THE TRADE EFFECTS OF Bt CORN

A Thesis

Presented to

The Faculty of Graduate Studies

of

The University of Guelph

In partial fulfillment of requirements

for the degree of

Master of Science

December, LOO0

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AB STRACT

THE ï'FtA.DE EFFECTS OF Bt CORN

Ivana Pekaric-Falak

University of Guelph, 2000

Advisor:

Professor K.D.Meïike

This thesis quantifies the impact of Bt corn on trade and the weEkre of economic

agents in three trading blocs by anticipating possible policy responses to the introduction

of this new technology. The three trading blocs are the Western Hemisphere, European

Union and Rest of the World. The model used in the study is a multi-regional, non-

spatial, partial equilibrium trade model. Consumers' surplus, producers' surplus and total

weifare for eleven different scenarios are compared.

The European Union alone cannot signincantly change the world corn pnce. If

corn demand f d s in both the European Union and the Rest of the World the effect on the

corn price is much larger. Western Hemisphere producers lose most if other two trading

regions only trade among themselves. The introduction of labeling could eliminate trade

Ection but it is costly.

ACKNOWLEDGEMENTS

1 wouid like to thank my supervisor Dr. Karl D. Meillce for a l l his support and

sincere interest in my research. It has been pnvilege to work with him for the last year

and a haK 1 am gratefül to two other members of rny advisory conunittee, Dr. Karen

Huffmd Dr. David Sparling for their help and valuable comments. Special thanks are

extended to Dr. M o n s Weersink who chaired the examination comrnittee,

I wouid dso like to thank the Department of Agicultural Economïcs and

Business for giving me a chance to do this research.

1 am deeply gratefid to my husband Igor and daughters Nha and Mia for their

unconditional support during the graduate school. And above dl , thanks to m y mother

and father for their love and encouragement.

TGBLE OF CONTENTS

................................................................... ACKNO WLEDGMENTS i

. . .................................................................... TABLE OF CONTENTS 11

........................................................................... LIST OF TABLES v

.......................................................................... LIST OF FIGURES vii

................................................................. CHAPTER 1 OVERVOEW 1

1 . 1 Introduction ................................................................ ................................................................. 1.2 Background

.......................................................... 1.3 Research Problem ...................................................... 1.4 Research Objectives

................................. 1 -5 B io technology and Trade Agreements 1.5.1 The Agreement on the Application of Sanitary and

.............................................. Phytosanitary Measures ......... 1 -5.2 The Agreement on Technical Barriers to Trade

........................................... 1.5.3 Biosafity Protocol 1.5.4 The Agreement on Trade Related Aspects of

.......................................... Inteilectual Property Rights .......... 1.6 Overview of Regdatory PoLicies Regardkg Biotechnology

.......................................... 1.6.1 The European Union 1.6.2 Japan ............................................................

...................................................... 1.6.3 Australia.. ............................................. 1.6.4 The United States

.......................................................... 1.6.5 Canada ................................................ 1 -7 Organization of the Study

........................... CHAPTER 2 THE INTEIRNATIONAL CORN MARKET 23

................................................................ 2.1 Introduction 23 ..................................... 2.2 Corn Production in North America 24

2.3 CornTrade ................................................................. 26 ...................................... 2.4 European Corn Borer and Bt Corn 28

.............................................. 2.5 The Case of StarLink Corn 32

CHAPTER3CONCEPTU. FUMEW0R.K AND LITERATURE REVIEW . . . 3 4

................................................................ 3.1 Introduction 34 3.2 EmpiricalModelsofTrade ............................................... 34

3 -3.1 Partial Equilibrium Two-Region versus Partial .....*....... ................... Equilibrium Multi-Region Models ..

3.2.2 Nonspatiai versus Spatial versus Flow Models of Trade . . . . . . . . . . . . . . . ~~~~~~~~~ .~~~~~~~~~~~~ . .~ . .~~ .~~~ . .~ . . . . . . ~ .~ . .~ . . . . . ~ 3.2.3 Partial versus General Equilibrium Models of Trade ..................................................................... 3 . 2.4 J u s t m g the Choice of a Nonspatial Partial

............................ Equilibrium Mode1 ....................... ,. 3.3 Perfect Cornpetition .......................................................

............................................... 3 3.1 The Supply Side ............................................. 3.3.2 The Demand Side

.............. 3.4 Measures of Welfare: Consumer and Producer Surplus ........................... 3 -5 Introduction of a Technologicd hovat ion

................... ................................. CHAPTER 4 EMPiRICAL MODEL ..

4.1 Introduction ............................................................... ................................................... 4.2 Regional Specification

4.3 The Model .................................................................. .......................................... 4-3.1 Model Spec%cation

4.3.1.1 Demand ....................................... .......................... 4.3.1.2 Corn Land Planted

4.3.1 -3 Corn Production .............................. 4.3.1.4 ComYield .................................... 4.3.1.5 Corn Supply .................................. 4.3.1.6 ComNetTrade ............................... 4.3.1.7 ComPrices .................................... 4.3.1.8 Closing Identity .............................. 4.3.1 -9 Mnemonics ....................................

4.4 Data .......................................................................... ........................ 4.4.1 Quantities Demanded and Supplied

......................................... 4.4.2 Elasticity of Demand .......................................... 4.4.3 Elasticity of Supply

.................................... 4.4.4 Yield ïncrease of Bt Corn ..................................................... 4.4.5 Cash Costs ................................................... 4.4.6 Cost of Seed

...................................................... 4.4.7 Corn Price

........................................... CHAPTER 5 SCENARIOS AND RESULTS

5.1 Introduction ................................................................. ................................... 5.2 Description of Scenarios and Results

5.2.1 Scenarios 1,2, 3 and 4: No Consumer BacHash, Free Trade .......................... ... ..................................... 5.2.2 Scenarios 5 and 6: Corn Demand Falls in the EU ........ 5.2.3 Scenarios 7, 8 and 10: One of the Regions is Isolated ....

CHAPTER (

5.2.4 Scenario 9: Demand Fails in the EU and ROW ........... 5.2.5 Scenario 1 1 : Labeiing Scenario.. ............................

..................................... UMMARY AND CONCLUSIONS

................................................................. 6.1 Introduction ......................................... 6.2 Summary of Results by Regions .......................................... 6.2.1 Western Hemisphere

............................................... 6-22 European Union. ............................................. 6.2.3 Rest of the World

6.3 Limitations and Suggestions for Further Research .................... .................................... 6.4 Conclusions and Recomrnendations

............................................................................... REFERENCES

Af P E N D E S . ..............................................................................

. Appendix A OMAFRA Corn Budget Grain Corn'99 .................. ...................................... Appendix B EU S e h g Price of Corn

.................................. Appendix C Detailed Simulation Results Appendix D Resuits of Scenarios 5 a,6a and 9a ...........................

LIST OF TABLES

Table 1.1 Table 1.2 Table 1.3 Table 2.1 Table 2.2 Table 2.3 Table 4.1 Table 4.2 Table 5.1 Table 5.2

Table 5.3 Table 5-4 Table 5.5 Table 5.6 Table 5.7 Table 5.8 Table 5.9 Table 5.10

Table 5.1 1 Table 5.12

Table 5.13 Table 5.14

Table 6.1 Table 6.2 TabIe 6.3 Table Al Table B 1 Table Cl Table C2 Table C3 Table C4 Table C5 Table C6 TabIe C7 TabIe C8 Table C9 Table Cl O

.......................... Global Area of GM Crops in 1999. by Country .............................. Global Area of GM Crops in 1999. by Crop

Estirnated GM Sales Wortdwide ............................................ ................................................................ Corn in Canada

Corn in the USA .............................................................. ......................................... Corn Imports and Exports in 1998

...................... Corn Production, Consumption and Trade in 1995 OveMew of 1995 Data Used in Empincal ha lys i s ................ .... O v e ~ e w of Policy Scenarios .............................................. The Structure of Economic Welfàre in the Three Regions for

...................................................................... Scenario 1 ..................... Regional Price Variations for Scenarios 1,2, 3 and 4

.......................... Regional Price Variations for Scenarios 5 and 6 Regional Price Variations for Scenarios 7, 8 and 10 ....................... Regional Price Variations for Scenaxio 9 ..................................

................................. Regional Price Variations for Scenario f 1 ................... Regional non-GMO Price Variations for Scenario 11

.................................. Welfare Results in Western Hemisphere Percentage Change Compared to pre-GMO Scenario (Scenario 1) in WH .............................................................................

........................................ Welfare Results in European Union f ercentage Change Compared to pre-GMO Scenario (Scenario 1) in EU ............................................................. Welfare Results in Rest of the World ..................................... Percentage Change Compared to pre-GMO Scenario (Scenario 1) in RO W .............................................*..............................

........................................... Best and Worst Scenarios in WH ............................................ Best and Worst Scenarios in EU

......................................... Best and Worst Scenarios in ROW Grain Corn 1999 Corn Prices in Individual EU Countries.. .................................

......*.... ............. Endogenous Variables in Western Hemisphere .. ............................................................ Percentage Change

................................. Welfare Results in Western Hemisphere ............................................................ Percentage Change

................................ Endogenous Variables in European Union ........................................................... Percentage Change

.. Welfare Results in European Union ................................... .. ........................................................... Percentage Change

Endogenous Variables in Rest of the World .............................. ........................................................... Percentage Change

Table C 1 1 Welfare Results in Rest of the World ...................................... 1 12 Table Cl2 Percentage Change ............................................................ 1 12 Table D 1 Cornparison of Welfare Results in WIH .................................... 1 14 Table D2 Percentage Change to Scenario 1 in WH .................................. 1 14 Table D3 Overview of the Additional Scenarios ..................................... 1 1 5

Figure 2.1 Figure 2.2 Figure 2-3 Figure 3.1 Figure 3 -2

Figure 3 -3 Figure 4.1 Figure 4.2

Figure 4.3

Figure 4.4

Figure 4.5 Figure 4.6

Figure 5-1

vii

LIST OF FIGURES

1999 World Production of Corn by Country. -. . . . . . . . . . . . . . . . . -. , . . , . , , . , 1999 World Production of Corn (Maize) Compared to Other Major Largest Sources of Traded Corn.. . . --. . . . . . . . . . . - ... .. -. . . .. , . . . . , . . . , . , ... Consumers' and Producers' Surplus.. . . . . . . - . . . . . . . . . . . . . . . . . . . . . . . . . . . , . . Consumers' Surplus, Compensating Variation and Equivalent Variation- . . . . . . - . . . . . . . . . . . . . . - . . . . . . . . . . . . . . . . . . - . . . . . . . . . . . . . . . . . . . . . . . . . . . . -. Benefits fiom Research. .. . . . . . . . . . . . . . . . -. . . . - --. . -. . -. . . . - -, . . . . . . . . . . . . , , . The International Corn Market Before the introduction of Bt Corn.. . Effect of a Technology Induced Supply Shift in the Exporting Region. . . , . . . . . . . . . . . . . . . . . . . . . . . . - . . . . . . . - . . . . . . . . . . . . . . . . . . . . . . . . . , . . , . . , . . . . . Effect of a Technology Spillover from the Exporting Region to the Importing Region. . - . . . . . . - - . . . . - . . . . . . . . . . . . . . . - . . - . . . . . . . . . . - . -. . . . . . . . . . . . . Effects of a Technology Spillover and Negative Consumer Attitudes in the Importing Region.. . .. . .. . . . . . .. .-. .. . .. . . .. . .. . . . . . . . . . . . . . .. .. . .. .... Demand for Corn Food and Feed Production in a Region.. . . . . . . . . . .... The Corn Production Curve Before and M e r Introduction of Bt Technology . . . . . . . . . . . . . . . . . . . . . . . . . - . . . . . . . . . . . . . . . . . . . . . . , . . . . . . . . . . . . . . . . , . . . Comparison of Market Sizes in the Three Regions (Base Scenario) ...

