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Global Competition for the Japanese Fruit Juice Market

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GLOBAL COMPETITION FOR THE JAPANESE FRUIT JUICE MARKET By SHIFERAW TESFAYE FELEKE A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2006

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Copyright 2006 By Shiferaw Tesfaye Feleke

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This document is dedicated to my mom

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iv ACKNOWLEDGMENTS Writer William Arthur Ward once said, “Fee ling gratitude and not expressing it is like wrapping a present and not giving it.” I couldn't agree more. My first, and most sincere, acknowledgment must go to the chai rman of my supervisory committee, Dr. Richard L Kilmer. I would like to express my deepest gratitude and sincere appreciation to him for his meticulous review of the manuscript, guidance, encouragement and patience to successfully complete my study. I gratefully acknowledge and thank him for everything he did throughout my program. I was very fortunate to work closely with him. Our frequent interactions were very invalu able learning experiences. I am also very grateful to Dr. Jonq Lee for introducing me the differential demand systems and TSP program and helping me understand the basi cs and analytics of differential demand systems that provide the basis of this study. I sincerely thank hi m for his patience in reviewing, providing me with invaluable co mments and suggestions from the very beginning of proposal preparation up until th e completion of this dissertation. Many thanks must also go to the other members of my supervisory committee, Drs. Ronald Ward, James Sterns and Lawrence Kenny, for providing me with constructive comments and suggestions. I would like to thank them a ll for their support and guidance. I am also grateful to Dr. Mark Brown for his assistance with the data analysis. I am grateful to the Food and Resource Economics Department of the University of Florida for affording me the opportunity of research assistantship to pursue my studies in the department for the last six years. Speci al thanks must go to the department chair,

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v Dr. Thomas Spreen, graduate coordinator Dr Jeffery Burkhardt, and graduate program assistant Jessica Herman. I am very apprec iative of the support I received from Dr. Spreen and Jessica Herman. I am also thankful to my officemate Katherine Finn for every help she offered me during the preparation of this dissertation and for being a nice officemate. I would also like to thank my friends and classmates Marc o, Angel, Lurleen, Joy, Mariana and Maria. Special thanks go to Lurleen for being an im portant force of motivation. Our frequent interactions have been the sour ce of learning. I am indebted to my fellow friends Seleshi, Worku, Abiy, Dr. Getachew, Dr. Ayalew, Dr. Te sfaye, Saba Haile Selasie, Saba Ataro and Measho for their support, encouragement and friendship. My final, and most heartfelt, acknowledgm ent must go to my father Tesfaye, my sister Firehiwot, my wife Genet and my daught er Biruktawit. I dedi cate this dissertation to my mother Yeshi who passed away a couple of years ago.

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vi TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES.............................................................................................................ix LIST OF FIGURES..........................................................................................................xii ABSTRACT.....................................................................................................................xi ii 1 INTRODUCTION........................................................................................................1 Background...................................................................................................................1 Objectives..................................................................................................................... 4 Hypotheses....................................................................................................................5 Outline........................................................................................................................ ..7 2 GLOBAL PRODUCTION, TRADE AND CONSUMPTION OF FRUIT..................9 Global Fruit Production................................................................................................9 The Production of Oranges, Lemons and Limes, and Grapefruits and Pomelos12 The Production of Grapes, Apples, and Pineapples............................................16 Global Fruit Trade......................................................................................................19 Global Fruit Consumption..........................................................................................21 3 THEORETICAL MODELS.......................................................................................24 Demand Approaches...................................................................................................24 Production Approach...........................................................................................25 Consumer Demand Approach.............................................................................28 Utility Maximization..................................................................................................29 The Rotterdam Model.................................................................................................32 Block Independence............................................................................................36 Block-wise Dependence......................................................................................39 Uniform Substitute Hypothesis...........................................................................42 Uniform substitute given block independence.............................................42 Uniform substitute given block-wise dependence........................................45

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vii 4 EMPIRICAL MODELS AND ESTIMATION PROCEDURES...............................48 Empirical Models........................................................................................................48 The Relative Price Version of the Rotterdam Model..........................................48 The Absolute Price Version of the Rotterdam Model.........................................52 Block Independent Non-uniform Substitute-Rotterdam Model..........................54 Block-wise Dependent Non-uniform Substitute-Rotterdam Model....................56 Block Independent Uniform Substitute-Rotterdam Model.................................60 Block-wise Dependent Uniform Substitute-Rotterdam Model...........................63 Data Sources...............................................................................................................66 Analytical Methods.....................................................................................................67 5 RESULTS AND DISCUSSION.................................................................................69 Descriptive Results.....................................................................................................69 Test for First-order Autocorrelation...........................................................................70 Hypothesis Testing for Model Selection....................................................................72 Block Independence and Uniform Substitute Hypothesis...................................72 Block-wise Dependence and Un iform Substitute Hypothesis.............................74 The relative Price Version of the Rotterdam Model...................................................76 Parameter Estimates............................................................................................77 Expenditure Elasticities.......................................................................................82 Own-price Elasticities.........................................................................................88 Cross-price Elasticities........................................................................................90 6 MARKET STRUCTURES AND STRATEGY OPTIONS.......................................97 Market Structures........................................................................................................97 Block Independence (Direct) with Non-uniform Substitution............................97 Block Independence (Direct) with Uniform Substitution...................................98 Block-wise Dependence with Non-uniform Substitution....................................98 Block-wise dependence with Uniform Substitution..........................................100 Parameter and Elasticity Estimates in Five Market Structures.........................101 Parameter estimates....................................................................................102 Expenditure elasticities..............................................................................104 Price elasticities..........................................................................................106 Market Strategy Options...........................................................................................109 7 SUMMARY, CONCLUSIONS AND IMPLICATIONS.........................................110 Summary and Conclusions.......................................................................................110 Implications..............................................................................................................114 APPENDIX A PRICE COEFFICIENTS OF FRUIT JUICES IN JAPAN.......................................118 B PRICE ELASTICITES OF FR UIT JUICES IN JAPAN..........................................124

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viii C PARAMETER ESTIMATES OF ROTTERDAM MODEL UNDER DIFFERENT SEPARABILITY ASSUMPTIONS.........................................................................136 D PRICE ELASTICITIES OF FRUIT JUICES IN JAPAN IN DIFFERENT MARKET STRUCTURES.......................................................................................142 E TWO-STAGE ROTTERDAM MODEL..................................................................166 F PARAMETER ESTIAMTES OF FRUIT JUCIES IN A TWO-STAGE ROTTERDAM MODEL..........................................................................................180 LIST OF REFERENCES.................................................................................................187 BIOGRAPHICAL SKETCH...........................................................................................192

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ix LIST OF TABLES Table page 2.1 Global citrus production, area harv ested and yield per hectare, 2005.....................10 2.2 Global production of oranges, grapefru it and pommels, and lemons and limes in 2005..........................................................................................................................1 2 2.3 Global production of apples, grapes, and pineapples, 2005.....................................16 2.4 Fruit juice imports to Ja pan by country of origin.....................................................22 2.5 Per capita consumption of fruits in industrialized and developing countries..........23 4.1 Codes for countries expor ting fruit juice to Japan...................................................50 5.1 Fruit juice quantity and price log-ch anges, and expenditure shares, Japan, December 1995 to May 2005...................................................................................70 5.2 Test for first-order autocorrelation...........................................................................71 5.3 Hypothesis testing for model selection....................................................................74 5.4 Marginal expenditure shares of imported fruit juices in Japan................................77 5.5 Parameter estimates of cross prices of fruit juices in Japan.....................................80 5.6 Parameter estimates of own pri ces of fruit juices in Japan......................................82 5.7 Expenditure elasticity estimates of fruit juices in Japan..........................................84 5.8 Own price elasticities of fruit juices in Japan...........................................................89 5.9 Cross-price elasticity estimates of substitutes..........................................................94 5.10 Cross-price elasticity es timates of complements.....................................................96 6.1 Importance of country of origin in five market structures.....................................101 6.2 Relative price coefficients of fruit juices in five market structures.......................104 6.3 Expenditure elasticity estimates of fruit juices in Japan in five market structures105

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x 6.4 Uncompensated own price elasticity es timates of fruit juices in Japan.................107 6.5 Compensated own price elasticity esti mates of fruit juices in Japan.....................108 6.6 Market strategies by market structures...................................................................109 A-1 Relative price coefficients of fruit juices in Japan.................................................118 A-2 Slutsky price coefficients of fruit juices in Japan..................................................121 B-1 Uncompensated price elasticiti es of fruit juices in Japan.......................................124 B-2 Compensated price elasticities of fruit juices in Japan..........................................130 C.1 Marginal value shares of fruit juices in a block independent Rotterdam model....136 C.2 Relative price coefficients of fruit juices in a block independent Rotterdam model......................................................................................................................136 C.3 Marginal value shares of fruit juices in a block independent uniform-substitute Rotterdam model....................................................................................................137 C.4 Marginal value shares of fruit jui ces in a block-wise dependent Rotterdam model......................................................................................................................138 C.5 Constant of proportionality of fruit ju ice groups in a in block-wise dependent Rotterdam model....................................................................................................138 C.6 Within-group relative price coefficients of fruit juices in a block-wise dependent Rotterdam...............................................................................................................138 C.7 Marginal value shares of fruit jui ces in a block-wise dependent uniformsubstitute Rotterdam model....................................................................................139 C.8 Constant of proportionality of fruit juice groups in a block-wise dependent uniform-substitute-R otterdam model.....................................................................140 C.9 Within-group relative price coefficients of block-wise dependent uniform substitute Rotterdam model....................................................................................140 F.1 Marginal value shares of fruit ju ices in a two-stage block independent Rotterdam model....................................................................................................180 F.2 Relative price coefficients of fruit juices in a two-stage block independent Rotterdam model....................................................................................................181 F.3 Marginal value shares of fruit juices in a two-stage block independent uniformsubstitute-Rotterdam model e.................................................................................182

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xi F.4 Marginal value shares of fruit jui ces in a two-stage bl ock-wise dependent Rotterdam model....................................................................................................183 F.5 Relative price coefficients of fruit ju ices in a two-stage block-wise dependent Rotterdam model....................................................................................................184 F.6 Marginal value shares of fruit jui ces in a two-stage bl ock-wise dependent uniform-substitute-R otterdam model.....................................................................185 F.7 Relative price coefficients of fruit ju ices in a two-stage block-wise dependent uniform-substitute-R otterdam model.....................................................................186

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xii LIST OF FIGURES Figure page 2.1 Citrus productions (MT) of major producers, 1961-2005........................................11 2.2 Orange productions (MT) of major producers, 1961-2005......................................13 2.3 Lemon and lime production (MT) of the top four producers, 1961-2005................14 2.4 Grapefruit and pomelos production (MT) in the U.S. and China, 1961-2005.........15 2.5 Grape productions (MT) of th e top three countries, 1961-2005..............................17 2.6 Apple productions (MT) in the U.S. and China.......................................................18 2.7 Pineapple productions (MT) of major producers, 1961-2005..................................19 3.1 A two stage profit maximization..............................................................................26 3.2 A two-stage utility maximization.............................................................................27

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xiii Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy GLOBAL COMPETITION FOR THE JAPANESE FRUIT JUICE MAREKT By Shiferaw Tesfaye Feleke August 2006 Chair: Richard L. Kilmer Major Department: Food and Resource Economics This study identifies the market structure of fruit juices imported into Japan within the context of a cons umer demand theory using three different versions of the Rotterdam model (the block independent uniform substitute-Rotterdam model, the blockwise dependent uniform substitu te-Rotterdam model, and the relative price version of the Rotterdam model). The models were formulated under the hypotheses of block independence/block-wise dependence among pr oducts that belong to different product groups and uniform substitute among products that belong to the same product group. They were estimated for six different kinds of fruit juices (orange, grapefruit, other citrus, apple, pineapple and grape juices imported fr om 18 countries) on monthly per capita data over the period December, 1995, to May, 2005, us ing the non-linear least squares (LSQ) in the Time Series Processor (TSP) program. Statistical tests select the relative price version of the Rotterdam de mand model as explaining the allocation decisions better compared with the other versions and identi fy a market structure which involves both direct and indirect competition ba sed on the country of origin.

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xiv The results have important implications fo r countries exporting fruit juices to Japan for identifying marketing stra tegies such as price reduc tion, product promotion, market integration, as well as export s upply decisions in light of the expansion and contraction of the Japanese market for imported fruit ju ices because of the change in income.

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1 CHAPTER 1 INTRODUCTION Japan, with the second largest economy in the world and a population of about 127 million, imports agricultural products wo rth over $30 billion each year (USDA). The U.S. is the leading agricultural supplier acc ounting for nearly one-third of Japan’s total agricultural imports, though this share has declined slightly since the mid-1990s. China and the EU-15 are the next-lar gest suppliers, each with over 12% of Japan’s agricultural imports (USDA). This study focuses on a portion of Japa n’s imports which include orange, grapefruit, other citrus, apple, pineapple and grape juices. Orange, grapefruit, apple and grape juices account for 86% of fruit jui ce imports on a value basis (JETRO). The leading exporters of orange and grapefruit juices to Japan are Brazil and the U.S., respectively. The U.S. is also a leading e xporter of grape and appl e juices while Thailand and Israel are the leading exporters of pinea pple and other citrus ju ices, respectively. Background Following the deregulation of imports of appl e, grapefruit, and pineapple juices as of April 1990 and that of orange juice as of April 1992, the import penetration ratio (the fraction of income spent on imports or the increase in the extent of consumption of imports) of processed fruits into Japan has increased (JETRO). Furthermore, Japan is undergoing a profound change as a result of its aging population. Japan's statistical agency has measured a decline in population growth that is about to become an absolute decline, and population shrank for the firs t time in 2006 and will gradually fall for a

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2 number of years thereafter. The impact of this demographic change on the demand for fruit in Japan is an empirical question, sin ce either the aging affluent consumers may increase consumption of fruits to stay hea lthy or demand may decrease with the absolute decrease in population size. In either case, the increase of import pe netration in the face of an aging population and declining populat ion growth will lead to an increased competition among exporters. The purpose of this study is to assess the competitiveness of the world’s largest exporters of fruit juice into Ja pan through the analysis of market structure. The analysis of market structure in marketing is concerne d with identifying closely competing brands of the same product (Clements and Selvanatha n, 1988). Consumption theory is amenable to the analysis of market st ructure in international market s through demand analysis. The approach involves the analysis of the change in marginal ut ilities of a certain product due to a change in consumption of a closely related product. The decrease in marginal utility of one product with an increased consumption of another product implies that the products are substitutes and are thus in a competitive market structure. Otherwise, they are not substitutes (i.e., comple ments or independent) and are thus in a non-competitive market stru cture. Substitute products can be uniform1 (close) or non-uniform. If two products are uniform substitutes, price-oriented marketing strategies and/or generic product promotion are recommended because consumers are not influenced by the country of origin of su ch products. If two products are non-uniform substitutes, consumers are influenced by the country of origin and thus exporters can exercise a monopolistic power over their respec tive products. In this case, a non-price 1 The change in the marginal utility of a dollar spent on product i is the same as that of another dollar spent on product j

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3 marketing strategy (e.g., product promotion) an d/or price reduction is recommended to increase market share. Be it uniform or non-uniform, the decision to use a particular marketing strategy depends on the price elasticity of demand for the product in question. Under a situation in which a product is a uniform substitute but price inelastic, the decision to reduce price is not advised because total revenue is redu ced when price is decreased. However, the response of demand to changes in price may be higher under the uniform substitute relationship than under the non-uniform substitute relationship. This implies that both the nature of substitution (uniform/non-uniform) and the magnitude of substitution (elasticities) are important in international tr ade since they have diffe rent implications to exporters for marketing strate gies such as market promotion, product differentiation as well as a product supply plan (expansi on or contraction of supply). Most empirical studies have pursued the estimation of conditional demand functions in isolation without testing for the nature of substitution within a product group, and the nature and magnitude of subs titution between product groups. However, conditional demand parameters thus estimated ar e rarely of interest for policy analysts because the appropriateness of marketing st rategy depends on the relationship between products within the same product group and across different product groups. If, for example, the relationship between products within the same product group is uniform, the appropriate marketing strate gy is price reduction b ecause consumers view those products as homogenous. If, however, the products in the group are non-uniform, product promotion is recommended because consumers can pay a different price since they view them as differentia ted products. Furthermore, si nce the optimal allocation of

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4 expenditure to products in a ny one partition may depend on prices of products outside that group in a uniform or non-uniform fashi on, the failure to consider the nature and magnitude of substitution between products in different products groups may misguide marketing strategists. For example, the effect of a change in price of Chinese apple juice on the demand for Brazilian may be the same as that on the demand for Florida orange juice. The marketing strategy that is appropria te for this situation is different from the situation in which the effect of a change in the price of Chinese apple juice on the demand for Brazilian orange juice is different from that on the demand for Florida orange juice. To be useful for policy applications in terms of designing an effective marketing strategy, the demand for fruit juices in this study is estimated under di fferent scenarios of market structures consistent with consumer’s preference structure. Objectives The objectives of this study are the following. (1) To characterize the trend and pattern of the world fruit production, trade and consumption. (2) To identify the market structure of fruit juices imported into Japan by estimating a differential consumer demand system. (3) To assess the competitiveness of the worl d’s largest exporters of fruit juice into Japan. (4) To simulate the impact of changes in population growth on the growth rate of demand for fruit juices by country of origin. In order to identify the market structur e of fruit juices in Japan, two hypotheses are tested. These are block independ ence/uniform substitute and block-wise dependence/uniform substitute hypotheses.

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5 Hypotheses Block Independence/Uniform Substitute Hypothesis The hypothesis of block independence/uniform substitute states that there is no change in marginal utility of a dollar spent on a product in one product group caused by an extra dollar spent on anothe r product in another product group. But, the change in the marginal utility of a dollar spent on a pr oduct in one product group caused by an extra dollar spent on another product in the same pr oduct group is the same for all pairs of products in that group. This hypothesis represents the ma rket structure of block independent (direct competition) with uniform substitution such that a change in the price of a product in one group (e.g. orange juice group) does not affect the demand for another product in another group (e.g. apple juice group) But, the change in the price of a product in one group (e.g. orange juice group) uniformly affects the demand for another product in the same group. The failure to reject the null hypothesis implies that exporters of one fruit juice group don’t have to worry about the change in price of products that belong to other juice groups because competition occurs only be tween products of the same product group or the same products differentiated by country of origin. Furthermore, exporters of products that belong to the same product group can only compete by reducing price (i.e. use a price-oriented marketing strategy and/or ge neric product promotion) because under such circumstances consumers are not influenced by the country of origin of the product, since they perceive products from di fferent countries as homogenous. Brand promotion is not recommended because brand promotion for a uniform substitute product is technically a generic promotion. For example, if Florid a orange juice is a uniform substitute to

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6 Brazilian orange juice, promoting Florida ora nge juice may rather help raise the sales of Brazilian orange juice. In summary, if two products are uniform, only a slight decrease in price makes a big difference in sales, implying that the market of uniform substitute products is very competitive. This may lead firms to merge so that they will be able to exercise a monopolistic power. Block-wise Dependence/Uniform Substitute Hypothesis The hypothesis of block-wise dependen ce/uniform substitute hypothesis states that the change in the marginal utility of a dollar spent on a product in one product group caused by an extra dollar spent on another prod uct which belongs to a different product group is the same for all pair s of products that belong to the two product groups. Also, the change in the marginal utility of a dollar spent on a product in one product group caused by an extra dollar spent on another prod uct in the same product group is the same for all pairs of products in that group. This hypothesis represents the market structure of block-wise dependent with uniform substituti on such that a change in the price of a product in one group (e.g. orange juice group) affects the demand for another product in another group (e.g. apple juice group) in a sim ilar fashion. Furthermore, the change in the price of a product in one group (e.g. or ange juice group) uniformly affects the demand for another product in the same group. The failure to reject the null hypothesis implies that exporters of one fruit juice group need to watch the change in price of products in other juice groups because competition occurs between products of diffe rent product groups. Since the competition between products in different groups occurs in a similar fashion, a slight change in price

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7 of one product in one group will significantly affect the demand for products in other groups. Furthermore, exporters of products that belong to the same product group can only compete by reducing price because under such circumstances consumers are not influenced by the country of origin of the product, since they perc eive products from different countries and product groups as homogenous. In summary, if two products are uniform within and across product groups, only a slight decrease in price make s a big difference in sales, im plying that the exporters of products that belong to different product groups is very compe titive. Hence, exporters of products that belong to differe nt product groups should pay close attention to the price behavior of either product because only a slight change in price of one juice group significantly affects the sales of another juice group. Based on results of the test of the ab ove hypothesis, the study will identify the market structure of Japan’s fruit juice market. This will allow analyzing the competitiveness of countries exporting fruit juic es to Japan, and drawing implications in terms of marketing strategies. Results will be useful for providing a structure for marketing research on closely related produc ts and identifying marketing strategies involving price reduction, product differe ntiation and market promotion. Outline The dissertation is organized as follows. Chapter 2 presents the global fruit production, trade and consumption. In this ch apter, the trend, patte rn and quantity of production, trade and consumption of ma jor players are investigated. Chapter 3 presents the theoretical sec tion in which the common approaches in import demand analysis and the different dema nd models are reviewed. The chapter also

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8 derives the different versions of the Rotterd am model used for empirical estimation and tests the hypothesis presented in chapter 1. Chapter 4 presents the empirical model and the estimation procedure. This chapter includes (1) the systems of equations that are empirically applied to statistical data (2) the procedures that n eed to be followed to estimate the models (3) the source of data and analytical methods. Chapter 5 presents the results and disc ussion. This chapter discusses (1) the model that best describes the import data of fruit juices (2) the expenditure and price elasticities estimated from the selected model (3) results of simulation about the effect of the decline in population growth on the gr owth of demand for fruit juices. Chapter 6 presents different market stru cture scenarios and compares the results of these different market structures with the results of chapter 5. Finally, chapter 7 summaries the results and draws conclusions. Based on the conclusions, implications are drawn.

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9 CHAPTER 2 GLOBAL PRODUCTION, TRADE AND CONSUMPTION OF FRUIT This chapter presents a descripti on of global fruit production, trade and consumption. Both citrus and non-citrus fru its are included. The ci trus fruits include orange, grapefruit, a nd lemons and limes while the noncitrus fruits include apples, grapes and pineapples. Data for this report come mainly from the website maintained by the Food and Agricultural Organization (FAO). Global Fruit Production Citrus (Citrus L.) is one of the world’s most important fruit crops commercially grown primarily between the latitudes 40N to 40S (University of Pretoria). According to the University of Pretoria, Yunnan provin ce in south-central China may be the center of origin due to the diversity of species f ound, and the network of rivers in this area which could have provided “on r oute dispersal” to the south. From there, they slowly spread to northern Africa mainly through migr ation and trade. Citrus spread throughout Europe during the Middle-Ages and were th en brought to the Americas by Spanish explorers. Worldwide trade of citrus fruits didn't appear until the 1800s and trade in orange juice developed as late as 1940. C itrus production in Florida dates back to the colonization of the state by the Spaniards in the 15th century (Spreen et al. 2006). Today, the major types of edible citrus include ci tron, sour orange, sweet orange, lime, lemon, shaddock (pomelos), grapefruit, mandarin, and kumquat. The world’s largest producers of citrus fruits are Brazil, China, U.S. and Mexico whose combined production accounted for half of the world’s total in 2005. During the

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10 same year, Brazil’s production accounted fo r the highest proportion (19%) followed by that of China (15%), U.S. (10%) and Mexico (6%) of the world’s total (Table 2.1). In terms of area, China, Brazil, Nigeria and Me xico rank first, sec ond, third, and fourth, respectively, accounting for about 23%, 12% a nd 10% and 7% of the global citrus area harvested in 2005, respectively. During the same year, the world’s highest yield per ha was obtained in Turkey, Syria, S. Korea and U.S., each producing about 26 Mt per hectare. The productivity of citrus in Chin a as measured by yield per ha is one of the lowest in the world (FAO, 2005). Table 2.1 Global citrus production, area ha rvested and yield per hectare, 2005 Country Production(MT)% Yield (MT/Ha) Area (ha) % Brazil 20,142,100 19 Turkey 26.7 China 1,714,300 23 China 16,019,500 15 Syria 26.3 Brazil 930,379 12 U.S. 10,317,200 10 S. Korea 26.2 Nigeria 730,000 10 Mexico 6,475,411 6 U.S. 26.0 Mexico 523,505 7 Spain 4,867,300 5 Guatemala24.7 U.S. 397,080 5 India 4,750,000 5 Palestine 24.5 India 264,500 3 Italy 3,836,793 4 Israel 23.7 Spain 240,759 3 Iran 3,825,000 4 Cyprus 23.2 Iran 232,500 3 Nigeria 3,250,000 3 Australia 22.8 Pakistan 185,400 2 Egypt 2,797,600 3 Italy 22.5 Italy 170,338 2 Total 78,801,620 74 Total 5,388,761 70 World 105,431,984 100World 13.9 World 7,605,363 100 (Source: FAO, 2005) During the last four decades, global citrus production showed a period of sustained growth, primarily due to expansion of cultivation (Figure 2.1). Over the same period, the world citrus production increased more than four fold from 24,999,430 Mt to 105,431,984 Mt, growing at an average annual rate of 1.5 % (Figure 2.1). The rate of growth could have been higher, were it not fo r the occurrence of fr eezes in Florida in the 1980s. Both bearing tree numbers and produc tion declined by 40% between 1975 and 1986 as freezes destroyed a la rge portion of the industry in Lake, Orange, and Pasco

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11 counties of the state of Florida (Spreen, et al 2006). However, the increase in prices caused by the slowed production in Florida stimulated the de velopment of new plantings (Spreen et al.). Given the la g between price signals and outpu t changes, an increase in production occurred in the 1990s and 2000s (Figure 2.1). Until the early 1980s during which freezes devastated the Florida citrus production, the U.S. was the world’s largest produ cer of citrus. During the decade of the 1980s, Brazil became the largest citrus producer in the world and the first, and almost exclusive, orange juice exporting country (UNC TAD). Brazil’s citrus production grew at an average rate of 4.5% over the last four decad es while that of the U.S. grew at 0.6%. 0 20,000,000 40,000,000 60,000,000 80,000,000 100,000,000 120,000,000 196119651969197319771981198519891993199720012005 World Brazil China Mexico U.S. Figure 2.1 Citrus productions (M T) of major producers, 1961-2005 Over the last few years, the Chinese c itrus production experienced a fast growth (over 3%) over the last few decades (parti cularly in the 1990s) mainly due to the expansion of cultivation, thus emerging as the second largest producer of citrus fruits in the early 2000s (Figure 2.1).

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12 The Production of Oranges, Lemons and Limes, and Grapefruits and Pomelos Oranges The major citrus fruits are oranges, lemons and limes, and grapefruit and pommels, whose combined production accoun ted for 55% of the world’s total citrus in 2005 (FAO, 2005). Among citrus fruits, orange is the most important fruit, accounting for about 43 percent of the world’s citr us production in 2005. The world’s largest producers of oranges are Brazil and U.S, w hose combined production in 2005 was 44% of the world’s total orange production with Brazil alone accounting for 30% of the world production. The U.S. produced 14 percent of th e world production in 2005 (Table 2.2). The top ten countries produced 76 percen t of the world production in 2005. Table 2.2 Global production of oranges, grapef ruit and pommels, and lemons and limes in 2005 Oranges Grapefruit and Pommels Lemons & Limes Country Production % Country production % country production % Metric tons Brazil 17,804,600 30 U.S. 914,440 25 Mexico 1,824,890 15 U.S. 8,266,270 14 China 443,000 12 India 1,420,000 11 Mexico 3,969,810 7 Mexico 257,711 7 Argentina 1,300,000 10 India 3,100,000 5 Israel 250,000 7 Iran 1,100,000 9 Italy 2,533,535 4 Cuba 226,000 6 Brazil 1,000,000 8 China 2,412,000 4 S. Africa 212,348 6 U.S. 745,500 6 Spain 2,149,900 4 Argentina 170,000 5 Spain 734,300 6 Iran 1,900,,000 3 Turkey 150,000 4 China 634,500 5 Egypt 1,789,000 3 India 142,000 4 Italy 609,435 5 Indonesia 1,311,703 2 Tunisia 72,000 2 Turkey 600,000 5 Total 45,236,818 76 Total 2,837,499 77 Total 9,968,625 79 World 59,858,474 100 World 3,667,862 100 World 12,554,879 100 (Source: FAO, 2005) From 1961 to 2005, global orange production increased almost four fold from 15,946,492 Mt to 59,858,474 Mt, growing at an av erage annual rate of 1.4 % (FAO. 2005). Most of the growth was accounted for by developing countries primarily in South America but also in Asia and to a lesser exte nt in Africa. In S outh America, the volume of production expanded consider ably in Brazil and Mexico (Figure 2.2). In Asia, production expanded significantly in China, India and Pakistan and Iran. Orange

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13 production in China, Brazil and Mexico incr eased at an average annual rate of 4.3%, 2.7% and 1.4%, respectively over the same period (FAO, 2005). Spreen and Brown (1995) noted that freezes in Florida in the 1980s provided a major impetus to the expansion of orange production in Brazil. The average orange production of Brazil and Mexico in the 1990s was 50 percent and 60 perc ent larger than the average production in the 1980s, respectively (FAO, 2005). Figure 2.2 Orange productions (M T) of major producers, 1961-2005 Lemons and limes Lemons and limes are the second most important citrus crops accounting for about 9 percent of the global citr us production in 2005. Like the case with oranges, there has been a si gnificant increase in producti on of lemons and limes through expansion of cultivation. Over the last four decades, the global lemon and lime production increased more than five fo ld from 2,625,865 MT in 1961 to 12,554,879MTt in 2005, growing at the average rate of 1.6% per annum (FAO, 2005). Most of the growth was accounted for by Mexico, I ndia and Argentina (Figure 2.3). 0 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 196119651969197319771981198519891993199720012005 Brazil China Mexico U.S.

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14 Figure 2.3 Lemon and lime production (MT) of the top four producers, 1961-2005 The world’s largest producers of lem ons and limes are Mexico, India and Argentina whose production in 2005 was 15%, 11% and 10% of the world production, respectively. Other major producers of lemons and limes include Spain, China, Italy and Turkey, each accounting for about 5 percent of the world’s tota l in 2005 (Table 2.2). The top ten countries produced about 80 per cent of the world’s total in 2005. Until the mid-1980s, the U.S. was the world’s largest producer of lemons and limes (Figure 2.3). Between the mid-1980s and mid-1990s, the U.S. production slowed while that of Mexico continued to rise particularly in the mid-1990s during which it emerged to be the world’s largest producer of lemons and limes. Over the last four decades, Mexico’s production grew at an aver age annual rate of 2.3% while that of U.S. grew at 0.4%. In 2005, U.S. produced 6% of the world’s total, which is way below the production of Mexico, India, Argentina, Ira n and Brazil (Table 2.2). Over the same period, India and Argentina al so increased their production and emerged as the second 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 2,000,000 196119661971197619811986199119962001 Argentina India Mexico U.S.

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15 and third largest producers of lemons and limes, respectively (Table 2.2). India and Argentina increased their production at an average annual rate of 1.4 and 2.8%, respectively. Grapefruit and pommels Grapefruit and pommels are the third most important citrus crops, accounting for about 3.5% of the wo rld citrus production. Over the last four decades, the global grapefruit and pommels production increased by 73% from 2,120,896 MT in 1961 to 3,667,862 MT in 2005, growing at average rate of 0.8% per annum (Figure 2.4). Figure 2.4 Grapefruit and pomelos production (MT) in the U.S. and China, 1961-2005 The growth rate of grapefruit and pome los production over the last four decades was modest compared to the growth rate of ot her citrus fruits. This is due to the slow growth of grapefruit produc tion in the U.S. On average, grapefruit and pomelos production in the U.S. grew at 0.2% per annum. Over the same period, China’s production grew at a 3.8%. 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 196119661971197619811986199119962001 China U.S.

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16 U.S. is the world’s larges t producer with 25% of the world’s total (Table 2.2). China is the second largest producer with 12 pe rcent of the world’s total. Mexico and Israel are also important producers, each pr oducing about 7% of the world’s total. The top ten countries produced 77 percent of the world production in 2005 (Table 2.2). The Production of Grapes, Apples, and Pineapples Grapes Among non-citrus fruits, grapes are th e most important non-citrus fruit in terms of production. The major producers of gr apes are Italy, France and the U.S. whose production in 2005 accounted for 14%, 10% and 10%, respectively (Table 2.3). China and Spain are also important producers of grapes, each accounting for about 9 percent. The top ten countries produced about 71 pe rcent of the world’ s total in 2005. Table 2.3 Global production of appl es, grapes, and pineapples, 2005 Apples Grapes Pineapples Country production % Country production % Country production % Metric tons China 25,006,500 39 Italy 9,256,814 14 Thailand 2,050,000 13 U.S. 4,254,290 7 France 6,787,000 10 Philippine 1,800,000 11 Turkey 2,550,000 4 U.S. 6,414,610 10 China 1,460,000 9 Iran 2,400,000 4 Spain 5,879,800 9 Brazil 1,418,420 9 Italy 2,194,875 3 China 5,698,000 9 India 1,300,000 8 France 2,123,000 3 Turkey 3,650,000 5 Nigeria 889,000 6 Poland 2,050,000 3 Iran 2,800,000 4 C. Rica 725,224 5 Russia 2,050,000 3 Argentina 2,365,000 4 Mexico 720,900 5 Germany 1,600,000 3 Chile 2,250,000 3 Indonesia 673,065 4 India 1,470,000 2 Australia 1,834,000 3 Kenya 600,000 4 Total 45,698,665 72 Total 46,935,224 71 Total 11,636,609 73 World 63,488,907 100 World 66,533,393 100 World 15,886,647 10 0 (Source: FAO, 2005) The production of grapes in the U.S. has b een growing steadily, while that in Italy and France appears to be declining since th e mid-1990s (Figure 2.5). Unlike the case with citrus fruits, the increas e in global grape pr oduction is modest. It increased by a little more than 50% over the last four decad es, growing at an average rate of 0.2% per annum (FAO, 2005). This is due to the dec line of production in the two major producing

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17 countries (France and Italy) whose production declined at an average rate of 0.4% and 0.2%, respectively. Figure 2.5 Grape productions (MT) of the top three countries, 1961-2005 Apples Apples are the second most important non-citrus fruits. Over the last four decades, the world apple production in creased nearly four fold from 17,053,651 MT in 1961 to 63,488,907 MT in 2005, growing at an average rate of 1.2% per annum. The world’s largest producers of apples are China and the U.S. China produced 39% of the world’s total in 2005. U.S. production accounts for 7% of the world’s total (Table 2.3). Until the early 1990, the U.S. was the larges t producer of apples (Figure 2.6). Since then, China has become the world’s largest producer of apples. On average, China’s apple production grew at the rate of 4.7% per annum while that of the U.S grew at 0.7% per annum over the last four decades. The growth of apple production in China is explained by an increase in area expansion. 0 2,000,000 4,000,000 6,000,000 8,000,000 10,000,000 12,000,000 14,000,0001961 1964 1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 France Italy U.S.

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18 Figure 2.6 Apple productions (MT) in the U.S. and China Pineapples Pineapples are the third most importa nt non-citrus fruit. Over the last four decades, the global pin eapple production increased almo st four fold from 3,831,437 MT to 15,886,647 MT at an average rate of 1.4% per annum. Until the early 1980s, U.S. was the world’s largest producer of pineappl es (Figure 2.7). Since then, its production has declined so that it is not in the list of the top 10 pr oducing countries (Table 2.3). Over the last four decades, the U.S. pr oduction declined at an annual rate of 1.3 percent per annum (FAO, 2005). Currently, th e world’s largest producers of pineapple are Thailand, and the Philippines, accounti ng for 13% and 11% of the world’s total, respectively (Table 2.3). They increased th eir production over the last four decades at 2.8% and 2.5% per annum, respectively. China and Brazil have also emerged as the third and fourth largest producers, ea ch producing about 9% of the world’s total. The top ten countries produced 73 percent of the world’s total in 2005. 0 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 30,000,000 196119661971197619811986199119962001 China U.S.

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19 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 4,000,000 196119651969197319771981198519891993199720012005 Brazil China Philippines Thailand U.S. Figure 2.7 Pineapple productions (M T) of major producers, 1961-2005 Global Fruit Trade International trade in fruits and vegetabl es has expanded more rapidly than trade in other agricultural commodities, especia lly since the 1980s (Huang, 2004). This is attributed to rising incomes, falling tran sportation costs, improved technology, and evolving international agreements. Citrus frui ts rank first in international fruit trade in terms of value (UNCTAD). As a result of tr ade liberalization and t echnological advances in fruit transport and storage, the citrus fru it industry is becoming more global in scope. The major players in the global trade of fru its and vegetables are the E.U, the North American Free Trade Agreement (NAFTA) countries, China and Japan. Exports of fresh citrus fruits represent r oughly 10% of total citr us fruit production (UNCTAD). The international trade on fruits and vegetables is dominated by processed forms. According to UNCTAD, international trad e in citrus juice only started to increase in the 1940s, after World War II, when citrus processing technologies were invented and developed. The advent of frozen concentrat ed orange juice (FCOJ) after World War II

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20 provided a new impetus for the citrus indus try (Spreen et al. 2006). Citrus fruit processing accounts for approximately one thir d of total citrus fr uit production. More than 80% of it is orange processing, mos tly for orange juice production. The major feature of the world market for orange ju ice is the geographical concentration of production. There are only two main players: the State of Florida in the U.S. and the State of Sao Paulo in Brazil. Production of orange juice between these two players account for over 80% of world orange juic e production (Spreen et al. 2006). The major difference between them is that Brazil exports 99 per cent of its production while 90 percent of Florida’s production is cons umed domestically and only 10 percent is exported (UNCTAD). The citrus industry in Florida currently faces two major challenges (citrus canker and citrus greening) and increasing urbanization in the state, which has resulted in increasing land values (Spreen et al. 2006). Nonetheless, the Florida citrus industry will continue to be an important supplier of citrus products to both the U.S. and world market. International trade in orange juice takes place in the form of frozen concentrated orange juice (FCOJ), in order to reduce the volume used, so that storage and transportation costs are lower. Spreen et al (2006) notes that FCOJ provided a means to (1) store orange juice from the harvest season into other time periods, (2) provided a way to produce a product with a consistent taste, and (3) offered new modes of transport and new retail package alternatives to the consumer. The E.U. is the largest importer of ora nge juice, accounting for over 80% of the world orange juice imports (UNCTAD). The other major importers of orange juice are Canada and Japan. Most of imports by the E.U. and Japan come from Brazil. Brazil’s

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21 exports of orange juice to Japan account for over 70% of Japan’s total import of orange juice (Table 2.4). In North America, the U. S. and Canada consume orange juice mainly from Florida, while a small quantity of impor ts comes from Brazil. The U.S. is the leading exporter of apple juic e, grapefruit juice and grape juice to Japan. Thailand and Israel are the leading exporters of pineapple juice and other citrus, respectively. The U.S. share of grapefruit import is significant. Howe ver, the slow growth rate of grapefruit production in U.S. implies that the U.S. is un likely to continue as a dominant supplier of grapefruit juice. The same is true with ap ple juice since the apple production growth rate in U.S. is slower relative to other countries such as Chin a. Currently, the U.S. is a dominant supplier of apple jui ce to the Japanese market, fo llowed by China and Austria. With regard to grape juice, the U.S. is s till the dominant supplie r and is expected to dominant the market since its production has be en growing while that of France and Italy, which are the world’s largest pr oducers, has been declining. Global Fruit Consumption Higher income, urbanization, demographi c shifts, improved transportation, and consumer perceptions regarding quality and safety are changing global food consumption patterns (Huang, 2004). Diet diversificati on and increasing demand for better quality products have increased imports of high-value and processe d food products in developed countries. Fruits are mainly consumed in industrialized countries, not only because consumers in these countries have high income levels but also because they have increasing concerns about healthy eating. However, the growth of per capita consumption of fruits in these countries s eems to be stagnating. Over the period 1980 to 2003, the per capita consumption of citrus fr uits (oranges, grapefruit and lemons and limes) in these countries grew at an aver age rate of one percent per annum.

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22 Table 2.4 Fruit juice imports to Japan by country of origin product Exporter % Brazil 72.4 U.S. 23.7 Orange juice Australia 1.4 U.S. 22.4 China 18.9 Apple juice Austria 18.6 U.S. 87.1 Israel 9.6 Grapefruit juice Australia 2.4 U.S. 46.9 Brazil 14.1 Grape juice Argentina 11.7 Thailand 42.4 USA 28.6 Pineapple juice The Philippines 27.6 Israel 40.5 Italy 21.8 Other citrus juice Argentina 13.9 (JETRO) Among 26 industrialized countries, the U.S. and Canada are the largest consumers of orange and mandarins followed by the EU. In fact, some E.U. countries such as Ireland, the Netherlands and Greece consume more oranges than do the U.S. and Canada on a per capita basis. The average per capit a consumption of oranges and Mandarins in industrialized countries over the period 1990 to 2003 is 29 kilograms while that of grapefruit and lemons and limes is 3.0 and 3.6 kilograms, respectively (Table 2.5). Japan’s consumption of both citrus (except gr apefruit) and non-citrus fruits is small compared to other industrialized countries. The average annual per capita consumption of oranges and apples in Japan over the pe riod 1980 to 2003 is about 14 and 12 kilograms, respectively, while those of grapes and grapefruit are 2.8 and 2.5 kilograms, respectively (Table 2.5).

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23 Table 2.5 Per capita consumption of fruits in industrialized and developing countries Fruits Developing countries Industrialized Countries E.U. Canada Japan U.S. Orange and mandarins 8.00 29.23 27.5246.28 13.80 39.87 Grapefruit 0.32 2.91 2.17 4.05 2.49 4.12 Lemons and limes 1.25 3.59 3.78 2.60 0.84 5.26 Apples 4.67 20.3 24.8218.82 11.58 21.02 Grapes 2.20 7.60 8.67 10.19 2.79 8.18 Pineapples 2.01 3.61 1.97 2.61 1.43 7.01 (Source: FAO, 2005) Japan’s domestic supply of pineapples is heavily dependent on imports. In 2003, 95% of the domestic supply of pineapples ca me from imports (FAO, 2005). Japan is also heavily dependent on imports for its supply of le mons and limes. In terms of apples and grapes, the significance of imports has been increasing since the last decade during which the deregulation was in effect.

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24 CHAPTER 3 THEORETICAL MODELS Demand Approaches Approaches common in the literature of import demand analysis involve use of consumer demand theory and production theor y. The consumer demand approach treats imports as final products that directly ente r a consumer’s utility function (Schmitz, A. and Seale, J. 2002) while the production theory treats imports as inputs (Washington and Kilmer, 2002). The first approach enables th e derivation of the traditional consumer demand and labor supply functions from utili ty maximization, while the second approach enables the derivation of de rived/input demand and output supply functions from profit maximization or cost minimization. The fact that output supply functions ar e derived in the production approach while labor supply functions are de rived in the consumer demand approach marks one major difference between the two approaches. Another major difference between the two approaches is that the parameter estim ates of unconditional consumer demand and unconditional input demand are di fferent. However, similar parameter estimates can be obtained for the conditional consumer de mand and derived demand for inputs. Furthermore, under the assumption of the consta nt percentage of retail price type of marketing margin, the demand for any given qua ntity of product is equally elastic (or inelastic) with respect to pr ice at all market levels (Goodw in, 1994). This implies that conflicts of interest between the producer leve l and subsequent market levels are reduced. The constant percentage of retail price marke ting margin is fairly typical for products for

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25 which the marketing process involves fixed investments and substantial economies of scale (Goodwin, 1994, pp. 292). Production Approach In the production approach, two allocati on decisions, one involving outputs and another involving inputs, are made. These two decisions can be made successively or simultaneously through a two-step profit maxi mization or one-step or direct profit maximization procedure yielding a system of output supply and input demand functions (Washington, 2000). They are made successively in such a way that given output and input prices, first the output manager deci des on the quantity of output, and knowing the quantity of output planned to be produced, the input manger decides on the quantity of inputs required to produce the planned output. The simultaneous decisions are made by one manager such that the input and output deci sions are not independent of each other. In this case, since the input demand and out put supply functions ar e not independent of each other and that th eir error terms are correlated (Laitinen, 1980), the input demand function can not be estimated independently of the output supply function and vice versa. Once the output supply and conditional i nput demand are estimated, the unconditional demand parameters can be derived from the parameter estimates of the two functions (Washington and Kilmer, 2002). The input allocation decisions that involve the use of conditional input demand functions can be implemented in stages/hie rarchies (Theil, 1980b). That is, total expenditure is first allocate d over broader groups of inputs and then group expenditures are allocated over individual inputs within each group. The two-st age input allocation decision of the production approach is compar able to the two-stag e utility maximization of consumer demand approach (Figure 3.2). The consumer demand approach can yield a

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26 system of group consumer demand and condi tional demand functions from which the parameter estimates of the unconditional de mand function can be derived. As noted earlier, the unconditional demand parameters t hus estimated are not the same as those derived from the system of output supply a nd conditional demand functions generated in the production approach di scussed earlier. However, the parameter estimates of the input demand f unction (P1), group demand function (P2) and condi tional input demand (P3) in Figure 3.1 are the same as that of the corresponding functions in Figure 3.2. That is, the parameter estimates of the input demand function (P1) are the same as that of the unconditional consumer demand (C1); the parameter estimates of the group i nput demand functions (P2) are the same as that of the group consumer demand functions (C2); and that the parameter estimates of the conditional input demand functions (P3) conditional consumer demand functions (C3) in Figure 3.2. Figure 3.1 A two stage profit maximization 2-Stage profit maximization Output supply function Input demand function (P1) Group input demand function (P2) Conditional input demand function (P3)

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27 Figure 3.2 A two-stage utility maximization Although the two approaches pr ovide the same empirical es timates with regard to the conditional demand, and that the demand for any given quantity of product is equally elastic (or inelastic ) with respect to price at all market levels unde r the assumption of the constant percentage of retail price ty pe of marketing margin (Goodwin, 1994), the production approach does not seem to lend itself to a theoretically consistent investigation of demand relationships am ong narrowly defined import products because of their independence. It may be realis tic for broadly defined groups of imported products. For example, Theil (1980b) applie d the production approach to broad imported products such as food, crude materials, semi -manufactures, finishedmanufactures under the assumption of input independence. Ho wever, when it comes to narrowly-defined products such as fruit juices, it does not seem conceptually defensible and practical to apply the production approach simply because the importing firm’s production function of an imported fruit juice is indepe ndent of other imported juices. Let the production function of a narrowly -defined import product such as orange juice be given by 2-Stage utility maximization Labor supply function Unconditional demand function (C1) Group consumer demand function (C2) Conditional consumer demand function (C3)

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28 (3.1) 1 1 11 1,..., ,...,m m g gx h x h x h h h where gh is a production function of each import product or input; gx is the import product or input. The groups run from 1 tom; the number of inputs in each group is only one to indicate that each import is a unique input that produces a unique output; the number of inputs in group g isgn. The total number of products ismn n ...1. Equation (3.1) implies that the elasticity of output with respect to each input is independent of all other inputs; henc e, all cross effect s are zero. Let .1h represents the production function of, say, Florida orange jui ce. This function does not have the orange juices of other countries as inputs because each individual input yields its own unique output. Hence, the constrained cost mini mization procedure will not yield a demand function that consists of the prices of other orange juices. As a result, theoretically we can’t investigate the relationship between Fl orida orange juice and other juices. The presence of input independence in the production function precludes us from investigating the substitution between imports of orange juice from different countries and competition among exporting countries. Consumer Demand Approach The present study chooses the consumer approach over the production approach since it allows inves tigating the nature of demand relationship among imported products and competition among different exporters. Consumption theory is amenable to analyze the market structure of commodities in fru it juice market. The theory involves the analysis of the change in ma rginal utilities of a certai n product due to a change in consumption of a closely related product. The changes in marginal utilities are related to the price substitution terms of demand functions.

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29 Starting with a traditional utility functi on that is assumed to be well behaved (twice differentiable, increasing in its argumen ts, strict concavity), we can derive the Marshallian demand functions. They satisfy th e properties of adding up, symmetry of the cross price derivatives, homogeneous of de gree zero in prices and expenditure, and negative semi-definiteness in co mpensated price responses. Utility Maximization The maximization of a utility function q u subject to a budget constraint q p m is set up in a constrained optimizati on problem using the Lagrange method as (3.2). q p m q u q L where q is the vector of consumption products; is the Lagrange multiplier which can be interpreted as the marginal utility of income; m is total expenditure; p is the vector of prices. The first order conditions are (3.2.1) 0 p q u q q L and (3.2.2) 0 q p m q L The first order conditions imply that the ma rginal rate of substitution should equal the price ratio at the optimum, which in turn im plies that the internal rate of trade should equal the external or market rate of trade. That is, a consumer will adjust purchases of products until their willingness to trade one fo r the other just matche s the rate at which they can be traded in the marketplace, as given by the ratio of prices.

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30 From the first order conditions, we deri ve the demand functions for all products i and the marginal utility of income function as (3.3) p m f qi i, and (3.4) p m The choice of a functional form is at the interface of ec onomic theory and the data. In other words, the functional form should sa tisfy the economic propr ieties and fit to a statistical data satisfactorily. Two steps are followed in demand specification (Fousekis and Revell, 2000). First, behavi oral assumptions are imposed wh ich lead to a cost or to an indirect utility function. Second, a functional form is selected. Parsimony and flexibility are desirable properties considered in the selection of functional forms. The most common and parsimonious dema nd model, which dominated the import demand literature in the past, was the Armington trade model. The application of the Armington model to trade data dates back to the late 1970s and became popular in the 1980s and 1990s (Grennes et al. 1977, Sarris, 1981; Sarris, 1983; Abbot and Paarberg, 1986; Babula, 1987; Alston et al. 1990; Duffy et al. 1990; Haniotis, 1990). However, the Armington trade model came to be increasingly criticized on both conceptual and empirical grounds. The hypothesis of separability and homotheticity may not be supported by import data (Alston, et al. 1990) Traditional methods of implementing the Armington trade model result in theoretically and statistically inconsistent parameter estimates (Davis and Kruse, 1993). Consequently, system-wide demand models such as the Rotterdam model and the Almost Ideal Demand Systems have come to be popular in the contemporary import

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31 demand literature (Clements and Theil, 1978, Le e et al. 1990; Seale et al. 1992; Zhang et al. 1994; Yang and Koo, 1994; Schmitz a nd Wahl, 1998; Fabiosa and Ukhova, 2000; Soshnin et al. 1999; Schmitz and Seale, 2002; Washington and Kilmer, 2002). The choice among different system-wid e demand specifications (e.g., the Rotterdam model versus AIDS model) is base d on statistical tests (B rown et al. 1994). Economic theory does not sugge st a criterion to choose ex ante between demand models. Barten (1993) demonstrates that the Rotterd am and AIDS models are special cases of a general demand model so that nested tests can be applied to choose either the Rotterdam or AIDS model or the hybrid of these two m odels (Central Statistical Bureau (CBS) and National Bureau of Research (NBR)). In the field of consumer demand analysis the issue of selecting among competing functional forms has been addressed in a numbe r of recent studies (Eales et al. 1997; Lee et al. 1994, Barten; 1993.; Schmitz and S eale, 2002; Weatherspoon and Seale, 1995). They have demonstrated that a family of competing systems can be generated through alternative parameterizations of Theil’ s differential system (Theil 1980). However, separability is an issue in es timating system-wide models (Seale, 1996). The AIDS model is not globally separable and only becomes separable locally under stringent conditions (Lee et al. 1994). This will render multi-stage demand estimation difficult. However, it is not uncommon to fi nd the application of the AIDS model in a two-stage budgeting framework (Heien and Pick 1991; Soshnin, et al. 1999). In these two studies, the AIDS model was used for both the first and second stages. Other studies have specified a two-stage demand system by applying the LES model for the first stage and the AIDS model for the second stage (Fan, et al. 1995; Han and Wahl, 1998;

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32 Michalek and Keyzer, 1992; Ma and Rae, 2003) Gao et al. (1996) specified a two-stage demand by applying the extension of the AIDS model for the first stage and Generalized Linear Expenditure System for the second stage. The Rotterdam model, which is globally separable, has been applied in several studies to specify a two-stage demand syst em. These include Duffy (1986); Clements and Johnson (1983), Clements and Selvanatha n (1988), Brown and Lee (1997), Xao et al. (1998); E. Selvanathan and ASelvanatha (2004 ). All of these studies have used the Rotterdam model for both the first and sec ond stage in a block independent framework for different applications, mo stly of advertising. The present study prefers to use the Ro tterdam model because of its global separability. Unlike the previous studies which have applied the Rotterdam model, the present study tests different separability hypot heses. The hypotheses will be discussed in the next sections. The Rotterdam Model Following Theil (1980a, 1980b), the Rotterd am model is derived from the maximization of a general utility function or total differentiation of a general demand function. Totally differentiating (3.3) yields (3.5) j N j j i i idp p q dm m q dq 1. Expressing (3.5) in log form i i iq dq q d log yields (3.6) j j N j j i i i ip d p p q m d m m q q d q log log log1

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33 where iq d logis the log change in quantity demanded of product i and jp d log is the log change in price of product j Based on Barten’s Fundamental matr ix, the total substitution effects j ip q in (3.6) can be decomposed into specif ic and general substitution terms as (3.7) j i j i ij j iq m q m q m q m u p q where iju is the thj i, element of 1 U the inverse of the Hessian; iju is the specific substitution effect, which shows that th e corresponding component depends upon the specific relation, in terms of iju between iand j In other words, the utility obtained from product i is a function of the consumption level of product j ; m q m q mj i is the general substitution effect, which shows that all products are competing for the consumer’s budget, and j iq m q is the income effect of the price changejdpon the demand for the thiproduct. Therefore, the total substitu tion effect of a price change can be expressed as the sum of the substitution effect m q m q m uj i ij and income effect j iq m q and is known as the Slutsky equation. The component ijuof j ip q is the effect on iqof a change in jpwhen the change is accompanied by an income change so that the marginal utility of income remains unchanged.

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34 Substituting (3.7) into (3.6) and multiplying both sides bym pi/, we find (3.8) j j i j i ij N j j i i i i ip d q m q m q m q m u m p p m d m q p q d w log log log1 where iw is the expenditure share of product i defined as m q p wi i i. Multiplying out the second terms of the right-hand expression of (3.8) yields (3.9) log log log log log1 1 1 N j j j i j i N j j j i j i j N j j ij i i i i ip d q m q m p p p d m q m q m m p p p d p u p m m d m q p q d w The first term of the right-hand side e xpression of (3.9) is the marginal value share defined as (3.9.1) m q pi i i The second term of the right-hand side e xpression of (3.9) is the relative price coefficient ijv defined as (3.9.2) j ij i ijp u p m v The third terms of the right hand-side e xpression of (3.9) can be rearranged to yield the general subs titution effect as

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35 (3.9.3) j N j j i j N j j j i i N j j j i j ip d p d m q p m m m q p p d m q m q m m p p log log log1 1 1 where 1m m, which is the reciprocal of the income elasticity of the marginal utility of income The fourth terms of the right hand-side e xpression of (3.9) can be rearranged to yield the income effect of a price change as (3.9.4) j N j j i j N j j j i i N j j j i j ip d w p d m q p m q p p d q m q m p plog log log1 1 1 Substituting (3.9.1) through (3.9.4) and rearranging them yields (3.10) N j j j i j N j ij N j j j i i ip d p d v q d w m d q d w1 1 1log log log log log Rearranging (3.10) and using the constrai nt that the sum of the relative price coefficients is proportional to the marginal value sharei N j ijv 1, we find the relative price version of the Rotter dam model (3.11) and the abso lute price version of the Rotterdam model (3.12) as (3.11) P p d v Q d q d wj N j ij i i ilog log log1. (3.12) j N j ij i i ip d Q d q d w log log log1 where N j j jq d w m d Q d1log log log is the real income term; j i ij ijv are the Slutsky price coefficients;N j j jp d P1log ) (log is the Frisch price index.

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36 In order to identify the market structure underlying the importati on of fruit juices into Japan, four different versions of the Rotterdam model are derived from the relative price version of the Rotterdam Model under different hypotheses. The hypotheses which represent different market structures are block independence, block-wise dependence, and uniform substitutes. The block inde pendence and block-wise dependence hypotheses are applied to products that belong to di fferent product groups while the uniform hypothesis is applied to products w ithin the same product group. The models derived under these hypotheses in this study are block independent non-uniform substitute-Rotte rdam model, block independent uniform-substituteRotterdam model, block-wise dependent nonuniform substitute-Rotterdam model and block-wise dependent uniform s ubstitute-Rotterdam model. Block Independence Block independence is a special case of strong separability where one can group commodities into different blocks depending on so me tangible criterion. Separability is a relative concept whose fr ame of reference is some partiti on of a product set into mutually exclusive and exhaustive subsets. Blundell and Robin (2000) indicate that the idea behind separability in consum er preferences is the existe nce of “natural” groupings of related commodities that reflect the budgeti ng decisions consistent with the true preference ordering of the representative cons umer. Otherwise, empirical estimates of structural demand parameters are invalid. The usefulness of separability depends on the ability to classify products into groups which are empirically valid (Barten, 1977). The grouping of commodities into blocks is of paramount significance from a statistical point of view since it increases the degrees of freedom. However, the blocking

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37 has to be theoretically consistent and empi rically plausible. Suppose that we have N G blocks or groups denoted as GS S,...,1 such that each product belongs to exactly one group, the consumer’s preferences under block independence is represented by the sum of G sub-utility functions, each involving the quantities of only one group given as (3.13) m gmn m m gn g g nq q u q q u q q u u u ,..., ,..., ,..., ,..., ,...,1 1 1 11 11 where gu is a sub-utility function; gq is a sub-vector of q which consists of the s qi that fall underG g Sg,..., 1 The groups run from 1 tom; the number of commodities in group 1 is 1n; the number of commodities in group g is gn. The total number of products is mn n ...1. Under (3.13), the u tility obtained from the products in group g is independent of the utility of products in group h. That is 02 j iq q u However, for i and j in the same group 02 j iq q u. That is, the consumption of an extra unit of product j has an effect on the utility of product i and vice versa. Formally, the hypothesis of block independence 0H states that the change in the marginal utility of a dollar spent on the thi product gS i caused by an extra dollar spent on the thj product which belongs to a different group h g S jh ,equals zero. The alternative hypothesis states that the change in the margin al utility of a dollar spent on the thi product gS i caused by an extra dollar spent on the thj product which belongs to a different group h g S jh is different from zero.

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38 0 :2 0 j j i iq p q p u H for gS i and hS j ; h g 0 :2 j j i i Aq p q p u H for gS i and hS j ; h g Under this hypothesis, the Hessian j iq q u 2and its inverse 1 2 j iq q u becomes a block diagonal. The marginal utility of each product depends only on the quantities consumed of the products that belong to the same group (Theil, 1975). Following Theil (1975), the changes in the marginal utilities can be related to demand parameters as j ij i ijp u p m v where ijv are the relative price coefficients. When i and j belong to different product groups, ijv can be set equal to zero because iju equals zero under the assump tion of block independence. This implies that the assumption of bl ock independence represents a market structure whereby the change in the relative price of a pr oduct in one product group does not affect the demand for another product in another product group. For instance, under this market structure, we ar e hypothesizing that the change in the price of U.S. grapefruit juice does not affect the demand for Brazilian orange juice. Orange juice and grapefruit juices are in differe nt product groups. Block independent non-uniform su bstitute-Rotterdam Model. Following Theil (1980a), the block independent non-uni form substitute-Rotterdam model can be derived from (3.11) by setting ijv equal to zero for iand j that belong to different groups as (3.14) gS j j ij i i iP p d v Q d q d w log log log.

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39 Since all ijv with i and j in different groups vanished, the number of free parameters is obviously reduced. Howeve r, no product is a specific substitute or complement of any product that belongs to a different group. The demand equation of the thiproduct contains gN relative prices when it belongs to setgS. The number of free parameters depends on the number of bloc ks and the number of commodities in each block. Theil (1980) shows that with G blocks having N commodities in total and an equal number of commodities in each bloc k, the number of free parameters is G N N/ 1 5 0. Block-wise Dependence In the previous section, we have assume d that the consumer’s utility function can be additively separated into group utility f unctions. A weaker assumption is that the consumer utility function q u equals some function f rather than the sum of the group utility functions. (3.15) m gMn M M Gn G G nq q u q q u q q u u u,..., ,..., ,..., ,..., ,...,1 1 1 11 11. Unlike the case with (3.13), the utility obtained from a product in one group under (3.15) is not independent of the consumption of another product in another group. That is, for i and j in different groups, 02 j iq q u. Since we are dealing with products in each group on a block-wise basis, we are assuming th at the effect of the consumption of an extra unit of product j hS jon the marginal utility of product i h g S ig ; is the same for all pairs of products in the two product groups; i.e., th is effect is independent of i and j

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40 Formally, the hypothesis of block-wise dependence 0H states that the change in marginal utility of a dollar spent on the thi product gS i caused by an extra dollar spent on the thj product which belongs to a different group h g S jh ,equals some constantgha; i.e., this effect is independent of i and j and hence, the same for all pairs of products in the two product groups. For in stance, in the orange and apple juice groups, an extra dollar spent on either U.S. orange ju ice or Brazilian orange juice in the orange juice group has the same effect on the marginal utility of a dollar sp ent on Chinese apple juice or Austrian apple juice in the apple juice group. The utility interaction of two products of different groups in a block-wise dependence fr amework is a matter of the groups rather than the individua l products (Theil, 1980a). gh j j i iq p q p u H 2 0: for all ) ( ,h g h j g i gh j j i i Aq p q p u H 2: for all ) ( ,h g h j g i Following Theil (1975), the changes in marg inal utilities can be related to the relative price coefficients ijv as (3.16) h g h g j j h i i g h g iju u u u u u u m q p u q p u u u u m v 2 2, where gS i;hS j ; and h g Equation (3.16) shows that the cross-group term is the same for all pairs of products from different groups. Following Theil (1975) and Brown (1993), the relative price coefficients corresponding to (3.16) can be given as (3.17) j i gh ijv

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41 where ijv is the relative price coefficient; gh is a factor of proportionality which is the same for all gS i andhS j; i is the marginal expenditure share. This implies that the assumption of bloc k-wise dependence represents a market structure whereby the change in the price of a product in one group would affect the demand for another product in another product gr oup in the same fashion. In other words, the effect of a change in the price of a product in group A on the demand for another product in group B is the same for all pairs of products in the two groups. For instance, under this market structure, we are hypothesizing that the effect of a change in the price of U.S. orange juice on the demand for Israelis grapefruit juice is the same as that of Brazilian orange juice on the dema nd for U.S. grapefruit juice. Block-wise dependent non-uniform substitute-Rotterdam model. Following Theil (1980a), the block-wise dependent nonuniform substitute-Rotterdam model can be derived from (3.11) as (3.18) P P d V P p d Q d q d wh g h gh i S j j ij i i iglog log log log' where i is the marginal expenditure share; ijv is the relative price coefficient, which applies for the products within a group; 'i is the conditional marginal expenditure share; ghV is the group relative pric e coefficient defined as g ih j ij ghv V, where h g Substituting equation (3.17) forijv, we can write the group price coefficient as h g gh ghV where g i i g and h j j h are the g are the group marginal expenditure shares of group g and h, respectively.

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42 Uniform Substitute Hypothesis In the previous two sections, no restrict ion was imposed within the groups of commodities, but weak separabi lity prevails between groups. Now, we impose a testable restriction (uniform hypothesi s) on products within a given group. A group of closelyrelated products are uniform substitutes when the cross effect of an additional dollar spent on one product on the marginal utility of another dollar spent on another product is the same for all pairs of products in th e group (Brown, 1993). The uniform substitute hypothesis was initially proposed by Theil (198 0a) to deal with the demand for closely related products such as diffe rent brands of a product. Sin ce the same products that are imported from different countries can be treate d like different brands of the same product, the application of this hypothesis to the same product differentiated by country of origin is relevant. We cons ider this hypothesis given block independence and block-wise dependence framework discussed earlier. In other words, we impose the uniform substitute hypothesis on (3.14) and (3.18). Uniform substitute given block independence Suppose that we have a product group gS that consists of the same product differentiated by country of origin of produc tion. The consumer’s preferences for a uniform product given block independence can be represented by the sum of G subutility functions, each involving the qua ntities of only one group given as (3.19) m gmn m m gn g g nq q u q q u q q u u u,..., ,..., ,..., ,..., ,...,1 1 1 11 11 Under (3.19), the utility that a consumer obtains from the products in one group is independent of the utility of produc ts in another group. That is, 02 j iq q u for gS i

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43 andhS j. However, for the thi and ths products in the same group, we are hypothesizing that the marginal utility of a dollar spent on the thi product gS icaused by an extra dollar spent on the ths product which belongs to the same group gS s is the same because i and s are the same products differentia ted by country of origin of production. Theil (1980a) writes the submatrix of the Hessian of the utility function ijin expenditure terms, multiplied by the scalar m. as nn s s i i ijk k k k k k q p q p u m 22 11 2., where all the off-diagonal elements( ij ij 1, j i ) are equal to a positive constant k. Since m. is negative, this type of preference st ructure implies that the marginal utility of a dollar spent on each product in gS is affected negatively and by the same amount m k. when an additional dollar is on any other product in the group. Thus, all products in gS are affected uniformly by the a dditional consumption of any other products in the group. Since we have between-group (block inde pendence) in addition to the within group restrictions (uniform substitute), we have two null hypotheses. The block independence hypothesis has to do with th e products between tw o product groups, and the uniform substitute has to do with products within the same group. Note that the

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44 uniform substitute hypothesis in this study is applied to the same product differentiated by country of origin. Formally, the null hypothesis of a uniform substitute relationship states that the marginal utility of a dollar spent on the thi product gS i caused by an extra dollar spent on the ths product which belongs to the same group gS s equals some positive constant k except when s i i.e., this effect is independent of i and s and hence, the same for all pairs of produc ts in the same group. g 2 0S s i, for : k q p q p u Hs s i i. The block independence hypothesis states th at the marginal utility of a dollar spent on the thi product g i caused by an extra dollar spent on the thj product which belongs to a different group h g h j ,equals zero. 0 : H2 0 j j i iq p q p u for gS i and hS j ; h g Combining the two null hypotheses corres ponding to the uniform substitute and block independence, the new null hypothesis wh ich corresponds to the uniform substitute hypothesis given block independence can be restated as 0 ; S s i, for :2 g 2 0 j j i i s s i iq p q p u k q p q p u H for gS i and hS j ; h g. 0 ; S s i, for :2 g 2 j j i i s s i i Aq p q p u k q p q p u H for gS i and gS j; h g Theil (1980a) derives the relative price coefficients of a block independent uniform substitute model as

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45 j i k k v j i k k vg j i ij g i i ij1 1 1 ) 20 3 ( where ijv is the relative price coefficients; i is the marginal value share, k is a constant; g is the group marginal value share; is the income flexibility. Block independent Uniform Substitute-Rotterdam Model. Substituting the price substitution terms (3.20) in the block independent non-uniform substituteRotterdam model (3.14), the block independe nt uniform substitute-Rotterdam model can be derived as (3.21) gS i j j g j i i g i i i i iP p d k k P p d k k Q d q d w log 1 log 1 1 log log where i is the unconditional marginal value share; is the income flexibility; k is a constant; g is the group marginal value share; Uniform substitute given block-wise dependence The consumer’s preferences for a uniform product given block-wise dependence can be represented by consumer utility function q u equals some functionf rather than the sum of the group utility functions. (3.22) m gMn M M Gn G G nq q u q q u q q u u u,..., ,..., ,..., ,..., ,...,1 1 1 11 11. Under (3.24), the utility that a consumer obtains from the products in one group is not independent of the utility of prod ucts in another group. That is, for thi and thj products in two different groups, 02 j iq q u. The consumption of product i has an

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46 effect on that of product j and vice versa. For the thi and ths products in the same group, 02 s iq q u. Since we have between-group (block-w ise dependence) and within group (uniform substitute) restrictions, we ha ve two null hypotheses. The block-wise dependence hypothesis has to do with the products between product groups, and the uniform substitute has to with pr oducts within the same group. Formally, the null hypothesis of a uniform substitute relationship states that the marginal utility of a dollar spent on the thi product gS i caused by an extra dollar spent on the ths product which belongs to the same group gS s equals some constant k, i.e., this effect is independent of i and s and hence, the same for all pairs of products in the same group. s i k q p q p u Hs s i i ; S s i, for :g 2 0. The block-wise dependence hypothesis states that the marginal utility of a dollar spent on the thi product gS icaused by an extra dollar spent on the thj product which belongs to a different group h g S jh ,equals some constantgha. gh j j i ia q p q p u 2 0: H for gS i and hS j ; h g Combining the two null hypotheses corres ponding to the uniform substitute and block-wise dependence, the new null hypot hesis which corresponds to the uniform substitute hypothesis given block-wise dependence can be restated as

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47 gh j j i i s s i ia q p q p u k q p q p u H 2 G 2 0 ; S s i, for : for gS i and hS j; h g, gh j j i i s s i i Aa q p q p u k q p q p u H 2 g 2 ; S s i, for : for gS i and hS j ; h g Seale (2003) derives the rela tive price coefficients for a block-wise dependent uniform substitute Rotterdam model as j i k k v j i k k vg gg j gg i ij gg gg i gg i ij1 1 1 ) 23 3 (' ' where ijv is the relative price coefficients; is the income flexibility; i is the conditional marginal value share, k is a constant; gg is the group marginal value share. Block-wise dependent Unifor m Substitute-Rotterdam Model Substituting the price substitution terms (3.23) in the blockwise-Rotterdam model (3.18), the block-wise dependent uniform substitute-Rotte rdam model can be derived as (3.24) P P d V P p d k k P p d k k Q d q d wh g h gh i S i j j gg j i i i gg i i i i i i iglog log 1 log 1 1 log log' The uniform substitute restriction resu lts in a substantial reduction in the parameter space and can be useful for obtai ning more precise parameter estimates and maintaining sufficient degrees of freedom (Brown, 1993).

