces and Trade Impacts Snce 1986, Chna has nvested heavly n botech research, rankng second only to the Unted States (Huang and Wang, 2002). By the year 2001, more than 130 speces were obtaned, ncludng nsect-resstant, bacteral-, fungus- and vrus-resstant, salt-tolerant, drought-resstant, nutrton enrchment, qualty mprovement, producton of edble oral vaccnes and recombnant pharmaceutcals (Marchant and Song, 2005). However, only Bt cotton, delayed rpenng tomatoes, cucumber mosac vrus (CMV)- resstant sweet peppers, and color-altered petunas were approved for producton wthn Chna. By far, Bt cotton s the domnant botech commodty n Chna, and no other food commodtes have been approved for producton (Marchant, Fang, and Song, 2002). 35

51 Currently, the Chnese government s strugglng wth the adopton and commercalzaton of botech rce. Chna s agrcultural researchers state that botechnologes for rce are mature and ready for adopton and commercalzaton. An offcal from the Chnese MOA sad that they have already accepted the applcaton for the safety evaluaton (for the safety certfcate) of botech rce varetes (Cheng and Peng, 2002). Ths offcal also mentoned that acceptng the safety evaluaton does not mean that the government wll approve the adopton and commercalzaton of botech rce varetes. Before commercalzaton of botech rce, a seres of feld experments, producton experments and other related experments are requred. The Chnese government wll be very cautous n the adopton and commercalzaton of botech rce, snce currently no other countres have approved botech rce for large-scale commercalzaton (Song and Marchant, 2005). Feld tests, envronmental releases and commercalzaton of botech plants are regulated n Chna (Fgure 19). In November, 1993, the State Scence and Technology Commsson of Chna (SSTC) ssued Bosafety Admnstraton Regulatons on Genetc Engneerng, whch was the frst law on bosafety n Chna (Marchant, Fang, and Song, 2002). Three years later, Bosafety Admnstraton Implementaton Regulatons on Agrcultural Genetc Engneerng was ssued by the Chnese Mnstry of Agrculture (MOA), and took effect on the same date, July 10, 1996 (Chnese MOA, 1996). 36

52 December 1993 July 1996 May 2001 July 2001 March 2002 Aprl 2002 October 2002 July 2003 Aprl 2004 May 2004 Bosafety Admnstraton Regulatons on Genetc Engneerng was ssued by the State Scence and Technology Commsson and took effect on the same date, December 24, Bosafety Admnstraton Implementaton Regulatons on Agrcultural Genetc Engneerng was ssued by the Mnstry of Agrculture of Chna, and took effect on the same date, July 10, Bosafety Admnstraton Regulatons on Agrcultural Transgenc Products were passed by the State Councl of Chna on May 9, 2001, and ssued and took effect on May 23, (1) Bosafety Evaluaton and Admnstraton Regulatons on Agrcultural Transgenc Products, (2) Labelng Admnstraton Regulatons on Agrcultural Transgenc Products, and (3) Import Safety Admnstraton Regulatons on Agrcultural Transgenc Products were passed by the Chnese Mnstry of Agrculture on July 11, 2001, wth an effectve date for mplementaton on March 20, Temporary Admnstraton Procedure of Import of Agrcultural botech Products was ssued on March 10, 2002 before the above effectve date March 20, 2002, and was scheduled to termnate on December 20, On Aprl 8, 2002, the Chnese Mnstry of Health ssued the Santary Admnstraton Rules for Transgenc Food whch took effect on July 1, On October 11, 2002, the Chnese Mnstry of Agrculture announced that the above temporary mport regulatons would be extended to September 20, On July 17, 2003, the Chnese Mnstry of Agrculture announced that the above temporary mport regulatons would be further extended to Aprl 20, The temporary mport regulatons expred and the above three regulatons took effect on Aprl 20, The Admnstratve Measures of Inspecton and Quarantne on Entry-Ext Transgenc Products was ssued on May 24, 2004 by Chna's State General Admnstraton for Qualty Supervson, Inspecton and Quarantne (AQSIQ) and took effect on the same day. Fgure 19. Hstory of Chna s Botech Regulatons 37

53 Pror to Chna s accesson nto the World Trade Organzaton on December 11, 2001, the Chnese government passed ts Bosafety Admnstraton Regulatons on Agrcultural Botech Products, whch were ssued and took effect on May 23, 2001 (Chnese MOA, 2001a). These regulatons provded general gudelnes for the development, dstrbuton, and use of agrcultural botech products and requred a safety certfcate and labelng for any agrcultural botech products from ether domestc sources or mports. The Chnese MOA ssued three separate mplementng regulatons for the above gudelnes on January 5, 2002: (1) Bosafety Evaluaton and Admnstraton Regulatons on Agrcultural Botech Products, (2) Import Safety Admnstraton Regulatons on Agrcultural Botech Products, and (3) Labelng Admnstraton Regulatons on Agrcultural Botech Products (Chnese MOA, 2001b). These new regulatons placed restrctons on Chnese mports of botech products, ncludng those mported from the Unted States. The effectve date for mplementaton was orgnally set for March 20, Specfc rules on mports of botech products from the above regulatons ncluded the followng: (1) botech products mported nto Chna requred test results or data obtaned from n-country feld experments wthn the exportng country (or a thrd country) to prove that the products are safe for human consumpton and do not mpose bosafety rsks to other plants, anmals, or the envronment, (2) each shpment of botech products mported nto Chna needs a sngle or separate safety certfcate accompanyng each shpment, 38

54 (3) the Chnese Mnstry of Agrculture s approval process can take up to 270 days to grant safety certfcates requred for mported botech products, (4) there s a "zero" threshold level (based on qualtatve test results) for botech content n foods, (5) decson-makng should be based on demonstrated rsks (boharzards) from scentfc data, whereby the expert panel should play an mportant role n the decsonmakng process. Rules on labelng botech products ncluded the followng: (1) all products contanng botech content should be labeled correctly, otherwse, the products are not allowed to enter unless they are re-labeled, (2) labelng rules are appled to the followng mported botech products: soybean seeds, soybeans, soybean flour, soymeal, soyol, corn seeds, corn, corn ol, corn meal, rapeseed seeds, rapeseeds, rapeseed ol, rapeseed meal, cotton seeds, tomato seeds, fresh tomatoes, and tomato ketchup (tomato jam). Before the effectve date to mplement these three regulatons (March 20, 2002), the Chnese government delayed ther mplementaton (Chnese MOA, 2003). Instead, the Chnese MOA ssued a temporary measure, Temporary Admnstraton Procedure of Import of Agrcultural Botech Products, whch allowed exporters to shp botech products, ncludng U.S. botech soybeans, nto Chna usng temporary mport certfcates through December 20, Each temporary mport certfcate granted by the Chnese MOA was good for 10 shpments (Chnese MOA, 2002). After three extensons of ths temporary measure, the above three regulatons eventually took effect on Aprl 20, 2004 (USDA-FAS, 2004). 39

55 Immedately after the effectve date of mplementaton for these three regulatons, Chna's State General Admnstraton for Qualty Supervson, Inspecton and Quarantne (AQSIQ) announced a new regulaton related to the admnstraton of botech products, Admnstratve Measures of Inspecton and Quarantne on Entry-Ext of Botech Products, on May 24, 2004 (Chnese AQSIQ, 2004; USDA-FAS, 2004). These measures not only apply to the nspecton and quarantne of botech products va trade, but also apply to processng, research, and producton. By these new measures, Chnese mporters must declare whether the mported products are botech or not when they apply for nspecton and quarantne. If the products are botech, the mporters shall provde relevant documents ncludng a safety certfcate and revew and approval documents needed for labelng. For botech products, labelng s mandatory by the above mplementng regulatons. In addton, these measures also authorze the AQSIQ to conduct random botech tests even f products are declared as non-botech. Chna s botech regulatons and polces dd rase concern by U.S. agrcultural exporters and polcymakers as well as Chnese agrcultural mporters. Requrng safety certfcates ncurred addtonal costs and shpment delays at the ntaton of these new regulatons n the late sprng and summer of In addton, these regulatons have the potental to be used by the Chnese government as a non-tarff barrer to control soybean mports. Upon examnng monthly data, Song and Marchant (2005) found that Chna s botech polcy dd not mpose sgnfcant mpacts on U.S. soybean exports to Chna n the long-run. Ths concluson wll be emprcally tested n ths research. 40

56 APTER FOUR LITERATURE REVIEW The Lerner Index Lerner (1934) developed an ndex (the Lerner Index) to measure market power of a sngle frm. The Lerner ndex s defned as (5) LI = P MC P where the varable P s the market prce and MC s the margnal cost. The Lerner Index s able to measure the degree of market power of a frm n an mperfect market, but t was dffcult to use emprcally because margnal cost data are typcally unavalable. However, the Lerner Index does provde a provocatve dea to measure market power. Based on the Lerner Index, subsequent lterature found other ways to approxmate the Lerner Index to measure market power n an mperfectly compettve market. These measures nclude Prcng to Market Model and Resdual Demand Elastcty Model. Prcng to Market Model Krugman (1986) frst developed the concept of prcng to market (PTM). PTM was used to address the relatonshp between the changes n exchange rates and mport prces. Krugman defned PTM as mport prces fall too lttle when a currency apprecates. Upon examnng the trade data of U.S. mported manufactured products from Germany, Krugman summarzed as prcng to market when the exchange rate changes s a real phenomenon and PTM s not unversal. Krugman also suggested both statc and dynamc models to explan PTM. Hs statc and dynamc models ncluded 41