CHAPTER 1: OVERVIEW

1.1 INTRODUCTION

The commercialization of transgenics that has exploded during the last five years

has been accompanied by a fierce debate between proponents and opponents of

geneticdly modified organisms (GMOs).

Proponents of biotechnology believe that artificial gene technologies are essential

for agriculture to meet the challenges of the twenty-first century. Genetically modified

crops are seen as the way to increase food supply and to feed an ever-growing human

population. The recent appearance of "Golden Rice" contauiing vitamin A could be a part

of the solution to the malnutrition problem in developing countries. Herbicide resistant

crops lead to lower use of herbicides and are a big step towards lowering pesticide

residuals in the environment. Life Science companies clairn that GMOs with agronomie

traits lower costs of production per unit and as a result promise a cheaper worldwide food

supply. Some quality-enhanced crops contain unsaturated instead of saturated fatty acids

and are therefore heaithier for humans. The plants with traits that contain gene(s) for

resistance to abiotic stress (drought, fiost, etc.), which are foreseen in the near fiiture

could open a new chapter in the production of agricdtural crops. In the fùture, crops that

contain cancer-fighting agents or have some other health-uriproving characteristics like

lowering " b a c cholesterol may be developed. To date, there is little scientific evidence

that GMOs pose a danger to human health. So why, then, has there been such a backlash

against the products of biotechnology, particularly in Western Europe?

Arguments against GMOs can be classified into four categories: 1) concems

about human health, 2) environmental concems, 3 ) ethical issues, and 4) political issues.

Dirninishing public trust in scientists and technical experts who are relied upon to

determine whether new technologies will result in unforeseen and unwanted side effects

are a big factor, particularly in the EU (E3uckweli 1999). Some of the recent European

health scares like Mad cow disease, the case of dioxin in Belgian chickens, and the Coca-

Cola scanda1 among others have undermined consumers' faith in government regdators.

Some of the opponents of GMOs are concemed about the release of transformeci

materials into the environment, which might lead to breeding with wild species and to the

creation of ccsuperbugs" or ccsuperweeds" resistant to pesticides. The ethical objection to

the transfer of genetic material between species that could not occur naturally represents,

to some people, interference with the "core" of Me and should not be permitted

(Buckwell 1999). Another important factor in explaining the fierce opposition to the

products of biotechnology is a perception among some consumers in the EU that the

drive to use GMOs in food production cornes fiom a limited number of large

transnsitional compmies that have significant econornic power, which, it is feared, may

enable such organizations to influence the regdatory approval process to their

cornmerciai advantage (BuckweI1 1999).

The goal of this study is not to resolve the GMO debate but to try and explore the

economic effects of the introduction of biotechnology on corn trade. As a case study, Bt

corn is examined. In order to do so, a nonspatial, partial equiiibrium trade mode1 is

constructed. Possible policy responses to the introduction of transgenic Pt ) corn are

examined. The mode1 is "shocked" in order to estimate the impact of the technology on

welfare in three trading regions.

1.2 BACKGROUND

The definition of what constitutes genetic modification (GM) is open to

considerabk discussion and interpretation. For the purpose of this study GM is defmed as

a collection of techniques of molecular biology including recombinant DNA techniques

(gene isolation, purification and engineering techniques), and eiiabling technologies

(transformation, gene mapping, promoters, regeneration, control of plant fùnctions and

some hybridization systems). The t ems genetic modification, genetic engineering, and

biotechnology vriill be used as synonyms in the analysis that follows.

Genes determine specific traits like color, height, or tolerance to specific

herbicides. Biotechnology's first stage featured crops with improved agronomie traits

valued by f m e r s . Most geneticaily engineered crops available cornrnercially have been

developed to cany genes that confer herbicide tolerance and hsect control (Roundup

Ready corn, soybeans, canola and cotton; Liberty Link resistant corn; Bt corn and

cotton). Traits c m dso provide field crops with value-enhanced qudities for end-users,

so called output traits. Some of the new crops are high oleic soybeans, soybeans with

improved animal nutrition, improved food-quality soybeans, high-lauric canola, high

stearate canola, rnid-oleic sunflower seed, high-oil corn, colored cotton, and many others

(USDA 1999).

Use of these crops has nsen dramatically in only a few years since commercial

approval. However, there are signs of adoption rates leveling off in the most developed

countries due to f m e r s ' fears that they wili not be able to sell their products in the EU

and certain Asian markets. The USDA estimates that geneticaliy altered crops were

planted on about 69 million acres in the US in spring 2000 (Agnet 2000a). That compares

to about 71 million acres planted with GMO crops in 1999, according to seed industry

estimates.

Although worldwide data for 2000 is not available, the International Service for

the Acquisition of Agi-biotech Applications (ISAAA) research States that in 1999 the

area planted with genetically engineered crops worldwide jumped to 39.9 million

hectares or a 44 percent increase compared to the previous year. According to the sarne

source, twelve countries grew GM crops in 1999 (Table 1.1) (James 1999, James and

Krattiger, 1999). Industrial countries accounted for 82percent of the total, less than in

1998 (84 percent), with 18 percent grown in developing countries. Seven genetically

engineered crops were grown in 1999, with soybeans being the most important one

(Table 1.2).

Table 1.1: Global Area of GM Crops in 1999, by Country

Canada I

Mexico I Spain I France I

I Ukraine

1 Source: James,

(million ha) (miilion ha)

Approx 0.3 1 0.2

Table 1.2: GIobal Area of GM Crops in 1999, by Crop

Increase fiom '98 (million ha)

7.1

Crop

Soybean

Cotton

Potato

Area (million ha)

21.6

3 -7

I l I I

Source: James, 1999

% of Total

54

<O. 1

Squash

Papaya

Total

9

<1

cl

<O. 1

<O. 1

Producer revenues £iom GM crops have grown about thirty fold fiom 1995 to

1999 (James 1999) exceeding $2 billion US in 1999.

1.2

I

<O. 1

<O. 1

39.9

Table 1.3: Estimated GM Saies Worldwide (in US$)

<1

Year

1995

1996

1997

1998

1999

(0.1

100

Sales

75 million

235 million

670 million

1.6 billion

2.2 billion

12.1

Source: James, 1999

In Canada, Ontario is the main corn-growing region and about one third of al1

corn acreage in 1999 was genetically rnodifïed. These were varieties approved by the EU.

Only about 2 percent of Ontario corn was pIanted to non-EU approved varieties. In 1999,

GMO soybeans were grown on 10-20 percent of d l soybean area in Canada

(Brandenburg 1999).

1.3 RESEARCH PROBLEM

The problem of consumer acceptance of GMOs is multileveled: it has scientific,

economic, political and ethical sides. In this research, the focus is on the following

economicproblem: How to quantifi the impact of Bt corn on trade, and the welfare of

economic agents in three trading blocs by anticipating possible policy responses to the

introduction of this new technology.

In addressing this research problem five specific research objectives are

identified.

1.4 RESEARCH OBJECTrVES

The objectives of this study are:

1) to anticipate possible policy reactions in various regions of the world to the

introduction of Bt corn;

2) to measure changes in price and economic welfare in the Western Hemisphere,

European Union and the Rest of the World under different assumptions about

consumer response to the introduction of Bt technology;

3) to analyze how trade is af5ected by eleven different policies regarding biotechnology;

4) to draw the implications of these results for trade policy in Canada; and

5) to provide recommendations to Canadian fanners regarding the adoption of Bt corn.

Before discussing the mode1 that forms the core of this analysis, some additional

information on trade agreements and the regdatory h e w o r k for Bt corn technology is

provided.

1.5 BIOTECHNOLOGY AND TRADE AGREEMENTS

Although not ccofficially" a trade dispute, the present situation regarding GMOs

has the potential to M e r poison the trade relationship between the US and EU that is

already under a heavy burden as a result of the beef-hormone and banana disputes.

There are four important international Agreements that can be applied to different

aspects of biotechnology :

1) concems about hurnan health and risk analysis are under the WTO Agreement

on the Application of Sanitary and Phytosanitary Measures;

2) the issue of labeling of GMOs is covered by the WTO Agreement on Technical

Barriers to Trade;

3) although, technicaily, not a trade agreement, the Biosafety Protocol addresses

environmental issues; and

4) protection of intellechd property rights is covered by the WTO Trade-Related

Intellectud Property Rights Agreement.

Each of these agreements is explained in more detail in the following subsections.

1-51 The Agreement on the Application of Sanifary and Phytosanitary Measures

The fear of hidden allergens and the unknown cumulative effect of toxic

substances that might be present in trace amounts in GMOs are the main reasons for the

health concems towards biotech products. Under WTO regulations, these issues are

regulated by the SPS Agreement.

The SPS Agreement concerns the application of rneasures associated with the

protection of human, animal and plant health in such a way that they are not a disguised

restriction on international trade. This Agreement has particular relevance to measures

taken to ensure food safety. It recognizes that govemments have the right to adopt

sanitary and phytosanitary measures but that they should be applied only to the extent

necessary to achieve the required level of protection- Governments shodd not

discriminate between members without smcient scientific evidence, or arbitrarily when

identical or similar conditions prevail. The SPS Agreement encourages countries to adopt

international standards.

That means that under the SPS, a country c m set its own standards for food safety

and animal and plant health, but at the same time requires that measures be based on

scientific risk assessments (Nielsen and Anderson 2000). Article 5.7 of the SPS

recognizes that when urgent problems of safety, health, environmental protection or

national security arise, and scientific evidence is unavailable or insufficient a country can

"skip" conforrnity assessrnent procedures (WTO). This article of the SPS Agreement is a

base for the widely disputed "precautionary principle" which is at the heart of the EU

policy towards GMOs.

Another contentious issue regarding GMOs and the SPS Agreement is the

treatment of consumers7 interests. After genetically modified crops entered füll

commercialization, consumers becarne the interest group that sought protection fiom

foreign imports. This situation is not accounted for in WTO regulations, The consumers'

right to know is one of the core arguments used by the EU in the dispute about GMOs.