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48 CHAPTER 4 EMPIRICAL MODELS AND ESTIMATION PROCEDURES Since the differential approach to consum ption theory discussed in chapter 3 does not postulate constancy for the coefficients of its demand equations, we are not entitled yet to talk about empirical estimation. In th is chapter, we discuss the ways in which the theoretical models in chapter 3 are parameterized so that they can be applied to statistical data. Since the nature of data forces us to work with fin ite rather than infinitesimal changes, we replace the infi nitesimal changes by finite changes. Furthermore, we postulate that the coefficients are constant to make the models operational. Finally, estimation procedures are presented for the diffe rent versions of the Rotterdam model. Empirical Models The Relative Price Version of the Rotterdam Model Following Theil (1975), the relative price version of the Rotterdam model (3.11) can be written in finite changes as (4.1) it t jt N j ij t i it itdP dp v dQ dq w 1. where 212 t i it itw w w is the average expenditure share ; 12 ,log t i it itq q dq is the finite change in quantity imported of product i; i is the marginal expenditure share of product i; t t t t tdq w dq w dQ18 18 1 1... is the finite change vers ion of the Divisia price index (real income) ; ijv is the relative (Frisch-deflated) price coefficients;

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49 12 ,logt j jt jtp p dp is the finite change in price of product j ; t t tdp dp dP18 18 1 1... is the finite change version of the Frisch price index; Note that the lower case p is for prices of individua l products and the upper case P is for Divisia price indices. it is the demand disturbance, which is regarded as the random effect of all variables other than income a nd prices. It is assu med that it has zero expectation, that the variances and contempor aneous covariances are constant over time, and that all other covariances vanish as (4.2) t s if t s ifij jt is 0 The coefficients of (4.1) are s ubject to the adding-up constrainti i1and the symmetry constraint ji ijv v and negative definiteness of the matrix ijv. Furthermore, the sum of the relative price coefficients is proportional to the marginal expenditure sharesi j ijv18 1, where is the income flexibility. In this study, six fruit ju ice groups (orange, grapefruit, other citrus, apple, pineapple and grape juices) imported from 18 countries with three countries for each juice group are included (Table 4.1). In order to estimate (4.1), three steps ar e followed. First, one of the 18 demand equations is deleted in order to eliminate si ngularity. Second, the constraint on the price coefficient i j ijv18 1 is imposed and third, the adding up constraint 118 1 k k is imposed on the income coefficients.

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50 Table 4.1 Codes for countries exporting fruit juice to Japan Product Exporting country Quantity log changes Price log changes Budget shares Code U.S. dq1 dp1 w1 1 Brazil dq2 dp2 w2 2 Orange juice ROW dq3 dp3 w3 3 U.S. dq4 dp4 w4 4 Israel dq5 dp5 w5 5 Grapefruit juice ROW dq6 dp6 w6 6 U.S. dq7 dp7 w7 7 Austria dq8 dp8 w8 8 Apple juice ROW dq9 dp9 w9 9 Thailand dq10 dp10 w10 10 Philippines dq11 dp11 w11 11 Pineapple juice ROW dq12 dp12 w12 12 U.S. dq13 dp13 w13 13 Argentina dq14 dp14 w14 14 Grape juice ROW dq15 dp15 w15 15 Italy dq16 dp16 w16 16 Israel dq17 dp17 w17 17 Other citrus juice ROW dq18 dp18 w18 18 aROW means rest of the world Imposing the constrainti j ijv 18 1 on the price coefficients, we write the own price coefficient iiv in terms of the other price coefficients as 18 i j ij i iiv vso that the price term of (4.1) becomes (4.3) 18 18 i j j ij i i j ij idP dp v dP dp v i j i j ij i idp dp v dP dp

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51 Imposing the adding-up constraint 17 1 181i k on the income coefficients, the price substitution term of (4.3) becomes (4.4) 18 17 1 1818i j i j ij k k k i idp dp v dp dp dp dp Substituting (4.4) into (4.1), we obtain (4.5) i i j i j ij i i i i idp dp v A dq dq w where 17 1 1818k k k i i idp dp dp dp A Equation (4.1) is still not estimable unless conditions are imposed on the matrix of price coefficients in addition to symmetry a nd negative definiteness, such as preference independence and/or block independence (T heil, 1980a). As soon as there is one constraint on the price coefficients such as 012 (preference independence between product 1 and product 2) in addition to symmetr y and negative definiteness, it is possible to estimate (4.1). The reason that (4.1) is s till not estimable is that the income flexibility is not identified because of its inva riance under monotone tr ansformation of the consumer’s utility function (Theil, 1980) in which case there may not be unique demand functions. Equation (4.1) can be estimated using the following system of symmetryconstrained equations. ) ( ... ) ( ... ) ( ...3 18 318 3 2 23 3 1 13 3 3 3 3 2 18 218 2 3 23 2 1 12 2 2 2 2 1 18 118 1 3 13 1 2 12 1 1 1 1dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w

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52 ) ( ... ) ( ... ) ( ...6 18 618 6 2 26 6 1 16 6 6 6 6 5 18 518 5 2 25 5 1 15 5 5 5 5 4 18 418 4 2 24 4 1 14 4 4 4 4dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w ) ( ... ) ( ... ) ( ...9 18 918 9 2 29 9 1 19 9 9 9 9 8 18 818 8 2 28 8 1 18 8 8 8 8 7 18 718 7 2 27 7 1 17 7 7 7 7dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w ) ( ... ) ( ... ) ( ...12 18 1218 12 2 212 12 1 112 12 12 12 12 11 18 1118 11 2 211 11 1 111 11 11 11 11 10 18 1018 10 2 210 10 1 110 10 10 10 10dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w ) ( ... ) ( ... ) ( ...15 18 1518 15 2 215 15 1 115 15 15 15 15 14 18 1418 14 2 214 14 1 114 14 14 14 14 13 18 1318 13 2 213 13 1 113 13 13 13 13dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w ) ( ... ) ( ...17 18 1718 17 2 217 17 1 117 17 17 17 17 16 18 1618 16 2 216 16 1 116 16 16 16 16dp dp v dp dp v dp dp v A dQ dq w dp dp v dp dp v dp dp v A dQ dq w The above system of equations provides th e specific price subs titution effect. The specific substitution effect accounts for the n price changes on the demand for the thiproduct (Theil, 1980). The specific substitution effect is one component of the effect of a change in price. In order to estimate the total price substitution effect, one needs to estimate the absolute price version of the Ro tterdam model. The total substitution effect is the sum of the specific and general substitution effect. The general substitution effect is concerned with the competition of all produc ts for an extra dollar of the consumer’s income. The Absolute Price Version of the Rotterdam Model The absolute price version of the Rotterdam model (3.12) can be written in finite changes as

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53 (4.7) i j N j ij i i idp dQ dq w 1 where j i ij ijv The Slutsky price coefficients ij are symmetric negative semi definite of rank n1 and satisfy the homogeneity property01 n j ij. A major convenience of the absolute price version is its linearity in the parameters, thus implying that a least-square regression estimation yields best linear unbiased para meter estimates when (1) the explanatory variables take non-stochastic values; (2) the disturbances have zero means and a constant contemporaneous covariance matrix and ar e serially uncorrelated; and (3) the homogeneity condition and the Sluts ky symmetry condition are ignored. A disadvantage of the absolute price version of the Rotterdam model is that the number of the Slutsky price coefficientsij grows rapidly when the number of commodities N increases. The number of free pa rameters in (4.7) is given by2N N where N is the number of commodities. Even after imposing the restrictions of adding up, homogeneity, and symmetry, the numb er of free parameters is reduced to1 2 5 0 N N. The absolute price version of the Rotterdam model with symmetry and homogeneity imposed can be estimated us ing the following system of equations. 18 17 318 18 2 23 18 1 13 3 3 3 18 17 218 18 2 22 18 1 12 2 2 2 18 17 118 18 2 12 18 1 11 1 1 1... ... ... ) 8 4 (dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w

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54 18 17 618 18 2 26 18 1 16 6 6 6 18 17 518 18 2 25 18 1 15 5 5 5 18 17 418 18 2 24 18 1 14 4 4 4... ... ...dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w 18 17 918 18 2 29 18 1 19 9 9 9 18 17 818 18 2 28 18 1 18 8 8 8 18 17 718 18 2 27 18 1 17 7 7 7... ... ...dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w 18 17 1218 18 2 212 18 1 112 12 12 12 18 17 1118 18 2 211 18 1 111 11 11 11 18 17 1018 18 2 210 18 1 110 10 10 10... ... ...dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w 18 17 1518 18 2 215 18 1 115 15 15 15 18 17 1418 18 2 214 18 1 114 14 14 14 18 17 1318 18 2 213 18 1 113 13 13 13... ... ...dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w 18 17 1718 18 2 217 18 1 117 17 17 17 18 17 1618 18 2 216 18 1 116 16 16 16... ...dp dp dp dp dp dp dQ dq w dp dp dp dp dp dp dQ dq w Block Independent Non-uniform Substitute-Rotterdam Model The block independent non-uniform substitute-Rotterdam model (3.14) can be written in finite changes as (4.9) i S j j ij i i igdP dp v dQ dq w The estimation procedure of (4.9) is similar to that of (4.1) pr esented earlier. In order to estimate (4.9), one of the 18 demand eq uations is deleted to eliminate singularity. Using the constrainti S j ijgv, we write the own price coefficient iiv in terms of the other price coefficients as i j ij i iiv vso that the price term of (4.9) becomes

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55 (4.10) g gS i j j ij i S i j ij idP dp v dP dp v. gS j i i j ij i idp dp v dP dp. Now, using the adding up constraint 18 1 181k k ,(4.10) becomes (4.11) gS j i j ij k k k i idp dp v dp dp dp dp17 1 1818 Substituting (4.11) into (4.9) yields (4.12) i i j i j ij i i i i i idp dp v A dq dq w Equation (4.9) can thus be estimated using the following symmetry-constrained system of equations. 3 2 23 3 1 13 3 3 3 3 2 3 23 2 1 12 2 2 2 2 1 3 13 1 2 12 1 1 1 1dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w 5 5 56 6 4 46 6 6 6 6 5 6 56 5 4 45 5 5 5 5 4 6 46 4 5 45 4 4 4 4dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w 9 8 89 9 7 79 9 9 9 9 8 9 89 8 7 78 8 8 8 8 7 9 79 7 8 78 7 7 7 7dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w

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56 12 11 1112 10 12 1012 12 12 12 12 11 12 1112 11 10 1011 11 11 11 11 10 12 1012 10 11 1011 10 10 10 10dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w 15 14 1415 15 13 1315 15 15 15 15 14 15 1415 14 13 1314 14 14 14 14 13 15 1315 13 14 1314 13 13 13 13dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w 17 18 1718 17 16 1617 17 17 17 17 16 18 1618 16 17 1617 16 16 16 16dp dp v dp dp v A dQ dq w dp dp v dp dp v A dQ dq w Block-wise Dependent Non-unifor m Substitute-Rotterdam Model The block-wise dependent non-uniform substitute-Rotterdam model (3.18,) can be written in finite changes as (4.14) i h g h gh S j i i S j j ij i i idP dP V dP dp dQ dq wg g 6 where ijv is the specific price coefficients of products within in a group; ghV is group relative price coefficients; hdP is the Frisch price index of a group, and i is the error term. The estimation procedure of equation (4.14) is also similar to that of (4.1). In order to estimate (4.14), one of the 18 de mand equations is deleted to eliminate singularity. Using the constraint that the sum of th e price substitution terms is proportional to the marginal value share i h gh S j j i S j ijVg g 1, we write the own price coefficient

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57 iiv in terms of the other price coefficients as 6 g h gh S j j i S j ij i iiV vg g and substitute it in equation (4.14) so that th e first price term of equation (4.14) which corresponds to the within group demand becomes (4.15) g g gS i j j ij i g h gh S j j i S j ij idP dp v dP dp V6 g gS i j i j ij i g h gh S j i i idp dp v dP dp V6 Now collecting equation (4.15) and the s econd price term of equation (4.14), the price substitution terms of equation (4.14) becomes (4.16) dP dP V dp dp v dP dp Vh g h gh S j i i S i j i j ij i g h gh S j i i ig g g 6 6 Substituting (4.16) into (4.14), we obtain (4.17) i h g h gh S j i i S i j i j ij i g h gh S j i i i i i idP dP V dp dp v dP dp V dQ dq wg g g 6 6 Equation (4.14) can thus be estimated using the following symmetry-constrained system of equations (equation 4.18).

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58 ) ( ... ...6 16 3 13 2 12 3 2 1 1 1 3 13 1 2 12 1 16 13 12 3 2 1 1 1 1 1 1dP dP V dP dP V dP dP V dp dp v dp dp v dP dp V V V dQ dq w ) ( ... ...6 26 3 23 2 12 3 2 1 2 2 3 23 2 1 12 2 16 13 12 3 2 1 2 2 2 2 2dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 16 3 13 2 12 3 2 1 3 3 2 23 3 1 13 3 26 23 12 3 2 1 3 3 3 3 3dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 26 3 23 1 12 6 5 4 4 4 6 46 4 5 45 4 26 23 12 6 5 4 4 4 4 4 4dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 26 3 23 1 12 6 5 4 5 5 6 56 5 4 45 5 26 23 12 6 5 4 5 5 5 5 5dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 26 3 23 1 12 6 5 4 6 6 5 56 6 4 46 6 26 23 12 6 5 4 6 6 6 6 6dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w

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59 ) ( ... ...6 36 2 23 1 13 9 8 7 7 7 9 79 7 8 78 7 36 23 13 9 8 7 7 7 7 7 7dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 36 2 23 1 13 9 8 7 8 8 9 89 8 7 78 8 36 23 13 9 8 7 8 8 8 8 8dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 36 2 23 1 13 9 8 7 9 9 8 89 9 7 79 9 36 23 13 9 8 7 9 9 9 9 9dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 46 2 24 1 14 12 11 10 10 10 12 1012 10 11 1011 10 46 24 14 12 11 10 10 10 10 10 10dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 46 2 24 1 14 12 11 10 11 11 12 1112 11 10 1011 11 46 24 14 12 11 10 11 11 11 11 11dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 46 2 24 1 14 12 11 10 12 12 11 1112 12 10 1012 11 46 24 14 12 11 10 12 12 12 12 12dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w

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60 ) ( ... ...6 56 2 25 1 15 15 14 13 13 13 15 1315 13 14 1314 13 56 25 15 15 14 13 13 13 13 13 13dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 56 2 25 1 15 15 14 13 14 14 15 1415 14 13 1314 14 56 25 15 15 14 13 14 14 14 14 14dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...6 56 2 25 1 15 15 14 13 15 15 14 1415 15 13 1315 15 56 25 15 15 14 13 15 15 15 15 15dP dP V dP dP V dP dP V dp dp V dp dp v dP dp V V V dQ dq w ) ( ... ...5 56 2 26 1 16 18 17 16 16 16 18 1618 16 17 1617 16 56 26 16 18 17 16 16 16 16 16 16dP dP V dP dP V dP dP V dp dp v dp dp v dP dp V V V dQ dq w ) ( ... ...5 56 2 26 1 16 18 17 16 17 17 18 1718 17 16 1617 17 56 26 16 18 17 16 17 17 17 17 17dP dP V dP dP V dP dP V dp dp v dp dp v dP dp V V V dQ dq w Block Independent Uniform Subs titute-Rotterdam Model The block independent uniform substitute-R otterdam model (3.21) can be written in finite changes as

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61 (4.20) gS i j j g j i i g i i i i idP dp k k dP dp k k dq dq w1 1 1 Equation (4.20) can be estimated usi ng the following system of equations. ) ( ) ( 1 ) ( ) ( 1 ) ( ) ( 1 13 3 2 1 1 3 1 1 2 3 2 1 1 2 1 1 1 3 2 1 1 1 1 1 1 1 1dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 ) ( ) ( 1 1 ) ( ) ( 13 3 2 1 1 3 2 1 2 3 2 1 1 2 1 2 1 3 2 1 1 2 1 1 2 2 2dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 1 ) ( ) ( 1 ) ( ) ( 13 3 2 1 1 3 1 3 2 3 2 1 1 3 2 1 1 3 2 1 1 3 1 1 3 3 3dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 ) ( ) ( 1 ) ( ) ( 1 16 6 5 4 2 6 4 2 5 6 5 4 2 5 4 2 4 6 5 4 2 4 2 4 4 4 4dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 ) ( ) ( 1 1 ) ( ) ( 16 6 5 4 2 6 5 2 5 6 5 4 2 5 2 5 4 6 5 4 2 5 4 2 5 5 5dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 1 ) ( ) ( 1 ) ( ) ( 16 6 5 4 2 6 2 6 5 6 5 4 2 6 5 2 4 6 5 4 2 6 4 2 6 6 6dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 ) ( ) ( 1 ) ( ) ( 1 19 9 8 7 3 9 7 3 8 9 8 7 3 8 7 3 7 9 8 7 3 7 3 7 7 7 7dP dp k k dP dp k k dP dp k k dQ dq w

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62 ) ( ) ( 1 ) ( ) ( 1 1 ) ( ) ( 19 9 8 7 3 9 8 3 8 9 8 7 3 8 3 8 7 9 8 7 3 8 7 3 8 8 8dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 1 ) ( ) ( 1 ) ( ) ( 19 9 8 7 3 9 3 9 8 9 8 7 3 9 8 3 7 9 8 7 3 9 7 3 9 9 9dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 ) ( )) ( 1 ) ( ) ( 1 112 12 11 10 4 12 10 4 11 12 11 10 4 11 10 4 10 12 11 10 4 10 4 10 10 10 10dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 ) ( ) ( 1 1 ) ( ) ( 112 12 11 10 4 12 11 4 11 12 11 10 4 11 4 11 10 12 11 10 4 11 10 4 11 11 11dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 1 ) ( ) ( 1 ) ( ) ( 112 12 11 10 4 12 4 12 11 12 11 10 4 12 11 4 10 12 11 10 4 12 10 4 12 12 12dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 ) ( ) ( 1 ) ( ) ( 1 115 15 14 13 5 15 13 5 14 15 14 13 5 14 13 5 13 15 14 13 5 13 5 13 13 13 13dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 ) ( ) ( 1 1 ) ( ) ( 115 15 14 13 5 15 14 5 14 15 14 13 5 14 5 14 13 15 14 13 5 14 13 5 14 14 14dP dp k k dP dp k k dP dp k k dQ dq w

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63 ) ( ) ( 1 1 ) ( ) ( 1 ) ( ) ( 115 15 14 13 5 15 5 15 14 15 14 13 5 15 14 5 13 15 14 13 5 15 13 5 15 15 15dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 ) ( ) ( 1 ) ( ) ( 1 118 18 17 16 6 18 16 6 17 18 17 16 6 17 16 6 16 18 17 16 6 16 6 16 16 16 16dP dp k k dP dp k k dP dp k k dQ dq w ) ( ) ( 1 ) ( ) ( 1 1 ) ( ) ( 118 18 17 16 6 18 17 6 17 18 17 16 6 17 6 17 16 18 17 16 6 17 16 6 17 17 17dP dp k k dP dp k k dP dp k k dQ dq w Block-wise Dependent Uniform Substitute-Rotterdam Model The block-wise dependent uniform substitute-Rotterdam model (3.24) can be written in finite changes as (4.22) dP dP V dP dp k k dP dp k k dQ dq wh g h gh i S i j j g j i i i g i i i i i i ig '1 1 1 Equation (4.22) can be estimated usi ng the following system of equations. ) ( ... ) ( 1 ) ( 1 ) ( 1 16 16 3 13 2 12 3 2 1 1 3 3 2 1 1 3 1 1 2 3 2 1 1 2 1 1 1 3 2 1 1 1 1 1 1 1 1dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 ) ( 1 1 ) ( 16 16 3 13 2 12 3 2 1 2 3 3 2 1 1 3 2 1 2 3 2 1 1 2 1 2 1 3 2 1 1 2 1 1 2 2 2dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w

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64 ) ( ... ) ( 1 1 ) ( 1 ) ( 16 16 3 13 2 12 3 2 1 3 3 3 2 1 1 3 1 3 2 3 2 1 1 3 2 1 1 3 2 1 1 3 1 1 3 3 3dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 ) ( 1 ) ( 1 16 26 3 23 1 12 6 5 4 4 6 6 5 4 2 6 4 2 5 6 5 4 2 5 4 2 4 6 5 4 2 4 2 4 4 4 4dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 ) ( 1 1 ) ( 16 26 3 23 1 12 6 5 4 5 6 6 5 4 2 6 5 2 5 6 5 4 2 5 2 5 4 6 5 4 2 5 4 2 5 5 5dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 1 ) ( 1 ) ( 16 26 3 23 1 12 6 5 4 6 6 6 5 4 2 6 2 6 5 6 5 4 2 6 5 2 4 6 5 4 2 6 4 2 6 6 6dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 ) ( 1 ) ( 1 16 36 2 23 1 13 9 8 7 7 9 9 8 7 3 9 7 3 8 9 8 7 3 8 7 3 7 9 8 7 3 7 3 7 7 7 7dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w

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65 ) ( ... ) ( 1 ) ( 1 1 ) ( 16 36 2 23 1 13 9 8 7 8 9 9 8 7 3 9 8 3 8 9 8 7 3 5 3 5 7 9 8 7 3 8 7 3 8 8 8dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 1 ) ( 1 ) ( 16 36 2 23 1 13 9 8 7 9 9 9 8 7 3 9 3 9 8 9 8 7 3 9 8 2 7 9 8 7 3 9 7 3 9 9 9dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 ) ( 1 ) ( 1 16 46 2 24 1 14 12 11 10 10 12 12 11 10 4 12 10 4 11 12 11 10 4 11 10 4 10 12 11 10 4 10 4 10 10 10 10dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 ) ( 1 1 ) ( 16 46 2 24 1 14 12 11 10 11 12 12 11 10 4 12 11 4 11 12 11 10 4 11 4 11 10 12 11 10 4 11 10 4 11 11 11dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 1 ) ( 1 ) ( 16 46 2 24 1 14 12 11 10 12 12 12 11 10 4 12 4 12 11 12 11 10 4 12 11 4 10 12 11 10 4 12 10 4 12 12 12dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w

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66 ) ( ... ) ( 1 ) ( 1 ) ( 1 16 56 2 25 1 15 15 14 13 13 15 15 14 13 5 15 13 5 14 15 14 13 5 14 13 4 13 15 14 13 5 13 5 13 13 13 13dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) 6 ( ... ) ( 1 ) ( 1 1 ) ( 156 2 25 1 15 15 14 13 14 15 15 14 13 5 15 14 5 14 15 14 13 5 14 5 14 13 15 14 13 5 14 13 5 14 14 14dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 1 ) ( 1 ) ( 16 56 2 25 1 15 15 14 13 15 15 15 14 13 5 15 5 15 14 15 14 13 5 15 14 5 13 15 14 13 5 15 13 5 15 15 15dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 ) ( 1 ) ( 1 15 56 2 26 1 16 18 17 16 16 18 18 17 16 6 18 16 6 17 18 17 16 6 17 16 6 16 18 17 16 6 16 6 16 16 16 16dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w ) ( ... ) ( 1 ) ( 1 1 ) ( 15 56 3 26 2 16 18 17 16 17 18 18 17 16 6 18 17 6 17 18 17 16 6 17 6 17 16 18 17 16 6 17 16 6 17 17 17dP dP V dP dP V dP dP V DP dp k k dP dp k k dP dp k k dQ dq w Data Sources The sources of data for this study are th e Statistics Bureau of Japan and Japan’s Ministry of Finance as well as the Food and Agricultural Orga nization. Monthly population data from December 1995 to May 2005 came from the web page

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67 ( http://www.stat.go.jp/english/data/jinsui/2-2.htm ) maintained by the Statistics Bureau of Japan’s Ministry of Internal Affairs and Co mmunications. Import data came from the Trade Statistics of Japan that are published by the Ministry of Finance and the Customs under the provision of the Customs Law and the re levant international conventions. It is available on the web page http://www.customs.go.jp The monthly imports and expenditures on imports of orange, grapefruit other citrus, apple, pineapple and grape juices were obtained for the period December, 1995 to May, 2005. The values of imports are on a cost, insurance and freight (CIF) ba sis, which include costs of the product, insurance and transportation. Unit import va lues, which proxy commodity prices, were obtained by dividing import values by impor t quantities. Data on the production, consumption and trade of fruit juices came from the webpage http://faostat.f ao.org/faostat/ maintained by the Food and Agricultural Organization. Analytical Methods The method used to estimate the model is the non-linear least s quare (LSQ) in the Time Series Processor Program (TSP 4.5). Th is method is based on the entire system of equations, and estimates all parameters jointly. When estimating the system of demand equations, one of the equations has to be deleted or the covariance matrix will be singular. However, parameter estimates of the deleted equation can be recovered by re-estimating the system with another equati on in the system. Parameter es timates are invariant to the deleted equation when using maximum lik elihood estimation (Barten, 1969). The LSQ command computes maximum likelihood estimates if it is specified with no instruments and more than one equati on (Cummins, 1999). Since the parameter estimates in this study are generated from a system of demand equations without specifying instruments, they can be take n as maximum likelihood estimates. With

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68 normally distributed disturbances (itu), the ML method has all the desirable asymptotical properties of Maximum Likelihood (ML) estimato rs and, therefore, is asymptotically efficient among all estimators (Greene, 2000). Th e likelihood ratio test is used to test for autocorrelation.

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69 CHAPTER 5 RESULTS AND DISCUSSION Descriptive Results Since Japan’s deregulation of imports in the 1990s, the imports of fruit juices have increased with the exception of U.S. apple juice (Table 5.1). Over the period January, 1995 to May, 2005, the imports of U.S. apple juice has decreased by 17% while that of U.S. orange, grapefruit and gr ape juices increased by 4%, 12% and 5%, respectively. The highest increase was atta ined by the ROW grapefruit juice (51%) followed by the Chinese apple juice (31%) and th e Israelis grapefruit fruit juice (26%). The analysis of import stability as measured by the coefficient of variation shows that the imports of fruit juices in Japan over the given period have exhibited a significant fluctuation. The fluctuation of imports varies from country to country. U.S. orange and grape juices have experienced the highes t fluctuation among U.S. fruit juices. Over the same period, Japan’s import price of all fruit juices has decreased (Table 5.1). On average, Japan’s import price of U. S. orange, grapefruit, apple and grape juices has decreased by 12%, 10%, 7% and 6% pe r month over the period December, 1995 to May, 2005. Over the same period, apple jui ce imported from the rest of the world has witnessed the largest price decrease (13%). Among U.S. products, prices of orange and grapefruit juices are relatively more stable than those of the respective competitors’ products. The prices of apples are less stable compared to their respec tive rival products. Except for Brazilian orange juice (25%) and the ROW apple juice (19%), the average expenditure share of fruit juices in Japan is below 10% (Table 5.1). Expenditure

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70 share of U.S. juices, expressed as a percenta ge of total fruit juice expenditure, ranges from 6% for apple juice to 8% for grapefruit juice. Table 5.1 Fruit juice quantity and price log-changes, and expenditure shares, Japan, December 1995 to May 2005 Quantity log-changes 1 ,log t i it iq q dq Price log-changes 1 ,log t i it ip p dp Expenditure shares iw Imports Mean SD Mean SD Mean SD U.S. oranges 0.0410 0.6701 -0.1155 0.2803 0.0724 0.0335 Brazilian. oranges 0.0982 0.98 47 -0.1033 0.2683 0.2542 0.0895 ROW oranges 0.0959 0.8876 -0.0083 0.4210 0.0324 0.0205 U.S. grapefruits 0.1200 0.4909 -0.0979 0.2907 0.0808 0.0302 Israelis grapefruits 0.2617 1.0503 -0.0720 0.5821 0.0259 0.0168 ROW grapefruits 0.5078 1.3739 -0.1149 0.8360 0.0111 0.0104 U.S. apples -0.1694 0.9249 -0.0690 0.2847 0.0567 0.0422 Chinese apples 0.3176 0.6891 -0.1405 0.2798 0.0727 0.0372 ROW apples 0.0760 0.4059 -0.0946 0.1958 0.1652 0.0510 Thai pineapples 0.1549 1.0317 -0.0572 0.3934 0.0109 0.0058 Philippines pineapples 0.1578 1.7814 -0.0606 0.3713 0.0075 0.0037 ROW pineapples 0.1109 1.5452 -0.0414 0.5171 0.0089 0.0062 U.S. grapes 0.0529 0.5942 -0.0647 0.2890 0.0621 0.0249 Argentinean grapes 0.2792 1.1260 -0.0969 0.3346 0.0091 0.0058 ROW grapes 0.1717 0.4728 -0.0802 0.2584 0.0648 0.0235 Israelis other citrus 0.0861 0. 6349 -0.0924 0.3138 0.0220 0.0064 Italian other citrus 0.1756 0. 7744 -0.0902 0.2412 0.0172 0.0069 ROW other citrus 0.2032 0.8238 -0.1031 0.5923 0.0250 0.0118 (Source: Study data) Test for First-order Autocorrelation A test for first order autocorrelation AR (1) was carried out for five different versions of the Rotterdam model. These are block independent non-uniform substitute Rotterdam model (4.9), block-wise dependent non-uniform substitute Rotterdam model (4.14), block independent uniform substitute Rotterdam model (4.20) and block-wise dependent uniform substitute Rotterdam mode l (4.22). The test was done considering each model with and without autocorrelation as the unrestricted and restricted model, respectively. The null hypothesis 0 :0 H was tested using the likelihood ratio test given as J L L LRd2ˆ ~ 2 where ~ is a vector of restricted parameter

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71 estimates and ˆ is a vector of parameter estimates associated with the unrestricted model. The restricted model is the one with first or der serial correlation while the unrestricted model is the one without firs t order autocorrelation. Under the null hypothesis 0H, the LR has an asymptotic chi-square distribution with the degrees of freedom equa l to the number of restrictionsJ. Since symmetry was imposed as part of the estimation procedure, the coefficient of autocorrelation was taken to be common across equations. The result of the test indicates that th e null hypothesis of no autocorrelation was rejected in all of the models (Table 5.2), impl ying that the data is serially correlated. The value of which is common across equations in each system, ranges from 0.31 for (4.1) to 0.36 for (4.9), and is significantly different from zero (P<0.001). The Hildreth and Lu (1960) approach was used for the correction. Table 5.2: Test for first-order autocorrelation Model Coefficient Log Likelihood value ~ ˆ 2L L a Rho = 0.00 4710.26 Equation (4.20) Rho = 0.35 4785.67 150.82*** Rho = 0.00 4716.24 Equation (4.9) Rho = 0.36 4789.90 147.32*** Rho = 0.00 4748.99 Equation (4.22) Rho = 0.33 4813.17 128.36*** Rho = 0.00 4757.74 Equation (4.14) Rho = 0.35 4826.09 136.70*** Rho = 0.00 4892.99 Equation (4.1) Rho = 0.31 4934.79 83.60*** a Twice the difference between the log likel ihood value for the unconstrained model, ˆL and the log likelihood value for the constrained model, ~ L. *** The chi-square critical value is at the 1% significance level.

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72 Hypothesis Testing for Model Selection Following the correction for first-order autocorrelation, the study tests two hypotheses (block independence/uniform substitute hypothesis and block-wise dependence/uniform substitute hypothesis) to se lect the model that best describes the import data of fruit juices in Japan. The hypotheses of block independence and blockwise dependence have to do w ith the relationship between pr oducts that belong to two different product groups while th at of the uniform substitute has to do with a relationship between products that bel ong to the same product group. Therefore, the blockindependence/uniform substitute hypothese s and block-wise dependence/uniform substitute hypothesis invo lve between-group (block i ndependence or block-wise dependence) and within-group (uniform substitu te) relationships. Recall that the uniform substitute hypothesis is applied to the same product differentiated by country of production. The result of these tests enables us to select the model that best describes the import data of fruit juices in Japan. In li ght of these hypotheses, two restricted models were derived from the relative price version of the Rotterdam model (4.1). The restricted models are block independent uniform substitute-Rotterdam model (4.20), and blockwise dependent uniform substi tute-Rotterdam model (4.22). Since these two restricted versions (4.20) and (4.22) are nested in the unrestricted ve rsion (4.1), the likelihood ratio test is used. Block Independence and Unifor m Substitute Hypothesis The hypothesis of block independence states that there is no specific cross price effect ij between any two products in any two different product groups. The uniform

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73 substitute hypothesis states that the specific cross price effect ij between any two products in the same product group is the same for all pairs of goods in that group. Combining the two null hypotheses, the null hypothesis of block independence and uniform substitute relati onship can be restated as 0 :0 ijH gS i hS j and h g ; kis for any gS s i 0 :ij AH gS i hS j and h g ; kis for any gS s i ,. The test for the hypothesis of block independence and uniform substitution involves a comparison between the uniform substitute block independent Rotterdam model (4.20) and the relative price version of the Rotterdam model (4.1). Since (4.20) is a restricted function, we expect its likelihood value to be smaller than that of (4.1). The likelihood value of (4.20) is 4785.67 with 24 degrees of freedom while the value of (4.1) is 4934.79 with 171 de grees of freedom (Table 5.3). The value of the model chi-square is 298.24 which is greate r than the critical chi-square value at 1% significance level. Therefore, we reject the null hypothesis, and conc lude that there is competition between products that belong to different product groups since there is a change in marginal utility of a dollar spent on a product in one product group caused by an extra dollar spent on anothe r product in another product group. For example, an extra dollar spent on U.S. orange juicei, affects the marginal utility of another dollar spent on the Chinese apple juicej. Furthermore, the change in marginal u tility of a dollar spent on a product caused by an extra dollar spent on anothe r product is not the same for all pairs of products within the same group. The country of origin ma kes a difference in one’s decision to buy a certain fruit juice. For example, the change in marginal utility of a dollar spent on the

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74 U.S. orange juice i, caused by an extra dollar sp ent on Brazilian orange juice r is not the same as that of the change in marginal utility of a dollar spent on the U.S. orange juice caused by an extra dollar spent on the ROW orange juice, s. This suggests that consumers decide to buy orange juice base d on the country of origin. In summary, consumers are influenced by the country of origin when they choose between products that belong to the same group. Table 5.3 Hypothesis testing for model selection Model Log likelihood value Free parameters ~ ˆ 2L L a Equation (4.20) 4785.67 24 298.24*** Equation (4.22) 4813.17 39 243.24*** Equation (4.1) 4934.79 171 a Twice the difference between the log likel ihood value for the unconstrained model, ˆL and the log likelihood value for the constrained model, ~ L. *** The chi-square critical value is at the 1% significance level. Block-wise Dependence and Unif orm Substitute Hypothesis The hypothesis of block-wise dependence stat es that the specific cross price effect ij between any two products in two different pr oduct groups is the sa me for all pairs of products in the two groups. The uniform s ubstitute hypothesis states that the specific cross price effect ij between any two products in the same product is the same for all pairs of products within that group. Combining the two null hypotheses, the new null hypothesis which corresponds to the block-wise dependence uniform substitute relationship can be restated as gh ija v H :0, gS i hS j and h g ; and k vir for any gS r i

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75 gh ij Aa v H :, gS i hS j and h gS S ; and k vir for any gS r i ,. The test for the hypothesis of block-wi se dependence and uniform substitution involves a comparison between the block-wise uniform substitute-Rotterdam model (4.22) and the relative price version of the Rotterdam model (4.1). The likelihood value of (4.22) is 4813.17 with 39 degrees of freed om while the value of (4.1) is 4934.79 with 171 degrees of freedom (Table 5.3). The va lue of the model chi-square is 243.24 which is greater than the critical chi-square value at 1% probability level. Therefore, we reject the null hypothesis, and conclude that th e competition between products in different groups is not the same for all pairs of products in the two groups th e change in marginal utility of a dollar spent on a product in one product group caused by an extra do llar spent on another product in another product group is not the same for all pairs of products in the two groups. In other words, the competition between product i of group g and product j of group his not the same as that of product i and product l of group h since the change in marginal utility of product i, caused by an extra dollar spent on product j is not the same as that of the change in marginal utility of a dollar spent on product i caused by an extra dollar spent on product l. For example, an extra dollar spent on U.S. orange juicej, affects the marginal utility of a nother dollar spent on Thai pineapple juiceidifferently than does it affect the marg inal utility of a dollar spent on the Philippines pineapple juice. In other words, the effect of the change in price of U.S. orange juice on the demand for Thai pineapple ju ice is not the same as that of the effect on the demand for the Philippines pineapple juice. This implies that the country of origin of the pineapple juice makes a difference wh en a consumer decides to buy orange and pineapple juices.

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76 Furthermore, we can conclude that the change in marginal utility of a dollar spent on a product caused by an extra dollar spent on another product is no t the same for all pairs of products within the same group. The country of origin makes a difference in one’s decision to choose between products th at belong to the same product group. For example, the change in marginal utility of a dollar spent on U.S. orange juice i, caused by an extra dollar spent on Brazilian orange juice r is not the same as that of the change in marginal utility of a dollar spent on U.S. orange juice icaused by an extra dollar spent on the ROW orange juice, s. This implies that consumers are influenced by the country of origin and thus decide to buy orange juice based on the country of origin. In summary, the country of origin is taken into acc ount by consumers when they choose between products that belong to diffe rent product groups and also when they choose between products that belong to th e same product group. Therefore, based on the resu lts of the likelihood ratio te st which rejected both restricted models (Table 5.3) the relative pr ice version of the Rotterdam model (4.1) is chosen to best describe the import data of Japan’s import of fruit juices. The relative Price Version of the Rotterdam Model Since the relative price version of th e Rotterdam model does not have any restriction within or across th e price coefficients, individual products are competing with each other based on the country of origin. In other words, it allows investigating the relationship between individual pr oducts based on the country of origin of the product. For example, we can investigate the relati onship between apple juice from China and orange juice from U.S.

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77 Parameter Estimates Marginal expenditure shares Results indicate that the marginal expenditure shares are all positive except for those of the Israel’s grapefruit juice and the ROW pineapple juice (Table 5.4). However, the coe fficient of the Israelis grapefruit juice is not statistically significant. The largest share of the increase in marginal expenditure on imported fruit juices goes to Brazilian ora nge juice (70%) followed by that of the ROW apple juice (8%). This is consistent with the average expenditure shares since the Brazilian orange juice (25%) and the ROW a pple juice (17%) have the first and second highest average expenditure shares (Table 5.1) Japanese imports of U.S. orange juice grapefruit and apple juice receive only 3-4% of the increase in marginal expenditures. Except for apple juice and grape juice, imports of fruit juices from ROW receive less than one percent of each dollar increase in expenditures. Table 5.4 Marginal expenditure shares of imported fruit juices in Japan Product Estimates SE U0.S0. oranges 0.0337*** 0.0100 Brazilian oranges 0.6997*** 0.0373 ROW oranges 0.0033 0.0058 U0.S0. grapefruits 0.0441*** 0.0078 Israelis grapefruits -0.0016 0.0059 ROW grapefruits 0.0051 0.0034 U0.S0. apples 0.04686*** 0.0124 Chinese apples 0.0473** 0.0092 ROW apples 0.0800*** 0.0159 Thai pineapples 0.0044* 0.0023 Philippine p0. apples 0.0024 0.0022 ROW pineapples -0.0073** 0.0036 U0.S0. grapes 0.0080 0.0076 Argentinean grapes 0.0017 0.0024 ROW grapes 0.0188*** 0.0066 Israelis other citrus 0.0045 0.0032 Italian other citrus 0.0019 0.0027 ROW other citrus 0.0064 0.0041 *** (**)* significance at 1%, 5% and 10%

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78 Price effects. Price effects are described here by both relative and Slutsky price coefficients. The Slutsky price coefficients ij can be derived from relative (Frischdeflated) price coefficients ijv and marginal value shares i using j i ij ijv where is the coefficient of income flexibility. The Slutsky price coefficients ij are the sum of the specific ijvand general substitution effects j i The Slutsky price coefficients ij measure the total substitution effect of a change in the thj price on the demand for the thi product or, equivalently, the effect of such a change when real income remains constant. The relative price coefficients measure the speci fic substitution effect which accounts for the n price changes on the demand for the thiproduct, or equivalently, the effect of such a change when the marginal utility of income remains constant. The general substitution effect j i which serves as a deflator of the specific substitution effect by transforming the absolute prices into relative prices, accounts for the Frisch price index changes on the demand for the thiproduct. If the relative price coefficients ijv and jiv are both positive, it means that an increase in the relative price of either produc t raises the demand for the other, and thus the two products are called specific substitutes. Similarly, if ijv and jiv are both negative, it means that an increase in th e relative price (opportunity cost) of either product reduces the demand for the other, or thus the two pr oducts are called specific complements. The Hicks’s definitions of net substitu tes and net complements are based on the signs of ij The sign of the parameter ij determines if products i and j are net

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79 complements0ij or net substitutes0ij In terms of the Slutsky equation, m q q p q p qj i s i j i j if the substitution term, 0 s i jp q for net (or Hicksian) substitutes, and 0 s i jp qfor net (or Hicksian) complements. While the Slutsky price coefficients provide the net substitution effects when real income remains constant, the relative price coe fficients provide the same effects when the marginal utility of income remains unchanged. The concepts of net substitutes and complements focus solely on the substitution effects. The statistically significant relative an d Slutsky cross pri ce coefficients are presented in Table 5.5. Most of these produc ts are substitutes. The difference between the coefficients of the relative and absolute price coefficients in terms of magnitude is small. This implies that the general substituti on effect is small. The general substitution effect is concerned with the competition of all products for an extra dollar of the consumer’s income. Contrary to expectation, th e cross price effects of produc ts that belong to the same group are not necessarily greater than the cross effects of products that belong to different product groups. For example, the cross price effect of U.S. grap efruit/ROW grapefruit juice is smaller than that of U.S. grapefruit /U.S apple juice. Furthermore, products that belong to the same product group are not necess arily substitutes. For example, U.S. apple/ROW apple that bel ong to the same product group are complements. Based on the cross price effects of substitute products, we can identify the market structure of fruit juice in Japan (Figure 5.6), showing th at there are both direct and indirect competitions based on the country of origin. Recall that the direct competition refers to the competition between products w ithin the same juice group (e.g., orange juice

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80 group) while the indirect competition refers to the competition between products in different juice groups (e.g., orange juice and ap ple juice). Except for grape juice, there is no direct competition in Japan’s fruit juice ma rket. The indirect competition appears to be more important than the direct comp etition in Japan’s fruit juice market. Table 5.5: Parameter estimates of cro ss prices of fruit juices in Japan Relative price coefficients Slutsky coefficients Products EstimatesSEEstimates SE U.S. orange/Brazilian orange 0.03950.0296 0.0822*** 0.0259 U.S. orange/ROW grapefruit -0.0089**0.0040-0.0086** 0.0040 U.S. orange/U.S. apple 0.0309**0.01260.0338*** 0.0128 U.S. orange/Philippines pineapple 0.0087**0.00440.0088** 0.0044 U.S. orange/Israelis citrus -0.0158**0.0062-0.0155** 0.0062 U.S. orange/ROW citrus -0.0107**0.0052-0.0103** 0.0052 Brazilian. orange/Chinese apple -0.0701***0.0236-0.0101 0.0207 Brazilian orange/ROW apple -0 .1769***0.0402-0.0754** 0.0354 Brazilian orange/ROW p. apple 0.0304***0.0099 0.0211** 0.0085 Brazilian orange/Israelis citrus 0.00760.93350.0134* 0.0080 ROW orange/U.S apple 0.0129**0.69360.0132* 0.0069 ROW orange/ROW apple 0.0216**0.01030.0221** 0.0102 ROW orange/Argentinean grape 0.0036*0.00220.0036* 0.0022 U.S. grapefruit/ROW grapefruit 0.0102***0.0030 0.0106*** 0.0030 U.S. grapefruit/U.S. apple 0.0230**0.00960.0267*** 0.0096 U.S. grapefruit/Thai. pineapple -0.0188***0.0035-0.0185*** 0.0035 U.S. grapefruit/Philippines pineappl e -0.0146***0.0034-0.0144*** 0.0034 U.S. grapefruit/U.S. grape -0.0161*0.0091-0.0155* 0.0091 U.S. grapefruit/ROW grape 0.0194**0.00950.0209** 0.0095 Israelis grapefruit/Italian citrus 0.00467**0.00 200.0046** 0.0020 ROW grapefruit/Italian citrus -0.0043***0.0013-0.0043*** 0.0013 U.S. apple/ROW apple -0.0445**0.0178-0.0377** 0.0176 U.S. apple/Philippines pineapple 0.00649**0.00310.0066** 0.0031 U.S. apple/ROW pineapple -0.0143***0.0046-0.0149*** 0.0046 U.S. apple/Argentinean grape -0.0177***0.0035-0.0176*** 0.0035 U.S. apple/Israelis citrus -0.0127***0.0045-0.0123*** 0.0045 U.S. apple/ROW citrus 0.0097**0.00470.0103** 0.0047 Chinese apple/ROW pineapple -0.00660.0043-0.0072* 0.0042 Chinese apple/U.S. grape 0. 0211**0.00870.0218** 0.0087 ROW apple/Israelis citrus 0.0127*0.00800.0133* 0.0079 Philipp. pineapple/Argentinean grape 0.0050***0.00190.0050*** 0.0019 Philipp. pineapple/ROW grape 0.0069*0.00390.0070* 0.0039 Philipp. pineapple/Israelis citrus 0.00477**0.00210.0047** 0.0021 ROW pineapple/Argentinean grape 0.0055***0.00170.0054*** 0.0017 U.S. grape/Argentinean grape 0.0108**0.00430.0108** 0.0043 U.S. grape/ROW citrus 0.0085**0.00390.0086** 0.0039 *** (**)* significance at 1%, 5% and 10%

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81Table 5.6 Market structure of fruit juices in Japan Orange Grapefruit Apple Pineapples Grapes Other citrus Product Country U.S. Brazil U.S. Israel U.S. China Thailan d Philipp ine U.S. Argenti na IsraelItaly U.S. SS SS CC Orange Brazil CC U.S. SS CC CC CC Grapefruit Israel SS U.S. SS SS SS CC CC Apple China CC SS Thailand CC Pineapple Philippin es SS CC SS SS SS U.S. CC SS S grape Argentin a CC SS SS S Israel CC CC CC SS Other citrus Italy SS

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82 Results also indicate that the relative pr ice coefficients and the Slutsky own price coefficients are all negative and significan tly different from zero except for the ROW apple juice (Table 5.7). Cont rary to expectation, the own price coefficient of the ROW apple juice is positive but not statistically si gnificant. The negative signs are consistent with demand theory since they ensure the negativity of the own substitution effect. Table 5.7 Parameter estimates of own prices of fruit juices in Japan Relative price coefficients iiv Slutsky price coefficients ii Juice Estimate SE Estimate SE U.S. oranges -0.1139*** 0.0222 -0.1118*** 0.0224 Brazilian oranges -0.9667*** 0.1275 -0.0791 0.0861 ROW oranges -0.0469*** 0.0053 -0.0469*** 0.0053 U.S. grapefruits -0.0471*** 0.0131 -0.0436*** 0.0131 Israelis grapefruits -0.0142*** 0.0045 -0.0142*** 0.0045 ROW grapefruits -0.0079*** 0.0015 -0.0078*** 0.0016 U.S. apples -0.0308* 0.0177 -0.0268 0.0180 Chinese apples -0.0439*** 0.0135 -0.0398*** 0.0134 ROW apples 0.0116 0.0383 0.0233 0.0371 Thai pineapples -0.0095*** 0.0021 -0.0095*** 0.0021 Philippine pineapples -0.0231*** 0.0020 -0.0231*** 0.0020 ROW pineapples -0.0057** 0.0027 -0.0057** 0.0027 U.S. grapes -0.0523*** 0.0126 -0.0522*** 0.0126 Argentinean grapes -0.0059 0.0038 -0.0058 0.0038 ROW grapes -0.0409*** 0.0149 -0.0402*** 0.0149 Israelis other citrus -0.0221*** 0.0042 -0.0220*** 0.0042 Italian other citrus -0.0202*** 0.0044 -0.0202*** 0.0044 ROW other citrus -0.0239*** 0.0026 -0.0238*** 0.0026 *** (**)* significance at 1%, 5% and 10% Expenditure Elasticities The value of income flexibility is estimated to be =-1.8126. The reciprocal of this coefficient, which is the value of the income elasticity of the marginal utility of income is 1= -0.5517. This estimate is consistent with the estimates of Frisch (1959) for the richest section of the population. According to Frisch (1959), a value of 1=-0.7

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83 is for the better off part of the populati on. Since Japanese consumers are among the richest in the world, a value of 1= -0.5517 obtained in this study is a reasonable estimate for Japan. The expenditure elasticities are calculated at the sample means of expenditure shares of the respective imported fruit juices using the equation i iw where i is the marginal value share of product i and iw is the average valu e share of the same product. Expenditure elasticiti es of imported products are us eful to provide guidance for marketing strategies and policy making in exporting countries. The estimates of the expenditure elasticities are positive except for those of the Israelis grapefruit juice and the ROW pin eapple juice (Table 5.8). However, the expenditure elasticity of Israel’s grapefruit jui ce is statistically insignificant while that of the ROW pineapple juice is statistically sign ificant. Thus, we can conclude that the Israelis grapefruit jui ce is not an inferior product while that of the ROW pineapple juice is an inferior product. Among the 18 fruit juices, only the demand for Brazili an orange juice is expenditure elastic (2.7522). All four major fruit juices (orange, grapefruit, apple and grape juices) that the U.S. e xports to Japan are expenditure inelastic, implyi ng that there is less preference for the U.S. juices. The expenditure elasticities of U.S. exports range from 0.1302 for grape juice to 0.8252 for a pple juice. The demand for these products exported by the rest of the world is also expenditure inelastic. The high expenditure elasticity of Brazi lian orange juice and low expenditure elasticities of U.S. and the ROW products is not surprising given that Brazil’s share of the total import expenditure is very high compared to that of other countries. The

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84 average expenditure share of Brazilian orange ju ice is 25% while that of U.S. ranges from 5% for apple juice to 8% for grapefruit juice (Table 5.1). The average expenditure share of fruit juices imported from the ROW is the smallest except for that of apple juice, which accounts for about 17% of the total import expenditure on imported fruit juices. The major exporting country of apple juice in the category of the ROW is Austria. Table 5.8 Expenditure elasticity es timates of fruit juices in Japan Product Estimate SE USA orange 0.4654*** 0.1390 Brazil orange 2.7525*** 0.1467 ROW orange 0.1047 0.1789 USA grapefruit 0.5463*** 0.0967 Israel grapefruit -0.0630 0.2300 ROW grapefruit 0.4603 0.3115 USA apple 0.8252*** 0.2189 Chinese apple 0.6504*** 0.1267 ROW apple 0.4842*** 0.0963 Thailand pineapple 0.4048* 0.2158 Philippines pineapple 0.3212 0.2954 ROW pineapple -0.8262** 0.4060 USA grape 0.1301 0.1226 Argentina grape 0.1921 0.2670 ROW grape 0.2912*** 0.1031 Israel other citrus 0.2065 0.1491 Italy other citrus 0.1153 0.1582 ROW other citrus 0.2578 0.1649 *** (**)* significance at 1%, 5% and 10% The high expenditure elasticity may imply that there is a strong preference for Brazilian orange juice, and that it is a luxury product. It al so implies that as expenditures on imported fruit juice increases, consumers change their consumption of Brazilian orange juice more, in terms of percentage, than they change their consumption of the same juice imported from the U.S. or the rest of the world. Furthermore, these results have important implications for exporting c ountries in terms of making export decisions in light of the expansion and contraction of the Japanese ma rket for imported fruit juices

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85 because of the change in expenditure. Unde r a situation where the Japanese market for imported fruit juices expands because of an increase in expenditure, Brazil will become much better off. This is because as the Japa nese market for imported fruit juices expands because of increasing expenditure, Brazilian oran ge juice market share will increase more than proportionately. Other Exporters will not be as well off since they are expenditure inelastic. Given that Brazilian orange juice make s up the larger proportion of the total imports of fruit juices in Ja pan, a one percent increase in expenditure on imported fruit juices results in a far greater increase in actual imports; and, its market share would increase further upon the expansion of the Japa nese market of imported fruit juices over time. However, under conditions in which th e economy goes to recession, or expenditure growth slows down, Brazil will be worse off because, a given percentage decrease in expenditure on imported fruit juices results in a far greater decrease in actual imports; and its market share would decrea se further upon the contraction of the market of imported fruit juices over time because of its larger ex penditure elasticity. The fact that recession has been more frequent in Japan over the pa st few years requires Brazil to devise an effective export strategy which takes account of the performance of the economy. In addition to recession, the growth of population is another major factor anticipated to affect the demand for imported fr uit juices in Japan as a result of its aging population. The population growth of Japan has turned negative in 2006 (Statistics Bureau of Japan). With per capita income gr owing at 2% per annum and assuming that it will remain constant until 2020, and population grow th starting to take negative rate since 2006, the growth of demand for fruit juices impor ted into Japan is projected (Table 5.9).

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86 The growth of demand for fruit juice in Japa n is positive except for that of Israelis grapefruit juice over the over the period 2006 through 2014. The demand for Israelis grapefruit is negative not only due to the popul ation growth but also negative expenditure elasticity. Products which have positive expendi ture elasticity will continue to grow at a declining rate regardless of the negative growth of populati on except for U.S. grape juice and Israelis and Italian other ci trus juices. From the result of the simulation, it appears that grape and other citrus juice will be mo re affected than the other juices. The demand for Brazilian orange juices declined from 5.53% in 2005 when the growth of population was 0.3% to 5.49% in 2006 when the grow th of population turned negative. It will continue to shrink over the period 2006 thr ough 2020 while the demand for U.S. orange is projected to shrink at 1.12.9 to 0.66% over the same period. Among U.S. products, apple juice will grow at a higher rate (more than 1%) while grape juice will grow at the smallest rate (less than 0.25%). These simulations were made under the assumption that the growth of per capita income will remain constant at 2% per annum over the period 2006 through 2020. The increase in the growth of per capita income will offset the decrease in popul ation growth so that the decline in the growth of demand may be checked. If inco me grows at more than 2%, demand may increase, though population growth slows down. The prospect of the growth of demand for fruit juices will depend on the growth of per capita income relative to the decline in growth of the population. If both move in th e same direction, the decline of the growth rate of demand for fruit juices will be greater.

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87Table 5.9 Projected estimates of the growth of demand for fruit juices in Japan Year Population growth rate U.S. oranges Brazilian Oranges U.S. grape fruits Israelis grapefruit U.S. apples Chinese apples Thai pine apple Philipp. p. apples U.S grapes Argentinean grapes Israelis citrus Italian citrus 2005 0.03 0.96 5.53 1.12 -0.09 1.68 1.33 0.83 0.67 0.29 0.41 0.44 0.26 2006 -0.01 0.92 5.49 1.08 -0.13 1.64 1.29 0.79 0.63 0.25 0.37 0.4 0.22 2007 -0.04 0.89 5.46 1.05 -0.16 1.61 1.26 0.76 0.6 0.22 0.34 0.37 0.19 2008 -0.07 0.86 5.43 1.02 -0.19 1.58 1.23 0.73 0.57 0.19 0.31 0.34 0.16 2009 -0.10 0.83 5.40 0.99 -0.22 1.55 1.20 0.7 0.54 0.16 0.28 0.31 0.13 2010 -0.13 0.80 5.37 0.96 -0.25 1.52 1.17 0.67 0.51 0.13 0.25 0.28 0.10 2011 -0.16 0.77 5.34 0.93 -0.28 1.49 1.14 0.64 0.48 0.10 0.22 0.25 0.07 2012 -0.19 0.74 5.31 0.90 -0.31 1.46 1.11 0.61 0.45 0.07 0.19 0.22 0.04 2013 -0.22 0.71 5.28 0.87 -0.34 1.43 1.08 0.58 0.42 0.04 0.16 0.19 0.01 2014 -0.25 0.68 5.25 0.84 -0.37 1.40 1.05 0.55 0.39 0.01 0.13 0.16 -0.01 2015 -0.28 0.65 5.22 0.81 -0.40 1.37 1.02 0.52 0.36 -0.01 0.10 0.13 -0.04 2016 -0.31 0.62 5.19 0.78 -0.43 1.34 0.99 0.49 0.33 -0.04 0.07 0.10 -0.07 2017 -0.35 0.58 5.15 0.74 -0.47 1.30 0.95 0.45 0.29 -0.08 0.03 0.06 -0.11 2018 -0.38 0.55 5.12 0.71 -0.50 1.27 0.92 0.42 0.26 -0.11 0.00 0.03 -0.14 2019 -0.4 0.53 5.10 0.69 -0.52 1.25 0.90 0.40 0.24 -0.13 -0.01 0.01 -0.16 2020 -0.43 0.50 5.07 0.66 -0.55 1.22 0.87 0.37 0.21 -0.16 -0.04 -0.01 -0.19

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Own-price Elasticities In order to assess the respons iveness of Japan’s imports to changes in prices, two types of own-price elasticitie s (uncompensated and compensa ted) are calculated using equation i i j i ij u ijw w w and equation i ij c ijw respectively, where ij is the Slutsky price coefficient. Uncompensated (Marshallian) own pr ice elasticity of imported juice i indicate the percentage change in quant ity demanded of imported juice i resulting from a one percent change in its own price, holding nominal expenditures on imported juices constant. Compensated (Slutsky/Hicks ian) own price elas ticity of juices i indicates the percentage change in quantity demanded of juice i resulting from a one percent change in its own price, holding real expenditu res on imported juices constant. The uncompensated price elasticities provide th e responsiveness of demand resulting from both substitution and income effects of a price change while the compensated price elasticities would provide the responsivene ss of demand resulting from the substitution effect of a price change ne t of the income effect. Results indicate that both uncompensated and compensated own price elasticities of the demand for fruit juices in Japan are a ll negative and statistically different from zero except for the ROW apple juice (Table 5.10). Among the 18 fruit juices four fruit juices are price elastic and two are unitary price el astic. These are Philippine pineapple juice, U.S. orange juice, the ROW ora nge juice, Italian ot her citrus juice, Is raelis other citrus juice and Brazilian orange juice. Of these, the demand for the Philippines pineapple juice is the most price elastic (-3.0543) followed by that of the U.S. orange juice (-1.5774), the ROW orange juice (-1.4521), and Italian othe r citrus juice (-1.1745). The demand for

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89 Brazilian orange juice (-1.0109) and Israelis other citrus juice (-1. 0039) are unitary price elastic. Table 5.10 Own price elasticitie s of fruit juices in Japan Uncompensated own price elasticities Compensated own price elasticities Product Estimate SE Estimate SE USA orange -1.577*** 0.3080 -1.5437*** 0.3100 Brazil orange -1.010*** 0.3404 -0.3112 0.3387 ROW orange -1.452*** 0.1649 -1.4487*** 0.1648 USA grapefruit -0.5835*** 0.1625 -0.5394*** 0.1624 Israel grapefruit -0.5453*** 0.1771 -0.5469*** 0.1762 ROW grapefruit -0.7108*** 0.1429 -0.7056*** 0.1435 USA apple -0.5191* 0.3150 -0.4722 0.3171 Chinese apple -0.5948*** 0.1848 -0.5474*** 0.1842 ROW apple 0.0609 0.2284 0.1410 0.2247 Thailand pineapple -0.8758*** 0.1945 -0.8714*** 0.1946 Philippines P. Apple -3.054*** 0.2731 -3.051*** 0.2730 ROW pineapple -0.6296** 0.3100 -0.6370** 0.3103 USA grape -0.8484*** 0.2029 -0.8404*** 0.2029 Argentina grape -0.6447 0.4223 -0.6430 0.4226 ROW grape -0.6403*** 0.2301 -0.6215*** 0.2303 Israel other citrus -1.003*** 0.1928 -0.9994*** 0.1925 Italy other citrus -1.1745*** 0.2567 -1.1725*** 0.2562 ROW other citrus -0.9584*** 0.1061 -0.9520*** 0.1060 *** (**)* significance at 1%, 5% and 10% Although the absolute value of uncompensat ed price elasticitie s of most of the fruit juices are higher than that of the re spective compensated price elasticities, the magnitude of difference between the two elas ticities is very small. Some notable exceptions are Brazilian orange juice, U.S. ora nge juice, U.S. grapefruit juices, and U.S. apple juice. These products have a relatively larger income effect. Suffice to mention the high income elasticity of the Brazilian orange juice. The uncompensated price elasticity of Brazilian orange juice is -1.01096 while that of compensated price elasticity is -.311240. This large difference is due to a la rge income effect. This is apparent in the large income elasticity of the Brazilian orange juice (2.7522). Base d on the magnitude of

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90 differences between the two el asticities, one can see whic h products have a relatively larger income effect. When commodities have elastic demand, price discounting can be an effective tool to expand exports and increasing total revenue for the exporters. Countries which can benefit from expanding their exports thr ough reducing prices are U.S. (orange juice), Brazil (orange juice), ROW (orange juice), Phi lippines (pineapples), Is rael (other citrus) and Italy (other citrus). Since the demand fo r other juices from other countries including U.S. (grapefruit, apple, grape juices) are pr ice inelastic, export supply expansion through price-oriented promotional measures, trade ne gotiations or other marketing activities that involve reduction of prices w ill result in a reduction of total revenue and a relatively smaller increase in quantity demand than countries with an elastic demand. Cross-price Elasticities Like the case with own price elasticities, two types of cross-price elasticities, uncompensated and compensated, were calc ulated. The uncompensated (Marshallian) cross-price elasticity of product i with respect to product j provides the percentage change in the quantity of product i demanded resulting from a one percent change in the price of productj, holding nominal expenditures on imported juices constant. The Slutsky (compensated) crossprice elasticity of product iwith respect to product j indicates the percentage res ponse in the quantity of product i demanded resulting from a one percent change in the price of product j, holding real expenditures on imported fruits constant. The elasticities were determin ed at the mean values of expenditure shares over the period December, 1995 to May, 2005.

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91 Results indicate that more compensated cr oss price elasticitie s are statistically significant than uncompensated price elasticities, and most products are substitutes (Tables B-1 and B-2). This is consistent with Hick’s second law of demand. Since the uncompensated price elasticities are not net of income effects, they don’t reflect the true substitution relationship. The uncompensated cross price elasticities include both substitution a nd income effects and determines if two products are gross substitutes and complements. Net substitutes and complements satisfy symmetry in the sense that it is not possible for 1qto be a substitute to 2qand for 2qto be a complement to 1q at the same time. Symmetry of sign and magnitude does not hold in gross substitutes and complements since it is possible for 1qto be a substitute to 2qand for 2qto be a complement to 1q at the same time. Notice that ne t refers to compensated demand (and thus confines itself to the substitution effect), while gross refers to uncompensated demand. Net substitute products become gross complements if the income effect is both adverse and large enough. The undesirable ch aracteristic of the gross substitutes and complements is that they are asymmetric. The compensated price elasticities, which are of income effects, are chosen to discuss the substitution and complementary relationships. They determine if two products are net substitute and complement s. Net substitutes and complements are symmetric. The whole set of the estimate s of uncompensated and compensated price elasticities are presented Tables B-1 and B-2 which provide different categories of products-gross and net substitutes, gross and net complements, gross complements and net substitutes and gross substi tutes and net complements.

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92 Gross and net substitutes have positive a nd statistically significant uncompensated and compensated cross price elasticities. Gross and net complements are negative and statistically significant uncompensated and co mpensated cross price elasticities. Gross complements and net substitutes are those products whose uncompensated cross price elasticities are negative and compensated cross price elasticities are positive while gross substitutes and net complements are those products whose uncompensated cross price elasticities are positive and co mpensated cross price elasticities are negative. Results indicate that Brazilian orange juice/U.S. gr apefruit juice, Brazilian orange juice/U.S. apple juice, Brazilian orange jui ce/Thai pineapple juice, Brazilian orange juice/ROW grape juice, and Brazilian orange juice/ROW other citrus juice are gross complements and net substitutes (Table B-1). Normally, we e xpect these products to be net substitutes. However, they are also gross complements b ecause of the strong income effect of the Brazilian orange juice. In other words, when the prices of U.S. grapefruit juice, U.S. apple juice, Thai pineapple juice, ROW grap e juice and ROW other citrus juice fall, the substitution effect may be so small that the consumer purchases more of Brazilian orange juice and less of the other juices. The estimates of the cross price elasticitie s of net substitutes and net complements are presented in Tables 5.11 and 5.12. Produc ts which are net subst itutes and thus belong to the same market structure include U.S. or ange juice/Brazilian or ange juice and U.S. orange juice/Philippines pin eapple juice, U.S. apple juice/Philippines pineapple juice (Table 5.11). Products which have compleme ntary relationship include Israelis grapefruit juice and Thai pineapple juice (Table 5.12).

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93 A decrease in the price of Brazilian orange juice has a larger negative effect on the quantity demanded of U.S. orange juice. However, the decrease in the price of U.S. orange juice has a very small negative effect on the demand for Brazilian orange juice. This is not unexpected given that Brazil ha s the highest market share (25%) in Japan’s market. Because of its high market share, it can influence the juice market in Japan. However, since the demand for Brazilian orange juice is compensated price inelastic and less uncompensated price elastic than that of U.S. orange juice, Brazil does not have a reason to decrease the price of its orange juice. The benefit to Brazil comes mainly from the increase in the level of income b ecause of its high income elasticity. Another important product to which U.S. orange juice is a substitute is the Philippines pineapple juice. A decrease in th e price of U.S. orange juice has a larger negative effect on the quantity demanded of the Philippines pineapple juice while a decrease in the price of the Philippines pineapple juice has a very small negative effect on the demand for U.S. orange juice. This implies that the U.S. may take some market share from the Philippines pineapple juice should th e price of the Philippines pineapple juice remain constant. Nonetheless, given that th e demand for both U.S. orange juice and the Philippines pineapple juice are price elastic, both have reasons to decrease price to raise total sales. The move by both countries to decrease price will positively impact the demand for their respective products. Similarly, the U.S. orange juice is also a substitute to U.S. apple juice, which, in turn, is a substitute to U.S. grap efruit juice, and vice versa. U. S. grapefruit juice is also a substitute to the ROW grapefruit juice. Since all of them are price inelastic, the change in price of one product will not have a big im pact on the demand for other product.