57 supply and demand, monopolstc prce dscrmnaton, and olgopolstc models. Krugman concluded n hs paper, explanng prcng to market s not as smple as one mght hope. It seems clear that a perfectly compettve model wll not do the trck and the best hope of understandng prcng to market therefore seems to come from dynamc models of mperfect competton. Although Krugman dd not attempt to fnd a better explanaton for PTM, hs provocatve research dd brng attenton to subsequent researchers. At the end of the 1980s, the U.S. dollar deprecated sharply, and the relatonshp between U.S. exports and fluctuatons of the exchange rates attracted researchers nterests. Knetter (1989) developed a specfc functonal model to study PTM assocated wth exchange rate fluctuaton. Based on solvng an exporters proft maxmzng problem, Knetter (1989) establshed hs model (6) Ln p t = θt + λ + β Ln st + ut where the varable p s the export prce to destnaton market at perod t, and s s the t exchange rate (destnaton market s currency per unt of exporter s currency) of the destnaton market at perod t. The parameter β measures the elastcty of the export prce changes relatve to the exchange rate changes. The parameter θ t s the tme effect, t λ the country effect, and u t the regresson dsturbance. Knetter s model was able to dstngush between three dfferent market condtons: a compettve market, an ntegrated market, and a noncompettve market, dependng on the estmated coeffcents values for λ and β. 42

58 If the market s compettve, by the Lerner Index we know that prce equals margnal cost and the Lerner Index s zero. In ths case, the tme effect, θ t, measures the common prce and there s no varaton n the data correlated to the country effect, λ, or the exchange rate, st. In ths model, the estmated coeffcents for λ and β should be zero. In contrast, f one or both of the estmated coeffcents of λ and β are not zero, then the market s not compettve. Knetter appled ths model to U.S. exports of onons, bourbon, orange juce, breakfast cereal, refrgerators, and swtches, as well as German exports of fan belts, ttanum doxde pgment, small cars, large cars, beer, whte wne, sparklng wne, and potassum chlorde. Knetter s estmaton results ndcated that U.S. export prces are rather nsenstve to exchange rate fluctuatons, and German export prces appear to be much more senstve to exchange rate fluctuatons. Usng a smlar model, Knetter (1993) subsequently studed the PTM behavors from both source and destnaton countres n the world market. Knetter used ndustry level data from the U.S., the Unted Kngdom, Germany, and Japan to compare the PTM behavors from these countres. Knetter found that the PTM behavors were very smlar across source countres, ncludng Germany, Japan, and the Unted Kngdom. For U.S. exports, the PTM behavors were very smlar across destnaton markets. The PTM model bascally deals wth the relatonshp between export prces and exchange rates. However, the PTM model does not work n Chna s case, snce the Chnese exchange rate does not fluctuate but rather s pegged to the U.S. dollar. The exchange rates between Chnese currency, RMB (Yuan), and U.S. dollars were qute 43

59 stable for a long tme. Fgure 20 shows that the exchange rate between Chnese currency, RMB (Yuan), and the U.S. dollar was almost constant at 8.28 (RMB/USD) from 1998 to 2005 (USDA-ERS, 2006). Recently, under nternatonal pressure, the Chnese Government promsed to reform Chna s exchange rate polcy, and s now practcng lmted floatng exchange rates. The current exchange rate s 8.01(RMB/USD) as of May 2006, showng slght movement RMB/USD Jan- 96 Jan- 97 Jan- 98 Jan- 99 Jan- 00 Jan- 01 Jan- 02 Jan- 03 Jan- 04 Jan- 05 Jan- 06 Fgure 20. Exchange Rate between Chnese Yuan (RMB) and U.S. Dollars Data Source: USDA-ERS, Resdual Demand Elastcty Model Baker and Bresnahan (1988) frst developed the resdual demand model to measure market power of a sngle frm n an mperfect market. Baker and Bresnahan argued that under perfect competton wth homogeneous products, f a frm reduced ts producton, then other frms would offset the shortage due to one frm s contracton. Therefore the resdual demand faced by any sngle frm was nfntely elastc. However, 44

60 wth mperfect competton or dfferentated products, the resdual demand curve faced by a sngle frm was negatvely sloped. They defned the nverse demand functon for the frm of nterest (frm 1) as 1 1 (7) P = P (Q,Q, Y; ) 1 1 α where the varables P 1 and Q 1 are prce and quantty for frm 1 s product, Q s a vector of quanttes for substtute products produced by the other frms, Y s a vector of exogenous demand shfters, and α 1 are parameters. If assumng that all products are homogenous, then equaton (7) can be wrtten as 1 1 (7 ) P1 = P (Q1 + Q,Y; α ) demand form In regards to vector Q n equaton (7), t s expressed n a smlar nverse resdual (8) P = P (Q,Q,Y; α ) for all 1. 1 The thrd component n Baker and Bresnahan s model ncludes the supply behavor of all frms for 1. These supply relatons are wrtten through the margnal cost (MC) equalng the perceved margnal revenue (PMR) (9) MC Q, W, W ; β ) = PMR ( Q, Q, Y; α, θ ) for all 1 ( 1 where the expresson PMR ( ) s P ) + Q [( P / Q )( Q / Q )]. The vector W ( j j j s the ndustry-wde factor prces and the vector W s the frm-specfc factor prces. 45

61 Parameters β are assocated wth the margnal cost functon, and the parameter ndexes the olgopoly soluton component ( Q / ) for all frms. j Q θ Sngle frm s resdual demand functon was derved by solvng equaton (8) and (9) smultaneously for the vectors Q and P. In mplct form, the soluton could be wrtten as (10) (, Q = E Q1 Y, W, W ; α, β, θ ) where the functon E ( ) means that ths was the equlbrum quantty n all markets for 1. Fnally, substtutng equaton (10) nto equaton (7) and removng redundances, equaton (7) becomes 1 (11) P = R( Q, Y, W, W ; α, β, θ ) 1 1 where the functon R( ) s the nverse resdual demand functon for frm 1. Baker and Bresnahan took three U.S. brewng frms Anheuser-Busch, Coors, and Pabst as ther samples to estmate and analyze the resdual demand curves faced by these three companes. They found that for the perod , Anheuser-Busch had some market power, Coors had substantal market power, and Pabst had no market power. Baker and Bresnahan s work provded a new approach to measure market power of a sngle frm wth dfferentated products wthn a natonal market. Goldberg and Knetter (1999) adopted the resdual demand model to measure the degree of competton n segmented export markets. They started from the general case, 46

62 whch assumed homogenous products and a group of exporters facng a partcular foregn destnaton market, and defned the resdual demand functon as ex ex 1 n (12) P D (Q,P,...,P, Z) ex = (13) P k k k j ex = D (Q,P,P, Z) where j = 1,..., n and j k where the varable ex ex P s the prce of the exported good, and Q s the total export quantty. The varables 1 P, n P are the prces of n competng products produced n other countres, and Z s a vector of demand shfters n the destnaton markets. By solvng the exporters proft maxmzng problem, Goldberg and Knetter wrote the specfc functonal form of the frst order condton as ex ex ' ' N (14) LnPmt = λ m + ηmlnq mt + α mlnz mt + β mlnwmt + ε mt where the subscrpt m ndexes a specfc market, the vector Z denotes demand shfters for destnaton market m, and the vector W conssts of cost shfters for the N compettors faced by the export group n a partcular destnaton market. Fnally, the random dsturbance ε s ndependently and dentcally dstrbuted (..d.). Goldberg and Knetter used annual data for U.S. Kraft lnerboard paper ( ) and German beer ( ) to estmate ths model. In the case of German beer, ther emprcal results ndcated that the elastcty of the resdual demand curve German exporters face n each destnaton s closely related to the presence of the Netherlands as a compettor, and for U.S. lnerboard exports, strong evdence of mperfect competton 47

63 n the case of Australa, whch s a very small market where U.S. frms face almost no competton from other producers. Carter, et al. (1999) tested the world wheat market usng the resdual demand elastcty (RDE) model. Ther applcaton of RDE model to the world wheat market provded a new approach to measure market power for wheat, a key nternatonal bulk agrcultural commodty market. Carter, et al. assumed that each country was a frm, and that parameters could be nterpreted as share-weghted ndustry averages for all frms wthn one country. Based on Goldberg and Knetter s RDE model, Carter, et al. drectly defned the reduced form of the nverse resdual demand functon for U.S. wheat as u u u c c a a (15) LnPt = α + η LnQt + β LnWt + β LnWt + γlnz t + ε t where the varable u P t s the prce of U.S. wheat exported to Japan n yen, and u Q t represents the quantty of U.S. wheat exported to Japan. The vector c W t s a set of cost shfters for a U.S. export compettor, Canada, and the vector a W t s a set of cost shfters for another U.S. export compettor, Australa. The vector Z t ncludes demand shfters n Japan. Parameters α, η, β, and γ are to be estmated. The error term ε s assumed to be dstrbuted ndependently and dentcally. The subscrpt t stands for tme perod. Through ths double-log form Carter, et al. estmated the prce flexblty for U.S. wheat exports to Japan drectly. Carter, et al. used quarterly data (1970 to 1991) to estmate ther model (15). Ther results ndcated that the Unted States s possbly a prce leader n the Japanese market for mported wheat whereas Australa and Canada form a compettve frnge. 48

