Technology gap, demand lag and trade : a case study on GM-Soybeans = Hiato tecnológico, rejeição de demanda e comércio internacional : um estudo de caso da soja transgênica

UNIVERSIDADE ESTADUAL DE CAMPINAS

INSTITUTO DE ECONOMIA

PAULO RICARDO DA SILVA OLIVEIRA

TECHNOLOGICAL GAP, DEMAND LAG AND TRADE: A

CASE STUDY ON GM-SOYBEANS

HIATO TECNOLÓGICO, LAG DA DEMANDA E

COMÉRCIO: UM ESTUDO DE CASO DA SOJA

TRANSGÊNICA

CAMPINAS

2016

UNIVERSIDADE ESTADUAL DE CAMPINAS

INSTITUTO DE ECONOMIA

PAULO RICARDO DA SILVA OLIVEIRA

TECHNOLOGICAL GAP, DEMAND LAG AND TRADE: A

CASE STUDY ON GM-SOYBEANS

HIATO TECNOLÓGICO, LAG DA DEMANDA E COMÉRCIO:

UM ESTUDO DE CASO DA SOJA TRANSGÊNICA

Prof. Dr. José Maria Ferreira Jardim da Silveira – orientador

Prof. Dr. David Streed Bullock – co-orientador

Tese apresentada ao Instituto de Economia da Universidade Estadual de Campinas como parte dos requisitos exigidos para a obtenção do título de Doutor em Desenvolvimento Econômico, na área de Desenvolvimento Econômico, Espaço e Meio Ambiente.

ESTE EXEMPLAR CORRESPONDE À VERSÃO FINAL DA TESE DEFENDIDA PELO ALUNO PAULO RICARDO DA SILVA OLIVEIRAI E ORIENTADA PELO PROF. DR. JOSÉ MARIA FERREIRA JARDIM DA SILVEIRA.

_______________________________________________ Orientador

CAMPINAS 2016

TESE DE DOUTORADO

PAULO RICARDO DA SILVA OLIVEIRA

TECHNOLOGICAL GAP, DEMAND LAG AND TRADE: A

CASE STUDY ON GM-SOYBEANS

HIATO TECNOLÓGICO, LAG DA DEMANDA E COMÉRCIO: UM

ESTUDO DE CASO DA SOJA TRANSGÊNICA

Defendida em 23/03/2016 COMISSÃO JULGADORA

A Ata de Defesa, assinada pelos

membros da Comissão

Examinadora, consta no processo de vida acadêmica do aluno.

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To all those people whom made the last four years seem too short…

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I would like to express the deepest appreciation to my committee chair Professor José Maria who has the attitude and the substance of a genius: he continually and convincingly conveyed a spirit of adventure in regard to research and scholarship, and an excitement in regard to teaching. Without his guidance this dissertation would not have been possible.

I would like to thank you Prof. Bullock for the hospitality and priceless contribution to improve the dissertation and guide through my fruitful visit to the University of Illinois.

In addition, thank very much for all my teachers and professors whose dedication can be seen as very important foundation to this work be built upon. I still believe in a better world, with better people and education is a reasonable way top get there.

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Surely, nothing can be more plain or even more trite common sense than a proposition that innovation […] is at the center of practically all the phenomena, difficulties, and problems of economic life in capitalist society (Schumpeter, 1939: 62).

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The last three decades was marked by several disputes and debates over the international trade of genetically modified organisms (GMOs). As national regulatory frameworks were built upon unilateral basis, many conflicts emerged from trading, opening a room for questioning the adverse effects of technology innovation and adoption on trade and wellbeing. Therefore, the central aim of this dissertation is to investigate the role of technological gap and demand lag on trade, in the context of high levels of technology hatred. The technology gap is the difference or technological distance of techniques employed by late-movers when compared with technology used by leaders. Likewise, the demand lag may be understood as the difference or technological distance of techniques employed by producers in exporting countries and level of acceptance or compatibility in destination markets. The GM-soybean case is interesting since it comprises all the relevant features to answer the key questions raised in this dissertation. The concentrate international market – in terms of both producing and consuming markets – along with distinct technological and regulatory postures across countries enables the analysis in spite of absence of disaggregated data on exports of conventional and genetically modified grains. By means of a gravity equation we empirically estimated the effects of the technology-gap and the demand-lag on bilateral trade flows of soybeans. In order to find theoretical basis for our analysis, we also carried out a concise literature review on related trade theories. From the theoretical perspective this dissertation points to the need of developing models to deal with different tastes among consumers from different countries and explicitly consider adverse technological effects in trade – i.e. effects beyond the common relation between innovation, efficiency and gains of market shares. The results confirm that both technological gap and demand lag had important impacts on bilateral trade of soybeans. Furthermore, results make clear that we need better theories to consider cases in which taste differences across countries play a role in bilateral trade.

Keywords: Bilateral Trade, Technology Gap, Demand Lag, Gravity Equation, Genetically Modified Organisms (GMO), Agricultural Economics.

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As últimas três décadas foram marcadas por inúmeros debates sobre o comércio internacional de organismos geneticamente modificados (OGM). Como os quadros regulatórios pertinentes foram desenhados de maneira unilateral, muitos conflitos surgiram no âmbito comercial abrindo espaço para se questionar o efeito adverso da inovação e adoção tecnológica no comércio e no bem-estar. Dado isto, o objeto central desta tese é investigar o papel do gap tecnológico e do lag da demanda no comércio sob o contexto de forte rejeição da demanda. O

gap tecnológico pode ser definido como a diferença ou distância entre a tecnologia utilizada

para produção em países atrasados (late-movers) quando comparada com a tecnologia adotada pelos país líderes. De forma similar, o lag da demanda pode ser entendido como a distância ou diferença da tecnologia adotada pelos países exportadores e o nível de aceitação ou compatibilidade nos mercados de destino. O caso da soja contem todas as características relevantes para o tratamento das questões levantadas neste trabalho. A concentração da oferta e da demanda nos mercados internacionais e padrões tecnológicos e regulatórios distintos entre os países possibilita a análise mesmo sem dados desagregados para exportação de grãos convencionais e transgênicos. Por meio de um modelo gravitacional nós estimamos de forma empírica os efeitos do gap tecnológico e do lag da demanda no comércio. Buscando-se bases teóricas, uma breve revisão da literatura sobre as teorias de comércio foi realizada. Da perspectiva teórica, a tese aponta para a necessidade de desenvolver-se modelos capazes de tratar preferências distintas entre os países e considerar explicitamente a possibilidade de efeitos adversos da tecnologia – isto é, considerar efeitos para além da relação usual entre inovação, eficiência e ganhos de mercado. Os resultados confirmam que tanto o gap tecnológico, como a o lag da demanda tiveram impactos importantes no fluxo bilateral de comércio da soja. Além disto, os resultados apontam para a necessidade de desenvolvimentos teóricos capazes de tratar de forma mais recorrente casos onde a diferença nas preferências sejam importantes.