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94 Table 5.11 Cross-price elasticity estimates of substitutes Uncompensated cross price elasticity Compensated cross price elasticity Products Estimate SE Estimate SE US orange/Brazilian orange 1.0173*** 0.3634 1.1356*** 0.3581 US orange/U.S. apple 0.4404*** 0.1756 0.4668*** 0.1768 US orange/Philipp. pineapple 0.1186** 0.0612 0.1221** 0.0612 Brazilian orange/U.S. oranges 0.1242 0.1021 0. 3236*** 0.1020 Brazilian orange/ROW pineapple 0.0583* 0.0334 0.0830** 0.0334 ROW orange/U.S. apple 0.4038* 0.2144 0.4097* 0.2157 ROW orange/ROW apple 0.6669** 0.3216 0.6842** 0.3160 ROW orange/Argent. grape 0.1121* 0.0696 0.1131* 0.0696 U.S. grapefruit/ROW grapefruit 0.1254*** 0.0380 0.1315*** 0.0382 U.S. grapefruit/U.S. apple 0.3001*** 0.1184 0.3311*** 0.1191 U.S. grapefruit/ROW grapes 0.2235* 0.1183 0. 2589** 0.1184 Israelis g. fruit/Italian citrus 0.1808** 0.0779 0.1797** 0.0776 ROW grapefruit/U.S. grapefruit 0.9143*** 0.2781 0.9515*** 0.2769 U.S. apples/U.S. oranges 0.5358** 0.2246 0.5955*** 0.2256 U.S. apples/ROW. orange 0.2070* 0.1235 0.2338* 0.1231 U.S. apples/U.S. grapefruit 0.4047** 0.1706 0.4714*** 0.1695 U.S. apples/Philippines pineapple 0.1116** 0.0558 0.1179** 0.0557 U.S. apples/ROW citrus 0.1614* 0.0847 0.1821** 0.0844 Chinese apple/U.S. grape 0. 2601** 0.1198 0. 3005** 0.1195 ROW apple/ROW orange 0.1184* 0.0619 0.1341** 0.0619 ROW apple/Israelis other citr us 0.0703 0.0480 0.0810* 0.0479 Philippines pineapple /U.S. orange 1.1434** 0.5806 0.0810* 0.0479 Philippines pineapple /U.S. apple 0.8645** 0.4145 1.166** 0.5846 Philippines pineapple/Argentinean grape 0.6659*** 0.2540 0.8828** 0.4171 Philippines pineapple/ROW grape 0.9049* 0.5209 0.6688*** 0.2541 Philippines pineapple/Israelis citr us 0.6247** 0.2798 0.9257* 0.5210 ROW pineapple/Brazilian orange 2.5687*** 0.9605 2.3586** 0.9501 ROW pineapple/Argentinean grape 0.6218** 0.1958 0.6143*** 0.1959 U.S. grape/Chinese apple 0. 3425** 0.1406 0. 3520** 0.1400 U.S. grape/Argentinean grape 0.1731** 0.0696 0.1743** 0.0696 U.S. grape/ROW citrus 0.1362** 0.0636 0.1395** 0.0636 Argentinean grape/ROW orange 0.3934* 0.2461 0.3996* 0.2461 Argentinean grape/Philipp. pineappl e 0.5516*** 0.21 03 0.5531*** 0.2102 Argent. grape/ROW pineapple 0.5975*** 0.1909 0.5992*** 0.1911 Argent. grape/U.S. grape 1.1695** 0.4713 1.1815** 0.4718 ROW grape/U.S. grapefruit 0.2995** 0.1479 0.3231** 0.1478 ROW grape/Philipp. pineapple 0.1061** 0.0610 0.1083* 0.0609 Israelis other citrus /Brazilian orange 0.5567 0.3710 0.6092* 0.3666 Israelis other citrus /ROW a pple 0.5721 0.3642 0.6062* 0.3585 Israelis other citrus /Philipp. pin eapple 0.2154** 0. 0960 0.2169** 0.0959 Italian other citrus /Israelis grap efruit 0.2672** 0.1171 0.2702** 0.1167 ROW other citrus /U.S. apple 0.3982** 0.1902 0.4129** 0.1914 ROW other citrus /U.S. grape 0.3300** 0.1583 0.3460** 0.1579 *** (**)* significance at 1%, 5% and 10%

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95 A decrease in the price of Brazilian orange juice has a larger negative effect on the quantity demanded of the ROW pineapple jui ce. However, the decrease in price of the ROW pineapple juice has a very small ne gative effect on the demand for Brazilian orange juice. Nonetheless, given that the demand for Brazilian orange juice is compensated price inelastic, the decrease of Br azilian orange juice is disadvantageous to both Brazil and the ROW. This is because consumers don’t significantly increase the consumption of Brazilian orange juice in spite of price decrease. The best option for both countries is to increase price. This wi ll, however, benefit th e ROW more if Brazil increases the price of its orange juice. Similarly, a decrease in th e price of U.S. grape juice has a larger negative effect on the quantity demanded of Argentinean grape ju ice. However, the decrease in price of the Argentinean grape juice has a very sma ll negative effect on the demand for U.S. grape juice. Nonetheless, gi ven that the demand for grape juice from both countries is price inelastic, the move by either country to decrease the price of its grape juice is disadvantageous to both of them. This is because consumers don’t significantly increase the consumption of grape juice in spite of a decrease in the price. Hence, the product option for both countries is to raise price. This will, however, bene fit Argentina more if the U.S. increases the pri ce of its grape juice. Given that most of the imported juices are price inelastic, most exporters can’t increase their market share at the expense of their rivals through reducing prices. Some notable exceptions are the Philippines pineapple juice, U.S. and ROW orange juice. In conclusion, product differentiat ion/promotion appears to be a better option to increase

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96 market share. Product differentiation will provide exporters with some monopolistic power over their products. Table 5.12 Cross-price elasticity estimates of complements Uncompensated cross price elasticity Compensated cross price elasticity Products Estimates SE Estimates SE U.S. orange/ROW grapefruit -0.1246** 0.0560 -0.1194** 0.0563 U.S. orange/Israelis citrus -0.2249*** 0.0865 -0.2146** 0.0862 U.S. orange/ROW citrus -0.1548** 0.0730 -0.1431** 0.0729 Brazilian orange/ROW orange -0.1598*** 0.0506 -0.0706 0.0503 Brazilian orange/Chinese apple -0.2401*** 0.0823 -0.0398 0.0815 Brazilian orange/ROW apple -0 .7516*** 0.1433 -0.2968** 0.1395 Brazilian orange/U.S. grape -0 .2100*** 0.0720 -0.0389 0.0712 Brazilian orange/ROW citrus -0.0835** 0.0360 -0.0145 0.0358 U.S. grapefruit/Thai pineapple -0.2349*** 0.0436 -0.2289*** 0.0437 U.S. grapefruit/Philippines pineappl e -0.1826*** 0.04 30 -0.1785** 0.0430 U.S. grapefruit/U.S. grape -0.2259** 0.1127 -0.1920* 0.1126 ROW. grapefruit/U.S. orange -0.8079** 0.3634 -0.7745** 0.3652 ROW. grapefruit/Italian citrus -0.3978*** 0.1204 -0.3898*** 0.1200 U.S. apple/ROW apple -0.8014** 0.3183 -0.6650** 0.3111 U.S. apple/ROW pineapple -0.2705*** 0.0821 -0.2631*** 0.0822 U.S. apple/Argentinean grape -0.3180*** 0.0629 -0.3105*** 0.0629 U.S. apple/Israelis citrus -0.2350*** 0.0803 -0.2168*** 0.0799 Chinese. apple/ROW p. apple -0.1052* 0.0588 -0.0994* 0.0588 Chinese. apple/ROW grape -0 .2106* 0.1205 -0.1684 0.1206 ROW apple/Brazilian orange -0 .5797*** 0.2162 -0.4566** 0.2146 ROW apple/U.S. apple -0.2560** 0.1061 -0.2285** 0.1069 Thai pineapple/U.S. grapefruit -1.7249*** 0.3230 -1.6922*** 0.3229 Philippines pineapple/U.S. grapefruit -1.9287*** 0.4587 -1.9027*** 0.4587 ROW pineapple/U.S. apple -1.6233*** 0.5187 -1.6702*** 0.5219 ROW pineapple/Chinese apple -0 .7491* 0.4808 -0.8093* 0.4788 U.S. grape/U.S. grapefruit -0.2603* 0.1468 -0.2497* 0.1465 Argentinean grape/U.S. apple -1.9336*** 0.3870 -1.9227*** 0.3894 Israelis other citrus/U.S. ora nge -0.7189** 0.2810 -0.7040** 0.2829 Israelis other citrus/U.S. apple -0.5692*** 0.2041 -0.5575*** 0.2054 Italian other citrus/ROW grapefru it -0.2533*** 0.0771 -0.2521*** 0.0776 ROW other citrus/U.S. orange -0.4326** 0.2100 -0.4139** 0.2110 *** (**)* significance at 1%, 5% and 10%

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97 CHAPTER 6 MARKET STRUCTURES AND STRATEGY OPTIONS Market Structures This chapter discusses four market st ructure scenarios:(1) block independence (direct) with non-uniform substitution; (2) block independence (dir ect) with uniform substitution; (3) block-wise dependence with non-uniform substitution; and (4) blockwise dependence with uniform substitution. They are identified based on the structure of competition (block independence or blockwise dependence) and degree of product substitutability (uniform or non-uniform) cons istent with the assu mptions of consumer preferences. Block Independence (Direct) with Non-uniform Substitution Block independence with non-uniform s ubstitution is a case where competition between products occurs within the same product group such that the effect of a change in price of a given product on the demand fo r another product varies from product to product. This means, for example, that the e ffect of a change in price of the ROW orange juice on the demand for U.S. orange juice is different from that on the demand for Brazilian orange juice. In this market structure, consumers care about the country of origin of the product because the change in marginal ut ility of a dollar spent on product i caused by an extra dollar spent on product j is different from the change in the marginal utility of a dollar spent on product k caused by an extra dollar spent on productj. This means, for example, that the change in marginal utility of a dollar spent on Brazilian orange juice

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98 caused by an extra dollar spent on the ROW orange juice is di fferent from the change in marginal utility of a dollar spent on the U.S. orange juice caused by an extra dollar spent on the ROW orange juice. This implies th at consumers may pay a different price for products of the same group since they percei ve one product as differentiated from the other. Block Independence (Direct) wi th Uniform Substitution Block independence with uniform su bstitution is similar to the block independence with non-uniform substitution in the fact that the competition is occurring within the same product group. However, unlike the case with th e block independence with non-uniform substitution, the effect of a change in price of a given product in this market structure is the same fo r all products in the group. This means, for example, that the effect of a change in th e price of the ROW orange juice on the demand for Brazilian orange juice is the same as that on the dema nd for U.S. orange juice because the change in marginal utility of a dollar spent on Br azilian orange juice caused by an extra dollar spent on the ROW orange juice is the same as that on U.S. orange juice caused by an extra dollar spent on the ROW orange juice. Since the country of origin does not make a difference in this market structure, the co mpetition between products is so high that a slight change in the price of one product will significantly affect the demand for another product. Consumers only care about prices. They buy a certain produc t when its price is lower than the price of the ri val product since they percei ve all products in the same group as homogenous. Block-wise Dependence with Non-uniform Substitution Block-wise dependence with non-uniform substitution is the case where a product is competing with another product outside its product group such that the effect of a

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99 change in price of a product in one gr oup on the demand for another product which belongs to a different group is the same for all pairs of pr oducts in the two groups. This implies that the competition between any two products in two different groups is so high that a slight change in the price of one product in one group will significantly affect the demand for another product in another group. This is because consumers don’t care about the country of origin of the product when they choose between products that belong to different product groups. However, wh en they have to choose between products within the same group, they consider the country of origin of the product. The effect of a change in the price of a pr oduct in one group on the dema nd for another product within the same group is different for all pairs of products within that group. The competition in the block-wise dependent non-uniform substitution market structure can be described in su ch a way that the effect of, for example, a change in price of U.S. orange juice on the demand for Thai pineapple juice is the same as that of a change in the price of Brazilian orange ju ice on the demand for the Philippines pineapple juice. This implies that a slight decrease in the price of the U.S. orange juice will cause consumers to quickly switch to the Philippine s pineapple juice. Conversely, a slight decrease in the price of Brazi lian orange juice causes consumers to switch to the Thai pineapple juice. It is assumed here that the price of Brazilian orange juice does not change when the price of the U.S. ora nge juice decreases or vice versa. The reason that consumers switch from the Thai pineapple juice to the Philippines juice or vice versa is that they don’t care a bout the country of orig in of the pineapple juice. They only care about prices. They can choose to buy one juice if its price is less than that of the competitors’ price. Howeve r, when they choose between products that

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100 belong to the same group, they consider th e country of origin. Consequently, the competition between products in the same group (either within orange juice or pineapple juice group) is not as high as is between pr oducts in different groups (orange juice versus pineapple juice). For example, they may cons ider whether the orange juice is from the U.S. or Brazil or the ROW when they choose between orange juices because the change in marginal utility of a dollar spent on Br azilian orange juice caused by another dollar spent on the ROW orange juice is not the same as the change in marginal utility of a dollar spent on the U.S. orange juice caused by an extra dollar spen t on the ROW orange juice. The same is true with the pineapple jui ce in that the change in marginal utility of a dollar spent on the Philippine s pineapple juice caused by another dollar spent on the ROW pineapple juice is not the same as the ch ange in marginal utility of a dollar spent on the Thai pineapple juice caused by an extra dollar spent on the ROW pineapple juice. Consumers are focused not only on price change s. They also consider other physical attributes. Therefore, they may pay a diffe rent price for the same product differentiated by country of origin since they perceive one product as differentiated from the other. Block-wise dependence with Uniform Substitution Block-wise dependence with uniform subs titution is similar to the block-wise dependent with non-uniform substitution market structure in the fact that the competition occurs between any two products in two different groups such that the effect of a change in price of a product in one group on the dema nd for another product in another group is the same for all pairs of products in the two gr oups. However, in this market structure, the effect of a change in price of a product in one group on the demand for another product within the same group is the same for all pairs of pr oducts within that group. This implies that consumers don’t care about the country of origin of the product when

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101 they choose between products within the same group. Recall that the county of origin is important when consumers choose between produc ts within the same group in the case of block-wise dependent with non-unifor m substitution market structure. Table 6.1 Importance of country of or igin in five market structures Country of origin Market structures Models Between groups Within a group Product-wise dependence with non-uniform substitution 4.1 Important Important Block independence with non-uniform substitution 4.9 NA Important Block independence with uniform substitution 4.20 NA Not important Block-wise dependence with non-uniform substitution 4.14 Not important Important Block-wise dependence with uniform substitution 4.22 Not important Not important Note: NA not applicable Parameter and Elasticity Estimate s in Five Market Structures Changes in marginal utilities are related to cross price effects as m p u p vj ij i ij where ijvis the specific cross price effects; ip is the price of producti;iju is the rate of change of marginal utilities; jp is the price of product j and m is total expenditure. Hence, the variation in cross pr ice effects between m odels is explained by the variation in the rate of changes of marginal utilities Based on the assumptions of preference structure associated with the models, we can hypothesize which models will provide higher cross price effects. Theoretically the cross price effects of the uniform substitution models (4.20 and 4.22) should be higher than those of the non-uniform substitute models (4.9 and 4.14) because th e former models subjec t the products to be

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102 close substitutes such that extra consumpti on of one product will have a larger effect on the marginal utility of another product. Given that price elasticities are defined as i j j iq p p q where is iq and jp are the quantity and prices of products, the va riation in elasticities between models is explained by the variation in the re sponse of demand to changes in price j ip q Based on the nature and degree of substitutability that the different models impose on products, we can hypothesize which models w ill result in higher demand response to changes in price. In light of this, the uniform substitution models (4.20 and 4.22) should theoretically result in a higher demand re sponse to changes in prices than the nonuniform substitute-models (4.9 and 4.14). Parameter estimates Results indicate that while only U.S/Argen tinean grape juices are substitutes in the selected market structure discussed in chap ter 5, which is (4.1), U.S. orange/Brazilian orange juice; U.S. grapefruit/Israelis grap efruit; and U.S. grape/Argentinean grape are substitutes in all the four ma rket structure scenarios (Table 6.2). Though U.S. apple juice and Chinese apple juice are the same products di fferentiated by country of origin, there is no substitution between them in all the five market structures. Thai/Philippines pineapple juices are subs titutes only in the block independence with non-uniform substitution and block independence with uniform substitution market structures. Israelis/Italian other citrus juices are substitutes only in the block independence with uniform substitution market structure. Grapefruit/apple juices are substitutes only in the block-wise dependent with uniform substitution market structure. Apples/pineapples, pineapple/other citrus, and

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103 grape/other citrus juices are substitutes in both the block-wise dependent non-uniform substitution and the block-wise dependent uni form substitution market structures. The competition between any two of these products (e.g. U.S. apple juice and Thai pineapple juice) is so high that a slight change in the price of either product has a significant impact on the demand for other product. They are comp eting with each other regardless of the country of origin. For example, it does not ma tter whether apple juices are from the U.S. or China or pineapple juices are from Thaila nd or the Philippines. If, for example, the price of U.S. apple juice decreases, the demand for Thai pineapple juice will significantly decrease. This implies that exporters of thes e substitute products need to watch the prices of the respective substitute products. The competition betwee n the same products in the selected market structure (4.1) is not as high as the case in the block-wise dependent market structures because consumers consider the country of origin in that market structure. They don’t switch from product to product for some slight price reduction. They also value the product attributes. Orange/apple and grapefruit/pineapple are complements in both the block-wise dependent non-uniform substitution and the block-wise dependent uniform substitution market structures. The above discussion implies that if we ha ppened to pick one of the four market structure scenarios, we would come up with wrong results leading to wrong conclusions. This is because most of the results obtained from the unselected models (4.9, 4.14, 4.20 and 4.22) are inconsistent with that of the selected model (4 .1). Unlike this study, most studies pick one of these uns elected models and estimate de mand parameters. As we can

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104 see here, we found relationships between produc ts in the unselected models while there was none in the selected model. Such resu lts will lead to wr ong conclusions. Table 6.2 Relative price coefficients of fruit juices in five market structures Products Equation (4.1) Equation (4.9) Equation (4.20) Equation (4.14) Equation (4.22) U.S. orange/Brazilian orange 0395 .0579** .0620** .0482* .0614** U.S. orange/ROW orange .004 3 .0055 .0007*** .0079 .0006*** Brazilian orange/ROW orange -. 0222 .0120 .0206*** .0210* .01967*** U.S. grapefruit/Israelis grapefruit .0033 .0081* .0030** .0121*** .0090*** U.S. grapefruit/ROW grapefruit 0102*** .0058** .0056** .0047** .0057*** Israelis. grapefruit/ROW grapefruit .0022 .0026* .0006** .0024* .0005*** U.S. apple/Chinese apple -.0094 -.0099 -.0135** -.0001 -.0159** U.S. apple/ROW apple -.0445** -.0393*** -.0181*** -.0250* -.0206*** Chinese apple/ROW apple 0156 -.0157 -.0195*** -.0016 -.0160*** Thai. pineapple/Philippines pine apple .0003 .0022* .0025* -.0006 .0009 Thai. pineapple/ROW pineapple -.0005 -.0005 .0003 -.0008 .0001 Philippines pineapple/ROW p. apple .0008 .0017 .0006 .0005 .0001 U.S. grapes/Argentinean grapes .0108** .0071* .0024* .0066* .0022* U.S. grapes/ROW grapes .0081 .01492* .0171** .0106 .01513** Argentinean grapes/ROW grapes .0023 .0015 .0028* .00085 .0032* Israelis citrus/Italian citrus .0013 .0039 .0018* .0022 .0017 Israelis citrus/ROW citrus .0024 .0034* .0017* .0024 .0010 Italian citrus/ROW citrus -.0010 -.0003 .0017* -.0019 .0011 Product groups Equation (4.14) Equation (4.22) Orange/grapefruit NA NA -.0178 -.0175 Orange/apple NA NA -.2276*** -.1197*** Orange/pineapple NA NA .0134 -.0118 Orange/grape NA NA -.0186 -.0487** Orange/other citrus NA NA -.0174 -.0011 Grapefruit/apple NA NA .0081 .0406** Grapefruit/pineapple NA NA -.0309*** -.0393*** Grapefruit/grape NA NA .0154 .0128 Grapefruit/other citrus NA NA -.0094 -.0129* Apple/pineapple NA NA .0293*** .0282*** Apple/grape NA NA -.0119 -.0055 Apple/other citrus NA NA .0194 .0088 Pineapple/grape NA NA .0107 .0053 Pineapple/other citrus NA NA .0095** .0112** Grape/other citrus NA NA .0270*** .0153* Note: NA: Not applicable; all the cross price ef fects of equation (4.1) are not presented here since they don’t have counterparts in the other models for comparison. Expenditure elasticities The estimates of the expenditure elasticities in all four market structure models (4.9, 4.14, 4.20 and 4.22) are less than one except for that of Brazilian orange juice

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105 (Table 6.3). This is consistent with the es timates of (4.1). However, the expenditure elasticities of Argentinean grape juice and Isr aelis grapefruit juice are negative in (4.9) and (4.14), respectively, though none of th em are statistically significant. The expenditure elasticity of Israelis grapefruit is also negative and statistically insignificant. The negative expenditure elasticity of the ROW pineapple juice in (4 .1) turns positive in the four models. However, in both cases, it is not statistically different from zero. Table 6.3 Expenditure elasticity estimates of fruit juices in Ja pan in five market structures Product Equation (4.1) Equation (4.9) Equation (4.20) Equation (4.14) Equation (4.22) U.S. orange 0.4654*** 0.3859*** 0.3756*** 0.4763*** 0.3303*** Brazilian orange 2.7522*** 2.93 31*** 2.9254*** 2. 8040*** 3.0748*** ROW orange 0.1047 0.3316** 0.2800*** 0.1249 0.2298*** U.S. grapefruit 0.5463*** 0.3681*** 0.3563*** 0.4501*** 0.3714*** Israelis grapefruit -0.0630 0.0911 0.1199 -.07707 0.0935* ROW grapefruit 0.4603 0.0463 0.1695* 0.2792* 0.1382* U.S. apple 0.8252*** 0.7092*** 0.6275*** 0.9190*** 0.6885*** Chinese apple 0.6504*** 0.5079* ** 0.5274*** 0.68 00*** 0.1124*** ROW apple 0.4842*** 0.2847*** 0.3110*** 0.4053*** 0.2607*** Thai pineapple 0.4048* 0.4213*** 0.3795*** 0.0882 0.6196*** Philippines pineapple 0.3212 1.0363*** 1.0774*** 0.1986 0.8107*** ROW pineapple -0.8262** 0.0953 0.1150 0.0146 0.0405 U.S. grape 0.1301 0.1417* 0.1460** 0.1246* 0.1480** Argentinean grape 0.1921 -0.0091 0.1662 0.0690 0.2152* ROW grape 0.2912*** 0.1764** 0.1673** 0.2022** 0.1991** Israelis other citrus 0.2065 0. 3238*** 0.3954*** 0.2400*** 0.4390*** Italian other citrus 0.1153 0. 5177*** 0.5075*** 0.3645*** 0.5500*** ROW other citrus 0.2578 0.3604*** 0.3344*** 0.2647*** 0.2361*** *** (**)* Significance at 1%, 5% and 10% Among the 18 fruit juices, only the demand for Brazili an orange juice is expenditure elastic in all four models. This is also the case in (4.1). The expenditure elasticity estimate of Brazilian orange in the four models is higher compared to the estimates of (4.1). It has the highest value in the (4.22). Brazilian orange juice, the ROW orange juice, Israelis and Ita lian other citrus juices have consistently higher expenditure elasticity in the four models compared to (4.1 ). All four fruit juices (orange, grapefruit, apple and grape juices) that the U.S. exports to Japan are expenditure inelastic in all

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106 models. Similarly, the demand for these pr oducts exported by ROW is also expenditure inelastic. In spite of some pattern, results indicate no systematic association of estimates of particular models with particular products. In other words, a particular model does not have the highest expenditure elasticities for all products or the lowe st estimates for all products. Some products have the highest valu e in some models and some other products have their highest values in other models, im plying that the magnitude of the expenditure elasticity is not theoretically associated with a particular market structure. Given that the same price holds for each product across the fi ve models, the variation in expenditure elasticity across models is expected to resu lt from the responsiveness of the quantity demanded of the product to a unit change in price. Price elasticities Results indicate that both uncompensated and compensated price elasticities are all negative and statistically different from zero except for the ROW apple juice (Table 6.4 and 6.5). Among the 18 fruit juices, five fruit juices are consis tently uncompensated price elastic in all four models (4.9, 4.14, 4. 20 and 4.22). These are th e U.S. orange juice, Brazilian orange juice, ROW orange juice, the Philippines pineapple juice and Italian other citrus juice. These products we re also price elastic in (4.1). Similarly, the demand for the Philippines pineapple juice is consistently the most price elastic in all models. However, it is le ss elastic in the four models (4.9, 4.14, 4.20 and 4.22) as compared to (4.1). Other produc ts which are less price inelastic in the four models include U.S. grape juice, Israelis other citrus, ROW pineapple and other citrus juice (Table 6.4). Most of th e products are more price elastic in the four models than in (4.1). Such products include Brazilian or ange juice, U.S. gr apefruit juice, ROW

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107 grapefruit juice, Thai pineapple juice and Argentinean grape juice. The ROW apple juice has turned its negative sign in (4.1) to pos itive in the other four models. Generally, products which were uncompensated price inelasti c in (4.1) are also pr ice inelastic in all four models. Table 6.4 Uncompensated own price elasticity estimates of fruit juices in Japan Product Equation (4.1) Equation (4.9) Equation (4.20) Equation (4.14) Equation (4.22) U.S. orange -1.5774*** -1.5840*** -1.5483*** -1.4733*** -1.5022*** Brazilian orange -1.010 9*** -2.3729*** -2.4111** -1.4440*** -2.2496*** ROW orange -1.4521*** -1.1494*** -1.1678*** -1.0803*** -1.0559*** U.S. grapefruit -0.5835*** -0.8491*** -0.8333*** -0.6174*** -0.8185*** Israelis grapefruit -0.5453*** -0.5808*** -0.5989*** -0.4937*** -0.5330*** ROW grapefruit -0.7108*** -0.8408*** -0.8658*** -0.8974*** -0.8012*** U.S. apple -0.5191* -0.4047*** -0.5602*** -0.1928*** -0.4825*** Chinese apple -0.5948*** -0.5705*** -0.4911*** -0.460 2*** -0.0213*** ROW apple 0.0609 -0.2055*** -0.3512*** -0.1519*** -0.2287*** Thai pineapple -0.8758*** -0.9244*** -0.9458*** -1.1098*** -1.0693*** Philippines p. apple -3.0543*** -2.405*** -2.3447*** -2.8050*** -1.4017*** ROW pineapple -0.6296** -0.3087*** -0.3143*** -0.1755*** -0.0726*** U.S. grape -0.8484*** -0.6185*** -0.5819*** -0.6434*** -0.5573*** Argentinean grape -0.6447 -0.9261*** -0.8741*** -1.0261*** -1.0159*** ROW grape -0.6403*** -0.5811*** -0.6154*** -0.7682*** -0.6475*** Israelis citrus -1.0039*** -0.9253*** -0.8710*** -0.9789*** -0.9159*** Italian other citrus -1.1745*** -1. 1452*** -1.1151*** -1.1805*** -1.1478** ROW other citrus -0.9584*** -0.7813*** -0.7407*** -0.8660*** -0.5187*** *** (**)* Significant at 1%, 5% and 10% However, this is not the case with rega rd to the compensated price elasticity (Table 6.5). Only three produc ts are consistently compensate d price elastic in all four models. These are U.S. orange juice, the ROW orange juice and the Philippines pineapple juice. Brazilian or ange juice is not consistently compensated price inelastic while Italian other citrus jui ce is not consistently compensated price elastic in all four models. Results indicate that some products are more price elastic in some models than in others. For example, Brazilian orange jui ce is more price elastic in (4.22) while U.S. and Israelis grapefruit juices are more price elastic in (4.9 ) and (4.20), respectively.

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108 Table 6.5 Compensated own price elasticity estimates of fruit juices in Japan Product Equation (4.1) Equation (4.9) Equation (4.20) Equation (4.14) Equation (4.22) U.S. Orange -1.5437*** -1.5561*** -1.5211*** -1.4388*** -1.4783*** Brazilian orange -0.3112 -1.6272** -1.6674*** -0. 7311*** -1.4679*** ROW orange -1.448*** -1.1386*** -1.1587*** -1.0762*** -1.0484*** U.S. grapefruit -0.5394*** -0.8193*** -0.8045*** -0.5810*** -0.7885*** Israelis grapefruit -0.5469*** -0.5784*** -0.5958*** -0.4957*** -0.5306*** ROW grapefruit -0.7056*** -0.8402*** -0.8639*** -0.8943*** -0.7996*** U.S. apple -0.4722 -0.3644*** -0.5246*** -0.1406*** -0.4434*** Chinese apple -0.5474*** -0.5335*** -0.4527*** -0.410 6*** -0.0131*** ROW apple 0.1410 -0.1584*** -0.2998*** -0.0849*** -0.1856*** Thai pineapple -0.8714** -0.9198*** -0.9416*** -1.1088*** -1.0626*** Philippines pineapple -3.0519*** -2.3973*** -2.3365*** -2.8035*** -1.3955*** ROW pineapple -0.6370** -0.3079*** -0.3133*** -0.1754*** -0.5481*** U.S. grape -0.8404*** -0.6097*** -0.5729*** -0.6356*** -1.013*** Argentinean grape -0.6430 -0.9261*** -0.8725*** -1.0255*** -0.6346*** ROW grape -0.6215*** -0.5697*** -0.6045*** -0.7551*** -0.9062*** Israelis other citrus -0.9994*** -0. 9182*** -0.8623*** -0.9736*** -1.1383*** Italian other citrus -1.1725*** -1. 1362*** -1.1063*** -1.1742*** -0.5128*** ROW other citrus -0.9520*** -0.7723*** -0.7323*** -0.8594*** -1.4783*** *** (**)* Significant at 1%, 5% and 10% Since the models represent different market structures, and that competitiveness is associated with the degree of responsiveness, it can be implied that a product is more competitive in the market structure that is re presented by the model in which it is more price elastic. In light of this, Brazilian orange juice is more competitive in the block-wise dependent with uniform substitution market structure while U.S. grapefruit juice and Israelis grapefruit juice are more competitive in the bloc k independent with non-uniform substitution and block independence with uniform substitution market structure, respectively. Similarly, Thai pineappl e and Argentinean grape juices are more competitive in the block-wise dependent with non-uniform substitution market structure (Tables D.1-D.4).

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109 Market Strategy Options Market strategies are associated with market structure (Table 6.6). Price reduction is appropriate when the relationship between product s is uniform while product differentiation (product promotion) is appropria te when the relationship between products is non-uniform. Table 6.6 Market strategies by market structures Country of origin Market structure Models Between groups Within a group Product-wise dependence with non-uniform substitution 4.1 Product differentiation Product differentiation Block independence with non-uniform substitution 4.9 NA Product differentiation Block independence with uniform substitution 4.20 NA Price reduction Block-wise dependence with non-uniform substitution 4.14 Price reduction Product differentiation Block-wise dependence with uniform substitution 4.22 Price reduction Price reduction Note: NA not applicable

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110 CHAPTER 7 SUMMARY, CONCLUSIONS AND IMPLICATIONS Summary and Conclusions The main theme of the study is to asse ss the competitivene ss of the world’s largest exporters of fr uit juice to Japan. As a background to this theme, the study has assessed the trend and pattern of global fruit production, trad e and consumption. Results indicate that there has been a sustained in crease in global produc tion and trade of both citrus and non-citrus fruits ove r the last four decades. Mo st of the growth was accounted for by developing countries, primarily in South America but also in Asia and to a lesser extent in Africa. In South America, the volume of product ion expanded consider ably in Brazil and Mexico. In Asia, production expanded significantly in China, India and Iran. Over the last four decades, Brazil’s and China’s citrus production grew at an average rate of 4.5% and 3.0%, respectively while that of the U.S. grew at 0.6% (FAO, 2005). The growth of production of both citrus and noncitrus fruits in the U.S. has slowed since the 1980/90s compared to that of Brazil, China, Mexico and Thailand, which have increased their production significantly through expansion of cultivation. Consequently, these countries have emer ged as the world’s largest producers of oranges, apples, lemons and limes and pineappl es in the 1980/90s, respectively. The U.S. was the world’s largest producer of both fruit types before the 1980/90s. The U.S. is still the world’s largest producer of grapefruit. Although the yield per ha of both citrus and non-citrus fruits in the U.S. is relatively la rge, the growth of production in the U.S. has

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111 not been keeping up with the faster growth of fruit cultivation in the rest of the world. This may have an implication for its competitiveness in the world market. In terms of consumption, fruits are consum ed mainly in industrialized countries, not only because consumers in these countries have high income levels but also because they have increasing concerns about hea lthy eating. However, the per capita consumption of fruits in Japan is small compar ed to that of other industrialized countries, implying that there is a potential to increase exports into Japan. In order to assess the competitiveness of e xporters, which is the main theme of the study, a differential consumer demand approach has been applied. Since competitiveness is associated with the type of ma rket structure, two hypotheses (block independent/uniform substitute hypothesis and block-wise dependent/uniform substitute) are tested to identify the market structur e of Japan’s fruit juice market. The block independence /block-wise de pendence involves the relatio nship among products that belong to different product groups while that of uniform substitute hypothesis involves the relationship among products that belong to the same product group. Thus, the above two hypotheses have both between-group and within-group relationships. The analysis of market stru cture in this study has invol ved the estimation of three different versions of the Rotterdam model derived in light of the above mentioned hypotheses (block independence/uniform substitute hypothesis and block-wise dependence/uniform substitute hypothesis). Th e three versions of the Rotterdam model are the block independent uniform substitute-Rotterdam model, the block-wise dependent uniform substitute-Rotterdam model, and the relative price version of the Rotterdam model.

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112 The block independent uniform substitute -Rotterdam model describes a market structure characterized by competition between products within the same group while the block-wise dependent uniform substitute-Rotterdam model de scribes a market structure characterized by competition between product groups. Block independent with uniform substitution is a case where one product is uniformly competing with another product which belongs to the same product group. Block-wise dependent with uniform substitution is a case where products in one gr oup are competing with products in another group in a similar fashion. The relative pric e version of the Rotterd am model describes a market structure whereby i ndividual products compete w ith one another based on the country of origin. The three models were estimated for six fr uit juices (orange, apple, grapefruit, pineapple, grape, and other citrus) importe d from 18 countries on data compiled over the period January, 1995 to May, 2005. Based on the likelihood ratio tests, both hypotheses are rejected leading to the selection of the relative pr ice version of the Rotterdam demand model. This model explains the allocation decisions better compared with the other versions. Based on the parameter estimates of the sel ected model (the rela tive price version of the Rotterdam model) and average expe nditure shares, both income and price elasticities are calculated. Re sults indicate that the expenditu re elasticities for all fruit juices are positive and statistically significan t except for Israelis grapefruit and the ROW pineapple juice. The demand for Brazilian orange juice is income elastic while the demand for U.S. and the ROW products is inco me inelastic. The low income elasticities in the face of a negative population growth indi cate that the growth of demand for fruit

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113 juices will be slow. At a zero population grow th rate and 2% annual growth rate of per capita income, the demand for Brazilian orange juices grows at a bout 5.5% while the demand U.S. orange juice is 1.1%. With a declining population growth, the growth of demand for these fruit juices a nd other fruit juices from the ROW is projected to decline in the years to come. The demands for U.S. orange juice and Philippines pineapple juice are price elastic while the demand for other juices from other countries including Brazil and U.S. (grapefruit, apple, grape juices) are price inelastic. Furthermore, the cross price elasticities of most of the juices imported into Japan are below one. Some notable exceptions are the U.S/Brazilian orange juice and U.S./Philippines pineapple juice. In order to identify a marketing strategy c onsistent with the market structure, the study has tested the plausibility of price reduction and product promotion given two different market structures-block indepe ndent market competition and block-wise dependent market competition. In this study, block i ndependent (direct) market competition is defined as a competition betw een the same fruit juice with different countries of origin (example, U.S. orange juice versus Brazilian orange juice). It is based on product group type in which case a change in the price of one product in a given product group does not affect the demand for a nother product in another product group. The block-wise dependent market competition is defined here as a competition between different product groups (orange ju ice with apple juice). It in dicates that a change in the price of one product in a give n product group affect the demand for another product in another group in a similar fashion.

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114 The choice between the price reduction and product promotion in the block independent market competition involves a likelihood ratio test of two models (block independent non-uniform substitute Rotterdam model versus and block independent uniform substitute-Rotterdam model). Like wise, the choice between the same policy options in the block-wise depe ndent market competition involv es a likelihood ratio test of two other models (block-wise dependent non-uniform substitute Rotterdam model and block-wise dependent uniform s ubstitute Rotterdam model). The study finds that the plausibility of the market strategies depends on the market structure. The price reduction is pl ausible in a market structure characterized by block independent market competition model while product promotion is more plausible in a market structure characterized by a bl ock-wise dependent market competition. Implications The results of the study have important im plications to countri es exporting fruit juices to Japan for making marketing stra tegies such as price reduction, product differentiation as well as export supply plan in light of the expansi on and contraction of the Japanese market for imported fruit juices because of the change in income. The effectiveness of a supply plan in raising market share th rough export expansion depends on the estimates of expenditure and price elasticities. In li ght of this, the country which benefits the most from the growth of income in Japan is Brazil. Brazilian orange juice has the highest income elasticity and market share in Japan’s market. Given that Brazilian orange juice is income elastic and makes up the largest proportion of the total imports of fruit juices in Japan (25%), an increase in expenditure on imported fruit juices results in a far greate r increase in actual im ports. Consequently, its market share will increase upon the expansi on of the Japanese market of imported fruit

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115 juices over time. However, under conditions in which the ec onomy goes to recession, or income growth slows down, Brazil will be wo rse off because, a decrease in expenditure on imported fruit juices results in a far greate r decrease in actual imports; and, its market share will decrease upon the contra ction of the market of import ed fruit juices over time. The fact that recession has been more freque nt in Japan over the past few years requires Brazil to devise an effective export strate gy which takes account of the performance of Japan’s economy. In addition to recession, the growth of population is another major factor anticipated to affect the de mand for imported fruit juices in Japan. The Japanese population growth turned negative in 2006. Cons equently, the growth of demand for fruit juices will be slow in the years to come. Supply plan (export supply expansion or contraction) also depends on the price elasticity of demand. Given th at the demand for the U.S. ora nge juice and the Philippines pineapple juice is price elasti c, price discounting can be an effective tool for the U.S. citrus industry and the Philippines fruit industr y in expanding their exports to Japan. Since the demand for other juices from ot her countries including Brazil and U.S. (grapefruit, apple, grape juices) are pri ce inelastic, export su pply expansion through price-oriented marketing strategies, trade ne gotiations or other marketing activities that involve reduction of prices will negatively impact the exporting country of the respective product. These countries should reduce th eir cost of production, processing, and marketing so that they can stay more competitive in Japan’s import market. The degree of competition or market stru cture depends on the magnitude of cross price elasticities. Given that the cross price elasticities of mo st of the juices imported into

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116 Japan are below one, an exporter can’t take market share from a nother exporter quickly through price reductions. Some notable excep tions are the U.S/Br azilian orange juice and U.S. apple/Philippines pineapple juice. A decrease in the pric e of Brazilian orange juice has a significant negative impact on the demand for U.S. orange juice but not vice versa. However, since the demand for Brazilia n orange juice is price inelastic, Brazil does not have a reason to decrea se price under the current market structure. Nonetheless, if the current market structure changes to other market structures such as block independent competition, Brazil may a have a reason to decrease its price since the demand for its product becomes pr ice elastic in the block inde pendent market structure. Therefore, the U.S. citrus industry should pa y close attention to th e development of the Brazilian citrus industry. Assume, for example, that Br azil becomes more competitive by introducing new technologies that reduce costs. Unless there is a similar response by the U.S. citrus industry, there may be adverse effects on the demand for U.S. orange juice. Similarly, the Philippines fruit industr y should pay close attention to the development of the U.S. orange and apple sector In particular, further reductions in the cost of production, processing or marketing act ivities of the U.S. or ange and apple juices, if not matched by decreases in the Philippines pineapple juice can have adverse effects on the demand for the Philippines pineapple juice. Generally, because of the low cross price elasticities of fruit juices in Japan, product promotion and further product differentiation seems to be a more plausible option than a price reduction option for most countries to stay more competitive in Japan’s fruit juice market. The decision to use a particular mark eting strategy depends on the degree of competition or market structure. Price re duction is plausible in a market structure

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117 characterized by block independent market competition while product promotion is plausible in the market structure charact erized by block-wise dependent market competition. This implies that exporters can only compete through price reduction in the block independent market competition while they can compete through product promotion in the block-wise dependent competition. This means that if the competition among fruit juices is restricted to within the product group (for example, orange juice from one country is competing only with ora nge juice from another country), competition through price reduction can be a plausible op tion since consumers are not influenced by the origin of the product under such circum stances. However, when the competition among fruits juices transce nds beyond the product group (i .e. block-wise dependent market competition), price reduction is not a plausible option, since consumers are influenced by the origin of the product and ba se their buying decisions on the country of origin of the product. In this case, produc t promotion is a better option than a price reduction strategy.

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118 APPENDIX A PRICE COEFFICIENTS OF FRUIT JUICES IN JAPAN Table A-1 Relative price coefficients of fruit juices in Japan Products Estimates SE t-statistics p-value U.S. orange/Brazilian orange .039517 .029610 1.33459 .182 U.S orange/ROW orange .433277E-02 .753276E-02 .575191 .565 U.S orange./US grapefruit -.419052E-02 .012167 -.344408 .731 U.S. orange/Israelis grapefruit .619232E-03 .663284E-02 .093359 .926 U.S. orange/ROW grapefruit -.897070E-02 .404618E-02 -2.21708 .027 U.S orange/US apple .030962 .012648 2.44788 .014 U.S orange/Chinese apple .306733E-02 .011940 .256886 .797 U.S orange/ROW apple .018597 .020765 .895618 .370 U.S orange/Thai pineapple .633658E-02 .450683E-02 1.40600 .160 U.S orange /Philippines pineapple .870130E-02 .441177E-02 1.97229 .049 U.S orange/ROW pineapple -.396189E-02 .554243E-02 -.714829 .475 U.S orange/US grapes .013335 .011726 1.13718 .255 U.S orange/Argentinean grapes -.776343E-02 .520873E-02 -1.49046 .136 U.S orange/ROW grapes -.018846 .012377 -1.52258 .128 U.S orange/Israelis -.015829 .621954E-02 -2.54507 .011 U.S orange/Italian citrus -.233757E-02 .555697E-02 -.420656 .674 U.S orange/ROW citrus -.010770 .526588E-02 -2.04517 .041 Brazilian orange/ROW orange -.022273 .014888 -1.49601 .135 Brazilian orange/U.S grapefruit -. 026268 .020834 -1.26081 .207 Brazilian orange/Israelis grapefruit .694081E-02 .014814 .468523 .639 Brazilian orange/ROW grap efruit -.781334E-02 .877812E-02 -.890093 .373 Brazilian orange/U.S apple -.045471 .030751 -1.47867 .139 Brazilian orange/Chinese apple -.070171 .023659 -2.96594 .003 Brazilian orange/ROW apple -.176993 .040216 -4.40110 .000 Brazilian orange/Thai pineapple -.494161E-02 .671348E-02 -.736073 .462 Brazilian orange/Philippines pineapple -. 535420E-02 .643771E-02 -.831693 .406 Brazilian orange/ROW pineapple .030486 .991511E-02 3.07471 .002 Brazilian orange/U.S grape -.020175 .020691 -.975063 .330 Brazilian orange/Argentinean grape -.445004E-02 .729550E-02 -.609971 .542 Brazilian orange/ROW grape .232805E-02 .019210 .121192 .904 Brazilian orange/Israelis citrus .7 67426E-02 .933543E-02 .822057 .411 Brazilian orange/Italian citrus .71 7348E-02 .800765E-02 .895829 .370 Brazilian orange/ROW citrus -.011894 .010566 -1.12570 .260 ROW orange/U.S grapefruit .447447E-02 .571291E-02 .783221 .433 ROW orange/Israelis grapefruit .293407E-02 .351068E-02 .835756 .403 ROW orange/ROW grapefruit .254609E-02 .206505E-02 1.23294 .218 ROW orange/U.S apple .012993 .693677E-02 1.87306 .061 ROW orange/Chinese apple .121044E-02 .602607E-02 .200867 .841 ROW orange/ROW apple .021687 .010393 2.08664 .037 ROW orange/Thai pineapple .154743E-02 .200063E-02 .773470 .439 ROW orange/Philippines pineapple -.822573E-03 .195193E-02 -.421414 .673 ROW orange/ROW pineapple -.178218E-02 .269732E-02 -.660720 .509 ROW orange/U.S grape .819075E-03 .552104E-02 .148355 .882 ROW orange/Argentinean grape .365527E-02 .225755E-02 1.61913 .105

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119 Table A-1 Continued Products Estimates SE t-statistics p-value ROW orange/ROW grape .278362E-02 .557101E-02 .499662 .617 ROW orange/Israelis citrus .223843E-02 .280532E-02 .797922 .425 ROW orange/Italian citrus .240343E-02 .243674E-02 .986331 .324 ROW orange/ROW citrus .207073E-02 .268926E-02 .770001 .441 U.S grapefruit/Israelis grapefruit .3 33785E-02 .499656E-02 .668030 .504 U.S grapefruit/ROW grapefruit .0 10222 .309575E-02 3.30180 .001 U.S grapefruit/U.S Apple .023026 .961601E-02 2.39453 .017 U.S grapefruit/Chinese Apple -.224555E-02 .914467E-02 -.245559 .806 U.S grapefruit/ROW Apple -.012776 .016320 -.782836 .434 U.S grapefruit/Thai pineapple -.018868 .353346E-02 -5.33991 .000 U.S grapefruit/Philippines pineapple -.014627 .348184E-02 -4.20103 .000 U.S grapefruit/ROW pineapple -.250641E-02 .424153E-02 -.590921 .555 U.S grapefruit/U.S grape -.016172 .912613E-02 -1.77205 .076 U.S grapefruit/Argentinean grape .258171E-02 .420159E-02 .614460 .539 U.S grapefruit/ROW grape .019431 .958208E-02 2.02785 .043 U.S grapefruit/Israelis citrus .299584E-02 .490923E-02 .610246 .542 U.S grapefruit/Italian citrus -.5559 28E-02 .446225E-02 -1.24585 .213 U.S grapefruit/R citrus .422583E-02 .401890E-02 1.05149 .293 Israelis grapefruit/ROW grapefruit .2 23771E-02 .191149E-02 1.17066 .242 Israelis grapefruit/U.S apple -.5487 59E-02 .656412E-02 -.835997 .403 Israelis grapefruit/Chinese apple .749554E-02 .548065E-02 1.36764 .171 Israelis grapefruit/ROW apple -.384568E-02 .899250E-02 -.427654 .669 Israelis grapefruit/Thai. pineapple -. 518240E-03 .172109E-02 -.301112 .763 Israelis grapefruit/Philippines pineapple .218158E-02 .164435E-02 1.32671 .185 Israelis grapefruit/ROW pineapple -.184889E-03 .240440E-02 -.076896 .939 Israelis grapefruit/U.S grape -.2122 74E-02 .491121E-02 -.432225 .666 Israelis grapefruit/Argentinean grape .166582E-02 .185501E-02 .898013 .369 Israelis grapefruit/ROW grape -.3415 07E-03 .471477E-02 -.072433 .942 Israelis grapefruit/Israelis citrus -. 161237E-02 .235387E-02 -.684987 .493 Israelis grapefruit/Italia n citrus .467622E-02 .201741E-02 2.31794 .020 Israelis grapefruit/ROW citrus -.7 82211E-03 .245829E-02 -.318193 .750 ROW grapefruit/U.S apple .456180E-03 .376387E-02 .121200 .904 ROW grapefruit/Chinese apple -.600853E-03 .337186E-02 -.178197 .859 ROW grapefruit/ROW apple .661544E-03 .574249E-02 .115202 .908 ROW grapefruit/Thai. pineapple -.622186E-03 .109468E-02 -.568374 .570 ROW grapefruit/Philippines pineapple .357053E-05 .106516E-02 .003352 .997 ROW grapefruit/ROW pineapple .105967E-02 .147464E-02 .718598 .472 ROW grapefruit/U.S grape .26643 9E-02 .300608E-02 .886336 .375 ROW grapefruit/Argentinean grape .486089E-03 .123008E-02 .395170 .693 ROW grapefruit/ROW grape .275034E-02 .302456E-02 .909338 .363 ROW grapefruit/Israelis c itrus -.253563E-03 .153248E-02 -.165459 .869 ROW grapefruit/Italian citrus -.4375 47E-02 .133541E-02 -3.27649 .001 ROW grapefruit/ROW citrus -.183852 E-02 .146474E-02 -1.25519 .209 U.S Apple/Chinese apple -.946959E-02 .010773 -.878992 .379 U.S Apple/ROW apple -.044572 .017847 -2.49741 .013 U.S Apple/Thai pineapple .308132E-02 .323551E-02 .952346 .341 U.S Apple/Philippines pineapple .649085E-02 .313969E-02 2.06736 .039 U.S Apple/ROW pineapple -.014317 .464092E-02 -3.08495 .002 U.S Apple/U.S grape .935256E-02 .942572E-02 .992238 .321 U.S Apple/Argentinean grape -.017787 .354220E-02 -5.02142 .000 U.S Apple/ROW grape -.114664E-02 .908601E-02 -.126199 .900 U.S Apple/Israelis citrus -.012704 .450465E-02 -2.82024 .005 U.S Apple/Italian citrus .647074E-03 .379601E-02 .170461 .865

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120 Table A-1 Continued Products Estimates SE t-statistics p-value U.S Apple/ROW citrus .979529E-02 .476176E-02 2.05707 .040 Chinese Apple/ROW apple .015667 .016813 .931881 .351 Chinese Apple/Thai. pineapple .225042E-02 .321070E-02 .700913 .483 Chinese Apple/Philippines pineapple .380558E-02 .308706E-02 1.23275 .218 Chinese Apple/ROW pineapple -.660875E-02 .431613E-02 -1.53117 .126 Chinese Apple/U.S grape .021190 .875605E-02 2.42002 .016 Chinese Apple/Argentinean grape -.122730E-02 .353006E-02 -.347671 .728 Chinese Apple/ROW grape -.013886 .881970E-02 -1.57448 .115 Chinese Apple/Israelis citrus .699838E-03 .446597E-02 .156704 .875 Chinese Apple/Italian citrus .246934E-02 .378790E-02 .651903 .514 Chinese Apple/ROW citrus .444569E-02 .425468E-02 1.04489 .296 ROW Apple/Thai pineapple .681398E-02 .572009E-02 1.19124 .234 ROW Apple/Philippines pineapple .162458E-04 .564016E-02 .002880 .998 ROW Apple/ROW pineapple .956209E-02 .733031E-02 1.30446 .192 ROW Apple/U.S grape -.456384E-02 .015306 -.298180 .766 ROW Apple/Argentinean grape .696273E-02 .661634E-02 1.05235 .293 ROW Apple/ROW grape -.014143 .016106 -.878080 .380 ROW Apple/Israelis citrus .012733 .803583E-02 1.58456 .113 ROW Apple/Italian citrus .227829E-02 .709473E-02 .321124 .748 ROW Apple/ROW citrus .516621E-02 .720261E-02 .717269 .473 Thai Pineapple/Philippines pineapple .396233E-03 .152006E-02 .260668 .794 Thai pineapple /ROW pineapple -.557884E-03 .154019E-02 -.362217 .717 Thai. pineapple /U.S grape .197651E-02 .356764E-02 .554011 .580 Thai pineapple /Argentinean grape -.135005E-02 .197110E-02 -.684921 .493 Thai pineapple /ROW grape .133803E-02 .401321E-02 .333407 .739 Thai pineapple /Israelis citrus .283899E-02 .214116E-02 1.32591 .185 Thai Pineapple /Italian citrus .269542E-02 .210120E-02 1.28280 .200 Thai Pineapple /ROW citrus -.874562E-03 .140846E-02 -.620935 .535 Philippines Pineapple /ROW pineapple .878964E-03 .150772E-02 .582977 .560 Philippines Pineapple /U.S grape -.232261E-02 .352548E-02 -.658807 .510 Philippines Pineapple /Argentinean grape .506606E-02 .192841E-02 2.62707 .009 Philippines Pineapple /ROW grape .694251E-02 .395334E-02 1.75611 .079 Philippines Pineapple /Israelis other .477432E-02 .212146E-02 2.25049 .024 Philippines Pineapple /Italian other .162857E-02 .207686E-02 .784150 .433 Philippines Pineapple /ROW other .990120E-03 .138554E-02 .714608 .475 ROW Pineapple /U.S grape .111495E-03 .410181E-02 .027182 .978 ROW Pineapple /Argentinean grape .551961E-02 .175497E-02 3.14513 .002 ROW Pineapple /ROW grape -.688996E-04 .423046E-02 -.016287 .987 ROW Pineapple /Israelis citrus .226408E-02 .217128E-02 1.04274 .297 ROW Pineapple /Italian citrus .172359E-02 .189352E-02 .910254 .363 ROW Pineapple /ROW citrus -.241507E-02 .192703E-02 -1.25326 .210 U.S grape /Argentinean grape .010813 .432607E-02 2.49947 .012 U.S grape /ROW grape .816719E-02 .988500E-02 .826220 .409 U.S grape /Israelis citrus .513264E-04 .497369E-02 .010320 .992 U.S grape /Italian citrus .600603E-02 .461376E-02 1.30177 .193 U.S grape /ROW citrus .857491E-02 .395721E-02 2.16691 .030 Argentinean grape /ROW grape .235407E-02 .506562E-02 .464715 .642 Argentinean grape /Israelis citrus -.334719E-03 .278251E-02 -.120294 .904 Argentinean grape /Italian citrus -.261527E-02 .296975E-02 -.880638 .379 Argentinean grape /ROW citrus -.864642E-03 .157661E-02 -.548419 .583 ROW grape /Israelis citrus .454343E-02 .563118E-02 .806836 .420 ROW grape /Italian citrus -.451451E-03 .549765E-02 -.082117 .935 ROW grape /ROW citrus .495812E-02 .392222E-02 1.26411 .206

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121 Table A-1 Continued Products Estimates SE t-statistics p-value Israelis citrus /Italian citrus .131769E-02 .300401E-02 .438645 .661 Israelis citrus /ROW citrus .245213E-02 .197170E-02 1.24366 .214 Italian citrus/ROW citrus -.102125E-02 .169281E-02 -.603289 .546 Table A-2 Slutsky price coefficien ts of fruit juices in Japan Products Estimates SE t-statistics p-value U.S orange/Brazilian orange .082282 .025949 3.17097 .002 U.S orange/ROW orange .454009E-02 .756354E-02 .600261 .548 U.S orange/U.S grapefruit -.149260E-02 .012198 -.122367 .903 U.S orange/Israelis grapefruit .517986E-03 .666639E-02 .077701 .938 U.S orange/ROW grapefruit -.865542E-02 .408132E-02 -2.12074 .034 U.S orange/U.S apple .033827 .012814 2.63988 .008 U.S orange/Chinese apple .596499E-02 .011921 .500388 .617 U.S orange/ROW apple .023483 .020525 1.14412 .253 U.S orange/Thai pineapple .660704E-02 .453142E-02 1.45805 .145 U.S orange/Philippines pineapple .885034E-02 .443495E-02 1.99559 .046 U.S orange/ROW pineapple -.441460E-02 .556065E-02 -.793900 .427 U.S orange/U.S grapes .013827 .011784 1.17337 .241 U.S orange/Argentinean grapes -.765712E-02 .524138E-02 -1.46090 .144 U.S orange/ROW grapes -.017687 .012464 -1.41903 .156 U.S orange/Israelis -.015551 .624978E-02 -2.48818 .013 U.S orange/Italian other citrus -.221666E-02 .558774E-02 -.396701 .692 U.S orange/ROW other citrus -.010372 .528722E-02 -1.96173 .050 Brazilian orange/ROW orange -.017968 .012793 -1.40455 .160 Brazilian orange/U.S grapefruit .029763 .018410 1.61672 .106 Brazilian orange/Israelis grapefruit .485829E-02 .012708 .382292 .702 Brazilian orange/row grapefruit -.1293 30E-02 .754557E-02 -.171399 .864 Brazilian orange/U.S apple .013972 .026524 .526754 .598 Brazilian orange/Chinese apple -.010119 .020733 -.488079 .625 Brazilian orange/ROW apple -.075466 .035468 -2.12770 .033 Brazilian orange/Thai pineapple .674517E-03 .581514E-02 .115993 .908 Brazilian orange/Philippines pineapple -. 226599E-02 .558795E-02 -.405514 .685 Brazilian orange/ROW pineapple .021105 .850128E-02 2.48251 .013 Brazilian orange/U.S grape -.9911 97E-02 .018119 -.547062 .584 Brazilian orange/Argentinean grape -.221559E-02 .630536E-02 -.351382 .725 Brazilian orange/ROW grape .026257 .016793 1.56364 .118 Brazilian orange/Israelis other citrus .013457 .809779E-02 1.66179 .097 Brazilian orange/Italian other citrus .970311E-02 .705267E-02 1.37581 .169 Brazilian orange/ROW other citrus -.3 70368E-02 .911090E-02 -.406512 .684 ROW orange/U.S grapefruit .474842E-02 .569236E-02 .834174 .404 ROW orange/Israelis grapefruit .292449E-02 .351147E-02 .832838 .405 ROW orange/ROW grapefruit .257776E-02 .207234E-02 1.24389 .214 ROW orange/U.S Apple .013279 .699220E-02 1.89916 .058 ROW orange/Chinese Apple .150242E-02 .599242E-02 .250721 .802 ROW orange/ROW Apple .022175 .010243 2.16488 .030 ROW orange/Thai pineapple .157489E-02 .200135E-02 .786913 .431 ROW orange/Philippines pineapple -.807215E-03 .195074E-02 -.413799 .679 ROW orange/ROW pineapple -.182784E-02 .269182E-02 -.679033 .497 ROW orange/U.S grape .869056E-03 .551943E-02 .157454 .875 ROW orange/Argentinean grape .366619E-02 .225791E-02 1.62371 .104 ROW orange/ROW grape .290152E-02 .557597E-02 .520361 .603 ROW orange/Israelis other citrus .226608E-02 .280284E-02 .808496 .419

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122 Table A-2 Continued Products Estimates SE t-statistics p-value ROW orange/Italian other citrus .241610E-02 .243604E-02 .991814 .321 ROW orange/ROW other citrus .211060E-02 .268820E-02 .785135 .432 U.S grapefruit/Israelis grapefruit .3 20838E-02 .497839E-02 .644463 .519 U.S grapefruit/ROW grapefruit .0 10633 .309481E-02 3.43581 .001 U.S grapefruit/U.S Apple .026777 .963178E-02 2.78009 .005 U.S grapefruit/Chinese Apple .154646E-02 .905958E-02 .170699 .864 U.S grapefruit/ROW Apple -.636382E-02 .016073 -.395942 .692 U.S grapefruit/Thai pineapple -.018514 .353372E-02 -5.23931 .000 U.S grapefruit/Philippines pineapple -.014434 .347973E-02 -4.14795 .000 U.S grapefruit/ROW pineapple -.309955E-02 .422474E-02 -.733665 .463 U.S grapefruit/U.S grape -.015526 .910662E-02 -1.70493 .088 U.S grapefruit/Argentinean grape .272285E-02 .419966E-02 .648351 .517 U.S grapefruit/ROW grape .020940 .957948E-02 2.18594 .029 U.S grapefruit/Israelis other citrus .336212E-02 .490233E-02 .685820 .493 U.S grapefruit/Italian other citrus -.5 40124E-02 .446068E-02 -1.21086 .226 U.S grapefruit/R other citrus .474331E-02 .400508E-02 1.18432 .236 Israelis grapefruit/ROW grapefruit .2 22278E-02 .191813E-02 1.15882 .247 Israelis grapefruit/U.S apple -.5626 06E-02 .662787E-02 -.848850 .396 Israelis grapefruit/Chinese apple .735612E-02 .544864E-02 1.35009 .177 Israelis grapefruit/ROW apple -.409241E-02 .885256E-02 -.462286 .644 Israelis grapefruit/Thai pineapple -.531611E-03 .172118E-02 -.308865 .757 Israelis grapefruit/Philipp pineapple .217403E-02 .164367E-02 1.32267 .186 Israelis grapefruit/ROW pineapple -.162539E-03 .240061E-02 -.067707 .946 Israelis grapefruit/U.S grape -.2148 27E-02 .491086E-02 -.437453 .662 Israelis grapefruit/Argentinean grape .166068E-02 .185574E-02 .894890 .371 Israelis grapefruit/ROW grape -.3951 91E-03 .472069E-02 -.083715 .933 Israelis grapefruit/Israelis other citrus -.162520E-02 .235185E-02 -.691032 .490 Israelis grapefruit/Italian other citrus .467061E-02 .201697E-02 2.31565 .021 Israelis grapefruit/ROW other citrus -. 802191E-03 .245760E-02 -.326413 .744 ROW grapefruit/U.S apple .894266E-03 .380753E-02 .234868 .814 ROW grapefruit/Chinese apple -.158872E-03 .336522E-02 -.047210 .962 ROW grapefruit/ROW apple .140690E-02 .566142E-02 .248506 .804 ROW grapefruit/Thai pineapple -.580800E-03 .110019E-02 -.527908 .598 ROW grapefruit/Philippines pineapple .260812E-04 .106917E-02 .024394 .981 ROW grapefruit/ROW pineapple .990709E-03 .147715E-02 .670690 .502 ROW grapefruit/U.S grape .27397 8E-02 .301673E-02 .908194 .364 ROW grapefruit/Argentinean grape .502918E-03 .123608E-02 .406864 .684 ROW grapefruit/ROW grape .292486E-02 .304144E-02 .961670 .336 ROW grapefruit/Israelis other citrus -. 210905E-03 .153769E-02 -.137157 .891 ROW grapefruit/Italian other citrus -.4 35647E-02 .134108E-02 -3.24847 .001 ROW grapefruit/ROW other citrus -.1 77760E-02 .146947E-02 -1.20969 .226 U.S Apple/Chinese apple -.544442E-02 .010787 -.504716 .614 U.S Apple/ROW apple -.037772 .017674 -2.13718 .033 U.S Apple/Thai pineapple .345748E-02 .326233E-02 1.05982 .289 U.S Apple/Philippines pineapple .669691E-02 .316462E-02 2.11618 .034 U.S Apple/ROW pineapple -.014945 .467049E-02 -3.19985 .001 U.S Apple/U.S grape .010037 .949319E-02 1.05732 .290 U.S Apple/Argentinean grape -.017637 .357247E-02 -4.93679 .000 U.S Apple/ROW grape .459419E-03 .916707E-02 .050116 .960 U.S Apple/Israelis other citrus -.012315 .453846E-02 -2.71349 .007 U.S Apple/Italian other citrus .815445E-03 .382526E-02 .213174 .831 U.S Apple/ROW other citrus .010345 .479600E-02 2.15703 .031 Chinese Apple/ROW apple .022531 .016566 1.36008 .174

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123 Table A-2 Continued Products Estimates SE t-statistics p-value Chinese Apple/Thai pineappl e .263183E-02 .319510E-02 .823708 .410 Chinese Apple/Philipp pineap ple .401380E-02 .306819E-02 1.30820 .191 Chinese Apple/ROW pineapple -.724174E-02 .428482E-02 -1.69009 .091 Chinese Apple/U.S grap e .021882 .870380E-02 2.51403 .012 Chinese Apple/Argentinean gr ape -.107513E-02 .351270E-02 -.306070 .760 Chinese Apple/ROW grape -.012265 .878017E-02 -1.39689 .162 Chinese Apple/Israelis other ci trus .109458E-02 .444353E-02 .246332 .805 Chinese Apple/Italian other c itrus .263951E-02 376621E-02 .700842 .483 Chinese Apple/ROW other citr us .499918E-02 .422676E-02 1.18274 .237 ROW Apple/Thai pineapple .745366E-02 .563993E-02 1.32159 .186 ROW Apple/Philippines pineappl e .371444E-03 .555838E-02 .066826 .947 ROW Apple/ROW pineapple .849048E-02 .720091E-02 1.17909 .238 ROW Apple/U.S grape -.338917E-02 .015068 -.224920 .822 ROW Apple/Argentinean grap e .721368E-02 .652161E-02 1.10612 .269 ROW Apple/ROW grape -.011404 .015899 -.717273 .473 ROW Apple/Israelis other ci trus .013391 .791921E-02 1.69099 .091 ROW Apple/Italian other citr us .256592E-02 699084E-02 .367040 .714 ROW Apple/ROW other citrus .610075E-02 .708296E-02 .861327 .389 Thai pineapple/Philippines pin eapple .416619E-03 .152016E-02 .274062 .784 Thai pineapple /ROW pinea pple -.617166E-03 .153899E-02 -.401021 .688 Thai pineapple /U.S grap e .204054E-02 .356986E-02 .571603 .568 Thai pineapple /Argentinean gr ape -.133573E-02 .197277E-02 -.677082 .498 Thai pineapple /ROW grap e .149119E-02 .401579E-02 .371332 .710 Thai pineapple /Israelis other citrus .287536E-02 .214106E-02 1.34296 .179 Thai pineapple /Italian other citrus .271276E-02 .210182E-02 1.29067 .197 Thai pineapple /ROW citrus -.822354E-03 .141002E-02 -.583223 .560 Philippines pineapple /ROW Pin eapple .846751E-03 .150464E-02 .562759 .574 Philippines pineapple /U.S gr ape -.228425E-02 .352466E-02 -.648076 .517 Philippines pineapple /Argentinean grape .507384E-02 .192828E-02 2.63128 .009 Philippines pineapple /ROW gr ape .702281E-02 .395287E-02 1.77663 .076 Philippines pineapple /Israelis ot her .479275E-02 .211923E-02 2.26155 .024 Philippines pineapple /Italian ot her .163808E-02 .207549E-02 .789249 .430 Philippines pineapple /ROW othe r .101901E-02 .138595E-02 .735243 .462 ROW pineapple /U.S grape .336520E-05 .409543E-02 .008216 .999 ROW pineapple /Argentinean gr ape .549660E-02 .175303E-02 3.13549 .002 ROW pineapple /ROW grape -.322326E-03 .422837E-02 -.076229 .939 ROW pineapple /Israelis citr us .220419E-02 216736E-02 1.01700 .309 ROW pineapple /Italian citr us .169638E-02 189107E-02 .897043 .370 ROW pineapple /ROW citrus -.250214E-02 .192251E-02 -1.30150 .193 U.S grape /Argentinean gr ape .010838 .432789E-02 2.50415 .012 U.S grape /ROW grape 844149E-02 .988916E-02 .853610 .393 U.S grape /Israelis citrus .113882E-03 .497135E-02 .022908 .982 U.S grape /Italian citrus .603460E-02 .461373E-02 1.30797 .191 U.S grape /ROW citrus .867090E-02 .395775E-02 2.19087 .028 Argentinean grape /ROW grap e .241619E-02 .506416E-02 .477115 .633 Argentinean grape /Israelis ci trus -.319937E-03 .278183E-02 -.115010 .908 Argentinean grape /Italian citr us -.260801E-02 .296938E-02 -.878300 .380 Argentinean grape /ROW citr us -.844436E-03 .157830E-02 -.535029 .593 ROW grape /Israelis other citr us .470066E-02 .562912E-02 .835060 .404 ROW grape /Italian other citr us -.384002E-03 .549607E-02 -.069868 .944 ROW grape /ROW other citrus .517972E-02 .392754E-02 1.31882 .187 Israelis other citrus /Italian citrus .133399E-02 .300169E-02 .444412 .657 Israelis other citrus /ROW ci trus .250478E-02 .197167E-02 1.27039 .204 Italian other citrus/ROW other citrus -.997712E-03 .169376E-02 -.589052 .556