64 Glauben and Loy (2003) compared the PTM model and the RDE model when examnng market power for German food and beverage export ndustres over nternatonal markets. They found controversal results from these two models: n some cases the PTM model ndcated market power, whle the RDE model dd not. They explaned ths conflct by fxed contracts, whch were often used n the food and beverage export market. Poosrpnyo and Reed (2005) appled the RDE model to the Japanese chcken meat market and estmated prce flexbltes of Japanese nverse resdual demand for whole brds, legs wth bone, and other cuts from Brazl, Chna, Thaland, and the Unted States. Ther results ndcated that only Brazl (n whole brds and leg wth bone) and the U.S. (n other cuts) have sgnfcant market power over Japanese chcken meat mporters as shown n Table 2 (Poosrpnyo and Reed, 2005). Table 2. Summary Results of Resdual (Inverse) Demand Elastctes Products Prce: Resdual (Inverse) Demand Elastcty (RDE) Brazl Chna Thaland Unted States Whole Brds ** ** Legs wth Bone ** Other Cuts ** ** sgnfcant at 1% level * sgnfcant at 5% level Poosrpnyo (2004) summarzed the advantage and dsadvantages of the RDE model. The advantages of the RDE model nclude 1) the RDE model can measure 49

65 market power wth modest data requrements, whch are generally lackng n domestc and nternatonal markets; 2) the RDE model can be defned n double-log form and the elastcty can be estmated drectly; and 3) the RDE model can ncorporate exchange rate varable n the model as an ndcator of margnal cost change. The dsadvantages of the RDE model nclude 1) the RDE model entals a loss of prce elastcty of demand; and 2) the estmated coeffcents are dffcult to nterpret. Wth these dsadvantages of the RDE model, however, n cases where the Lerner Index s very dffcult or nfeasble to compute, the RDE model appears to be the next best alternatve to evaluate market power. Revew of World Soybean Market Studes The FAPRI/CARD Internatonal Olseed Model The Food and Agrcultural Polcy Research Insttute (FAPRI) n the Center for Agrcultural and Rural Development (CARD) developed an Internatonal Olseed Model, a non-spatal, partal-equlbrum econometrc global model. The FAPRI s nternatonal olseed model ncludes major olseed producng, exportng, and mportng countres or regons. Ther model also assumes each seed, meal, and ol as a homogeneous commodty. A key factor n the FAPRI s model s that when world prces are lnked to domestc prces, estmated or consensus prce transmsson elastctes are used, assumng that agents n each country are prce-takers n the world market (FAPRI/CARD, 2005). FAPRI/CARD s prce transformaton model was wrtten as D W (16) P = α + βp * r * ( 1+ d ) Where D P s the domestc prce, and W P s the world prce of the commodty ncludng 50

66 nternatonal transportaton costs. Varable r s the exchange rate, and d captures polcy nterventons between the world and domestc markets and s expressed n ad valorem form. Parameter α and β are to be estmated. The FAPRI/CARD nternatonal olseed trade model ncorporated four olseeds ncludng soybeans, rapeseed, sunflower seed, and peanuts. Ther model also ncluded palm ol, palm kernel meal, and palm kernel ol. The countres/regons covered n ther model can be found n Table 3 (FAPRI/CARD, 2005). Table 3. Commodty and Country Coverage of the FAPRI/CARD Internatonal Olseed Model Soybeans Soybean Meal Soybean Ol Argentna Argentna Argentna Brazl Brazl Brazl Canada Canada Canada Chna Chna Chna EU New Member States EU New Member States EU New Member States European Unon - 15 European Unon - 15 European Unon - 15 Inda Inda Inda Japan Japan Japan Other Former Sovet Unon Other Former Sovet Unon Other Former Sovet Unon South Korea South Korea South Korea Tawan Tawan Tawan Unted States Unted States Unted States Rest of World Rest of World Rest of World Rapeseed Rapeseed Meal Rapeseed Ol Australa Canada Australa Canada Chna Canada Chna EU New Member States Chna EU New Member States European Unon - 15 EU New Member States European Unon - 15 Inda European Unon - 15 Inda Japan Inda 51

67 Japan Other Former Sovet Unon Japan Other Former Sovet Unon Unted States Other Former Sovet Unon Unted States Rest of World Unted States Rest of World Rest of World Sunflower Seed Sunflower Meal Sunflower Ol Argentna Argentna Argentna Chna Chna Chna EU New Member States EU New Member States EU New Member States European Unon - 15 European Unon - 15 European Unon - 15 Other Former Sovet Unon Other Former Sovet Unon Other Former Sovet Unon Unted States Unted States Unted States Rest of World Rest of World Rest of World Palm Ol Palm Kernel Meal Palm Kernel Ol Chna European Unon - 15 Chna European Unon - 15 Indonesa European Unon - 15 Inda Malaysa Indonesa Indonesa Rest of World Malaysa Malaysa Rest of World Rest of World Peanuts Peanut Meal Peanut Ol Argentna Argentna Argentna Canada Chna Chna Chna European Unon - 15 European Unon - 15 European Unon - 15 Inda Inda Inda Unted States Unted States Mexco Rest of World Rest of World Unted States Rest of World From a supply perspectve, the FAPRI/CARD s nternatonal olseeds model ncorporates equatons for area harvested, yeld and producton. From the demand sde, t 52

68 ncludes crush, seed, food, stocks, and other consumpton. The crush demand s drven by the ol demand and/or by meal demand. Gven the jont product of ol and meal and the postve economc value attached to meal, the derved demand from crushng reflects both ol and meal. The derved demand for crush olseeds s drven by the crush margn. (FAPRI/CARD, 2005). Another assumpton made n the FAPRI/CARD model s that trade n seeds, ol, and meal s an excess demand/supply and provdes market closure. For each commodty, world prce adjusts to clear the world market and ensure that the sum of excess demands over all countres s zero. The FARPRI/CARD model s also lnked to other FAPRI model components n ther lvestock and commodtes models. Economcs Research Servce/Penn State Trade Model The USDA-Economc Research Servce (ERS)/Penn State Trade Model s a multple-commodty, multple-regon model of agrcultural polcy and trade. Ther model does not dstngush a regon's mports by ther source or a regon's exports by ther destnaton. The model s a gross trade model that accounts for exports and mports of each commodty n every regon. The ERS/Penn State Trade Model ncorporates 12 countres/regons and 35 commodtes as shown n Table 4 (Abler, 2005). In addton, the model also ncludes both general polcy and country specfc components. General polcy components nclude specfc and ad valorem mport and export taxes/subsdes, tarff-rate quotas (TRQs), and producer and consumer subsdes. Country specfc components nclude the U.S. loan rate; producton quotas for mlk for Canada; producer target prces, producer compensaton schemes for Japan and South Korea; nterventon 53

69 prces, varable mport leves, compensatory payments, acreage set-asdes, base area bounds, and producton quotas for raw mlk and sugar n the European Unon. Table 4. Country and Commodty Coverage of the ERS/Penn State Trade Model Country Coverage (12 countres/regons) Commodty Coverage 13 commodtes 12 olseed products 4 lvestock products 6 processed dary products Unted States, European Unon (EU-15), Japan, Canada, Mexco, Brazl, Argentna, Chna, Australa, New Zealand, South Korea, and a regon for the rest of the world (ROW). rce, wheat, corn, other coarse grans (barley, sorghum, mllet, and oats), soybeans, sunflower seed, rapeseed, peanuts, cotton, other olseeds (canola, flax seed, and others), tropcal ols, and sugar soybean ol and meal, sunflower seed ol and meal, rapeseed ol and meal, cottonseed ol and meal, peanut ol and meal, other olseed ol and meal beef and veal (combned), pork, poultry, raw mlk flud mlk, butter, cheese, nonfat dry mlk, whole dry mlk, and other dary products (ce cream, yogurt, and whey) The ERS/Penn State Trade Model adopted a reduced-form economc model n whch the behavor of producers, consumers, and other economc agents s represented by elastctes and other model parameters. The elastctes used n ths model are assumed to be constant and draw from other trade models, ncludng the European Smulaton Model (ESIM), the ERS baselne projectons model, and the Food and Agrcultural Polcy Smulator (FAPSIM), among others. 54

70 APTER FIVE THEORETICAL MODEL Introducton As presented n Chapter two, globally, Chna s the number one soybean mporter, and the U.S., Brazl, and Argentna are the top three soybean exporters. In 2004, Chnese soybean mports accounted for 35% of the world total, and soybean exports from the above three soybean exportng countres accounted for over 90% of the world total. Gven the above aggregate market shares of these soybean traders n the world soybean market, the world soybean market may not be perfectly compettve. Focusng on the Chnese soybean mport market, t may be characterzed as ether a monopsony where Chna, as the leadng soybean mporter, has stronger market power relatve to the U.S., Brazl, and Argentna, or as an olgopoly where the U.S., Brazl, and Argentna, as the leadng soybean supplers, have relatvely stronger market power than Chnese soybean mporters. Ths research seeks to test who has stronger market power n the Chnese soybean mport market, analyze ts compettve structure, and compare compettveness of the three soybean exporters. To conduct the compettve structure analyss of the Chnese soybean mport market, t s crtcal to know whether the market s characterzed as ether a monopsony or an olgopoly. Therefore, knowng the market power of dfferent players n the Chnese soybean mport market s a key factor n understandng the compettve structure of the market. To measure market power of soybean traders n the Chnese soybean mport market, an nverse resdual soybean supply, an nverse resdual soybean demand, and a 55