1-52 The Agreement on Technical Barriers to Trade

The TBT Agreement seeks to ensure that technicd regulations and standards,

including packaging, marking and labeling requirements and procedures for assessing

confomiity with technical regulations and standards do not create unnecessary obstacles

to international trade. It recognizes that a country has the right to take necessary

measures, at a level it considers appropriate, to ensure the quality of its exports (the

protection of human health or safety, animal or plant life or heaith) and the environment;

and to prevent deceptive practices- A coutltry may also take the necessary steps to ensure

that rnandated levels of protection are met, as long as the measures or action taken to

impIement them, do not create unnecessary obstacles to international trade. The

provisions of the TBT Agreement do not apply to sanitary and phytosanitary measures

subject to the SPS Agreement, which includes measures to protect human, animal and

plant life or health fiom pests and diseases and food borne health hazards. The TBT

Agreement also encourages countries to adopt international standards.

1.5-3 Biosafety Prorocol

The Cartagena Protocol on Biosafety was adopted on Jan 29,2000. It is a part of

the Convention on Biological Diversity established in 1992 by the United Nations.

Although not explicitly a trade agreement, the BioSafety Protocol includes consideration

of import and export activities, so it can be treated as a de facto trade agreement (Isaac

and Phillips 1999).

The Protocol, which must be ratified by 50 corntries before it goes ùito effect,

establishes an international W e w o r k for coumies to use when making decisions about

genetically modified crops. It also requires, for the f is t time under an international

agreement, labeling of commodity shipments that "rnay contain" genetically modified

foods. However, there is no specific requirement that the farmers or the grain industry

segregate conventional and modified crops.

The Protocol strikes a balance between the so-called Miami Group of the US,

Canada, Argentha, Uruguay and Chile, and the G-77 group of developing nations backed

by Europe. With its language on the "precautionary principle" the proposed Protocol

could set the stage for countnes to close their markets to genetically modified crops

without conclusive scientific evidence of harm. In the other hand, the Protocol also

contains a "savings clause" which emphasizes the new pact does not override rights and

obligations under other international agreements, including the World Trade Organization

agreements.

1.5.4 The Agreement on Trade Related Aspects of lntellectd Properîy Rights

The TRIPS Agreement, which came into effect on Jan. 1, 1995, is the most

comprehensive multilateral agreement dealing with intellectual property. The areas of

intellectual-property that it covers are: copyright and related nghts; trademarks including

service marks; g e ~ ~ p p h i c a l indications including appellations of origin; industrial

designs; patents including the protection of new varieties of plants; the layout-designs o f

integrated circuits; and, undisclosed information including trade secrets and test data.

The three main features of the Agreement are: 1) standards. 2) enforcement, and 3)

dispute settlement.

Regdation of intellectual property rights (IPR) is important in order to ensure

private investment in new tecbnology. Agicultural biotechnology creates a situation in

which the inventors of the intellectual property can capture the intellectual property value

of agriculhïral products. lntellectual property piracy is becoming an increasing

internationai concen.

The debate over protection of intellectual property nghts are largely polarized

between developed countries, which produce most of the world's intellectual propem

and are advocates of strong international protection, and developing countries which

perceive that the payment of monopoly rents for the use of intellectual property is

detrimental to their development process (Gaisford and Richardson 1996). The

complexity of the issues relathg to the international protection of agricultural

biotechnology suggests three things:

there is a wide range of potential problems between developed and

developing countries;

it may be developing counties who will seek dispute settlement at the WTO in

order to protect their native species; and

some counûies may not want to enforce certain forms of intellectual property

protection in the area of biotechnology (Klein, Kerr and Hobbs 1998).

However, the problems that arise £kom inteUectuai property rights issues

regarding biotechnoIogy are not the focus of this research.

To stmmarize, there are several contentious issues that arise fiom the present

trade agreements and the Biosafety Protocol, and their application to GMOs (Nielsen and

Anderson 2000).

First, based on whether it is concern for the environment andor human health, a

country's regulations wiU fdl under one of the above rnentioned WTO agreements. This

may be very important in ternis of interpreting the Biosafety Protocol and its relation to

the WTO d e s . Second, the SPS requires that any policy towards GMOs be based on

scientific evidence. This may not be in accordance with the Biosafety Protocol which

explicitly States that the lack of such evidence does not prevent importing c o d e s from

taking action. Third, the product/process distinction: the Biosafety Protocol draws a

distinction between products based on their production processes, unlike WTO d e s on

"like products". Fhally, mandatory 1abeIing requirements for d l GMO-inclusive

products including processed foods. As long as these d e s do not discriminate between

foreign and domestic goods they will probably not violate existing WTO d e s , even if

they add significantly to consumer costs.

Beside international agreements that are meant to enhance trade, each country

implernents its own d e s regarding GMOs. These individual regdatory regimes are very

important since they rnirror consumers' attitudes toward GMOs in each country.

1.6 OVERVIEW OF REGULATORY POLICIES REGARDING

BIOTECrnOLOGY

To Mly understand the maze of regdations imposed by the EU, Australia and

Japan a iegal counsel would be needed. Therefore, the discussion below should be

considered a simple review of key policies. The main players in the biotech game are

covered. The review starts with the policies of the EU because of the European

consumers' concem over GMOs.

1.6.1 The European Union

In June 1999, EU environment ministers signaled a halt to authorizing any new

GMOYs until the Cornmunity's revised approvd process comes into force sometime after

2002. The Council agreed to a series of revisions to the EU legisfation governing the

approval of GMO ' s (Directive 90/220) whic h would limit any product s authorization to

a maximum of ten years, set clearer Iabeling rules, and include provisions to extend

traceability and liability throughout the food chah (Agra Europe 1999). The amenciments

to the existing procedures should establish common risk assessrnent standards, labeling

requirements, monitoring methods, an approvals procedure and limit the duration of the

license to ten years.

Although in principle EU member couutries are rinified in their decision to hait

the approval of new GMOs, there are two different views of the problem. Germany,

Austria, Belgium, Sweden, the Netherlands and Fiidand signed a declaration which

makes no specifïc mention of any moratorium, suspension or hait in approvais. However,

a second faction including France, ItaIy, Denmark, Greece and Luxembourg signed a

much stronger statement calling for a "suspension" of al1 approvais until shicter

traceability and liability controls are in place (Agra Europe 1999). These five countries

bave the necessary votes within the EU to prevent any GMO application fkom being

approved. Therefore, their policy statement, whiie not approved by the Council of

Ministers, amounts to a de facto moratorium on any approvals (Inside US Trade 1999).

This situation, had little effect on the position of countries who wish to export GMOs to

the EU because the EU had not approved the sale of a single GMO product in 1999.

On July 15,2000 the EU Environmental Ministers agreed to maintain the

moratorium on the licensing of GMOs but the European Commissioner said she was

hopeful the ban would be lifted by the end of the year (Agnet 2000b). The Ministers said

they would review their position in the fa11 afier the Commission had presented the full

proposal for tighter laws on GMOs including a legal fiamework to insure the

controversial products could always be traced .

In August 2000 (Agnet 2000c) the European Commission, according to an article

in Lancet, moved towards ending its rmofficial moratorium on genetically modified

foods. In exchange for expediting authorizations of GM products, the Commission wants

tighter controls governing the labeling and traceability of GM crops. The fast track

authorization mechanism would be in place as soon as European Union goveniments and

the European Parliament reach agreement, but before they legally enter into force in

individual states. This could mean the changes take effect by the end of 2000. The

proposals have met with criticism by opponents of GM foods in Europe.

European Union regdations require labeling of food products whose ingredients

contain genetically modified strains of soybeans or corn (Inside US Trade 1998). The

basis for the EU'S regdation is that bioengineered foods are not equivalent to

conventional products and therefore require Iabeling. The EU regulations do not state

when the label signieing the presence of GMOs shodd be used.

The EU also requires labeling of al1 foodstuffs, additives and flavors containing 1

percent or more geneticdy engineered material (regulations 1 139198 and 4912000). This

tolerance level allows for the unintentional contamination during the transportation

process or handling. Labeling in the EU is based on scientific evidence proving the

presence of genetically engineered DNA or protein (Nielsen and Anderson 2000). In the

case of processed foods, if the production process has eiiminated the external DNA or

protein, a product does not have to be labeled.

The Novel Foods Regulation (NFR) that came into being on May 15, 1997 is

another set of EU d e s that apply to GMO foods @articutarly processed food). NFR

established a system for formal mandatory evaluation of novel foods - once approved,

such foods were supposed to be regarded as any other food (Trends in Food Science and

Technology 1998). Whether this tegislation is still in force is unclear because sorne later

EU rulings suggest that licenses for GM products wili have to be renewed every ten

years. EU regulations on labeling products of biotechnology are not clear and consistent.

1.6.2 J q a n

Another country that has proposed mandatory labeling requirements for foods

containing genetically modified organisms is Japan. The Japanese system is based on

segregating GMO foods fiom those not containing GMOs throughout the production and

distribution process to avoid the mixhg of DNA and protein fkom GMO products with

conventional products. A compiex system of mandatory labeling requirements Cs set for

roughly 30 food products made IÎom corn and soybeans.

The regulations set up three categories for the purposes of labeling, with different

requirements. First, mandatory labeling is required for a group that covers high-oleic

soybean oil and processed food that uses soybean oil. A second category, which includes

genetically modified primary products and processed foods in which geneticaily-

rnodified DNA or proteins are present, contains 23 products. This category has a

combination of voluntary and mandatory labeling requirements. Fïnally, no labeling is

required for a third category of food that are sufficiently processed that geneticdly

modified DNA or proteins no longer exist.

As of April200 1 al1 imported products that contain genetically modified

organisms are to be tested to ensure that they do not contain unapproved varieties. The

mandatory testing wiII mainly af5ect products containing soybeans and corn, including

processed foods to ensure their safety. Penalties may be applied in instances where a food

contains an unapproved GMO variety (Inside US Trade 2000). Under the current food

sanitation law it is illegal to sel1 non-qualifiing foods.

The regulations are meant to implement a niling by the Japanese government

subcommittee on biotechnology that safety assessments of foods containing GMOs

shouid be required- No sdety assessrnent or testing is currently required.

To ensure cornpliance with the regulations, Japan will require a system of

"social verification". This involves ensuring the preservation of identity by providing

certificates of every processing and distribution step to show that a product is GMO-fiee.

Social venfication could also involve genetic testing by public organizations such as

consumer groups to ensure the truthfdness of labeling. The labeling will be implernented

under the Japan Agricultural Standards/ Quality Labeling Standards Law (Inside US

Trade 2000).

1.6.3 Australia

Australia's position on labeling of GMOs has changed fiom being a f imi

supporter of the US position, not to label GMO foods, to mandatory labeling.

For a long time the Federai Government of Australia (together with the National

Farmers Federation and most major food manufacturers) supported the view that

genetically altered foods that do not Vary in appearance and taste should not require

labeling. The Austrdian Medical Association, the Australian Consumer Association and

the Australian Conservation Foundation were the ones who voiced concerns about

regulations that would allow foods that contain genetically modified ingredients to avoid

being labeled, provided the end product is "substantially equivalent" to the unrnodified

food.