Palavras-chaves: Comércio Internacional, Hiato Tecnológico, Rejeição da Demanda, Modelo Gravitacional, Organismos Geneticamente Modificados, Economia Agrícola.

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TABLE 1 – EXPORTS OF SOYBEAN SEEDS 2014 19 TABLE 2 -THE WORLD'S TOP 10 SEED COMPANIES 2010 20 TABLE 3 – WORLD EXPORTS OF SOY PRODUCTS BY COUNTRY (2014) 22 TABLE 4. HECTARE AREA PLANTED WITH GM-SEEDS BY COUNTRY (2013) 24 TABLE 5 – WORLD IMPORTS OF SOYA PRODUCT BY COUNTRY (2014) 29 TABLE 6 – UNITED STATES’ APPROVED GM SOYBEAN (2015) 35 TABLE 7 – ARGENTINA’S APPROVED VARIETIES OF GM SOYBEAN (2015) 39 TABLE 8 – BRAZIL’S APPROVED GM EVENTS OF SOYBEAN 41 TABLE 9- GM SOYBEAN APPROVED IN THE EU FOR FOOD AND FEED 47 TABLE 10 - CHINA’S APPROVED GM SOYBEANS 52

TABLE 11. UNEP-GEF COUNTRIES 56

TABLE 12 – TEST FOR SAMPLE SELECTION AND FIRM HETEROGENEITY BIASES 108

TABLE 13 – DESCRIPTIVE STATISTICS 115

TABLE 14 – ESTIMATES RESULTS 116

FIGURE 1 – EUROPEAN UNION APPROVAL PROCESS OF NEW GMOS FOR FOOD AND FEED 45

CHART 1 – EUROPEAN IMPORTS BY SOURCE (BILLIONS OF USD FROM 1990-2014) 63 CHART 2 – EUROPEAN COUNTRIES’ IMPORTS BY CLUSTER 67 CHART 3 – CHINA’S IMPORTS BY SOURCE (TONES 1990-2014) 69

BOX 1 – SUMMARY OF MAJOR ESTIMATES STEPS ... 109 BOX 2– MODEL’S VARIABLES DESCRIPTIONS ... 111

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Chapter I - The Private and Public Agents and Controversies Around GMOs ... 16

1.1 Soybean Industry Organization ... 16

1.2 Countries’ Regulatory Frameworks and Public Opinion Towards GMOs ... 31

1.2.1 Producing Countries: Regulation, Adoption and Consumers’ Perception ... 34

1.2.2 Importing Countries: Regulation, Adoption and Consumers’ Perception ... 43

1.3 Remarks ... 58

Chapter II – Technological Effects and Trade Theories ... 60

2.1 Evidences of Technological Effect on International Trade of GMOs ... 61

2.2 Trade theories and Dual-market System ... 79

2.2.1 The Ricardian Models of Trade and underlying role of technology ... 80

2.2.2 Firm Heterogeneity Models ... 87

2.2.3 Technological Gap and Trade ... 93

2.3 Theories of Trade and the Case of GMOs ... 96

Chapter III - Empirical Estimation ... 99

3.1 Method ... 99

3.2 Data ... 110

3.3 Results and Discussion ... 114

IV. Conclusions... 127

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The genetically modified organisms (GMOs) have been produced and exported since 1996, when the combination of scientific developments and genetic appropriability mechanisms enabled the first commercial production of GM-soybeans in the United States (US). The technology became rapidly available to other producing countries via trade in technology headed by large multinational seed companies. But, some important consuming markets have taken contrary positions to the production and consumption of genetically modified food, arguing mainly about high health, environmental and economic involved risks.

Together, Brazil, United States and Argentina accounts for approximately 87% of world exports of soybeans, and the European Union (EU) and China accounts for more than 83% of world imports. Noteworthy, it was possible for growers in United States and Argentina adopt GM seeds already in 1996. Policymakers in Brazil, on the other hand, took almost a decade to legalize cultivation from GM seeds. But, on the demand side, many European countries have been contrary to use of GM seeds in agriculture, encouraging the raising of trade barriers or even fully banning importation of food or contents deriving from genetic modified plants. In China, however, in spite of some few limitations to free trade of GM food, policymakers have passed no rules preventing the country of being a certain destination for GMOs, partially because of large amounts demanded by the internal processing and livestock industry.

In sum, the absence of multilateral bodies powerful enough to enforce a compromise, national policymakers ended up taking unilateral positions, in terms of approval, coexistence, labeling, and other issues related to GMOs production and trade. As expected, technology became a new source of trade conflicts lasting until today, as pointed by many applied studies.

Nonetheless technology has been an issue in trade models at least since the rise of Ricardo’s model. The baseline model assumes that countries make use of different technologies – or different production functions –, which become a source of comparative advantage (CA) leading to different degrees of specialization. More recent works have advanced in technology and trade mainly under the umbrella of firm heterogeneity and technology-gap models of trade. Current interpretations of Ricardo and firm heterogeneity model are similar to the extent they resort to the neoclassical tools. On the other hand, technology-gap models are based on the building blocs of evolutionary economics.

At first, innovation and adoption could be treated as a shock in neoclassical models, but the problem of different tastes leading to different trade patterns cannot be addressed straightly. Preferences has been treated as identical and homothetic in the form of Constant Elasticity of Substitution (CES) utility functions in these models.

However, we have enough evidences to believe that the case studied is not only impacted by relative productivity changes, but also by differentiated consumers’ perceptions of the technology across countries. In other words, consumers in different countries can have different tastes. Also important, they can demand more than goods, i.e., they can choose among different technologies based not only on price or efficiency criteria. Empirics show that this can be especially true if they are from high-income countries. That is important from both the empirical and theoretical perspective.

Many interesting questions arise from this simple case. First, how the technological change can impact trade flows? Will the first-movers have some advantage in the presence of technology hatred? Is it possible for a mover rip some benefits of late-adoption? What are the key variables impacting trade in the case of backward effects of technology? We believe that current theoretical frameworks cannot provide reasonable answers to these and other related questions.

Our central hypothesis to be assessed in this dissertation is that of technological innovation leading to a double effect in trade in the presence of asymmetrical adoption and acceptance of a particular technology. The first effect is the technology-gap in relation to the most advanced countries, and the second is the demand-lag1 in relation to consuming markets. The concepts of technology gap, i.e., how advanced or efficient a technology employed by producers in a country is when compared to most productive technologies available, and demand lag, i.e., how accepted a technology employed by producers in a country is by consumers in destination markets in a point of time, are very insightful to the purposes of this study. To the best of our knowledge these concepts were discussed firstly by Posner (1961), but have been neglected in the new developments of trade theory, perhaps because of the lack of cases in which these two effects play such a clear and opposing role.