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124 APPENDIX B PRICE ELASTICITES OF FR UIT JUICES IN JAPAN Table B-1 Uncompensated price elasticities of fruit juices in Japan Products Estimates SE t-statistics P-value U.S orange /Brazilian orange 1.01730 .363449 2.79902 .005 U.S orange /ROW orange .047577 .104560 .455020 .649 U.S orange /U.S grapefruit -.058235 .168667 -.345268 .730 U.S orange /Israelis grapefruit -.004943 .092568 -.053402 .957 U.S orange /ROW grapefruit -.124661 .056044 -2.22433 .026 U.S orange /U.S apple .440432 .175644 2.50753 .012 U.S orange /Chinese apple .048443 .165292 .293073 .769 U.S orange /ROW apple .247186 .288515 .856754 .392 U.S orange /Thai pineapple .086096 .062549 1.37645 .169 U.S orange /Philippines pineapple .118619 .061281 1.93566 .053 U.S orange /ROW pineapple -.065094 .076698 -.848701 .396 U.S orange /U.S grape .161903 .162868 .994076 .320 U.S orange /Argentinean grape -.109951 .072340 -1.51992 .129 U.S orange /ROW grape -.274281 .171684 -1.59759 .110 U.S orange /Israelis citrus -.224905 .086521 -2.59945 .009 U.S orange /Italian citrus -.038637 .077298 -.499848 .617 U.S orange /ROW citrus -.154814 .073022 -2.12010 .034 Brazilian orange/U.S orange .124232 .102147 1.21621 .224 Brazilian orange /ROW orange -.159867 .050603 -3.15923 .002 Brazilian orange /U.S grapefruit -.105466 .073526 -1.43440 .151 Brazilian orange /Israelis grapefru it -.052393 .050359 -1.04039 .298 Brazilian orange /ROW grapefruit -.035843 .029621 -1.21003 .226 Brazilian orange /U.S apple -.101359 .104006 -.974551 .330 Brazilian orange /Chinese apple -.240162 .082360 -2.91601 .004 Brazilian orange /ROW apple -.751689 .143362 -5.24330 .000 Brazilian orange /Thai Pineapple -.027458 .022913 -1.19838 .231 Brazilian orange /Philippines pineapple -.029791 .022038 -1.35177 .176 Brazilian orange /ROW Pineapple .058385 .033422 1.74692 .081 Brazilian orange /U.S grape -.210059 .072015 -2.91687 .004 Brazilian orange /Argentinean grape -.033961 .024833 -1.36754 .171 Brazilian orange /ROW grape -.075079 .066525 -1.12859 .259 Brazilian orange /Israelis citrus -.007861 .032109 -.244832 .807 Brazilian orange /Italian citrus -.009394 .027917 -.336525 .736 Brazilian orange /ROW citrus -.083522 .036088 -2.31443 .021 ROW orange/U.S orange .132507 .232275 .570473 .568 ROW orange/Brazilian orange -.581065 .398317 -1.45880 .145 ROW orange /U.S grapefruit .138055 .176274 .783184 .434 ROW orange /Israelis grapefruit .087521 .108918 .803547 .422 ROW orange /ROW grapefruit .078372 .063671 1.23090 .218 ROW orange /U.S apple .403814 .214469 1.88285 .060 ROW orange /Chinese apple .038737 .185700 .208600 .835 ROW orange /ROW apple .666951 .321627 2.07368 .038 ROW orange /Thai pineapple .047451 .061743 .768529 .442 ROW orange /Philippines pineapple -.025703 .060271 -.426454 .670

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125 Table B-1 Continued Products Estimates SE t-statistics P-value ROW orange /ROW pineapple -.057339 .082988 -.690934 .490 ROW orange /U.S grape .020307 .170785 .118905 .905 ROW orange /Argentinean grape .112168 .069678 1.60980 .107 ROW orange /ROW grape .082746 .171975 .481150 .630 ROW orange /Israelis citrus .067612 .086753 .779363 .436 ROW orange /Italian citrus .072744 .075386 .964951 .335 ROW orange /ROW citrus .062504 .083084 .752293 .452 U.S grapefruit/U.S orange -.058049 .149991 -.387013 .699 U.S grapefruit/Brazilian orange .229191 .229876 .997020 .319 U.S grapefruit/ROW orange .041020 .070458 .582192 .560 U.S grapefruit/Israelis grapefruit .025485 .061894 .411754 .681 U.S grapefruit /ROW grapefruit .125402 .038093 3.29204 .001 U.S grapefruit /U.S apple .300139 .118405 2.53486 .011 U.S grapefruit /Chinese apple -.020650 .112550 -.183474 .854 U.S grapefruit /ROW apple -.169006 .202082 -.836322 .403 U.S grapefruit /Thai Pineapple -.234957 .043684 -5.37853 .000 U.S grapefruit /Philippines Pineapple -.182657 .043078 -4.24016 .000 U.S grapefruit /ROW Pineapple -.043223 .052210 -.827867 .408 U.S grapefruit /U.S grape -.225985 .112734 -2.00459 .045 U.S grapefruit /Argentinean grape .028663 .051931 .551957 .581 U.S grapefruit /ROW grape .223572 .118393 1.88839 .059 U.S grapefruit /Israelis citrus .029513 .060780 .485568 .627 U.S grapefruit /Italian citrus -.076243 .055296 -1.37881 .168 U.S grapefruit /ROW citrus .044975 .049553 .907601 .364 Israelis grapefruit/U.S orange .024507 .255321 .095986 .924 Israelis grapefruit/Brazilian orange .203036 .492739 .412056 .680 Israelis grapefruit/ROW orange .114612 .135514 .845760 .398 Israelis grapefruit/U.S grapefruit .128595 .192431 .668265 .504 Israelis grapefruit/ROW grapefruit .086263 .073575 1.17246 .241 Israelis grapefruit /U.S apple -.212975 .253414 -.840422 .401 Israelis grapefruit /Chinese apple .287740 .210750 1.36532 .172 Israelis grapefruit /ROW apple -.147102 .347287 -.423574 .672 Israelis grapefruit /Thai Pineapple -.019773 .066299 -.298233 .766 Israelis grapefruit /Philippines Pineapple .084160 .063374 1.32800 .184 Israelis grapefruit /ROW Pineapple -.005692 .092335 -.061647 .951 Israelis grapefruit /U.S grape -.078771 .189903 -.414796 .678 Israelis grapefruit /Argentinean grape .064501 .071452 .902717 .367 Israelis grapefruit /ROW grape -.011125 .181725 -.061218 .951 Israelis grapefruit /Isr aelis citrus -.061164 .090942 -.672561 .501 Israelis grapefruit /Italian citrus .180869 .077938 2.32068 .020 Israelis grapefruit /ROW citrus -.029298 .094840 -.308917 .757 ROW grapefruit/U.S orange -.8 07905 .363400 -2.22318 .026 ROW grapefruit/Brazilian orange -.232761 .682333 -.341125 .733 ROW grapefruit/ROW orange .215761 .185835 1.16103 .246 ROW grapefruit/U.S grapefruit .914322 .278100 3.28774 .001 ROW grapefruit/Israelis grapefru it .186953 .172509 1.08373 .278 ROW grapefruit /U.S apple .053883 .338594 .159136 .874 ROW grapefruit /Chinese apple -.047727 .302162 -.157950 .874 ROW grapefruit /ROW apple .049827 .517778 .096232 .923 ROW grapefruit /Thai Pineapple -.057011 .098391 -.579430 .562 ROW grapefruit /Philippines Pineapple -.001157 .095792 -.012087 .990 ROW grapefruit /ROW Pineapple .084538 .132043 .640227 .522 ROW grapefruit /U.S grape .216565 .271057 .798963 .424

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126 Table B-1 Continued Products Estimates SE t-statistics P-value ROW grapefruit /Argentinean grape .040783 .110599 .368743 .712 ROW grapefruit /ROW grape .231909 .271878 .852989 .394 ROW grapefruit /Israelis citrus -.029041 .137973 -.210481 .833 ROW grapefruit /Italian citrus -.397805 .120468 -3.30217 .001 ROW grapefruit /ROW citrus -.170606 .131778 -1.29464 .195 U.S apple/U.S orange .535800 .224661 2.38492 .017 U.S apple/Brazilian orange .036199 .472513 .076609 .939 U.S apple/ROW orange .207066 .123565 1.67576 .094 U.S apple/U.S grapefruit .404743 .170654 2.37172 .018 U.S apple/Israelis grapefruit -.120498 .117512 -1.02541 .305 U.S apple/ROW grapefruit .006523 .066747 .097738 .922 U.S apple /Chinese apple -.155936 .190625 -.818024 .413 U.S apple /ROW apple -.801436 .318350 -2.51747 .012 U.S apple /Thai Pineapple .051848 .057452 .902448 .367 U.S apple /Philippines Pineapple .111653 .055828 1.99996 .046 U.S apple /ROW Pineapple -.270519 .082156 -3.29276 .001 U.S apple /U.S grape .125434 .168230 .745608 .456 U.S apple /Argentinean grape -.318097 .062956 -5.05272 .000 U.S apple /ROW grape -.045390 .161440 -.281157 .779 U.S apple /Israelis citrus -.235060 .080338 -2.92590 .003 U.S apple /Italian citrus .000097 .067568 .001437 .999 U.S apple /ROW citrus .161472 .084730 1.90572 .057 Chinese apple/U.S orange .034808 .162927 .213642 .831 Chinese apple/Brazilian orange -.304383 .287227 -1.05973 .289 Chinese apple/ROW orange -.000442 .082433 -.005364 .996 Chinese apple/U.S grapefruit -.031352 .124832 -.251156 .802 Chinese apple/Israelis grapefruit .084149 .075261 1.11809 .264 Chinese apple/ROW grapefruit -.009451 .046039 -.205288 .837 Chinese apple /U.S apple -.111732 .147318 -.758443 .448 Chinese apple /ROW apple .201989 .231144 .873868 .382 Chinese apple /Thai Pineapple .029036 .043876 .661773 .508 Chinese apple /Philippines Pineapple .050202 .042202 1.18955 .234 Chinese apple /ROW Pineapple -.105297 .058808 -1.79052 .073 Chinese apple /U.S grape .260147 .119876 2.17012 .030 Chinese apple /Argentin ean grape -.020735 .048254 -.429710 .667 Chinese apple /ROW grape -.210633 .120544 -1.74735 .081 Chinese apple /Israelis citrus .000667 .061216 .010911 .991 Chinese apple /Italian citrus .025017 .051889 .482131 .630 Chinese apple /ROW citrus .052375 .058165 .900448 .368 ROW apple/U.S orange .107005 .123498 .866451 .386 ROW apple/Brazilian orange -.579753 .216202 -2.68154 .007 ROW apple/ROW orange .118483 .061943 1.91276 .056 ROW apple/U.S grapefruit -.077664 .097293 -.798248 .425 ROW apple/Israelis grapefruit -.037344 .053830 -.693737 .488 ROW apple/ROW grapefruit .003101 .034075 .091010 .927 ROW apple /U.S apple -.256057 .106199 -2.41111 .016 ROW apple /Chinese apple .101073 .100362 1.00709 .314 ROW apple /Thai Pineapple .039802 .034110 1.16687 .243 ROW apple /Philippines Pineapple -.001426 .033667 -.042359 .966 ROW apple /ROW Pineapple .047041 .043524 1.08082 .280 ROW apple /U.S grape -.050609 .091436 -.553490 .580 ROW apple /Argentinean grape .039206 .039469 .993355 .321 ROW apple /ROW grape -.100389 .096014 -1.04557 .296

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127 Table B-1 Continued Products Estimates SE t-statistics P-value ROW apple /Israelis citrus .070331 .048041 1.46397 .143 ROW apple /Italian citrus .007157 .042412 .168754 .866 ROW apple /ROW citrus .024781 .042907 .577562 .564 Thai pineapple/U.S orange .574566 .411579 1.39600 .163 Thai pineapple/Brazilian orange -.041274 .538182 -.076691 .939 Thai pineapple /ROW orange .130829 .182919 .715228 .474 Thai pineapple /U.S grapefruit -1.72498 .323097 -5.33889 .000 Thai pineapple /Israelis grapefruit -.059108 .158017 -.374063 .708 Thai pineapple /ROW grapefruit -.057611 .100026 -.575956 .565 Thai pineapple /U.S apple .293028 .296411 .988590 .323 Thai pineapple /Chinese apple .211083 .293336 .719596 .472 Thai pineapple /ROW apple .614374 .524229 1.17196 .241 Thai pineapple /Philippines pineapple .035009 .139039 .251793 .801 Thai pineapple /ROW Pineapple -.060033 .140571 -.427063 .669 Thai pineapple /U.S grape .161346 .326045 .494859 .621 Thai pineapple /Argentinean GR -.125802 .180211 -.698084 .485 Thai pineapple /ROW grape .110063 .367130 .299792 .764 Thai pineapple /Israelis citrus .253872 .196042 1.29499 .195 Thai pineapple /Italian citrus .240957 .192482 1.25184 .211 Thai pineapple /ROW citrus -.085308 .128739 -.662640 .508 Philippines pineapple/U.S orange 1.14343 .580643 1.96926 .049 Philippines pineapple/Brazilian orange -.380386 .745731 -.510085 .610 Philippines pineapple /ROW orange -.116823 .257193 -.454221 .650 Philippines pineapple /U.S grapefruit -1.92872 .458748 -4.20432 .000 Philippines pineapple /Israelis grapefruit .278250 .217713 1.27805 .201 Philippines pineapple /ROW grapefruit -.000151 .140211 -.001080 .999 Philippines pineapple /U.S apple .864587 .414549 2.08561 .037 Philippines pineapple /Chinese apple .505740 .406232 1.24495 .213 Philippines pineapple /ROW apple -.004122 .744671 -.005536 .996 Philippines pineapple /Thai pineapple .051407 .200281 .256675 .797 Philippines pineapple /ROW pineapple .108750 .198210 .548660 .583 Philippines pineapple /U.S grape -.321091 .464205 -.691702 .489 Philippines pineapple /Argentinean grape .665921 .254076 2.62095 .009 Philippines pineapple /ROW grape .904976 .520934 1.73722 .082 Philippines pineapple /Israelis other citrus .624716 .279880 2.23209 .026 Philippines pineapple /Italian citrus .210391 .274132 .767480 .443 Philippines pineapple /ROW other citrus .126285 .182412 .692308 .489 ROW pineapple/U.S orange -.433511 .618055 -.701413 .483 ROW pineapple/Brazilian orange 2.56872 .960501 2.67435 .007 ROW pineapple /ROW orange -.177503 .301080 -.589554 .555 ROW pineapple /U.S grapefruit -.279599 .473241 -.590818 .555 ROW pineapple /Israelis grapefruit .003300 .269649 .012240 .990 ROW pineapple /ROW grapefruit .119955 .164301 .730094 .465 ROW pineapple /U.S apple -1.62332 .518702 -3.12958 .002 ROW pineapple /Chinese apple -.749191 .480858 -1.55803 .119 ROW pineapple /ROW apple 1.08545 .819207 1.32501 .185 ROW pineapple /Thai pineapple -.059935 .171895 -.348671 .727 ROW pineapple /Philippines pineapple .100901 .168355 .599335 .549 ROW pineapple /U.S grape .051734 .458327 .112875 .910 ROW pineapple /Argentinean grape .621882 .195892 3.17462 .002 ROW pineapple /ROW grape .017522 .472157 .037111 .970 ROW pineapple /Israelis citrus .264592 .242764 1.08991 .276 ROW pineapple /Italian citrus .203866 .211865 .962244 .336

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128 Table B-1 Continued Products Estimates SE t-statistics P-value ROW pineapple /ROW citrus -.258939 .215039 -1.20415 .229 U.S grape/U.S orange .213019 .188475 1.13022 .258 U.S grape/Brazilian orange -.192560 .294080 -.654789 .513 U.S grape/ROW orange .009763 .088865 .109864 .913 U.S grape/U.S grapefruit -.260314 .146804 -1.77321 .076 U.S grape/Israelis grapefruit -.037944 .079435 -.477669 .633 U.S grape/ROW grapefruit .042624 .048300 .882471 .378 U.S grape/U.S apple .154090 .151838 1.01483 .310 U.S grape/Chinese apple .342560 .140657 2.43542 .015 U.S grape/ROW apple -.076039 .246697 -.308227 .758 U.S grape/Thai Pineapple .031405 .057409 .547029 .584 U.S grape /Philippines Pineapple -.037737 .056761 -.664837 .506 U.S grape /ROW Pineapple -.001110 .065844 -.016867 .987 U.S grape /Argentinean grape .173165 .069613 2.48753 .013 U.S grape /ROW grape .127373 .159132 .800425 .423 U.S grape /Israelis citrus -.001043 .080177 -.013009 .990 U.S grape /Italian citrus .094837 .074390 1.27486 .202 U.S grape /ROW citrus .136238 .063673 2.13966 .032 Argentinean grape/U.S orange -.848684 .567265 -1.49610 .135 Argentinean grape/Brazilian orange -.290384 .697277 -.416454 .677 Argentinean grape/ROW orange .393454 .246106 1.59872 .110 Argentinean grape/U.S grapefruit .281305 .458102 .614067 .539 Argentinean grape/Israelis grapefruit .176053 .203177 .866502 .386 Argentinean grape/ROW grapefruit .052680 .133995 .393148 .694 Argentinean grape/U.S apple -1.93361 .387091 -4.99523 .000 Argentinean grape/Chinese apple -.131195 .384502 -.341207 .733 Argentinean grape/ROW apple .754669 .722820 1.04406 .296 Argentinean grape/Thai pineapple -.147720 .214881 -.687450 .492 Argentinean grape /Philippines pineapple. .551683 .210311 2.62317 .009 Argentinean grape /ROW Pineapple .597509 .190995 3.12840 .002 Argentinean grape /U.S grape 1.16956 .471310 2.48151 .013 Argentinean grape /ROW grape .250957 .552739 .454025 .650 Argentinean grape /Israelis other citrus -.039123 .303658 -.128837 .897 Argentinean grape /Italian citrus -.287640 .324357 -.886799 .375 Argentinean grape /ROW other CT -.096872 .171753 -.564020 .573 ROW grape/U.S orange -.294039 .191043 -1.53912 .124 ROW grape/Brazilian orange .331122 .262422 1.26179 .207 ROW grape/ROW orange .035333 .086060 .410568 .681 ROW grape/U.S grapefruit .299574 .147939 2.02499 .043 ROW grape/Israelis grapefruit -.013666 .073207 -.186672 .852 ROW grape/ROW grapefruit .041878 .046684 .897053 .370 ROW grape/U.S apple -.009454 .140601 -.067243 .946 ROW grape/Chinese apple -.210464 .136026 -1.54724 .122 ROW grape/ROW apple -.224117 .249520 -.898191 .369 ROW grape/Thai Pineapple .019824 .061918 .320159 .749 ROW grape /Philippines Pineapple .106159 .061047 1.73898 .082 ROW grape /ROW Pineapple -.007580 .065207 -.116248 .907 ROW grape /U.S grape .112155 .152514 .735374 .462 ROW grape /Argentinean grape .034612 .078101 .443174 .658 ROW grape /Israelis citrus .066102 .087016 .759649 .447 ROW grape /Italian citrus -.010959 .084977 -.128966 .897 ROW grape /ROW citrus .072630 .060573 1.19905 .231 Israelis citrus/U.S orange -.718991 .281024 -2.55847 .011

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129 Table B-1 Continued Products Estimates SE t-statistics P-value Israelis citrus /Brazilian orange .556726 .371001 1.50060 .133 Israelis citrus /ROW orange .095900 .126939 .755481 .450 Israelis citrus /U.S grapefruit .135515 .222058 .610266 .542 Israelis citrus /Israelis grapefruit -.078944 .107006 -.737755 .461 Israelis citrus /ROW grapefruit -.011856 .069276 -.171146 .864 Israelis citrus /U.S apple -.569275 .204169 -2.78825 .005 Israelis citrus /Chinese apple .034520 .201885 .170988 .864 Israelis citrus /ROW apple .572135 .364275 1.57061 .116 Israelis citrus /Thai pineapple .127918 .096861 1.32064 .187 Israelis citrus /Philippines pineapple .215417 .096017 2.24353 .025 Israelis citrus /ROW Pineapple .097943 .098067 .998735 .318 Israelis citrus /U.S grape -.007681 .224844 -.034165 .973 Israelis citrus /Argentinean GR -.016379 .125873 -.130125 .896 Israelis citrus /ROW grape .199430 .254829 .782603 .434 Israelis citrus /Italian citrus .056825 .136156 .417351 .676 Israelis citrus /ROW citrus .108225 .089128 1.21427 .225 Italian citrus/U.S orange -.136630 .321111 -.425493 .670 Italian citrus /Brazilian orange .532182 .412199 1.29108 .197 Italian citrus /ROW orange .136078 .140906 .965732 .334 Italian citrus /U.S grapefruit -.321885 .258107 -1.24710 .212 Italian citrus /Israelis grapefruit .267284 .117198 2.28061 .023 Italian citrus /ROW grapefruit -.253390 .077159 -3.28401 .001 Italian citrus /U.S apple .040638 .220069 .184662 .853 Italian citrus /Chinese apple .144348 .218866 .659528 .510 Italian citrus /ROW apple .129425 .411250 .314712 .753 Italian citrus /Thai pineapple .155721 .121520 1.28145 .200 Italian citrus /Philippines pineapple .093918 .120168 .781555 .434 Italian citrus /ROW Pineapple .097134 .109392 .887950 .375 Italian citrus /U.S grape .342044 .266627 1.28285 .200 Italian citrus /Argentinean grape -.151979 .171695 -.885169 .376 Italian citrus /ROW grape -.029695 .318080 -.093358 .926 Italian citrus /Israelis citrus .074648 .173907 .429241 .668 Italian citrus /ROW citrus -.060625 .097837 -.619658 .535 ROW citrus/U.S orange -.432676 .210033 -2.06003 .039 ROW citrus /Brazilian orange -.213379 .366838 -.581672 .561 ROW citrus /ROW orange .075887 .107417 .706476 .480 ROW citrus /U.S grapefruit .168478 .160409 1.05030 .294 ROW citrus /Israelis grapefruit -.038717 .098598 -.392679 .695 ROW citrus /ROW grapefruit -.073833 .058395 -1.26437 .206 ROW citrus /U.S apple .398274 .190262 2.09330 .036 ROW citrus /Chinese apple .180769 .169474 1.06665 .286 ROW citrus /ROW apple .200896 .288067 .697392 .486 ROW citrus /Thai pineapple -.035644 .056262 -.633539 .526 ROW citrus /Philippines pineapple .038717 .055391 .698982 .485 ROW citrus /ROW Pineapple -.102178 .076658 -1.33290 .183 ROW citrus /U.S grape .330066 .158350 2.08441 .037 ROW citrus /Argentinean GR -.036070 .063003 -.572516 .567 ROW citrus /ROW grape .190036 .156688 1.21283 .225 ROW citrus /Israelis citrus .094281 .078957 1.19408 .232 ROW citrus /Italian citrus -.044278 .067806 -.653013 .514

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130 Table B-2 Compensated price elastic ities of fruit juices in Japan Products Estimates SE t-statistics P-value U.S orange /Brazilian orange 1.13564 .358135 3.17097 .002 U.S orange /ROW orange .062661 .104390 .600261 .548 U.S orange /U.S grapefruit -.020600 .168350 -.122367 .903 U.S orange /Israelis grapefruit .007149 .092007 .077701 .938 U.S orange /ROW grapefruit -.119459 .056329 -2.12074 .034 U.S orange /U.S apple .466868 .176852 2.63988 .008 U.S orange /Chinese apple .082327 .164526 .500388 .617 U.S orange /ROW apple .324111 .283284 1.14412 .253 U.S orange /Thai Pineapple .091188 .062541 1.45805 .145 U.S orange /Philippines Pineapple .122150 .061210 1.99559 .046 U.S orange /ROW Pineapple -.060929 .076746 -.793900 .427 U.S orange /U.S grape .190834 .162638 1.17337 .241 U.S orange /Argentinean grape -.105681 .072340 -1.46090 .144 U.S orange /ROW grape -.244117 .172030 -1.41903 .156 U.S orange /Israelis citrus -.214624 .086258 -2.48818 .013 U.S orange /Italian citrus -.030594 .077120 -.396701 .692 U.S orange /ROW citrus -.143153 .072973 -1.96173 .050 Brazilian orange/U.S orange .323646 .102065 3.17097 .002 Brazilian orange /ROW orange -.070674 .050318 -1.40455 .160 Brazilian orange /U.S grapefruit .117070 .072412 1.61672 .106 Brazilian orange /Israe lis grapefruit .019109 .049986 .382292 .702 Brazilian orange /ROW grapefruit -.005087 .029679 -.171399 .864 Brazilian orange /U.S apple .054956 .104329 .526754 .598 Brazilian orange /Chinese apple -.039803 .081551 -.488079 .625 Brazilian orange /ROW apple -.296834 .139509 -2.12770 .033 Brazilian orange /Thai Pineappl e .002653 .022873 .115993 .908 Brazilian orange /Philippines pineapple -.008912 .021979 -.405514 .685 Brazilian orange /ROW pineapple .083012 .033439 2.48251 .013 Brazilian orange /U.S grape -.038987 .071267 -.547062 .584 Brazilian orange /Argentinean grape -.008714 .024801 -.351382 .725 Brazilian orange /ROW grape .103280 .066051 1.56364 .118 Brazilian orange /Israelis citrus .052930 .031851 1.66179 .097 Brazilian orange /Italian citrus .038166 .027741 1.37581 .169 Brazilian orange /ROW citrus -.014568 .035836 -.406512 .684 ROW orange/U.S orange .140095 .233390 .600261 .548 ROW orange/Brazilian orange -.554440 .394745 -1.40455 .160 ROW orange /U.S grapefruit .146523 .175650 .834174 .404 ROW orange /Israelis grapefruit .090241 .108354 .832838 .405 ROW orange /ROW grapefruit .079543 .063947 1.24389 .214 ROW orange /U.S apple .409762 .215760 1.89916 .058 ROW orange /Chinese apple .046361 .184909 .250721 .802 ROW orange /ROW apple .684259 .316073 2.16488 .030 ROW orange /Thai Pineapple .048597 .061756 .786913 .431 ROW orange /Philippines pineapple -.024908 .060194 -.413799 .679 ROW orange /ROW pineapple -.056402 .083062 -.679033 .497 ROW orange /U.S grape .026817 .170314 .157454 .875 ROW orange /Argentinean grape .113128 .069673 1.62371 .104 ROW orange /ROW grape .089533 .172059 .520361 .603 ROW orange /Israelis citrus .069925 .086488 .808496 .419 ROW orange /Italian citrus .074554 .075169 .991814 .321 ROW orange /ROW citrus .065127 .082950 .785135 .432 U.S grapefruit/U.S orange -.018460 .150858 -.122367 .903 U.S grapefruit/Brazilian orange .368103 .227684 1.61672 .106

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131 Table B-2 Continued Products Estimates SE t-statistics P-value U.S grapefruit/ROW orange .058727 .070401 .834174 .404 U.S grapefruit/Israelis grapefruit .039680 .061571 .644463 .519 U.S grapefruit /ROW grapefruit .131508 .038276 3.43581 .001 U.S grapefruit /U.S apple .331172 .119123 2.78009 .005 U.S grapefruit /Chinese apple .019126 .112046 .170699 .864 U.S grapefruit /ROW apple -.078706 .198781 -.395942 .692 U.S grapefruit /Thai Pineapple -.228979 .043704 -5.23931 .000 U.S grapefruit /Philippines Pineapple -.178512 .043036 -4.14795 .000 U.S grapefruit /ROW Pineapple -.038334 .052250 -.733665 .463 U.S grapefruit /U.S grape -.192023 .112628 -1.70493 .088 U.S grapefruit /Argentinean grape .033675 .051940 .648351 .517 U.S grapefruit /ROW grape .258981 .118476 2.18594 .029 U.S grapefruit /Israelis citrus .041582 .060631 .685820 .493 U.S grapefruit /Italian citrus -.066801 .055168 -1.21086 .226 U.S grapefruit /ROW citrus .058664 .049534 1.18432 .236 Israelis grapefruit/U.S orange .019938 .256600 .077701 .938 Israelis grapefruit/Brazilian orange .187004 .489164 .382292 .702 Israelis grapefruit/ROW orange .112568 .135162 .832838 .405 Israelis grapefruit/U.S grapefruit .123496 .191626 .644463 .519 Israelis grapefruit/ROW grapefruit .085558 .073832 1.15882 .247 Israelis grapefruit /U.S apple -.216557 .255118 -.848850 .396 Israelis grapefruit /Chinese apple .283150 .209727 1.35009 .177 Israelis grapefruit /ROW apple -.157524 .340750 -.462286 .644 Israelis grapefruit /Thai Pineapple -.020463 .066251 -.308865 .757 Israelis grapefruit /Philippines Pineapple .083682 .063267 1.32267 .186 Israelis grapefruit /ROW Pineapple -.006256 .092404 -.067707 .946 Israelis grapefruit /U.S grape -.082691 .189027 -.437453 .662 Israelis grapefruit /Argentinean grape .063922 .071431 .894890 .371 Israelis grapefruit /ROW grape -.015212 .181707 -.083715 .933 Israelis grapefruit /Isr aelis citrus -.062557 .090526 -.691032 .490 Israelis grapefruit /Italian citrus .179780 .077637 2.31565 .021 Israelis grapefruit /ROW citrus -.030878 .094597 -.326413 .744 ROW grapefruit/U.S orange -.7 74553 .365228 -2.12074 .034 ROW grapefruit/Brazilian orange -.115735 .675236 -.171399 .864 ROW grapefruit/ROW orange .230678 .185449 1.24389 .214 ROW grapefruit/U.S grapefruit .951541 .276948 3.43581 .001 ROW grapefruit/Israelis grapefru it .198911 .171649 1.15882 .247 ROW grapefruit /U.S apple .080026 .340727 .234868 .814 ROW grapefruit /Chinese apple -.014217 .301146 -.047210 .962 ROW grapefruit /ROW apple .125900 .506628 .248506 .804 ROW grapefruit /Thai Pineapple -.051974 .098454 -.527908 .598 ROW grapefruit /Philippines Pineapple .002333 .095678 .024394 .981 ROW grapefruit /ROW Pineapple .088656 .132187 .670690 .502 ROW grapefruit /U.S grape .245176 .269960 .908194 .364 ROW grapefruit /Argentinean grape .045005 .110614 .406864 .684 ROW grapefruit /ROW grape .261739 .272171 .961670 .336 ROW grapefruit /Israelis citrus -.018873 .137604 -.137157 .891 ROW grapefruit /Italian citrus -.389851 .120010 -3.24847 .001 ROW grapefruit /ROW citrus -.159073 .131499 -1.20969 .226 U.S apple/U.S orange .595592 .225613 2.63988 .008 U.S apple/Brazilian orange .246002 .467014 .526754 .598 U.S apple/ROW orange .233809 .123112 1.89916 .058 U.S apple/U.S grapefruit .471467 .169587 2.78009 .005

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132 Table B-2 Continued Products Estimates SE t-statistics P-value U.S apple/Israelis grapefruit -.099058 .116697 -.848850 .396 U.S apple/ROW grapefruit .015745 .067039 .234868 .814 U.S apple /Chinese apple -.095860 .189929 -.504716 .614 U.S apple /ROW apple -.665053 .311183 -2.13718 .033 U.S apple /Thai Pineapple .060876 .057440 1.05982 .289 U.S apple /Philippines Pineapple .117913 .055720 2.11618 .034 U.S apple /ROW Pineapple -.263135 .082234 -3.19985 .001 U.S apple /U.S grape .176727 .167147 1.05732 .290 U.S apple /Argentinean grape -.310527 .062901 -4.93679 .000 U.S apple /ROW grape .008089 .161405 .050116 .960 U.S apple /Israelis citrus -.216832 .079909 -2.71349 .007 U.S apple /Italian citrus .014358 .067351 .213174 .831 U.S apple /ROW citrus .182147 .084443 2.15703 .031 Chinese apple/U.S orange .081939 .163750 .500388 .617 Chinese apple/Brazilian orange -.139007 .284804 -.488079 .625 Chinese apple/ROW orange .020638 .082315 .250721 .802 Chinese apple/U.S grapefruit .021243 .124448 .170699 .864 Chinese apple/Israelis grapefruit .101048 .074846 1.35009 .177 Chinese apple/ROW grapefruit -.002182 .046227 -.047210 .962 Chinese apple /U.S apple -.074788 .148178 -.504716 .614 Chinese apple /ROW apple .309493 .227555 1.36008 .174 Chinese apple /Thai Pineapple .036152 .043890 .823708 .410 Chinese apple /Philippines Pineapple .055136 .042147 1.30820 .191 Chinese apple /ROW Pineapple -.099477 .058859 -1.69009 .091 Chinese apple /U.S grape .300579 .119561 2.51403 .012 Chinese apple /Argentin ean grape -.014769 .048253 -.306070 .760 Chinese apple /ROW grape -.168478 .120610 -1.39689 .162 Chinese apple /Israelis citrus .015036 .061039 .246332 .805 Chinese apple /Italian citrus .036258 .051735 .700842 .483 Chinese apple /ROW citrus .068672 .058061 1.18274 .237 ROW apple/U.S orange .142094 .124195 1.14412 .253 ROW apple/Brazilian orange -.456630 .214612 -2.12770 .033 ROW apple/ROW orange .134177 .061979 2.16488 .030 ROW apple/U.S grapefruit -.038506 .097252 -.395942 .692 ROW apple/Israelis grapefruit -.024762 .053565 -.462286 .644 ROW apple/ROW grapefruit .008512 .034256 .248506 .804 ROW apple /U.S apple -.228551 .106941 -2.13718 .033 ROW apple /Chinese apple .136328 .100236 1.36008 .174 ROW apple /Thai Pineapple .045101 .034126 1.32159 .186 ROW apple /Philippines Pineapple .002247 .033633 .066826 .947 ROW apple /ROW Pineapple .051374 .043571 1.17909 .238 ROW apple /U.S grape -.020507 .091176 -.224920 .822 ROW apple /Argentinean grape .043649 .039461 1.10612 .269 ROW apple /ROW grape -.069005 .096204 -.717273 .473 ROW apple /Israelis citrus .081028 .047918 1.69099 .091 ROW apple /Italian citrus .015526 .042300 .367040 .714 ROW apple /ROW citrus .036915 .042858 .861327 .389 Thai Pineapple/U.S orange .603899 .414183 1.45805 .145 Thai Pineapple/Brazilian orange .061652 .531517 .115993 .908 Thai Pineapple /ROW orange .143949 .182928 .786913 .431 Thai Pineapple /U.S grapefruit -1.69225 .322991 -5.23931 .000 Thai Pineapple /Israelis grapefruit -.048590 .157320 -.308865 .757 Thai Pineapple /ROW grapefruit -.053086 .100560 -.527908 .598

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133 Table B-2 Continued Products Estimates SE t-statistics P-value Thai Pineapple /U.S apple .316022 .298184 1.05982 .289 Thai Pineapple /Chinese apple .240555 .292040 .823708 .410 Thai Pineapple /ROW apple .681282 .515502 1.32159 .186 Thai Pineapple /Philippines pineapple .038080 .138946 .274062 .784 Thai Pineapple /ROW Pineapple -.056410 .140667 -.401021 .688 Thai Pineapple /U.S grape .186510 .326293 .571603 .568 Thai pineapple /Argentinean grape -.122089 .180316 -.677082 .498 Thai pineapple /ROW grape .136298 .367053 .371332 .710 Thai pineapple /Israelis citrus .262815 .195698 1.34296 .179 Thai pineapple /Italian citrus .247953 .192111 1.29067 .197 Thai pineapple /ROW citrus -.075165 .128879 -.583223 .560 Philippines pineapple/U.S orange 1.16671 .584644 1.99559 .046 Philippines pineapple/Brazilian orange -.298718 .736640 -.405514 .685 Philippines pineapple /ROW orange -.106412 .257159 -.413799 .679 Philippines pineapple /U.S grapefruit -1.90275 .458721 -4.14795 .000 Philippines pineapple /Israelis grapefruit .286595 .216679 1.32267 .186 Philippines pineapple /ROW grapefruit .003438 .140945 .024394 .981 Philippines pineapple /U.S apple .882831 .417181 2.11618 .034 Philippines pineapple /Chinese apple .529125 .404469 1.30820 .191 Philippines pineapple /ROW apple .048966 .732742 .066826 .947 Philippines pineapple /Thai pineapple .054921 .200398 .274062 .784 Philippines pineapple /ROW pineapple .111624 .198352 .562759 .574 Philippines pineapple /U.S grape -.301125 .464644 -.648076 .517 Philippines pineapple /Argentinean grape .668868 .254198 2.63128 .009 Philippines pineapple /ROW grape .925793 .521094 1.77663 .076 Philippines pineapple /Israelis other citrus .631812 .279371 2.26155 .024 Philippines pineapple /Italian citrus .215942 .273604 .789249 .430 Philippines pineapple /ROW other citrus .134333 .182706 .735243 .462 ROW pineapple/U.S orange -.493378 .621461 -.793900 .427 ROW pineapple/Brazilian orange 2.35865 .950108 2.48251 .013 ROW pineapple /ROW orange -.204280 .300840 -.679033 .497 ROW pineapple /U.S grapefruit -.346407 .472159 -.733665 .463 ROW pineapple /Israelis grapefruit -.018165 .268294 -.067707 .946 ROW pineapple /ROW grapefruit .110722 .165087 .670690 .502 ROW pineapple /U.S apple -1.67025 .521976 -3.19985 .001 ROW pineapple /Chinese apple -.809341 .478874 -1.69009 .091 ROW pineapple /ROW apple .948901 .804777 1.17909 .238 ROW pineapple /Thai pineapple -.068975 .171998 -.401021 .688 ROW pineapple /Philippines pineapple .094633 .168160 .562759 .574 ROW pineapple /U.S grape .000376 .457708 .000821 .999 ROW pineapple /Argentinean grape .614303 .195919 3.13549 .002 ROW pineapple /ROW grape -.036023 .472565 -.076229 .939 ROW pineapple /Israelis citrus .246342 .242225 1.01700 .309 ROW pineapple /Italian citrus .189588 .211347 .897043 .370 ROW pineapple /ROW citrus -.279640 .214860 -1.30150 .193 U.S grape/U.S orange .222450 .189582 1.17337 .241 U.S grape/Brazilian orange -.159466 .291496 -.547062 .584 U.S grape/ROW orange .013982 .088798 .157454 .875 U.S grape/U.S grapefruit -.249789 .146509 -1.70493 .088 U.S grape/Israelis grapefruit -.034562 .079007 -.437453 .662 U.S grape/ROW grapefruit .044078 .048534 .908194 .364 U.S grape/U.S apple .161483 .152729 1.05732 .290 U.S grape/Chinese apple .352037 .140029 2.51403 .012

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134 Table B-2 Continued Products Estimates SE t-statistics P-value U.S grape/ROW apple -.054526 .242424 -.224920 .822 U.S grape/Thai Pineapple .032829 .057433 .571603 .568 U.S grape /Philippines Pineapple -.036750 .056706 -.648076 .517 U.S grape /ROW Pineapple .005414 .065888 .000821 .999 U.S grape /Argentinean grape .174359 .069628 2.50415 .012 U.S grape /ROW grape .135809 .159099 .853610 .393 U.S grape /Israelis citrus .001832 .079980 .022908 .982 U.S grape /Italian citrus .097086 .074227 1.30797 .191 U.S grape /ROW citrus .139500 .063673 2.19087 .028 Argentinean grape/U.S orange -.834763 .571405 -1.46090 .144 Argentinean grape/Brazilian orange -.241539 .687398 -.351382 .725 Argentinean grape/ROW orange .399680 .246153 1.62371 .104 Argentinean grape/U.S grapefruit .296840 .457838 .648351 .517 Argentinean grape/Israelis grapefruit .181044 .202309 .894890 .371 Argentinean grape/ROW grapefruit .054827 .134755 .406864 .684 Argentinean grape/U.S apple -1.92270 .389463 -4.93679 .000 Argentinean grape/Chinese apple -.117209 .382947 -.306070 .760 Argentinean grape/ROW apple .786420 .710972 1.10612 .269 Argentinean grape/Thai pineapple -.145618 .215067 -.677082 .498 Argentinean grape /Philippines pineapple. .553140 .210217 2.63128 .009 Argentinean grape /ROW Pineapple .599228 .191111 3.13549 .002 Argentinean grape /U.S grape 1.18150 .471817 2.50415 .012 Argentinean grape /ROW grape .263408 .552084 .477115 .633 Argentinean grape /Israelis other citrus -.034879 .303269 -.115010 .908 Argentinean grape /Italian citrus -.284320 .323716 -.878300 .380 Argentinean grape /ROW other citrus -.092059 .172063 -.535029 .593 ROW grape/U.S orange -.272934 .192338 -1.41903 .156 ROW grape/Brazilian orange .405177 .259125 1.56364 .118 ROW grape/ROW orange .044773 .086042 .520361 .603 ROW grape/U.S grapefruit .323126 .147820 2.18594 .029 ROW grape/Israelis grapefruit -.006098 .072845 -.083715 .933 ROW grape/ROW grapefruit .045133 .046932 .961670 .336 ROW grape/U.S apple .007089 .141456 .050116 .960 ROW grape/Chinese apple -.189259 .135486 -1.39689 .162 ROW grape/ROW apple -.175977 .245342 -.717273 .473 ROW grape/Thai pineapple .023010 .061967 .371332 .710 ROW grape /Philippines pineapple .108369 .060997 1.77663 .076 ROW grape /ROW pineapple -.004973 .065248 -.076229 .939 ROW grape /U.S grape .130260 .152599 .853610 .393 ROW grape /Argentinean grape .037284 .078145 .477115 .633 ROW grape /Israelis citrus .072536 .086863 .835060 .404 ROW grape /Italian citrus -.005925 .084810 -.069868 .944 ROW grape /ROW citrus .079928 .060606 1.31882 .187 Israelis citrus/U.S orange -.704027 .282948 -2.48818 .013 Israelis citrus /Brazilian orange .609234 .366614 1.66179 .097 Israelis citrus /ROW orange .102593 .126894 .808496 .419 Israelis citrus /U.S grapefruit .152214 .221945 .685820 .493 Israelis citrus /Israelis grapefruit -.073578 .106476 -.691032 .490 Israelis citrus /ROW grapefruit -.009548 .069616 -.137157 .891 Israelis citrus /U.S apple -.557545 .205471 -2.71349 .007 Israelis citrus /Chinese apple .049555 .201173 .246332 .805 Israelis citrus /ROW apple .606269 .358529 1.69099 .091 Israelis citrus /Thai pineapple .130177 .096933 1.34296 .179

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135 Table B-2 Continued Products Estimates SE t-statistics P-value Israelis citrus /Philippines pineapple .216984 .095945 2.26155 .024 Israelis citrus /ROW Pineapple .099791 .098123 1.01700 .309 Israelis citrus /U.S grape .005155 .225070 .022908 .982 Israelis citrus /Argentinean grape -.014485 .125943 -.115010 .908 Israelis citrus /ROW grape .212814 .254849 .835060 .404 Israelis citrus /Italian citrus .060394 .135897 .444412 .657 Israelis citrus /ROW citrus .113400 .089264 1.27039 .204 Italian citrus/U.S orange -.128274 .323353 -.396701 .692 Italian citrus /Brazilian orange .561502 .408126 1.37581 .169 Italian citrus /ROW orange .139815 .140969 .991814 .321 Italian citrus /U.S grapefruit -.312561 .258132 -1.21086 .226 Italian citrus /Israelis grapefruit .270280 .116719 2.31565 .021 Italian citrus /ROW grapefruit -.252101 .077606 -3.24847 .001 Italian citrus /U.S apple .047188 .221361 .213174 .831 Italian citrus /Chinese apple .152744 .217944 .700842 .483 Italian citrus /ROW apple .148485 .404548 .367040 .714 Italian citrus /Thai pineapple .156983 .121628 1.29067 .197 Italian citrus /Philippines pineapple .094793 .120105 .789249 .430 Italian citrus /ROW pineapple .098166 .109433 .897043 .370 Italian citrus /U.S grape .349212 .266988 1.30797 .191 Italian citrus /Argentinean grape -.150921 .171833 -.878300 .380 Italian citrus /ROW grape -.022222 .318048 -.069868 .944 Italian citrus /Israelis citrus .077196 .173703 .444412 .657 Italian citrus /ROW citrus -.057736 .098015 -.589052 .556 ROW citrus/U.S orange -.413995 .211035 -1.96173 .050 ROW citrus /Brazilian orange -.147830 .363654 -.406512 .684 ROW citrus /ROW orange .084243 .107297 .785135 .432 ROW citrus /U.S grapefruit .189325 .159859 1.18432 .236 ROW citrus /Israelis grapefruit -.032019 .098093 -.326413 .744 ROW citrus /ROW grapefruit -.070952 .058653 -1.20969 .226 ROW citrus /U.S apple .412918 .191429 2.15703 .031 ROW citrus /Chinese apple .199538 .168708 1.18274 .237 ROW citrus /ROW apple .243507 .282711 .861327 .389 ROW citrus /Thai pineapple -.032824 .056280 -.583223 .560 ROW citrus /Philippines pineapple .040673 .055319 .735243 .462 ROW citrus /ROW Pineapple -.099871 .076735 -1.30150 .193 ROW citrus /U.S grape .346092 .157971 2.19087 .028 ROW citrus /Argentinean grape -.033705 .062997 -.535029 .593 ROW citrus /ROW grape .206745 .156765 1.31882 .187 ROW citrus /Israelis citrus .099976 .078698 1.27039 .204 ROW citrus /Italian citrus -.039823 .067605 -.589052 .556

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136 APPENDIX C PARAMETER ESTIMATES OF ROTTERDAM MODEL UNDER DIFFERENT SEPARABILITY ASSUMPTIONS Table C-1. Marginal value shares of fruit ju ices in a block independent Rotterdam model Product Estimates i SE t-statistics P-value U.S. orange .027961 .913834E-02 3.05978 0.002 Brazilian orange .745750 .034906 21.3644 0.000 ROW orange .010748 .558347E-02 1.92496 0.054 U.S. grapefruit .029762 .580410E-02 5.12771 0.000 Israelis grapefruit .236792E-02 .298566E-02 .793096 0.428 ROW grapefruit .517695E-03 .169452E-02 .305512 0.760 U.S. apple .040278 .944699E-02 4.26357 0.000 Chinese apple .036968 .773508E-02 4.77923 0.000 ROW apple .047043 .012962 3.62937 0.000 Thai pineapple .460872E-02 .148641E-02 3.10056 0.002 Philippines pineapple .786131E-02 .156078E-02 5.03680 0.000 ROW pineapple .853774E-03 .178778E-02 .477560 0.633 U.S. grapes .880780E-02 .497279E-02 1.77120 0.077 Argentinean grapes -.846428E-04 .185156E-02 -.045714 0.964 ROW grapes .011431 .471108E-02 2.42647 0.015 Israelis other citrus .715117E-02 .224853E-02 3.18038 0.001 Italian other citrus .894720E-02 .227572E-02 3.93159 0.000 ROW other citrus .902818E-02 .217923E-02 4.14283 0.000 Coefficient of income flexibility -1.81278 .279739 -6.48024 0.000 Table C-2. Relative price coefficients of fr uit juices in a block independent Rotterdam model Products Estimates ij SE t-statistics P-value U.S. orange -.114167 .020919 -5.45760 0.000 U.S. orange/Brazilian orange .057930 .026494 2.18651 0.029 U.S. orange/ROW orange .554920E-02 .682128E-02 .813514 0.416 Brazilian orange -1.42189 .247776 -5.73861 0.000 Brazilian orange/ROW orange .012078 .012434 .971341 0.331 ROW orange -.037110 .486140E-02 -7.63370 0.000 U.S. grapefruit -.067859 .010130 -6.69859 0.000 U.S. grapefruit/Israelis gr apefruit .810086E-02 .440660E-02 1.83835 0.066 U.S. grapefruit/ROW grapefruit .58 0657E-02 .257851E-02 2.25191 0.024 Israelis grapefruit -.015038 .395186E-02 -3.80540 0.000 Israelis. grapefruit/ROW grapefruit .2 64504E-02 .160837E-02 1.64455 0.100 ROW grapefruit -.939007E-02 .130989E-02 -7.16862 0.000 U.S. apple -.023643 .013639 -1.73356 0.083 U.S. apple/Chinese apple -.998880E-02 .897542E-02 -1.11291 0.266 U.S. apple/ROW apple -.039383 .014233 -2.76692 0.006 Chinese apple -.041321 .012269 -3.36804 0.001

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137 Table C-2. Continued Products Estimates ij SE t-statistics P-value Chinese apple/ROW apple -.015704 .013935 -1.12695 0.260 ROW apple -.030191 .026148 -1.15461 0.248 Thai. pineapple -.010102 .186886E-02 -5.40530 0.000 Thai. pineapple/Philippines pineapple .229312E-02 .142989E-02 1.60371 0.109 Thai. pineapple/ROW pineapple -.545936E-03 .143880E-02 -.379438 0.704 Philippines pineapple -.018299 .189011E-02 -9.68162 0.000 Philippines pineapple/ROW apple .175536E-02 .145313E-02 1.20799 0.227 ROW pineapple -.275713E-02 .248249E-02 -1.11063 0.267 U.S. grapes -.038038 .010333 -3.68119 0.000 U.S. grapes/Argentinean grapes .714373E-02 .428626E-02 1.66666 0.096 U.S. grapes/ROW grapes .014928 .871201E-02 1.71350 0.087 Argentinean grapes -.849552E-02 .393029E-02 -2.16155 0.031 Argentinean grapes/ROW grapes .150522E-02 .469637E-02 .320507 0.749 ROW grapes -.037156 .011279 -3.29425 0.001 Israelis citrus -.020374 .361853E-02 -5.63055 0.000 Israelis citrus/Italian citrus .392133E-02 .258285E-02 1.51822 0.129 Israelis citrus/ROW citrus .348951E-02 .186858E-02 1.86746 0.062 Italian citrus -.019783 .372399E-02 -5.31230 0.000 Italian citrus/ROW citrus -.357662E-03 .160896E-02 -.222294 0.824 ROW citrus -.019498 .337577E-02 -5.77585 0.000 Table C-3. Marginal value shares of fruit juices in a block independent uniform-substitute Rotterdam model Product Estimates i SE t-statistics P-value U.S. orange .027220 .792396E-02 3.43511 0.001 Brazilian orange .907700E-02 .306674E-02 2.95983 0.003 ROW orange .743746 .035095 21.1922 0.000 U.S. grapefruit .028811 .566702E-02 5.08406 0.000 Israelis grapefruit .311609E-02 .199038E-02 1.56558 0.117 ROW grapefruit .189446E-02 .110629E-02 1.71245 0.087 U.S. apple .035644 .891810E-02 3.99682 0.000 Chinese apple .038398 .761162E-02 5.04471 0.000 ROW apple .051404 .013209 3.89161 0.000 Thai pineapple .415274E-02 .136728E-02 3.03723 0.002 Philippine pineapple .817306E-02 .156327E-02 5.22817 0.000 ROW pineapple .102950E-02 .921286E-03 1.11746 0.264 U.S. grape .907845E-02 .462842E-02 1.96146 0.050 Argentinean grape .152513E-02 .968323E-03 1.57503 0.115 ROW grape .010845 .458813E-02 2.36372 0.018 Israelis other citrus .873475E-02 .204385E-02 4.27369 0.000 Italian other citrus .877093E-02 .216511E-02 4.05103 0.000 ROW other citrus .837951E-02 .191502E-02 4.37568 0.000 -1.79007 .273683 -6.54066 0.000 K1 .733130 .177836 4.12250 0.000 K2 19.5729 8.29988 2.35822 0.018 K3 -18.1472 14.8485 -1.22215 0.222 K4 27.0649 16.8737 1.60397 0.109 K5 31.4922 16.8636 1.86747 0.062 K6 9.85689 6.17161 1.59713 0.110

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138 Table C-4. Marginal value shares of fruit juices in a block-wise dependent Rotterdam model Products Estimates i SE t-statistics P-value U.S. orange .034515 .973502E-02 3.54549 0.000 Brazilian orange .712897 .035439 20.1161 0.000 ROW orange .404939E-02 .594273E-02 .681402 0.496 U.S. grapefruit .036395 .736038E-02 4.94476 0.000 Israelis grapefruit -.200246E-02 .250301E-02 -.800022 0.424 ROW grapefruit .312040E-02 .163735E-02 1.90576 0.057 U.S. apple .052199 .010814 4.82675 0.000 Chinese apple .049507 .801679E-02 6.17537 0.000 ROW apple .066990 .014307 4.68229 0.000 Thai pineapple .965923E-03 .123731E-02 .780663 0.435 Philippine pineapple .150696E-02 .192426E-02 .783138 0.434 ROW pineapple .130863E-03 .253873E-03 .515466 0.606 U.S. grape .775069E-02 .434665E-02 1.78314 0.075 Argentinean grape .633438E-03 .137377E-02 .461094 0.645 ROW grape .013108 .565344E-02 2.31853 0.020 Israelis other citrus .530260E-02 .198499E-02 2.67135 0.008 Italian other citrus .629891E-02 .219617E-02 2.86813 0.004 ROW other citrus .663242E-02 .228522E-02 2.90231 0.004 -1.81259 Table C-5. Constant of proporti onality of fruit juice groups in a in block-wise dependent Rotterdam model Products Estimates gh SE t-statistics P-value Orange/grapefruit .347771 .318666 1.09133 0.275 Orange/apple .991497 .180586 5.49044 0.000 Orange/pineapple -3.79227 6.36190 -.596090 0.551 Orange/grapes .633182 .679618 .931673 0.352 Orange/other citrus .702609 .482882 1.45503 0.146 Grapefruit/apple -.715711 1.53489 -.466294 0.641 Grapefruit/pineapple 174.662 226.483 .771191 0.441 Grapefruit/grape -10.4734 9.74829 -1.07439 0.283 Grapefruit/other citrus 7.54488 6.33844 1.19034 0.234 Apple/pineapple -36.9035 50.4271 -.731819 0.464 Apple/grapes 1.76609 3.16376 .558226 0.577 Apple/other citrus -3.48605 2.88642 -1.20774 0.227 Pineapple/grape -105.564 156.725 -.673559 0.501 Pineapple/other citrus -111.149 160.841 -.691045 0.490 Grapes/other citrus -38.1447 25.1767 -1.51508 0.130 Table C-6. Within-group relative price coefficients of fruit juices in a block-wise dependent Rotterdam Products Estimates SE t-statistics P-value U.S. Orange -.106408 .020796 -5.11685 0.000 U.S. orange/Brazilian orange .048202 .025105 1.92002 0.055 U.S. orange/ROW orange .795979E-02 .679637E-02 1.17118 0.242 Brazilian orange -1.10707 .108089 -10.2423 0.000 Brazilian orange/ROW orange .021053 .011660 1.80558 0.071 ROW orange -.034908 .486964E-02 -7.16855 0.000 U.S. grapefruit -.049379 .012263 -4.02655 0.000

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139 Table C-6. Continued Products Estimates SE t-statistics P-value U.S. grapefruit/Israelis grapefruit .012179 .354942E-02 3.43113 0.001 U.S. grapefruit/ROW grapefruit .47 3403E-02 .216328E-02 2.18835 0.029 Israelis grapefruit -.012886 .351582E-02 -3.66509 0.000 Israelis grapefruit/ROW grapefruit .2 49360E-02 .147894E-02 1.68608 0.092 ROW grapefruit -.010011 .127196E-02 -7.87072 0.000 U.S. apple -.012925 .012130 -1.06555 0.287 U.S. apple/Chinese apple -.145159E-03 .871601E-02 -.016654 0.987 U.S. apple/ROW apple -.025104 .013887 -1.80777 0.071 Chinese apple -.034340 .011599 -2.96050 0.003 Chinese apple/ROW apple -.172017E-02 .013678 -.125766 0.900 ROW apple -.022167 .022440 -.987838 0.323 Thai. pineapple -.012133 .209892E-02 -5.78078 0.000 Thai. pineapple/Philippines pineapple -.677701E-03 .147053E-02 -.460856 0.645 Thai. pineapple/ROW P. apple -.877698E-03 .135307E-02 -.648669 0.517 Philipp. pineapple -.021271 .208471E-02 -10.2034 0.000 Philip. pineapple/ROW apple .592741E-03 .142519E-02 .415902 0.677 ROW pineapple -.156960E-02 .226334E-02 -.693489 0.488 U.S. grape -.039620 .010588 -3.74213 0.000 U.S. grapes/Argentinean grapes .669583E-02 .424842E-02 1.57608 0.115 U.S. grapes/ROW grape .010593 .951660E-02 1.11313 0.266 Argentinean grape -.940781E-02 .389373E-02 -2.41614 0.016 Argentinean grape/ROW grape .886930E-03 .487254E-02 .182026 0.856 ROW grape -.049246 .013584 -3.62531 0.000 Israelis citrus -.021556 .502676E-02 -4.28828 0.000 Israelis citrus/Italian citrus .221872E-02 .276928E-02 .801189 0.423 Israelis citrus/ROW citrus .240213E-02 .187447E-02 1.28150 0.200 Italian citrus -.020363 .561152E-02 -3.62880 0.000 Italian citrus/ROW citrus -.197293E-02 .162961E-02 -1.21068 0.226 ROW citrus -.021612 .511057E-02 -4.22881 0.000 Table C-7. Marginal value shares of fruit juices in a block-wi se dependent uniformsubstitute Rotterdam model Products Estimates i SE t-statistics P-value U.S. orange .023935 .807320E-02 2.96476 0.003 Brazilian orange .781733 .026914 29.0453 0.000 ROW orange .744781E-02 .288702E-02 2.57975 0.010 U.S. grapefruit .030032 .553653E-02 5.42426 0.000 Israelis grapefruit .243101E-02 .142535E-02 1.70555 0.088 ROW grapefruit .154478E-02 .809084E-03 1.90929 0.056 U.S. apple .039106 .837319E-02 4.67034 0.000 Chinese apple .818502E-02 .265280E-02 3.08543 0.002 ROW apple .043093 .011718 3.67749 0.000 Thai pineapple .677959E-02 .111513E-02 6.07963 0.000 Philippine pineapple .614985E-02 .734483E-03 8.37304 0.000 ROW pineapple .362882E-03 .913188E-03 .397379 0.691 U.S. grapes .920016E-02 .442613E-02 2.07860 0.038 Argentinean grape .197440E-02 .107270E-02 1.84059 0.066 ROW grape .012908 .467776E-02 2.75942 0.006 Israelis citrus .969673E-02 .194521E-02 4.98492 0.000 Italian citrus .950458E-02 .210530E-02 4.51459 0.000 ROW citrus .591649E-02 .146101E-02 4.04957 0.000 -1.97888 .311601 -6.35068 0.000

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140 Table C-7 Continued Products Estimates i SE t-statistics P-value K1 .783859 .164457 4.76634 0.000 K2 21.2047 7.18763 2.95016 0.003 K3 841.401 19338.8 .043508 0.965 K4 4.94019 17.2078 .287090 0.774 K5 27.6275 13.9415 1.98167 0.048 K6 11.4152 7.02358 1.62527 0.104 Table C-8. Constant of propor tionality of fruit juice groups in a block-wise dependent uniform-substitute-Rotterdam model Products Estimates gh SE t-statistics P-value Orange/grapefruit .251369 .398478 .630825 0.528 Orange/apple .791079 .291463 2.71416 0.007 Orange/pineapple .341223 .482032 .707885 0.479 Orange/grapes 1.34229 .674993 1.98861 0.047 Orange/other citrus -.094332 .435253 -.216729 0.828 Grapefruit/apple -7.41443 3.23381 -2.29279 0.022 Grapefruit/pineapple 50.6194 13.4650 3.75932 0.000 Grapefruit/grapes -8.11878 9.42408 -.861493 0.389 Grapefruit/other citrus 6.87398 5.71871 1.20202 0.229 Apple/pineapple -15.7554 5.15323 -3.05738 0.002 Apple/grape 1.85589 5.43242 .341633 0.733 Apple/other citrus -1.71658 3.12146 -.549928 0.582 Pineapple/grape -11.7357 13.9605 -.840635 0.401 Pineapple/other citrus -20.4015 9.37285 -2.17666 0.030 Grapes/other citrus -13.0223 10.3033 -1.26389 0.206 Table C-9 Within-group relative price coefficients of block-wise dependent uniform substitute Rotterdam model Products Estimates SE t-statistics P-value U.S. Orange -.108070 .019726 -5.47866 0.000 U.S. orange/Brazilian orange .067488 .023219 2.90661 0.004 U.S. orange/ROW orange .642978E-03 .150383E-03 4.27559 0.000 Brazilian orange -1.39291 .059985 -23.2209 0.000 Brazilian orange/ROW orange .021000 .576683E-02 3.64151 0.000 ROW orange -.034071 .481407E-02 -7.07730 0.000 U.S. grapefruit -.065260 .897959E-02 -7.26760 0.000 U.S. grapefruit/Israelis grapefruit .926256E-02 .304626E-02 3.04064 0.002 U.S. grapefruit/ROW grapefruit .58 8587E-02 .156089E-02 3.77084 0.000 Israelis grapefruit -.013795 .363264E-02 -3.79765 0.000 Israelis grapefruit/ROW grapefruit .4 76452E-03 .198748E-03 2.39727 0.017 ROW grapefruit -.893998E-02 .130118E-02 -6.87068 0.000 U.S. apple -.027739 .012240 -2.26633 0.023 U.S. apple/Chinese apple -.598793E-02 .317106E-02 -1.88831 0.059 U.S. apple/ROW apple -.031526 .011917 -2.64553 0.008 Chinese apple -.107132E-02 .379707E-02 -.282144 0.778 Chinese apple/ROW apple -.659852E-02 .296054E-02 -2.22882 0.026 ROW apple -.033782 .019677 -1.71680 0.086 Thai. pineapple -.011702 .159136E-02 -7.35359 0.000 Thai. pineapple/Philippines pineapple .367849E-03 .130420E-02 .282051 0.778 Thai. pineapple/ROW pineapple .217055E-04 .908518E-04 .238911 0.811

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141 Table C-9 Continued Products Estimates SE t-statistics P-value Philipp. pineapple -.010649 .105798E-02 -10.0657 0.000 Philip. pineapple/ROW apple .196894E-04 .824165E-04 .238901 0.811 ROW pineapple -.646910E-03 .161833E-02 -.399739 0.689 U.S. grape -.034212 .961848E-02 -3.55695 0.000 U.S. grape/Argentinean grape .250221E-02 .129180E-02 1.93699 0.053 U.S. grape/ROW grape .016359 .742953E-02 2.20183 0.028 Argentinean grape -.930737E-02 .368287E-02 -2.52721 0.011 Argentinean grape/ROW grape .351062E-02 .196294E-02 1.78845 0.074 ROW grape -.041408 .010598 -3.90724 0.000 Israelis citrus -.020174 .331409E-02 -6.08720 0.000 Israelis citrus/Italian citrus .246119E-02 .148253E-02 1.66013 0.097 Israelis citrus/ROW citrus .153206E-02 .863379E-03 1.77449 0.076 Italian citrus -.019823 .348924E-02 -5.68105 0.000 Italian citrus/ROW citrus .150170E-02 .824028E-03 1.82239 0.068 ROW citrus -.012906 .221224E-02 -5.83400 0.000

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142 APPENDIX D PRICE ELASTICITIES OF FRUIT JUIC ES IN JAPAN IN DIFFERENT MARKET STRUCTURES Table D-1 Compensated price el asticities in the block inde pendent non-uniform substitute Rotterdam model Products Estimates SE t-statistic p-value U.S orange /Brazilian orange 1.32124 .289587 4.56250 0.000 U.S orange /ROW orange .084107 .094148 .893351 0.372 U.S orange /U.S grapefruit .020821 .788673E-02 2.63995 0.008 U.S orange /Israelis grapefruit .165653E-02 .213166E-02 .777110 0.437 U.S orange /ROW grapefruit .362166E-03 .119832E-02 .302228 0.762 U.S orange /U.S apple .028177 .011604 2.42832 0.015 U.S orange /Chinese apple .025862 .010026 2.57943 0.010 U.S orange /ROW apple .032910 .014574 2.25809 0.024 U.S orange /Thai pineapple .322414E-02 .141774E-02 2.27414 0.023 U.S orange /Philippines pineapple .549957E-02 .197710E-02 2.78164 0.005 U.S orange /ROW pineapple .597278E-03 .126514E-02 .472102 0.637 U.S orange /U.S grape .616171E-02 .406805E-02 1.51466 0.130 U.S orange /Argentinean grape -.592139E-04 .129673E-02 -.045664 0.964 U.S orange /ROW grape .799705E-02 .441252E-02 1.81235 0.070 U.S orange /Israelis citrus .500277E-02 .221493E-02 2.25865 0.024 U.S orange /Italian citrus .625923E-02 .263442E-02 2.37594 0.018 U.S orange /ROW citrus .631588E-02 .208804E-02 3.02478 0.002 Brazilian orange/U.S orange .376541 .082530 4.56250 0.000 Brazilian orange /ROW orange .104657 .031357 3.33755 0.001 Brazilian orange /U.S grapefruit .158256 .029750 5.31954 0.000 Brazilian orange /Israelis grapefru it .012591 .015786 .797640 0.425 Brazilian orange /ROW grapefruit .27 5280E-02 .899244E-02 .306124 0.760 Brazilian orange /U.S apple .214174 .052592 4.07236 0.000 Brazilian orange /Chinese apple .196573 .043131 4.55758 0.000 Brazilian orange /ROW apple .250147 .065800 3.80161 0.000 Brazilian orange /Thai Pineapple .024506 .796387E-02 3.07721 0.002 Brazilian orange /Philippines pineapple .041802 .805902E-02 5.18698 0.000 Brazilian orange /ROW Pineapple .453987E-02 .957600E-02 .474089 0.635 Brazilian orange /U.S grape .046835 .025360 1.84680 0.065 Brazilian orange /Argentinean grape -.450081E-03 .984323E-02 -.045725 0.964 Brazilian orange /ROW grape .060785 .025038 2.42773 0.015 Brazilian orange /Israelis citrus .038026 .011626 3.27073 0.001 Brazilian orange /Italian citrus .047576 .011853 4.01387 0.000 Brazilian orange /ROW citrus .048007 .883406E-02 5.43427 0.000 ROW orange/U.S orange .188043 .210492 .893351 0.372 ROW orange/Brazilian orange .821035 .245999 3.33755 0.001 ROW orange /U.S grapefruit .017893 .010040 1.78216 0.075 ROW orange /Israelis grapefruit .142361E-02 .194436E-02 .732175 0.464 ROW orange /ROW grapefruit .311243E-03 .103301E-02 .301297 0.763 ROW orange /U.S apple .024215 .012856 1.88366 0.060 ROW orange /Chinese apple .022225 .012497 1.77840 0.075 ROW orange /ROW apple .028283 .016161 1.75001 0.080