The Australia and New ZeaIand Foods Standards Council (consisting of the health

minisiers of the two nations) agreed in August 1999 to mandatory labehg of all foods

containing GMOs. At a meeting on July 28,2000 the Council agreed to a s+mdard that

"requires Iabeling of food and food ingredients when novel DNA andlor protein is

present in the final food". (Agnet 2000d). The Council also requires labeling of food and

food. ingredients when the food has altered characteristics. Exempt fiom these

requirements are: higkdy refined food where the effect of the refining process is to

remove novel DNA andor protein; processing aids and food additives except those where

novel DNA and/or protein is present in the final food; flavors which are present in a

concentration less than or equal to O. 1 percent in the final foods; and, food prepared at the

point of sale. The standard allows an ingredient to contain up to 1 percent of unintended

GMOs. The new standards will corne into effect in Spring 2000.

The Australian Prime Minister's bid to relax proposais for mandatory Iabeling of

GMOs by allowing foods to contain up to 1 percent of modified content before requiring

Iabeling was, hence, defeated.

1.6. Cl The United Srates

In the United Stzites the appropriate administrative divisions of the United States

Department of Agriculture (USDA) and Food and Drug Agency (FDA) regdate the

development of animai and human heaith products, including those developed through

genetic engineering.

The release of geneticdy engineered food plants into the environment and their

testing is regulated through the Animal and Plant Health Inspection Service (APHIS).

APHZS exercises its regdatory authority through a permit system.

In May 1992, the FDA determined that foods derived fiom new plant varieties

produced by genetic engineering would be regulated no differently than foods created by

conventional means, unless special circumstances apply. The FDA detennined that a

special review of a genetically engineered food product would be needed only when

specific safety issues were raised.

The FDA does not require that al1 genetically engineered food products be

labeled. However, it does recognize that in certain situations when the modified product

differs substantially fiom its conventional counterpart consumers should be advised

through labeling. The introduction of a gene fiom a known aliergen and the changes in

the product's nutritional content are two of these situations. Some other safety issues that

require labeling are: unexpected genetic effects, significantly higher levels of toxicants,

altered levels of important nutrients, new substances appearing in a food, and antibiotic

resistance.

1.6.5 Canada

The Canadian policy on GMOs is very similar to the poIicy of the United States.

In November 1999 a cornmittee was created to develop standards for the voluntary

labeling of foods whether derived using genetic engineering or not. The committee was

created under the Canadian General Standards Board, at the request of the Canadian

Council of Grocery Distributors. Voluntary iabeling was already an option, but without

standards virtually no companies have done so. (The Globe and Mail 1999)- "The

Govemment of Canada believes in the right of consumers to have access to infcrmation

as it relates to biotechnology and food. This is a complex issue and any iabeling bas to be

meaningful to consumers", said Agriculture Pl..linister Lyle Vanclief. He also mentioned

the possibility of making these standards mandatory, although it doesn't seem very

probable. The standards for voluntary labels on foodstuffs will have to ensure that labels

are easily understandable, easily applicable and not misleading. In reality, this is an

exercise about negative labeling ("does not contain") since it seems unlikely that any

manufacturer or distributor would pay to have the foods certified voliintarily as

containing GM ingredients (Ontario Corn Producer 2000a; OCP 2000b)-

In the Canadian public two substmtially different views about biotech products

are represented.

On the pro-biotech side are the Canadian governrnent, industry, and some other

interest groups. The Food Biotechnology Cornmunications Network, for example,

includes representatives fiom the Consumers' Association of Canada, the Canadian

Council of Grocery Distributors, the University of Guelph, AAFC and the Nationai

Institute of Nutrition. The Network portrays itself as being neutral, but the media (The

Toronto Star 1999) sees it as pro-biotech. Agricultural Groups Concemed About

Resources and the Environment (AGCare), which represents about 45,000 Ontario

Farmers also support the use of biotechnology.

Groups opposing biotech include Greenpeace, the Sierra Club, the Council of

Canadians, and the non-governmental organizations concerned about the environmental

and health risks of GMOs.

. The regdatory regime towards GMOs in Canada is the last piece of information

that provides background for the problem of GMOs and trade. Before presenting the

conceptual fiamework a short overview of the corn market is provided. More details on

the organization of the study are given in the foilowing section.

1.7 ORGANIZATION OF TEIE STUDY

Chapter 2 provides an overview of the corn market: corn acreage and production data

is presented, as well as figures on corn trade. The biology of the European Corn Borer

and the characteristics of Bt corn are dso given in this chapter.

Chapter 3 provides the conceptual W e w o r k that was used in building the empiricai

model. Several different types of trade models are reviewed as is the supply and demand

theory needed for the empirical part of the study. The concepts needed to measure the

welfare effects and trade patterns as a result of the introduction of Genetically Modified

Organisms into commercial agricultural production are presented. Previous studies with a

focus on the introduction of new technology are also explored.

Chapter 4 describes the model used in this study and shows how the model was

calibrated.

Chapter 5 explains the scenarios that represent simplified policy responses to the

introduction of GMOs and provides the simulation results.

Chapter 6 provides the summary of the study, as well as the conclusions and

recornmendations flowing ficm the results. Caveats to the model, together with the

suggestions for m e r research are also given in this chapter.

23

CHAPTER 2: THE INTERNATIONAL CORN MARKET

2.1 INTRODUCTION

Corn (Zea mays ssp. Mays) is a gigantic domesticated grass of tropical Mexican

origin. Its production equaled 600 million tonnes in 2999 (FAOSTAT 2000). The US,

China and Brazil account for more than 80 percent of worid corn production (Figure 2.1).

It is the third most planted crop in the worid - following wheat and rice (Figure 2.2).

Figure 2.1: 1999 World Production of Corn by Country (percent of total production)

China (21%)

Figure 2.2: 1999 World Production of Corn (Maize) Compared to Other Major Crops (millions of hectares)

Wheat Rice Maize Soybeans BarIey Sorghum

2.2 CORN PRODUCTION IN NORTH AMERICA

Given that the Western Hemisphere is the biggest corn-producing region in this

analysis, this section provides information on corn production, area planted and yield in

Canada and the United States.

Canada is the 10" Iargest producer of corn in the world. The area planted with

corn has a positive trend. About 1.12 million ha was planted to corn in 2000, while in

1 995 corn area was only 1 .O million ha (FAOSTAT 2000). However, the area planted is

about 20,000 ha smaller in 2000 than it was in 1999 (Table 2.1). The decrease in the

number of hectares planted to corn in Canada in 2000 might be related to a problem that

some Canadian farmers had in 1999, trying to sel1 non-EU approved corn hybrids.

Within Canada, Ontario and Quebec are the biggest provincial producers. In

Ontario, some 700,000 ha were planted to corn in spring 2000 (OMAFRA 2000). This is

a decrease of 38,000 ha compared to 1999. Total Ontario corn production in 1999 was

5.87 million tonnes, with the total value of CA$646.8 million. The main corn producing

region in the province is in Southern Ontario, which produced about 46 percent

(2,73 1,200 tonnes) of Ontario's corn in 1999. As can be seen fiom the value of

production and the area planted, corn is an important crop in Canada and Ontario. This

Corn has the largest acreage of d l crops grown in the US. Planted area totaled

more than 29 million ha in 1998 (Table 2.2) which represented 25 percent of the area

planted to al1 crops in the US (Gianesi and Carpenter 1999). The area planted to con ,

fact was a big motivation in undertaking this study.

Table 2.1: Corn in Canada

corn yields, production, and the production of seed al1 have positive trends in the US. ALI

Unit

1995

1996

1997

1998

1999

2000

Source: FAOSTAT

48 conterminous states plant corn and, in many states, corn is the single most important

crop in terms of area and production value. Corn production is centered in the Midwest,

Area

Million ha

1-90

1 .O9

1 .O4

1.12

1.14

1.12

where ten states account for 85 percent of the US acreage and production (Gianesi and

Y ield

Tha

7.26

6.92

6.87

8.0 1

7.97

7.83

Production

Million t

7.28

7.54

7.18

8.95

9.10

8.50

Seed

Million f

0.03 O

0.029

0.030

0.03 1

0.03 1

0.03 1

2.3 CORN TRADE

The US is the largest source of traded corn. Et produces 70 percent of al1 traded

corn (Figure 2.3). It is intereshg that ody three countries - US, Argentina and China -

produce more than 90 percent of the corn that is traded on the world market.

Carpenter 1999). Individually the States of Illinois and Iowa account for more than 10

million acres of corn each.

Table 2.2: Corn in the USA

Unit

1995

1996

1997

1998

1999

2000

Source: FAOSTAT

Yield

Tha

7.12

7.98

7.95

8.44

8 -40

8-90

Area

Million ha

26.39

29.40

29.4 1

29.3 8

28.55

29.57

Production

Million t

187.97

234.53

233.87

247.88

239.72

263 -22

Seed

Mflion t

0.517

0.518

0.503

0.533

0.537

0.53 7

Figure 2.3: Largest Sources of Traded Corn

Argentina 0 China

Others O Canada is a small net corn importer with the main source of irnported corn being

the US. The value of impoas fiom the US was US$89 million in 2999. The second and

third sources of Canadian corn Unports in 1999 were Canadian re-imports ($4.9 million)

and Argentina ($ 0.37 million) (Strategis 2000). A more detailed analysis of import and

export data reveals that the value of Canadian exports decreased substantially in 1997 and

1998. From 5 12,700 tonnes in 1996, exports decreased to 263,205 tomes in 1997 and

258,705 tonnes in 1998. The dollar value of exports was also cut in ha16 fiom US$102

million in '96 to $43 million in '98 (Table 2.3) (FAOSTAT). The biggest destination for

Canadian corn exports is Iran, followed by the EU and Cuba (Strategis 2000).

As shown above, the US is the world7s largest corn exporter. Another big corn-

exporting region is South Arnerica. As a result, in the mode1 used in this study, under the

base set of assurnptions the Western Hemisphere is a net corn exporter. The European

Union is the second biggest corn importer in the study (Table 2.3) given this region is

dso a big corn exporter. The biggest single corn importer is Japan with virtually no corn

production and unports worth more than US$2 billion in 1998. China is another big corn

producer but ïmport and export data for China are not available.

Table 2.3: Volume and Value of Corn Imports and Exports in 1998 (in million tonnes and million dollars).

Imports- Quantity

Canada

Irnports-Value

USA

1.22

South America

Exports- QuanGty

0.30

Japan

I

Source: FAOSTAT

Exports-Value

157.79

7.39

Australia

Corn is primarily used as an animal feed because it is valued for its highly

digestible carbohydrates and low fiber content. More than one-half of toltal corn usage is

for animal feed, In some Asian, African and South American countries corn is a staple

food. In developed countries corn is an important ingredient in the cereal industry. It also

has its industrial uses: manufactured into high quality starch, ethanol, sweeteners, and

lysine. It c m also be used in pharrnaceutical, nutraceutical and chemical industries.

Industriai use of corn is about 65 million tonnes globally @uckwell 1999).