One of the main goals of this dissertation, therefore, is to evaluate how technological gap and demand lag have been impacting on the bilateral trade in presence of unequal technology adoption and significant levels of technology rejection. We also seek to bring out the bottleneck of the inexistence of treatment for consumer preferences beyond the

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As it will be discussed latter on this dissertation, we can treat this distance or proximity as the other geographical costs relating to bilateral trade.

“corollary” of identical tastes within and across countries. Specific objectives include estimating trade elasticities for technology gap and demand lag for the case of soybeans from 1996 and 2012. Also, we will review literature on Ricardian, firm heterogeneity and technology-gap models discussing their overlays, divergences and contributions to explain the case of soybean trade. It is important to say this study is primary focused on identifying possible stylized facts, instead of developing a new theoretical approach to deal with the flaws in demand side modeling approaches as presented in neoclassical models 2.

We consider this particular experiment very important for several reasons. First, this seemingly unique case is very passible of recurrence with other agricultural commodities intend to be used as food and feed components. An example of analogous case, that is high-income countries revealing preferences for production means, is the increased demand for certified organic crops, decent work – e.g. no child labor, slavery, etc. – and more environment-friendly farming activities.

Likewise, technology is becoming more complex also outside the farm gates; at the same pace consumers are becoming more and more aware of production means used to manufacturing the goods they acquire. Complex technologies involve social, economic, ethical, ethnical, religious, environmental and health issues, which can potentially be new sources of trade conflicts between countries. Biotechnology itself has many others applications in different industries such as genetic improvement of animal and humans, development of organic materials and new pharmaceuticals.

Hence, this study can be valuable for both policymakers and private actors since better understanding the relation across innovation, technology adoption, market rejection and trade can improve decision-making and consequently wellbeing – adverse trade impacts will lead to unequal gains and losses across countries and to different actors.

This study contributes to current literature by raising issues about the role of consumer preferences, and the impacts of these preferences towards certain technologies in trade. We also advance by estimating the effects of demand lag and technology gap in the same model. In spite of the importance of these concepts for the study of agricultural production and trade, the technological-gap hasn’t been explicitly considered in empirical models. The combination of technology-gap theories, Ricardian models, and gravity equations are innovative to studies in this area as far as we know.

This dissertation is divided into four more chapters besides this introduction. In

chapter I, we bring out figures on GM-food production and outline the trade controversy foundations. The underlying goal of Chapter I is to show how the soybean global chain operates, how different agents see the new developments and how country authorities acted to mitigate increased commercial risks of adoption.

Chapter II introduces the major evidences of changes in the trade patterns from 1996-2012, and how theoretical developments can contribute to shed some light in the case of trade of GMOs. We present a discussion on technology and trade having as background models based on Ricardian and technology-gap theorists’ ideas. The main goal of this chapter is to provide the reader with the grounds to understand what occurred in soybeans market, and show how theorists that considered technology impacts on trade contributes to answering some of the questions we have raised so far. Additionally, the inadequacies or absence of treatment of particular points of our case are indicated for future treatment.

In chapter III we introduce and discuss the empirical results of the gravity equation highlighting how technological variables – technology-gap and demand-lag – impacted on GM soybeans trade from 1996-2012. The adopted estimating strategy is also described in Chapter III, including the gravity equation foundations, limitations and approaches we have employed in this particular study.

Finally, Chapter VI concludes the dissertation underlining the major findings from the theoretical and empirical perspectives and retaking points that can be of interest of policymakers and others decision makers. Also, considerations about open questions to be addressed in future research programs are outlined.

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GMO

In this chapter, we show how important players in international markets of soybeans held different views of the technology innovation in seed industry. In addition, the complexity of biotechnology developments and the resulting lack of compromise in terms of principles and regulation among countries are discussed.

This chapter is split into three more sections. Section 1.1 brings some figures on main global players and major characteristics of the commercial relations in soybeans markets. In Section 1.2, we discuss how complexity of biotechnology developments led to unilateral regulations on labeling and other issues. Section 1.2 explicit the role of policymakers in managing the commercial risk. Finally, section 1.3 concludes Chapter I.

1.1 Soybean Industry Organization

Soybean production has faced an upsurge in the last decades, mainly after the 1970s. The broad usage of soybean and its by-products – meal and oil – in several industrial processes is surprising, as long as soybean production in large scale is a relatively new activity. Historians usually consider the plant gained US farmers interest after 1940s and South Americans only by the 1980s (HighQuest & Soytech, 2011).

Global consumption has been pushed by high economic growth of developing world – especially East Asia – and the emergence of new uses, such as feedstock for biodiesel fuel production. Increased demand along with institutional speculation has been raising soybean prices remarkably in the last decades.

The primary product of soybean is soybean meal, whereas the RBD (refined, bleached, deodorized) soybean oil is a secondary product. Indeed, soybean oil is a residual product of soybean meal manufacturing after solvent extraction process is employed3. Over the past five decades, soybean meal has become the most available and preferred source of protein for animal feed manufacturers. The high level of protein (up to 50%), as well as low fiber content, make it especially good for poultry, swine, aquaculture and dairy and livestock cattle leading to rapid gain of muscle mass and weight.

Other efficient sources of protein such as fish, meat and bones in spite of high protein contents have considerable drawbacks. Fishmeal, for example, is significantly more

expensive and supply is unsteady. Moreover, it is often claimed that poultry acquire fish taste when feed with fishmeal. Meat and bone meals were the main source of protein for feeding before soybean meal came into scene. However, many countries have prohibited the use of these products in breeding especially after the so-called “mad cow” disease. In this way, we can say that steady supply, some intrinsic characteristics and changes in institutional rules related to food safety are the major factors behind sustained growth of consumption of soybean meal. There is no a perfect substitute in meal markets worldwide4.

However, soybean is usually considered an inferior source of oil because of its low content compared to other major oilseeds. Typically, the low prices and more reliable supply drives food processors and food service operators to use oil as an ingredient for baked and fried food, or for cooking oil production. However, drawbacks as trans fat content and availability of other better sources of vegetal oil (sunflower, canola and rapeseed) make this market less attractive than market for soybean meal. Noteworthy, developments in biodiesel industry have attracted more attention to soybean oil.

Although competition for soybean is weak among other vegetal protein sources, the crop compete for acreage with corn as they convey very similar growing conditions – hot, wet and humid climate with fertile lands for the highest yields. But, intense competition between corn and soybeans is more likely to be seen in the U.S. and Argentina, because of climate issues, rather than other markets such as Brazil.

Agents in the supply chain are settled out all over the world according to the nature of their activities. They are in general closer to large consuming and producing markets to rip benefits of reduced transportation costs. However, different processes of soybean production – such as seed production, growing, processing and manufacturing – can occur in different countries.