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143 Table D-1 Continued Products Estimates SE t-statistic p-value ROW orange /Thai pineapple .277080E-02 .171742E-02 1.61335 0.107 ROW orange /Philippines pineapple .472630E-02 .264276E-02 1.78839 0.074 ROW orange /ROW pineapple .513297E-03 .111734E-02 .459390 0.646 ROW orange /U.S grape .529533E-02 .397220E-02 1.33310 0.182 ROW orange /Argentinean grape -.508881E-04 .111433E-02 -.045667 0.964 ROW orange /ROW grape .687261E-02 .448822E-02 1.53125 0.126 ROW orange /Israelis citrus .429935E-02 .258938E-02 1.66038 0.097 ROW orange /Italian citrus .537914E-02 .306400E-02 1.75560 0.079 ROW orange /ROW citrus .542783E-02 .281229E-02 1.93004 0.054 U.S grapefruit/U.S orange .018657 .706730E-02 2.63995 0.008 U.S grapefruit/Brazilian orange .497606 .093543 5.31954 0.000 U.S grapefruit/ROW orange .717161E-02 .402412E-02 1.78216 0.075 U.S grapefruit/Israelis grapefruit .101769 .053267 1.91054 0.056 U.S grapefruit /ROW grapefruit .072159 .031081 2.32165 0.020 U.S grapefruit /U.S apple .026876 .784770E-02 3.42465 0.001 U.S grapefruit /Chinese apple .024667 .670010E-02 3.68157 0.000 U.S grapefruit /ROW apple .031390 .010538 2.97884 0.003 U.S grapefruit /Thai Pineapple .307519E-02 .110592E-02 2.78066 0.005 U.S grapefruit /Philippines Pineapple .524550E-02 .128740E-02 4.07450 0.000 U.S grapefruit /ROW Pineapple .569685E-03 .119376E-02 .477218 0.633 U.S grapefruit /U.S grape .587705E-02 .354771E-02 1.65658 0.098 U.S grapefruit /Argentinean grape -.564783E-04 .123661E-02 -.045672 0.964 U.S grapefruit /ROW grape .762760E-02 .346979E-02 2.19829 0.028 U.S grapefruit /Israelis citrus .477165E-02 .170892E-02 2.79221 0.005 U.S grapefruit /Italian citrus .597006E-02 .171974E-02 3.47148 0.001 U.S grapefruit /ROW citrus .602410E-02 .112057E-02 5.37593 0.000 Israelis grapefruit/U.S orange .46 1992E-02 .594500E-02 .777110 0.437 Israelis grapefruit/Brazilian orange .123217 .154477 .797640 0.425 Israelis grapefruit/ROW orange .177583E-02 .242542E-02 .732175 0.464 Israelis grapefruit/U.S grapefruit .316733 .165782 1.91054 0.056 Israelis grapefruit/ROW grapefruit .101898 .061756 1.65001 0.099 Israelis grapefruit /U.S apple .665494E-02 .838059E-02 .794089 0.427 Israelis grapefruit /Chinese apple .610801E-02 .780126E-02 .782951 0.434 Israelis grapefruit /ROW apple .777268E-02 .992639E-02 .783032 0.434 Israelis grapefruit /Thai Pineapple .761478E-03 .999705E-03 .761703 0.446 Israelis grapefruit /Philippines Pineapple .129889E-02 .165398E-02 .785311 0.432 Israelis grapefruit /ROW Pineapple .141065E-03 .349551E-03 .403561 0.687 Israelis grapefruit /U.S grape .145527E-02 .208258E-02 .698783 0.485 Israelis grapefruit /Argentinean grape -.139852E-04 .306963E-03 -.045560 0.964 Israelis grapefruit /ROW grape .188874E-02 .252413E-02 .748275 0.454 Israelis grapefruit /Israelis citrus .118156E-02 .156192E-02 .756475 0.449 Israelis grapefruit /Italian citrus .147831E-02 .192165E-02 .769292 0.442 Israelis grapefruit /ROW citrus .149169E-02 .187534E-02 .795422 0.426 ROW grapefruit/U.S orange .23482 2E-02 .776969E-02 .302228 0.762 ROW grapefruit/Brazilian orange .062629 .204587 .306124 0.760 ROW grapefruit/ROW orange .902623E-03 .299579E-02 .301297 0.763 ROW grapefruit/U.S grapefruit .522116 .224890 2.32165 0.020 ROW grapefruit/Israelis grapefruit .236898 .143574 1.65001 0.099 ROW grapefruit /U.S apple .338258E-02 .011218 .301536 0.763 ROW grapefruit /Chinese apple .310459E-02 .010345 .300091 0.764 ROW grapefruit /ROW apple .395071E-02 .013065 .302394 0.762 ROW grapefruit /Thai Pineapple .387045E-03 .127665E-02 .303173 0.762 ROW grapefruit /Philippines Pineapple .660202E-03 .216847E-02 .304455 0.761 ROW grapefruit /ROW Pineapple .717009E-04 .283864E-03 .252589 0.801

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144 Table D-1 Continued Products Estimates SE t-statistic p-value ROW grapefruit /U.S grape .739689E-03 .246901E-02 .299590 0.764 ROW grapefruit /Argentinean grape -.710840E-05 .156141E-03 -.045526 0.964 ROW grapefruit /ROW grape .960014E-03 .319410E-02 .300559 0.764 ROW grapefruit /Israelis citrus .600563E-03 .197850E-02 .303545 0.761 ROW grapefruit /Italian citrus .751396E-03 .246251E-02 .305134 0.760 ROW grapefruit /ROW citrus .758197E-03 .248439E-02 .305184 0.760 U.S apple/U.S orange .035946 .014803 2.42832 0.015 U.S apple/Brazilian orange .958718 .235421 4.07236 0.000 U.S apple/ROW orange .013817 .733532E-02 1.88366 0.060 U.S apple/U.S grapefruit .038261 .011172 3.42465 0.001 U.S apple/Israelis grapefruit .304413E-02 .383349E-02 .794089 0.427 U.S apple/ROW grapefruit .665536E-03 .220715E-02 .301536 0.763 U.S apple /Chinese apple -.128349 .151178 -.848993 0.396 U.S apple /ROW apple -.632934 .241559 -2.62021 0.009 U.S apple /Thai Pineapple .592485E-02 .235090E-02 2.52025 0.012 U.S apple /Philippines Pineapple .010106 .288415E-02 3.50409 0.000 U.S apple /ROW Pineapple .109759E-02 .231411E-02 .474303 0.635 U.S apple /U.S grape .011323 .699435E-02 1.61889 0.105 U.S apple /Argentinean grape -.108815E-03 .238045E-02 -.045712 0.964 U.S apple /ROW grape .014696 .712247E-02 2.06330 0.039 U.S apple /Israelis citrus .919336E-02 .351033E-02 2.61895 0.009 U.S apple /Italian citrus .011502 .408548E-02 2.81541 0.005 U.S apple /ROW citrus .011606 .289072E-02 4.01506 0.000 Chinese apple/U.S orange .025740 .997880E-02 2.57943 0.010 Chinese apple/Brazilian orange .686498 .150628 4.55758 0.000 Chinese apple/ROW orange .989397E-02 .556340E-02 1.77840 0.075 Chinese apple/U.S grapefruit .027397 .744170E-02 3.68157 0.000 Chinese apple/Israelis grapefruit .217978E-02 .278405E-02 .782951 0.434 Chinese apple/ROW grapefruit .476562E-03 .158806E-02 .300091 0.764 Chinese apple /U.S apple -.100134 .117945 -.848993 0.396 Chinese apple /ROW apple -.172418 .185903 -.927462 0.354 Chinese apple /Thai Pineapple .424254E-02 .151665E-02 2.79730 0.005 Chinese apple /Philippines Pineapple .723671E-02 .192800E-02 3.75347 0.000 Chinese apple /ROW Pineapple .785939E-03 .165091E-02 .476065 0.634 Chinese apple /U.S grape .810799E-02 .492428E-02 1.64653 0.100 Chinese apple /Argentinean grape -.779176E-04 .170353E-02 -.045739 0.964 Chinese apple /ROW grape .010523 .497631E-02 2.11463 0.034 Chinese apple /Israelis citrus .658298E-02 .229570E-02 2.86753 0.004 Chinese apple /Italian citrus .823631E-02 .264109E-02 3.11853 0.002 Chinese apple /ROW citrus .831086E-02 .183976E-02 4.51735 0.000 ROW apple/U.S orange .014428 .638953E-02 2.25809 0.024 ROW apple/Brazilian orange .384809 .101223 3.80161 0.000 ROW apple/ROW orange .554597E-02 .316911E-02 1.75001 0.080 ROW apple/U.S grapefruit .015357 .515542E-02 2.97884 0.003 ROW apple/Israelis grapefruit .122185E-02 .156041E-02 .783032 0.434 ROW apple/ROW grapefruit .267132E-03 .883391E-03 .302394 0.762 ROW apple /U.S apple -.217513 .083014 -2.62021 0.009 ROW apple /Chinese apple -.075948 .081888 -.927462 0.354 ROW apple /Thai Pineapple .237811E-02 .970736E-03 2.44980 0.014 ROW apple /Philippines Pineapple .405646E-02 .127597E-02 3.17911 0.001 ROW apple /ROW Pineapple .440550E-03 .923691E-03 .476945 0.633 ROW apple /U.S grape .454485E-02 .302379E-02 1.50303 0.133 ROW apple /Argentinean grape -.436759E-04 .953259E-03 -.045818 0.963 ROW apple /ROW grape .589859E-02 .285285E-02 2.06761 0.039

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145 Table D-1 Continued Products Estimates SE t-statistic p-value ROW apple /Israelis citrus .369002E-02 .157714E-02 2.33969 0.019 ROW apple /Italian citrus .461678E-02 .169382E-02 2.72567 0.006 ROW apple /ROW citrus .465857E-02 .128729E-02 3.61890 0.000 Thai pineapple/U.S orange .021352 .938905E-02 2.27414 0.023 Thai pineapple/Brazilian orange .569475 .185062 3.07721 0.002 Thai pineapple /ROW orange .820742E-02 .508719E-02 1.61335 0.107 Thai pineapple /U.S grapefruit .022727 .817320E-02 2.78066 0.005 Thai pineapple /Israelis grapefruit .180821E-02 .237390E-02 .761703 0.446 Thai pineapple /ROW grapefruit .395326E-03 .130396E-02 .303173 0.762 Thai pineapple /U.S apple .030757 .012204 2.52025 0.012 Thai pineapple /Chinese apple .028230 .010092 2.79730 0.005 Thai pineapple /ROW apple .035923 .014664 2.44980 0.014 Thai pineapple /Philippines pineapple .215600 .129259 1.66797 0.095 Thai pineapple /ROW Pineapple -.049248 .130583 -.377139 0.706 Thai pineapple /U.S grape .672588E-02 .438852E-02 1.53261 0.125 Thai pineapple /Argentinean GR -.646356E-04 .141318E-02 -.045738 0.964 Thai pineapple /ROW grape .872926E-02 .458452E-02 1.90407 0.057 Thai pineapple /Israelis citrus .546083E-02 .242554E-02 2.25138 0.024 Thai pineapple /Italian citrus .683233E-02 .273757E-02 2.49576 0.013 Thai pineapple /ROW citrus .689417E-02 .220942E-02 3.12035 0.002 Philippines pineapple/U.S orange .052529 .018884 2.78164 0.005 Philippines pineapple/Brazilian orange 1.40099 .270098 5.18698 0.000 Philippines pineapple /ROW orange .020191 .011290 1.78839 0.074 Philippines pineapple /U.S grapefruit .055912 .013722 4.07450 0.000 Philippines pineapple /Israelis grapefruit .444845E-02 .566457E-02 .785311 0.432 Philippines pineapple /ROW grapefruit .972560E-03 .319443E-02 .304455 0.761 Philippines pineapple /U.S apple .075667 .021594 3.50409 0.000 Philippines pineapple /Chinese apple .069449 .018503 3.75347 0.000 Philippines pineapple /ROW apple .088376 .027799 3.17911 0.001 Philippines pineapple /Thai pineapple .310952 .186425 1.66797 0.095 Philippines pineapple /ROW pineapple .233007 .190120 1.22558 0.220 Philippines pineapple /U.S grape .016547 .986842E-02 1.67673 0.094 Philippines pineapple /Argentinean grape -.159013E-03 .347860E-02 -.045712 0.964 Philippines pineapple /ROW grape .021475 .940750E-02 2.28278 0.022 Philippines pineapple /Israelis other citrus .013434 .481960E-02 2.78746 0.005 Philippines pineapple /Italian citrus .016809 .520368E-02 3.23012 0.001 Philippines pineapple /ROW other citrus .016961 .309996E-02 5.47125 0.000 ROW pineapple/U.S orange .483651E-02 .010245 .472102 0.637 ROW pineapple/Brazilian orange .128994 .272088 .474089 0.635 ROW pineapple /ROW orange .185909E-02 .404686E-02 .459390 0.646 ROW pineapple /U.S grapefruit .514795E-02 .010787 .477218 0.633 ROW pineapple /Israelis grapefruit .409583E-03 .101492E-02 .403561 0.687 ROW pineapple /ROW grapefruit .895467E-04 .354515E-03 .252589 0.801 ROW pineapple /U.S apple .696694E-02 .014689 .474303 0.635 ROW pineapple /Chinese apple .639437E-02 .013432 .476065 0.634 ROW pineapple /ROW apple .813709E-02 .017061 .476945 0.633 ROW pineapple /Thai pineapple -.060217 .159668 -.377139 0.706 ROW pineapple /Philippines pineapple .197540 .161181 1.22558 0.220 ROW pineapple /U.S grape .152350E-02 .333130E-02 .457329 0.647 ROW pineapple /Argentinean grape -.146408E-04 .322087E-03 -.045456 0.964 ROW pineapple /ROW grape .197730E-02 .420240E-02 .470516 0.638 ROW pineapple /Israelis citrus .123695E-02 .265972E-02 .465068 0.642 ROW pineapple /Italian citrus .154761E-02 .328073E-02 .471728 0.637 ROW pineapple /ROW citrus .156162E-02 .329046E-02 .474591 0.635

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146 Table D-1 Continued Products Estimates SE t-statistic p-value U.S grape/U.S orange .718253E-02 .474201E-02 1.51466 0.130 U.S grape/Brazilian orange .191564 .103727 1.84680 0.065 U.S grape/ROW orange .276087E-02 .207101E-02 1.33310 0.182 U.S grape/U.S grapefruit .764503E-02 .461496E-02 1.65658 0.098 U.S grape/Israelis grapefruit .608256E-03 .870451E-03 .698783 0.485 U.S grape/ROW grapefruit .132982E-03 .443882E-03 .299590 0.764 U.S grape/U.S apple .010346 .639101E-02 1.61889 0.105 U.S grape/Chinese apple .949604E-02 .576730E-02 1.64653 0.100 U.S grape/ROW apple .012084 .803981E-02 1.50303 0.133 U.S grape/Thai Pineapple .118386E-02 .772449E-03 1.53261 0.125 U.S grape /Philippines Pineapple .201937E-02 .120435E-02 1.67673 0.094 U.S grape /ROW Pineapple .219312E-03 .479550E-03 .457329 0.647 U.S grape /Argentinean grape .114908 .068875 1.66836 0.095 U.S grape /ROW grape .243103 .139356 1.74447 0.081 U.S grape /Israelis citrus .183695E-02 .121649E-02 1.51004 0.131 U.S grape /Italian citrus .229830E-02 .144642E-02 1.58896 0.112 U.S grape /ROW citrus .231911E-02 .128542E-02 1.80416 0.071 Argentinean grape/U.S orange -.467724E-03 .010243 -.045664 0.964 Argentinean grape/Brazilian orange -.012475 .272817 -.045725 0.964 Argentinean grape/ROW orange -.179787E-03 .393691E-02 -.045667 0.964 Argentinean grape/U.S grapefruit -.497842E-03 .010900 -.045672 0.964 Argentinean grape/Israelis grapefruit -.396094E-04 .869395E-03 -.045560 0.964 Argentinean grape/ROW grapefruit -.865977E-05 .190218E-03 -.045526 0.964 Argentinean grape/U.S apple -.673750E-03 .014739 -.045712 0.964 Argentinean grape/Chinese apple -.618379E-03 .013520 -.045739 0.964 Argentinean grape/ROW apple -.786912E-03 .017175 -.045818 0.963 Argentinean grape/Thai pineapple -.770926E-04 .168554E-02 -.045738 0.964 Argentinean grape /Philippines pineapple. -.131501E-03 .287673E-02 -.045712 0.964 Argentinean grape /ROW Pineapple -.142815E-04 .314184E-03 -.045456 0.964 Argentinean grape /U.S grape .778648 .466716 1.66836 0.095 Argentinean grape /ROW grape .163905 .510347 .321164 0.748 Argentinean grape /Israelis other citrus -.119622E-03 .261243E-02 -.045789 0.963 Argentinean grape /Italian citrus -.149665E-03 .327287E-02 -.045729 0.964 Argentinean grape /ROW other CT -.151019E-03 .330236E-02 -.045731 0.964 ROW grape/U.S orange .894107E-02 .493340E-02 1.81235 0.070 ROW grape/Brazilian orange .238466 .098226 2.42773 0.015 ROW grape/ROW orange .343683E-02 .224445E-02 1.53125 0.126 ROW grape/U.S grapefruit .951681E-02 .432919E-02 2.19829 0.028 ROW grape/Israelis grapefruit .757180E-03 .101190E-02 .748275 0.454 ROW grape/ROW grapefruit .165541E-03 .550779E-03 .300559 0.764 ROW grape/U.S apple .012880 .624218E-02 2.06330 0.039 ROW grape/Chinese apple .011821 .559012E-02 2.11463 0.034 ROW grape/ROW apple .015043 .727540E-02 2.06761 0.039 ROW grape/Thai Pineapple .147371E-02 .773979E-03 1.90407 0.057 ROW grape /Philippines Pineapple .251378E-02 .110119E-02 2.28278 0.022 ROW grape /ROW Pineapple .273008E-03 .580232E-03 .470516 0.638 ROW grape /U.S grape .233171 .133663 1.74447 0.081 ROW grape /Argentinean grape .023200 .072237 .321164 0.748 ROW grape /Israelis citrus .228670E-02 .116738E-02 1.95883 0.050 ROW grape /Italian citrus .286101E-02 .130515E-02 2.19210 0.028 ROW grape /ROW citrus .288691E-02 .119962E-02 2.40651 0.016 Israelis citrus/U.S orange .016410 .726559E-02 2.25865 0.024 Israelis citrus /Brazilian orange .437681 .133817 3.27073 0.001 Israelis citrus /ROW orange .630796E-02 .379911E-02 1.66038 0.097

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147 Table D-1 Continued Products Estimates SE t-statistic p-value Israelis citrus /U.S grapefruit .017467 .625569E-02 2.79221 0.005 Israelis citrus /Israelis grapefruit .138973E-02 .183711E-02 .756475 0.449 Israelis citrus /ROW grapefruit .303835E-03 .100096E-02 .303545 0.761 Israelis citrus /U.S apple .023639 .902618E-02 2.61895 0.009 Israelis citrus /Chinese apple .021696 .756620E-02 2.86753 0.004 Israelis citrus /ROW apple .027609 .011800 2.33969 0.019 Israelis citrus /Thai pineapple .270485E-02 .120142E-02 2.25138 0.024 Israelis citrus /Philippines pineapple .461380E-02 .165520E-02 2.78746 0.005 Israelis citrus /ROW Pineapple .501080E-03 .107743E-02 .465068 0.642 Israelis citrus /U.S grape .516929E-02 .342329E-02 1.51004 0.131 Israelis citrus /Argentinean GR -.496768E-04 .108490E-02 -.045789 0.963 Israelis citrus /ROW grape .670903E-02 .342501E-02 1.95883 0.050 Israelis citrus /Italian citrus .182783 .115721 1.57952 0.114 Israelis citrus /ROW citrus .163280 .084438 1.93374 0.053 Italian citrus/U.S orange .026244 .011046 2.37594 0.018 Italian citrus /Brazilian orange .699947 .174382 4.01387 0.000 Italian citrus /ROW orange .010088 .574609E-02 1.75560 0.079 Italian citrus /U.S grapefruit .027934 .804666E-02 3.47148 0.001 Italian citrus /Israelis grapefruit .222248E-02 .288900E-02 .769292 0.442 Italian citrus /ROW grapefruit .485899E-03 .159241E-02 .305134 0.760 Italian citrus /U.S apple .037804 .013428 2.81541 0.005 Italian citrus /Chinese apple .034697 .011126 3.11853 0.002 Italian citrus /ROW apple .044154 .016199 2.72567 0.006 Italian citrus /Thai pineapple .432565E-02 .173320E-02 2.49576 0.013 Italian citrus /Philippines pineapple .737848E-02 .228427E-02 3.23012 0.001 Italian citrus /ROW Pineapple .801336E-03 .169872E-02 .471728 0.637 Italian citrus /U.S grape .826683E-02 .520268E-02 1.58896 0.112 Italian citrus /Argentinean grape -.794441E-04 .173728E-02 -.045729 0.964 Italian citrus /ROW grape .010729 .489450E-02 2.19210 0.028 Italian citrus /Israelis citrus .233632 .147914 1.57952 0.114 Italian citrus /ROW citrus -.012224 .092850 -.131649 0.895 ROW citrus/U.S orange .018265 .603858E-02 3.02478 0.002 ROW citrus /Brazilian orange .487153 .089645 5.43427 0.000 ROW citrus /ROW orange .702097E-02 .363774E-02 1.93004 0.054 ROW citrus /U.S grapefruit .019442 .361641E-02 5.37593 0.000 ROW citrus /Israelis grapefruit .154682E-02 .194465E-02 .795422 0.426 ROW citrus /ROW grapefruit .338179E-03 .110811E-02 .305184 0.760 ROW citrus /U.S apple .026311 .655310E-02 4.01506 0.000 ROW citrus /Chinese apple .024149 .534578E-02 4.51735 0.000 ROW citrus /ROW apple .030730 .849159E-02 3.61890 0.000 ROW citrus /Thai pineapple .301060E-02 .964826E-03 3.12035 0.002 ROW citrus /Philippines pineapple .513532E-02 .938601E-03 5.47125 0.000 ROW citrus /ROW Pineapple .557719E-03 .117516E-02 .474591 0.635 ROW citrus /U.S grape .575360E-02 .318908E-02 1.80416 0.071 ROW citrus /Argentinean GR -.552920E-04 .120908E-02 -.045731 0.964 ROW citrus /ROW grape .746738E-02 .310299E-02 2.40651 0.016 ROW citrus /Israelis citrus .143952 .074443 1.93374 0.053 ROW citrus /Italian citrus -.843113E-02 .064043 -.131649 0.895

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148 Table D-2 Compensated price elas ticities of fruit juices in the block independent uniform substitute Rotterdam model Products Estimates SE t-statistics p-value U.S orange /Brazilian orange 1.35664 .140729 9.64010 0.000 U.S orange /ROW orange .016557 .347986E-02 4.75796 0.000 U.S orange /U.S grapefruit .019375 .683231E-02 2.83585 0.005 U.S orange /Israelis grapefruit .209554E-02 .147707E-02 1.41872 0.156 U.S orange /ROW grapefruit .127401E-02 .836867E-03 1.52235 0.128 U.S orange /U.S apple .023970 .904463E-02 2.65021 0.008 U.S orange /Chinese apple .025823 .910398E-02 2.83640 0.005 U.S orange /ROW apple .034569 .013784 2.50788 0.012 U.S orange /Thai pineapple .279267E-02 .119275E-02 2.34137 0.019 U.S orange /Philippines pineapple .549629E-02 .180020E-02 3.05316 0.002 U.S orange /ROW pineapple .692329E-03 .645454E-03 1.07262 0.283 U.S orange /U.S grape .610516E-02 .358166E-02 1.70456 0.088 U.S orange /Argentinean grape .102563E-02 .709685E-03 1.44520 0.148 U.S orange /ROW grape .729317E-02 .386648E-02 1.88625 0.059 U.S orange /Israelis citrus .587402E-02 .212249E-02 2.76751 0.006 U.S orange /Italian citrus .589835E-02 .227377E-02 2.59408 0.009 U.S orange /ROW citrus .563513E-02 .163536E-02 3.44581 0.001 Brazilian orange/U.S orange .386631 .040106 9.64010 0.000 Brazilian orange /ROW orange .128930 .015603 8.26342 0.000 Brazilian orange /U.S grapefruit .150877 .028799 5.23897 0.000 Brazilian orange /Israelis grapefru it .016318 .010331 1.57954 0.114 Brazilian orange /ROW grapefruit .99 2072E-02 .570828E-02 1.73795 0.082 Brazilian orange /U.S apple .186657 .049195 3.79425 0.000 Brazilian orange /Chinese apple .201081 .042108 4.77532 0.000 Brazilian orange /ROW apple .269186 .066068 4.07439 0.000 Brazilian orange /Thai Pineapple .021747 .721234E-02 3.01519 0.003 Brazilian orange /Philippines pineapple .042800 .782044E-02 5.47281 0.000 Brazilian orange /ROW Pineapple .539119E-02 .481788E-02 1.11900 0.263 Brazilian orange /U.S grape .047541 .023125 2.05586 0.040 Brazilian orange /Argentinean grape .798666E-02 .503245E-02 1.58703 0.113 Brazilian orange /ROW grape .056792 .023989 2.36740 0.018 Brazilian orange /Israelis citrus .045741 .983527E-02 4.65073 0.000 Brazilian orange /Italian citrus .045931 .011038 4.16096 0.000 Brazilian orange /ROW citrus .043881 .803815E-02 5.45908 0.000 ROW orange/U.S orange .037018 .778012E-02 4.75796 0.000 ROW orange/Brazilian orange 1.01146 .122402 8.26342 0.000 ROW orange /U.S grapefruit .014446 .566488E-02 2.55002 0.011 ROW orange /Israelis grapefruit .156235E-02 .113281E-02 1.37918 0.168 ROW orange /ROW grapefruit .949849E-03 .642005E-03 1.47950 0.139 ROW orange /U.S apple .017871 .717880E-02 2.48945 0.013 ROW orange /Chinese apple .019252 .755050E-02 2.54980 0.011 ROW orange /ROW apple .025773 .010890 2.36675 0.018 ROW orange /Thai pineapple .208211E-02 .966564E-03 2.15413 0.031 ROW orange /Philippines pineapple .409782E-02 .153002E-02 2.67828 0.007 ROW orange /ROW pineapple .516173E-03 .489660E-03 1.05415 0.292 ROW orange /U.S grape .455177E-02 .274755E-02 1.65667 0.098 ROW orange /Argentinean grape .764674E-03 .538824E-03 1.41915 0.156 ROW orange /ROW grape .543750E-02 .298340E-02 1.82259 0.068 ROW orange /Israelis citrus .437944E-02 .173810E-02 2.51967 0.012 ROW orange /Italian citrus .439758E-02 .183113E-02 2.40157 0.016 ROW orange /ROW citrus .420133E-02 .140617E-02 2.98779 0.003 U.S grapefruit/U.S orange .017362 .612243E-02 2.83585 0.005

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149 Table D-2 Continued Products Estimates SE t-statistics p-value U.S grapefruit/Brazilian orange .474404 .090553 5.23897 0.000 U.S grapefruit/ROW orange .578984E-02 .227051E-02 2.55002 0.011 U.S grapefruit/Israelis grapefruit .1 17086 .136823E-02 85.5749 0.000 U.S grapefruit /ROW grapefruit .071184 .779499E-03 91.3199 0.000 U.S grapefruit /U.S apple .022736 .698958E-02 3.25281 0.001 U.S grapefruit /Chinese apple .024493 .650614E-02 3.76456 0.000 U.S grapefruit /ROW apple .032788 .010617 3.08834 0.002 U.S grapefruit /Thai Pineapple .264886E-02 .975307E-03 2.71592 0.007 U.S grapefruit /Philippines Pineapple .521325E-02 .125832E-02 4.14302 0.000 U.S grapefruit /ROW Pineapple .656676E-03 .592520E-03 1.10828 0.268 U.S grapefruit /U.S grape .579076E-02 .318094E-02 1.82046 0.069 U.S grapefruit /Argentinean grape .972818E-03 .634359E-03 1.53355 0.125 U.S grapefruit /ROW grape .691759E-02 .320989E-02 2.15509 0.031 U.S grapefruit /Israelis citrus .557153E-02 .160619E-02 3.46878 0.001 U.S grapefruit /Italian citrus .559461E-02 .159199E-02 3.51422 0.000 U.S grapefruit /ROW citrus .534494E-02 .101128E-02 5.28533 0.000 Israelis grapefruit/U.S orange .58 4426E-02 .411941E-02 1.41872 0.156 Israelis grapefruit/Brazilian orange .159688 .101097 1.57954 0.114 Israelis grapefruit/ROW orange .194890E-02 .141308E-02 1.37918 0.168 Israelis grapefruit/U.S grapefruit .364404 .425831E-02 85.5749 0.000 Israelis grapefruit/ROW grapefruit .023961 .479156E-03 50.0066 0.000 Israelis grapefruit /U.S apple .765302E-02 .529825E-02 1.44444 0.149 Israelis grapefruit /Chinese apple .824442E-02 .569723E-02 1.44709 0.148 Israelis grapefruit /ROW apple .011037 .766012E-02 1.44081 0.150 Israelis grapefruit /Thai Pineapple .891622E-03 .643206E-03 1.38622 0.166 Israelis grapefruit /Philippines Pineapple .175481E-02 .115787E-02 1.51555 0.130 Israelis grapefruit /ROW Pineapple .221042E-03 .244049E-03 .905727 0.365 Israelis grapefruit /U.S grape .194921E-02 .163711E-02 1.19064 0.234 Israelis grapefruit /Argentinean grape .327457E-03 .300618E-03 1.08928 0.276 Israelis grapefruit /ROW grape .232851E-02 .181310E-02 1.28427 0.199 Israelis grapefruit /Israelis citrus .187541E-02 .127453E-02 1.47145 0.141 Israelis grapefruit /Italian citrus .188318E-02 .127557E-02 1.47635 0.140 Israelis grapefruit /ROW citrus .179914E-02 .114897E-02 1.56587 0.117 ROW grapefruit/U.S orange .82604 2E-02 .542609E-02 1.52235 0.128 ROW grapefruit/Brazilian orange .225706 .129869 1.73795 0.082 ROW grapefruit/ROW orange .275462E-02 .186185E-02 1.47950 0.139 ROW grapefruit/U.S grapefruit .51 5058 .564015E-02 91.3199 0.000 ROW grapefruit/Israelis grapefruit .0 55706 .111397E-02 50.0066 0.000 ROW grapefruit /U.S apple .010817 .698299E-02 1.54904 0.121 ROW grapefruit /Chinese apple .011653 .749386E-02 1.55499 0.120 ROW grapefruit /ROW apple .015600 .010045 1.55304 0.120 ROW grapefruit /Thai Pineapple .126024E-02 .846561E-03 1.48866 0.137 ROW grapefruit /Philippines Pineapple .248029E-02 .150239E-02 1.65090 0.099 ROW grapefruit /ROW Pineapple .312425E-03 .335513E-03 .931186 0.352 ROW grapefruit /U.S grape .275506E-02 .219401E-02 1.25572 0.209 ROW grapefruit /Argentinean grape .462835E-03 .407403E-03 1.13606 0.256 ROW grapefruit /ROW grape .329117E-02 .241929E-02 1.36039 0.174 ROW grapefruit /Israelis citrus .265075E-02 .166666E-02 1.59046 0.112 ROW grapefruit /Italian citrus .266173E-02 .165783E-02 1.60555 0.108 ROW grapefruit /ROW citrus .254295E-02 .148028E-02 1.71789 0.086 U.S apple/U.S orange .030579 .011538 2.65021 0.008 U.S apple/Brazilian orange .835539 .220212 3.79425 0.000 U.S apple/ROW orange .010197 .409621E-02 2.48945 0.013 U.S apple/U.S grapefruit .032367 .995060E-02 3.25281 0.001

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150 Table D-2 Continued Products Estimates SE t-statistics p-value U.S apple/Israelis grapefruit .350068E-02 .242355E-02 1.44444 0.149 U.S apple/ROW grapefruit .212828E-02 .137393E-02 1.54904 0.121 U.S apple /Chinese apple -.195784 .015172 -12.9039 0.000 U.S apple /ROW apple -.262096 .021506 -12.1873 0.000 U.S apple /Thai Pineapple .466527E-02 .194148E-02 2.40294 0.016 U.S apple /Philippines Pineapple .918178E-02 .270749E-02 3.39126 0.001 U.S apple /ROW Pineapple .115656E-02 .106526E-02 1.08571 0.278 U.S apple /U.S grape .010199 .582505E-02 1.75087 0.080 U.S apple /Argentinean grape .171337E-02 .116862E-02 1.46614 0.143 U.S apple /ROW grape .012184 .610349E-02 1.99616 0.046 U.S apple /Israelis citrus .981280E-02 .322691E-02 3.04093 0.002 U.S apple /Italian citrus .985345E-02 .354608E-02 2.77869 0.005 U.S apple /ROW citrus .941372E-02 .251109E-02 3.74885 0.000 Chinese apple/U.S orange .025701 .906104E-02 2.83640 0.005 Chinese apple/Brazilian orange .702242 .147057 4.77532 0.000 Chinese apple/ROW orange .857047E-02 .336123E-02 2.54980 0.011 Chinese apple/U.S grapefruit .027204 .722627E-02 3.76456 0.000 Chinese apple/Israelis grapefruit .294220E-02 .203318E-02 1.44709 0.148 Chinese apple/ROW grapefruit .178874E-02 .115033E-02 1.55499 0.120 Chinese apple /U.S apple -.152746 .011837 -12.9039 0.000 Chinese apple /ROW apple -.220282 .016359 -13.4652 0.000 Chinese apple /Thai Pineapple .392100E-02 .141692E-02 2.76726 0.006 Chinese apple /Philippines Pineapple .771697E-02 .193201E-02 3.99426 0.000 Chinese apple /ROW Pineapple .972052E-03 .879485E-03 1.10525 0.269 Chinese apple /U.S grape .857184E-02 .476039E-02 1.80066 0.072 Chinese apple /Argentinean grape .144002E-02 .970316E-03 1.48408 0.138 Chinese apple /ROW grape .010240 .489075E-02 2.09372 0.036 Chinese apple /Israelis citrus .824731E-02 .228754E-02 3.60532 0.000 Chinese apple /Italian citrus .828148E-02 .254828E-02 3.24983 0.001 Chinese apple /ROW citrus .791190E-02 .166761E-02 4.74444 0.000 ROW apple/U.S orange .015155 .604306E-02 2.50788 0.012 ROW apple/Brazilian orange .414099 .101635 4.07439 0.000 ROW apple/ROW orange .505385E-02 .213536E-02 2.36675 0.018 ROW apple/U.S grapefruit .016042 .519421E-02 3.08834 0.002 ROW apple/Israelis grapefruit .173496E-02 .120416E-02 1.44081 0.150 ROW apple/ROW grapefruit .105479E-02 .679178E-03 1.55304 0.120 ROW apple /U.S apple -.090071 .739062E-02 -12.1873 0.000 ROW apple /Chinese apple -.097032 .720611E-02 -13.4652 0.000 ROW apple /Thai Pineapple .231214E-02 .933327E-03 2.47731 0.013 ROW apple /Philippines Pineapple .455055E-02 .133857E-02 3.39955 0.001 ROW apple /ROW Pineapple .573201E-03 .524794E-03 1.09224 0.275 ROW apple /U.S grape .505466E-02 .309022E-02 1.63569 0.102 ROW apple /Argentinean grape .849156E-03 .608877E-03 1.39463 0.163 ROW apple /ROW grape .603824E-02 .293661E-02 2.05620 0.040 ROW apple /Israelis citrus .486329E-02 .169898E-02 2.86248 0.004 ROW apple /Italian citrus .488344E-02 .169020E-02 2.88926 0.004 ROW apple /ROW citrus .466550E-02 .120581E-02 3.86918 0.000 Thai pineapple/U.S orange .018495 .789903E-02 2.34137 0.019 Thai pineapple/Brazilian orange .505342 .167599 3.01519 0.003 Thai pineapple /ROW orange .616742E-02 .286307E-02 2.15413 0.031 Thai pineapple /U.S grapefruit .019576 .720791E-02 2.71592 0.007 Thai pineapple /Israelis grapefruit .211725E-02 .152736E-02 1.38622 0.166 Thai pineapple /ROW grapefruit .128720E-02 .864674E-03 1.48866 0.137 Thai pineapple /U.S apple .024219 .010079 2.40294 0.016

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151 Table D-2 Continued Products Estimates SE t-statistics p-value Thai pineapple /Chinese apple .026090 .942810E-02 2.76726 0.006 Thai pineapple /ROW apple .034927 .014099 2.47731 0.013 Thai pineapple /Philippines pineapple .240930 .238113E-02 101.183 0.000 Thai pineapple /ROW Pineapple .030348 .704226E-03 43.0944 0.000 Thai pineapple /U.S grape .616840E-02 .374974E-02 1.64502 0.100 Thai pineapple /Argentinean GR .103626E-02 .745014E-03 1.39093 0.164 Thai pineapple /ROW grape .736872E-02 .398682E-02 1.84827 0.065 Thai pineapple /Israelis citrus .593487E-02 .228441E-02 2.59798 0.009 Thai pineapple /Italian citrus .595946E-02 .237175E-02 2.51268 0.012 Thai pineapple /ROW citrus .569351E-02 .186220E-02 3.05741 0.002 Philippines pineapple/U.S orange .052498 .017195 3.05316 0.002 Philippines pineapple/Brazilian orange 1.43444 .262102 5.47281 0.000 Philippines pineapple /ROW orange .017506 .653647E-02 2.67828 0.007 Philippines pineapple /U.S grapefruit .055568 .013412 4.14302 0.000 Philippines pineapple /Israelis grapefruit .600990E-02 .396549E-02 1.51555 0.130 Philippines pineapple /ROW grapefruit .365378E-02 .221321E-02 1.65090 0.099 Philippines pineapple /U.S apple .068745 .020271 3.39126 0.001 Philippines pineapple /Chinese apple .074058 .018541 3.99426 0.000 Philippines pineapple /ROW apple .099141 .029163 3.39955 0.001 Philippines pineapple /Thai pineapple .347485 .343423E-02 101.183 0.000 Philippines pineapple /ROW pineapple .086145 .183038E-02 47.0638 0.000 Philippines pineapple /U.S grape .017509 .944625E-02 1.85357 0.064 Philippines pineapple /Argentinean grape .294147E-02 .192807E-02 1.52560 0.127 Philippines pineapple /ROW grape .020916 .933541E-02 2.24055 0.025 Philippines pineapple /Israelis other citrus .016846 .465127E-02 3.62189 0.000 Philippines pineapple /Italian citrus .016916 .498566E-02 3.39297 0.001 Philippines pineapple /ROW other citrus .016161 .278002E-02 5.81338 0.000 ROW pineapple/U.S orange .560620E-02 .522663E-02 1.07262 0.283 ROW pineapple/Brazilian orange .153183 .136893 1.11900 0.263 ROW pineapple /ROW orange .186951E-02 .177348E-02 1.05415 0.292 ROW pineapple /U.S grapefruit .593405E-02 .535430E-02 1.10828 0.268 ROW pineapple /Israelis grapefruit .641794E-03 .708595E-03 .905727 0.365 ROW pineapple /ROW grapefruit .390186E-03 .419020E-03 .931186 0.352 ROW pineapple /U.S apple .734127E-02 .676171E-02 1.08571 0.278 ROW pineapple /Chinese apple .790858E-02 .715546E-02 1.10525 0.269 ROW pineapple /ROW apple .010587 .969311E-02 1.09224 0.275 ROW pineapple /Thai pineapple .037108 .861080E-03 43.0944 0.000 ROW pineapple /Philippines pineapple .073032 .155177E-02 47.0638 0.000 ROW pineapple /U.S grape .186981E-02 .192404E-02 .971815 0.331 ROW pineapple /Argentinean grape .314118E-03 .342824E-03 .916265 0.360 ROW pineapple /ROW grape .223366E-02 .218496E-02 1.02229 0.307 ROW pineapple /Israelis citrus .179902E-02 .166480E-02 1.08062 0.280 ROW pineapple /Italian citrus .180647E-02 .166462E-02 1.08521 0.278 ROW pineapple /ROW citrus .172585E-02 .153880E-02 1.12156 0.262 U.S grape/U.S orange .711661E-02 .417504E-02 1.70456 0.088 U.S grape/Brazilian orange .194453 .094585 2.05586 0.040 U.S grape/ROW orange .237319E-02 .143251E-02 1.65667 0.098 U.S grape/U.S grapefruit .753279E-02 .413786E-02 1.82046 0.069 U.S grape/Israelis grapefruit .814705E-03 .684259E-03 1.19064 0.234 U.S grape/ROW grapefruit .495309E-03 .394443E-03 1.25572 0.209 U.S grape/U.S apple .931915E-02 .532257E-02 1.75087 0.080 U.S grape/Chinese apple .010039 .557535E-02 1.80066 0.072 U.S grape/ROW apple .013440 .821645E-02 1.63569 0.102 U.S grape/Thai Pineapple .108574E-02 .660014E-03 1.64502 0.100

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152 Table D-2 Continued Products Estimates SE t-statistics p-value U.S grape /Philippines Pineapple .213685E-02 .115283E-02 1.85357 0.064 U.S grape /ROW Pineapple .269164E-03 .276971E-03 .971815 0.331 U.S grape /Argentinean grape .039092 .378769E-03 103.209 0.000 U.S grape /ROW grape .277981 .201337E-02 138.067 0.000 U.S grape /Israelis citrus .228371E-02 .128703E-02 1.77439 0.076 U.S grape /Italian citrus .229317E-02 .129962E-02 1.76448 0.078 U.S grape /ROW citrus .219083E-02 .109370E-02 2.00314 0.045 Argentinean grape/U.S orange .810137E-02 .560572E-02 1.44520 0.148 Argentinean grape/Brazilian orange .221360 .139481 1.58703 0.113 Argentinean grape/ROW orange .270158E-02 .190366E-02 1.41915 0.156 Argentinean grape/U.S grapefruit .857513E-02 .559170E-02 1.53355 0.125 Argentinean grape/Israelis grapefruit .927439E-03 .851425E-03 1.08928 0.276 Argentinean grape/ROW grapefruit .563847E-03 .496317E-03 1.13606 0.256 Argentinean grape/U.S apple .010609 .723580E-02 1.46614 0.143 Argentinean grape/Chinese apple .011428 .770073E-02 1.48408 0.138 Argentinean grape/ROW apple .015299 .010970 1.39463 0.163 Argentinean grape/Thai pineapple .123597E-02 .888598E-03 1.39093 0.164 Argentinean grape /Philippines pineapple. .243254E-02 .159448E-02 1.52560 0.127 Argentinean grape /ROW Pineapple .306410E-03 .334412E-03 .916265 0.360 Argentinean grape /U.S grape .264899 .256663E-02 103.209 0.000 Argentinean grape /ROW grape .316446 .274614E-02 115.233 0.000 Argentinean grape /Israelis other citrus .259971E-02 .177406E-02 1.46541 0.143 Argentinean grape /Italian citrus .261048E-02 .178099E-02 1.46575 0.143 Argentinean grape /ROW other CT .249399E-02 .158467E-02 1.57382 0.116 ROW grape/U.S orange .815410E-02 .432291E-02 1.88625 0.059 ROW grape/Brazilian orange .222801 .094112 2.36740 0.018 ROW grape/ROW orange .271916E-02 .149192E-02 1.82259 0.068 ROW grape/U.S grapefruit .863095E-02 .400492E-02 2.15509 0.031 ROW grape/Israelis grapefruit .933476E-03 .726853E-03 1.28427 0.199 ROW grape/ROW grapefruit .567517E-03 .417173E-03 1.36039 0.174 ROW grape/U.S apple .010678 .534914E-02 1.99616 0.046 ROW grape/Chinese apple .011503 .549400E-02 2.09372 0.036 ROW grape/ROW apple .015399 .748901E-02 2.05620 0.040 ROW grape/Thai Pineapple .124402E-02 .673073E-03 1.84827 0.065 ROW grape /Philippines Pineapple .244837E-02 .109275E-02 2.24055 0.025 ROW grape /ROW Pineapple .308404E-03 .301680E-03 1.02229 0.307 ROW grape /U.S grape .266623 .193111E-02 138.067 0.000 ROW grape /Argentinean grape .044791 .388703E-03 115.233 0.000 ROW grape /Israelis citrus .261664E-02 .124001E-02 2.11018 0.035 ROW grape /Italian citrus .262747E-02 .121925E-02 2.15498 0.031 ROW grape /ROW citrus .251022E-02 .106985E-02 2.34632 0.019 Israelis citrus/U.S orange .019268 .696237E-02 2.76751 0.006 Israelis citrus /Brazilian orange .526486 .113205 4.65073 0.000 Israelis citrus /ROW orange .642547E-02 .255013E-02 2.51967 0.012 Israelis citrus /U.S grapefruit .020395 .587965E-02 3.46878 0.001 Israelis citrus /Israelis grapefruit .220583E-02 .149909E-02 1.47145 0.141 Israelis citrus /ROW grapefruit .134106E-02 .843192E-03 1.59046 0.112 Israelis citrus /U.S apple .025232 .829740E-02 3.04093 0.002 Israelis citrus /Chinese apple .027182 .753933E-02 3.60532 0.000 Israelis citrus /ROW apple .036388 .012712 2.86248 0.004 Israelis citrus /Thai pineapple .293966E-02 .113151E-02 2.59798 0.009 Israelis citrus /Philippines pineapple .578558E-02 .159739E-02 3.62189 0.000 Israelis citrus /ROW Pineapple .728769E-03 .674397E-03 1.08062 0.280 Israelis citrus /U.S grape .642650E-02 .362180E-02 1.77439 0.076

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153 Table D-2 Continued Products Estimates SE t-statistics p-value Israelis citrus /Argentinean GR .107962E-02 .736736E-03 1.46541 0.143 Israelis citrus /ROW grape .767703E-02 .363810E-02 2.11018 0.035 Israelis citrus /Italian citrus .088372 .209589E-02 42.1645 0.000 Israelis citrus /ROW citrus .084428 .126626E-02 66.6754 0.000 Italian citrus/U.S orange .024731 .953356E-02 2.59408 0.009 Italian citrus /Brazilian orange .675741 .162400 4.16096 0.000 Italian citrus /ROW orange .824704E-02 .343402E-02 2.40157 0.016 Italian citrus /U.S grapefruit .026177 .744891E-02 3.51422 0.000 Italian citrus /Israelis grapefruit .283117E-02 .191769E-02 1.47635 0.140 Italian citrus /ROW grapefruit .172124E-02 .107205E-02 1.60555 0.108 Italian citrus /U.S apple .032385 .011655 2.77869 0.005 Italian citrus /Chinese apple .034887 .010735 3.24983 0.001 Italian citrus /ROW apple .046704 .016165 2.88926 0.004 Italian citrus /Thai pineapple .377303E-02 .150159E-02 2.51268 0.012 Italian citrus /Philippines pineapple .742574E-02 .218857E-02 3.39297 0.001 Italian citrus /ROW Pineapple .935369E-03 .861923E-03 1.08521 0.278 Italian citrus /U.S grape .824836E-02 .467466E-02 1.76448 0.078 Italian citrus /Argentinean grape .138568E-02 .945376E-03 1.46575 0.143 Italian citrus /ROW grape .985341E-02 .457238E-02 2.15498 0.031 Italian citrus /Israelis citrus .112957 .267896E-02 42.1645 0.000 Italian citrus /ROW citrus .108363 .180921E-02 59.8952 0.000 ROW citrus/U.S orange .016297 .472942E-02 3.44581 0.001 ROW citrus /Brazilian orange .445287 .081568 5.45908 0.000 ROW citrus /ROW orange .543448E-02 .181890E-02 2.98779 0.003 ROW citrus /U.S grapefruit .017250 .326370E-02 5.28533 0.000 ROW citrus /Israelis grapefruit .186563E-02 .119143E-02 1.56587 0.117 ROW citrus /ROW grapefruit .113423E-02 .660248E-03 1.71789 0.086 ROW citrus /U.S apple .021340 .569251E-02 3.74885 0.000 ROW citrus /Chinese apple .022989 .484556E-02 4.74444 0.000 ROW citrus /ROW apple .030776 .795412E-02 3.86918 0.000 ROW citrus /Thai pineapple .248628E-02 .813200E-03 3.05741 0.002 ROW citrus /Philippines pineapple .489328E-02 .841728E-03 5.81338 0.000 ROW citrus /ROW Pineapple .616372E-03 .549568E-03 1.12156 0.262 ROW citrus /U.S grape .543535E-02 .271342E-02 2.00314 0.045 ROW citrus /Argentinean GR .913111E-03 .580188E-03 1.57382 0.116 ROW citrus /ROW grape .649302E-02 .276732E-02 2.34632 0.019 ROW citrus /Israelis citrus .074434 .111637E-02 66.6754 0.000 ROW citrus /Italian citrus .074743 .124789E-02 59.8952 0.000 Table D-3 Compensated price elas ticities of fruit juices in the block-wise dependent nonuniform substitute Rotterdam model Products Estimates SD t-statistic p-value U.S orange /Brazilian orange 1.28083 .282607 4.53218 0.000 U.S orange /ROW orange .113355 .093998 1.20594 0.228 U.S orange /U.S grapefruit .011616 .017615 .659440 0.510 U.S orange /Israelis grapefruit -.000639 .001230 -.519525 0.603 U.S orange /ROW grapefruit .000995 .001601 .622045 0.534 U.S orange /U.S apple -.035930 .019872 -1.80811 0.071 U.S orange /Chinese apple -.034077 .018055 -1.88738 0.059 U.S orange /ROW apple -.046112 .026299 -1.75339 0.080 U.S orange /Thai pineapple .006567 .004082 1.60853 0.108 U.S orange /Philippines pineapple .010245 .006032 1.69847 0.089 U.S orange /ROW pineapple .000889 .001460 .609119 0.542

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154 Table D-3 Continued Products Estimates SD t-statistic p-value U.S orange /U.S grape -.000988 .008365 -.118156 0.906 U.S orange /Argentinean grape -.000080 .000693 -.116462 0.907 U.S orange /ROW grape -.001671 .014148 -.118160 0.906 U.S orange /Israelis citrus -.001252 .004129 -.303321 0.762 U.S orange /Italian citrus -.001487 .004859 -.306142 0.759 U.S orange /ROW citrus -.001566 .005051 -.310128 0.756 Brazilian orange/U.S orange .365024 .080540 4.53218 0.000 Brazilian orange /ROW orange .103392 .030470 3.39330 0.001 Brazilian orange /U.S grapefruit .068377 .103344 .661641 0.508 Brazilian orange /Israelis grapefruit -.003762 .007228 -.520477 0.603 Brazilian orange /ROW grapefruit .005862 .009350 .626958 0.531 Brazilian orange /U.S apple -.211498 .094338 -2.24193 0.025 Brazilian orange /Chinese apple -.200590 .086278 -2.32491 0.020 Brazilian orange /ROW apple -.271428 .120918 -2.24472 0.025 Brazilian orange /Thai Pineapple .038656 .020728 1.86492 0.062 Brazilian orange /Philippines pineapple .060308 .030041 2.00754 0.045 Brazilian orange /ROW Pineapple .005237 .008429 .621271 0.534 Brazilian orange /U.S grape -.005818 .049042 -.118643 0.906 Brazilian orange /Argentinean grape -.00475 .004070 -.116820 0.907 Brazilian orange /ROW grape -.009839 .082944 -.118634 0.906 Brazilian orange /Israelis citrus -.007372 .024064 -.306361 0.759 Brazilian orange /Italian citrus -.008757 .028312 -.309320 0.757 Brazilian orange /ROW citrus -.009221 .029489 -.312697 0.755 ROW orange/U.S orange .253434 .210156 1.20594 0.228 ROW orange/Brazilian orange .811115 .239034 3.39330 0.001 ROW orange /U.S grapefruit .003046 .006228 .489167 0.625 ROW orange /Israelis grapefruit -.001673 .000396 -.423284 0.672 ROW orange /ROW grapefruit .000261 .000549 .475047 0.635 ROW orange /U.S apple -.009424 .013975 -.674378 0.500 ROW orange /Chinese apple -.008938 .013722 -.651417 0.515 ROW orange /ROW apple -.012095 .018411 -.656940 0.511 ROW orange /Thai pineapple .001722 .002676 .643703 0.520 ROW orange /Philippines pineapple .002687 .004137 .649538 0.516 ROW orange /ROW pineapple .002333 .000506 .461089 0.645 ROW orange /U.S grape -.000259 .002216 -.116958 0.907 ROW orange /Argentinean grape -.000021 .000183 -.115402 0.908 ROW orange /ROW grape -.000043 .003749 -.116954 0.907 ROW orange /Israelis citrus -.000328 .001178 -.278836 0.780 ROW orange /Italian citrus -.000390 .001387 -.281230 0.779 ROW orange /ROW citrus -.000410 .001447 -.283820 0.777 U.S grapefruit/U.S orange .010409 .015785 .659440 0.510 U.S grapefruit/Brazilian orange .214997 .324945 .661641 0.508 U.S grapefruit/ROW orange .001221 .002496 .489167 0.625 U.S grapefruit/Israelis grapefruit .148987 .043520 3.42342 0.001 U.S grapefruit /ROW grapefruit .061095 .026486 2.30672 0.021 U.S grapefruit /U.S apple .097839 .113102 .865052 0.387 U.S grapefruit /Chinese apple .092793 .107689 .861671 0.389 U.S grapefruit /ROW apple .125562 .146899 .854753 0.393 U.S grapefruit /Thai Pineapple -.248714 .056484 -4.40328 0.000 U.S grapefruit /Philippines Pineapple -.388024 .068007 -5.70563 0.000 U.S grapefruit /ROW Pineapple -.033696 .049471 -.681124 0.496 U.S grapefruit /U.S grape .126374 .100765 1.25415 0.210 U.S grapefruit /Argentinean grape .010328 .024192 .426929 0.669

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155 Table D-3 Continued Products Estimates SD t-statistic p-value U.S grapefruit /ROW grape .213719 .157773 1.35460 0.176 U.S grapefruit /Israelis citrus -.054840 .047911 -1.14461 0.252 U.S grapefruit /Italian citrus -.065144 .054519 -1.19489 0.232 U.S grapefruit /ROW citrus -.068593 .061144 -1.12182 0.262 Israelis grapefruit/U.S orange -. 001782 .003430 -.519525 0.603 Israelis grapefruit/Brazilian orange -.036815 .070734 -.520477 0.603 Israelis grapefruit/ROW orange -.000209 .000494 -.423284 0.672 Israelis grapefruit/U.S grapefruit .463688 .135446 3.42342 0.001 Israelis grapefruit/ROW grapefruit .095547 .056916 1.67873 0.093 Israelis grapefruit /U.S apple -.016754 .028293 -.592153 0.554 Israelis grapefruit /Chinese apple -.015889 .026757 -.593844 0.553 Israelis grapefruit /ROW apple -.021501 .036321 -.591964 0.554 Israelis grapefruit /Thai Pineapple .042589 .052997 .803605 0.422 Israelis grapefruit /Philippines Pineapple .066444 .083515 .795594 0.426 Israelis grapefruit /ROW Pineapple .005769 .010845 .532046 0.595 Israelis grapefruit /U.S grape -.021640 .031283 -.691754 0.489 Israelis grapefruit /Argentinean grape -.001768 .004719 -.374713 0.708 Israelis grapefruit /ROW grape -.036597 .052753 -.693737 0.488 Israelis grapefruit /Israelis citrus .009390 .014119 .665110 0.506 Israelis grapefruit /Italian citrus .011155 .016583 .672662 0.501 Israelis grapefruit /ROW citrus .011746 .018159 .646836 0.518 ROW grapefruit/U.S orange .006457 .010381 .622045 0.534 ROW grapefruit/Brazilian orange .133374 .212733 .626958 0.531 ROW grapefruit/ROW orange .000757 .001594 .475047 0.635 ROW grapefruit/U.S grapefruit .442059 .191639 2.30672 0.021 ROW grapefruit/Israelis grapefruit .222133 .132322 1.67873 0.093 ROW grapefruit /U.S apple .060695 .075145 .807705 0.419 ROW grapefruit /Chinese apple .057564 .071635 .803577 0.422 ROW grapefruit /ROW apple .077893 .097274 .800758 0.423 ROW grapefruit /Thai Pineapple -.154291 .079717 -1.93548 0.053 ROW grapefruit /Philippines Pineapple -.240712 .118528 -2.03086 0.042 ROW grapefruit /ROW Pineapple -.020903 .032333 -.646503 0.518 ROW grapefruit /U.S grape .078397 .070842 1.10664 0.268 ROW grapefruit /Argentinean grape .006407 .015265 .419726 0.675 ROW grapefruit /ROW grape .132582 .112827 1.17509 0.240 ROW grapefruit /Israelis citrus -.034020 .033901 -1.00352 0.316 ROW grapefruit /Italian citrus -.040412 .039002 -1.03617 0.300 ROW grapefruit /ROW citrus -.042552 .043290 -.982962 0.326 U.S apple/U.S orange -.045837 .025351 -1.80811 0.071 U.S apple/Brazilian orange -.946737 .422287 -2.24193 0.025 U.S apple/ROW orange -.005377 .007974 -.674378 0.500 U.S apple/U.S grapefruit .139287 .161015 .865052 0.387 U.S apple/Israelis grapefruit -.007663 .012942 -.592153 0.554 U.S apple/ROW grapefruit .011942 .014785 .807705 0.419 U.S apple /Chinese apple .079917 .151156 .528707 0.597 U.S apple /ROW apple -.330413 .239359 -1.38041 0.167 U.S apple /Thai Pineapple .109245 .039794 2.74523 0.006 U.S apple /Philippines Pineapple .170435 .056741 3.00377 0.003 U.S apple /ROW Pineapple .014800 .022252 .665123 0.506 U.S apple /U.S grape -.028422 .074801 -.379961 0.704 U.S apple /Argentinean grape -.002322 .007904 -.293840 0.769 U.S apple /ROW grape -.048065 .126125 -.381094 0.703 U.S apple /Israelis citrus .064651 .041515 1.55729 0.119

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156 Table D-3 Continued Products Estimates SD t-statistic p-value U.S apple /Italian citrus .076798 .046045 1.66791 0.095 U.S apple /ROW citrus .080864 .056066 1.44230 0.149 Chinese apple/U.S orange -.033917 .017970 -1.88738 0.059 Chinese apple/Brazilian orange -.700527 .301313 -2.32491 0.020 Chinese apple/ROW orange -.003979 .006108 -.651417 0.515 Chinese apple/U.S grapefruit .103063 .119609 .861671 0.389 Chinese apple/Israelis grapefruit -.005670 .009548 -.593844 0.553 Chinese apple/ROW grapefruit .008836 .010996 .803577 0.422 Chinese apple /U.S apple .062349 .117928 .528707 0.597 Chinese apple /ROW apple .058946 .184747 .319066 0.750 Chinese apple /Thai Pineapple .080834 .028601 2.82632 0.005 Chinese apple /Philippines Pineapple .126112 .040593 3.10671 0.002 Chinese apple /ROW Pineapple .010951 .016427 .666664 0.505 Chinese apple /U.S grape -.021030 .055556 -.378537 0.705 Chinese apple /Argentinean grape -.001718 .005877 -.292416 0.770 Chinese apple /ROW grape -.035565 .093662 -.379720 0.704 Chinese apple /Israelis citrus .047838 .030630 1.56179 0.118 Chinese apple /Italian citrus .056826 .033945 1.67407 0.094 Chinese apple /ROW citrus .059835 .042297 1.41462 0.157 ROW apple/U.S orange -.020216 .011530 -1.75339 0.080 ROW apple/Brazilian orange -.417547 .186013 -2.24472 0.025 ROW apple/ROW orange -.002371 .003610 -.656940 0.511 ROW apple/U.S grapefruit .061431 .071869 .854753 0.393 ROW apple/Israelis grapefruit -.003379 .005709 -.591964 0.554 ROW apple/ROW grapefruit .005266 .006577 .800758 0.423 ROW apple /U.S apple -.113549 .082258 -1.38041 0.167 ROW apple /Chinese apple .025965 .081379 .319066 0.750 ROW apple /Thai Pineapple .048181 .017491 2.75466 0.006 ROW apple /Philippines Pineapple .075168 .024951 3.01265 0.003 ROW apple /ROW Pineapple .006527 .009820 .664696 0.506 ROW apple /U.S grape -.012535 .033141 -.378236 0.705 ROW apple /Argentinean grape -.001024 .003517 -.291212 0.771 ROW apple /ROW grape -.021199 .055731 -.380373 0.704 ROW apple /Israelis citrus .028513 .018413 1.54854 0.121 ROW apple /Italian citrus .033871 .020149 1.68106 0.093 ROW apple /ROW citrus .035664 .024413 1.46085 0.144 Thai pineapple/U.S orange .043491 .027038 1.60853 0.108 Thai pineapple/Brazilian orange .898281 .481673 1.86492 0.062 Thai pineapple /ROW orange .005102 .007926 .643703 0.520 Thai pineapple /U.S grapefruit -1.83810 .417438 -4.40328 0.000 Thai pineapple /Israelis grapefruit .101132 .125848 .803605 0.422 Thai pineapple /ROW grapefruit -.157592 .081423 -1.93548 0.053 Thai pineapple /U.S apple .567116 .206582 2.74523 0.006 Thai pineapple /Chinese apple .537867 .190306 2.82632 0.005 Thai pineapple /ROW apple .727813 .264211 2.75466 0.006 Thai pineapple /Philippines pineapple -.061702 .134429 -.458997 0.646 Thai pineapple /ROW Pineapple -.080203 .123655 -.648599 0.517 Thai pineapple /U.S grape .238571 .175750 1.35745 0.175 Thai pineapple /Argentinean GR .019498 .042904 .454451 0.650 Thai pineapple /ROW grape .403463 .273516 1.47510 0.140 Thai pineapple /Israelis citrus .171808 .086405 1.98839 0.047 Thai pineapple /Italian citrus .204089 .100443 2.03188 0.042 Thai pineapple /ROW citrus .214894 .120744 1.77975 0.075

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157 Table D-3 Continued Products Estimates SD t-statistic p-value Philippines pineapple/U.S orange .097859 .057616 1.69847 0.089 Philippines pineapple/Brazilian orange 2.02123 1.00682 2.00754 0.045 Philippines pineapple /ROW orange .011481 .017676 .649538 0.516 Philippines pineapple /U.S grapefruit -4.13593 .724885 -5.70563 0.000 Philippines pineapple /Israelis grapefruit .227558 .286022 .795594 0.426 Philippines pineapple /ROW grapefruit -.354599 .174606 -2.03086 0.042 Philippines pineapple /U.S apple 1.27607 .424825 3.00377 0.003 Philippines pineapple /Chinese apple 1.21026 .389563 3.10671 0.002 Philippines pineapple /ROW apple 1.63766 .543595 3.01265 0.003 Philippines pineapple /Thai pineapple -.088991 .193882 -.458997 0.646 Philippines pineapple /ROW pineapple .078186 .187860 .416193 0.677 Philippines pineapple /U.S grape .536813 .391140 1.37243 0.170 Philippines pineapple /Argentinean grape .043872 .096498 .454640 0.649 Philippines pineapple /ROW grape .907838 .607558 1.49424 0.135 Philippines pineapple /Israelis other citrus .386587 .185970 2.07876 0.038 Philippines pineapple /Italian citrus .459223 .216054 2.12550 0.034 Philippines pineapple /ROW other citrus .483537 .263230 1.83694 0.066 ROW pineapple/U.S orange .007204 .011828 .609119 0.542 ROW pineapple/Brazilian orange .148805 .239517 .621271 0.534 ROW pineapple /ROW orange .000845 .001833 .461089 0.645 ROW pineapple /U.S grapefruit -.304491 .447042 -.681124 0.496 ROW pineapple /Israelis grapefruit .016753 .031488 .532046 0.595 ROW pineapple /ROW grapefruit -.026106 .040380 -.646503 0.518 ROW pineapple /U.S apple .093946 .141246 .665123 0.506 ROW pineapple /Chinese apple .089101 .133651 .666664 0.505 ROW pineapple /ROW apple .120566 .181386 .664696 0.506 ROW pineapple /Thai pineapple -.098066 .151197 -.648599 0.517 ROW pineapple /Philippines pineapple .066285 .159265 .416193 0.677 ROW pineapple /U.S grape .039521 .065703 .601504 0.548 ROW pineapple /Argentinean grape .003229 .008547 .377864 0.706 ROW pineapple /ROW grape .066836 .109084 .612702 0.540 ROW pineapple /Israelis citrus .028461 .043343 .656647 0.511 ROW pineapple /Italian citrus .033808 .051000 .662904 0.507 ROW pineapple /ROW citrus .035598 .054427 .654055 0.513 U.S grape/U.S orange -.001152 .009751 -.118156 0.906 U.S grape/Brazilian orange -.023799 .200591 -.118643 0.906 U.S grape/ROW orange -.000135 .001155 -.116958 0.907 U.S grape/U.S grapefruit .164391 .131078 1.25415 0.210 U.S grape/Israelis grapefruit -.009044 .013075 -.691754 0.489 U.S grape/ROW grapefruit .014094 .012736 1.10664 0.268 U.S grape/U.S apple -.025970 .068349 -.379961 0.704 U.S grape/Chinese apple -.024630 .065068 -.378537 0.705 U.S grape/ROW apple -.033329 .088116 -.378236 0.705 U.S grape/Thai Pineapple .041992 .030935 1.35745 0.175 U.S grape /Philippines Pineapple .065513 .047735 1.37243 0.170 U.S grape /ROW Pineapple .005689 .009458 .601504 0.548 U.S grape /Argentinean grape .107867 .068279 1.57981 0.114 U.S grape /ROW grape .173388 .153024 1.13308 0.257 U.S grape /Israelis citrus .084064 .043558 1.92991 0.054 U.S grape /Italian citrus .099858 .049998 1.99725 0.046 U.S grape /ROW citrus .105145 .057393 1.83201 0.067 Argentinean grape/U.S orange -.000633 .005479 -.116462 0.907 Argentinean grape/Brazilian orange -.013180 .112821 -.116820 0.907 Argentinean grape/ROW orange -.000074 .000648 -.115402 0.908

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158 Table D-3 Continued Products Estimates SD t-statistic p-value Argentinean grape/U.S grapefruit .091040 .213243 .426929 0.669 Argentinean grape/Israelis grapefruit -.005008 .013367 -.374713 0.708 Argentinean grape/ROW grapefruit .007805 .018596 .419726 0.675 Argentinean grape/U.S apple -.014382 .048945 -.293840 0.769 Argentinean grape/Chinese apple -.013640 .046647 -.292416 0.770 Argentinean grape/ROW apple -.018457 .063381 -.291212 0.771 Argentinean grape/Thai pineapple .023255 .051172 .454451 0.650 Argentinean grape /Philippines pineapple. .036281 .079802 .454640 0.649 Argentinean grape /ROW Pineapple .003150 .008338 .377864 0.706 Argentinean grape /U.S grape .730936 .462673 1.57981 0.114 Argentinean grape /ROW grape .098332 .529644 .185657 0.853 Argentinean grape /Israelis other citrus .046554 .100989 .460984 0.645 Argentinean grape /Italian citrus .055302 .119983 .460912 0.645 Argentinean grape /ROW other CT .058230 .125553 .463786 0.643 ROW grape/U.S orange -.001869 .015818 -.118160 0.906 ROW grape/Brazilian orange -.038603 .325396 -.118634 0.906 ROW grape/ROW orange -.000219 .001874 -.116954 0.907 ROW grape/U.S grapefruit .266654 .196850 1.35460 0.176 ROW grape/Israelis grapefruit -.014671 .021148 -.693737 0.488 ROW grape/ROW grapefruit .022862 .019455 1.17509 0.240 ROW grape/U.S apple -.042125 .110537 -.381094 0.703 ROW grape/Chinese apple -.039952 .105215 -.379720 0.704 ROW grape/ROW apple -.054061 .142127 -.380373 0.704 ROW grape/Thai Pineapple .068114 .046176 1.47510 0.140 ROW grape /Philippines Pineapple .106267 .071118 1.49424 0.135 ROW grape /ROW Pineapple .009228 .015061 .612702 0.540 ROW grape /U.S grape .166304 .146772 1.13308 0.257 ROW grape /Argentinean grape .013918 .074968 .185657 0.853 ROW grape /Israelis citrus .136357 .059527 2.29066 0.022 ROW grape /Italian citrus .161977 .069118 2.34348 0.019 ROW grape /ROW citrus .170553 .085054 2.00523 0.045 Israelis citrus/U.S orange -.004108 .013545 -.303321 0.762 Israelis citrus /Brazilian orange -.084856 .276981 -.306361 0.759 Israelis citrus /ROW orange -.000481 .001728 -.278836 0.780 Israelis citrus /U.S grapefruit -.200748 .175385 -1.14461 0.252 Israelis citrus /Israelis grapefruit .011045 .016606 .665110 0.506 Israelis citrus /ROW grapefruit -.017211 .017151 -1.00352 0.316 Israelis citrus /U.S apple .166238 .106748 1.55729 0.119 Israelis citrus /Chinese apple .157664 .100951 1.56179 0.118 Israelis citrus /ROW apple .213343 .137771 1.54854 0.121 Israelis citrus /Thai pineapple .085100 .042798 1.98839 0.047 Israelis citrus /Philippines pineapple .132766 .063868 2.07876 0.038 Israelis citrus /ROW Pineapple .011529 .017558 .656647 0.511 Israelis citrus /U.S grape .236560 .122576 1.92991 0.054 Israelis citrus /Argentinean GR .019333 .041939 .460984 0.645 Israelis citrus /ROW grape .400062 .174649 2.29066 0.022 Israelis citrus /Italian citrus .103190 .124971 .825712 0.409 Israelis citrus /ROW citrus .111639 .084809 1.31636 0.188 Italian citrus/U.S orange -.006237 .020376 -.306142 0.759 Italian citrus /Brazilian orange -.128842 .416532 -.309320 0.757 Italian citrus /ROW orange -.000731 .002602 -.281230 0.779 Italian citrus /U.S grapefruit -.304807 .255092 -1.19489 0.232 Italian citrus /Israelis grapefruit .016770 .024931 .672662 0.501 Italian citrus /ROW grapefruit -.026133 .025221 -1.03617 0.300