71 two-country partal equlbrum soybean trade model, combnng the nverse resdual soybean supply and the nverse resdual soybean demand, were developed, estmated, and compared n ths research. Modfcaton of the Lerner Index from the Exporters Perspectve Followng Carter, et al. (1999), assumng that all the soybean exporters n the soybean exportng country can be consdered as an aggregated frm, estmated coeffcents can be nterpreted as the share-weghted ndustry averages for all soybean exporters n a soybean exportng country. In addton, soybeans exported to Chna from dfferent countres are assumed homogeneous products. As shown n Fgure 21, left panel, the Chnese resdual soybean demand for country s (=the U.S, Brazl, and Argentna) soybeans equals the summaton of the Chnese domestc soybean supply, S ; plus Chnese mports from countres other than country, IMP OTH ; and the net change of soybean stocks n Chna, STK ; ths cumulatve supply mnus the Chnese domestc soybean demand, D. From the soybean exportng country s perspectve, t s assumed that soybean exporters n country face a downward slopng resdual soybean demand curve RD as shown n Fgure 21, rght panel. The curve MC n the rght panel of Fgure 21, s the margnal cost for soybean exporters n country. To maxmze soybean export profts, the soybean exporters n country choose pont A n Fgure 21, rght panel, where margnal cost equals margnal revenue, as the optmal choce. Accordngly, the equlbrum export quantty s XPT Q at the equlbrum export prce, XPT P mark-up for soybean exporters n country.. The dstance between A and B can be vewed as the 56

72 P S + IMP OTH + STK P XPT P B MC O D Farm P Q O A XPT Q MR RD Q Chna s Domestc Soybean Market Soybean Exports of Country --Chnese Resdual Soybean Demand for Country * = the U.S., Brazl, and Argentna Fgure 21. Chna s Resdual Demand for Country s Soybeans XPT Q Mathematcally, soybean exporters n country choose export quantty to Chna,, to maxmze ther profts, π, (17) Max π = P XPT Q XPT ( Q XPT )* Q XPT ( P Farm + C )* Q XPT where = the U.S., Brazl, and Argentna, and π s profts obtaned by soybean exporters n country. The varable XPT P s the soybean export prce by country, whch s a XPT Farm functon of ts export quantty,. The varable s the soybean farm level prce Q P n country, or the exporters purchase cost from soybean farmers n country, and the soybean exporters transacton costs n country. C s 57

73 The frst order condton (FOC) gves XPT π P XPT XPT Farm (18) = * Q + P ( P + C ) = 0 XPT XPT Q Q XPT P XPT XPT Farm ==> * Q + P ( P + C ) = 0 XPT Q ==> XPT Farm P P ( P + C ) = * Q Q XPT XPT XPT XPT Farm XPT XPT XPT XPT P ( P + C ) P Q P / P (19) ==> = * = XPT XPT XPT XPT XPT P Q P Q / Q Comparng equaton (19) wth the Lerner Index, equaton (5), the left hand sde of equaton (19) looks smlar to the Lerner Index, LI P MC =. Defnng P P ( P + C ) XPT P Farm XPT as the Adjusted Lerner Index for country (ALI ), the market power for soybean exporters n country over Chnese soybean mporters can be measured by the Adjusted Lerner Index for country. The rght hand sde of equaton (19) s the prce flexblty of Chna s nverse resdual demand for soybeans from country. Therefore the prce flexblty of Chna s nverse resdual demand for soybeans from country can be used as an ndrect measure to evaluate market power of soybean exporters n country. 58

74 The next step s to derve the relatonshp between the soybean export prce n XPT Farm country,, and the farm level soybean prce n country,. Consder equaton P (19) above. Assumng that the untary transacton costs of soybean exporters n country, C, are a constant rato, γ, of the country s farm level soybean prce, P Farm P,.e. C P / P XPT XPT γ =, and set θ Farm = XPT XPT P Q / Q, whch s the prce flexblty of the Chnese nverse resdual demand for soybeans from country, then equaton (19) can be wrtten as P XPT ( P + γ P ) Farm XPT P Farm = θ ==> P ( 1+ γ ) P = θ * P XPT Farm XPT ==> ( 1+ θ ) * P = (1 + γ ) P XPT Farm (20) ==> (1 + θ Farm XPT P = P (1 + γ ) ) (1 + θ ) (21) Set ϕ = (1 + γ ) Then equaton (20) can be wrtten as (22) P Farm = ϕ P XPT Equaton (22) ndcates a lnear relatonshp between the farm level prce and the export prce n country, assumng that n the short-run, the prce flexblty of the Chnese nverse resdual demand s constant. 59

75 Modfcaton of the Lerner Index from the Importers Perspectve From the Chnese soybean mporters sde, facng exportng country s upward slopng resdual soybean supply, Chnese soybean mporters choose an optmal mport quantty to maxmze ther mport profts. The curve RS, n the left panel of Fgure 22, s exportng country s resdual soybean supply for Chna, whch equals the exportng country s domestc supply, ; mnus domestc demand, D ; mnus exports to countres other than Chna, XPT ; mnus the change of soybean stocks n exportng country, Chnese mport profts, facng the resdual soybean supply curve, OTH STK. To maxmze RS, Chnese soybean mporters choose pont C n Fgure 22, left panel, where Chnese soybean mporters margnal revenue, MR, equals ther margnal mport costs, MC. S Accordngly, Chna s equlbrum mport quantty s IMP prce. P, IMP Q, at the equlbrum mport Mathematcally, Chnese soybean mporters choose mport quantty from IMP exportng country, Q,, to maxmze ther mport profts, π : (23) Max π, IMP Q = P ER * Q, IMP [(1 + t) P, IMP ( Q, IMP ) + C ]* Q, IMP where π s the mport profts obtaned by Chnese soybean mporters, and P s the Chnese domestc soybean retal prce. The varable IMP P, s the Chnese soybean mport prce from exportng country, and IMP Q, s the Chnese soybean mport quantty 60

76 from exportng country. The varable ER s the exchange rate, t s the Chnese mport tarff rate (ad valorem) on soybean mports, and by Chnese soybean mporters. C s the transacton costs pad P MR P P C RS S IMP P, D MC 0 IMP Q 0 Q, D + XPT OTH + STK Q Chnese Soybean Imports --Exportng Country s Resdual Soybean Supply Exportng Country s Domestc Soybean Market = the U.S., Brazl, and Argentna Fgure 22. Exportng Country s Resdual Soybean Supply to Chna The frst order condton (FOC) gves, IMP π,, P P IMP IMP (24) = 1 1 = 0, ( + t) *Q + [( + t)p + C ], IMP IMP Q ER Q, IMP P,, P IMP IMP ==> ( 1+ t) *Q + [( 1+ t)p + C ] = 0, IMP ER Q ==> (P P, IMP, IMP, IMP /ER ) C ( 1+ t)p = ( 1+ t) *Q, IMP Q 61

77 (P ==> /ER ) C (1 + t) P P, IMP, IMP, IMP = *Q, IMP 1+ t Q, IMP, IMP, IMP, IMP, IMP (P /ER ) C (1 + t) P P Q P / P (25) ==> = * =, IMP, IMP, IMP, IMP, IMP (1 + t) P Q P Q / Q Smlar to equaton (19), the left hand sde of equaton (25) looks smlar to the Lerner Index, LI P MC (P /ER ) C ( 1+ t) P =. Defne, IMP P ( 1+ t)p, IMP as the Adjusted Lerner Index for Chnese soybean mporters, ALI, whch can be used to measure monopsony power of Chnese soybean mporters over soybean exporters n country. The rght hand sde of equaton (25) s the prce flexblty of the country s nverse resdual soybean supply for Chna. The market power of Chnese soybean mporters can be measured ndrectly by estmatng the prce flexblty of country s nverse resdual soybean supply functon for Chna. The next step s to derve the relatonshp between the Chnese soybean mport prce from exportng country, IMP P,, and the Chnese domestc soybean retal prce, RTL P. Reconsderng equaton (25), the followng s obtaned RTL, IMP P / P (P /ER ) C ( 1 + t )P = ( 1+ t )P Q / Q, IMP, IMP, IMP, IMP, IMP, IMP, IMP RTL P / P, IMP ==> P /ER = ( 1 + t )P, IMP, IMP + C + ( 1+ t ) P Q / Q, IMP 62

78 , IMP, IMP RTL P Q IMP ==> P, /ER = ( * + 1 )( 1+ t)*p, IMP, IMP + C Q P, IMP, IMP RTL P Q IMP ==> P, = ( * + 1 )( 1+ t)*p, IMP, IMP + C *ER Q P Smlarly, assumng that transacton costs for Chnese soybean mporters,, C are a constant rato, γ, of the Chnese soybean mport prce,.e. γ = and, IMP P C settng θ = P Q * Q P, whch s the prce flexblty of exportng country s, IMP, IMP, IMP, IMP nverse resdual soybean supply functon for Chna, and t can be used to measure the market power of Chnese soybean mporters over soybean exporters n country, then, the above equaton becomes P RTL = [( 1,IMP θ + 1 )( + t )P + γ P,IMP ]*ER RTL (26) ==> P = [( 1 + t)( 1+ θ ) + γ, IMP ]*ER*P Durng the perod of ths research (January 1999 February 2005), the Chnese mport tarffs on soybeans and the Chnese exchange rate to U.S. dollars were constant. Settng (27) ϕ + = [( 1+ t )(1 + θ ) γ ]* ER *5.1 then equaton (27) can be wrtten as (28) ==> P = ϕ *P, IMP *5.1 Snce Chna had a fxed exchange rate, whch was pegged to the U.S. dollar, there were no changes n the Chnese exchange rate. 63