Major soybean producing countries are the United States, Brazil and Argentina. The larger crushers, feed and food manufacturers and a vast industry for animal breeding is also based in these countries. However, China and the European Union are the largest importers of soybean and have a small internal production when compared to volume demanded by their processing industries.

In general, an input sector (seed and crop protection industries overall), growers, logistic operators (elevators, crushers, trading companies, etc.) and consumers (feed millers, food processors and other consumers such as biodegradable plastics and biodiesel producers)

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The lack of substitutes will be reflected in our empirical exercise showing that imported quantity of other goods to produce meals is positively related with imports of soybean.

are the agents in the soybean value chain. In the case of new conflicting technologies, such as GMOs innovation, policymakers will also play a strategic role by establishing rules for national production and consumption.

The combination of high specialization or international labor division, clashing views of technology by different agents in the value chain and lack of multilateral regulation are the roots of trade impacts in the case of GMOs.

Seed Industry

The modern and multinational seed industry can be seen as the centerpiece of the GMO innovation. Actually, very often the history of GM-seeds in agriculture can overlap the history of global seed industry itself. This industry passed through a drastic transformation in terms of product portfolios and technology during the last decades.

Scientific and legal developments occurring in the 1980s brought forth a new technological trajectory – from common methods of seed selection and reproductions to the hybrid and the genetically modified techniques to selection of desirable intrinsic characteristics for the seeds (see Wilkinson & Castelli, 2000). The new technology and appropriability mechanisms required a completely new base of knowledge to the new developments. Specialists usually agree that we migrated from chemistry to biology-based innovation trajectories.

Unsurprisingly, the new challenges called for a general movement of merging and acquisitions, as part of companies’ effort to be competitive in face of the new scientific and economic requirements. Before 1970s, the seed industry was primary regional with small-scale firms replicating seeds developed under public domain. A large fraction of famers used to save their own seeds, since legal framework for appropriability or substantial scientific innovations weren’t significant at the time. In the 1970s, after transgenia and appropriability came into scene, seed industry turned out to be more concentrated and international, pursuing profits not only from their day-to-day replication activities but also from royalties of specialty varieties (Wilkinson & Castelli, 2000). However, the big clash will come to international trade chains in 1996, with the first commercial release of Monsanto GM-soybean. Table 1 shows the major exporting countries of soybeans seed in 2014.

Table 1 – Exports of soybean seeds 2014

Exporter Trade Value (US) % of world

exports. Accumulated % USA 51,120,057.00 30.21 30.21 Argentina 28,041,752.00 16.57 46.78 Canada 26,145,221.00 15.45 62.23 Paraguay 12,242,793.00 7.24 69.47 Malaysia 7,269,400.00 4.30 73.77 Chile 6,242,947.00 3.69 77.46 Uruguay 4,696,756.00 2.78 80.23 Brazil 4,315,733.00 2.55 82.78 India 4,175,584.00 2.47 85.25 Zambia 2,891,612.00 1.71 86.96

Note: Code HS12 120110 was selected to return these data. It was only possible to segregate seed and grain data internationally after the adoption of HS12 classification system.

Source: Elaborated by the authors based on Comtrade database (2015).

Top 5 countries exporting seeds accounted for 73.77% of world exports in 2014. As it can be seen, seed companies with higher international presence are based in the United States and they accounted for 30% of global exports of seed in 2014. The United States are followed by Argentina (16.57%), Canada (15.45%), Paraguay (7.24%) and others (30%). To a certain extent the global importance of seed industry in each country can be seen as a reflection of how long countries took to allow production of GMOs in their territories. Brazil, for instance, authorized the growth of GMOs a decade later the first commercial release and stand for the 8th position in the global seed exporters rank, accounting for only 2.55% of world trade.

It is worth noting that seed exports are not expressive when compared to soybean trade because much of the seeds grew in major producer countries are nationally produced.

From a broader perspective, the commercial seed market can be divided into proprietary and non-proprietary. Simplistically, the first comprehend seeds owned and marketed by brand companies while the second comprehends seeds traded by local farmers or plant breeders – the common situation prior to the 1970s. Accordingly to estimates from International Seed Organization (ISO), 85% of commercial seed market is proprietary nowadays, a sign of the economic power of these companies in global food chains. Table 2 shows the Top ten firms operating in the seed industry, their annual sales and shares of global proprietary seed market in 2010.

Table 2 -The World's Top 10 Seed Companies 2010

Company – 2010 Seed sales (USD billions) % of global proprietary seed market

Monsanto (US) 4.964 23%

DuPont (US) 3.300 15%

Syngenta (Switzerland) 2.018 9% Groupe Limagrain (France) 1.226 6% Land O' Lakes (US) 917 4%

KWS AG (Germany) 702 3%

Bayer Crop Science (Germany) 524 2% Sakata (Japan) 396 <2% DLF-Trifolium (Denmark) 391 <2% Takii (Japan) 347 <2% Top 10 Total 14,785m 67%

[of global proprietary seed market]

Source: ETC Group

As it can be seen, the top 10 firms already accounted for more than 67% percent of the global proprietary seed market in 2010. This structure has direct impacts on the pace of technological diffusion, as trade in technology became globally available very quickly and these companies could control the availability of conventional seeds in the largest agricultural producing countries as large-scale farmers have been increasingly dependent on the proprietary seed market. Moreover, they could put together a higher amount of resources to lobby other agents including policymakers.

The predominant strategy used by giant seed companies has been both heavy investments in R&D and merger and acquisitions of companies with know-how or large market-share in areas of interest (Howard, 2009). Innovations have pursued to boost production yields, cut down production costs and deliver nutritional profiles and value-added traits desired by consumers – industrial and individual ones.

Monsanto, which had more than 23% of global seed markets in 2010, turns out to be a key player only from the 1980s. Besides patenting technologies the company acquired over 50 seed companies between 1996-2013. Some important acquisitions comprehend Delta & Pine land (1.5 USD billions), Cargill’s5 International Seed Division (1.4 USD billions) and Holdens’s Fondation Seeds (1.02 USD billions). DuPont major acquisition was Pionner Hi-Bred, the world’s largest seed company at the time. However, DuPont strategy has involved more customized agreements with some of the largest remaining independent seed companies to share germplasm. The other companies adopted very similar strategies to gain market shares and keep sustained increasing returns (Howard, 2009).

The economic power of seed companies come not only from economic concentration but also from their ability to coordinate activities between themselves (mainly R&D) and vertical integration downstream and upstream to farming activities, such as partnerships with processors, which allows easy identification of their needs and increased proximity with farmers worldwide. Monsanto and Cargill partnership is only an example of seed companies engaging in partnerships with processors. GreenLeaf Genetics is an example of a partnership between two seed companies to sell foundation seeds6.

These companies also sell or develop partnerships with sellers of crop protection inputs. Indeed, usually they don’t sell a particular seed but a technological package, meaning herbicides and insecticides that work along with plants with specific traits.