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159 Table D-3 Continued Products Estimates SD t-statistic p-value Italian citrus /U.S apple .252409 .151332 1.66791 0.095 Italian citrus /Chinese apple .239391 .142999 1.67407 0.094 Italian citrus /ROW apple .323931 .192694 1.68106 0.093 Italian citrus /Thai pineapple .129212 .063592 2.03188 0.042 Italian citrus /Philippines pineapple .201586 .094842 2.12550 0.034 Italian citrus /ROW Pineapple .017506 .026407 .662904 0.507 Italian citrus /U.S grape .359183 .179839 1.99725 0.046 Italian citrus /Argentinean grape .029355 .063689 .460912 0.645 Italian citrus /ROW grape .607437 .259203 2.34348 0.019 Italian citrus /Israelis citrus .131897 .159737 .825712 0.409 Italian citrus /ROW citrus -.109788 .094188 -1.16563 0.244 ROW citrus/U.S orange -.004530 .014608 -.310128 0.756 ROW citrus /Brazilian orange -.093573 .299245 -.312697 0.755 ROW citrus /ROW orange -.000531 .001872 -.283820 0.777 ROW citrus /U.S grapefruit -.221370 .197331 -1.12182 0.262 ROW citrus /Israelis grapefruit .012180 .018830 .646836 0.518 ROW citrus /ROW grapefruit -.018979 .019308 -.982962 0.326 ROW citrus /U.S apple .183315 .127099 1.44230 0.149 ROW citrus /Chinese apple .173861 .122903 1.41462 0.157 ROW citrus /ROW apple .235259 .161043 1.46085 0.144 ROW citrus /Thai pineapple .093842 .052727 1.77975 0.075 ROW citrus /Philippines pineapple .146404 .079700 1.83694 0.066 ROW citrus /ROW Pineapple .012714 .019438 .654055 0.513 ROW citrus /U.S grape .260861 .142391 1.83201 0.067 ROW citrus /Argentinean GR .021319 .045968 .463786 0.643 ROW citrus /ROW grape .441159 .220004 2.00523 0.045 ROW citrus /Israelis citrus .098424 .074770 1.31636 0.188 ROW citrus /Italian citrus -.075726 .064965 -1.16563 0.244 Table D-4 Compensated price elasticities of fruit juices in the block-wise dependent uniform substitute Rotterdam model Products Estimates SD t-statistic p-value U.S orange /Brazilian orange 1.36236 .137491 9.90867 0.000 U.S orange /ROW orange .012980 .282909E-02 4.58790 0.000 U.S orange /U.S grapefruit .961063E-02 .011016 .872392 0.383 U.S orange /Israelis grapefruit .777966E-03 .100635E-02 .773058 0.439 U.S orange /ROW grapefruit .494356E-03 .627476E-03 .787848 0.431 U.S orange /U.S apple -.689830E-02 .010577 -.652216 0.514 U.S orange /Chinese apple -.144385E-02 .225587E-02 -.640041 0.522 U.S orange /ROW apple -.760172E-02 .011820 -.643096 0.520 U.S orange /Thai pineapple .160928E-02 .304587E-02 .528347 0.597 U.S orange /Philippines pineapple .145979E-02 .274833E-02 .531158 0.595 U.S orange /ROW pineapple .861375E-04 .268313E-03 .321033 0.748 U.S orange /U.S grape -.628742E-02 .624819E-02 -1.00628 0.314 U.S orange /Argentinean grape -.134931E-02 .138383E-02 -.975055 0.330 U.S orange /ROW grape -.882131E-02 .849967E-02 -1.03784 0.299 U.S orange /Israelis citrus .618641E-02 .409829E-02 1.50951 0.131 U.S orange /Italian citrus .606382E-02 .422129E-02 1.43648 0.151 U.S orange /ROW citrus .377466E-02 .260870E-02 1.44695 0.148 Brazilian orange/U.S orange .388260 .039184 9.90867 0.000 Brazilian orange /ROW orange .120813 .014278 8.46124 0.000 Brazilian orange /U.S grapefruit .089455 .099507 .898986 0.369 Brazilian orange /Israelis grapefruit .7 24126E-02 .911753E-02 .794213 0.427

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160 Table D-4 Continued Products Estimates SD t-statistic p-value Brazilian orange /ROW grapefruit .46 0144E-02 .567576E-02 .810717 0.418 Brazilian orange /U.S apple -.064209 .095645 -.671324 0.502 Brazilian orange /Chinese apple -.013439 .020426 -.657936 0.511 Brazilian orange /ROW apple -.070756 .106205 -.666225 0.505 Brazilian orange /Thai Pineapple .014979 .027921 .536485 0.592 Brazilian orange /Philippines pineapple .013588 .025194 .539332 0.590 Brazilian orange /ROW Pineapple .801763E-03 .248616E-02 .322491 0.747 Brazilian orange /U.S grape -.058523 .054171 -1.08035 0.280 Brazilian orange /Argentinean grape -.012559 .012192 -1.03017 0.303 Brazilian orange /ROW grape -.082108 .072746 -1.12870 0.259 Brazilian orange /Israelis citrus .057583 .033956 1.69580 0.090 Brazilian orange /Italian citrus .056442 .034976 1.61371 0.107 Brazilian orange /ROW citrus .035134 .022236 1.58006 0.114 ROW orange/U.S orange .029019 .632515E-02 4.58790 0.000 ROW orange/Brazilian orange .947781 .112014 8.46124 0.000 ROW orange /U.S grapefruit .668603E-02 .771332E-02 .866816 0.386 ROW orange /Israelis grapefruit .541224E-03 .703277E-03 .769574 0.442 ROW orange /ROW grapefruit .343919E-03 .438182E-03 .784878 0.433 ROW orange /U.S apple -.479909E-02 .749026E-02 -.640710 0.522 ROW orange /Chinese apple -.100447E-02 .159920E-02 -.628109 0.530 ROW orange /ROW apple -.528845E-02 .835891E-02 -.632672 0.527 ROW orange /Thai pineapple .111956E-02 .213331E-02 .524800 0.600 ROW orange /Philippines pineapple .101557E-02 .192494E-02 .527584 0.598 ROW orange /ROW pineapple .599251E-04 .187108E-03 .320271 0.749 ROW orange /U.S grape -.437411E-02 .445997E-02 -.980749 0.327 ROW orange /Argentinean grape -.938705E-03 .985018E-03 -.952982 0.341 ROW orange /ROW grape -.613691E-02 .608998E-02 -1.00771 0.314 ROW orange /Israelis citrus .430384E-02 .295876E-02 1.45461 0.146 ROW orange /Italian citrus .421855E-02 .303273E-02 1.39101 0.164 ROW orange /ROW citrus .262600E-02 .188159E-02 1.39563 0.163 U.S grapefruit/U.S orange .861208E-02 .987181E-02 .872392 0.383 U.S grapefruit/Brazilian orange .281275 .312880 .898986 0.369 U.S grapefruit/ROW orange .267979E-02 .309153E-02 .866816 0.386 U.S grapefruit/Israelis grapefruit .1 16063 .989322E-03 117.316 0.000 U.S grapefruit /ROW grapefruit .073752 .583666E-03 126.360 0.000 U.S grapefruit /U.S apple .324087 .124901 2.59474 0.009 U.S grapefruit /Chinese apple .067833 .033093 2.04976 0.040 U.S grapefruit /ROW apple .357134 .150466 2.37352 0.018 U.S grapefruit /Thai Pineapple -.350699 .058706 -5.97383 0.000 U.S grapefruit /Philippines Pineapple -.318124 .052397 -6.07142 0.000 U.S grapefruit /ROW Pineapple -.018771 .047162 -.398023 0.691 U.S grapefruit /U.S grape .082947 .091900 .902588 0.367 U.S grapefruit /Argentinean grape .017801 .020461 .870002 0.384 U.S grapefruit /ROW grape .116376 .124390 .935576 0.349 U.S grapefruit /Israelis citrus -.062922 .055330 -1.13723 0.255 U.S grapefruit /Italian citrus -.061675 .053788 -1.14664 0.252 U.S grapefruit /ROW citrus -.038392 .034046 -1.12765 0.259 Israelis grapefruit/U.S orange .21 6968E-02 .280662E-02 .773058 0.439 Israelis grapefruit/Brazilian orange .070863 .089224 .794213 0.427 Israelis grapefruit/ROW orange .675130E-03 .877277E-03 .769574 0.442 Israelis grapefruit/U.S grapefruit .361221 .307904E-02 117.316 0.000 Israelis grapefruit/ROW grapefruit .018581 .257048E-03 72.2846 0.000 Israelis grapefruit /U.S apple .081648 .054871 1.48800 0.137 Israelis grapefruit /Chinese apple .017089 .012568 1.35972 0.174

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161 Table D-4 Continued Products Estimates SD t-statistic p-value Israelis grapefruit /ROW apple .089974 .063396 1.41925 0.156 Israelis grapefruit /Thai Pineapple -.088353 .051088 -1.72942 0.084 Israelis grapefruit /Philippines Pineapple -.080146 .045179 -1.77399 0.076 Israelis grapefruit /ROW Pineapple -.472915E-02 .012279 -.385153 0.700 Israelis grapefruit /U.S grape .020897 .025319 .825351 0.409 Israelis grapefruit /Argentinean grape .448466E-02 .558437E-02 .803074 0.422 Israelis grapefruit /ROW grape .029319 .034275 .855416 0.392 Israelis grapefruit /Israelis citrus -.015852 .016834 -.941693 0.346 Israelis grapefruit /Italian citrus -.015538 .016405 -.947153 0.344 Israelis grapefruit /ROW citrus -.967231E-02 .010293 -.939713 0.347 ROW grapefruit/U.S orange .32053 2E-02 .406844E-02 .787848 0.431 ROW grapefruit/Brazilian orange .104687 .129129 .810717 0.418 ROW grapefruit/ROW orange .997386E-03 .127075E-02 .784878 0.433 ROW grapefruit/U.S grapefruit .533640 .422317E-02 126.360 0.000 ROW grapefruit/Israelis grapefruit .0 43197 .597601E-03 72.2846 0.000 ROW grapefruit /U.S apple .120621 .073853 1.63326 0.102 ROW grapefruit /Chinese apple .025247 .017216 1.46651 0.143 ROW grapefruit /ROW apple .132921 .085289 1.55848 0.119 ROW grapefruit /Thai Pineapple -.130526 .066405 -1.96560 0.049 ROW grapefruit /Philippines Pineapple -.118402 .058498 -2.02403 0.043 ROW grapefruit /ROW Pineapple -.698649E-02 .018076 -.386516 0.699 ROW grapefruit /U.S grape .030872 .036724 .840655 0.401 ROW grapefruit /Argentinean grape .662529E-02 .812521E-02 .815400 0.415 ROW grapefruit /ROW grape .043314 .049741 .870781 0.384 ROW grapefruit /Israelis citrus -.023419 .024059 -.973391 0.330 ROW grapefruit /Italian citrus -.022955 .023399 -.981037 0.327 ROW grapefruit /ROW citrus -.014289 .014709 -.971482 0.331 U.S apple/U.S orange -.880028E-02 .013493 -.652216 0.514 U.S apple/Brazilian orange -.287421 .428141 -.671324 0.502 U.S apple/ROW orange -.273835E-02 .427393E-02 -.640710 0.522 U.S apple/U.S grapefruit .461381 .177814 2.59474 0.009 U.S apple/Israelis grapefruit .037348 .025100 1.48800 0.137 U.S apple/ROW grapefruit .023733 .014531 1.63326 0.102 U.S apple /Chinese apple -.096026 .400697E-02 -23.9647 0.000 U.S apple /ROW apple -.505566 .019164 -26.3808 0.000 U.S apple /Thai Pineapple .212565 .061409 3.46149 0.001 U.S apple /Philippines Pineapple .192821 .055655 3.46456 0.001 U.S apple /ROW Pineapple .011378 .028765 .395543 0.692 U.S apple /U.S grape -.022163 .093699 -.236538 0.813 U.S apple /Argentinean grape -.475639E-02 .020223 -.235199 0.814 U.S apple /ROW grape -.031096 .131501 -.236467 0.813 U.S apple /Israelis citrus .043051 .058527 .735584 0.462 U.S apple /Italian citrus .042198 .057112 .738868 0.460 U.S apple /ROW citrus .026268 .035172 .746834 0.455 Chinese apple/U.S orange -.143704E-02 .224523E-02 -.640041 0.522 Chinese apple/Brazilian orange -.046934 .071336 -.657936 0.511 Chinese apple/ROW orange -.447159E-03 .711912E-03 -.628109 0.530 Chinese apple/U.S grapefruit .075341 .036756 2.04976 0.040 Chinese apple/Israelis grapefruit .609875E-02 .448531E-02 1.35972 0.174 Chinese apple/ROW grapefruit .387543E-02 .264263E-02 1.46651 0.143 Chinese apple /U.S apple -.074917 .312614E-02 -23.9647 0.000 Chinese apple /ROW apple -.082556 .346618E-02 -23.8177 0.000 Chinese apple /Thai Pineapple .034711 .014817 2.34266 0.019 Chinese apple /Philippines Pineapple .031487 .013561 2.32177 0.020

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162 Table D-4 Continued Products Estimates SD t-statistic p-value Chinese apple /ROW Pineapple .185792E-02 .473434E-02 .392435 0.695 Chinese apple /U.S grape -.361918E-02 .015433 -.234507 0.815 Chinese apple /Argentinean grape -.776694E-03 .333149E-02 -.233137 0.816 Chinese apple /ROW grape -.507774E-02 .021665 -.234376 0.815 Chinese apple /Israelis citrus .703006E-02 .991531E-02 .709010 0.478 Chinese apple /Italian citrus .689075E-02 .968113E-02 .711771 0.477 Chinese apple /ROW citrus .428941E-02 .597903E-02 .717409 0.473 ROW apple/U.S orange -.333268E-02 .518224E-02 -.643096 0.520 ROW apple/Brazilian orange -.108847 .163379 -.666225 0.505 ROW apple/ROW orange -.103702E-02 .163911E-02 -.632672 0.527 ROW apple/U.S grapefruit .174726 .073614 2.37352 0.018 ROW apple/Israelis grapefruit .014144 .996566E-02 1.41925 0.156 ROW apple/ROW grapefruit .898762E-02 .576692E-02 1.55848 0.119 ROW apple /U.S apple -.173742 .658595E-02 -26.3808 0.000 ROW apple /Chinese apple -.036365 .152681E-02 -23.8177 0.000 ROW apple /Thai Pineapple .080499 .025738 3.12769 0.002 ROW apple /Philippines Pineapple .073022 .023563 3.09904 0.002 ROW apple /ROW Pineapple .430875E-02 .010908 .395022 0.693 ROW apple /U.S grape -.839335E-02 .035585 -.235865 0.814 ROW apple /Argentinean grape -.180125E-02 .767938E-02 -.234557 0.815 ROW apple /ROW grape -.011776 .049872 -.236122 0.813 ROW apple /Israelis citrus .016304 .022502 .724545 0.469 ROW apple /Italian citrus .015981 .021877 .730470 0.465 ROW apple /ROW citrus .994769E-02 .013486 .737639 0.461 Thai pineapple/U.S orange .010657 .020171 .528347 0.597 Thai pineapple/Brazilian orange .348079 .648814 .536485 0.592 Thai pineapple /ROW orange .331625E-02 .631908E-02 .524800 0.600 Thai pineapple /U.S grapefruit -2.59181 .433861 -5.97383 0.000 Thai pineapple /Israelis grapefruit -.209803 .121314 -1.72942 0.084 Thai pineapple /ROW grapefruit -.133319 .067826 -1.96560 0.049 Thai pineapple /U.S apple 1.10348 .318786 3.46149 0.001 Thai pineapple /Chinese apple .230963 .098590 2.34266 0.019 Thai pineapple /ROW apple 1.21600 .388785 3.12769 0.002 Thai pineapple /Philippines pineapple .039981 .157894E-02 25.3216 0.000 Thai pineapple /ROW Pineapple .235915E-02 .954555E-03 2.47147 0.013 Thai pineapple /U.S grape .195801 .222746 .879035 0.379 Thai pineapple /Argentinean GR .042020 .049519 .848560 0.396 Thai pineapple /ROW grape .274710 .309032 .888938 0.374 Thai pineapple /Israelis citrus .351352 .148721 2.36250 0.018 Thai pineapple /Italian citrus .344390 .146229 2.35514 0.019 Thai pineapple /ROW citrus .214379 .091838 2.33431 0.020 Philippines pineapple/U.S orange .013943 .026251 .531158 0.595 Philippines pineapple/Brazilian orange .455392 .844363 .539332 0.590 Philippines pineapple /ROW orange .433865E-02 .822363E-02 .527584 0.598 Philippines pineapple /U.S grapefruit -3.39087 .558497 -6.07142 0.000 Philippines pineapple /Israelis grapefruit -.274485 .154728 -1.77399 0.076 Philippines pineapple /ROW grapefruit -.174421 .086175 -2.02403 0.043 Philippines pineapple /U.S apple 1.44368 .416699 3.46456 0.001 Philippines pineapple /Chinese apple .302169 .130146 2.32177 0.020 Philippines pineapple /ROW apple 1.59089 .513348 3.09904 0.002 Philippines pineapple /Thai pineapple .057664 .227725E-02 25.3216 0.000 Philippines pineapple /ROW pineapple .308648E-02 .123898E-02 2.49116 0.013 Philippines pineapple /U.S grape .256167 .291250 .879542 0.379 Philippines pineapple /Argentinean grape .054975 .064703 .849640 0.396

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163 Table D-4 Continued Products Estimates SD t-statistic p-value Philippines pineapple /ROW grape .359404 .403773 .890114 0.373 Philippines pineapple /Israelis other citrus .459674 .193120 2.38025 0.017 Philippines pineapple /Italian citrus .450565 .190809 2.36134 0.018 Philippines pineapple /ROW other citrus .280471 .119762 2.34190 0.019 ROW pineapple/U.S orange .697506E-03 .217269E-02 .321033 0.748 ROW pineapple/Brazilian orange .022781 .070641 .322491 0.747 ROW pineapple /ROW orange .217040E-03 .677679E-03 .320271 0.749 ROW pineapple /U.S grapefruit -.169628 .426175 -.398023 0.691 ROW pineapple /Israelis grapefruit -.013731 .035651 -.385153 0.700 ROW pineapple /ROW grapefruit -.872538E-02 .022574 -.386516 0.699 ROW pineapple /U.S apple .072220 .182584 .395543 0.692 ROW pineapple /Chinese apple .015116 .038518 .392435 0.695 ROW pineapple /ROW apple .079584 .201467 .395022 0.693 ROW pineapple /Thai pineapple .288461E-02 .116716E-02 2.47147 0.013 ROW pineapple /Philippines pineapple .261667E-02 .105038E-02 2.49116 0.013 ROW pineapple /U.S grape .012815 .035370 .362302 0.717 ROW pineapple /Argentinean grape .275009E-02 .763540E-02 .360177 0.719 ROW pineapple /ROW grape .017979 .049381 .364088 0.716 ROW pineapple /Israelis citrus .022995 .058650 .392071 0.695 ROW pineapple /Italian citrus .022539 .057264 .393604 0.694 ROW pineapple /ROW citrus .014031 .035664 .393410 0.694 U.S grape/U.S orange -.732907E-02 .728333E-02 -1.00628 0.314 U.S grape/Brazilian orange -.239371 .221569 -1.08035 0.280 U.S grape/ROW orange -.228056E-02 .232533E-02 -.980749 0.327 U.S grape/U.S grapefruit .107900 .119546 .902588 0.367 U.S grape/Israelis grapefruit .873437E-02 .010583 .825351 0.409 U.S grape/ROW grapefruit .555023E-02 .660227E-02 .840655 0.401 U.S grape/U.S apple -.020252 .085617 -.236538 0.813 U.S grape/Chinese apple -.423877E-02 .018075 -.234507 0.815 U.S grape/ROW apple -.022317 .094616 -.235865 0.814 U.S grape/Thai Pineapple .034464 .039207 .879035 0.379 U.S grape /Philippines Pineapple .031263 .035544 .879542 0.379 U.S grape /ROW Pineapple .184471E-02 .509164E-02 .362302 0.717 U.S grape /Argentinean grape .040744 .423866E-03 96.1243 0.000 U.S grape /ROW grape .266368 .214706E-02 124.062 0.000 U.S grape /Israelis citrus .054435 .042863 1.26998 0.204 U.S grape /Italian citrus .053356 .042038 1.26925 0.204 U.S grape /ROW citrus .033214 .025146 1.32083 0.187 Argentinean grape/U.S orange -.010658 .010931 -.975055 0.330 Argentinean grape/Brazilian orange -.348097 .337904 -1.03017 0.303 Argentinean grape/ROW orange -.331643E-02 .348005E-02 -.952982 0.341 Argentinean grape/U.S grapefruit .156910 .180356 .870002 0.384 Argentinean grape/Israelis grapefruit .012702 .015816 .803074 0.422 Argentinean grape/ROW grapefruit .807123E-02 .989850E-02 .815400 0.415 Argentinean grape/U.S apple -.029450 .125214 -.235199 0.814 Argentinean grape/Chinese apple -.616409E-02 .026440 -.233137 0.816 Argentinean grape/ROW apple -.032453 .138360 -.234557 0.815 Argentinean grape/Thai pineapple .050118 .059063 .848560 0.396 Argentinean grape /Philippines pineapple. .045463 .053508 .849640 0.396 Argentinean grape /ROW Pineapple .268261E-02 .744803E-02 .360177 0.719 Argentinean grape /U.S grape .276090 .287222E-02 96.1243 0.000 Argentinean grape /ROW grape .387357 .342908E-02 112.962 0.000 Argentinean grape /Israelis other citrus .079160 .067539 1.17206 0.241 Argentinean grape /Italian citrus .077591 .066198 1.17212 0.241

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164 Table D-4 Continued Products Estimates SD t-statistic p-value Argentinean grape /ROW other CT .048300 .039802 1.21350 0.225 ROW grape/U.S orange -.986263E-02 .950303E-02 -1.03784 0.299 ROW grape/Brazilian orange -.322119 .285388 -1.12870 0.259 ROW grape/ROW orange -.306892E-02 .304545E-02 -1.00771 0.314 ROW grape/U.S grapefruit .145200 .155199 .935576 0.349 ROW grape/Israelis grapefruit .011754 .013740 .855416 0.392 ROW grape/ROW grapefruit .746887E-02 .857721E-02 .870781 0.384 ROW grape/U.S apple -.027252 .115248 -.236467 0.813 ROW grape/Chinese apple -.570406E-02 .024337 -.234376 0.815 ROW grape/ROW apple -.030031 .127185 -.236122 0.813 ROW grape/Thai Pineapple .046378 .052172 .888938 0.374 ROW grape /Philippines Pineapple .042070 .047264 .890114 0.373 ROW grape /ROW Pineapple .248240E-02 .681814E-02 .364088 0.716 ROW grape /U.S grape .255485 .205934E-02 124.062 0.000 ROW grape /Argentinean grape .054828 .485369E-03 112.962 0.000 ROW grape /Israelis citrus .073252 .056263 1.30197 0.193 ROW grape /Italian citrus .071801 .054847 1.30911 0.190 ROW grape /ROW citrus .044695 .033202 1.34617 0.178 Israelis citrus/U.S orange .020293 .013444 1.50951 0.131 Israelis citrus /Brazilian orange .662784 .390838 1.69580 0.090 Israelis citrus /ROW orange .631454E-02 .434106E-02 1.45461 0.146 Israelis citrus /U.S grapefruit -.230334 .202540 -1.13723 0.255 Israelis citrus /Israelis grapefruit -.018645 .019800 -.941693 0.346 Israelis citrus /ROW grapefruit -.011848 .012172 -.973391 0.330 Israelis citrus /U.S apple .110699 .150491 .735584 0.462 Israelis citrus /Chinese apple .023170 .032679 .709010 0.478 Israelis citrus /ROW apple .121986 .168363 .724545 0.469 Israelis citrus /Thai pineapple .174032 .073664 2.36250 0.018 Israelis citrus /Philippines pineapple .157866 .066323 2.38025 0.017 Israelis citrus /ROW Pineapple .931515E-02 .023759 .392071 0.695 Israelis citrus /U.S grape .153183 .120618 1.26998 0.204 Israelis citrus /Argentinean grape .032874 .028048 1.17206 0.241 Israelis citrus /ROW grape .214917 .165071 1.30197 0.193 Israelis citrus /Italian citrus .118389 .002331 50.7888 0.000 Israelis citrus /ROW citrus .073696 .000869 84.7633 0.000 Italian citrus/U.S orange .025425 .017699 1.43648 0.151 Italian citrus /Brazilian orange .830381 .514580 1.61371 0.107 Italian citrus /ROW orange .007911 .005687 1.39101 0.164 Italian citrus /U.S grapefruit -.288579 .251672 -1.14664 0.252 Italian citrus /Israelis grapefruit -.023360 .024663 -.947153 0.344 Italian citrus /ROW grapefruit -.014844 .015131 -.981037 0.327 Italian citrus /U.S apple .138691 .187707 .738868 0.460 Italian citrus /Chinese apple .029029 .040784 .711771 0.477 Italian citrus /ROW apple .152833 .209226 .730470 0.465 Italian citrus /Thai pineapple .218039 .092580 2.35514 0.019 Italian citrus /Philippines pineapple .197786 .083760 2.36134 0.018 Italian citrus /ROW Pineapple .011671 .029651 .393604 0.694 Italian citrus /U.S grape .191918 .151206 1.26925 0.204 Italian citrus /Argentinean grape .041187 .035139 1.17212 0.241 Italian citrus /ROW grape .269263 .205683 1.30911 0.190 Italian citrus /Israelis citrus .151324 .002979 50.7888 0.000 Italian citrus /ROW citrus .092331 .001202 76.7658 0.000 ROW citrus/U.S orange .010916 .007544 1.44695 0.148 ROW citrus /Brazilian orange .356530 .225643 1.58006 0.114

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165 Table D-4 Continued Products Estimates SD t-statistic p-value ROW citrus /ROW orange .003396 .002433 1.39563 0.163 ROW citrus /U.S grapefruit -.123903 .109877 -1.12765 0.259 ROW citrus /Israelis grapefruit -.010030 .010673 -.939713 0.347 ROW citrus /ROW grapefruit -.006373 .006560 -.971482 0.331 ROW citrus /U.S apple .059548 .079734 .746834 0.455 ROW citrus /Chinese apple .012464 .017373 .717409 0.473 ROW citrus /ROW apple .065620 .088959 .737639 0.461 ROW citrus /Thai pineapple .093616 .040104 2.33431 0.020 ROW citrus /Philippines pineapple .084921 .036261 2.34190 0.019 ROW citrus /ROW Pineapple .005010 .012737 .393410 0.694 ROW citrus /U.S grape .082401 .062386 1.32083 0.187 ROW citrus /Argentinean GR .017684 .014573 1.21350 0.225 ROW citrus /ROW grape .115610 .085880 1.34617 0.178 ROW citrus /Israelis citrus .064972 .000766 84.7633 0.000 ROW citrus /Italian citrus .063685 .000829 76.7658 0.000

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166 APPENDIX E TWO-STAGE ROTTERDAM MODEL Theoretical Models Parameter estimates of a system of c onsumer demand can be obtained in two ways. One is direct estimation by including all the products of interest in one system of equations. The other is estimating a multi-st age demand system consistent with a multistage budget allocation. Both ways provide the same estimates. However, under situations where there are a limited number of observations, it is advantageous to apply a multi-stage system. In this study, a twostage Rotterdam demand system is applied consistent with a two stage budget allocation. In the first stage, total expenditure is allocated over broader groups of goods. In the second stage, group expenditures are allocated over individual goods. In this framew ork, the first stage i nvolves the allocation of total expenditure over groups of imported fr uit juice including orange, grapefruit, other citrus, apple, pineapple and grape juices, and the second stage i nvolves allocation of group expenditure over supplying countries of a certain product group. The optimal allocation of expenditure on imported fruit juices will be carried out by specifying a first stage (group) demand e quation for the fruit juice groups and a second stage (conditional) demand equation fo r individual country-specific products. Since the system of the first and seco nd stage demand systems can be estimated simultaneously, it is possible to show how a ch ange in trade policy applied to a product group translates into an imp act on the export of individual countries, and conversely how

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167 a change in trade policy applied to a product fr om a certain country is translated into an impact on the total demand for imported fruit juices. The study estimates four two-stage dema nd systems of fruit juices using the relative price version of the Rotterdam model. These are (1) Two-stage block independent Rotterdam model (2) Two-stage block-wise depe ndent Rotterdam model (3) Two-stage block independent uniform substitute-Rotterdam model (4) Two-stage block-wise dependent uniform substitute-Rotterdam model Two-Stage Block Independent Rotterdam Model First-stage (Group) demand. Following Theil (1980a) the first stage or group demand equation of the block independent Rotterdam model can be given by (1) 'log log logP P d Q d Q d Wg g g g g, where gS i i gw W is the average expenditure share of group g ; gS i i g is the marginal expenditure share of group g; i S i g i gq d W w Q dglog log; is the group Divisia volume index; is the income flexibility of the marginal utility of income, i S i g i gp d P dglog log' is the Frisch price index of group g ; G g g gQ d W Q d1log log is the overall Divisia volume index of all groups in the system; j N j j G g g gp d P d P d log log log1 1 is the overall Frisch price index. Second-stage demand. Continuing to follow Theil (1980a), the second stage demand equation can be given by.

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168 (2) gS j g j ij g g i i iP p d v Q d W q d w' 'log log log, where g i i is the marginal share of good i within its group; ij is the relative price coefficients. The share 'i answers the question that if the consumer’s income increases by one dollar, result ing in an additional amount of g dollars spent ongS, what is the proportion of this additiona l amount that is allocated to goodi? The first stage function is related to the second stage function through the quantity demanded of the product group term g gQ d Wlog which is found in both stage functions. It is assumed that this term found in the second stage demand e quation is exogenously determined. Two-stage Block-wise De pendent Rotterdam Model Like the case with block independence, we can apply the two-stage utility maximization procedure in a block-wise depe ndence framework and estimate as a system of first and second-stage demand equations. First-stage demand. Following Theil (1980a), the first stage demand equation of the block-wise dependent Rotte rdam model can be given as (3) G h h gh gg g gP P d V Q d Q d W1 'log log log where ghV is the group relative price coefficients defined as. g ih j ij ghV. Second-stage demand. The second stage demand equation of the block-wise dependent Rotterdam model is the same as that of the block independent Rotterdam model. So, we can reproduce equation (2) here.

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169 (4) gS j g j ij g g i i iP p d v Q d W q d w' 'log log log. Two-stage Block Independent Unif orm Substitute-Rotterdam Model First stage demand. Since the uniform substitute hypothesis is imposed on a set of goods within the same group, the first st age block independent uniform substituteRotterdam model is the same as that of the first-stage equation of the block independent Rotterdam demand model. Thus, we reproduce it here as it is. (5) 'log log logP P d Q d Q d Wg g g g g. Second stage demand. Following Theil (1980a), the second-stage equation of the block independent uniform substitu teRotterdam model can be given as (6) ' 'log 1 log logg i g i g g g i i iP p d k Q d W q d w Two-stage Block-wise dependent Un iform Substitute-Rotterdam Model Since the uniform substitute hypothesis is imposed on a set of goods within the same group, the first stage equation of the block-wise dependent uniform substituteRotterdam model is the same as that of the block-wise dependent Ro tterdam model. Thus, we reproduce equation (3) here as it is. (7) G h h gh gg g gP P d V Q d Q d W1 'log log log. Following Seale (2003) the second-stage e quation of the block-wise dependent uniform substitute-Rotterdam model can be given as

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170 (8) ' 'log 1 log logg i g i gg g g i i iP p d k Q d W q d w If two-stage utility maximization is appropriate, then the two-stage demand system and the unconditional demand systems s hould yield the same results. Edgerton (1997) derived the formulae which convert th e calculated two-stage demand parameters to corresponding unconditional demand elasticities. Hence, the total expenditure elasticity of the thi good within commodity group A is given by (9) A i A iE E E where i AE is the second-stage elasticity of the thi good in group A and AE is the firststage (group) expenditure elasticity for the thA group. For two goods, i andj, belonging to commodity groups A and B Edgerton (1997) gives the total pr ice elasticities for goods i andj as (10) B A AB j B i A ij A AB ije w E e e where is the Kronecker’s delta equal to one when B A and zero otherwise; ij Aeis the second-stage cross pri ce elasticity between goods i andj within group A and j Bwthe budget share of the thj good within group B Empirical Models of a Two-stage Demand System Since the differential approach to consum ption theory discussed in the previous section does not postulate constancy for the coefficients of its demand equations, we can’t talk about empirical estimation. In this section, we postulate that the coefficients are constant and discuss the ways in which th e theoretical models in the previous section are parameterized so that they can be applied to statistical data. Sin ce the nature of data

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171 forces us to work with finite rather th an infinitesimal changes, we replace the infinitesimal changes of the theoretical models presented in the previous section by finite changes. Finally, estimation procedures are presented for the different versions of the Rotterdam model. Two-Stage Block Independent Rotterdam Model The system of first-stage (group) a nd second-stage (second-stage) demand equations for the block independent Ro tterdam demand model can be given by (11) i g j S j ij g g i i i g g g g g gdP dp v dQ W dq w dP dP dQ dQ Wg ' ''. where 212 t g gt gtW W W is the average budget share of group g ; 6 6 1 1...dQ W dQ W dQ ; j S j j gdp dPg '; 6 1'g g gdP dP ; g is a group demand disturbance equal to the sum of i over gS i Since the si have multinomial distribution with zero means, so have the group demand disturbances. If the error te rms of the second-stage demand equation disturbances are correlated w ith the group demand equation dist urbances were correlated, the consumer can no longer separate their allocation problem into two stages (Theil, 1980b). Also, a non-zero correlation of the Divisia volume index gdQand the disturbance of the second-stage equation i imply that the volume index is not a predetermined variable in the second-stage demand systems.

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172 The first-stage or group demand function can be estimated after deleting one of the six group demand equations as (12) ' ' '5 5 5 5 5 4 4 4 4 4 3 3 3 3 3 2 2 2 2 2 1 1 1 1 1 dP dP dQ dQ W dP dP dQ dQ W dP dP dQ dQ W dP dP dQ dQ W dP dP dQ dQ W The second stage requires some manipulation to put it into an estimable form. In order to estimate the second equation of eq uation (12) one of the three second-stage demand equations is deleted from each of th e second-stage demand systems. Using the constrainti S j ijgv, we write the own price coefficient iiv in terms of the other price coefficients as i j ij i iiv vso that the price term of equation (12) becomes (13) g gS i j g j ij g i S i j ij idP dp v dP dp v' ' gS i j i j ij g i idp dp v dP dp' Now, using the constraint n k k n 1' we obtain (14) gS i j i j ij n k n k k n i idp dp v dp dp dp dp1 ' Combining equation (13) a nd equation (14) yields (15) i i j i j ij i i i i i idp dp v B dq dq w '

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173 where n k n k i n i i idp dp dp dp B1 ' The estimable system of equations fo r the second-stage block independent Rotterdam model can thus be given in equation (16) as 2 3 2 1 1 3 1 223 12 2 1 1 2 2 2 13 12 1 1 1 1 1 1dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w 5 6 5 4 4 6 4 556 45 5 2 2 1 5 5 5 46 45 4 2 2 4 4 4dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w 8 9 8 7 7 9 7 889 78 8 3 3 1 8 8 8 79 78 7 3 3 7 7 7dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w 11 12 11 10 10 12 10 111112 1011 11 4 4 1 11 11 11 1012 1011 10 4 4 10 10 10dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w 14 15 14 13 13 15 13 141415 1314 14 5 5 1 14 14 14 1315 1314 13 5 5 13 13 13dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w 17 18 17 16 16 18 16 171718 1617 17 6 6 17 17 17 1618 1617 16 6 6 16 16 16dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w Estimating equation (12) and equation (16) in one system will yield the parameter estimates of the group demand function and second-stage demand functions. The error terms of the second-stage and group demand fu nctions are assumed to be uncorrelated, and that the group Divisia volum e index is predetermined.

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174 Two-Stage Block-wise Dependent Rotterdam Model The system of group and second-stage demand equations of the block-wise dependent Rotterdam demand model can be given by (17) i g j S j ij g g i i i g h h gh gg g ge dP dp v dQ W dq w dP dP V dQ dQ Wg' 6 1 '' The estimation procedure of the block wise dependent Rotterdam model is similar to that of the second-stage block independe nt Rotterdam model pr esented earlier. In order to estimate the group demand equation ( 17) one of the six demand equations would be deleted. Using the constraintgg h ghV 1, we write the own price coefficient ggV in terms of the other price coefficients as 6 g h gh gg ggV Vand substitute it in equation (17) so that the price term of equation (14) becomes (18) dP dP V dP dP Vh g h gh g g h gh gg 6 6' ' 6 g h g h gh gdP dP V A Now combining the first-stage of equati on (17) and equation (18), we obtain (19) g g h g h ij g gg i idP dP V A dQ dq w ' where 6 1 k n k k m h gg gdP dP dP dP A

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175 The estimable systems of the first–st age (equation 20) for the block-wise dependent Rotterdam demand model are given by (20) 5 6 56 5 4 45 5 3 35 5 2 25 5 1 15 5 5 5 5 4 6 46 4 5 45 4 3 34 4 2 24 4 1 14 4 4 4 4 3 6 36 3 5 35 3 4 34 3 2 23 3 1 13 3 3 3 3 2 6 26 2 5 25 2 4 24 2 3 23 2 1 12 2 2 2 2 1 6 16 1 5 15 1 4 14 1 3 13 1 2 12 1 1 1 1( ) ( ) ( ) ( ) ( ) dP dP V dP dP V dP dP V dP dP V dP dP V A dQ dQ W dP dP V dP dP V dP dP V dP dP V dP dP V A dQ dQ W dP dP V dP dP V dP dP V dP dP V dP dP V A dQ dQ W dP dP V dP dP V dP dP V dP dP V dP dP V A dQ dQ W dP dP V dP dP V dP dP V dP dP V dP dP VA dQ dQ W The estimable systems of the second-st age demand equations (equation 21) for the relative price version of the Rotterdam model under block-wise dependence are given by (21) 2 3 2 1 1 3 1 223 12 2 1 1 2 2 2 13 12 1 1 1 1 1 1dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w 5 6 5 4 4 6 4 556 45 5 2 2 1 5 5 5 46 45 4 2 2 4 4 4dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w 8 9 8 7 7 9 7 889 78 8 3 3 1 8 8 8 79 78 7 3 3 7 7 7dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w 11 12 11 10 10 12 10 111112 1011 11 4 4 1 11 11 11 1012 1011 10 4 4 10 10 10dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w 14 15 14 13 13 15 13 141415 1314 14 5 5 1 14 14 14 1315 1314 13 5 5 13 13 13dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w

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176 17 18 17 16 16 18 16 171718 1617 17 6 6 17 17 17 1618 1617 16 6 6 16 16 16dp dp v dp dp v B dQ W dq w dp dp v dp dp v B dQ W dq w Two-Stage Block independent Uniform Substitute-Rotterdam Model The system of group and second-stage demand equations for uniform-substitute block independent Rotterdam dema nd model can be given by (22) i g i g i g g g i i i g g g g g ge dP dp k dQ W dq w dP dP dQ dQ W' ' '1 The estimable systems of the first–stag e (equation 23) and se cond-stage demand equations (equation 24) for the block indepe ndent Rotterdam demand model can be given by ' ' ) 23 (5 5 5 5 5 4 4 4 4 4 3 3 3 3 3 2 2 2 2 2 1 1 1 1 1 dP dP dQ dQ W dP dP dQ dQ W dP dP dQ dQ W dP dP dQ dQ W dP dP dQ dQ W (24) 3 2 3 1 3 2 1 3 2 3 1 3 1 1' 2 1 2 1 1 1 1 1 2 2 2 2 1 1 1 1 1 1 1 1 1 1dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w 6 5 6 4 6 5 1 6 5 6 4 6 4 1' 5 4 5 2 2 2 2 2 5 5 5 5 4 4 2 2 2 2 2 4 4 4dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w

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177 9 8 9 7 9 8 1 9 8 9 7 9 7 1' 8 7 8 3 3 3 3 3 8 8 8 8 7 7 3 3 3 3 3 7 7 7dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w 12 11 12 10 12 11 1 12 11 12 10 12 10 1' 11 10 11 4 4 4 4 4 11 11 11 11 10 10 4 4 4 4 4 10 10 10dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w 15 14 15 13 15 14 1 15 14 15 13 15 13 1' 14 13 14 5 5 5 5 5 14 14 14 14 13 13 5 5 5 5 5 13 13 13dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w 18 17 18 16 18 17 1 18 17 18 16 18 16 1' 17 16 17 6 6 6 6 6 17 17 17 17 16 16 6 6 6 6 6 16 16 16dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w Two-Stage Block-wise dependent uni form substitute-Rotterdam Model The system of group and second-stage demand equations of the block-wise dependent uniform substituteRotterda m demand model can be given by (25) i g i g i gg g g i i i g h h gh gg g ge dP dp k dQ W dq w dP dP V dQ dQ W1 ' 6 1 '1 The estimable systems of the first–stag e (equation 26) and se cond-stage demand equations (equation 27) of the block-wise dependent uniform substituteRotterdam model can be given by (26)

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178 1 6 16 1 5 15 1 4 14 1 3 13 1 2 12 1 1 11 1 1( ) dP dP V dP dP V dP dP V dP dP V dP dP V dP dP dQ dQ W 2 6 26 2 5 25 2 4 24 2 3 23 2 1 12 2 2 22 2 2( ) dP dP V dP dP V dP dP V dP dP V dP dP V dP dP dQ dQ W 3 6 36 3 5 35 3 4 34 3 2 23 3 1 13 3 3 33 3 3( ) dP dP V dP dP V dP dP V dP dP V dP dP V dP dP dQ dQ W 4 6 46 4 5 45 4 3 34 4 2 24 4 1 14 4 4 44 4 4( ) dP dP V dP dP V dP dP V dP dP V dP dP V dP dP dQ dQ W 5 6 56 5 4 45 5 3 35 5 2 25 5 1 15 5 5 55 5 5( ) dP dP V dP dP V dP dP V dP dP V dP dP V dP dP dQ dQ W 3 2 3 1 3 2 1 3 2 3 1 3 1 1' 2 1 2 11 1 11 1 1 2 2 2 2 1 1 11 1 11 1 1 1 1 1dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w 6 5 6 4 6 5 1 6 5 6 4 6 4 1' 5 4 5 22 2 22 2 2 5 5 5 5 4 4 22 2 22 2 2 4 4 4dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w 9 8 9 7 9 8 1 9 8 9 7 9 7 1' 8 7 8 33 3 33 3 3 8 8 8 8 7 7 33 3 33 3 3 7 7 7dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w 12 11 12 10 12 11 1 12 11 12 10 12 10 1' 11 10 11 44 4 44 4 4 11 11 11 11 10 10 44 4 44 4 4 10 10 10dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w 15 14 15 13 15 14 1 15 14 15 13 15 13 1' 14 13 14 55 5 5 5 5 14 14 14 14 13 13 55 5 55 5 5 13 13 13dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w

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179 18 17 18 16 18 17 1 18 17 18 16 18 16 1' 17 16 17 6 6 6 6 6 17 17 17 17 16 16 66 6 66 6 6 16 16 16dp dp dp dp dp dp k dQ W dq w dp dp dp dp dp dp k dQ W dq w

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180 APPENDIX F PARAMETER ESTIAMTES OF FRUIT JU CIES IN A TWO-STAGE ROTTERDAM MODEL Table F-1 Marginal value shares of fruit juices in a two-stag e block independent Rotterdam model Products Estimates SE t-statistics P-value First-stage g Orange .784658 .028024 27.9994 0.000 Grapefruit .032615 .006289 5.18583 0.000 Apple .124181 .019870 6.24952 0.000 Pineapple .013296 .002634 5.04708 0.000 Grape .020134 .007185 2.80217 0.005 Other citrus .025117 .004603 5.45600 0.000 Second-stage i U.S. orange .035610 .011509 3.09418 0.002 Brazilian orange .950692 .013339 71.2725 0.000 ROW orange .013697 .006854 1.99844 0.046 U.S. grapefruit .911801 .039109 23.3142 0.000 Israelis grapefruit .072429 .034661 2.08966 0.037 ROW grapefruit .015770 .019992 .788809 0.430 U.S. apple .324157 .029096 11.1411 0.000 Chinese apple .297490 .023956 12.4181 0.000 ROW apple .378353 .033876 11.1686 0.000 Thai pineapple .345634 .025559 13.5231 0.000 Philippine p. apple .591278 .029544 20.0137 0.000 ROW pineapple .063088 .036658 1.72099 0.085 U.S. grape .436304 .036702 11.8879 0.000 Argentinean grape -.004066 .019330 -.210375 0.833 ROW grape .567762 .034258 16.5729 0.000 Israelis other citrus .284424 .029932 9.50221 0.000 Italian other citrus .356137 .025032 14.2275 0.000 ROW other citrus .359439 .030920 11.6249 0.000 -1.81427 .274134 -6.61821 0.000

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181 Table F-2 Relative price coefficients of fr uit juices in a two-stage block independent Rotterdam model Products Estimates SE t-statistics P-value First-stage ggV Orange -1.42358 .247270 -5.75721 0.000 Grapefruit -.059172 .011022 -5.36847 0.000 Apple -.225298 .039028 -5.77275 0.000 Pineapple -.024123 .004467 -5.39940 0.000 Grape -.036528 .012941 -2.82264 0.005 Other citrus -.045569 .006885 -6.61821 0.000 Second-stage ij U.S. orange -.114667 .021029 -5.45290 0.000 U.S. orange/Brazilian orange .044702 .030979 1.44298 0.149 U.S. orange/ROW orange .005357 .006837 .783593 0.433 Brazilian orange -1.77649 .269315 -6.59635 0.000 Brazilian orange/ROW orange .006975 .015121 .461312 0.645 ROW orange -.037184 .004877 -7.62350 0.000 U.S. grapefruit -1.52703 .268499 -5.68727 0.000 U.S. grapefruit/Israelis grapefruit -.107800 .055164 -1.95419 0.051 U.S. grapefruit/ROW grapefruit -.019429 .032544 -.596994 0.551 Israelis grapefruit -.024248 .009785 -2.47800 0.013 Israelis grapefruit/ROW grapefruit .000642 .003121 .205710 0.837 ROW grapefruit -.163230 .033177 -4.92004 0.000 U.S. apple -.190613 .043210 -4.41137 0.000 U.S. apple/Chinese apple -.163230 .033177 -4.92004 0.000 U.S. apple/ROW apple -.234266 .037809 -6.19601 0.000 Chinese apple -.181944 .037199 -4.89110 0.000 Chinese apple/ROW apple -.194555 .037917 -5.13107 0.000 ROW apple -.257614 .068542 -3.75849 0.000 Thai. pineapple -.223952 .046327 -4.83419 0.000 Thai. pineapple/Philippines pineapple -.363552 .062524 -5.81460 0.000 Thai. pineapple/ROW pineapple -.039571 .022792 -1.73620 0.083 Philippines pineapple -.644166 .109387 -5.88887 0.000 Philippines pineapple/ROW apple -.065022 .038729 -1.67891 0.093 ROW pineapple -.009866 .008921 -1.10597 0.269 U.S. grape -.376426 .076567 -4.91628 0.000 U.S. grape/Argentinean grape .010298 .015761 .653395 0.514 U.S. grape/ROW grape -.425447 .071035 -5.98929 0.000 Argentinean grape -.008522 .003875 -2.19981 0.028 Argentinean grape/ROW grape .005604 .020168 .277910 0.781 ROW grape -.610234 .115943 -5.26324 0.000 Israelis citrus -.163454 .038524 -4.24295 0.000 Israelis citrus/Italian citrus -.175235 .034100 -5.13892 0.000 Israelis citrus/ROW citrus -.177333 .031369 -5.65313 0.000 Italian citrus -.244121 .048530 -5.03027 0.000 Italian citrus/ROW citrus -.226773 .039828 -5.69380 0.000 ROW citrus -.248015 .052568 -4.71796 0.000

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182 Table F-3 Marginal value shares of fruit juic es in a two-stage bloc k independent uniformsubstitute-Rotterdam model Product estimates SE t-statistics p-value First-stage g Orange .779670 .028880 26.9966 0.000 Grapefruit .033851 .006573 5.14986 0.000 Apple .125694 .020189 6.22585 0.000 Pineapple .013412 .002554 5.24986 0.000 Grape .021455 .007565 2.83594 0.005 Other citrus .025919 .004640 5.58519 0.000 Second-stage i U.S. orange .034893 .010019 3.48271 0.000 Brazilian orange .953467 .013316 71.6023 0.000 ROW orange .011640 .003894 2.98891 0.003 U.S. grapefruit .851736 .036264 23.4872 0.000 Israelis grapefruit .092200 .025224 3.65530 0.000 ROW grapefruit .056065 .015162 3.69775 0.000 U.S. apple .283858 .027503 10.3212 0.000 Chinese apple .305403 .022680 13.4660 0.000 ROW apple .410739 .031858 12.8929 0.000 Thai pineapple .312187 .024819 12.5785 0.000 Philippine p. apple .610394 .026926 22.6695 0.000 ROW pineapple .077419 .031026 2.49529 0.013 U.S. grape .432947 .035615 12.1564 0.000 Argentinean grape .071831 .018053 3.97889 0.000 ROW grape .495222 .033521 14.7735 0.000 Israelis other citrus .337320 .027963 12.0630 0.000 Italian other citrus .339260 .024568 13.8088 0.000 ROW other citrus .323420 .027410 11.7992 0.000 -1.78992 .268601 -6.66385 0.000 K1 .733602 .182670 4.01601 0.000 K2 19.5402 6.19318 3.15512 0.002 K3 -18.1022 14.9335 -1.21219 0.225 K4 26.6874 14.1197 1.89009 0.059 K5 31.4253 16.4634 1.90880 0.056 K6 9.80751 6.01929 1.62935 0.103

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183 Table F-4. Marginal value shares of fruit ju ices in a two-stage block-wise dependent Rotterdam model Product estimates SE t-statistics P-value First-stage g Orange .751464 .028163 26.6830 0.000 Grapefruit .037536 .007504 5.00159 0.000 Apple .168712 .020470 8.24180 0.000 Pineapple .002608 .003264 .798972 0.424 Grape .021447 .008919 2.40436 0.016 Other citrus .018233 .005562 3.27800 0.001 Second-stage i U.S. orange .045940 .011898 3.86129 0.000 Brazilian orange .948666 .013595 69.7803 0.000 ROW orange .005393 .006911 .780370 0.435 U.S. grapefruit .970290 .037857 25.6301 0.000 Israelis grapefruit -.053392 .033523 -1.59268 0.111 ROW grapefruit .083102 .019281 4.30995 0.000 U.S. apple .309579 .028504 10.8608 0.000 Chinese apple .293365 .023683 12.3870 0.000 ROW apple .397056 .033429 11.8774 0.000 Thai pineapple .371217 .024475 15.1671 0.000 Philippine p. apple .578753 .028411 20.3710 0.000 ROW pineapple .050030 .034488 1.45064 0.147 U.S. grape .363085 .036141 10.0462 0.000 Argentinean grape .028087 .018890 1.48685 0.137 ROW grape .608828 .033910 17.9541 0.000 Israelis other citrus .290771 .028499 10.2027 0.000 Italian other citrus .345494 .024718 13.9772 0.000 ROW other citrus .363735 .029818 12.1985 0.000

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184 Table F-5. Relative price coefficients of fru it juices in a two-stag e block-wise dependent Rotterdam model Product estimates SE t-statistics P-value First-stage ghV Orange -1.08115 .092591 -11.6766 0.000 Orange/grapefruit -.017084 .017447 -.979229 0.327 Orange/apple -.225097 .045249 -4.97466 0.000 Orange/pineapple .013484 .008623 1.56358 0.118 Orange/grape -.018079 .022379 -.807850 0.419 Orange/other citrus -.017143 .013417 -1.27770 0.201 Grapefruit -.033411 .012913 -2.58748 0.010 Grapefruit/apple .008405 .017001 .494383 0.621 Grapefruit/pineapple -.030916 .005324 -5.80600 0.000 Grapefruit/grape .015116 .011628 1.29997 0.194 Grapefruit/other citrus -.009295 .007211 -1.28886 0.197 apple -.122978 .045207 -2.72035 0.007 Apple/pineapple .029394 .008759 3.35558 0.001 Apple/grape -.011129 .021099 -.527482 0.598 Apple/other citrus .019422 .012870 1.50910 0.131 pineapple -.036891 .005172 -7.13208 0.000 Pineapple/grape .010691 .006959 1.53630 0.124 Pineapple/other citrus .009568 .004232 2.26061 0.024 grape -.062155 .021528 -2.88713 0.004 Grape/other citrus .027168 .009685 2.80498 0.005 Other citrus -.062355 .008608 -7.24365 0.000 Second-stage ij U.S. orange/Brazilian orange .017866 .031392 .569128 0.569 U.S. orange/ROW orange .007783 .006843 1.13729 0.255 Brazilian orange/ROW orange .017496 .015275 1.14538 0.252 U.S. grapefruit/Israelis grapefruit .103170 .061379 1.68086 0.093 U.S. grapefruit/ROW grapefruit -.136896 .031218 -4.38522 0.000 Israelis grapefruit/ROW grapefruit .010289 .005612 1.83326 0.067 U.S. apple/Chinese apple -.151502 .017968 -8.43157 0.000 U.S. apple/ROW apple -.229964 .019423 -11.8395 0.000 Chinese apple/ROW apple -.195847 .021253 -9.21488 0.000 Thai. pineapple/Philippines pineapple -.377307 .028929 -13.0424 0.000 Thai. pineapple/ROW pineapple -.033435 .021830 -1.53162 0.126 Philippines pineapple/ROW apple -.050163 .033530 -1.49607 0.135 U.S. grape/Argentinean grape -.010914 .012270 -.889442 0.374 U.S. grape/ROW grape -.371457 .024538 -15.1378 0.000 Argentinean grape/ROW grape -.028606 .020595 -1.38900 0.165 Israelis citrus/Italian citrus -.171333 .017623 -9.72188 0.000 Israelis citrus/ROW citrus -.180312 .014563 -12.3816 0.000 Italian citrus/ROW citrus -.219075 .017856 -12.2687 0.000 ROW citrus

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185 Table F-6 Marginal value shares of fruit ju ices in a two-stage block-wise dependent uniform-substitute-Rotterdam model Products Estimates SE t-statistics P-value First-stage g Orange .756406 .027528 27.4781 0.000 Grapefruit .040781 .007866 5.18436 0.000 Apple .156724 .019876 7.88518 0.000 Pineapple .004118 .003230 1.27475 0.202 Grape .021782 .008928 2.43948 0.015 Other citrus .020188 .005502 3.66866 0.000 Second-stage i U.S. orange .037614 .010406 3.61459 0.000 Brazilian orange .950939 .013520 70.3377 0.000 ROW orange .011447 .003791 3.01952 0.003 U.S. grapefruit .887821 .034415 25.7974 0.000 Israelis grapefruit .065535 .022347 2.93255 0.003 ROW grapefruit .046644 .015161 3.07647 0.002 U.S. apple .251557 .027094 9.28458 0.000 Chinese apple .310132 .022592 13.7275 0.000 ROW apple .438311 .031785 13.7898 0.000 Thai pineapple .366144 .023983 15.2667 0.000 Philippine pineapple .588128 .026478 22.2123 0.000 ROW pineapple .045727 .030486 1.49996 0.134 U.S. grape .329439 .034654 9.50646 0.000 Argentinean grape .070893 .017576 4.03346 0.000 ROW grape .599668 .033227 18.0478 0.000 Israelis other citrus .339165 .026889 12.6135 0.000 Italian other citrus .322025 .024246 13.2814 0.000 ROW other citrus .338810 .026834 12.6262 0.000 K1 .656030 .211131 3.10722 0.002 K2 15.4812 5.81309 2.66316 0.008 K3 -17.1306 10.9864 -1.55925 0.119 K4 182.938 190.418 .960718 0.337 K5 30.5385 19.0871 1.59996 0.110 K6 19.5314 13.7109 1.42451 0.154

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186 Table F-7 Relative price coefficients of fru it juices in a two-stag e block-wise dependent uniform-substitute-Rotterdam model Products Estimates SE t-statistics P-value Orange -1.21855 .095938 -12.7014 0.000 Orange/grapefruit -.018566 .018860 -.984413 0.325 Orange/apple -.229599 .045051 -5.09648 0.000 Orange/pineapple .011628 .855837E-02 1.35863 0.174 Orange/grape -.021365 .023077 -.925846 0.355 Orange/other citrus -.020387 .013641 -1.49452 0.135 Grapefruit -.041094 .014669 -2.80141 0.005 Grapefruit/apple -.153681E-02 .018222 -.084339 0.933 Grapefruit/pineapple -.030683 .570167E-02 -5.38142 0.000 Grapefruit/grape .021011 .012734 1.65002 0.099 Grapefruit/other citrus -.983250E02 .777688E-02 -1.26432 0.206 apple -.102394 .045164 -2.26717 0.023 Apple/pineapple .024435 .859537E-02 2.84279 0.004 Apple/grape -.020097 .021009 -.956610 0.339 Apple/other citrus .019055 .012798 1.48885 0.137 pineapple -.035858 .471975E-02 -7.59752 0.000 Pineapple/grape .011926 .696278E-02 1.71287 0.087 Pineapple/other citrus .010403 .425146E-02 2.44689 0.014 grape -.057979 .021841 -2.65464 0.008 Grape/other citrus .023401 .982678E-02 2.38131 0.017 Other citrus -.062588 .851760E-02 -7.34811 0.000

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187 LIST OF REFERENCES Abbot, P. and P. Paarlberg. 1986. “Modeling th e Impact of the 1980 Grain Embargo.” Embargoes, Surplus Disposal and U.S. Agriculture. U.S. Department of Agriculture, Economic Research Service Staff Report No. AGES860910. Washington, D.C.: ERS/USDA. Alston, J.M., C.A Carter, R. Green, and D. Pick. 1990. “Whither Armington Trade Models.” American Journal of Agricultural Economics 72(1990): 455–67. Armington, P. 1969. “A Theory of Demand for Products Differentiated by Place of Production.” International Monetary Fund Staff Papers, 16:159-178. Babula, R. 1987.“An Armington Model of U.S. Cotton Exports.” Journal of Agricultural Economics Research 39:12–22. Barten, A. 1964. “Consumer Demand Functions under Conditions of Almost Additive Preferences.” Econometrica 32:1–38. _____. 1969. “Maximum Likelihood Estimation of a Complete System of Demand Equations.” European Economic Review 1:7–73. _____, 1977. “The Systems of Consumer Demand Functions Approach: A Review.” Econometrica 45:23–51. _____. 1993. “Consumer Allocation Models : Choice of Functional Form.” Empirical Economics 18:1:129–58. Blundell, R. and J.M. Robin 2000 “Latent Separability: Grouping Goods without Weak Separability” Econometrica 68: 53-84. Brown, M. 1993. “Demand Systems for Compe ting Commodities: An Application of the Uniform Substitute Hhypothesis.” Review of Agricultural Economics 15(3): 577-589. Brown, M., J. Lee and J. Seale. 1994 “Demand Relationships among Juice Beverages: A Differential Demand System Approach.” Journal of Agricultural and Applied Economics 26(2): 417-29.

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189 Frisch. 1959. “A Complete Scheme for Computing all Direct and Cross Demand Elasticities in a Model with Many Sectors.” Econometrica 27:177-196 Gao, X., E. Wailes, G. Cramer. 1996. “A Tw o-stage Rural Household Demand Analysis: Micro Data Evidence from Jiangsu Province, China.” American Journal of Agricultural Economics 78(3):604-613. Goodwin, J. 1994. Agricultural Price Analysis and Forecasting New York: John Wiley and Sons, Inc. Greene, W., 2000. Economic Analysis Upper Saddle River, NJ: Prentice Hall. Grennes, T., P.R. Johnson, and M. Thursby. 1977. The Economics of World Grain Trade. New York: Praeger Publishers. Hall, B and C. Cummins. 1999. Time Series Processor version 4.5. Reference Manual TSP International Palo Alto, California, USA Haniotis, R. 1990. “European Community Enlargement: Impact on U.S. Corn and Soybean Exports.” American Journal of Agricultural Economics 72: 289–97. Huang, S. 2004. Global Trade Patterns in Fruits and Vegetables. Agriculture and Trade Report No. WRS-04-06. Available at http://www.errs/usdagov/publications/wrs 0406/wrs040dfm.pdf (11 April 2006) JETRO (Japan External Trade Organization) Market Information for Fruit Drinks. Available at http://www.jetro.go.jp/en/market/reports/jmr/024.pdf (3 March 2005) Lee, J., J. Seale, and P. Jierwiriyapant. 1990. “Do Trade Agreements Help U.S. Exports? A Study of the Japa nese Citrus Industry.” Agribusiness 6: 505-14. Lee, J., M. Brown, and J. Seale. 1992. “D emand Relationships among Fresh Fruit and Juices in Canada.” Review of Agricultural Economics 14:255–62. Lee, J., M. Brown, and J. Scale 1994. “Model Choice in Consumer Demand Analysis: Taiwan 1970–89.” American Journal of Agricultural Economics 76:504–12. Sarris, A. 1981. “Empirical Models of International Trade in Agricultural Commodities,” in Imperfect Markets in Agricultural Trade edited by A. McCalla and T. Josling. Montclair: Allenheld, Osmun and Co. _____. 1983. “European Community Enlargement and World Trade in Fruits and Vegetables.” American Journal of Agricultural Economics 65: 235–46.

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190 Schmitz, T. and J. Seale. 2002. “Import Demand for Disaggregated Fresh Fruits Japan.” Agricultural and Res ource Economics Review 34(3): 585-602. Seale, J. 1996. Import Demand for Products Differentiated by Place of Production. Intentional Working Paper Series IW96-13, Un iversity of Florida, Gainesville, FL 32611 Seale, J. 2003. “Uniform Substitute When Group Preferences are Block-wise Dependent.” Journal of Agricultur al and Applied Economics 35(0): 51-55. Seale, J., A. Sparks and B. Buxton. 1992. “A Rotterdam Application to International Trade in Fresh Appl es: A Differential Approach.” Journal of Agricultural and Resource Economics 17(1): 138-49. Selvanathan, E. and S. Selvanathan, 2004. “Economic and Demographic Factors in Australian Alcohol Demand.” Applied Economics 36:2405-2417. Soshnin, A., W. Tomek and H. Gorter. 1999. “Elasticities of Demand for Imported Meats in Russia.” Working Paper 19, Department of Applied Economics and Management, Cornell University, Ithaca, New York 14853-7801. Spreen,T.,R. Barber, M.Brown,, A. Hodges, J.Malugen, D. Mulkey, R., Muraro, R. Norberg, M. Rahmani, F. Roka and R. Rouse 2006. An Economic Assessment of the Future Prospects for the Florid a Citrus Industry. Available at http://www.fred.ifas.ufl.edu/ec onomic_assess_flciturus_indus.pdf (14 April 2006) Statistics Bureau of Japan’s Ministry of Internal Affair s and Communications Population Eestimates. Available at ( http://www.stat.go.jp/eng lish/data/jinsui/2-2.htm (12 March 2006) Theil, H. 1965. “The Information Approach to Demand Analysis”. Econometrica 33:67–87. ______. 1971. Principles of Econometrics 1971. New York: John Wiley and Sons, Inc. ______. 1975. Theory and Measurement of Consumer Demand Vol. I and II. Amsterdam: North Holland. _______. 1980(a). The System-Wide Approac h to Microeconomics Chicago: University of Chicago Press. _______. 1980(b). System-Wide Explorations in Inte rnational Economics, Input-Output Analysis and Marketing Research North-Holland Pub lishing Company, Amsterdam.

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191 Theil, H. and Clements, K.1978. “A Differen tial Approach to U.S. Import demand.” Economics Letters 1:249-252. UNCTAD (United Nations Conference on Trad e and Development). Citrus fruit. Available at. http://r0.unctad.org/infocomm /anglais/orange/market.htm (12 March 2006) University of Pretoria. Global citrus industry. Available at http://www.up.ac.za/academic/ fabi/citrus/global.html (12 March 2006) USDA (United States Department of Agri culture). Japan: Trade. Available at http://www.ers.usda.gov/Bri efing/Japan/trade.htm (12 March 2005) Washington, A. 2000. The derived demand for imported dairy products in selected international markets. PhD dissertation, University of Florida, Gainesville, FL 32611 Washington, A. and R. Kilmer. 2002. “The Production Theory Approach to Import Demand Analysis: A Comparison of the Rotterdam Model and the Differential Production Approach.” Journal of Agricultural and Applied Economics 34(3): 431-43. Weatherspoon, D., and J. L. Scale. 1995. “D o the Japanese Consumers Discriminate AgainstAustralian Beef Imports? Eviden ce from the Differential Approach.” Journal of Agricultural and Applied Economics 27(2):536–543. Yang, R. and W. Koo. 1994. “Japanese Meat Import Demand Estimation with the Source Differentiated AIDS Model.” Journal of Agricultural and Resource Economics .19: 396:408. Zhang, P., S. Fletcher and D. Carle y. 1994. “Japan’s Peanut Import Demand: Implications for United States Exports.” Agricultural Economics 11 (1):51-59.

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192 BIOGRAPHICAL SKETCH Shiferaw Tesfaye Feleke was born in Et hiopia on 13 July 1971. He joined the Alemaya University of Agriculture in Et hiopia in 1988 and received a Bachelor of Science degree in agricultural economics in 1992. He worked for the Awassa Agricultural Research Center (Southern Ethiopia) for eight years before he joined the Food and Resource Economics Department at the University of Florida in 2000 for further education. He received the Master of Science degree in agricultural economics in 2002 and continued a PhD program in the same field in the same department and received a PhD in 2006.


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GLOBAL COMPETITION FOR THE JAPANESE FRUIT JUICE MARKET


By

SHIFERAW TESFAYE FELEKE
















A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


2006


































Copyright 2006

By

Shiferaw Tesfaye Feleke

































This document is dedicated to my mom















ACKNOWLEDGMENTS

Writer William Arthur Ward once said, "Feeling gratitude and not expressing it is

like wrapping a present and not giving it." I couldn't agree more. My first, and most

sincere, acknowledgment must go to the chairman of my supervisory committee, Dr.