79 Equaton (28) shows the relatonshp between the Chnese soybean mport prce from exportng country, IMP P,, and the Chnese domestc soybean retal prce, P. Chna s Inverse Resdual Soybean Demand Model As shown n Fgure 21, the Chna s resdual demand for exportng coun try s soybeans equals the Chnese domestc demand for soybeans, D ; mnus Chnese domestc soybean supply, S ; mnus Chnese soybean mports from countres other than country, IMP OTH ; plus the net change of Chnese soybean stocks, STK. Mathematcally, the Chnese resdual demand functon for exportng country s soybeans can be wrtten as (29) RD = D ( S + IMP OTH ) + STK where the Chnese domestc demand and supply functons are defned as D (30) D = D ( P ; Z ) S (31) S = S (P ; Z ) P D where the varable s the Chnese domestc soybean retal prce, s a vector of Chnese demand shfters, ncludng the prces of substtutes or complements, ncome, Z populaton, among others; and S Z s a vector of Chnese supply shfters, ncludng prces of substtutes or complements, technology, producton costs, am ong others. Chnese mports from countres other than country and Chnese stocks of soybeans are consdered as exogenous varables n ths research. 64

80 Substtutng the Chnese soybean domestc demand (equaton (30)) and the Chnese domestc supply (equaton (31)) nto the Chnese resdual demand for exportng country s soybeans (equaton (29)), and wrtng t n ts mplct form, equaton (29) becomes D S OTH (32) RD = RD P ; Z, Z, IMP, STK ) ( Chapter 2 revewed Chnese botech polces and ther mpacts on soybean trade. To test the mpacts of Chnese botech polces on soybean exports to Chna, a dummy vara ble, the Chnese botech polcy, becomes BP, s added to ths model, then equaton (32) D S OTH (33) RD = RD P ; Z, Z, IMP, STK, BP ) ( Consderng the relatonshp between the Chnese soybean mport prce from exportng country and the Chnese domestc soybean retal prce, equaton (28) s substtuted nto equaton (33) to obtan, IMP D S OTH (34) RD = RD( P ; Z, Z, IMP, STK, BP ) Wrtng equaton (34) n ts nverse form, t becomes (35) P, IMP = P, IMP ( RD ; Z D, Z S, IMP OTH, STK, BP ) Equaton (35) s the Chnese nverse resdual demand functon for exportng country s soybeans. 65

81 Exportng Country s Inverse Resdual Soybean Supply Model As shown n Fgure 22, exportng country s resdual soybean supply to Chna equals the domestc soybean supply n exportng country, S ; mnus ts domestc OTH soybean demand, D ; mnus the soybean exports to countres other than Chna, XPT ; plus the net change of soybean stocks, STK. Mathematcally, exportng country s resdual soybean supply functon to Chna can be wrtten as (36) RS + STK OTH = S ( D + XPT ) Where domestc demand and supply functons n exportng country are defned as (37) D = D( P Farm ; Z D ) *5.2 (38) S = S(P Farm ; Z S ) Farm D The varable s the farm level soybean prce n exportng country, s a vector P of demand shfters n exportng country, ncludng prces of substtutes or complements, S ncome, populaton, among others; and s a vector of supply shfters n country, ncludng the prces of substtutes or complements, technology, producton costs, among others. The soybean exports from country to countres other than Chna, Z Z OTH XPT, and the soybean stock changes, STK, are consdered as exogenous varables. *5.2 Assumng a constant marketng margn between the U.S. soybean retal prce and the U.S. farm level prce, the U.S. farm level prce can be used n the U.S. domestc demand functon nstead of the U.S. soybean retal prce for estmaton purposes. 66

82 Substtutng domestc soybean supply (equaton (38)) and domestc soybean demand (equaton (37)) nto exportng country s resdual soybean supply functon for Chna (equaton (36)) and wrtng t n ts mplct form, equaton (36) becomes Farm S D OTH (39) RS = RS( P ; Z, Z, XPT, STK ) Consderng the relatonshp between the soybean export prce for Chna and the farm level soybean prce n exportng country, substtutng equaton (22) nto equaton (39) results n XPT S D OTH (40) RS = RS( P ; Z, Z, XPT, STK ) Wrtng equaton (40) n ts nverse form as XPT XPT S D OTH (41) P = P ( RS ;Z,Z, XPT, STK ) equaton (41) s exportng country s nverse resdual soybean supply functon to Chna. The Two-Country Partal Equlbrum Trade Model Assumng other source countres for Chnese mported soybeans and destnaton countres of country s soybean exports are exogenous factors, a two-country partal equlbrum trade model can be specfed (35) P, IMP = P, IMP ( RD ; Z D, Z S, IMP OTH, STK, BP ) XPT XPT S D OTH (41) P ( RS ; Z, Z, XPT, STK P = ) (42) RD = RS,IMP,IMP XPT (43) P P ( P ) = Where = exportng countres: U.S., Brazl, and Argentna. 67

83 Equaton (35) s the Chnese nverse resdual demand functon for exportng country s soybeans, and equaton (41) s exportng country s nverse resdual soybean supply functon for Chna. Equaton (42) s the equlbrum condton where, at equlbrum, the Chnese resdual soybean demand for country equals exportng country s resdual soybean supply for Chna. Equaton (43) captures the relatonshp between the Chnese soybean mport prce and exportng country s soybean export prce. Data used n ths research for the Chnese soybean mport prce s CIF (Cost, Insurance, and Freght) prce, whch ncludes the transportaton costs and nsurance costs. Data for exportng country s soybean export prce s FOB (Free on Board) prce. Equaton (43) reflects the nformaton of transportaton and nsurance costs. 68

84 APTER SIX VARIABLE IDENTIFICATION For emprcal estmaton purposes, varables n equaton (35) and (41) wll be dentfed and the specfc functonal form for Chna s nverse resdual demand model, exportng country s nverse resdual supply model, and the two-country partal equlbrum trade model wll be developed n ths chapter. Chna s Inverse Resdual Soybean Demand Model Equaton (35) ncludes four groups of varables. The frst group s the Chnese soybean mport quantty from exportng country or the Chnese resdual demand for country s soybeans, D Z RD. The second group s Chnese domestc demand shfters,. Theoretcally, demand shfters nclude ncome, populaton, prces of substtutes and complements, and consumers preferences, among others. In ths research, demand shfters for Chnese domestc soybeans nclude: the prce of corn n the Chnese domestc market, P Corn, assumng that corn s a substtute for soybeans for both soybeans and corn can be used for feed and ol, the Chnese personal dsposable ncome, INC, and the lvestock development ndex, LDI, snce soybeans can be crushed nto soymeal, whch s manly used for feed. In regards to the varable LDI, the Chnese lvestock ndustry has developed rapdly n recent years, whereby soymeal s a man feed materal for Chnese lvestock. As presented n Chapter two, n 2004, about 74% or 28 mllon metrc tons of soybeans were crushed n Chna and soyme al from crushed soybeans are manly used for feed 69

85 purposes. The development of the lvestock ndustry n Chna spurred an ncreasng demand for soymeal, whch led to an ncrease n soybean demand. The lvestock development ndex, LDI, was developed by calculatng the chan growth rate of Chnese total meat output. Meats used to calculate ths ndex nclude beef, pork, poultry, and fsh. In addton, the Chnese domestc soybean product prces -- soyol prce, Ol P, and soymeal prce, P -- were also ncluded n the model. Ol The thrd group s Chnese soybean supply shfters. Theoretcally, supply shfters nclude producton co sts, the prces of substtutes or complements, and technology, among others. In ths research, supply shfters of Chnese soybeans nclude the corn prce n the Chnese domestc market, Corn P. Smlarly, as n the Chnese domestc soybean demand model, corn s assumed to be a substtute for soybeans. Another varable ncluded n the Chnese domestc soybean supply model s technology, measured by the tme trend varable, T. Producton costs are not ncluded n the model. Data used n ths research s monthly data. However, data for producton costs for soybeans s yearly data. Producton costs are not ncluded n the model to avod a multcollnearty problem wth tme trend varable. OTH The last group ncludes Chnese soybean mports from other countres, IMP, and the Chnese botech polcy, BP. For the varable representng Chnese botech polcy, as dscussed n Chapter thre e, Chna passed ts frst botech product regulaton n May Therefore, n ths research, the varable BP equals 0 before May 2001 and 1 otherwse. Snce Chnese soybean stocks are very low and have not changed much 70

86 durng the perod of ths research (January 1999 February 2005), changes of the Chnese soybean stocks are not ncluded n ths model. Based on the theoretcal model and the above analyss, the specfc functonal form of the Chnese nverse resdual demand for exportng country s soybeans s wrtten as (44) P = α + αrd + α P + α INC + α LDI + α,imp 0 Corn Meal OTH α P + α T + α IMP + α BP ε 4 P Ol Defntons of the varables n equaton (44), ncludng unts, where $ equals U.S. dollars, MT equals metrc tons, and RMB equals Chnese yuan, are lsted as follows.,imp P : The Chnese soybean mport prce from exportng country ($/MT); RD Corn P : The Chnese resdual demand for exportng country s soybeans (MT), or the Chnese soybean mport quantty from exportng country ; : Chnese corn prce (RMB/MT); INC : Chnese personal dsposable ncome (RMB); LDI : The Chnese lvestock ndustry development ndex, whch s the growth rate of Chnese meat producton, ncludng pork, beef, poultry, and fsh; Ol P : Chnese soyol prce (RMB/MT); Meal P : Chnese soymeal prce (RMB/MT); T : Tme trend varable, measurng technologcal progress; 71