167.58

2.4 EUROPEAN CORN BORER AND Bt CORN

0.26

948.97

1

0.00

43 -42 r

. . 16.05

42.13

12.75

0.002 2,113.81

0.17

4,6 19.04

1,467.33

0.02 3.353

European Corn Borer (Ostrinia Nubilalis) is a major pest of corn (Zea Mays L.)

in many regions of North America (Gianesi and Carpenter 1999). Also, it is a major corn

pest in many regions of Europe (Melchinger et al. 1998).

ECB moths hatch at the end of June and deposit their eggs on plants at the late

whorl stage. ECB larvae feed on leaves and pollen before entering the stalk, The main

damage caused by ECB is the tunneling of larvae in the stalk and ear shank, resulting in

reduced plant growth and grain yield (Hyde et al. 1999). Damaged plants show increased

susceptibility to secondary infections caused by various pathogens (e-g. Fusariurn ssp.,

Diplodia ssp and others) and are more prone to lodging.

Few economically feasible ECB control methods exist for most corn farmers. In

the past, f m e r s have used cultural practices (Le. moldboard plowing and crop rotation)

to protect their fields against ECB idestation (Rice and Pilcher 1998). Today f m e r s

have three more "tools" to manage ECB: granular insecticides, liquid insecticides and

transgenic corn. Liquids are generally not as effective as granular insecticides because

they are more difficult to direct into the whorl where the insecticides are most effective.

However, neither liquid nor granular applications are 100 percent effective in killing

ECB. Estimates of efficacy are about 80 percent against first geaeration borers and 67

percent against second generation (Ostlie et al. 1997). For a pesticide treatment to be

effective, timing must be precise. The high cost of scouting - especially for second-

generation borers - makes it uneconornical for the great majority of corn farrriers to spray

against ECB (Hyde et al. 1999). As a result, for most fanners there are no effective

substitutes for Bt corn.

Based on t h , the mode1 used in this study does not consider ECB scouting and

spraying to be viable production alternatives. Therefore, farmers either use Bt corn and

experience a yield increase (compared to traditionai hybrids) in the case of ECB

infestation, or grow traditional corn and suffer yield losses fiom ECB damage.

Bt corn hybrids contain genes fiom one or more strains of Bacillus thuringiensis

(Bt). There are five unique iypes of Bt corn- Each is the result of a different "event", or

successfùl insertion of the Bt gene into the corn's DNA. They were developed in order to

prevent crop damage fiom the European Corn Borer, the second most important pest, of

corn, in North America (Nelson et al. 1999).

Bacillus thuringiensis is a soIiborne bacteriurn that produces iC~ry" proteins. These

are crystal-like substances that act like a poison when digested by ECB larvae. The

insect's digestive enzymes activate the toxin. A specific cry protein is toxic only to

specific groups of insects and has no effect on mammals.

Bt proteins have been known for more than 30 years in the organic food industry

(Nelson et al. 1999) as a biopesticide. While treating corn with Bt is relatively

complicated because the toxic effect breaks down after exposure to W radiation, dry

conditions or heat, modifying a corn plant to produce its own Bt protein overcomes these

problems. There are more than 60 Cry proteins, some of them effective against

mosquitoes, blacldlies, gypsy moth and other insects. In generd, Bt corn hybrids are

effective against the insects fiom the Lepidoptera, Diptera, and Coleoptera species

(Krattiger 1997).

There are two possible problems resulting fkom the introduction of Bt corn. The fist -

widely explored by media - is the alleged negative effects of Bt corn pollen on Monarch

butterflies, and the other one is the potential development of insect resistance to this

natural insecticide.

Identification of the first problem was based on a study conducted at the Corne11

University in 1999 that claimed that Bt pollen deposits on milkweed had Iethal effects on

the Monarch butterfly larvae. Some circles rejected this study because Monarch larvae

were "force-fed" pollen, which would never occur naturally. In August 2000, another

study - this time fiom Iowa State University - explored the same issue and came to the

conclusion that the larvae rnortality rate was seven tirnes higher than when fed with

conventional corn pollen. Again, the study was conducted partidly in lab conditions,

which casts some cioubt on the resuits-

Possible insect resistance has much more interesting agronomie implications.

In order to prevent the development of insect resistance to Bt corn there are guidelines for

responsible deployment of this technology. The five companies that have received

authorization for Bt corn in Canada (Monsanto, Pioneer, Novartis, Mycogen and AgrEvo)

have each developed Resistance Management Plans designed to delay development of Bt

resistance insects. The mandatory implementation of a minimum 20 percent unsprayed

refuge of non-Bt corn on each farm planted with Bt corn is a critical component of these

plans.

It is important to understand the various aspects of biotechnology. The most recent

GMO crisis (September 2000) is related to both biology and the regdatory regime for Bt

corn. The example of StarLink corn, described in the next subsection, shows that there

are no winners in the case of inadequate regulation of GMOs.

2.5 TEE CASE OF STARLINK CORN

The regulztory mechanisms dealing with corn are based on the approval of "events".

Each "event7' represents successful insertion of a DNA sequence into corn. In the case of

Bt corn these gene sequences enable the corn plant to produce the above described cry

proteins which are toxic when digested by ECB larvae. Each "event" or gene sequence

produces a different kind of cry protein. This is why an approval process is needed for

each "event",

The transformation used in StarLink corn enables it to produce cry9c protein. The

cry9c protein breaks down slowly in the human stomach making it more likely to trigger

an allergic reaction. That is why StarLink corn was approved for animai feed but not for

food consumption in the US.

In September 2000, traces of StarLink corn were found in chips and Taco shells (the

kind that is sold in supermarkets) produced by Kraft. It is not clear how StarLink corn

entered the food c h a h Although there is no proof that StarLin. would cause allergic

reactions in hurnans, the presence of this corn hybrid in human food is unlawfiil. The

event was widely publicized in the media and sent a shock wave through the food

industry. Examples of the problems that have arisen fkom the StarLink case are described

below.

Kraft announced the voluntary withdrawal of Taco shells, lost millions of dollars

and tamished its food safety reputation. Farmers Say that they were not adequately

informed about the restrictions on how to plant, store and sel1 StarLink. It is possible that

as a result of this case many farmers are going to be reluctant to plant GM crops in the

future. In order to help farmers the USDA wiii buy al1 StarLink corn fkom them. A

French company Aventis - the producer of StarLink - has announced that it will

reimburse the American government. The US Environmental Protection Agency (EPA)

has cancelled StarLink corn registration. Japan slowed its purchases of US corn for the

first quarter of 200 2 , The USDA Foreign Agriculture Service (FAS) has adopted a

comprehensive protocol to ensure exports to Japan are StarLink fkee. US consumers aiso

reacted. A recent Reuters/Zogby poll showed that more than one-haLf (54.4percent ) of

Americans believe that recent recalls of food containhg GMOs raise concems about US

food safety. The announcement by the owner of the StarLink trademark (Aventis) that

the company is going to spin off its agriculture division fiom its chernical division might

be related to the scandal. It remains to be seen what lessons have been learned fiom the

Starlink example. The consolidation of the US food safety agencies would be a step

fonvard, as well as a set of international rules on GMOs.

CHAPTER 3: CONCEPTUAL FRAMEWORK AND LITERATURE REVIEW

3.1 INTRODUCTION

The purpose of this chapter is to provide the theoretical background that is needed

for the development of an empirical model. Several types of trade model that could be

employed in this study are reviewed and their strengths and w-eaknesses are discussed.

Based on the review, the choice of a nonspatial, partial equilibrium ~ a d e model to use in

measuring the impact of the introduction of a new technology (Bt corn) is justified. ne

suppIy and demand theory used in the analysis is reviewed as are the welfare measures

needed to quantifi changes in the gains fiom trade that result fkom different policies

towards GMOs. Previous studies of the introduction of a new production technology are

dso reviewed.

3.2 EMPIRICAL MODELS OF TRADE

There are several different types of trade modeIs that can be used depending on the

purpose of the analysis, mathematical rnethods used in solving models, treatment of

pnces and some other characteristics. The classification of models presented by

Thompson (1 98 1) is discussed here.

Trade models can be single-sector partial equilibrium, multiple sector partial

equilibrium or Cornputable General Equilibriurn. Both single-sector and multiple-sector

partial equilibrium models c m be solved in spatial or non-spatial settings.

3.2.1 Partial Eq uilibrium Two-Region versus Partial Equilibriurn Multi-Region

Models

Two-region trade models are the simplest form of trade model. They are based on

adding export demand or import supply equations to the existing commodity market of

the domestic country. This kind of model has strong limitations since they can only be

used to analyze domestic policy issues.

Multi-region models are basicaliy simultaneous systerns of equations specified to

reflect the behavior of a number of trading regions and their intenelationships through a

world market. Multi-region models can be divided into nonspatial price equilibrium

models, spatial price equilibrium models and trade flow or market share models. The

main difference among these multi-region models is the assumedprice link among the

regions and the procedure used to solve the models (Thornpson 1 98 1). The next

subsection discusses the dBerences between spatial, nonspatial, and trade flow models in

more detail.

3-2.2 Nonspatial versus Spatial versus Trade FZo w Models

Nonspatial price equilibritm models are the simplest multi-region models of

agricultural trade. The world price in these models is solved simultaneously, based on the

supply-demand b a h c e in al1 trading regions. The solution of the model gives the world-

market clearing pnce and net trade of each of the regions. n i e disadvantage of this kind

of model is that they do not generate source-destination trade flows. Nonspatial price

equilibrium models are generally good at reflecting tariff policies but are not very good at

reflecting nontariff barriers.

There are three subclasses of nonspatial models and their classification is based

on the nature of the price M a g e between the regions. As Thompson (1 98 1) points out,

in the first subclass there is one global market-clearing price at which al1 trade occurs.

In the second subclass the cornmodiw prices in al1 but one region are linked by

transportation costs to the Nth region. This subclass recognizes that in a spatial

equilibrium prices dif5er among trading regions by exactly transport costs. In the third

subclass, pnces are linked through tmspoa costs painvise dong the principal historical

trade flows. This type of nonspatial mode1 generates the net trade position of each region,

while spatial models, which are discussed next, generate source-destination trade flows.

Spatial price equilibrium models used to be the most cornmon class of agricultural

trade models . The y endogenize source-destination trade flo ws and market shares- Prices

are directly linked only between those pairs of countries that actually trade with each

other, The main difference between spatial and nonspatial pnce equilibrium models is in

the solution method. Most early spatial price equilibriurn models were linear and were

solved using quadratic programrning (Thompson 198 1).

Trade flow and market share modeIs use two techniques to explain or predict

agiculturai trade flows. The first category uses relatively mechanical techniques to

decompose past changes in the observed trade flows. The second method uses

econometric models in which an equation is estimated to expiain the variation in each

element of the trade flow matrix, as well as trade models in which the elasticity of

substitution among alternative sources of supply &ect the solution.