Richard L Kilmer. I would like to express my deepest gratitude and sincere appreciation

to him for his meticulous review of the manuscript, guidance, encouragement and

patience to successfully complete my study. I gratefully acknowledge and thank him for

everything he did throughout my program. I was very fortunate to work closely with him.

Our frequent interactions were very invaluable learning experiences. I am also very

grateful to Dr. Jonq Lee for introducing me the differential demand systems and TSP

program and helping me understand the basics and analytics of differential demand

systems that provide the basis of this study. I sincerely thank him for his patience in

reviewing, providing me with invaluable comments and suggestions from the very

beginning of proposal preparation up until the completion of this dissertation. Many

thanks must also go to the other members of my supervisory committee, Drs. Ronald

Ward, James Stems and Lawrence Kenny, for providing me with constructive comments

and suggestions. I would like to thank them all for their support and guidance. I am also

grateful to Dr. Mark Brown for his assistance with the data analysis.

I am grateful to the Food and Resource Economics Department of the University

of Florida for affording me the opportunity of research assistantship to pursue my studies

in the department for the last six years. Special thanks must go to the department chair,









Dr. Thomas Spreen, graduate coordinator Dr. Jeffery Burkhardt, and graduate program

assistant Jessica Herman. I am very appreciative of the support I received from Dr.

Spreen and Jessica Herman.

I am also thankful to my officemate Katherine Finn for every help she offered me

during the preparation of this dissertation and for being a nice officemate. I would also

like to thank my friends and classmates Marco, Angel, Lurleen, Joy, Mariana and Maria.

Special thanks go to Lurleen for being an important force of motivation. Our frequent

interactions have been the source of learning. I am indebted to my fellow friends Seleshi,

Worku, Abiy, Dr. Getachew, Dr. Ayalew, Dr. Tesfaye, Saba Haile Selasie, Saba Ataro

and Measho for their support, encouragement and friendship.

My final, and most heartfelt, acknowledgment must go to my father Tesfaye, my

sister Firehiwot, my wife Genet and my daughter Biruktawit. I dedicate this dissertation

to my mother Yeshi who passed away a couple of years ago.
















TABLE OF CONTENTS

page

A C K N O W L E D G M E N T S ................................................................................................. iv

LIST OF TABLES .............. .......... .. ....... ........... ....... ix

L IST O F F IG U R E S .... ...... ................................................ .. .. ..... .............. xii

A B S T R A C T .............................................. ..........................................x iii

1 IN TR OD U CTION ............................................... .. ......................... ..

B ack g rou n d ...................................... .............................. .... ......... ...... .
O objectives ................................................................. ........ .......... 4
H ypotheses ................................................ 5
O u tlin e ............................................................................ . 7

2 GLOBAL PRODUCTION, TRADE AND CONSUMPTION OF FRUIT................9

G lobal Fruit P reduction ... ..... ... ... ......... .......... ......... ..................... 9
The Production of Oranges, Lemons and Limes, and Grapefruits and Pomelos 12
The Production of Grapes, Apples, and Pineapples ..........................................16
Global Fruit Trade .................................... .. .......... .. ............19
G lobal Fruit Consum ption .......................................................... ............... 21

3 TH EORETICAL M OD ELS ............................................... ............................ 24

D em and A pproaches............. ........................................................ ... ...... 24
Production A pproach............................................................ ............... 25
Consum er D em and A approach ........................................ ......... ............... 28
U utility M axim ization ........................................ .... ....... ..... ...... 29
The Rotterdam M odel .................. ............................ ........ .................. 32
B lock Independence ........................ .. ...................... .. ...... .... ..... ...... 36
B lock-w ise D ependence ............................................. ............................. 39
Uniform Substitute Hypothesis ....................................... ....................... 42
Uniform substitute given block independence ..........................................42
Uniform substitute given block-wise dependence.......................................45









4 EMPIRICAL MODELS AND ESTIMATION PROCEDURES ...............................48

E m pirical M models ............... ........... .................... .................... 4 8
The Relative Price Version of the Rotterdam Model ........................................48
The Absolute Price Version of the Rotterdam Model .......................................52
Block Independent Non-uniform Substitute-Rotterdam Model........................54
Block-wise Dependent Non-uniform Substitute-Rotterdam Model....................56
Block Independent Uniform Substitute-Rotterdam Model ..............................60
Block-wise Dependent Uniform Substitute-Rotterdam Model.........................63
Data Sources ............ .......... ..................... 66
A n alytical M eth od s........... .......................................................................... ............... 67

5 RESULTS AND DISCU SSION ........................................... .......................... 69

D descriptive R results .......... ........ ... ........ ........ ............ ...... .............. 69
Test for First-order A utocorrelation ........................................ ....................... 70
H ypothesis Testing for M odel Selection .......................................... ............... .... 72
Block Independence and Uniform Substitute Hypothesis................................72
Block-wise Dependence and Uniform Substitute Hypothesis...........................74
The relative Price Version of the Rotterdam Model.................................................76
P aram eter E stim ates ................................................................ ....................7 7
Expenditure Elasticities ................................ .................. .......... ..... 82
Own-price Elasticities ......................... .... .... ... ............... 88
C ross-price E lasticities ............................................... ............................. 90

6 MARKET STRUCTURES AND STRATEGY OPTIONS ......................................97

M ark et Structu res................ .. .. .... .... ........ .. ..... ... .. .................... 97
Block Independence (Direct) with Non-uniform Substitution..........................97
Block Independence (Direct) with Uniform Substitution ..................................98
Block-wise Dependence with Non-uniform Substitution.............................. 98
Block-wise dependence with Uniform Substitution............... ................... 100
Parameter and Elasticity Estimates in Five Market Structures .......................101
Param eter estim ates ........................................................ ............. 102
Expenditure elasticities ........................................ ......................... 104
P rice elasticities....... ............................................. ...... ...... ... ......... 106
M market Strategy O ptions................................................. .............................. 109

7 SUMMARY, CONCLUSIONS AND IMPLICATIONS ............... ..................110

Sum m ary and C onclu sions ............................................................ ..................... 110
Im plications ........... ......................................... ........... ... ..... ....... 114

APPENDIX

A PRICE COEFFICIENTS OF FRUIT JUICES IN JAPAN...................................118

B PRICE ELASTICITES OF FRUIT JUICES IN JAPAN ............. ...............124









C PARAMETER ESTIMATES OF ROTTERDAM MODEL UNDER DIFFERENT
SEPARABILITY A S SUM PTION S ........................................................................136

D PRICE ELASTICITIES OF FRUIT JUICES IN JAPAN IN DIFFERENT
M ARKET STRU CTURES ............................................................. ............ .142

E TWO-STAGE ROTTERDAM MODEL ..............................166

F PARAMETER ESTIAMTES OF FRUIT JUCIES IN A TWO-STAGE
R O T TE R D A M M O D E L ........................................ ...........................................180

LIST OF REFEREN CES ........................................................... .. ............... 187

BIOGRAPHICAL SKETCH ............................................................. ............... 192
















LIST OF TABLES


Table page

2.1 Global citrus production, area harvested and yield per hectare, 2005 ...................10

2.2 Global production of oranges, grapefruit and pommels, and lemons and limes in
2 0 0 5 ............................................................................................... 12

2.3 Global production of apples, grapes, and pineapples, 2005.................................16

2.4 Fruit juice imports to Japan by country of origin..................................................22

2.5 Per capital consumption of fruits in industrialized and developing countries ..........23

4.1 Codes for countries exporting fruit juice to Japan .............................. ...............50

5.1 Fruit juice quantity and price log-changes, and expenditure shares, Japan,
D ecember 1995 to M ay 2005 ............................................................................70

5.2 Test for first-order autocorrelation..................................................71

5.3 H hypothesis testing for m odel selection ........................................ .....................74

5.4 Marginal expenditure shares of imported fruit juices in Japan ..............................77

5.5 Parameter estimates of cross prices of fruit juices in Japan .............. ...............80

5.6 Parameter estimates of own prices of fruit juices in Japan ................................82

5.7 Expenditure elasticity estimates of fruit juices in Japan .............. ......................84

5.8 Own price elasticities of fruit juices in Japan........................... .... ............... 89

5.9 Cross-price elasticity estimates of substitutes ......................................................94

5.10 Cross-price elasticity estimates of complements .............................................. 96

6.1 Importance of country of origin in five market structures ................................... 101

6.2 Relative price coefficients of fruit juices in five market structures ....................... 104

6.3 Expenditure elasticity estimates of fruit juices in Japan in five market structures 105









6.4 Uncompensated own price elasticity estimates of fruit juices in Japan ............... 107

6.5 Compensated own price elasticity estimates of fruit juices in Japan ..................... 108

6.6 Market strategies by market structures ..................................... ...............109

A-i Relative price coefficients of fruit juices in Japan .............................................. 118

A-2 Slutsky price coefficients of fruit juices in Japan ...........................121

B-l Uncompensated price elasticities of fruit juices in Japan..................................... 124

B-2 Compensated price elasticities of fruit juices in Japan ......................................... 130

C.1 Marginal value shares of fruit juices in a block independent Rotterdam model....136

C.2 Relative price coefficients of fruit juices in a block independent Rotterdam
m odel .................................... ................... ............... ........... 136

C.3 Marginal value shares of fruit juices in a block independent uniform-substitute
R otterdam m odel ............................................. ... .... ................. 137

C.4 Marginal value shares of fruit juices in a block-wise dependent Rotterdam
m odel .................................... ................... ............... ........... 138

C.5 Constant of proportionality of fruit juice groups in a in block-wise dependent
R otterdam m odel ............................................. ... .... ................. 138

C.6 Within-group relative price coefficients of fruit juices in a block-wise dependent
R otterdam ............................................................... ... .... ......... 138

C.7 Marginal value shares of fruit juices in a block-wise dependent uniform-
substitute R otterdam m odel ......................................................... .......... ..... 139

C.8 Constant of proportionality of fruit juice groups in a block-wise dependent
uniform-substitute-Rotterdam model ........... ..................................140

C.9 Within-group relative price coefficients of block-wise dependent uniform
substitute R otterdam m odel ......................................................... .......... ..... 140

F.1 Marginal value shares of fruit juices in a two-stage block independent
R otterdam m odel ............................................. ... .... .................. 180

F.2 Relative price coefficients of fruit juices in a two-stage block independent
R otterdam m odel ............................................. ... .... ........... ....... 181

F.3 Marginal value shares of fruit juices in a two-stage block independent uniform-
substitute-R otterdam m odel e........................................... .......................... 182









F.4 Marginal value shares of fruit juices in a two-stage block-wise dependent
R otterdam m odel ............................................. ... .... .................. 183

F.5 Relative price coefficients of fruit juices in a two-stage block-wise dependent
R otterdam m odel ............................................. ... .... .................. 184

F.6 Marginal value shares of fruit juices in a two-stage block-wise dependent
uniform-sub stitute-Rotterdam model ........... ..... .............. ............... 185

F.7 Relative price coefficients of fruit juices in a two-stage block-wise dependent
uniform-sub stitute-Rotterdam model ........... ..... .............. ............... 186
















LIST OF FIGURES


Figure page

2.1 Citrus productions (MT) of major producers, 1961-2005.............. ................. 11

2.2 Orange productions (MT) of major producers, 1961-2005.............. ...................13

2.3 Lemon and lime production (MT) of the top four producers, 1961-2005 ..............14

2.4 Grapefruit and pomelos production (MT) in the U.S. and China, 1961-2005 .........15

2.5 Grape productions (MT) of the top three countries, 1961-2005 ............................17

2.6 Apple productions (M T) in the U.S. and China...................................................18

2.7 Pineapple productions (MT) of major producers, 1961-2005................................19

3.1 A tw o stage profit m axim ization .............. ..................... ........... ... ............ 26

3.2 A two-stage utility maximization......... ..... ............................. ... ............ 27















Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

GLOBAL COMPETITION FOR THE JAPANESE FRUIT JUICE MAREKT

By

Shiferaw Tesfaye Feleke

August 2006

Chair: Richard L. Kilmer
Major Department: Food and Resource Economics

This study identifies the market structure of fruit juices imported into Japan

within the context of a consumer demand theory using three different versions of the

Rotterdam model (the block independent uniform substitute-Rotterdam model, the block-

wise dependent uniform substitute-Rotterdam model, and the relative price version of the

Rotterdam model). The models were formulated under the hypotheses of block

independence/block-wise dependence among products that belong to different product

groups and uniform substitute among products that belong to the same product group.

They were estimated for six different kinds of fruit juices (orange, grapefruit, other citrus,

apple, pineapple and grape juices imported from 18 countries) on monthly per capital data

over the period December, 1995, to May, 2005, using the non-linear least squares (LSQ)

in the Time Series Processor (TSP) program. Statistical tests select the relative price

version of the Rotterdam demand model as explaining the allocation decisions better

compared with the other versions and identify a market structure which involves both

direct and indirect competition based on the country of origin.









The results have important implications for countries exporting fruit juices to Japan

for identifying marketing strategies such as price reduction, product promotion, market

integration, as well as export supply decisions in light of the expansion and contraction of

the Japanese market for imported fruit juices because of the change in income.














CHAPTER 1
INTRODUCTION

Japan, with the second largest economy in the world and a population of about

127 million, imports agricultural products worth over $30 billion each year (USDA). The

U.S. is the leading agricultural supplier accounting for nearly one-third of Japan's total

agricultural imports, though this share has declined slightly since the mid-1990s. China

and the EU-15 are the next-largest suppliers, each with over 12% of Japan's agricultural

imports (USDA).

This study focuses on a portion of Japan's imports which include orange,

grapefruit, other citrus, apple, pineapple and grape juices. Orange, grapefruit, apple and

grape juices account for 86% of fruit juice imports on a value basis (JETRO). The

leading exporters of orange and grapefruit juices to Japan are Brazil and the U.S.,

respectively. The U.S. is also a leading exporter of grape and apple juices while Thailand

and Israel are the leading exporters of pineapple and other citrus juices, respectively.

Background

Following the deregulation of imports of apple, grapefruit, and pineapple juices as

of April 1990 and that of orange juice as of April 1992, the import penetration ratio (the

fraction of income spent on imports or the increase in the extent of consumption of

imports) of processed fruits into Japan has increased (JETRO). Furthermore, Japan is

undergoing a profound change as a result of its aging population. Japan's statistical

agency has measured a decline in population growth that is about to become an absolute

decline, and population shrank for the first time in 2006 and will gradually fall for a









number of years thereafter. The impact of this demographic change on the demand for

fruit in Japan is an empirical question, since either the aging affluent consumers may

increase consumption of fruits to stay healthy or demand may decrease with the absolute

decrease in population size. In either case, the increase of import penetration in the face

of an aging population and declining population growth will lead to an increased

competition among exporters.

The purpose of this study is to assess the competitiveness of the world's largest

exporters of fruit juice into Japan through the analysis of market structure. The analysis

of market structure in marketing is concerned with identifying closely competing brands

of the same product (Clements and Selvanathan, 1988). Consumption theory is amenable

to the analysis of market structure in international markets through demand analysis. The

approach involves the analysis of the change in marginal utilities of a certain product due

to a change in consumption of a closely related product.

The decrease in marginal utility of one product with an increased consumption of

another product implies that the products are substitutes and are thus in a competitive

market structure. Otherwise, they are not substitutes (i.e., complements or independent)

and are thus in a non-competitive market structure. Substitute products can be uniform1

(close) or non-uniform. If two products are uniform substitutes, price-oriented marketing

strategies and/or generic product promotion are recommended because consumers are not

influenced by the country of origin of such products. If two products are non-uniform

substitutes, consumers are influenced by the country of origin and thus exporters can

exercise a monopolistic power over their respective products. In this case, a non-price

1 The change in the marginal utility of a dollar spent on product i is the same as that of another dollar spent
on product j .









marketing strategy (e.g., product promotion) and/or price reduction is recommended to

increase market share.

Be it uniform or non-uniform, the decision to use a particular marketing strategy

depends on the price elasticity of demand for the product in question. Under a situation

in which a product is a uniform substitute but price inelastic, the decision to reduce price

is not advised because total revenue is reduced when price is decreased. However, the

response of demand to changes in price may be higher under the uniform substitute

relationship than under the non-uniform substitute relationship. This implies that both

the nature of substitution (uniform/non-uniform) and the magnitude of substitution

elasticitiess) are important in international trade since they have different implications to

exporters for marketing strategies such as market promotion, product differentiation as

well as a product supply plan (expansion or contraction of supply).

Most empirical studies have pursued the estimation of conditional demand

functions in isolation without testing for the nature of substitution within a product group,

and the nature and magnitude of substitution between product groups. However,

conditional demand parameters thus estimated are rarely of interest for policy analysts

because the appropriateness of marketing strategy depends on the relationship between

products within the same product group and across different product groups.

If, for example, the relationship between products within the same product group

is uniform, the appropriate marketing strategy is price reduction because consumers view

those products as homogenous. If, however, the products in the group are non-uniform,

product promotion is recommended because consumers can pay a different price since

they view them as differentiated products. Furthermore, since the optimal allocation of









expenditure to products in any one partition may depend on prices of products outside

that group in a uniform or non-uniform fashion, the failure to consider the nature and

magnitude of substitution between products in different products groups may misguide

marketing strategists. For example, the effect of a change in price of Chinese apple juice

on the demand for Brazilian may be the same as that on the demand for Florida orange

juice. The marketing strategy that is appropriate for this situation is different from the

situation in which the effect of a change in the price of Chinese apple juice on the

demand for Brazilian orange juice is different from that on the demand for Florida orange

juice. To be useful for policy applications in terms of designing an effective marketing

strategy, the demand for fruit juices in this study is estimated under different scenarios of

market structures consistent with consumer's preference structure.

Objectives

The objectives of this study are the following.

(1) To characterize the trend and pattern of the world fruit production, trade and
consumption.

(2) To identify the market structure of fruit juices imported into Japan by
estimating a differential consumer demand system.

(3) To assess the competitiveness of the world's largest exporters of fruit juice
into Japan.

(4) To simulate the impact of changes in population growth on the growth rate of
demand for fruit juices by country of origin.


In order to identify the market structure of fruit juices in Japan, two hypotheses

are tested. These are block independence/uniform substitute and block-wise

dependence/uniform substitute hypotheses.









Hypotheses

Block Independence/Uniform Substitute Hypothesis

The hypothesis of block independence/uniform substitute states that there is no

change in marginal utility of a dollar spent on a product in one product group caused by

an extra dollar spent on another product in another product group. But, the change in the

marginal utility of a dollar spent on a product in one product group caused by an extra

dollar spent on another product in the same product group is the same for all pairs of

products in that group. This hypothesis represents the market structure of block

independent (direct competition) with uniform substitution such that a change in the price

of a product in one group (e.g. orange juice group) does not affect the demand for another

product in another group (e.g. apple juice group). But, the change in the price of a

product in one group (e.g. orange juice group) uniformly affects the demand for another

product in the same group.

The failure to reject the null hypothesis implies that exporters of one fruit juice

group don't have to worry about the change in price of products that belong to other juice

groups because competition occurs only between products of the same product group or

the same products differentiated by country of origin. Furthermore, exporters of products

that belong to the same product group can only compete by reducing price (i.e. use a

price-oriented marketing strategy and/or generic product promotion) because under such

circumstances consumers are not influenced by the country of origin of the product, since

they perceive products from different countries as homogenous. Brand promotion is not

recommended because brand promotion for a uniform substitute product is technically a

generic promotion. For example, if Florida orange juice is a uniform substitute to









Brazilian orange juice, promoting Florida orange juice may rather help raise the sales of

Brazilian orange juice.

In summary, if two products are uniform, only a slight decrease in price makes a

big difference in sales, implying that the market of uniform substitute products is very

competitive. This may lead firms to merge so that they will be able to exercise a

monopolistic power.

Block-wise Dependence/Uniform Substitute Hypothesis

The hypothesis of block-wise dependence/uniform substitute hypothesis states

that the change in the marginal utility of a dollar spent on a product in one product group

caused by an extra dollar spent on another product which belongs to a different product

group is the same for all pairs of products that belong to the two product groups. Also,

the change in the marginal utility of a dollar spent on a product in one product group

caused by an extra dollar spent on another product in the same product group is the same

for all pairs of products in that group. This hypothesis represents the market structure of

block-wise dependent with uniform substitution such that a change in the price of a

product in one group (e.g. orange juice group) affects the demand for another product in

another group (e.g. apple juice group) in a similar fashion. Furthermore, the change in

the price of a product in one group (e.g. orange juice group) uniformly affects the

demand for another product in the same group.

The failure to reject the null hypothesis implies that exporters of one fruit juice

group need to watch the change in price of products in other juice groups because

competition occurs between products of different product groups. Since the competition

between products in different groups occurs in a similar fashion, a slight change in price









of one product in one group will significantly affect the demand for products in other

groups. Furthermore, exporters of products that belong to the same product group can

only compete by reducing price because under such circumstances consumers are not

influenced by the country of origin of the product, since they perceive products from

different countries and product groups as homogenous.

In summary, if two products are uniform within and across product groups, only a

slight decrease in price makes a big difference in sales, implying that the exporters of

products that belong to different product groups is very competitive. Hence, exporters of

products that belong to different product groups should pay close attention to the price

behavior of either product because only a slight change in price of one juice group

significantly affects the sales of another juice group.

Based on results of the test of the above hypothesis, the study will identify the

market structure of Japan's fruit juice market. This will allow analyzing the

competitiveness of countries exporting fruit juices to Japan, and drawing implications in

terms of marketing strategies. Results will be useful for providing a structure for

marketing research on closely related products and identifying marketing strategies

involving price reduction, product differentiation and market promotion.

Outline

The dissertation is organized as follows. Chapter 2 presents the global fruit

production, trade and consumption. In this chapter, the trend, pattern and quantity of

production, trade and consumption of major players are investigated.

Chapter 3 presents the theoretical section in which the common approaches in

import demand analysis and the different demand models are reviewed. The chapter also









derives the different versions of the Rotterdam model used for empirical estimation and

tests the hypothesis presented in chapter 1.

Chapter 4 presents the empirical model and the estimation procedure. This

chapter includes (1) the systems of equations that are empirically applied to statistical

data (2) the procedures that need to be followed to estimate the models (3) the source of

data and analytical methods.

Chapter 5 presents the results and discussion. This chapter discusses (1) the

model that best describes the import data of fruit juices (2) the expenditure and price

elasticities estimated from the selected model (3) results of simulation about the effect of

the decline in population growth on the growth of demand for fruit juices.

Chapter 6 presents different market structure scenarios and compares the results

of these different market structures with the results of chapter 5.

Finally, chapter 7 summaries the results and draws conclusions. Based on the

conclusions, implications are drawn.














CHAPTER 2
GLOBAL PRODUCTION, TRADE AND CONSUMPTION OF FRUIT

This chapter presents a description of global fruit production, trade and

consumption. Both citrus and non-citrus fruits are included. The citrus fruits include

orange, grapefruit, and lemons and limes while the non-citrus fruits include apples,

grapes and pineapples. Data for this report come mainly from the website maintained by

the Food and Agricultural Organization (FAO).

Global Fruit Production

Citrus (Citrus L.) is one of the world's most important fruit crops commercially

grown primarily between the latitudes 400N to 400S (University of Pretoria). According

to the University of Pretoria, Yunnan province in south-central China may be the center

of origin due to the diversity of species found, and the network of rivers in this area

which could have provided "on route dispersal" to the south. From there, they slowly

spread to northern Africa mainly through migration and trade. Citrus spread throughout

Europe during the Middle-Ages and were then brought to the Americas by Spanish

explorers. Worldwide trade of citrus fruits didn't appear until the 1800s and trade in

orange juice developed as late as 1940. Citrus production in Florida dates back to the

colonization of the state by the Spaniards in the 15th century (Spreen et al. 2006). Today,

the major types of edible citrus include citron, sour orange, sweet orange, lime, lemon,

shaddock pomeloss), grapefruit, mandarin, and kumquat.

The world's largest producers of citrus fruits are Brazil, China, U.S. and Mexico

whose combined production accounted for half of the world's total in 2005. During the









same year, Brazil's production accounted for the highest proportion (19%) followed by

that of China (15%), U.S. (10%) and Mexico (6%) of the world's total (Table 2.1). In

terms of area, China, Brazil, Nigeria and Mexico rank first, second, third, and fourth,

respectively, accounting for about 23%, 12% and 10% and 7% of the global citrus area

harvested in 2005, respectively. During the same year, the world's highest yield per ha

was obtained in Turkey, Syria, S. Korea and U.S., each producing about 26 Mt per

hectare. The productivity of citrus in China as measured by yield per ha is one of the

lowest in the world (FAO, 2005).

Table 2.1 Global citrus production, area harvested and yield per hectare, 2005
Country Production(MT) % Yield (MT/Ha) Area (ha) %
Brazil 20,142,100 19 Turkey 26.7 China 1,714,300 23
China 16,019,500 15 Syria 26.3 Brazil 930,379 12
U.S. 10,317,200 10 S. Korea 26.2 Nigeria 730,000 10
Mexico 6,475,411 6 U.S. 26.0 Mexico 523,505 7
Spain 4,867,300 5 Guatemala 24.7 U.S. 397,080 5
India 4,750,000 5 Palestine 24.5 India 264,500 3
Italy 3,836,793 4 Israel 23.7 Spain 240,759 3
Iran 3,825,000 4 Cyprus 23.2 Iran 232,500 3
Nigeria 3,250,000 3 Australia 22.8 Pakistan 185,400 2
Egypt 2,797,600 3 Italy 22.5 Italy 170,338 2
Total 78,801,620 74 Total 5,388,761 70
World 105,431,984 100 World 13.9 World 7,605,363 100
(Source: FAO, 2005)

During the last four decades, global citrus production showed a period of

sustained growth, primarily due to expansion of cultivation (Figure 2.1). Over the same

period, the world citrus production increased more than four fold from 24,999,430 Mt to

105,431,984 Mt, growing at an average annual rate of 1.5 % (Figure 2.1). The rate of

growth could have been higher, were it not for the occurrence of freezes in Florida in the

1980s. Both bearing tree numbers and production declined by 40% between 1975 and

1986 as freezes destroyed a large portion of the industry in Lake, Orange, and Pasco










counties of the state of Florida (Spreen, et al. 2006). However, the increase in prices

caused by the slowed production in Florida stimulated the development of new plantings

(Spreen et al.). Given the lag between price signals and output changes, an increase in

production occurred in the 1990s and 2000s (Figure 2.1).

Until the early 1980s during which freezes devastated the Florida citrus

production, the U.S. was the world's largest producer of citrus. During the decade of the

1980s, Brazil became the largest citrus producer in the world and the first, and almost

exclusive, orange juice exporting country (UNCTAD). Brazil's citrus production grew at

an average rate of 4.5% over the last four decades while that of the U.S. grew at 0.6%.
< ... 7 ." .., :r ..,r .: .., ~." .., .: .., ~."

2 ,000,0 00- world
,, ---- Brazil
10o,O ,O0 ---- China
"*t- Mexico
: *,.: .. -....--- U.S.
80,000,000


< 60',OO( O.-. /-









S / 1961 1965 190 1973 977.1981 1.985,119 19.93A997 2001 .2405 /

Figure 2.1 Citrus productions (MT) of major producers, 1961-2005

Over the last few years, the Chinese citrus production experienced a fast growth

(over 3%) over the last few decades (particularly in the 1990s) mainly due to the

expansion of cultivation, thus emerging as the second largest producer of citrus fruits in

the early 2000s (Figure 2.1).
the early 2000s (Figure 2.1).










The Production of Oranges, Lemons and Limes, and Grapefruits and Pomelos

Oranges. The major citrus fruits are oranges, lemons and limes, and grapefruit

and pommels, whose combined production accounted for 55% of the world's total citrus

in 2005 (FAO, 2005). Among citrus fruits, orange is the most important fruit, accounting

for about 43 percent of the world's citrus production in 2005. The world's largest

producers of oranges are Brazil and U.S, whose combined production in 2005 was 44%

of the world's total orange production with Brazil alone accounting for 30% of the world

production. The U.S. produced 14 percent of the world production in 2005 (Table 2.2).

The top ten countries produced 76 percent of the world production in 2005.

Table 2.2 Global production of oranges, grapefruit and pommels, and lemons and limes
in 2005
Oranges I Grapefruit and Pommels I Lemons & Limes
Country Production % Country production % country production %
Metric tons
Brazil 17,804,600 30 U.S. 914,440 25 Mexico 1,824,890 15
U.S. 8,266,270 14 China 443,000 12 India 1,420,000 11
Mexico 3,969,810 7 Mexico 257,711 7 Argentina 1,300,000 10
India 3,100,000 5 Israel 250,000 7 Iran 1,100,000 9
Italy 2,533,535 4 Cuba 226,000 6 Brazil 1,000,000 8
China 2,412,000 4 S. Africa 212,348 6 U.S. 745,500 6
Spain 2,149,900 4 Argentina 170,000 5 Spain 734,300 6
Iran 1,900,,000 3 Turkey 150,000 4 China 634,500 5
Egypt 1,789,000 3 India 142,000 4 Italy 609,435 5
Indonesia 1,311,703 2 Tunisia 72,000 2 Turkey 600,000 5
Total 45,236,818 76 Total 2,837,499 77 Total 9,968,625 79
World 59,858,474 100 World 3,667,862 100 World 12,554,879 100

(Source: FAO, 2005)

From 1961 to 2005, global orange production increased almost four fold from

15,946,492 Mt to 59,858,474 Mt, growing at an average annual rate of 1.4 % (FAO.

2005). Most of the growth was accounted for by developing countries, primarily in South

America but also in Asia and to a lesser extent in Africa. In South America, the volume

of production expanded considerably in Brazil and Mexico (Figure 2.2). In Asia,

production expanded significantly in China, India and Pakistan and Iran. Orange










production in China, Brazil and Mexico increased at an average annual rate of 4.3%,

2.7% and 1.4%, respectively over the same period (FAO, 2005). Spreen and Brown

(1995) noted that freezes in Florida in the 1980s provided a major impetus to the

expansion of orange production in Brazil. The average orange production of Brazil and

Mexico in the 1990s was 50 percent and 60 percent larger than the average production in

the 1980s, respectively (FAO, 2005).

Brazil
-- China
--- Mexico
SU.S.

















Figure 2.2 Orange productions (MT) of major producers, 1961-2005

Lemons and limes. Lemons and limes are the second most important citrus crops

accounting for about 9 percent of the global citrus production in 2005. Like the case with

oranges, there has been a significant increase in production of lemons and limes through

expansion of cultivation. Over the last four decades, the global lemon and lime

production increased more than five fold from 2,625,865 MT in 1961 to 12,554,879MTt

in 2005, growing at the average rate of 1.6% per annum (FAO, 2005). Most of the

growth was accounted for by Mexico, India and Argentina (Figure 2.3).











2,000,000- Argentina
-m- India
1,800,000 Mexco
1,600,000- -o-- U.S.
1,400,000-

1,200,000-

1,000,000
800,000-

600,000-

400,000 -
200,000


1961 1966 1971 1976 1981 1986 1991 1996 2001

Figure 2.3 Lemon and lime production (MT) of the top four producers, 1961-2005

The world's largest producers of lemons and limes are Mexico, India and

Argentina whose production in 2005 was 15%, 11% and 10% of the world production,

respectively. Other major producers of lemons and limes include Spain, China, Italy and

Turkey, each accounting for about 5 percent of the world's total in 2005 (Table 2.2). The

top ten countries produced about 80 percent of the world's total in 2005.

Until the mid-1980s, the U.S. was the world's largest producer of lemons and

limes (Figure 2.3). Between the mid-1980s and mid-1990s, the U.S. production slowed

while that of Mexico continued to rise particularly in the mid-1990s during which it

emerged to be the world's largest producer of lemons and limes. Over the last four

decades, Mexico's production grew at an average annual rate of 2.3% while that of U.S.

grew at 0.4%. In 2005, U.S. produced 6% of the world's total, which is way below the

production of Mexico, India, Argentina, Iran and Brazil (Table 2.2). Over the same

period, India and Argentina also increased their production and emerged as the second










and third largest producers of lemons and limes, respectively (Table 2.2). India and

Argentina increased their production at an average annual rate of 1.4 and 2.8%,

respectively.

Grapefruit and pommels. Grapefruit and pommels are the third most important

citrus crops, accounting for about 3.5% of the world citrus production. Over the last four

decades, the global grapefruit and pommels production increased by 73% from 2,120,896

MT in 1961 to 3,667,862 MT in 2005, growing at average rate of 0.8% per annum

(Figure 2.4).



3,000,000 --- China
-- U. S.
2,500,000

2,000,000

1,500,000

1,000,000

500,000-



1961 1966 1971 1976 1981 1986 1991 1996 2001

Figure 2.4 Grapefruit and pomelos production (MT) in the U.S. and China, 1961-2005

The growth rate of grapefruit and pomelos production over the last four decades

was modest compared to the growth rate of other citrus fruits. This is due to the slow

growth of grapefruit production in the U.S. On average, grapefruit and pomelos

production in the U.S. grew at 0.2% per annum. Over the same period, China's

production grew at a 3.8%.










U.S. is the world's largest producer with 25% of the world's total (Table 2.2).

China is the second largest producer with 12 percent of the world's total. Mexico and

Israel are also important producers, each producing about 7% of the world's total. The

top ten countries produced 77 percent of the world production in 2005 (Table 2.2).

The Production of Grapes, Apples, and Pineapples

Grapes. Among non-citrus fruits, grapes are the most important non-citrus fruit in

terms of production. The maj or producers of grapes are Italy, France and the U.S. whose

production in 2005 accounted for 14%, 10% and 10%, respectively (Table 2.3). China

and Spain are also important producers of grapes, each accounting for about 9 percent.

The top ten countries produced about 71 percent of the world's total in 2005.

Table 2.3 Global production of apples, grapes, and pineapples, 2005
Apples Grapes Pineapples
Country production % Country production % Country production %
Metric tons
China 25,006,500 39 Italy 9,256,814 14 Thailand 2,050,000 13
U.S. 4,254,290 7 France 6,787,000 10 Philippine 1,800,000 11
Turkey 2,550,000 4 U.S. 6,414,610 10 China 1,460,000 9
Iran 2,400,000 4 Spain 5,879,800 9 Brazil 1,418,420 9
Italy 2,194,875 3 China 5,698,000 9 India 1,300,000 8
France 2,123,000 3 Turkey 3,650,000 5 Nigeria 889,000 6
Poland 2,050,000 3 Iran 2,800,000 4 C. Rica 725,224 5
Russia 2,050,000 3 Argentina 2,365,000 4 Mexico 720,900 5
Germany 1,600,000 3 Chile 2,250,000 3 Indonesia 673,065 4
India 1,470,000 2 Australia 1,834,000 3 Kenya 600,000 4
Total 45,698,665 72 Total 46,935,224 71 Total 11,636,609 73
World 63,488,907 100 World 66,533,393 100 World 15,886,647 10
0
(Source: FAO, 2005)

The production of grapes in the U.S. has been growing steadily, while that in Italy

and France appears to be declining since the mid-1990s (Figure 2.5). Unlike the case

with citrus fruits, the increase in global grape production is modest. It increased by a

little more than 50% over the last four decades, growing at an average rate of 0.2% per

annum (FAO, 2005). This is due to the decline of production in the two major producing







17


countries (France and Italy) whose production declined at an average rate of 0.4% and

0.2%, respectively.


14,000,00 --- France
t- Italy

12,000,000 U.S.


10,000,000-
8,ox,oo@.

8,000,01PT


6,000,000 -


-4,000,000 -


2,000,000



.- ,D- t-- t( -- t-- 0 00 oo '0 -- -
i- o O- O-i ; (- (^ (- 0- 0 ;0
S*CD CD

Figure 2.5 Grape productions (MT) of the top three countries, 1961-2005

Apples. Apples are the second most important non-citrus fruits. Over the last

four decades, the world apple production increased nearly four fold from 17,053,651 MT

in 1961 to 63,488,907 MT in 2005, growing at an average rate of 1.2% per annum. The

world's largest producers of apples are China and the U.S. China produced 39% of the

world's total in 2005. U.S. production accounts for 7% of the world's total (Table 2.3).

Until the early 1990, the U.S. was the largest producer of apples (Figure 2.6).

Since then, China has become the world's largest producer of apples. On average,

China's apple production grew at the rate of 4.7% per annum while that of the U.S grew

at 0.7% per annum over the last four decades. The growth of apple production in China is

explained by an increase in area expansion.










30,000,000 China

U. S.
25,000,00.0

20,000,000

15,000,000

10,000,000

5,000,000

0g
1961 1966 1971 1976 1981 1986 1991 1996 2001

Figure 2.6 Apple productions (MT) in the U.S. and China

Pineapples. Pineapples are the third most important non-citrus fruit. Over the last

four decades, the global pineapple production increased almost four fold from 3,831,437

MT to 15,886,647 MT at an average rate of 1.4% per annum. Until the early 1980s, U.S.

was the world's largest producer of pineapples (Figure 2.7). Since then, its production

has declined so that it is not in the list of the top 10 producing countries (Table 2.3).

Over the last four decades, the U.S. production declined at an annual rate of 1.3

percent per annum (FAO, 2005). Currently, the world's largest producers of pineapple

are Thailand, and the Philippines, accounting for 13% and 11% of the world's total,

respectively (Table 2.3). They increased their production over the last four decades at

2.8% and 2.5% per annum, respectively. China and Brazil have also emerged as the third

and fourth largest producers, each producing about 9% of the world's total. The top ten

countries produced 73 percent of the world's total in 2005.











4,000,000 --- Brazil
China
3,500,000 --- Philippines

3,000,000 ---- Thailand
--(-- U. S.
2,500,000

2,000,000

1,500,000

1,000,000

500,000
0-
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005

Figure 2.7 Pineapple productions (MT) of major producers, 1961-2005

Global Fruit Trade

International trade in fruits and vegetables has expanded more rapidly than trade

in other agricultural commodities, especially since the 1980s (Huang, 2004). This is

attributed to rising incomes, falling transportation costs, improved technology, and

evolving international agreements. Citrus fruits rank first in international fruit trade in

terms of value (UNCTAD). As a result of trade liberalization and technological advances

in fruit transport and storage, the citrus fruit industry is becoming more global in scope.

The major players in the global trade of fruits and vegetables are the E.U, the North

American Free Trade Agreement (NAFTA) countries, China and Japan.

Exports of fresh citrus fruits represent roughly 10% of total citrus fruit production

(UNCTAD). The international trade on fruits and vegetables is dominated by processed

forms. According to UNCTAD, international trade in citrus juice only started to increase

in the 1940s, after World War II, when citrus processing technologies were invented and

developed. The advent of frozen concentrated orange juice (FCOJ) after World War II









provided a new impetus for the citrus industry (Spreen et al. 2006). Citrus fruit

processing accounts for approximately one third of total citrus fruit production. More

than 80% of it is orange processing, mostly for orange juice production. The major

feature of the world market for orange juice is the geographical concentration of

production. There are only two main players: the State of Florida in the U.S. and the

State of Sao Paulo in Brazil. Production of orange juice between these two players

account for over 80% of world orange juice production (Spreen et al. 2006).

The major difference between them is that Brazil exports 99 percent of its production

while 90 percent of Florida's production is consumed domestically and only 10 percent is

exported (UNCTAD). The citrus industry in Florida currently faces two major

challenges (citrus canker and citrus greening) and increasing urbanization in the state,

which has resulted in increasing land values (Spreen et al. 2006). Nonetheless, the

Florida citrus industry will continue to be an important supplier of citrus products to both

the U.S. and world market.

International trade in orange juice takes place in the form of frozen concentrated

orange juice (FCOJ), in order to reduce the volume used, so that storage and

transportation costs are lower. Spreen et al. (2006) notes that FCOJ provided a means to

(1) store orange juice from the harvest season into other time periods, (2) provided a way

to produce a product with a consistent taste, and (3) offered new modes of transport and

new retail package alternatives to the consumer.

The E.U. is the largest importer of orange juice, accounting for over 80% of the

world orange juice imports (UNCTAD). The other major importers of orange juice are

Canada and Japan. Most of imports by the E.U. and Japan come from Brazil. Brazil's









exports of orange juice to Japan account for over 70% of Japan's total import of orange

juice (Table 2.4). In North America, the U.S. and Canada consume orange juice mainly

from Florida, while a small quantity of imports comes from Brazil. The U.S. is the

leading exporter of apple juice, grapefruit juice and grape juice to Japan. Thailand and

Israel are the leading exporters of pineapple juice and other citrus, respectively. The U.S.

share of grapefruit import is significant. However, the slow growth rate of grapefruit

production in U.S. implies that the U.S. is unlikely to continue as a dominant supplier of

grapefruit juice. The same is true with apple juice since the apple production growth rate

in U.S. is slower relative to other countries such as China. Currently, the U.S. is a

dominant supplier of apple juice to the Japanese market, followed by China and Austria.

With regard to grape juice, the U.S. is still the dominant supplier and is expected to

dominant the market since its production has been growing while that of France and Italy,

which are the world's largest producers, has been declining.

Global Fruit Consumption

Higher income, urbanization, demographic shifts, improved transportation, and

consumer perceptions regarding quality and safety are changing global food consumption

patterns (Huang, 2004). Diet diversification and increasing demand for better quality

products have increased imports of high-value and processed food products in developed

countries. Fruits are mainly consumed in industrialized countries, not only because

consumers in these countries have high income levels but also because they have

increasing concerns about healthy eating. However, the growth of per capital

consumption of fruits in these countries seems to be stagnating. Over the period 1980 to

2003, the per capital consumption of citrus fruits (oranges, grapefruit and lemons and

limes) in these countries grew at an average rate of one percent per annum.









Table 2.4 Fruit juice imports to Japan by country of origin
product Exporter %
Orange juice Brazil 72.4
U.S. 23.7
Australia 1.4
Apple juice U.S. 22.4
China 18.9
Austria 18.6
Grapefruit juice U.S. 87.1
Israel 9.6
Australia 2.4
Grape juice U.S. 46.9
Brazil 14.1
Argentina 11.7
Pineapple juice Thailand 42.4
USA 28.6
The Philippines 27.6
Other citrus juice Israel 40.5
Italy 21.8
Argentina 13.9
(JETRO)

Among 26 industrialized countries, the U.S. and Canada are the largest consumers

of orange and mandarins followed by the EU. In fact, some E.U. countries such as

Ireland, the Netherlands and Greece consume more oranges than do the U.S. and Canada

on a per capital basis. The average per capital consumption of oranges and Mandarins in

industrialized countries over the period 1990 to 2003 is 29 kilograms while that of

grapefruit and lemons and limes is 3.0 and 3.6 kilograms, respectively (Table 2.5).

Japan's consumption of both citrus (except grapefruit) and non-citrus fruits is small

compared to other industrialized countries. The average annual per capital consumption

of oranges and apples in Japan over the period 1980 to 2003 is about 14 and 12 kilograms,

respectively, while those of grapes and grapefruit are 2.8 and 2.5 kilograms, respectively

(Table 2.5).









Table 2.5 Per capital consumption of fruits in industrialized and developing countries
Developing Industrialized
Fruits countries Countries E.U. Canada Japan U.S.
Orange and mandarins 8.00 29.23 27.52 46.28 13.80 39.87
Grapefruit 0.32 2.91 2.17 4.05 2.49 4.12
Lemons and limes 1.25 3.59 3.78 2.60 0.84 5.26
Apples 4.67 20.3 24.82 18.82 11.58 21.02
Grapes 2.20 7.60 8.67 10.19 2.79 8.18
Pineapples 2.01 3.61 1.97 2.61 1.43 7.01
(Source: FAO, 2005)

Japan's domestic supply of pineapples is heavily dependent on imports. In 2003,

95% of the domestic supply of pineapples came from imports (FAO, 2005). Japan is also

heavily dependent on imports for its supply of lemons and limes. In terms of apples and

grapes, the significance of imports has been increasing since the last decade during which

the deregulation was in effect.














CHAPTER 3
THEORETICAL MODELS

Demand Approaches

Approaches common in the literature of import demand analysis involve use of

consumer demand theory and production theory. The consumer demand approach treats

imports as final products that directly enter a consumer's utility function (Schmitz, A.

and Seale, J. 2002) while the production theory treats imports as inputs (Washington and

Kilmer, 2002). The first approach enables the derivation of the traditional consumer

demand and labor supply functions from utility maximization, while the second approach

enables the derivation of derived/input demand and output supply functions from profit

maximization or cost minimization.

The fact that output supply functions are derived in the production approach while

labor supply functions are derived in the consumer demand approach marks one major

difference between the two approaches. Another major difference between the two

approaches is that the parameter estimates of unconditional consumer demand and

unconditional input demand are different. However, similar parameter estimates can be

obtained for the conditional consumer demand and derived demand for inputs.

Furthermore, under the assumption of the constant percentage of retail price type of

marketing margin, the demand for any given quantity of product is equally elastic (or

inelastic) with respect to price at all market levels (Goodwin, 1994). This implies that

conflicts of interest between the producer level and subsequent market levels are reduced.

The constant percentage of retail price marketing margin is fairly typical for products for









which the marketing process involves fixed investments and substantial economies of

scale (Goodwin, 1994, pp. 292).

Production Approach

In the production approach, two allocation decisions, one involving outputs and

another involving inputs, are made. These two decisions can be made successively or

simultaneously through a two-step profit maximization or one-step or direct profit

maximization procedure yielding a system of output supply and input demand functions

(Washington, 2000). They are made successively in such a way that given output and

input prices, first the output manager decides on the quantity of output, and knowing the

quantity of output planned to be produced, the input manger decides on the quantity of

inputs required to produce the planned output. The simultaneous decisions are made by

one manager such that the input and output decisions are not independent of each other.

In this case, since the input demand and output supply functions are not independent of

each other and that their error terms are correlated (Laitinen, 1980), the input demand

function can not be estimated independently of the output supply function and vice versa.

Once the output supply and conditional input demand are estimated, the unconditional

demand parameters can be derived from the parameter estimates of the two functions

(Washington and Kilmer, 2002).

The input allocation decisions that involve the use of conditional input demand

functions can be implemented in stages/hierarchies (Theil, 1980b). That is, total

expenditure is first allocated over broader groups of inputs and then group expenditures

are allocated over individual inputs within each group. The two-stage input allocation

decision of the production approach is comparable to the two-stage utility maximization

of consumer demand approach (Figure 3.2). The consumer demand approach can yield a









system of group consumer demand and conditional demand functions from which the

parameter estimates of the unconditional demand function can be derived. As noted

earlier, the unconditional demand parameters thus estimated are not the same as those

derived from the system of output supply and conditional demand functions generated in

the production approach discussed earlier.

However, the parameter estimates of the input demand function (P ), group

demand function (P2) and conditional input demand (P3) in Figure 3.1 are the same as

that of the corresponding functions in Figure 3.2. That is, the parameter estimates of the

input demand function (P ) are the same as that of the unconditional consumer demand

(Cl); the parameter estimates of the group input demand functions (P2) are the same as

that of the group consumer demand functions (C2); and that the parameter estimates of

the conditional input demand functions (P3) conditional consumer demand functions (C3)

in Figure 3.2.

2-Stage profit maximization




Output supply function Input demand function
(P 1)

-I

Group input demand function Conditional input demand
(P2) function (P3)


Figure 3.1 A two stage profit maximization
























Figure 3.2 A two-stage utility maximization

Although the two approaches provide the same empirical estimates with regard to

the conditional demand, and that the demand for any given quantity of product is equally

elastic (or inelastic) with respect to price at all market levels under the assumption of the

constant percentage of retail price type of marketing margin (Goodwin, 1994), the

production approach does not seem to lend itself to a theoretically consistent

investigation of demand relationships among narrowly defined import products because

of their independence. It may be realistic for broadly defined groups of imported

products. For example, Theil (1980b) applied the production approach to broad imported

products such as food, crude materials, semi-manufactures, finished- manufactures under

the assumption of input independence. However, when it comes to narrowly-defined

products such as fruit juices, it does not seem conceptually defensible and practical to

apply the production approach simply because the importing firm's production function

of an imported fruit juice is independent of other imported juices.

Let the production function of a narrowly-defined import product such as orange

juice be given by









(3.1) h = h(hl(xl ),...,+hg (xgl ,.,+h, (xm))

where hg is a production function of each import product or input; xg is the import

product or input. The groups run from 1 tom ; the number of inputs in each group is only

one to indicate that each import is a unique input that produces a unique output; the

number of inputs in group g is n The total number of products isn, +...+ nm.

Equation (3.1) implies that the elasticity of output with respect to each input is

independent of all other inputs; hence, all cross effects are zero. Let h (.) represents the

production function of, say, Florida orange juice. This function does not have the orange

juices of other countries as inputs because each individual input yields its own unique

output. Hence, the constrained cost minimization procedure will not yield a demand

function that consists of the prices of other orange juices. As a result, theoretically we

can't investigate the relationship between Florida orange juice and other juices. The

presence of input independence in the production function precludes us from

investigating the substitution between imports of orange juice from different countries

and competition among exporting countries.

Consumer Demand Approach

The present study chooses the consumer approach over the production approach

since it allows investigating the nature of demand relationship among imported products

and competition among different exporters. Consumption theory is amenable to analyze

the market structure of commodities in fruit juice market. The theory involves the

analysis of the change in marginal utilities of a certain product due to a change in

consumption of a closely related product. The changes in marginal utilities are related to

the price substitution terms of demand functions.









Starting with a traditional utility function that is assumed to be well behaved

(twice differentiable, increasing in its arguments, strict concavity), we can derive the

Marshallian demand functions. They satisfy the properties of adding up, symmetry of the

cross price derivatives, homogeneous of degree zero in prices and expenditure, and

negative semi-definiteness in compensated price responses.

Utility Maximization

The maximization of a utility function u(q) subject to a budget constraint

m = p'q is set up in a constrained optimization problem using the Lagrange method as

(3.2). L(q,A)= u(q)+ A(m p'q)


where q is the vector of consumption products; A is the Lagrange multiplier which can

be interpreted as the marginal utility of income; m is total expenditure; p is the vector

of prices.

The first order conditions are


(3.2.1) L(q ) (q)- p = 0
9q

and


(3.2.2) mL(qA) p' q = 0 .


The first order conditions imply that the marginal rate of substitution should equal

the price ratio at the optimum, which in turn implies that the internal rate of trade should

equal the external or market rate of trade. That is, a consumer will adjust purchases of

products until their willingness to trade one for the other just matches the rate at which

they can be traded in the marketplace, as given by the ratio of prices.









From the first order conditions, we derive the demand functions for all products i

and the marginal utility of income function as

(3.3) q, = f (m,p)


and

(3.4) A= A(m,p).


The choice of a functional form is at the interface of economic theory and the data.

In other words, the functional form should satisfy the economic proprieties and fit to a

statistical data satisfactorily. Two steps are followed in demand specification (Fousekis

and Revell, 2000). First, behavioral assumptions are imposed which lead to a cost or to

an indirect utility function. Second, a functional form is selected. Parsimony and

flexibility are desirable properties considered in the selection of functional forms.

The most common and parsimonious demand model, which dominated the import

demand literature in the past, was the Armington trade model. The application of the

Armington model to trade data dates back to the late 1970s and became popular in the

1980s and 1990s (Grennes et al. 1977, Sarris, 1981; Sarris, 1983; Abbot and Paarberg,

1986; Babula, 1987; Alston et al. 1990; Duffy et al. 1990; Haniotis, 1990). However,

the Armington trade model came to be increasingly criticized on both conceptual and

empirical grounds. The hypothesis of separability and homotheticity may not be

supported by import data (Alston, et al. 1990). Traditional methods of implementing the

Armington trade model result in theoretically and statistically inconsistent parameter

estimates (Davis and Kruse, 1993).

Consequently, system-wide demand models such as the Rotterdam model and the

Almost Ideal Demand Systems have come to be popular in the contemporary import









demand literature (Clements and Theil, 1978, Lee et al. 1990; Seale et al. 1992; Zhang et

al. 1994; Yang and Koo, 1994; Schmitz and Wahl, 1998; Fabiosa and Ukhova, 2000;

Soshnin et al. 1999; Schmitz and Seale, 2002; Washington and Kilmer, 2002).

The choice among different system-wide demand specifications (e.g., the

Rotterdam model versus AIDS model) is based on statistical tests (Brown et al. 1994).

Economic theory does not suggest a criterion to choose ex ante between demand models.

Barten (1993) demonstrates that the Rotterdam and AIDS models are special cases of a

general demand model so that nested tests can be applied to choose either the Rotterdam

or AIDS model or the hybrid of these two models (Central Statistical Bureau (CBS) and

National Bureau of Research (NBR)).

In the field of consumer demand analysis, the issue of selecting among competing

functional forms has been addressed in a number of recent studies (Eales et al. 1997; Lee

et al. 1994, Barten; 1993.; Schmitz and Seale, 2002; Weatherspoon and Seale, 1995).

They have demonstrated that a family of competing systems can be generated through

alternative parameterizations of Theil's differential system (Theil 1980).

However, separability is an issue in estimating system-wide models (Seale, 1996).

The AIDS model is not globally separable and only becomes separable locally under

stringent conditions (Lee et al. 1994). This will render multi-stage demand estimation

difficult. However, it is not uncommon to find the application of the AIDS model in a

two-stage budgeting framework (Heien and Pick, 1991; Soshnin, et al. 1999). In these

two studies, the AIDS model was used for both the first and second stages. Other studies

have specified a two-stage demand system by applying the LES model for the first stage

and the AIDS model for the second stage (Fan, et al. 1995; Han and Wahl, 1998;









Michalek and Keyzer, 1992; Ma and Rae, 2003). Gao et al. (1996) specified a two-stage

demand by applying the extension of the AIDS model for the first stage and Generalized

Linear Expenditure System for the second stage.

The Rotterdam model, which is globally separable, has been applied in several

studies to specify a two-stage demand system. These include Duffy (1986); Clements

and Johnson (1983), Clements and Selvanathan (1988), Brown and Lee (1997), Xao et al.

(1998); E. Selvanathan and A- Selvanatha (2004). All of these studies have used the

Rotterdam model for both the first and second stage in a block independent framework

for different applications, mostly of advertising.

The present study prefers to use the Rotterdam model because of its global

separability. Unlike the previous studies which have applied the Rotterdam model, the

present study tests different separability hypotheses. The hypotheses will be discussed in

the next sections.

The Rotterdam Model

Following Theil (1980a, 1980b), the Rotterdam model is derived from the

maximization of a general utility function or total differentiation of a general demand

function.

Totally differentiating (3.3) yields


(3.5) dq, = dm + lp,.
am J-\ P j

Expressing (3.5) in log form (dlog q, = dq /q, ) yields


(3.6) q,d(logq)= a (m)d(logm)+ i q d(logp)
am J1,l









where d(log q, )is the log change in quantity demanded of product i and d(log p ) is the

log change in price of product j.


Based on Barten's Fundamental matrix, the total substitution effects cq, in


(3.6) can be decomposed into specific and general substitution terms as

(37) aq, Au A aq, aqj aq,
(3.7) =- Au q
pj aA/m am am am

where u' is the (i, j)h element of U 1 the inverse of the Hessian; Au' is the specific

substitution effect, which shows that the corresponding component depends upon the

specific relation, in terms of u' between i and j. In other words, the utility obtained

a aq, aqqj
from product i is a function of the consumption level of products ; is
OA/ I m am 9m

the general substitution effect, which shows that all products are competing for the

q,
consumer's budget, and q, is the income effect of the price change dp on the
am

demand for the ith product. Therefore, the total substitution effect of a price change can


be expressed as the sum of the substitution effect A' and income
9A/m am am m


effect -am q and is known as the Slutsky equation. The component Au of


aq, /ap@ is the effect on q, of a change in pj when the change is accompanied by an

income change so that the marginal utility of income remains unchanged.









Substituting (3.7) into (3.6) and multiplying both sides by p, /m, we find


w,(dlogq,)=p, q' d(logm)+
am
(3.8) N Ppp A aq, aq, aq,

n- m 1 M aAamm amam m

where w, is the expenditure share of product i defined as w, = p q
m
Multiplying out the second terms of the right-hand expression of (3.8) yields

w,(dlogq)= p (dlogm)+ -pup jP (logpj)
(3.9)m
j A _-q, q- "d(log pj) -N a" q d(logp).
am AI am ahn m m m a J


The first term of the right-hand side expression of (3.9) is the marginal value

share defined as

cq,
(3.9.1) 0, =p,-
dm

The second term of the right-hand side expression of (3.9) is the relative price

coefficient v, defined as


(3.9.2) v A = p p, p.
m

The third terms of the right hand-side expression of (3.9) can be rearranged to


yield the general substitution effect as









Np,p, A Sq, aq, Zq, A am' a /q
a a d(log pj ppj p lo p
( ) m A/1am am d m Sm m Am Jm
(3.9.3)
N
O= 00j d(log p)
J-1


where m = q, which is the reciprocal of the income elasticity of the marginal


utility of income A .

The fourth terms of the right hand-side expression of (3.9) can be rearranged to

yield the income effect of a price change as

(3.9.4) P q, d(log )p (logp ) = 0, w dlogp).
I gm dm ma m m

Substituting (3.9.1) through (3.9.4) and rearranging them yields

(3.10) wd(logq,)= d(logm)- w jd(logq) + vd(log p)- 0, d(logp) .
J =1 ) J=1 J-=1

Rearranging (3.10) and using the constraint that the sum of the relative price

N
coefficients is proportional to the marginal value share Y v, = 00,, we find the relative
J-1

price version of the Rotterdam model (3.11) and the absolute price version of the

Rotterdam model (3.12) as

(3.11) w,d(logq,)= Od(logQ)+ vd logP .
N

(3.12) w,d(logq,)=O,d(logQ)+ r d (log p).
J-1

where d(log Q) = d(logm)- w d(logq,)\ is the real income term; r-, = v, 0,0j


are the Slutsky price coefficients; (logP) = ,d(og p,) is the Frisch price index.
J-1









In order to identify the market structure underlying the importation of fruit juices

into Japan, four different versions of the Rotterdam model are derived from the relative

price version of the Rotterdam Model under different hypotheses. The hypotheses which

represent different market structures are block independence, block-wise dependence,

and uniform substitutes. The block independence and block-wise dependence hypotheses

are applied to products that belong to different product groups while the uniform

hypothesis is applied to products within the same product group.

The models derived under these hypotheses in this study are block independent

non-uniform substitute-Rotterdam model, block independent uniform-substitute-

Rotterdam model, block-wise dependent non-uniform substitute-Rotterdam model and

block-wise dependent uniform substitute-Rotterdam model.

Block Independence

Block independence is a special case of strong separability where one can group

commodities into different blocks depending on some tangible criterion. Separability is a

relative concept whose frame of reference is some partition of a product set into mutually

exclusive and exhaustive subsets. Blundell and Robin (2000) indicate that the idea

behind separability in consumer preferences is the existence of "natural" groupings of

related commodities that reflect the budgeting decisions consistent with the true

preference ordering of the representative consumer. Otherwise, empirical estimates of

structural demand parameters are invalid. The usefulness of separability depends on the

ability to classify products into groups which are empirically valid (Barten, 1977).

The grouping of commodities into blocks is of paramount significance from a

statistical point of view since it increases the degrees of freedom. However, the blocking






37

has to be theoretically consistent and empirically plausible. Suppose that we have

G < N blocks or groups denoted as S,,..., SG such that each product belongs to exactly

one group, the consumer's preferences under block independence is represented by the

sum of G sub-utility functions, each involving the quantities of only one group given as

(3.13) u= u u(q ,...,qn ,...,+ug(qg,...,qg ,...,+um(q i,...,q n))


where ug is a sub-utility function; qg is a sub-vector of q which consists of the q, s that

fall underSg(g = 1,...,G). The groups run from 1 tom; the number of commodities in

group 1 is n,; the number of commodities in group g is ng. The total number of products

is n, +...+ -m.


Under (3.13), the utility obtained from the products in group g is independent of

02u
the utility of products in group h. That is = 0. However, for i and j in the same
aq,8qj

02u
group 0 That is, the consumption of an extra unit of product j has an effect
Oq,Oqj

on the utility of product i and vice versa.

Formally, the hypothesis of block independence (H0) states that the change in the

marginal utility of a dollar spent on the ith product (i e Sg )caused by an extra dollar

spent on the jth product which belongs to a different group (j e Sh, g # h) equals zero.

The alternative hypothesis states that the change in the marginal utility of a dollar spent

on the ith product (i G Sg )caused by an extra dollar spent on the jth product which

belongs to a different group (j e Sh,g g h) is different from zero.









d2H
Ho : 2,q q = O for i Sg and jeSh; g h,


82U
HA: T( 0 Ofori Sg and j Sh; g h.


Under this hypothesis, the Hessian (2 u/aq, 9q, )and its inverse (2 u/aq, qj )l

becomes a block diagonal. The marginal utility of each product depends only on the

quantities consumed of the products that belong to the same group (Theil, 1975).

Following Theil (1975), the changes in the marginal utilities can be related to


demand parameters as v, = Ap,u'p, where v, are the relative price coefficients. When
m

i and j belong to different product groups, v0 can be set equal to zero because u'

equals zero under the assumption of block independence.

This implies that the assumption of block independence represents a market

structure whereby the change in the relative price of a product in one product group does

not affect the demand for another product in another product group. For instance, under

this market structure, we are hypothesizing that the change in the price of U.S. grapefruit

juice does not affect the demand for Brazilian orange juice. Orange juice and grapefruit

juices are in different product groups.

Block independent non-uniform substitute-Rotterdam Model. Following

Theil (1980a), the block independent non-uniform substitute-Rotterdam model can be

derived from (3.11) by setting v, equal to zero for i and j that belong to different groups

as


(3.14) w,d(log q,)=O,d(logQ)+ _vd log .
JE-S I 'P









Since all v, with i and j in different groups vanished, the number of free

parameters is obviously reduced. However, no product is a specific substitute or

complement of any product that belongs to a different group. The demand equation of

the ith product contains Ng relative prices when it belongs to set S. The number of free

parameters depends on the number of blocks and the number of commodities in each

block. Theil (1980) shows that with G blocks having N commodities in total and an

equal number of commodities in each block, the number of free parameters is

0.5N(1+ N/G).

Block-wise Dependence

In the previous section, we have assumed that the consumer's utility function can

be additively separated into group utility functions. A weaker assumption is that the

consumer utility function u(q) equals some functions( ) rather than the sum of the

group utility functions.

(3.15) u = uu (q ,...,q ...,u (qG ,...,q g M., (q ,..., q )

Unlike the case with (3.13), the utility obtained from a product in one group under

(3.15) is not independent of the consumption of another product in another group. That is,

a2u
for i and j in different groups, -- + 0. Since we are dealing with products in each
9q, 9qj

group on a block-wise basis, we are assuming that the effect of the consumption of an

extra unit of product j j Sh ) on the marginal utility of product i (i e S; g # h) is the

same for all pairs of products in the two product groups; i.e., this effect is independent of

i and j.








Formally, the hypothesis of block-wise dependence (Ho) states that the change in

marginal utility of a dollar spent on the ith product (i e Sg)caused by an extra dollar

spent on the jth product which belongs to a different group (j e Sh, g # h) equals some

constantagh; i.e., this effect is independent of i and j and hence, the same for all pairs

of products in the two product groups. For instance, in the orange and apple juice groups,

an extra dollar spent on either U.S. orange juice or Brazilian orange juice in the orange

juice group has the same effect on the marginal utility of a dollar spent on Chinese apple

juice or Austrian apple juice in the apple juice group. The utility interaction of two

products of different groups in a block-wise dependence framework is a matter of the

groups rather than the individual products (Theil, 1980a).

H,: 2 O(p q, )(pJ qJ)= agh for all i e g,j e h(g f h).


HA: B2 u/(p, q, )(p J q a g for all i e g, j e h(g h) .

Following Theil (1975), the changes in marginal utilities can be related to the

relative price coefficients (vy ) as

OM 2Un CU g 2 h M 02U A A
(3.16) v' =qAOm 2 Ug 'uh m a2u A A
A u, a uh g0({p,q,) Oqj )=A h C'u/IUg */iuh'

where i Sg; je Sh; and g h.

Equation (3.16) shows that the cross-group term is the same for all pairs of

products from different groups. Following Theil (1975) and Brown (1993), the relative

price coefficients corresponding to (3.16) can be given as

(3.17) v, = gh gh, O









where vY is the relative price coefficient; ~gh is a factor of proportionality which is the

same for all i e Sg andj e Sh ; 0, is the marginal expenditure share.

This implies that the assumption of block-wise dependence represents a market

structure whereby the change in the price of a product in one group would affect the

demand for another product in another product group in the same fashion. In other words,

the effect of a change in the price of a product in group A on the demand for another

product in group B is the same for all pairs of products in the two groups. For instance,

under this market structure, we are hypothesizing that the effect of a change in the price

of U.S. orange juice on the demand for Israelis grapefruit juice is the same as that of

Brazilian orange juice on the demand for U.S. grapefruit juice.

Block-wise dependent non-uniform substitute-Rotterdam model. Following

Theil (1980a), the block-wise dependent non-uniform substitute-Rotterdam model can be

derived from (3.11) as


(3.18) w,d(logq,)= O,d(logQ)+ s vjd log + 0, Vghd log P
P h3g P


where 6, is the marginal expenditure share; v, is the relative price coefficient,

which applies for the products within a group; 0, is the conditional marginal expenditure

share; Vgh is the group relative price coefficient defined as Vgh = Z v, where g h.
itg jth

Substituting equation (3.17) forv0 we can write the group price coefficient as


Vgh = -(~fghg where = Z6, and 0, = ZO are the 0, are the group marginal
leg ]jh


expenditure shares of group g and h, respectively.









Uniform Substitute Hypothesis

In the previous two sections, no restriction was imposed within the groups of

commodities, but weak separability prevails between groups. Now, we impose a testable

restriction (uniform hypothesis) on products within a given group. A group of closely-

related products are uniform substitutes when the cross effect of an additional dollar

spent on one product on the marginal utility of another dollar spent on another product is

the same for all pairs of products in the group (Brown, 1993). The uniform substitute

hypothesis was initially proposed by Theil (1980a) to deal with the demand for closely

related products such as different brands of a product. Since the same products that are

imported from different countries can be treated like different brands of the same product,

the application of this hypothesis to the same product differentiated by country of origin

is relevant. We consider this hypothesis given block independence and block-wise

dependence framework discussed earlier. In other words, we impose the uniform

substitute hypothesis on (3.14) and (3.18).

Uniform substitute given block independence

Suppose that we have a product group S, that consists of the same product

differentiated by country of origin of production. The consumer's preferences for a

uniform product given block independence can be represented by the sum of G sub-

utility functions, each involving the quantities of only one group given as

(3.19) u = uul(q ..., q ,...,+u, qg,...,qg ,...,+um(q ,..., qmn)


Under (3.19), the utility that a consumer obtains from the products in one group is

02U
independent of the utility of products in another group. That is, = 0 for i e Sg
aq,8q,









andj j Sh. However, for the ith and sth products in the same group, we are

hypothesizing that the marginal utility of a dollar spent on the ith product (i e S, )caused

by an extra dollar spent on the sth product which belongs to the same group (s e S ) is

the same because i and s are the same products differentiated by country of origin of

production.

Theil (1980a) writes the submatrix of the Hessian of the utility function 0 in

expenditure terms, multiplied by the scalar ..m/A as

011 k -.. k

[o1 _.nm 02U k 022 ... k
A L (pqj)O(pqj)
k k 0""

1
where all the off-diagonal elements(O' = -, i j) are equal to a positive constant k.


Since O.m/A is negative, this type of preference structure implies that the marginal utility

of a dollar spent on each product in Sg is affected negatively and by the same amount

kAI/.m when an additional dollar is on any other product in the group. Thus, all

products in S, are affected uniformly by the additional consumption of any other

products in the group.