87 IMP OTH : Chnese soybean mports from countres other than exportng country (MT); BP : Chnese botech polcy, a dummy varable, equalng 0 before May 2001 and 1 otherwse; ε : Error term, assumed dentcally and ndependently dstrbuted. Exportng Country s Inverse Resdual Soybean Supply Model Smlar to the Chnese nverse resdual demand functon for country s soybeans, exportng country s nverse resdual soybean supply functon for Chna, equaton (41), also ncludes fve groups of varables. The frst group s the soybean export quantty from country to Chna, or exportng country s resdual soybean supply for Chna, RS. The second group s soybean demand shfters n exportng country, ncludng personal dsposable ncome wthn country, INC ; the domestc prce of corn n country, P Corn, a substtute for soybeans; the soyol prce n country, P prce n country, Meal P ; and the soymeal. The thrd group s soybean supply shfters for exportng Ol country, ncludng technology, measured by the tme trend varable, T, and the prce of corn n country, P Corn. The fourth group s country s soybean exports to countres other than Chna, OTH XPT. The last group s country s soybean begnnng stocks, STK. Then, based upon the theoretcal model and the above analyss, the specfc functonal form of exportng country s nverse resdual soybean supply functon for Chna can be wrtten as (45) P XPT β + = 0 + β XPT 6 βrs OTH + β P 1 + β STK 7 Corn + β INC + ε 2 + β P 3 Ol + β P 4 Meal + β T 5 72

88 where XPT P : Exportng country s soybean export prce to Chna ($/MT); RS : Exportng country s resdual soybean supply for Chna, or country s soybean exports to Chna (MT); INC : Personal dsposable ncome for exportng country ($); P : Corn prce n country ( $/MT); Corn Ol P : Soyol prce n country ($/MT); Meal P : Soymeal prce n country ($/MT); OTH XPT : Soybean exports from country to countres other than Chna (MT); STK : Begnnng soybean stocks n country (MT); ε : Error term, assumed dentcally and ndependently dstrbuted. Two-Country Partal Equlbrum Trade Model Combnng Chna s nverse resdual demand for exportng country s soybean (equaton (44)) and exportng country s nverse resdual soybean supply for Chna (equaton (45)), and ncorporatng the equlbrum condton, where Chna s resdual demand for exportng country s soybeans equals exportng country s resdual soybean supply to Chna,.e., RD = RS, the specfc functonal form of the two-country partal equlbrum trade model can be wrtten as 73

89 (44) P +,IMP Corn = α0 + αrd + α1p α2 + α 5 P Meal + α T + α IMP 6 7 OTH INC + α 8 + α BP 3 LDI + ε + α 4 P Ol (45) P XPT = β + βrs 0 + β XPT 6 OTH + β P 7 1 Corn + β STK + β INC + ε 2 + β P 3 Ol + β P 4 Meal + β T 5 (42) RD = RS,IMP (43) P = φ 0 + φ P XPT 1 where = exportng countre s: the U.S., Brazl, and Argentna. Assumng that n the short-run, the prce flexblty of ether the Chnese nverse resdual demand for exportng country s soybeans or exportng country s nverse resdual soybean supply to Chna s constant, then equatons (42)-(45) can be estmated by the double-log or sem-log form as shown by equatons (46) to (49). (46) LnP = + θ LnRD + α LnP + α LnPINC + α LnLDI,IMP α 0 + α 4 LnP Ol + α 5 LnP 1 Meal Corn + α LnT + α LnIMP OTH 3 + α 8 BP + ε (47) (48) LnP XPT = β + θ + β LnP LnRD = LnRS 4 0 Meal LnRS + β LnP Corn + β LnT + β LnXPT β LnPINC + β LnP 2 OTH + β LnSTK ε Ol (49) LnP = φ 0 + φ1lnp,imp XPT where =exportng countres: the U.S., Brazl, and Argentna. 74

90 The equaton system, equatons (46) to (49), s the fnalzed specfc functonal form of the two-country partal equlbrum soybean trade model. 75

91 APTER SEVEN EMPIRICAL ESTIMATION AND INTERPRETATION Introducton Snce most of the data for Brazl and Argentna are not avalable, only the U.S.- Chna partal equlbrum soybean trade model (equaton system (46-49) s estmated n ths research. Data Descrpton Data used n ths research are monthly data from January 1999 to February 2005, 74 observatons. The varables used n ths research and ther sources are lsted n Table 5. For Chna s nverse resdual soybean demand model, the varables for Chnese soybean US resdual demand,, U.S. resdual soybean supply,, are from the Chnese RD RS US Mnster of Agrculture (MOA, 2006). The varable Chnese soybean mport prce s a derved prce Chnese soybean mport value (Cost Insurance and Freght (CIF) value) dvded by mport quantty, and s also obtaned from the Chnese Mnster of Agrculture. The varable Chnese corn prce, soyol prce and soymeal prce are from Shangha JC Intellgence Co., Ltd. (2005). The varable Chnese personal dsposable ncome comes from the U.S. Department of Agrculture, Economcs Research Servce (USDA-ERS) Internatonal Macroeconomc Data Set (USDA-ERS, 2006). The raw data for Chnese personal dsposable ncomes are annual data. However, n ths research, monthly data s requred. To nclude personal dsposable ncome n ths model, the personal dsposable ncome was transformed nto monthly format, as descrbed below. 76

92 Table 5. Varables and Ther Sources Varable Meanng Source Chnese soybean mport prce US,IMP The Chnese Mnster of P from the Unted States Agrculture. (RMB/MT); US RD Corn P INC LDI Chnese resdual demand for U.S. soybeans (MT); Chnese corn prce at Dalan Port (RMB/MT); Chnese personal dsposable ncome (RMB); Chnese lvestock ndustry development ndex; The Chnese Mnster of Agrculture. Shangha JC Intellgence Co., Ltd. USDA-ERS. Chnese Statstcs Yearbook ( ). Ol P Chnese soyol prces (RMB/MT); Shangha JC Intellgence Co., Ltd. Meal P BR IMP AR IMP EXP P US RS US INC US Corn P US Chnese soymeal prces (RMB/MT); Chnese soybean mports from Brazl (MT); Chnese soybean mports from Argentna (MT); U.S. soybean export prce to Chna ($/MT); U.S. soybean resdual supply for Chna (MT); U.S. personal dsposable ncome ($); U.S. corn retal prce at Chcago market ($/MT); Shangha JC Intellgence Co., Ltd. The Chnese Mnster of Agrculture. The Chnese Mnster of Agrculture. USDA-FAS. The Chnese Mnster of Agrculture. USDA-ERS. USDA-ERS. Ol P US U.S. soyol prce ($/MT); USDA-ERS. Meal P US U.S. soymeal prce ($/MT); USDA-ERS. EU XPT US JP XPT US MX XPT US STK US U.S. soybean exports to the EU (MT); U.S. soybean exports to Japan (MT); U.S. soybean exports to Mexco (MT); U.S. soybean begnnng stocks (MT). USDA-FAS. USDA-FAS. USDA-FAS. USDA-ERS. 77

93 To transform the personal dsposable ncome from annual form to monthly form, the average growth rate, consstence, and precson were taken nto consderaton. Frst, the annual growth rate of Chnese personal dsposable ncome was calculated. Second, an ntal value was set as the January ncome. Then the calculated annual growth rate and the assumed ntal value were used to estmate the ncomes of the remanng months of the year. Next step s by usng tral-and-error method to adjust the January ncome to ensure that the sum of the estmated ncome for each month equals the actual annual ncome. Fgure 23 compares the actual annual data and the estmated monthly data for Chnese personal dsposable ncome. Fgure 23 ndcates that the estmated monthly data has a smlar trend as the actual annual data, statstcally, the estmated monthly ncome can be used as an approxmate to the real monthly ncome n the emprcal estmaton. The varable Chnese lvestock development ndex, LDI, s developed by calculatng the annual growth rate of Chnese total meat output, ncludng beef, pork, and poultry, and fsh *7.1. The actual data of meat output s annual data from the Chnese Statstcs Yearbook, (Chnese Natonal Bureau of Statstcs, 2005). The same method s used to transform the actual annual data nto estmated monthly data. The estmated monthly data was used as an approxmate of the real monthly data. Then the monthly growth rate of the estmated meat output s calculated as an ndex to reflect the demand change n feed due to rapd development of the Chnese lvestock ndustry, LDI. *7.1 Although fsh does not belong to the lvestock ndustry, feed for fsh also contans a great amount of soymeal. Therefore, when calculatng the lvestock development ndex, I also ncluded fsh meat n the total meat output. 78

94 Chnese Personal Dsposable Income (Actual Annual Data) 9000 RMB (Yuan) Chnese Personal Dsposable Income (Estmated Monthly Data) 800 RMB (Yuan) Jan- 99 Jul-99 Jan- 00 Jul-00 Jan- 01 Jul-01 Jan- 02 Jul-02 Jan- 03 Jul-03 Jan- 04 Jul-04 Jan- 05 Fgure 23. Chnese Personal Dsposable Income: Annual and Monthly The varable Chnese soybean mports from other countres, OTH IMP, ncludes two countres--brazl and Argentna. So n the specfc functonal form of the Chnese nverse resdual demand model, the varable OTH IMP s dvded nto two varables: Chnese soybean mports from Brazl, Argentna, AR IMP BR IMP, and Chnese soybean mports from. Data for these two varables are also from the Chnese Mnster of 79