3.2.3 Partial versus General Equilibriurn Models of Trade

Trade models can be partial or general equilibrium in nature. Partial equilibnum

models look at only one market at the t h e . The principal 'cresult'y of partial equilibrium

models of prke determination in cornpetitive markets is the Marshallian "crossyy diagram

of supply and demand. This kind of model looks at only one market at a time. Partial

equilibrium models link domestic and international prices through pnce transmission

elasticities or a set price wedges. Policies are often limited to pnce wedges and simple

quotas.

General equilibrium models are models of the whole economy that reflect

interrelationships arnong various markets and various economic agents (Nicholson 1992).

While general equilibrium models provide more general results on the impact of policies

on the whole economy, due to the degree of data aggregation they are often unable to

model the impact of sector specific policies or technology changes.

3.2.4 Justz3ing the Choice of a hionspatial Partial Equilibriurn Model

Given the spatial distribution of corn production and consumption, a two-region

model can not capture al1 of the important elements of world trade in corn, Even the

three-region model employed in this study has some limitations, but this simplifj6ng

assumption contributes to the clarity of the results and policy recommendations.

Although spatial models produce source-destination trade flows, they rely heavily

on transportation costs with small changes in fieight rates affecting the results. Knowing

that reliable fieight rates are diEficult to obtain, a nonspatial model, again, seemed to be a

better choice.

Although general equilibrium models take into account ïnterrelationships among

economic agents they tend to be heavily aggregated and are not always convenient for

policy modeling at a fine level of commodity disaggregation. NSO, in the model used in

this study only the change in the price of one good (corn) is considered and the effect of

this change on the prices of other goods in economy is small. Therefore, a partial

equilibrium setting was chosen for the analysis.

The analytical approach to the problem is static. The term "static" does not mean

"changeless", but "timeless". The passage of calendar time is not specifically accounted

for. However, the static supply and demand relationships used in this analysis have been

chosen to represent long-run relationships. They show how quantities demanded and

supplied change in response to price signals after sufficient time has elapsed to allow

both supply and demand to adjust following significant changes in the corn production

technology (Houck 1992).

3.3 PERFECT COMPETITION

This mode1 assumes a large number of suppliers and demanders of each good so that

each of them must be a price taker, Le. perfect cornpetition. Therefore, each demander

represents so small a fkaction of the market that his or her decision of what to buy has no

impact on market pnces (Nicholson 1992). Also, each farmer7s decision on the quantity

to supply does not influence the price he or she receives for its product,

The assumptions of the classicai economic model are easily applied to the corn-

producing sector: few would argue that there are not a large number of corn seliers

(producers)- The assumption of a large number of buyers may be met to a degree at a

central grain exchange in Minneapolis or Chicago, but many agricultural products are

traded in markets in which comparatively few buyers exist. So why then retain the model

of perfect competition? Despite its weaknesses, it comes closer to representing farming

than any other comprehensive model of economic behavior (Debertin 1986).

Mthough it would be useful to recognize that producers of Bt technology will

exercise their monopoly rights, cornpetitive behavior on the side of technology suppliers

is assumed. Although not in accordance with the nature of private investment in research

and development, this decision can be justified by the specific nature of Bt corn and the

fact that its adoption rate is related to the factors like the expectation of the infestation

level and the level of a fanner's risk aversion,

Hence, the economic model used in this study implicitly assumes perfect

competition for al1 economic agents. The next two subsections provide the

rnicroeconornic framework used in the anaiysis.

3.3.1 The Supply Side

Each of the h s in the market tries to maximize its profit by choosing its output

level. The firm's supply curve shows how much it will produce at various possible output

prices. For a profit-maximizing firrn that takes the pnce of its output as given, this curve

consists of the positively sloped segment of the firrn's margind cost curve above the

point of minimum average variable cost. For prices below this level, the h 7 s profit-

maximizing decision is to shut down and produce no output (Nicholson 1992).

Producers' profit maximizing behavior can be described by the following

formula:

x = max{p- y - v - x } .v .x

(3.1)

where p represents output price, y is output, v represents vector of input prices and x is a

vector of inputs. The producer is assurned to choose the combination of variable inputs

that maximizes profit subject to the avaiIabte technology. By applying Hotelling7s lemma

to the profit funcîion supply and input demand functions are obtained.

3.3.2 B e Demand Side

Neoclassical economic theory assumes that individuals who are constrained by

limited incornes will behave as if they were using their purchashg power in such a way

as to achieve the highest possible utility. Although the applications of this model are

quite varied, al1 of them are based on the sarne fundamental mathematical model

(Nicholson 1992). The consumers' problem is to maximize utility with respect to the

budget constraint:

subject to

where xi are goods consumed, pi are their corresponding @ces and rn is the available

incone. The market prices reflect the trade-off among the commodities that individuals

consume. The solution to the optirnization problem gives the consumers' demand

function (Boadway and Bruce 1 984).

In the empirical model, presented in Chapter three, the weIfare effects of different

trade policies regarding the introduction of Bt corn as it aflècts the utility function are not

directly accounted for. The problem is that utility wodd have to be expressed as a

fünction of consumers' preferences towards a new good, genetically modified corn. To

quanti@ these preferences is very di£îïcult since very little data is available at this time to

quant* consumers' reactions to GMO and traditional corn products.

An interesting study in modeling consumers' preferences is represented by the work

of Bureau et al (1998). They try to account for consumers' preferences using the EU-US

trade dispute on hormone treated beef as a case study. The analytical framework assumes

that consumers are imperfectly infonned about the quality of irnports, and the welfare

effects of trade liberalization in the case of credence1 goods are investigated. The

theoretical model in Bureau's study builds on the work of Mussa and Rosen (1978). -

Although very sophisticated in accounting for consumers' preferences theoretically, the

Bureau et al. model is not well suited for ernpiricai analysis.

Before presenting the studies that include empirical analysis the welfare measures

needed for this iype of andysis are reuiewed.

3.4 ME,4SURES OF WELFARE: CONSUMER AND PRODUCER

1 Credence goods are goods whose characteristics cannot be distinguished either before or afier consumption.

In order to compare a number of potential scenarios related to the introduction of

Bt corn, a measure of welfare change associated with each of the scenarios in cornparison

to the base scenario (the situation before Bt corn is introduced) is needed. The changes in

consumer and producer welfare are used as a way to account for the gains fkom trade.

Measuring consumer welfare is more controversial than measuring producer

welfare- There are several potentiai measures of consumer welfare:

1) Consumers' Surplus,

2) Compensating Variation, and

3) Equivalent Variation.

Consumers' surplus (CS) is a partial equilibrium measure of consumer welfare

that is appropriate for the empirical mode1 used in this study, given that the mode1 does

not include an explicit expenditure or utility function.

Consumers' surplus is the consurners' gain fkom trade. It is the amount by which

the value of a consumers' purchases exceed what they actually pay for them.

Geometrically, consumers' surplus is the area under the demand curve d o m to the pnce

paid. Consumers' surplus is based on the Marshallian ( D , ) or uncompensated demand

curve. It reflects both income and substitution effects. Consumers' surplus is the area

p, p, ae on Figure 3.2.

For a continuous, inverse demand fùnction where p= pl and q= q, , consumers'

surplus is - I

CS = %' D (494 (3 -4)

provided this value is positive Figure 3.1).

Compensating variation (CV) and equivalent variation (EV) are both measures of

a consumers' gain fÏom trade that are appropriate in a general equilibrium setting. Both

CV and EV are based on the Hicksian ( D: and DO in Figure 3.2) or compensated

demand curves. Compensating Variation is the arnount of money needed to keep the

consumer on the same indifference curve a$er the change in price. It corresponds to the

area p,p,be in the Figure 3.2, The equivalent variation is the arnount of money that the

consumer needs to forgo the change in price. It corresponds to the area p,p,af in Figure

2.2. CV and EV incorporate only the substitution effect of a pnce change. In general,

CV 2 CS > EV (3 -5)

for a normal good. The results of Willig (1976) show that consumers' surplus is often a

good approximation to the "û-ue" welfare effect when income effects are small.

Producers' surplus is the producers' gain fiom trade. It is a partial equilibrium

measure of producers' rent. Producers' surplus is the amount by which revenue exceeds

the variable costs of production. PS is the area above the marginal cost curve up to the

price received. If the producer is cornpetitive, his marginal cost curve is e q d to his

supply curve. The value of producers' surplus is (Figure 3- 1):

The consumers' and producers' surpluses provide a measure of gains to both

parties. Their sum is called the welfare gain or social gain to a representative consumer

or a group of consumers.

Figure 3.1: Consumers' and Producers' Surplus

Figure 3.2: Consumers' Surplus, Compensating Variation, and Equivalent

Variation

3.5 INTRODUCTION OF A TECHNOLOGICAL INNOVATION

On a microeconomic level, the basic idea in modeling a technological innovation is

that improved production techniques allow farmers to supply a Iarger amount of output at

any given pnce level, resulting from a productivity induced supply shift (Moschini and

Lapan 1997). The analytical fiamework of aimost al1 previous work in the area of

investment in scientific research and development can be represented by the mode1

illustrated in Alston, Norton and Pardey (1995). This modei is shown in Figure 3.3.

Figure 3.3: Benefits from Research

The c w e S, (p) represents the preinnovation supply, S, (p) represents the post-

innovation supply curve, and D@) is the demand curve. In a closed economy partial

equilibrïum model area abcd is a measure of the Ïncrease in economic surplus, what is

ofien called the "gross annual research benefit7' (Moschini and Lappan, 1997).

Based on this fhmework other empirical models can be developed to investigate

returns to research. Alston, Edwards and Freebairn (1988) analyze the effects of a variety

of product market distortions on returns to research.

Moschini and Lapan (1997), however, recognize that an increasing portion of

agricultural R&D cornes fiom pnvate firms and that the innovations that corne from the

private sector are usually protected by the intellectual property rights (PR$. They aiso

recognize that given the opportunity, private agents will exploit their monopoly rights.

Hence they recognize that in the presence of Pb when monopoly profits are possible,

gross benefits fiom agricuitural innovations cannot be measured in the agricdtural

market alone. In this case the area abcd (Figure 3.3) is not an apprapriate estimate of the

benefits fiom private research. Moschini and Lapan develop a k e w o r k for two kinds

of technological innovations: cirastic and non-drastic, and solve for the welfare changes

and monopoly prices in this fiamework. Their simulation results suggest that welfare

changes under the assumption of monopoly profits are smailer than in the conventional

(competitive) framework. This study dso points out that what is conventionaily measured

as benefits ta consumers and agrîcultural producers from R & D could be captrued by the

innovathg finns.

Moschini et al. (1999) extend this line of inquiry to modeling the welfae effects

of Roundup ReadyB soybeans. The model of the soybean complex is based on a

monopolist who markets the technoIogical innovation to a large number of competitive

f m e r s on domestic and international markets. In any country, the total supply of beans

is writien as:

= L ( z ( ~ B Y r , -&) - Y ( P , 3 r , (3 -7)

where YB is total supply of soybeans; L is land allocated to soybeans; de notes profit as

a fimction of soybean price, p, , and the pnce vector of dl inputs (excluding land and

seed) r; S is a constant optimal planting density for seed; w is the price of soybean seed;

and y represents yield per hectare.