Since we have between-group (block independence) in addition to the within

group restrictions (uniform substitute), we have two null hypotheses. The block

independence hypothesis has to do with the products between two product groups, and

the uniform substitute has to do with products within the same group. Note that the









uniform substitute hypothesis in this study is applied to the same product differentiated

by country of origin.

Formally, the null hypothesis of a uniform substitute relationship states that the

marginal utility of a dollar spent on the ith product (i e S, )caused by an extra dollar

spent on the sh product which belongs to the same group (s e Sg )equals some positive

constant k except when i = s, i.e., this effect is independent of i and s and hence, the

same for all pairs of products in the same group.

02U
Ho =k fori, sSg.

The block independence hypothesis states that the marginal utility of a dollar

spent on the ith product (i e g) caused by an extra dollar spent on the jh product which


belongs to a different group (j e h,g # h)equals zero.


H : 7 2 = 0 for i S and je Sh; g h.
0(qp, q, )n\P 4 nh

Combining the two null hypotheses corresponding to the uniform substitute and

block independence, the new null hypothesis which corresponds to the uniform substitute

hypothesis given block independence can be restated as


H = k fori, s S ,; = 0 for i S and j Sh;
0(Pq(pqpq, )gqj
g h.

HA .: k fori, s e Sp = 0 for i e Sg and

jESg; g h.

Theil (1980a) derives the relative price coefficients of a block independent

uniform substitute model as









f ,o((1-ko)
v =# --7=--I i--
1- kO,
(3.20) k-0j
v, = -0 I
vj lkO ij


where vj is the relative price coefficients; 0, is the marginal value share, k is a

constant; 0, is the group marginal value share; q is the income flexibility.

Block independent Uniform Substitute-Rotterdam Model. Substituting the

price substitution terms (3.20) in the block independent non-uniform substitute-

Rotterdam model (3.14), the block independent uniform substitute-Rotterdam model can

be derived as


(3.21) wd(logq,)= Od(logQ)+ 0(1-kO) d( logP + k d log '
1-k P) -k P


where 0, is the unconditional marginal value share; q is the income flexibility; k is a

constant; 0g is the group marginal value share;

Uniform substitute given block-wise dependence

The consumer's preferences for a uniform product given block-wise dependence

can be represented by consumer utility function u(q) equals some function f( ) rather

than the sum of the group utility functions.

(3.22) u =u(u(q,,...,q ),...,u(qG, ..,q ),Gn M(qM,...,q1 M)).

Under (3.24), the utility that a consumer obtains from the products in one group is

not independent of the utility of products in another group. That is, for ith and jth

82
products in two different groups, -- # 0. The consumption of product i has an
tq,9 qj









effect on that of product j and vice versa. For the ith and sth products in the same

82U
group, -- 0.
tq, Oq,

Since we have between-group (block-wise dependence) and within group

(uniform substitute) restrictions, we have two null hypotheses. The block-wise

dependence hypothesis has to do with the products between product groups, and the

uniform substitute has to with products within the same group.

Formally, the null hypothesis of a uniform substitute relationship states that the

marginal utility of a dollar spent on the ith product (i S )caused by an extra dollar

spent on the sth product which belongs to the same group (S e Sg )equals some constant

k, i.e., this effect is independent of i and s and hence, the same for all pairs of products

in the same group.

82U
Ho 2U (p,,=kfori,seS,;ig s.

The block-wise dependence hypothesis states that the marginal utility of a dollar

spent on the th product (i e Sg )caused by an extra dollar spent on the jth product which

belongs to a different group (j e Sh,g g h) equals some constantagh.

82u
H0* = pq,)(pj ( j agh for iSg and jiSh; gfh,


Combining the two null hypotheses corresponding to the uniform substitute and

block-wise dependence, the new null hypothesis which corresponds to the uniform

substitute hypothesis given block-wise dependence can be restated as









U2U 12U
HO: .=U =k fori, seSG 0U agh for i Sg and
S (Gq,)(pq) k f(orisJ
jeSh; g h,

02U 12U
HA (: .pq)(pqqj)#-kfor i,seSg ;p,, agh for i eS and j Sh;

g h.
Seale (2003) derives the relative price coefficients for a block-wise dependent

uniform substitute Rotterdam model as


S Ogg (1- kO,jgg)
1-kO,
(3.23) k

1 -kOg

where vj is the relative price coefficients; 0 is the income flexibility; 08 is the

conditional marginal value share, k is a constant; 9g is the group marginal value share.

Block-wise dependent Uniform Substitute-Rotterdam Model Substituting the

price substitution terms (3.23) in the block-wise-Rotterdam model (3.18), the block-wise

dependent uniform substitute-Rotterdam model can be derived as

I1 k-OI (p
wd(logq)=Od(logQ)+ 1- d logP + d logP +
(3.24) 1 -Sk,0 ) P IS1- P)
O,'I Vgh dlog Phj
h1g P )

The uniform substitute restriction results in a substantial reduction in the

parameter space and can be useful for obtaining more precise parameter estimates and

maintaining sufficient degrees of freedom (Brown, 1993).














CHAPTER 4
EMPIRICAL MODELS AND ESTIMATION PROCEDURES

Since the differential approach to consumption theory discussed in chapter 3 does

not postulate constancy for the coefficients of its demand equations, we are not entitled

yet to talk about empirical estimation. In this chapter, we discuss the ways in which the

theoretical models in chapter 3 are parameterized so that they can be applied to statistical

data. Since the nature of data forces us to work with finite rather than infinitesimal

changes, we replace the infinitesimal changes by finite changes. Furthermore, we

postulate that the coefficients are constant to make the models operational. Finally,

estimation procedures are presented for the different versions of the Rotterdam model.

Empirical Models

The Relative Price Version of the Rotterdam Model

Following Theil (1975), the relative price version of the Rotterdam model (3.11)

can be written in finite changes as



(4.1) ,dq,,t = 0dQ, + I v +
J-1 IdP,


where, = (Mw +w,,, 12)/2 is the average expenditure share ;dq, = log(q,,/q,, 1,) is the

finite change in quantity imported of product i; 0, is the marginal expenditure share of

product i; dQ, = w,,dql, +... + wl,,dql,, is the finite change version of the Divisia price

index (real income) ; vj is the relative (Frisch-deflated) price coefficients;










dpt, = log(pt /p,t- 1) is the finite change in price of product j;

dPt = Odpl +... + 018dpl,, is the finite change version of the Frisch price index; Note

that the lower case p is for prices of individual products and the upper case P is for

Divisia price indices. ,, is the demand disturbance, which is regarded as the random

effect of all variables other than income and prices. It is assumed that it has zero

expectation, that the variances and contemporaneous covariances are constant over time,

and that all other covariances vanish as


(4.2)
=0 if s t


The coefficients of (4.1) are subject to the adding-up constraint = 1 and the


symmetry constraint vJ = v, and negative definiteness of the matrix v, Furthermore,


the sum of the relative price coefficients is proportional to the marginal expenditure

18
shares V, = SO,, where q is the income flexibility.
J-1

In this study, six fruit juice groups (orange, grapefruit, other citrus, apple,

pineapple and grape juices) imported from 18 countries with three countries for each

juice group are included (Table 4.1).


In order to estimate (4.1), three steps are followed. First, one of the 18 demand

equations is deleted in order to eliminate singularity. Second, the constraint on the price

18 18
coefficient vv, = 80, is imposed and third, the adding up constraint Ok = 1 is
j=1 k=1


imposed on the income coefficients.












Table 4.1 Codes for countries exporting fruit juice to Japan
Exporting Quantity log Price log Budget
Product country changes changes shares Code

Orange juice U.S. dqi dpi wi 1
Brazil dq2 dp2 W2 2
ROW dq3 dp3 w3 3

Grapefruit juice U.S. dq4 dp4 w4 4
Israel dq5 dp5 W5 5
ROW dq6 dp6 w6 6

Apple juice U.S. dq7 dp7 w7 7
Austria dqs dps w8 8
ROW dq9 dp9 W9 9

Pineapple juice Thailand dqio dpio wlo 10
Philippines dq11 dpi1 wii 11
ROW dqi2 dpi2 w12 12

Grape juice U.S. dq13 dp13 w13 13
Argentina dq14 dp14 w14 14
ROW dq15 dp15 w15 15

Other citrus juice Italy dq16 dp16 w16 16
Israel dq17 dp17 w17 17
ROW dqis dpis wls 18
aROW means rest of the world


18
Imposing the constraint vi,
71=


60, on the price coefficients, we write the own


18
price coefficient v, in terms of the other price coefficients as v,, = 00, Yv, so that the


price term of (4.1) becomes


00,


18


18
dP) + v, (dpj


dP)


, (dp,- dP)+ v (dpJ -dp,)


(4.3)









17
Imposing the adding-up constraint 01 = 1- 6Ok on the income coefficients, the


price substitution term of (4.3) becomes

17 18
(4.4) = 00, dp -dp18 -Z Ok(dpk -dp18) + v, (dpj -dp,).
k=-1 J#

Substituting (4.4) into (4.1), we obtain


(4.5) W,dq, = O,dq, +OA,(O)+zv, (dp, -dp,)+E,
J#i

17
whereA,(O) = dp, -dp18 Ok(dpk -dp1 8) .
k=l

Equation (4.1) is still not estimable unless conditions are imposed on the matrix of

price coefficients in addition to symmetry and negative definiteness, such as preference

independence and/or block independence (Theil, 1980a). As soon as there is one

constraint on the price coefficients such as v12 = 0 (preference independence between

product 1 and product 2) in addition to symmetry and negative definiteness, it is possible

to estimate (4.1). The reason that (4.1) is still not estimable is that the income flexibility

q is not identified because of its invariance under monotone transformation of the

consumer's utility function (Theil, 1980) in which case there may not be unique demand

functions.

Equation (4.1) can be estimated using the following system of symmetry-

constrained equations.


dq, = dQ + QA, (0)+v1(dp2 dp)+v13 (dp3 dp,) +... +v, 8(dp8 dp,)
w2dq2 =2dQ + A2 (0)+ v(dp dp2)+ 23(dp3 -dp2)+ + (dp1 -dp2)
T3dq3 03dQ + A3(O)+ v13 dp, -dp3 )+3 (dp2 -dp3)+ +v318 (dp8 d)3








S4dq4 = 04dQ + A4 (0) + v14 (dp1 dp4) + v24 (dp dp4 )+ + V418 (dp dp4)
5 dq = BdQO + A,(0)+ v,,dp, -dp ,)+ v25dp2 -dp5,)+ +v518(dp1 -dp5)
Sdq, =,6dQ + A, (0)+v,,dp, -dp6 )+v26 dp, d)+...+v,,,18(dp, dp,)

wAdq7 = 0,dQ + A7(0) +v7 (dp dp,) + 27dp2 -dp,) +... + V71(dp dp7)

w dq8 = -08d + (Q0) + v,, dp, dp,) + 2 d +...+ 0 ,, V81(dp, dp8)
Wgdqg9 = dQ + A9 ()+19 (dp dp9 + V29 dp2 dp9) + 91 8 (dp8 dp9)

w1Odq1, = O1dQ + A10 ()+v1o(dp1 -dpO1)+v210(dp2 -dp1O)+...-+v118(dp18 -dp1O)
wdq, =,,dQ+A (O)+v,,, (dp, -dp1,,)+v2,(dp2 -dp1,,)+...+ v,111,(dp, -dp,,)
w12dq, =012dQ + (A12(0)+v112(dp -dp12)+v22(dp2 -dp12)+...+121(dp1 -dp12)

w,3dq,3 =013dQ + (A13(0)+v 113(dp, -dp,13)+v213 (dp2 -dp,13) +... +v1318 (dpS -dp,13)
wi, Jq1, = 014dQ + A(0) +v1 (dp, -dp,14)+v214 (dp2 -dp14)+...+v1418 (dp18 -dp,14)
w5,dq1, = ,,dQ + A5,(0)+ 1,(dp, dp,)+v215(dp -dp,)+... + v51(dp, dp)

116d16 = 16dQ + A16(0)+v116(dp -dp16) +216 (d dpl6)+*+ 618s(dpl dpl6)
w17dq,, = 0,7dQ + (A17(0)+ v,17 (dp -dp7) + 217 (dp -dp17) +... +v171 (dp dp)

The above system of equations provides the specific price substitution effect. The

specific substitution effect accounts for the n price changes on the demand for the

ith product (Theil, 1980). The specific substitution effect is one component of the effect

of a change in price. In order to estimate the total price substitution effect, one needs to

estimate the absolute price version of the Rotterdam model. The total substitution effect

is the sum of the specific and general substitution effect. The general substitution effect is

concerned with the competition of all products for an extra dollar of the consumer's

income.

The Absolute Price Version of the Rotterdam Model

The absolute price version of the Rotterdam model (3.12) can be written in finite

changes as









N
(4.7) wdq, = dQ + 7rdpJ +,
J-1

where vrj = v J b0, 0

The Slutsky price coefficients r, are symmetric negative semi definite of rank n-

n
1 and satisfy the homogeneity property Trj = 0. A major convenience of the absolute
j=1

price version is its linearity in the parameters, thus implying that a least-square regression

estimation yields best linear unbiased parameter estimates when (1) the explanatory

variables take non-stochastic values; (2) the disturbances have zero means and a constant

contemporaneous covariance matrix and are serially uncorrelated; and (3) the

homogeneity condition and the Slutsky symmetry condition are ignored.

A disadvantage of the absolute price version of the Rotterdam model is that the

number of the Slutsky price coefficients r, grows rapidly when the number of

commodities N increases. The number of free parameters in (4.7) is given by N + N2,

where N is the number of commodities. Even after imposing the restrictions of adding

up, homogeneity, and symmetry, the number of free parameters is reduced

to0.5(N+ 2)(N -).

The absolute price version of the Rotterdam model with symmetry and

homogeneity imposed can be estimated using the following system of equations.

w,dql = 01dQ + [T, (dp, dp8)+ ,12 (dp2 dp,8)+... + ,18 (dp7, dp,8)]
(4.8) w2dq, =O dQ + [r,2(dp, dp,8)+ ,z22(dp2 -dp,8)+...+,, .(dp7, -dp,,)]
w,3dq3 =03dQ + [7r (dp, -dpd)+ c23 (dp -p2 dp8))+ ...' +n d,,7 -dp8 )]









SW4dq4
Swdq5 =
T6dq 6



wdq, =
w9dq9 =

w10dq 0
w1 dq 1
w12dq12
Twedq

{W13dq13
W-14dql4
W15dq15


SW-16dq16
w17dq 17


0dQ + [l4 (dp, -

0,dQ +[ [ dp, -
06dQ + [1T6 dp1 -


0,dQ +[;0dp, -

0,1dQ + [11, dp, -

0gdQ + [T19 dp, -
= +,dQ +T 10(dp,
=01 dQ +[TII(dp,
=0,12dQ+[T1Z(dp,

=013dQ + [113, dp1
-014dQ + [1T14 (1
= 015dQ + [115 (dp1


=016dQ + [IT16 (dp
= 01dQ + ,17 (dp,


1)+.. + .7418( 17 dp18)
p,) +...+ (dp,, 7 dp dp,
18 )++518 (417 -18)]
p,1 )+... + 7618 41, 1dp)1


p18)+...+ 718(dp4, -dp ]
,18) +. + 1(dp1 dp18)]

p18)+ + 91 1 (dp1 dp1)


dPls)+" 2(dP2

IPls8)+:25(CdP2 d

1p)+) 27 (d2 -

dp18)+'7 (CdP2 -d


dp18 )+- (dp-d
-dp,1 )+ : 1 (dp2

- dp1 )+212 (d -


-dp18+7;T213(dp2
-dp,,)+7 ,dp
-dp1)+, 4dp2
-P -21
-dp18)+z (dp2
- dp18,) +z (dp



- dp,8) +7 21 (dp2


Block Independent Non-uniform Substitute-Rotterdam Model

The block independent non-uniform substitute-Rotterdam model (3.14) can be

written in finite changes as

(4.9) wudq, = Od + Iv,, d +6, .


The estimation procedure of (4.9) is similar to that of (4.1) presented earlier. In

order to estimate (4.9), one of the 18 demand equations is deleted to eliminate singularity.

Using the constraint v1, = 00,, we write the own price coefficient v,, in terms of


t Vo so that the price term of (4.9) becomes
j#1


-d18) )+ +1018 (d17
dp18)+ ...+ 1118 (d17


- dp18 +.. + ,. + 4(17
-18 )+* +71318 (17
- 18)+ +.. +71j (- p17
dp18 )+ ...+ 1518 (d17


-p18 )+. + 71618 ( 17
- p,)+ +...,,(1p,,


-dp1)]
dp18)]
dp18)]


-d18)]
-dp18)]
-dp18)]


-dp18)]
-dp1)]


the other price coefficients as v,, = 00,










00,


dP) + v,(dp, dP).
J^zlS,


, (dp, dP)- + vZv, (dp
I^jeS,


dp,).


18
Now, using the adding up constraint 01 = 1 Ok ,(4.10) becomes
k=1


17
dp 18 Ok(dpk
k=l


dpl8) + v, d(p,
jGSg


Substituting (4.11) into (4.9) yields

(4.12) w,dq, = O,dq, + 4,A, ()+ v, (dp -dp,)+,


Equation (4.9) can thus be estimated using the following symmetry-constrained

system of equations.


OdQ + A, (0)+ V12 (dp2,
-02dQ + A2 (o0) + v12 (dp1
- ,dQ + A,3 (0) + V13 (dp1

04dQ + #A (0) +v,, (dp,
O4dQ +A4(0) v45(dp5
S5dQ + -A, (0)+ v45 dp4
06dQ + A6 (o) + V46 (dp4


SOdQ + OA7 (0) + v,7 (dp,
:0dQ +A, (0)+ v7(dp,7
S9dQ + A9 (0)+ v79 (dP7


dp ,) + V23(dp3 dp)




-dp4)+46(dp dp4)
-dp,)+ 56 (dp6 -dp,)
dp6)+ v56 (dp5 -dp5)


-dp7) +v79(dp9 -dp,)
-dp,)+ v89 (dp9 dp)
dp9)+v89(dp8 -dp9)


(4.10)


(4.11)


00, dp,


dp,).


Swdq, :
wdqw

Tw24dq 2



SWadq 6


{7dq7

w8 dq8
w9wdq9
w[dq,3

[9dq94


IV, (dp,
Ji^ J









Sw,,dq,,
w1 ,dql ,



{W13dq13
S14dq14
w15 dq15


S-16dq16
w117dq17


O10dQ+ Ao(0)+ v101,(dp,,
0,1dQ + ZA1 (0) + v10, (dp
OB~dQ + A12 (0) + v10,1 (dp1


03dQ + A13 (0)+ ,v314 (dp14
014dQ + A14 (0) + v1314 (dp13
O15dQ + A15 (0) +v1315 (dp,3


016dQ + A16 (0)+v1617(dp17
,17dQ+ A17(0)+Av1617 (dp16


Block-wise Dependent Non-uniform Substitute-Rotterdam Model

The block-wise dependent non-uniform substitute-Rotterdam model (3.18,) can be

written in finite changes as


dp j 01 6 dph
(4.14) wdq, =,dQ + V + --I Vs, + E
dP Y ^ ^ dP 0 h
J S,
where v, is the specific price coefficients of products within in a group; Vgh is group

relative price coefficients; dPh is the Frisch price index of a group, and E, is the error

term.

The estimation procedure of equation (4.14) is also similar to that of (4.1). In

order to estimate (4.14), one of the 18 demand equations is deleted to eliminate

singularity.

Using the constraint that the sum of the price substitution terms is proportional to

the marginal value share I V, + Y Vgh = 00,, we write the own price coefficient
jGSg 0 h l
J Sg


-dp,)+v1012(dp12
-dp,)+ v1112 (d12
-dp10)+v112 (dp 11


-d13)+ V1315 415
-d14)+ V1415 (15
dp15) + V1415 (d14


-dp16)+1618 (d18
-dp17)+ 718 (dp18


-dpo)
dp,,)
-*12)


-dp13)
-dp14)
-dp5)


-dp16)
-dp17)









01 6
v, in terms of the other price coefficients as v,, = 00, V, Vgh and
JS hg

substitute it in equation (4.14) so that the first price term of equation (4.14) which

corresponds to the within group demand becomes



(4.15) = o V Vg- dp, -dP)+ Zv,(dp, -dP)






(4.16) 0 d d6
01 6
V= Jd V (dp, dP) + v,((dp, -dp, )













Substituting (4.16) into (4.14), we obtain



j sg
(4.17) s
o Vy (dV@P dP)+ E,


Equation (4.14) can thus be estimated using the following symmetry-constrained

system of equations (equation 4.18).
system of equations (equation 4.18).








W dql = OdQ + o0, -K + (V2 +V3 +... +V6) (dp, dP)+
v 1(dp2 dp)+ V3 (dp3 dp)+
0 [v, (dP2 -dP) + V (dP3 -dP) +... + V(d d)]


dq2 =0dQ+ 00 (V12 +V3 +...V16)(d2 -dP)+
o u^ +o u + ua j
v(dq -d p) + 1 +2+ O)
v12 (dp1- dp2)+ V23(dP3 dP2)
02 IV12 +Po2 -d + V23 + P3 -dp+ V d -d yp2
01, +02 +0

,dqz,=dQ+ 0 +0 V2 +V2+...+ -dP)+
v13 (dp- d3 ) + V23 (d dp3)
03 V1 [2(dP -dP)+ V13(dP3 -dP)+.. + V6(dP6 -dP)]
o, +2, +0

wi4, = 4,dQ+ !4 04 (V12 + V23 + +.V26) (dp4 -dP)+
1 04 + 5 + 068
V45 (dp5 -dp4,)+ V46 (dp6 dp4)+

S 054 0 v12(dl -dp)+23d3 -d)+...+V26(dP6 -dP)
04 +05 +03

T 5 =0d+ 0 05 (V12 + V2( 3 V V+...+ V26)dp -dP)+
1 04 +05 + 6
V45 (d4 -dp)+ V(d s dp) +
05- [V12(dP -dP) + 2(dP3 -dP)+...+ V26(d -dP)]
04 + 0, + 06 )

wdq, =06dQ+ 006- (V,2+V +...+V + )(dp6 -dP)+
V46 (dP4 -dP6) + V56 (dP 5 e6 ) +
06 [V (p -dP) + V{ P( -dP)+... + V(dP -dP)]
0 4 +5 + 06








w dq, =0_dQ + (V, 7+V, 23 +...36 -dP)+
07s( +0s8+09 9
V78 (dP8 dP7) + V79 (dP9 dP7) +
07 [V, (dP, dP) +-V (dP, dP) +... +V36 (dP6 dP)]
dq + 0, + 09

wdq, =0dQ + 008 0 (V +V3 + ...+V36 d -dP)+
07 +08 +09 -
v78 (dp, dp,) + V89 (d9- dp,8) +
08 [V13 ( 09 ( +13 V23 +V36(dp9-dp)


wTdq9 = OdQ + V09 09 + O, + 09 +'3)(dp P)+
V,,9 (dp dp9)+ V9(dp, dp9) )+
07. + + 0936





[0d +001 010 (V14 + _V24 _+_ + _V46) (dplo dP)_+
dq,9 =dQ + 0o9 -V +V- + + ...dP)+
lOll (dll d9) + V9(dP dp ) +



010 9 V14 (dp -dP)+V2 (dP2 -dP)+...+V36(dP6 -dP)
o +ol011 ++0

,,.JLq,, = OldQ + 01 -_ 10 (V +V24 +...+ (d dP)+



K 010 + [v( l + 02
VlOll(dPlo -d+Pll)+ V-2(dPl2 dPll) +
01 [V14(dP -dP)+ V24(dP2 -dP)+... +V46dP6 -dP)]

Ol1 + On + O12



2dq2 =01dQ+ (V4+V24 +...+V46) (dp -dP)+
-0, + +ol + 1-012
V01 ( d10 n 1) + V1112 ( d12 dn1) +




v1012 (dp10 -dp12)+V112 (dp11 -dpl2)+
K010 V011 (dP dP) +V24dP2 -dP)+...+ 46 dP6 -dP)]
01. +oil + 012








w13dq13 = 03dQ +01+ 013 -+15 + V25+ + +...+V) (dp3 dP)+
1314(d14 )+J315(5 -13)+
013 14- [015 5(d4 -dp+ V(dP2 d)+'...+ V5(d6 -dP)]
013 + 014 + 0dP1+

w,,J, =0 ,,dQ+ 014 (V15 +V25 +-...+ V56(dp -dP)+
lq13 + 14dQ + 3 015
v1314(dP13 -dP14)+V1415(dP15 -dP4)
[ 041 5 (d -d)+25 (d-dp)+...+V56(dP6 -dP)]
013 +0 +01

wIdq1, = 0,dQ + 0 15 (5 V25 +.. + V56 (dp5 -dP)+
L1q (013 + 014 + 015
V1315 (dP13 dP15) + V1415 (dP14 dP15)+
[ 013 4 15 ([v15i -dP)+ V25(dP2 -d)+...+ 6(dP6 -dP)
013 +6014 + 1

w16dql6 =16dQ + 0016 016 --+0 16 +V26 + + 56) dp16 -dP)+
1 016 +017 +018
V1617(dp17 -dp16)+1618(d18 dp16+
016 16(dP -dP)+V26 dP -dP)+...+V6(dP -dP)]


7dq, = 017dQ+ 0017 01 +0+01 + 26 + +...+V56) (dp -dP)+
1 617(dp16 dp17 ) + 718 (dp18 dp ) +

K016 +817 +818
Block Independent Uniform Substitute-Rotterdam Model
The block independent uniform substitute-Rotterdam model (3.21) can be written


in finite changes as









8d (1-kIo,) d -, k @,p dp
(4.20) wdq = ,dq + (-k dP + d
I' -k k dP l-k dP

Equation (4.20) can be estimated using the following system of equations.

1, 1O k, 1 ) k] 8, 0,
01 j) (dp, dP) + (dP2 dP) +
1-k,(0, +02 +03) 1-kI(, + 02 +03 )
w,dq, = 0,dQ + _
k013 (dp3 dP)
1 -k,(01,+0 + 03)

_- 1-2-- (dp, dP) + (dp2 dP) +
1 k, (, + 0, + 03 ) 1- k, (, + 0, + 0)
wzdq2 = 0dQ + I
-k1( 0203) (dp, dP)
1-k,1(0, +0 + 03,)

-k0103 (dp, dP) + (dp dP) +
1- k (0, +0, +03) 1- k(0, + 02 +03)
03 (1 k, 03)
lq =k(O O2Od+ c/ )

04(1- k204) d k20405 -
S'14 =04dQ+ k2(04+05+6)
k20406 (dp6 dP)
1- k,(0, +0 +06)



S- k2 (dp dP) + 5- k (d5 -dP) +
Td5=1- k2 (04 +08 +06) 1-k4 (04 + 8, + 06
20506 (dp6 dP)

1-k (04 +05 +06)
-k,0, 0,( 1-k 6,)


-k20406 (dp4 dP)+ k205 (dp dP) +
1 k2 (04+ 5 ) 1- k (04 +05 +)
wdq, = ,dQ + (
06- k 2 -6 dp, dP)




1- k2 (04 + 85 6+ c)
k 040 k 0 0


07 k30 (dp -dP) + (dp dP) +
1- k3(07 +0,+0 ) 1- k (0 +0 +09)
wdq6 = 67dQ + _
S(1 k8 0)


k3009 (dp9 dP)



1-k3(8 +0,+09)










k3008 (p7
(dp,
k3(07 +08 +09)
-k30809
(dp9
-k ( +0 8 +09)

k30709 (cp7
k, (07 +08 +09)
09 (1- k309)
k3(O7 + 08 + 09)


0,(1-k0+0)
k4(01o + 11 + 012




-k401001 (dp
-k4(010 + 011 + 012)




-k410(12 dp
--k4 +0111+ )




-k4(010 +01 + 012)



-k4(10 +011 + 012)

k4(010 +0112 0
-^(fo 7ft+f2)(d12


013(1- k5013)-d)
k5 (013 +014 +015) (d Pl
k50130 (d dP)
k5 (013 + 014 + 015 )

k51314 (d3 dP)
- k5(013 +014 + 015)
k5014015 ( )
-k5(013 +014 (d dP)
-k,(8, +014 +1


08(1- k3o8)
dP)+ (dp8
1-k3(07 +08 +09)

dP)



dP)+ 30809 (dp8
1- k (07 +08 + 09)

dP)


-d k4010011 ]
dP) + (diI dP) +
1 k (010 +011 + 012))

dP)


dP) +


8k1 (1 k411 ) (pl1
1- k4(o + 8Oil + 012)


dP)


-P k4011012 (
-dP)+ (dpl,
1- k4(0 + 1 +1 2)

- dP)


k501301 (
1- k(0 + 014 + 01 )


+ 014(1-k5014)
+- (dp14 dP) +
1- k,(013+014 + 015)


w 1
w ,/q, = 0dQ + {

1 =



w9dq9 = 09dQ + (-)

1


,,,Jiq,,, =01odQ + [
1-






w1dq,, = 01dQ +

d = +

w12dq1 = 012dQ +


w13dq13 = 013dQ +


w1q11 =014dQ 1 + -

1










1-
15dq15 = 15dQ + 0



16 = 16dQ + 1

16dq16 O16dQ+c/{
1


k5013015 d13
^) (-dp,
k,(013 +014 + 015)
8,0 15(1 k,5 015 ) (dp15-
(dp,,
k, (013 +014 + 015

8016 (1- k6 016) (dp16
-k6(016 + 017 + 018)
k6016018 (dp8
- k6(016 + 017 + 018)


dP) + -k5014 15 (4 dP) +
1- k,(013+04 + 15)

dP)


- dP) + (-01617, dP) +
1- k6 16 + 17 81

- dP)


k6 167 dP )+ 017 (1- k6 17) (dp17
17 -(dpl6 dP) + (dp,, dP) +
1 k6 (16 + 17 18) 1-k6(16 17 + 18)
17dq7 = 017dQ + k0101
k6 17
-1 + -8 -(dp,, -dP)
1- k6 (,16 + 17+ 180 )

Block-wise Dependent Uniform Substitute-Rotterdam Model

The block-wise dependent uniform substitute-Rotterdam model (3.24) can be

written in finite changes as

(4.22) w,dq, = 0,dO+ Q+ 1 k,0 + Vgh dP
-k,, dP 1-ke, dP hsg dP

Equation (4.22) can be estimated using the following system of equations.

0,(1-k,0,) -kze0e, ^
-k01(1 -k01- (dp, dP) + k--l0 (dP2 dP) +-
wdq1 =-dQ(0+ + 03) 1 k, (012 +0 + 0
wldq, = 1,dO + # +
-k,003 (dp3 -DP)
1 k,(01 +02 +03)

01 [V2(dP2 -dP+VPPP)+ Vd3 -dP)+...+V16(dP6 -dP)]


k10102 (dp -dP) + 01 dp, -dP)+

1 k ((0, ++ 0 0
w2dq2 O2 dQ. + k1023 (003



[ 01 +2 [(dP2-dP)+ 3(dP3 -dP)+...+6(dP6 -dP)]
9 + 0 + b3







-k1013 (dpl dP) + -k10 (dp2 -dP)+
1- k (0 + 02 + 03) 1- k,(0 + 02 + 03)
wzdq, = dQ +<
(1 k, _)
3dq3 3dQ3) (dp3 DP)
1- k1 (01 + 02 + 03)

l02+03+0,
K +01 o jV12(dP2 dP)+V13(dP3 dP)+...+ Vl(dP6-dP)]

S0(1 k204) d k204 dp
1dq(=0d +O24 05 ) 1-k2(04 +05 +06)
w4dq4 = 04dQ +D
-k20406 (dpp DP)
1-k (04 +05 +06)+
-04 05 V12 (dRl -dP) + V23(dP3 -dP )+...+ V26( -d)
8, +0, + 06
F k20405 ((1 dP)- k )dP)
dq5 1- (04 + 05 +06) 1-k (04 +,05 +06)
wdq, = 8,dQ +a>
k20506 (dp-DP)
1- k (04 + 05 + 06)
5 [V 1 2(d -dP) + V23(dP, dP) +... +V26(dP6 dP
04+0 +5+06

-k206 (dp -dP)+ -k200 (d) -dP
-1- k(04 +0, + 0) 1-k (0+4 8 +06)
wdq, = 6,d6 +0 k06
(dp6 DP)
1- k (04 + 0, + 06)
06 V2 (d dP) + 2 (dP2 dP)+... + V26(dP6 dP

8 (1- k30 -dP k30 (d -dPk)+
7 =e + 1-k07, 8 +0, + ) d- k?(8 +0 +0) 09)
w d-k379 (dp9 -DP)
1-k3(7 + +09)
07 + [V13(dp -dp) + V23 (P2 -dP)+ ...+V36(dP6 -dp)
0 + 8 +9


+


j


7
I +









-k3078 ( dp dP) + (05(1-3 -_p dP)+
1- k3 (0,+0, + 09) 1- k3 (0 + 8 + 09)

,8d k3(389 (dp9 DP)
1-k3(0,7 + 0,8 +0,9

08 V13 (dp -dP)+ V (dP dP)+...+ (dP6 dP)]
07 +08 + 09


k3079 (dp, dP)+
1- k (0 + 08 + 09) 1-
wdq, =9,dQ + ,
9 -k1 k,
9dq9 309d+ ( (dp 9 DP)
L1- k3 (O7 + + 9)

09 [V3 (dP dP() Vd+ V3 (dP


I 0 ( 1 + 082 + 91)
\ ..Ji/, =0 81dQ +
0 11 0 ( 1 k 4 0 1 0 1 2d 2
-1 -k4 (0 10 + + 012 )
010 [V4 (dP1 dP) + V4 (dP2 -
0 1 0 + oil + i 1


-k2089 dp,- dP) +
k3(07 +.08+09) dP



- dP)+ + V3( dP6 dP)


-k401,0 2l(dp
k4(010 + 81 + 012)


dP )+... + V4(dP


dP) +
+


dP)]


k-401l,, _l(1- 11)- _
S k4O -01 2 (dplo dP)+ (dp, dP)+
1- k (1, + 4(01 + 012) 1- k4 (010 + 0i + 012)
wndq,1 = 6,,dQ + +
w1-d1 Q + k400 + D,)

in [V4 (dP -dP)+V24(dP2 -dP)+...+V46(dP6 -dP)
010 + Ol1 + 012)
k-401012 (dp, -dP) + k-40,0 (dpc, -dP)+
1- k4(010 +o +) 1- k4(o ( +0o1) + 12)
W12dq2 = 012dQ + 012 4012) +
1 12 12 3 11 /k )
1+ )(dp12 -DP)

8 0 [14(ai -dP)+ V24(dP2 -P)+...+ 46(dP6 -P)]
10 + ol + 012









013(1- k5013) -(dp1 k4013014 d -dP)
1-q k5(013 +014 +015) 1- k5(03 +014 + 15)
13dq13 = 013dQ + 13
k 03 015 (dp15 DP)
1-k,(013 +01 + +015)

013 [V1 (dP, -dP)+ V25(dP -dP)+... + V5(dP6 -dP)
013 + 014 + 015
-k5013014 (dp13 -dP)+ 014(1k5014) (4 -dP)
1-k (013+14 + 015) 1-k5(013+014 +015)
w ,, 4k 1 = 0,dQ+p + D
5 13 15 (dp15 -DP)


1 k5 (03 + 014 + 015)




S015- [V15(dP dP) +V25(dP2- dP)+... + V56(dP6 -dP)]

613 + 014 + 015
-01(1 kk01 k(p0 )+ i(d7 -dP) +
1 k (1+01 +0 + 08) 1 k6 (016 + 0 + 018)
wl5dq, = 8,dQ+p +



-6 016 0 18) (dp18 DP)
1 k, (8,0 + 8,0 + 0,1)






016- +01 P[V16(dP -dP)+ V26 (dP2 -dP)+ ... + V56(dP5 -dP)
013 + 014 + 051



16 (1-k60160) (d6 1P)+ 0 ( 1 (dp7 -d+
1-((61,, +-,, +P ,, d +


W-17dq17 = 071 + k6 (16 17 +018) 1- k6 (16 17 + 018)
k601 18 (p DP)
+1-k6 16 + )17 + 18 )
017 [V16 dP2 dP)+ V26 dP, dP)+... + V56(dP, dP)]


016 + 017 + 018)
( A,, dP)+ (d^ ^ dP) +
1- k (0,s +0, + 818) 1- ks(0,s +0, + 8+^)
17dq17 17 = d d + +
-- k--6 (dp8 DP)
1- k_(0,s +0, + 8+^)

-V-16, (dP, dP)+ V,, (dP3 dP)+... + V, (dP, dP)}
1^ si +6'^ +6'i


+


Data Sources

The sources of data for this study are the Statistics Bureau of Japan and Japan's

Ministry of Finance as well as the Food and Agricultural Organization. Monthly

population data from December 1995 to May 2005 came from the web page


t









(http://www.stat.go.jp/english/data/jinsui/2-2.htm) maintained by the Statistics Bureau of

Japan's Ministry of Internal Affairs and Communications. Import data came from the

Trade Statistics of Japan that are published by the Ministry of Finance and the Customs

under the provision of the Customs Law and the relevant international conventions. It is

available on the web page http://www.customs.go.jp. The monthly imports and

expenditures on imports of orange, grapefruit, other citrus, apple, pineapple and grape

juices were obtained for the period December, 1995 to May, 2005. The values of imports

are on a cost, insurance and freight (CIF) basis, which include costs of the product,

insurance and transportation. Unit import values, which proxy commodity prices, were

obtained by dividing import values by import quantities. Data on the production,

consumption and trade of fruit juices came from the webpage

http://faostat.fao.org/faostat/ maintained by the Food and Agricultural Organization.

Analytical Methods

The method used to estimate the model is the non-linear least square (LSQ) in the

Time Series Processor Program (TSP 4.5). This method is based on the entire system of

equations, and estimates all parameters jointly. When estimating the system of demand

equations, one of the equations has to be deleted or the covariance matrix will be singular.

However, parameter estimates of the deleted equation can be recovered by re-estimating

the system with another equation in the system. Parameter estimates are invariant to the

deleted equation when using maximum likelihood estimation (Barten, 1969).

The LSQ command computes maximum likelihood estimates if it is specified with

no instruments and more than one equation (Cummins, 1999). Since the parameter

estimates in this study are generated from a system of demand equations without

specifying instruments, they can be taken as maximum likelihood estimates. With






68


normally distributed disturbances (u,), the ML method has all the desirable asymptotical

properties of Maximum Likelihood (ML) estimators and, therefore, is asymptotically

efficient among all estimators (Greene, 2000). The likelihood ratio test is used to test for

autocorrelation.














CHAPTER 5
RESULTS AND DISCUSSION

Descriptive Results

Since Japan's deregulation of imports in the 1990s, the imports of fruit juices

have increased with the exception of U.S. apple juice (Table 5.1). Over the period

January, 1995 to May, 2005, the imports of U.S. apple juice has decreased by 17% while

that of U.S. orange, grapefruit and grape juices increased by 4%, 12% and 5%,

respectively. The highest increase was attained by the ROW grapefruit juice (51%)

followed by the Chinese apple juice (31%) and the Israelis grapefruit fruit juice (26%).

The analysis of import stability as measured by the coefficient of variation shows that the

imports of fruit juices in Japan over the given period have exhibited a significant

fluctuation. The fluctuation of imports varies from country to country. U.S. orange and

grape juices have experienced the highest fluctuation among U.S. fruit juices.

Over the same period, Japan's import price of all fruit juices has decreased (Table

5.1). On average, Japan's import price of U.S. orange, grapefruit, apple and grape juices

has decreased by 12%, 10%, 7% and 6% per month over the period December, 1995 to

May, 2005. Over the same period, apple juice imported from the rest of the world has

witnessed the largest price decrease (13%). Among U.S. products, prices of orange and

grapefruit juices are relatively more stable than those of the respective competitors'

products. The prices of apples are less stable compared to their respective rival products.

Except for Brazilian orange juice (25%) and the ROW apple juice (19%), the

average expenditure share of fruit juices in Japan is below 10% (Table 5.1). Expenditure









share of U.S. juices, expressed as a percentage of total fruit juice expenditure, ranges

from 6% for apple juice to 8% for grapefruit juice.

Table 5.1 Fruit juice quantity and price log-changes, and expenditure shares, Japan,
December 1995 to May 2005
Imports Quantity log-changes Price log-changes Expenditure shares
dq, = log(q,, /q,l,) dp, = log(p,,/p,,,_) (T,)
Mean SD Mean SD Mean SD
U.S. oranges 0.0410 0.6701 -0.1155 0.2803 0.0724 0.0335
Brazilian. oranges 0.0982 0.9847 -0.1033 0.2683 0.2542 0.0895
ROW oranges 0.0959 0.8876 -0.0083 0.4210 0.0324 0.0205
U.S. grapefruits 0.1200 0.4909 -0.0979 0.2907 0.0808 0.0302
Israelis grapefruits 0.2617 1.0503 -0.0720 0.5821 0.0259 0.0168
ROW grapefruits 0.5078 1.3739 -0.1149 0.8360 0.0111 0.0104
U.S. apples -0.1694 0.9249 -0.0690 0.2847 0.0567 0.0422
Chinese apples 0.3176 0.6891 -0.1405 0.2798 0.0727 0.0372
ROW apples 0.0760 0.4059 -0.0946 0.1958 0.1652 0.0510
Thai pineapples 0.1549 1.0317 -0.0572 0.3934 0.0109 0.0058
Philippines pineapples 0.1578 1.7814 -0.0606 0.3713 0.0075 0.0037
ROW pineapples 0.1109 1.5452 -0.0414 0.5171 0.0089 0.0062
U.S. grapes 0.0529 0.5942 -0.0647 0.2890 0.0621 0.0249
Argentinean grapes 0.2792 1.1260 -0.0969 0.3346 0.0091 0.0058
ROW grapes 0.1717 0.4728 -0.0802 0.2584 0.0648 0.0235
Israelis other citrus 0.0861 0.6349 -0.0924 0.3138 0.0220 0.0064
Italian other citrus 0.1756 0.7744 -0.0902 0.2412 0.0172 0.0069
ROW other citrus 0.2032 0.8238 -0.1031 0.5923 0.0250 0.0118
(Source: Study data)

Test for First-order Autocorrelation

A test for first order autocorrelation AR (1) was carried out for five different

versions of the Rotterdam model. These are block independent non-uniform substitute

Rotterdam model (4.9), block-wise dependent non-uniform substitute Rotterdam model

(4.14), block independent uniform substitute Rotterdam model (4.20) and block-wise

dependent uniform substitute Rotterdam model (4.22). The test was done considering

each model with and without autocorrelation as the unrestricted and restricted model,


respectively. The null hypothesis(H0 : p


0) was tested using the likelihood ratio test


-2(L(O)- L(O))~2[J] where 6 is a vector of restricted parameter


given as LR









estimates and 6 is a vector of parameter estimates associated with the unrestricted model.

The restricted model is the one with first order serial correlation while the unrestricted

model is the one without first order autocorrelation.

Under the null hypothesis (H0), the LR has an asymptotic chi-square distribution

with the degrees of freedom equal to the number of restrictions J. Since symmetry was

imposed as part of the estimation procedure, the coefficient of autocorrelation was taken

to be common across equations.

The result of the test indicates that the null hypothesis of no autocorrelation was

rejected in all of the models (Table 5.2), implying that the data is serially correlated. The

value of p, which is common across equations in each system, ranges from 0.31 for (4.1)

to 0.36 for (4.9), and is significantly different from zero (P<0.001). The Hildreth and Lu

(1960) approach was used for the correction.

Table 5.2: Test for first-order autocorrelation
Model Coefficient Log Likelihood 2(L( )- L( ))a
value
Equation (4.20) Rho= 0.00 4710.26 150.82***
Rho= 0.35 4785.67
Equation (4.9) Rho = 0.00 4716.24 147.32***
Rho = 0.36 4789.90
Equation (4.22) Rho = 0.00 4748.99 128.36***
Rho= 0.33 4813.17
Equation (4.14) Rho= 0.00 4757.74 136.70***
Rho= 0.35 4826.09
Equation (4.1) Rho = 0.00 4892.99 83.60***
Rho= 0.31 4934.79
a Twice the difference between the log likelihood value for the unconstrained model, L ) and the
log likelihood value for the constrained model, L (o).
*** The chi-square critical value is at the 1% significance level.









Hypothesis Testing for Model Selection

Following the correction for first-order autocorrelation, the study tests two

hypotheses (block independence/uniform substitute hypothesis and block-wise

dependence/uniform substitute hypothesis) to select the model that best describes the

import data of fruit juices in Japan. The hypotheses of block independence and block-

wise dependence have to do with the relationship between products that belong to two

different product groups while that of the uniform substitute has to do with a relationship

between products that belong to the same product group. Therefore, the block-

independence/uniform substitute hypotheses and block-wise dependence/uniform

substitute hypothesis involve between-group (block independence or block-wise

dependence) and within-group (uniform substitute) relationships. Recall that the uniform

substitute hypothesis is applied to the same product differentiated by country of

production.

The result of these tests enables us to select the model that best describes the

import data of fruit juices in Japan. In light of these hypotheses, two restricted models

were derived from the relative price version of the Rotterdam model (4.1). The restricted

models are block independent uniform substitute-Rotterdam model (4.20), and block-

wise dependent uniform substitute-Rotterdam model (4.22). Since these two restricted

versions (4.20) and (4.22) are nested in the unrestricted version (4.1), the likelihood ratio

test is used.

Block Independence and Uniform Substitute Hypothesis

The hypothesis of block independence states that there is no specific cross price

effect (v ) between any two products in any two different product groups. The uniform









substitute hypothesis states that the specific cross price effect (v, )between any two

products in the same product group is the same for all pairs of goods in that group.

Combining the two null hypotheses, the null hypothesis of block independence

and uniform substitute relationship can be restated as

Ho: v, =O, i Sg j Sh and g h; v,, =k for anyi, s eSg.

HA : v, 0, i eSg j Sh and g h; v,, k for any i, sSg.

The test for the hypothesis of block independence and uniform substitution

involves a comparison between the uniform substitute block independent Rotterdam

model (4.20) and the relative price version of the Rotterdam model (4.1).

Since (4.20) is a restricted function, we expect its likelihood value to be smaller

than that of (4.1). The likelihood value of (4.20) is 4785.67 with 24 degrees of freedom

while the value of(4.1) is 4934.79 with 171 degrees of freedom (Table 5.3). The value

of the model chi-square is 298.24 which is greater than the critical chi-square value at 1%

significance level. Therefore, we reject the null hypothesis, and conclude that there is

competition between products that belong to different product groups since there is a

change in marginal utility of a dollar spent on a product in one product group caused by

an extra dollar spent on another product in another product group. For example, an extra

dollar spent on U.S. orange juice, affects the marginal utility of another dollar spent on

the Chinese apple juice j .

Furthermore, the change in marginal utility of a dollar spent on a product caused

by an extra dollar spent on another product is not the same for all pairs of products within

the same group. The country of origin makes a difference in one's decision to buy a

certain fruit juice. For example, the change in marginal utility of a dollar spent on the









U.S. orange juice i, caused by an extra dollar spent on Brazilian orange juice r is not the

same as that of the change in marginal utility of a dollar spent on the U.S. orange juice

caused by an extra dollar spent on the ROW orange juice, s. This suggests that

consumers decide to buy orange juice based on the country of origin. In summary,

consumers are influenced by the country of origin when they choose between products

that belong to the same group.

Table 5.3 Hypothesis testing for model selection
Model Log likelihood Free parameters 2(L()- L()a
value
Equation (4.20) 4785.67 24 298.24***

Equation (4.22) 4813.17 39 243.24***

Equation (4.1) 4934.79 171

a Twice the difference between the log likelihood value for the unconstrained model, L (0 and the
log likelihood value for the constrained model, L ().
*** The chi-square critical value is at the 1% significance level.


Block-wise Dependence and Uniform Substitute Hypothesis

The hypothesis of block-wise dependence states that the specific cross price effect

(v, ) between any two products in two different product groups is the same for all pairs of

products in the two groups. The uniform substitute hypothesis states that the specific

cross price effect (v,) between any two products in the same product is the same for all

pairs of products within that group.

Combining the two null hypotheses, the new null hypothesis which corresponds to

the block-wise dependence uniform substitute relationship can be restated as

Ho : vJ = agh, i E Sg j e Sh and g h; and v,, = k for any i,r e Sg









HA : vY agh, i Sg j Sh and Sg Sh ; and v,, k for any i,r e Sg.

The test for the hypothesis of block-wise dependence and uniform substitution

involves a comparison between the block-wise uniform substitute-Rotterdam model

(4.22) and the relative price version of the Rotterdam model (4.1). The likelihood value

of (4.22) is 4813.17 with 39 degrees of freedom while the value of (4.1) is 4934.79 with

171 degrees of freedom (Table 5.3). The value of the model chi-square is 243.24 which

is greater than the critical chi-square value at 1% probability level. Therefore, we reject

the null hypothesis, and conclude that the competition between products in different

groups is not the same for all pairs of products in the two groups the change in marginal

utility of a dollar spent on a product in one product group caused by an extra dollar spent

on another product in another product group is not the same for all pairs of products in

the two groups. In other words, the competition between product i of group g and

product j of group h is not the same as that of product i and product / of group h since

the change in marginal utility of product i, caused by an extra dollar spent on product j

is not the same as that of the change in marginal utility of a dollar spent on product i

caused by an extra dollar spent on product 1. For example, an extra dollar spent on U.S.

orange juice j, affects the marginal utility of another dollar spent on Thai pineapple

juice differently than does it affect the marginal utility of a dollar spent on the

Philippines pineapple juice. In other words, the effect of the change in price of U.S.

orange juice on the demand for Thai pineapple juice is not the same as that of the effect

on the demand for the Philippines pineapple juice. This implies that the country of origin

of the pineapple juice makes a difference when a consumer decides to buy orange and

pineapple juices.









Furthermore, we can conclude that the change in marginal utility of a dollar spent

on a product caused by an extra dollar spent on another product is not the same for all

pairs of products within the same group. The country of origin makes a difference in

one's decision to choose between products that belong to the same product group. For

example, the change in marginal utility of a dollar spent on U.S. orange juice i, caused

by an extra dollar spent on Brazilian orange juice r is not the same as that of the change

in marginal utility of a dollar spent on U.S. orange juice i caused by an extra dollar spent

on the ROW orange juice, s. This implies that consumers are influenced by the country

of origin and thus decide to buy orange juice based on the country of origin. In summary,

the country of origin is taken into account by consumers when they choose between

products that belong to different product groups and also when they choose between

products that belong to the same product group.

Therefore, based on the results of the likelihood ratio test which rejected both

restricted models (Table 5.3) the relative price version of the Rotterdam model (4.1) is

chosen to best describe the import data of Japan's import of fruit juices.

The relative Price Version of the Rotterdam Model

Since the relative price version of the Rotterdam model does not have any

restriction within or across the price coefficients, individual products are competing with

each other based on the country of origin. In other words, it allows investigating the

relationship between individual products based on the country of origin of the product.

For example, we can investigate the relationship between apple juice from China and

orange juice from U.S.









Parameter Estimates

Marginal expenditure shares Results indicate that the marginal expenditure

shares are all positive except for those of the Israel's grapefruit juice and the ROW

pineapple juice (Table 5.4). However, the coefficient of the Israelis grapefruit juice is not

statistically significant. The largest share of the increase in marginal expenditure on

imported fruit juices goes to Brazilian orange juice (70%) followed by that of the ROW

apple juice (8%). This is consistent with the average expenditure shares since the

Brazilian orange juice (25%) and the ROW apple juice (17%) have the first and second

highest average expenditure shares (Table 5.1). Japanese imports of U.S. orange juice

grapefruit and apple juice receive only 3-4% of the increase in marginal expenditures.

Except for apple juice and grape juice, imports of fruit juices from ROW receive less than

one percent of each dollar increase in expenditures.

Table 5.4 Marginal expenditure shares of imported fruit juices in Japan
Product Estimates SE
UO.SO. oranges 0.0337*** 0.0100
Brazilian oranges 0.6997*** 0.0373
ROW oranges 0.0033 0.0058
UO.SO. grapefruits 0.0441*** 0.0078
Israelis grapefruits -0.0016 0.0059
ROW grapefruits 0.0051 0.0034
UO.SO. apples 0.04686*** 0.0124
Chinese apples 0.0473** 0.0092
ROW apples 0.0800*** 0.0159
Thai pineapples 0.0044* 0.0023
Philippine pO. apples 0.0024 0.0022
ROW pineapples -0.0073** 0.0036
UO.SO. grapes 0.0080 0.0076
Argentinean grapes 0.0017 0.0024
ROW grapes 0.0188*** 0.0066
Israelis other citrus 0.0045 0.0032
Italian other citrus 0.0019 0.0027
ROW other citrus 0.0064 0.0041
*** (**)* significance at 1%, 5% and 10%









Price effects. Price effects are described here by both relative and Slutsky price

coefficients. The Slutsky price coefficients n, can be derived from relative (Frisch-

deflated) price coefficients v, and marginal value shares O, using -,j = v, ,00 ,

where q is the coefficient of income flexibility.

The Slutsky price coefficients (r, )are the sum of the specific v, and general

substitution effects (- 00,Oj ). The Slutsky price coefficients n, measure the total

substitution effect of a change in the jh price on the demand for the ith product or,

equivalently, the effect of such a change when real income remains constant. The

relative price coefficients measure the specific substitution effect which accounts for the

n price changes on the demand for the ith product, or equivalently, the effect of such a

change when the marginal utility of income remains constant. The general substitution

effect(- 00,Oj ), which serves as a deflator of the specific substitution effect by

transforming the absolute prices into relative prices, accounts for the Frisch price index

changes on the demand for the ith product.

If the relative price coefficients v, and v,, are both positive, it means that an

increase in the relative price of either product raises the demand for the other, and thus

the two products are called specific substitutes. Similarly, if v and vj, are both negative,

it means that an increase in the relative price (opportunity cost) of either product reduces

the demand for the other, or thus the two products are called specific complements.

The Hicks's definitions of net substitutes and net complements are based on the

signs of n-,. The sign of the parameter rn determines if products i and j are net









complements r, < 0 or net substitutes r, > 0. In terms of the Slutsky

equation, qj, /9p, = (qj, /9p,) q, (Sq, /1m), if the substitution term, (q, 1/p, ) > 0 for

net (or Hicksian) substitutes, and (aq, /p, ) < 0 for net (or Hicksian) complements.

While the Slutsky price coefficients provide the net substitution effects when real

income remains constant, the relative price coefficients provide the same effects when the

marginal utility of income remains unchanged. The concepts of net substitutes and

complements focus solely on the substitution effects.

The statistically significant relative and Slutsky cross price coefficients are

presented in Table 5.5. Most of these products are substitutes. The difference between

the coefficients of the relative and absolute price coefficients in terms of magnitude is

small. This implies that the general substitution effect is small. The general substitution

effect is concerned with the competition of all products for an extra dollar of the

consumer's income.

Contrary to expectation, the cross price effects of products that belong to the same

group are not necessarily greater than the cross effects of products that belong to different

product groups. For example, the cross price effect of U.S. grapefruit/ROW grapefruit

juice is smaller than that of U.S. grapefruit /U.S apple juice. Furthermore, products that

belong to the same product group are not necessarily substitutes. For example, U.S.

apple/ROW apple that belong to the same product group are complements.

Based on the cross price effects of substitute products, we can identify the market

structure of fruit juice in Japan (Figure 5.6), showing that there are both direct and

indirect competitions based on the country of origin. Recall that the direct competition

refers to the competition between products within the same juice group (e.g., orange juice










group) while the indirect competition refers to the competition between products in

different juice groups (e.g., orange juice and apple juice). Except for grape juice, there is

no direct competition in Japan's fruit juice market. The indirect competition appears to

be more important than the direct competition in Japan's fruit juice market.

Table 5.5: Parameter estimates of cross prices of fruit juices in Japan
Products Relative price coefficients Slutsky coefficients


U.S. orange/Brazilian orange
U.S. orange/ROW grapefruit
U.S. orange/U.S. apple
U.S. orange/Philippines pineapple
U.S. orange/Israelis citrus
U.S. orange/ROW citrus
Brazilian. orange/Chinese apple
Brazilian orange/ROW apple
Brazilian orange/ROW p. apple
Brazilian orange/Israelis citrus
ROW orange/U.S apple
ROW orange/ROW apple
ROW orange/Argentinean grape
U.S. grapefruit/ROW grapefruit
U.S. grapefruit/U.S. apple
U.S. grapefruit/Thai. pineapple
U.S. grapefruit/Philippines pineapple
U.S. grapefruit/U.S. grape
U.S. grapefruit/ROW grape
Israelis grapefruit/Italian citrus
ROW grapefruit/Italian citrus
U.S. apple/ROW apple
U.S. apple/Philippines pineapple
U.S. apple/ROW pineapple
U.S. apple/Argentinean grape
U.S. apple/Israelis citrus
U.S. apple/ROW citrus
Chinese apple/ROW pineapple
Chinese apple/U.S. grape
ROW apple/Israelis citrus
Philipp. pineapple/Argentinean grape
Philipp. pineapple/ROW grape
Philipp. pineapple/Israelis citrus
ROW pineapple/Argentinean grape
U.S. grape/Argentinean grape
U.S. grape/ROW citrus
*** (**)* significance at 1%, 5% and 10%


Estimates
0.0395
-0.0089**
0.0309**
0.0087**
-0.0158**
-0.0107**
-0.0701***
-0.1769***
0.0304***
0.0076
0.0129**
0.0216**
0.0036*
0.0102***
0.0230**
-0.0188***
-0.0146***
-0.0161*
0.0194**
0.00467**
-0.0043***
-0.0445**
0.00649**
-0.0143***
-0.0177***
-0.0127***
0.0097**
-0.0066
0.0211**
0.0127*
0.0050***
0.0069*
0.00477**
0.0055***
0.0108**
0.0085**


SE
0.0296
0.0040
0.0126
0.0044
0.0062
0.0052
0.0236
0.0402
0.0099
0.9335
0.6936
0.0103
0.0022
0.0030
0.0096
0.0035
0.0034
0.0091
0.0095
0.0020
0.0013
0.0178
0.0031
0.0046
0.0035
0.0045
0.0047
0.0043
0.0087
0.0080
0.0019
0.0039
0.0021
0.0017
0.0043
0.0039


Estimates
0.0822***
-0.0086**
0.0338***
0.0088**
-0.0155**
-0.0103**
-0.0101
-0.0754**
0.0211**
0.0134*
0.0132*
0.0221**
0.0036*
0.0106***
0.0267***
-0.0185***
-0.0144***
-0.0155*
0.0209**
0.0046**
-0.0043***
-0.0377**
0.0066**
-0.0149***
-0.0176***
-0.0123***
0.0103**
-0.0072*
0.0218**
0.0133*
0.0050***
0.0070*
0.0047**
0.0054***
0.0108**
0.0086**


SE
0.0259
0.0040
0.0128
0.0044
0.0062
0.0052
0.0207
0.0354
0.0085
0.0080
0.0069
0.0102
0.0022
0.0030
0.0096
0.0035
0.0034
0.0091
0.0095
0.0020
0.0013
0.0176
0.0031
0.0046
0.0035
0.0045
0.0047
0.0042
0.0087
0.0079
0.0019
0.0039
0.0021
0.0017
0.0043
0.0039













Table 5.6 Market structure of fruit juices in Japan


Country


Brazil


U.S.


U.S.


Orange


Brazil


Grapefruit


U.S.


Israel


Israel I I I I I I


Apple
U.S. China

SS


Pineapples
Thailan Philipp
d ine


Grapes I Other citrus


U.S.


Argenti Israel Italy
na


4.4 14 441444


U.S.

China


Thailand I


Philippin
es


9* 11


Argentin
a


V 1


Israel


a-,


I I


Italy I Iss I I


4 1 4 4 4. 6 4 1


9 I 9 9 9. I 9 I


SS SS S


SS


Product


Orange


Grapefruit


Apple


Pineapple


grape


Other citrus


SS


Italy


SI SSI









Results also indicate that the relative price coefficients and the Slutsky own price

coefficients are all negative and significantly different from zero except for the ROW

apple juice (Table 5.7). Contrary to expectation, the own price coefficient of the ROW

apple juice is positive but not statistically significant. The negative signs are consistent

with demand theory since they ensure the negativity of the own substitution effect.

Table 5.7 Parameter estimates of own prices of fruit juices in Japan
Juice Relative price Slutsky price
coefficients (v,) coefficients (zn)
Estimate SE Estimate SE

U.S. oranges -0.1139*** 0.0222 -0.1118*** 0.0224
Brazilian oranges -0.9667*** 0.1275 -0.0791 0.0861
ROW oranges -0.0469*** 0.0053 -0.0469*** 0.0053
U.S. grapefruits -0.0471*** 0.0131 -0.0436*** 0.0131
Israelis grapefruits -0.0142*** 0.0045 -0.0142*** 0.0045
ROW grapefruits -0.0079*** 0.0015 -0.0078*** 0.0016
U.S. apples -0.0308* 0.0177 -0.0268 0.0180
Chinese apples -0.0439*** 0.0135 -0.0398*** 0.0134
ROW apples 0.0116 0.0383 0.0233 0.0371
Thai pineapples -0.0095*** 0.0021 -0.0095*** 0.0021
Philippine pineapples -0.0231*** 0.0020 -0.0231*** 0.0020
ROW pineapples -0.0057** 0.0027 -0.0057** 0.0027
U.S. grapes -0.0523*** 0.0126 -0.0522*** 0.0126
Argentinean grapes -0.0059 0.0038 -0.0058 0.0038
ROW grapes -0.0409*** 0.0149 -0.0402*** 0.0149
Israelis other citrus -0.0221*** 0.0042 -0.0220*** 0.0042
Italian other citrus -0.0202*** 0.0044 -0.0202*** 0.0044
ROW other citrus -0.0239*** 0.0026 -0.0238*** 0.0026
*** (**)* significance at 1%, 5% and 10%

Expenditure Elasticities

The value of income flexibility is estimated to be =-1.8126. The reciprocal of

this coefficient, which is the value of the income elasticity of the marginal utility of

income is 1/0= -0.5517. This estimate is consistent with the estimates of Frisch (1959)

for the richest section of the population. According to Frisch (1959), a value of 1/0=-0.7









is for the better off part of the population. Since Japanese consumers are among the

richest in the world, a value of 1/0= -0.5517 obtained in this study is a reasonable

estimate for Japan.

The expenditure elasticities are calculated at the sample means of expenditure

shares of the respective imported fruit juices using the equation 77 = 8, /w, where 0, is

the marginal value share of product i and wj is the average value share of the same

product. Expenditure elasticities of imported products are useful to provide guidance for

marketing strategies and policy making in exporting countries.

The estimates of the expenditure elasticities are positive except for those of the

Israelis grapefruit juice and the ROW pineapple juice (Table 5.8). However, the

expenditure elasticity of Israel's grapefruit juice is statistically insignificant while that of

the ROW pineapple juice is statistically significant. Thus, we can conclude that the

Israelis grapefruit juice is not an inferior product while that of the ROW pineapple juice

is an inferior product.

Among the 18 fruit juices, only the demand for Brazilian orange juice is

expenditure elastic (2.7522). All four major fruit juices (orange, grapefruit, apple and

grape juices) that the U.S. exports to Japan are expenditure inelastic, implying that there

is less preference for the U.S. juices. The expenditure elasticities of U.S. exports range

from 0.1302 for grape juice to 0.8252 for apple juice. The demand for these products

exported by the rest of the world is also expenditure inelastic.

The high expenditure elasticity of Brazilian orange juice and low expenditure

elasticities of U.S. and the ROW products is not surprising given that Brazil's share of

the total import expenditure is very high compared to that of other countries. The









average expenditure share of Brazilian orange juice is 25% while that of U.S. ranges from

5% for apple juice to 8% for grapefruit juice (Table 5.1). The average expenditure share

of fruit juices imported from the ROW is the smallest except for that of apple juice,

which accounts for about 17% of the total import expenditure on imported fruit juices.

The major exporting country of apple juice in the category of the ROW is Austria.

Table 5.8 Expenditure elasticity estimates of fruit juices in Japan
Product Estimate SE

USA orange 0.4654*** 0.1390
Brazil orange 2.7525*** 0.1467
ROW orange 0.1047 0.1789
USA grapefruit 0.5463*** 0.0967
Israel grapefruit -0.0630 0.2300
ROW grapefruit 0.4603 0.3115
USA apple 0.8252*** 0.2189
Chinese apple 0.6504*** 0.1267
ROW apple 0.4842*** 0.0963
Thailand pineapple 0.4048* 0.2158
Philippines pineapple 0.3212 0.2954
ROW pineapple -0.8262** 0.4060
USA grape 0.1301 0.1226
Argentina grape 0.1921 0.2670
ROW grape 0.2912*** 0.1031
Israel other citrus 0.2065 0.1491
Italy other citrus 0.1153 0.1582
ROW other citrus 0.2578 0.1649
*** (**)* significance at 1%, 5% and 10%

The high expenditure elasticity may imply that there is a strong preference for

Brazilian orange juice, and that it is a luxury product. It also implies that as expenditures

on imported fruit juice increases, consumers change their consumption of Brazilian

orange juice more, in terms of percentage, than they change their consumption of the

same juice imported from the U.S. or the rest of the world. Furthermore, these results

have important implications for exporting countries in terms of making export decisions

in light of the expansion and contraction of the Japanese market for imported fruit juices









because of the change in expenditure. Under a situation where the Japanese market for

imported fruit juices expands because of an increase in expenditure, Brazil will become

much better off. This is because as the Japanese market for imported fruit juices expands

because of increasing expenditure, Brazilian orange juice market share will increase more

than proportionately. Other Exporters will not be as well off since they are expenditure

inelastic.

Given that Brazilian orange juice makes up the larger proportion of the total

imports of fruit juices in Japan, a one percent increase in expenditure on imported fruit

juices results in a far greater increase in actual imports; and, its market share would

increase further upon the expansion of the Japanese market of imported fruit juices over

time. However, under conditions in which the economy goes to recession, or expenditure

growth slows down, Brazil will be worse off because, a given percentage decrease in

expenditure on imported fruit juices results in a far greater decrease in actual imports; and

its market share would decrease further upon the contraction of the market of imported

fruit juices over time because of its larger expenditure elasticity. The fact that recession

has been more frequent in Japan over the past few years requires Brazil to devise an

effective export strategy which takes account of the performance of the economy.

In addition to recession, the growth of population is another major factor

anticipated to affect the demand for imported fruit juices in Japan as a result of its aging

population. The population growth of Japan has turned negative in 2006 (Statistics

Bureau of Japan). With per capital income growing at 2% per annum and assuming that it

will remain constant until 2020, and population growth starting to take negative rate since

2006, the growth of demand for fruit juices imported into Japan is projected (Table 5.9).









The growth of demand for fruit juice in Japan is positive except for that of Israelis

grapefruit juice over the over the period 2006 through 2014. The demand for Israelis

grapefruit is negative not only due to the population growth but also negative expenditure

elasticity. Products which have positive expenditure elasticity will continue to grow at a

declining rate regardless of the negative growth of population except for U.S. grape juice

and Israelis and Italian other citrus juices. From the result of the simulation, it appears

that grape and other citrus juice will be more affected than the other juices. The demand

for Brazilian orange juices declined from 5.53% in 2005 when the growth of population

was 0.3% to 5.49% in 2006 when the growth of population turned negative. It will

continue to shrink over the period 2006 through 2020 while the demand for U.S. orange

is projected to shrink at 1.12.9 to 0.66% over the same period.

Among U.S. products, apple juice will grow at a higher rate (more than 1%) while

grape juice will grow at the smallest rate (less than 0.25%). These simulations were

made under the assumption that the growth of per capital income will remain constant at

2% per annum over the period 2006 through 2020. The increase in the growth of per

capital income will offset the decrease in population growth so that the decline in the

growth of demand may be checked. If income grows at more than 2%, demand may

increase, though population growth slows down. The prospect of the growth of demand

for fruit juices will depend on the growth of per capital income relative to the decline in

growth of the population. If both move in the same direction, the decline of the growth

rate of demand for fruit juices will be greater.