95 OTH BR AR Agrculture. After dvdng the varable IMP nto two varables: IMP and IMP, Chna s nverse resdual demand for U.S. soybean model (equaton 46) becomes LnP US,IMP α 0 = + θ US LnRD US + α 1 LnP Corn + α 2 LnPINC + α 3 LnLDI (50) + α 4 LnP Ol + α 5 LnP Meal + α LnT + α LnIMP 6 7 BR + α 8 LnIMP AR + α 9 BP + ε For the U.S. nverse resdual soybean supply to Chna model, the varables U.S. soybean export prce to Chna s a derved prce (FOB prce) obtaned by dvdng the total monthly value of U.S. soybean exports by the total monthly volume of U.S. soybean exports. Data for U.S. soybean export value and volume were obtaned from the U.S. Department of Agrculture, Foregn Agrculture Servce (USDA-FAS, 2006) U.S. Trade Internet System. The varable U.S. personal dsposable ncome comes from USDA-ERS, Internatonal Macroeconomc Data Set (2006). Smlar to Chnese personal dsposable ncome, the raw data of U.S. personal dsposable ncome s annual data. Usng the same method as used for Chnese personal dsposable ncome, U.S. monthly personal dsposable ncome s estmated from the actual annual ncome. Fgure 24 compares the actual annual data and the estmated monthly data for U.S. personal dsposable ncome, and t shows that the estmated monthly data has the smlar trend as the actual annual data. 80

96 U.S. Personal Dsposable Income (Actual Annual Data) USD($) U.S. Personal Dsposable Income (Estmated Monthly Data) USD($) Jan- 99 Jul- 99 Jan- 00 Jul- 00 Jan- 01 Jul- 01 Jan- 02 Jul- 02 Jan- 03 Jul- 03 Jan- 04 Jul- 04 Jan- 05 Fgure 24. U.S. Personal Dsposable Income: Annual and Monthly The varable the U.S. corn prce comes from USDA-ERS, Feed Outlook Report from 1995 to 2005 (USDA-ERS, 2005b). The varables U.S. soyol prce, U.S. soymeal prce, and U.S. soybean stocks come from USDA-ERS, Ol Crops Yearbook from (USDA-ERS, 2005c). The varable U.S. soybean exports to countres other than OTH EU Chna, EXP, s dvded nto three varables: U.S. soybean exports to the EU, EXP, US US 81

97 JP MX U.S. soybean exports to Japan, EXP, and U.S. soybean exports to Mexco, EXP. Data for these three varables come from USDA-FAS U.S. Trade Internet System OTH EU (USDA-FAS, 2006). After dvdng the varable EXP nto three varables: EXP, EXP JP US becomes US MX, and EXP, U.S. nverse resdual soybean supply for Chna model (equaton 47) US US US US LnP XPT US = β + θ 0 US LnRS US + β LnP 1 Corn US + β LnPINC 2 US + β LnP 3 Ol US (51) + β LnP 4 Meal US + β LnT + β LnXPT 5 6 EU US + β LnXPT 7 JP US + β LnXPT 8 MX US + β LnSTK 9 US + ε US becomes Then the U.S.-Chna partal equlbrum soybean trade model (equatons 46-49) LnP US,IMP α 0 = + θ US LnRD US + α 1 LnP Corn + α 2 LnPINC + α 3 LnLDI (50) + α 4 LnP Ol + α 5 LnP Meal + α LnT + α LnIMP 6 7 BR + α 8 LnIMP AR + α 9 BP + ε LnP XPT US = β + θ 0 US LnRS US + β LnP 1 Corn US + β LnPINC 2 US + β LnP 3 Ol US (51) + β LnP 4 Meal US + β LnT + β LnXPT 5 6 EU US + β LnXPT 7 JP US + β LnXPT 8 MX US + β LnSTK 9 US + ε US (52) (53) LnRD = LnRS US US,IMP US LnP = φ 0 + φ1lnp XPT US Specfcaton Test Before estmatng the U.S.-Chna partal equlbrum soybean trade model, heteroskedastcty, autocorrelaton, and multcollnearty tests are conducted for both 82

98 Chna s nverse resdual demand functon for U.S. soybeans (equaton 50) and U.S. nverse resdual soybean supply functon for Chna (equaton 51). Heteroskedastcty Test Whte s test (Whte 1980) s used to test the heteroskedastcty problems for both Chna s nverse resdual demand functon for U.S. soybeans (equaton 50) and U.S. nverse resdual soybean supply functon for Chna (equaton 51). The resduals of estmaton are used to nvestgate the heteroskedastcty of the true dsturbances. The null hypothess for Whte s test s 2 2 H 0 : σ = σ for all. SAS proc model procedure gves the test results when the opton Whte s gven (SAS, v.8.02). Test results, shown n Table 6, ndcate that the null hypothess for equaton (50) and (51) cannot be rejected for both models. These test results mply that both Chna s nverse resdual demand functon and U.S. nverse resdual soybean supply functon do not encounter the heteroskedastcty problem. Table 6. Whte s Test Results for Heteroskedastcty Functon Whte's Test Statstc Crtcal Value Pr>ChSq Result The Chna s nverse resdual demand functon for U.S. soybeans (equaton 50) Fal to reject H 0. The U.S. nverse resdual soybean supply functon for Chna (equaton 51) Fal to reject H 0. 83

99 Autocorrelaton Test Autocorrelaton problem was tested by testng the correlaton of the current resdual and the lagged resdual obtaned from the ordnary least square estmaton (OLS). Frst, ntal resduals were obtaned by OLS estmaton (by SAS). Next step s runnng et e t 1 regresson of the current resdual on the lagged resdual to test whether the parameter of e t 1 s sgnfcant or not. Mathematcally, (54) e c + c e u t = 0 1 t 1 + et e t 1 where s the resdual from the OLS estmaton, and s the lagged resdual. Hypothess to be tested s H 0 : c1 =0, Ha: c1 0. Test results for both Chna s nverse resdual demand functon (equaton 50) and U.S. nverse resdual supply functon (equaton 51), shown n Table 7, mply that the null hypothess for Chna s nverse resdual demand functon, cannot be rejected. However, the null hypothess for U.S. nverse resdual supply functon s rejected. These test results ndcate that Chna s nverse resdual demand functon does not appear to encounter the autocorrelaton problem, whle the U.S. nverse resdual soybean supply functon does have autocorrelaton. To mprove emprcal estmaton results, the autocorrelaton problem for the U.S. nverse resdual soybean supply functon need to be corrected. 84

100 Table 7. Test Results for Autocorrelaton Functon The Chnese nverse resdual demand functon for U.S. soybeans (equaton 50) The U.S. nverse resdual soybean supply functon for Chna (equaton 51) Coeffcent Standard Error T-value Pr>ChSq Result Fal to reject H Reject H 0. Multcollnearty Test Two methods are used to test for multcollnearty. The frst one looks at the correlatons among ndependent varables. If the correlaton between two varables s very hgh, then the multcollnearty problem may be present. Test results for Chna s nverse resdual demand functon for U.S. soybeans, reported n Table 8, show that the correlaton between the tme trend varable, T, and Chnese personal dsposable ncome, INC, s 0.99 and the correlaton between the tme trend varable, T, and the Chnese lvestock development ndex, LDI, s That means the tme trend varable, T, s possbly a problematc varable, whch causes multcollnearty problem. 85

101 Table 8. Correlaton between Independent Varables for the Chnese Inverse Resdual Demand for U.S. Soybeans Correlaton US RD Corn P INC LDI Ol P US RD 1 Corn P INC LDI Ol P Meal P T Meal P BR IMP AR IMP BP T BR IMP AR IMP BP Test results for U.S. nverse resdual soybean supply for Chna, reported n Table 9, show that the correlaton between the tme trend varable, T, and the U.S. personal dsposable ncome, INC US, s 0.96, whch means that there s a possble collnearty problem between these two varables. From ths method, results ndcate that for both Chna s nverse resdual demand functon and U.S. nverse resdual soybean supply, the tme trend varable, T, mght cause the multcollnearty problem. 86

102 Table 9. Correlaton between Independent Varables for the U.S. Inverse Resdual Soybean Supply for Chna Correlaton RS US INC US RS US 1 INC US Corn P US Ol P US Meal PUS Corn P US Ol P US Meal P US T EU XPT US JP XPT US MX XPTUS STKUS T EU XPT US JP XPT US MX XPT US STK US The second method s the Condton Indces developed by Belsey, Kuh, and Welsch (1980). When the calculated condton ndex s around 10, weak dependences may be startng to affect the regresson estmates. When ths number s larger than 100, the estmates may have a far amount of numercal error (SAS, v8.02). In SAS, opton COLLIN automatcally tests multcollnearty problem and gves suggested varables whch may cause multcollnearty problem. SAS estmaton results for both Chna s nverse resdual demand functon and U.S. nverse resdual soybean supply functon, ndcate that the tme trend varable, T, was the only varable that caused the multcollnearty problem. To avod multcollnearty problem, n the fnal estmaton, the tme trend varable, T, was dropped. 87