But, even though seed companies have bargaining power to influence important actors determining most of the direction and pace of technological innovation, they cannot fully control end-consumers aversion to the technology and the design of the national regulatory frameworks.

In sum, this partial power to coordinate agents all over the value chain and the absence of effective multilateral regulation will be constant source of increased commercial risk and/or opportunity costs for producers that serve markets with certain levels of technology hate. In other words decisions taken by the seed companies in terms of the pace and scope of the new developments, as well their ability to coordinate innovation and adoption will impact the entire value chain in many ways.

Growers

The major producing countries – namely United States, Brazil7 and Argentina – accounted for respectively 35.02%, 28.13% and 17.31% of world total soybean production in 2014. These three leading producers were followed by China (3.96%), India (3.41%) Paraguay (3.23%), Canada (1.96%), Ukraine (1.06%) and Uruguay (1.03%) (FAOSTAT, 2015). Data on shares of world exports are provided in Table 3.

Besides the US, Brazil and Argentina (the G3 hereinafter) a sub-group of countries also play considerable role in international markets of soya products, given their expressive exporting and production volumes. This group is made up of Canada, Paraguay,

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Foundation seed is seed so designated by an agriculture experiment station. Its production must be carefully supervised or approved by representatives of an agricultural experiment station. It is the source of all other certified seed classes, either directly or through registered seeds (Rice Knowledge Bank, 2015).

7 _{Note that Brazil is the only giant producer of soybeans that has no expressive role in international markets of}

soybean seeds. As we have argued before, this may be a result of later approval for GMOs cultivation in the country.

India, Ukraine, China, Bolivia and Uruguay - the G7 hereinafter. These countries together accounted for 20.30% of world production of soybeans in 2013 (FAO, 2015).

Not surprisingly, besides being leaders in soybean exports, the G3 are also the largest exporters of the two major by-products, soybean meal and oil. Argentina has a noteworthy position in meal and oil markets, which can be partially explained by the country tax policy, which favors exports of meal and oil instead of soybeans. On the other hand, Brazil and US export more soybeans than oil and meal, supplying markets with large crushing capacity such as European Union (EU) and China.

Table 3 – World Exports of Soy Products by Country (2014)

Soybeans (HS12 – 120190)

Exporter Trade Value (USD trillion) % of world share Accumulated

USA 24.206 41.0% 41.0% Brazil 23.273 39.0% 80.0% Argentina 3.748 6.0% 87.0% Paraguay 2.292 4.0% 91.0% Canada 1.756 3.0% 94.0% Uruguay 1.616 3.0% 96.0% Ukraine 0.701 1.0% 98.0%

Flour and Meal (HS12- 230400 and 120810)

Argentina 11.853 35.61% 35.61% Brazil 7.000 21.03% 56.65% USA 5.476 16.45% 73.10% Netherlands* 2.151 6.46% 79.57% India 1.292 3.88% 83.45% China 1.181 3.55% 87.00% Paraguay 1.109 3.33% 90.34% Oil (HS12 - 150710 and 150790) Argentina 3.467 41% 41% Brazil 1.129 13% 54% USA 0.806 9% 63% Paraguay 0.481 6% 69% Spain* 0.415 5% 74% Netherlands* 0.375 4% 78% Germany* 0.328 4% 82% Bolivia 0.293 3% 85%

Notes: Both codes 230400 and 120810 are used in HS for meal and flour. Code 120190 was adopted after HS12 version and exclude soybean seeds (120110), previously classified in a single code 120100. Oil different codes only discriminate between refined (150790) and crude (150710). Countries marked with “*” are processors or distribution ports as they don’t produce meaningful amounts of soybean.

Specialists usually agree that soybean production in Brazil and Argentina has cost advantages when compared to production in the United States. That would be a reason behind the increasing market share of Brazil and Argentina over the US shares (HighQuest & Soytech, 2011). However, there are other differences explaining how importers (crushers and processors) decide upon where to source their soybeans such as the level of foreign material, moisture, beans integrity, protein and oil content.

The discrimination between GM and conventional seeds are the additional setback the seed technology industry put to growers’ decision making. Actually, the modern version of this problem is set in term of which GM variety is being produced and approved for importation in different countries. Considering low variability of prices and traditional quality standards across major producing countries, such a discrimination seems to have been played an underlying role in deciding from where to source soybean in the last decades – as we are arguing in this Ph.D. dissertation.

Brazil was the only country from the G3 group that has taken almost a decade to approve production of GMOs internally. There are two equally valid explanations for that. First, the legal moratorium was effective in prohibiting farmers to grow GM-seeds until 2005. We know it can be only partially true on account of growers in south of Brazil have started planting GM-seeds by the late-1990s, making use of pirate seeds smuggled from Argentina. Second, the first GM-seeds weren’t good enough for tropical regions, performing poorly in terms of yield. This explanation seems very plausible if we consider the lobby of large farmers in Brazil. As soon as these farmers could see any significant rewards in growing genetically modified seeds in Brazilian Middle West, they would fight for GMOs liberalization – as happened in the early-2000s.

On the other hand, U.S. and Argentina growers are ripping the benefits and paying the costs of planting GM-seeds since 1996. U.S. has notably higher average yields per hectare than Brazil, as a result of more capital-intensive production means. The existence of a large producer supplying large amounts of conventional soybean along with adverse markets demanding GM-free products created a dual-market system – i.e. a market for GMOs and another for conventional crops. However, with the Brazilian Biosafety Law of 2005, dual-market basis will be significantly weakened by a severe reduction on supply of conventional soybean. Adoption in Brazil was rapid in pace, making the country the second largest country in terms of planted area with GM-crops already in 2013, as can been in Table 4.

Table 4. Hectare area planted with GM-seeds by country (2013)

Rank Country Area (millions of hectares 2013)

Area (millions of

hectares 2013) Crops

1 United

States 70.1 73.1

Maize, soybeans, cotton, canola, sugar beet, alfalfa, papaya, squash

2 Brazil 40.3 42.2 Soybean, maize, cotton

3 Argentina 22.9 24.3 Soybean, maize, cotton

4 India 11 11.6 Cotton

5 Canada 10.8 11.6 Canola, maize, soybean, sugar beet

6 China 4.2 3.9 Cotton, papaya, poplar, tomato, sweet pepper

7 Paraguay 3.6 3.9 Soybean, maize, cotton

8 Pakistan 2.8 2.9 Cotton

9 South Africa 2.9 2.7 Maize, soybeans, cotton

10 Uruguay 1.5 1.6 Soybean, maize

11 Bolivia 1 1 Soybean

12 Australia 0.6 0.5 Cotton, canola

13 Philippines 0.8 0.8 Maize 14 Myanmar 0.3 0.3 Cotton 15 Burkina Faso 0.5 0.5 _Cotton 16 Spain 0.1 0.1 Maize

17 México 0.1 0.2 Cotton, soybean

18 Colombia 0.1 0.1 Cotton, Maize

19 Chile <0.1 <0.1 Maize, soybean, canola

20 Honduras <0.1 <0.1 Maize

21 Portugal <0.1 <0.1 Maize

22 _Republic Czech <0.1 <0.1 Maize

23 Poland <0.1 <0.1 Maize

24 Egypt <0.1 <0.1 Maize

25 Slovakia <0.1 <0.1 Maize

26 Costa Rica <0.1 <0.1 Cotton, soybean

27 Romania <0.1 <0.1 Maize

Source: James (2014)

Table 4 shows that the three largest soybean producers also figures among the largest world producers of GMOs. However, countries adopted technology in different times, for different crops and varieties as we are going to discuss in more details in the next section.