Total demaud for soybean seed is written as:

X(p, , r , w) = um,, r ) -&) -6

where X is the demand for soybeans.

The new technology is embedded in the seed. The innovator-monopolist's

probkm is to select the price, w, to charge for the new seed, given that the conventional

seed is available at price W.

The analysis includes three regions (US, South Arnenca and Rest of the World)

that are the main producing regions for soybeans. Numerous scenarios are analyzed. The

specifications used to mode1 the supply side in this thesis are similar to the idea that

Moschini et al. (1999) exploited in analyzing the welfare effects of transgenic soybeans

on trade in the soybean sector.

The most recent work that quantitatively explores the relationship between GMOs

and trade and their effect on welfare in rich and poor countries is a study by Nielsen and

Anderson (2000) that uses a general equilibrium setting. Four different scenarios are

analyzed under the assumption that the effect of adopting GM crops can be captured by a

Hicks-neutral technology shift, i.e. a uniform reduction in ail inputs to obtain the same

level of production (Le. a total factor productivity shock). This aççumption is

questionable; Bt corn, for exarnple, does not directly reduce costs, but improves yieids.

The empirical mode1 used in this study is based on the theoreticaï fiamework and

the studies mentioned above. It is described in the next chapter.

CHAPTER 4: EMPIRICAL MODEL

4.1 INTRODUCTION

Bt corn is a product of biotechnology that is designed to increase the productivity of

corn production through increased corn yields in the case of a European Corn Borer

(ECB) infestation. The model described below tries to capture the main points of

econornics and biology of Bt corn: increased yield in case of ECB infestation and

increased cost of production due to the technology fee attached to the use of Bt corn. The

model also takes into account two other issues regarding the introduction of Bt corn:

technology spillovers and potential consumers' reaction to the introduction of Bt

technology in a three-region setting which is described in the foliowing section.

4.2 REGIONAI, SPECIFICATION

The world is divided into three regions. The regional specification is based on

corn production (FAOSTAT 2000). Consumers' attitudes towards biotechnology are also

taken into account in creating the trading blocs.

The Western Hemisphere (WH) is the main corn producer and corn exporter. This

is due to the fact that the US is the biggest corn producer in the world and is also the

biggest source of traded corn. Genetically rnodified products are generally accepted in the

WH. Consurners' attitudes in the US, Canada and Argentina show that WH consumers

are rather unconcerned about the possible negative effects of biotechnology (Environics

International 1 999).

The European Union (EU) is an importer of corn and corn products. This region,

however, has two relatively large corn producers (France and M y ) . European

consumers are very concerned about the introduction of genetically modified organisms.

The Rest of the World is also a net importer of corn. This region is heterogeneous

and includes the world's largest food importer (Japan), the country with the largest

potentiai in corn production (China) and the coutry that recently announced a set of

stringent d e s about trade in GMOs (Australia). However, for the purposes of this study,

it is assumed that al1 consumers in this region share the same attitudes and al1 producers

have the same technology.

4.3 THE MODEL

There are various techniques used to mode1 agricdtüral markets. This study uses

a synthetic model. It is based on market activity in the year of interest. In order to solve

for synthetic demand and supply equations, the data on key market variables is gathered

and assurned eiasticities are used in obtaining parameter estimates for the empirical

model.

The first year that Bt corn entered commercial production was 1996, so that year

is a logical choice for the baseline - it was the last year when corn yields represented

only traditionally grown corn worldwide. However, 1996 had atypically high corn pnces

due to low corn stocks in the US. Therefore, 1995 is chosen as the baseline year against

which al1 other alternatives are compared.

The situation in the world corn market before the introduction of Bt corn is shown

in Figure 4.1. Panel (a) represents the exporting region (Western Hemisphere) , panel (b)

shows the excess demand and supply curves and panel (c) represents an irnporting region.

The excess supply curve is given as the difference between supply and demand in the

exporting region. By the same token, the excess demand curve is the Merence between

demand and supply in the importing region. -Market clearing is enforced by equating

excess supply and excess demand. For simplicity, the two irnporting regions (European

Union and Rest of the World) are combined in Figures 4.1 - 4.4. Everywhere else in the

study (data, mode1 specifications, results) these are treated as two separate regions.

Figure 4.1: The International Corn Market Before the Introduction of Bt Corn

The introduction of Bt corn causes the supply curve S, to shift outward. This is a

technology-induced shift in supply (Figure 4.2). As a result of the technology-induced

suppIy shift, the excess supply cuve also moves outward to ES' and the world price fails

to pw'.

A pardel shift in the supply curve is assumed. Although the actuai horizontal

distance between the pre- and post-technology supply curves is not known over the entire

pnce range, the calcuiations show that over the price range between US$80 and $ 180

the two curves are parailel. A parallel shift in the supply curve, in general, rnight

overestimate the benefits fkom research (Alston, Norton and Pardey 1984).

Figure 4.2: Effect of a Technology-Induced Supply Shift in the Exporting Region

Technology spillovers arise when the other two regions are able to adopt the

results of WH research (Alston, Norton and Pardey 1984). Thus, the research-induced

supply shift in the Western Hemisphere may be accornpanied by a supply shift in cither

the EU or ROW regions (or both). In Figure 4.3 dl cuves are as previously d e k e d but

there are two extra curves: S, ' and ED ' which illustrate the effect of adopting Bt

technology in the importing regions. As a result, the world price fûrther decreases to pw".

Figure 4.3: Effect of a Technology Spiiiover from the Exporting Region to the Importing Region

In the case of consurners' non-acceptance of GMOs in the importing region,

demand fdls in that region. This is shown in Figure 4.4 as an inward demand shift to D, '

in the importing region. As a result, the excess demand curve (panel (b)) also shifis

inward. The world pnce further decreases to pw"'. It is worth pointing out that this shift

in demand c m happen even without the technology spillover; it could be caused solely by

Bt corn imports into the EU.

54

Figure 4.4: Effects of a Technology SpiHover and Negative Consumer Attitudes in the Importing Region

(a) @)

The four three-panel diagrams (Figures 4.1-4.4) provide the basic fiamework for

the eIeven sllriulations used in the study. Each of the simulations is a 'variation on the

theme' shown in the figures above.

4- 3.1 Model Speczfication

There are seven endogenous variables and seven equations that describe the corn

market in the Western Hernisphere. The European Union and Rest of the World regions

are each modeled with eight equations representing eight endogenous variables to explain

them. The first seven equations are simiiar in structure across the regions with the only

difference being that each uses region-specific data. These seven equations explain

demand for food, demand for feed, producers' profit, land allocated to the production of

corn, corn supply, corn production and net û-ade in each of the regions. The European

Union and Rest of the World each have a price linkage equation to account for their

pnces which are linked to the price in the Western Hemisphere. The Western Hemisphere

pnce is the world price and is solved for simultaneously by equating world srrpply to

world demand.

The following subsections present the variables and the equations that define

them.

4-3. I . 1. Demand

Tbere are separate demand equations for food dfo) and feed dfe) in each of the

regions. In the case of consumers' non-acceptance of GMOs, dernand for food, feed or

both can shift inward for the region in question. The different policy scenarios (described

in detail in Chapter 5) are based, mong other things, on various degrees of the shifl in

demand in one, two or all three regions. Demand for food ( d ( fo ) , ) and demand for feed

( d ( fe), ) in Figure 4.5 denote the baseline demand curves for food and feed corn in a

region. The curves d( fo) , and d( fe) , show schematically new demand curves that

mirror the assumed fall in demand for food andor feed corn as a result of consumers'

concerns over Bt technology.

Figure 4.5: Demand for Corn Food and Feed Production in a Region

Both the demand for food and feed are assurneci to be linear with the general

form:

dfo) = a + b - p

dCfe) = c + d - p

where:

dfo) = demand for food in a region in tomes,

d B ) = demand for feed in a region in tonnes,

a = synthetic parameter representing the intercept of the food demand c w e ,

b = synthetic parameter representing the slope of the food demand curve,

c = synthetic parmeter representing the intercept of the feed demand curve,

d = synthetic parameter representing the siope of the feed demand curve, and

p = price of corn in US dollars (US dollars are used throughout the analysis).

4.3.1.2 Corn Land Planted

@n the supply side, the amount of land allocated to the production of corn is

modeled as a double logarithmic function and solved for as the synthetic equation:

InL = InA +- & - h m (4-3)

where:

L = amount of land used in corn production (ha),

A = synthetic coefficient, and

E = elasticity of land supply with respect to profit.

In deciding how much land to allocate to the production of corn producers

responded to changes in their profit:

~ = p - y -WX-Ws -G

where:

n = profit in $ per hectare,

p = pnce of corn ($/t),

y = yield of corn in tonnes per hectare,

X = vector of input use except seecf (quaatityha),

W = vector of variable input pices except the price of seed ($/ha),

W;. = pnce of seed ($/ha), and

G = quantity of seed needed for planting a hectare of corn.

4-3.1.3 Corn Production

P(nGii4) in Figure 4.6 represents the production of corn before the introduction of

the transgenic technology and P(GW represents the production of corn after the yield-

increasing GMO techndogy has been adopted in a region.

Figure 4.6: The Corn Production Curve Before and After Introduction of Bt Technology

Corn production is a function of the land allocated to corn, and yield per hectare.

p r o d = L - y (4-5)

where :

prod = production of corn in tonnes,

L = land allocated to the production of corn (ha), and

y = yield of corn (tlha).

3.3.1.4 Corn Yield

In the US, different subspecies of ECB produce one to four generations of borer

per growing season, but two-generation corn borers dominate the central Corn Belt

(Mason et al. 1996). The amount of yield loss caused by ECB depends on the level of

infestation in each generation, which in turn depends on a variety of weather factors,

Estimates of damage Vary, but for the purpose of this analysis the following estirnates of

yield decreases are adopted:

-the first generation of corn borers reduces corn yield by five percent per borer per

plant (bl=0.05);

-the second generation ECB causes a yield loss of three percent per borer per

plant (b2=0.03) (Bessin 1998; Bode and Caivin 1990; Mason et ai. 1996).

Therefore, the yield of Bt corn can be expressed as

where:

y = yield of traditional corn (tlha);

a = number of borer larvae of first generation per plant;

E(a) = expected number of borer larvae of first generation per plant;

c = number of borer larvae of first generation per plant;

E(c) = expected number of borer larvae of second generation per plant;

bl = yield decrease by one first generation larvae of ECB (0.05);

b2 = yield decrease by one second generation larvae of ECB (0.63).

As it can be seen, there is a probability distribution on the expected number of

borers in each generation. (Borers of 3rd and 4h generation are not considered

economically signincant and therefore are not included in the specification).

4 3 - 1.5 Corn Supply

Corn supply is equal to the sum of the arnount supplied and the stocks of corn at

the beginning of the year (corn stocks are considered exogenous in this analysis).

S = prod + Bst (4-7)

where :

S = supply of corn in a region in tonnes, and

Bst = stocks at the begirining of 1995 in tomes.