103 Emprcal Estmaton and Interpretaton In ths secton, the two-country partal equlbrum trade model (equaton 50-53) s estmated smultaneously by SAS full nformaton maxmum lkelhood (FIML) method. Estmaton results, reported n Table 10, show that for Chna s nverse resdual demand functon (equaton 50), four varables, ncludng the Chnese resdual demand, US RD Corn, the Chnese domestc corn prce,, and the prces of soyol and soymeal n Ol Meal Chna, and, are statstcally sgnfcant at a 1% sgnfcant level. P P P The sgn of the estmated coeffcent for the Chnese resdual demand, US RD negatve as expected, ndcatng a downward slopng resdual demand for U.S. soybeans. By equaton (55), the estmated coeffcent s also the prce flexblty of the Chnese resdual demand functon for U.S. soybeans, equalng the Adjusted Lerner Index, ALI whch can be used to measure the market power of U.S. soybean exporters as shown by equaton (19). From another perspectve, the estmated coeffcent also ndcates the market margn of U.S. soybean exporters (the dfference between the U.S. soybean export prce and the sum of the U.S. farm level soybean prces and the transacton costs of U.S. soybean exporters). Results from Table 10 mply that the U.S. soybean exporters marketng margn s 4% of the U.S. farm level soybean prce., s US, For the estmated coeffcent of the Chnese domestc corn prce, results mply that keepng other varables constant, a 1% corn prce ncrease wll cause a 27% ncrease n the Chnese soybean mport prce from the Unted States. For the Chnese domestc prces of soyol and soymeal, they are movng n the same drecton wth the soybean 88

104 mport prce. The estmated cross prce elastctes of the Chnese soybean mport prce from the U.S. wth respect to the soyol or soymeal prces are 0.44 and 0.30 respectvely. Table 10. Estmaton Results of the Two-country Partal Equlbrum Model Equaton Varable Coeffcent Standard Error t Value Pr > t Chnese Inverse Resdual Demand: IMP US P = P( RD,...) US Intercept US RD *** Corn P *** INC LDI Ol P *** <.0001 Meal P *** BR IMP AR IMP BP U.S. Inverse Resdual Supply: XPT P = P( RS, US US...) Intercept *** RS US *** Corn P US INC US ** Ol P US *** <.0001 Meal P US *** EU XPT US JP XPT US MX XPT *** STK US *** Prce Relatonshp: IMP XPT P P( P ) US = XPT US US Intercept P *** <.0001 Note: *** 1% sgnfcance level, ** 5% sgnfcance level, * 10% sgnfcance level. 89

105 For the varable Chnese botech polcy, BP, the sgn s negatve as expected ndcatng that the mpacts of Chnese botech polcy on U.S. soybean exports to Chna s negatve. However, the varable BP s not sgnfcant (10% sgnfcance level), mplyng that Chnese botech polcy dd not mpose sgnfcant mpacts on U.S. soybean exports to Chna n the long-run. Ths result s consstent wth the actual observatons dscussed n Chapter three. For U.S. nverse resdual soybean supply functon (equaton 51), seven ndependent varables, ncludng the resdual supply quantty, RS US, the U.S. personal Ol Meal dsposable ncome, INC US, the U.S. soyol prces,, the U.S. soymeal prces,, JP MX the U.S. soybean exports to Japan, XPT US, the U.S. soybean exports to Mexco, XPT US, P US P US and the U.S. soybean stocks, STK US, are statstcally sgnfcant at 1% to 5% sgnfcance levels respectvely as shown n Table 10. The sgn of the parameter for the U.S. soybean resdual supply for Chna, RS US U.S. resdual soybean supply for Chna., s postve as expected, ndcatng an upward slopng quantty, By equaton (56), the estmated coeffcent for the U.S. soybean resdual supply RS US, s also the prce flexblty of the U.S. nverse resdual soybean supply functon for Chna, whch s also the Adjusted Lerner Index, ALI by equaton (25), whch can be used to measure the market power of Chnese soybean mporters. From another perspectve, accordng to the left hand sde of equaton (25), ths estmated coeffcent also ndcates the marketng margn of Chnese soybean mporters (the dfference between the Chnese domestc soybean prce and the sum of Chnese soybean mport prce from the U.S. and transacton costs of Chnese soybean mporters and mport 90

106 tarffs). Results from Table 10 mply that the marketng margn of Chnese soybean mporters s 13% of the soybean mport prce from the U.S. plus tarffs. Table 11 summarzes the above dscusson. The estmated prce flexblty of the Chnese nverse resdual demand for U.S. soybeans s -0.04, mplyng that the marketng margn for U.S. soybean exporters (the dfference between the U.S. soybean export prce and the sum of the U.S. farm level soybean prces and the transacton costs of U.S. soybean exporters) s 4% of the export prce. The estmated prce flexblty of the U.S. nverse resdual soybean supply functon for Chna s 0.13, mplyng that the marketng margn for Chnese soybean mporters s 13% of the soybean mport prce plus tarffs. Comparng these two coeffcents, t can be nferred that the market power of Chnese soybean mporters s stronger than that of U.S. soybean exporters. Table 11. Summary of the Estmaton Results Model Coeffcent for Quantty Standard Error T- Value Pr> t Chnese Inverse Resdual Demand: IMP IMP P = P( Q,...) US U.S. Inverse Resdual Supply: XPT XPT P = P( Q...) US US -0.04*** *** Note: *** 1% sgnfcance level, ** 5% sgnfcance level, * 10% sgnfcance level. 91

107 APTER EIGHT COMPETITIVE ANAYSIS OF INA S SOYBEAN IMPORT MARKET Results of Chapter seven show that n the Chnese soybean mport market Chnese soybean mporters have stronger market power than U.S. soybean exporters. In addton, t s assumed that Chnese soybean mporters also have stronger market power than soybean exporters from Brazl and Argentna. Based on the above results and assumpton, a compettve analyss of the Chnese soybean mport market s conducted by examnng both annual and monthly data of Chnese soybean mports from these three soybean exportng countres. In addton, after examnng the compettve structure of these three soybean exporters n the Chnese soybean mport market, compettveness of the U.S., Brazl, and Argentna n the Chnese soybean mport market s compared by analyzng ther soybean exports costs. The U.S., Brazl, and Argentna n the Chnese Soybean Import Market As revewed n Chapter two, Chna s the number one soybean mporter and the U.S., Brazl, and Argentna are the top three soybean exporters n the world. Fgure 25 shows that soybean surpluses (defned as the dfference between the domestc supply and the domestc consumpton n soybean exportng countres) n the U.S., Brazl, and Argentna ncreased annually n recent years. In 2005, soybean surpluses n the U.S., Brazl, and Argentna reached 33, 25, and 10 mllon metrc tons, respectvely (USDA- FAS, 2006b). To avod hgh accumulaton of soybean stockples, export markets are crucal for the soybean ndustres n the U.S., Brazl, and Argentna. 92

108 40 30 Soybean Surpluses n the U.S., Brazl, and Argentna 33 Mllon Metr Tons US Brazl Argentna Fgure 25. Soybean Surplus n Man Soybean Exportng Countres Source: USDA-FAS, PS&D data, 2006b. 30 Soybean Shortages n Chna, the EU, Japan, and Mexco 27 Mllon Metr Tons Chna EU Japan Mexco Fgure 26. Soybean Shortage n Man Soybean Importng Countres Source: USDA-FAS, PS&D data, 2006b. 93

109 Fgure 26 shows the trends of soybean shortages (defned as the dfference between the domestc consumpton and the domestc producton n the soybean mportng countres) for the top soybean mporters n the world, ncludng Chna, the European Unon, Japan, and Mexco. Soybean shortage n Japan was qute stable n the past, and soybean shortage n the EU and Mexco dd not ncrease much n the past decade. By these trends, t can not be expected that the EU, Japan, and Mexco wll ncrease ther soybean mports much n the future. However, for Chna, ts soybean shortage ncreased dramatcally n recent years, from almost null n 1991 to 27 mllon metrc tons n Combnng the above trends of soybean exporters and soybean mporters, t s reasonable to state that Chna s and wll contnue to be the most mportant market for the U.S., Brazl, and Argentna s soybean surpluses. Results from Chapter seven ndcate that Chnese soybean mporters had stronger market power over U.S. soybean mporters. Three large soybean supplers facng one large soybean buyer wth a rapd growth potental may support the assumpton that Chnese soybean mporters may have stronger market power than soybean exporters from Brazl and Argentna. Because Chna s the most mportant market for the U.S., Brazl, and Argentna, these three soybean exporters compete wth each other n the Chnese soybean mport market to expand ther soybean market shares. From a soybean supplers perspectve, the compettve relatonshp among the U.S., Brazl, and Argentna n the Chnese soybean mport market wll be examned n the followng secton. To smplfy the problem, Brazl and Argentna are consdered as a group, the South Amerca (SA) soybean suppler. As shown n fgure 27, the U.S. and South Amerca (Brazl and Argentna) are competng n the leadng soybean mport market, Chna. However, the 94

110 queston s what s the relatonshp between the U.S. and South Amerca n the Chnese soybean mport market? U.S. Chna Brazl Argentna South Amerca the U.S. Brazl Argentna Substtutes or Complements? Chna Fgure 27. Chnese Soybean Import Market * Source: MapQuest, Inc. (Mapquest.com). Are the U.S. and South Amerca Substtutve Soybean Supplers for Chna? Fgure 28 shows that Chnese annual soybean mports from South Amerca were slghtly lower than that from the U.S. before 2001 and n From 2001 to 2003 and 95