Considering their strategic position in the supply chain, farmers acquire seeds from input industries to carry out their core activities. Usually, along with seeds farmers are also choosing part of other technologies. Although farmers can be substantially different worldwide in terms of size or technology-level, the new shape of soybean value chain has certainly decreased their scope of decision, especially in terms of choosing across different varieties of the same crop.

Decisions are made considering legal approvals at home, costs – including the overall costs of technological package – yield delivered given the environment conditions, and crusher’s acceptance of available varieties. In other words, seed industry, crushers, food and feed processors, and policymakers have been playing a more central role in technology development, adoption and acceptance. By the end of the day these agents determine the premiums and penalties related to different seeds adoption, and growers respond accordingly to their rationale of higher returns. We can sum up the role of growers in global trade as to produce as many as soybeans as possible.

Grain elevators, Domestic Crushers and Trading Companies

Grain elevators are usually complete receival points comprehending activities like receiving, testing, weighting and storing grains until selling them to crushers or other elevators. They are called this way because they scoop up grains from lower level into silos or other storage facility. There are many types of elevators, but from a broader perspective they can be classified as country and exporting elevators – also called exporting terminal.

Country elevators sell to other larger elevators in the country or processors whereas export terminals sell beans to trading companies, international processors or end-consumers in international markets. As this study deals with soybean trade we are mainly concerned about GM-soybeans being exported to be processed in countries averse to the technology.

Domestic processors or crushers are companies carrying out all activities from handling and elevating to extraction of soybean meal and crude degummed oil. As cited before, hexane extraction is the most common method employed to produce soybean meal and have oil as a residue8. Domestic processors buy soybeans from country elevators and sell soybean meal and oil to end-consumers in the country or abroad – directly or through trading companies.

8 _{Other extraction methods like mechanical press can delivery a higher quality oil but affects productivity of}

Export terminals, in turn, acquire soybeans from country elevators or growers to sell to trading companies or direct to countries with high crushing capacity – such as the EU and China. Very often country elevators, crushers, exporting terminals and trading companies are controlled by the same corporations making difficult to breakdown their activities and commercial relationships. ADM, Bunge, Cargill, Louis Dreyfus, AGP and CHS are important players controlling grain distribution activities all over the world.

Countries differ substantially in terms of presence and size of these agents. Brazil and Argentina, for instance, are more likely to sell the grains to domestic processors or export terminals as these countries have less complex logistic operations. Otherwise, U.S. growers usually sell to country elevators, making soybean pass through at least 3 or 4 operators before entering the exporting market.

The better infrastructure in the U.S. cuts down logistic costs but has some quality drawbacks because of the higher levels of foreign materials and breakage of beans, resulting from over handling. On the other hand, U.S. growers gain as they can sell FOB9 to elevators operating nearby their farmers, which requires much less expertise in logistic issues. Many specialists consider logistic advantages partially pay down lower production costs in South America – due to relatively lower wages and land prices.

Just to provide a better picture of the relative importance of these agents, let’s take into account some estimates from the American Soybean Association (ASA). According to them, U.S. processors purchased on average 55% of all soybeans domestically produced from 2006 to 2010. Export terminals purchased 36% and cattle breeders 5%10. Processors, likewise country elevators, are mainly sited closer to large producing or consuming areas around the world.

Export terminals, otherwise, are located in ports of easy access to growers or elevators in major producing regions. They seek to minimize overall costs of transportation and storage at the same time they mitigate the transaction costs related to moving soybean from a country to another. Thus, these companies have offices, facilities and others branches in both major producing and consuming countries and often sell to their own affiliates.

The concentration and hierarchical control in distribution can be partially explained by high risks involved in these activities. Besides soybean is normally considered a commodity, transactions in the segment can be often considered complex. Indeed,

9 _{Free on board price.}

coordination in agro-food chains in general has been considered complex mainly because of high risks involved in farming.

Considering the risks from the standpoint of transaction costs, the more agriculture assets become specific the more complex transactions will be. Frequency and uncertainty are also other two issues to be considered. Even before the GM-seeds came on the scene, other qualities criteria, the significant economies of scale – calling for operating at full capacity – overall level of uncertainty, and market concentration were far enough to make soybean chains complex. Nonetheless, it is very clear that GM-seeds created one more source of asset specificity. For each different variety of soybeans emerging a result of innovation in seed industry, we have an increased range of similar but different products in the marketplace11.

Therefore, logistic operators and soybean processors – often the same agent – are managing significant part of the risks related to production and trade of soybean. They depend on many independent growers to keep their activities at full capacity. They usually play a very important role in assuring or achieving quality standards and in IP (identity preservation). They have a strategic position not only between end-consumer (domestic and international ones) but also between input industry and farmers – being common to processors and seed companies commit themselves in partnerships. Last but not least, they are subjected to different national regulatory frameworks to carry their grains from producing to processing countries.

In sum, these corporations are in charge of managing national and international growers decisions to guarantee their supply of soybeans to operate at full capacity. In the relationship with seed industry they signalize what their needs are, in terms of output traits – higher oil or protein content for instance – and also input traits demanded by growers given their closeness to them. Other important role is to align premiums they pay to growers that are producing varieties they demand and royalties paid by growers to seed companies. Moreover, they are also a key agent in monitoring royalties’ payment as they can easily test varieties they acquire and request documents to proof that seeds were obtained by legal means.

11

This idea is not only realistic but convenient for theoretical and empirical analysis, since monopolistic competition is a good representation for markets like this.

External Processors, Feed millers and Food Processors

After been grown and/or processed soybean and by-products follow to internal consumption or exports. As we have seen, soybeans are mostly used to produce feed and food contents. Feed is produced from soybean meal and used as protein source especially for poultry, swine, aquaculture and diary cattle breeding. Food ends include consumption of beans, flours, oil, among others, and alternative source of protein. Many food products have soybean products in their composition, for example the chocolate with soy lecithin.

More recently, soybean has been used as feedstock for biodiesel production and raw material in biodegradable plastic. Noteworthy, sometimes companies operating elevators, processing and trading activities also controls or have ownership of feed manufacturing facilities and other end-consumers – e.g. the Cargill corporation operating in feed sector.

In general, countries with crushing capacity and low production of soybeans will be largest consuming markets of soybeans. That is the case of the European Union and China. Countries with large presence of feed processors, as a result of large animal breeding sectors, but without crushing capacity will be key markets to soybean meal. Lastly, large presence of food processors, biodiesel industry and low crushing capacity will determine the major importers of soybean oil. Very often countries are important players for both soybean and by-products markets given general gains of scope. Table 5 shows world largest importers, value of trade, percentage and accumulated percentage of world imports for soybeans, soybean meal and oil.

Table 5 – World Imports of Soya Product by Country (2014)

Soybeans (HS12 – 120190)

Exporter Trade Value (USD

billions) % of world share Accumulated

China 40.265 69.13% 69.13% EU-27 8.277 14.21% 83.34% Mexico 2.071 3.56% 86.89% Japan 1.831 3.14% 90.04% USA 1.149 1.97% 92.01% Turkey 1.119 1.92% 93.93% Thailand 1.076 1.85% 95.78% Egypt 1.057 1.82% 97.60%

Flour and Meal (HS12- 230400 and 120810)

EU-27 _13.311 51.92% 51.92% Thailand _1.676 6.54% 58.46% Japan _1.057 4.12% 62.58% Philippines _0.974 3.80% 66.38% Mexico _0.826 3.22% 69.60% Algeria _0.822 3.21% 72.81% Malaysia _0.790 3.08% 75.89% Egypt _0.644 2.51% 78.41% Peru _0.602 2.35% 80.76% Canada _0.515 2.01% 82.77% Oil (HS12 - 150710 and 150790) India _1.985 29.10% 29.10% China _1.092 16.01% 45.11% EU-27 _0.999 14.65% 59.76% Algeria _0.566 8.30% 68.06% Peru _0.335 4.92% 72.98% Mexico _0.190 2.79% 75.77% South Africa _0.158 2.33% 78.10% Dominican Rep. _0.129 1.90% 80.00% Pakistan _0.119 1.76% 81.76% Ecuador _0.119 1.75% 83.50%

Notes: Codes 230400 and 120810 have been used in international classification for meal and flour. Code 120190 was adopted after HS12 version and exclude soybean seeds (120110), previously classified in a single code 120100. Oil different codes only discriminate between refined (150790) and crude (150710)

The top 5 destinations together for each product accounted for 92.01% of soybeans, 69.60% of meal and flour and 72.98% of oil world imports in 2014. This level of concentration makes decisions in major markets a big deal for production and exporting decisions taken in sourcing countries – what we are naming as commercial risk. In this way, the EU large importing volumes combined with high levels of technology “hatred” is undoubtedly a source of trade conflicts (see Anderson & Jackson, 2004).

China (69.13%), Europe Union (14.21%), Mexico (3.56%) and Japan (3.14%) are currently the world major importers of soybeans. These countries have minor levels of soybean production, excluded China that is the fourth largest producer in the world, but still a net major importer. The European Union is also the major destination for soybean meal and flour (51.92% of world’s imports in 2014). Major oil importers are India, China and European Union, respectively.

Crushers in these countries are highly dependent on imports of soybean to supply soybean meal to feed and food manufacturers operating internally. Usually, these countries are also dependent on imports of soybean meal and oil, as national crushing capacity is not enough to fulfill internal demand by feed and food manufacturers.

From the perspective of commercial risks, end-consumers opposing to the technology in some of the major importing countries are the agents creating additional risks for the supply chain given the presence of genetic engineered seeds in marketplace, even in the absence of legal barriers. Again, because of contrary position of manufacturing industry – a result consumers’ aversion of soy products along with strict government regulations – logistic operators and processors in sourcing countries have to plan their production strategies also based on technological rejection worldwide.

As we have been arguing consumers’ aversion to products of GMOs and government policies towards the technology adoption will play an underlying role in the level of commercial risks. Indeed, we defend that these two agents sustain many of the controversy established in the production chain. If not by the commercial risk related to the law and the end-consumer aversion to the technology we believe that processors and manufacturers would have no reasons to keep skeptical to the technology. These two additional burdens will be treated in the next section.

1.2 Countries’ Regulatory Frameworks and Public Opinion Towards GMOs

In this section we introduce the way in which the countries have been regulating GM production and trade during the past three decades of agricultural biotechnology developments. At first, regulation can be thought from the unilateral and multilateral perspectives. The latter is especially necessary when norms placed by national authorities in one country can potentially affect business and citizens as a whole in another country.

History has shown that many conflicts can emerge from international affairs, including those propelled by environmental, social, economic, ethical matters. The nature of the conflict should be taken into account, as the drivers and remedies for each type of dispute will depend on it.

Trade agreements determining sanitary and other technical standards for example, have mostly employed scientific-based approaches, whereas environment-based agreements have employed the precautionary principle to establish international standards and norms (Winham, 2009).

The precautionary principle states that the introduction of a new product or process, whose ultimate effects are disputed or unknown, should be restrict. In the absence of precautionary principle the matter can be treated under more pragmatic approaches, such as the substantial equivalence principle. Substantial equivalence states that a product containing comparable amounts of a few basic components, such as proteins, fats, and carbohydrates as its counterpart, should be considered as safe as the comparable one.

Modern biotechnology is particularly complex because its multi-issue profile. Ethical, environmental, economic and health issues have basically the same weight in terms of pros and cons. Consequently, regulation was spread out in few different agreements based on distinctive matters relating to this same technology.

These agreements, however, in spite of incomplete congruence in some specific points, are equally valid and their principles and guidelines can be claimed accordingly to the parts’ particular views of the technology. The contrasting scopes can partially explain the mismatches between rules enacted in World Trade Organization (WTO) agreements and the Cartagena Protocol for Biosafety (CPB). These are considered the main agreements on international regulation of modern agricultural biotechnology.

The Cartagena Protocol, opened for signatures in May/2000, is primarily focused on environmental risks. So, it is based on the precautionary approach and seeks to

“(…) contribute to ensuring an adequate level of protection in the field of safe transfer, handling and use of living modified organisms resulting from modern biotechnology that may have adverse effects on the conservation and sustainable use of biological diversity (…)”(Secretariat of the Convention on Biological Diversity, 2000).

Even though risks to human health are taken into consideration – as declared in other parts of the protocol – focus is kept on environment issues and monitoring of living modified organisms. Living modified organisms means that the organisms are capable of transferring or replicating genetic material. Currently 170 countries have signed the protocol, being worth noting that the United States and Argentina have not ratified it yet. This fact alone is enough to bring out the weakness of the Protocol to reach compromise among big players when it comes to commercial disputes.

On the other hand, the World Trade Organization (WTO) agreements and their reference to the Codex Alimentarius are clearly more scientific-based. Unsurprisingly, they are primarily focused on assuring harmonious trade of products involving sanitary, phytosanitary and other technical standards instead of potential risks involving environment and ethical issues.

Of course, these differences in scope and principles alone will be an obstacle to achieve harmonization of norms and procedures. Some countries can base their regulatory framework in a more scientific-based approach at the same time others can claim for the right of enacting precautionary measures.

One example of these incongruences is the establishment of minimum and maximum levels of protection and the possibility of claiming the so-called safeguard measures. The scientific-based approaches under substantial equivalence principle tend to offer a very limited space for safeguards and set up standard ceilings whereas precautionary approach, by taking into account uncertainty, set up standard floors.

Both Technical Barriers to Trade (TBT agreement of WTO) and Sanitary and Phytosanitary Measures (SPS agreement of WTO) came into force in 1995, at the very beginning of commercial production of GMOs. Time mismatch of regulation and conflicts may partially explains why GMOs are not straightly treated in the scope of these agreements. The SPS establishes a “…multilateral framework of rules and disciplines to guide the development, adoption and enforcement of sanitary and phytosanitary measures in order

to minimize their negatives effects on trade (SPS agreement text, emphasis mine) ”.

Alimentarius Commission – will provide the bases to guide the building of regulatory frameworks. The TBT seeks to ensure that

…technical regulations and standards, including packaging, marking and labeling requirements, and procedures for assessment of conformity with technical regulations and standards do not create unnecessary obstacles to

international trade (TBT agreement text, emphasis mine).

The UN Food Agriculture Organization (FAO) and the World Health Organization (WHO) established the Codex Alimentarius Commission or “Food Code” in 1962. Membership in Codex is open to all member nations of the United Nations (UN) and currently 165 countries participate. It has been developing a series of guidelines, including labeling rules to GMOs that may bring more harmonization to the field.

However, the current scenario makes clear that multilateral regulation failed in fully organizing the production and trade of GMOs. The complexity involving biotechnology, the lack of clear general standards for dealing with GMOs production and trade, the existence of a couple of agreements not always in congruence with one another, as well as the lack of more efficient sanction mechanisms, made country-level regulation the relevant part for understanding the state of affairs of GMOs.

National regulations differs in restrictiveness degree, type of approach or principle (scientific or precaution-based), type of basis (scientific or political), and liability (private or public sector)(Josling, Orden, & Roberts, 2004). A range of questions is treated by national regulations, such as approval process, coexistence rules, labeling regimes, traceability, liability schemes, and others. For our purposes approval process in producing and importing countries and labeling rules in importing countries in particular will be central questions.

We see countries regulatory profile as a result of internal disputes across different groups of interest, such as firms, consumers, Non Governmental Organizations (NGOs) and the government itself. That is why the largest agricultural countries tend to take more pragmatic regulatory posture whereas net importers of agricultural goods with high-income levels tend to implement more strict rules (P. R. S. Oliveira, Silveira, Magalhães, & Souza, 2013).

Accordingly, policymakers took two important dimensions into account when considering commercial risks of producing GMOs. First, the approval of many varieties can raise risks of producing events not approved in every destination countries. Second, even

with just a few approved varieties, if adoption rates are too high and logistic capacity for IP is poor the country can have problems in exporting to countries that are strongly averse to technology. Indeed, in the 1990s the pertinent dilemma was between the GM-Free vs GM as many manufacturers preferred to import conventional products as a precautionary measure in face of large supply amounts. After 2005, when Brazil finally allowed farmers to legally grown GM crops, the dilemma became one of asymmetrical approval, i.e. a risk of approving varieties not allowed for consumption in destination markets.

Needless to say, to keep IP of different GM varieties is a huge challenge considering current transportation structure based on large gains of scale. From a policymaking perspective, it is simpler to deny approval of varieties not accepted in the most important destination markets.

These polices implications show how policymakers became very important to keep commercial risks at a manageable level to middlemen – export elevators, processors and trading companies being very often owned by the same corporations. In other words, the absence of certain level of regulation and a less concentrate industry would make risk management much more complicated than it actually was.

1.2.1 Producing Countries: Regulation, Adoption and Consumers’ Perception

As we have been arguing the aftermaths of ongoing debates in each country resulted in different regulatory frameworks for global production and trade of GMOs. Only by considering the G3 countries we can see differences in regulation that will shape the new pattern of trade. The U.S. has approved a larger number of soybean varieties for cultivation and other processing uses when compared to Brazil and Argentina. The country also accounts for the highest global shares of GMOs production over the total agricultural outcome – i.e. considering all crops to which GM varieties are available (see table 4).

Table 6 shows the events, traits, developing company, purpose and year of approval for soybean varieties in the U.S..

Table 6 – United States’ Approved GM Soybean (2015)

Event Trait Company Authorized _For Food and Year Feed

Year Cultivation

ACS-GMØØ2-9*** Glufosinate herbicide _tolerance (including fully and partly Bayer CropScience owned companies) Cultivation n/a 1996 DD-Ø26ØØ5-3 Modified oil/fatty acid, Antibiotic resistance, Visual marker

DuPont Pioneer Feed/CultivaFood and tion

1997 1997

A5547-127 Glufosinate herbicide _tolerance Bayer CropScience Feed/CultivaFood and tion 1998 1998 GU262*** Glufosinate herbicide tolerance, Antibiotic resistance Bayer CropScience (including fully and partly

owned companies)

Food and Feed/Cultiva

tion 1998 1998

MON 89788 Herbicide Tolerant Monsanto

Food and Feed/Cultiva tion 2007 2007 DP-3Ø5423-1 Sulfonylurea herbicide tolerance, Modified oil/fatty acid

DuPont Pioneer Feed/CultivaFood and tion

2009 2009

MON 87705 * Herbicide Tolerance + Modified Product Quality

Monsanto Feed/CultivaFood and

tion

2011 2011

SYHTØH2 *** Glufosinate herbicide tolerance, Mesotrione Herbicide Tolerance

Bayer CropScience and

Syngenta Cultivation n/a 2014

DAS-44406-6 * Glufosinate herbicide tolerance, Glyphosate herbicide tolerance, 2,4-D herbicide tolerance

Dow AgroSciences LLC Feed/CultivaFood and tion 2014 2014 DAS-81419-2 * Glufosinate herbicide tolerance, Lepidopteran insect resistance Dow AgroSciences LLC Food and Feed/Cultiva tion 2014 2014

40-3-2 Glyphosate herbicide _tolerance Monsanto

Food and Feed/Cultiva

tion

1995 1993

A2704-12 Glufosinate herbicide _tolerance Bayer CropScience Feed/CultivaFood and tion

1996 1998

MON 87701 Lepidopteran insect _resistance Monsanto

Food and Feed/Cultiva

tion 2010 2011