4.3.1.6 Corn Net Trade

Net trade is calculated as the difference between total production and total

demand for corn in a region.

nt = S - ( d o + dfe)) - Est

where:

nt = net trade in tonnes, and

Est = ending stocks (tomes).

The sign of net trade shows whether a region is a net exporter or a net importer. In

the base scenario the Western Hemisphere is a net corn exporter while the other two

regions (the European Union and Rest of the World) are net corn importers.

4.3.1.7 Corn Prices

The Western Kemisphere price is the world price because it is the price in two

regions and the price in the third region (EU) is Iïnked to this price by addZng a fixed

margin to it.

The EU price is obtained by adding $90.76 to the WH price in aii scenarios. The

rationale for this is the data for 1995 in which the intemal EU price is $90.76 higher than

the WH price. This $90.76 accounts for the EU tanffand the fi-eight cost t o the EU.

Therefore,

peu = pwh + 90.76 (4-9)

where:

peu = pnce of corn in the EU ($US/t), and

pwh = price of corn in the WH ($US/t).

The price of corn in the Rest of the World is set equal to the WH price. Therefore,

pr = pwh (4.1 O )

where:

pr = price of grain corn in the Rest of the World ($US/t).

4.3.1.8 Closingidenti&

In order to make sure that net imports equal net exports for the wodd as a whole,

the following identity is used:

ntr + ntwh + nteu = O (4.1 1)

where:

nh. = net trade in the Rest of the World (t),

n M i = net trade in Western Hemisphere, and

nteu = net trade in the European Union.

4-3.1.9 Mnernonics

In this subsection the mnemonics used in this study are listed. The list contains al1

of the endogenous variables in the model:

dwhfol = demand for Food in Western Hemisphere,

deufol = demand for Food in EU,

&fol = demand for Food in Rest of World,

dwhfel = demand for Feed in WH,

deufel = demand for Feed in EU,

drfel = demand for Feed in ROW,

prwhl = profit in WH,

preul = profit in EU,

prrl = profit in RO W,

Zwhl = land allocated to the production of corn in WH,

Zezrl = land allocated to the production of corn in EU,

Zrl = land allocated to the production of corn in ROW,

prodtvhl = production of corn in WH,

prodeul = production of corn in EU,

prodrl = production of corn in ROW,

swhl= supply in WH,

seul = supply in EU,

srl = supply in ROW,

nfwh = net Trade in WH,

nteu = net Trade in EU,

ntr = net Trade in ROW,

pwhl = price in WH,

peul = pnce in EU,

prl = pnce in RO W,

pwhnonl = pnce of non-GMO corn in WH (appears only in scenario 1 l),

pezuzonl = price of non-GMO corn in EU (appears only in scenario 1 1), and

prnonl = price of non-GMO corn in ROW (appears only in scenario 1 1).

4.4 DATA

Corn is one of the most studied crops in North America. Data on corn production

and trade abound in the US and Canada but in other regions, included in this analysis,

there is significantly less ùiformation available on various aspects of corn production.

Therefore, in calibrating the mode1 certain assumptions are made. Finding the required

data was particularly difficdt for the Rest of the World for two reasons: 1) the ROW is a

heterogeneous region that is made up of corntries that d s e r substantialiy; and 2) some of

. the countrîes in the region (e.g.China) have a big corn market but do not publish much

data.

4- 4- I Qzrantities Demanded and Supplied

The quantity demanded for food, quantity demanded for feed, as weil as the

quantity produced are based on the USDA's Foreign Agricuitural Service files. Al1 of the

data is for 1995. Table 4.1 presents the information as well as data on area, yields, trade

and stocks.

Table 4.1: Corn Production, Consumption and Trade in 1995

Variable

Production

Area Harvested

Yield

Imports

1 tomes 1 1 I

Units

O00 tomes

O00 ha

tonnes

, 1 1 1

O00 tonnes

Consumption I tonnes I I I

Western Hemisphere

265,252

56,262

4.716

Exports I I t l

14,359

7,480

Food

European Union 29,224

3,732

7.83 1

O00 6,879

I 1 I 1

I

Source: USDA

Rest of World

222,644

74,242

2.998

1 0,42 1

65,299

O00

Feed 1 O00 Consurnption Beginning Stocks Ending Stocks

4.4- 2 Elasticis of Demand

The pnce elasticity of corn2 in food uses is very low. A value of -0.1 is used as a

price elasticity of food demand in the Western Hemisphere and the European Union. The

54,878

Elasticity estimates are based on personal communication with Dr. K. Meilke

70,645

176,3 90 1 24,543 tonnes

O00 tomes

O00 tonnes

168,117

8,225

5 1,487

18,674

94,655

2,934

2,33 1

39,657

47,527

pnce elasticity is assumed to be somewhat larger in the Rest of the World. Its value is set

at -0-2. This assumption is based on the fact that consumers in developing countries

(which dominate the Rest of the World region) consume corn in less processed forms

and are more responsive to the changes in corn prices as a result of lower average

incomes than in the EU and WH-

In general, the demand for corn used in feed is more responsive to changes in

price because it has more substitutes than food corn. The price elasticity of feed demand

is assumed to be -0.4 in the Western Hemisphere and -0.6 is used in the European Union

and the Rest of the World. Both the European Union and the Rest of the World are corn

importers.

4.3.3 Elasticiiy of Supply

There are various estimates of the price elasticity of corn yields. Houck and

Gallagher (1 976) corne up with a broad range: they estimate that yield elasticities with

respect to corn prices lie between 0.24 to 0.76. The sarne authors argue that taking

acreage response estimates as an approximation to the total supply elasticity (total supply

elasticity is the sum of the acreage response and yield response) leads to seriously

underestirnating the price responsiveness of corn production when fertilizer prices are

held constant. Houck and Gallagher argue that the total corn supply elasticity may

actually be as high as 1 .O, ceteris paribus,

Whittaker and Bancroft (1979) estimate the corn area elasticity to be 0.22 using

double logharitmic fùnctionai fonns. This is a bit higher than sorne earlier estimates (e.g.

Ryan and Abel 1973) which are d l in the range of 0.12 to 0.17. Reed and Riggins (1 98 1 )

cornpared disaggregate data at the state level with the aggregate ones in Kentucky. In

their çtudy the elasticity of corn acreage with respect to the relative price of corn ranged

fkom 0.34 to 0.56 in the short m and from 0.93 to 2.07 in the long run. These elasticities

are much higher than Whitacker and Bancroft's , but it shouid be taken into account that

in Kentucky some pastures can easily be turned into cropland when the pnces are

favorable.

Menz and Pardey (1983) explore the relationship between technology and corn

yields, considering yield plateaus and price responsiveness. Without giving specific

estirnates, the study challenges Houck and Gallagher's findings.

After considering the available estimates on the elasticity of corn supply with

respect to changes in price, the price elasticity of supply is set to 0.5 in d l three regions.

Results were also generated using a supply eIasticity of 1.0, but they are not reported

here.

4.4.4 Yield lncrease of Bt Corn

The main characteristic of Bt corn is that it increases corn yields in the case of a

European Corn Borer infestation.

The numbers on average yield loss due to the ECB infestation are based on data

fiom numerous US exqension service surveys conducted by the Universities of Illinois,

Minnesota and Wisconsin during the fd l seasons of 1943 through 1997 (Nelson et ai.

1999). Time series are based on the number of fifth instar', second generation borers per

corn stalk.

Instars are growth stages of ECB larvae

As discussed earlier European Corn Borer larvae of first generation decrease the

corn yield by about 5 percent and ECB larvae of second generation decrease the corn

yield by about 3 percent (Nelson et al. 1999). Based on the average yield loss due to ECB

infestation in three Midwestern states in 54 years, Nelson et al. assume that corn borer

larvae infestation reduces per-acre corn yields on average by 3.53 percent. Another recent

study (Hyde et al. 1999) finds that the probability of having ECB in the US is 25 percent.

Hence, there is a probabilis distribution on the infestation ievel and consequently yield

increases due to Bt corn.

Analyzing the estirnates used in both studies, it c m be concluded that Bt corn

increases corn yields more than 3.53 percent (up to 3.53 / 0.25) in the areas actuaily

affected by the pest. Or,

- Y(Bt Increase) = 0.25. (0.05. E(b, ) + 0.03 - E(b, )) = 3 -53

where:

- Y (Br Increase) = average yield increase due to the use of Bt corn, in percentage;

E(b, ) = expected number of larvae of first generation; and

E(b2 ) = expected number of larvae of second generation.

In general, the corn yield decrease due to a ECB ùifestation is between 0-1 8

percent under natural infestation and between 0-40 percent under artificial (manual)

infestation. The actual infestation level varies greatly from year - to - year and depends

on numerous factors, including weather.

Given the lack of data on the probability distribution of ECB, the parameter that

reflects the Bt corn yieId increase enters the mode1 as an average value rather than a

probability distribution. The Nelson et al. estimate of a yield increase of 3.53 percent is

used as an average value for the Western Hemisphere. Although the available

informatiod suggests that ECB is not as significant a pest in South Amenca as it is in

the US and Canada, gïven the importance of North America in WH corn production the

3.53 percent average yield increase is used for the entire region.

In Europe there are some regions that have a history of hi& ECB populations and

damage, and other areas that receive Little damage5. Overall, however, the average yield

Ioss is similar to that in the WH. Based on this, a value of 3.53 percent is used as an

average yield increase of Bt corn in the EU.

In tropical regions, ECB is not an economically significant pest but there are other

insects such as fa11 armysvorm (Spodoptera), corn earworm (HeZÏcoverpa) and other corn

borers (Diafrea) that adversely &ect corn yield6. Bt corn is very effective against

Dialrea, but offers only moderate protection against Spodoptera and Helicoverpa. Given

the available information on Pest darnage, an average yield increase of Bt corn in the Rest

of the World of 2-53 percent is used.

4 3.5 Cash Costs

The Ontario corn budget for 1999 is used as a benchmark for the cost of corn

production in the Western Hemisphere (Appendix A). The budget is for non-Bt seed7 . A

budget for Bt corn is calculated by assuming that the original OMAFRA cost estimate for

insecticides is cut in half because it is assumed that half of this expense is used for

4 Moellenenbeck, D. 2000. Personal communication. Moellenenbeck, D. 2000. Persona1 communication. MoelIenenbeck, D. 2000. Personal communication

7 Reesor, C. 2000. Personal communication.

treatments against ECB . Aithough ECB treatments are not considered an economically

sound option in this study the deduction of $12.5 fiom the original insecticide expense

recognizes that Ontario farmers do treat agaïnst ECB but this practice is not widespread

throughout the entire WH region. Some expenses like marketing fees, consuiting and land

rents are set equal to zero. What is Left are the cash costs of producing corn.

The EU is a region consisting of 15 countries that ciiffer in climatic conditions,

percentage of fanriers in total population, GDP and many other things. There is no

average EU corn budget available. Given the fact that the EU has higher prices of various

agricultural inputs, the cost of producing corn in this region is assumed to be 10 percent

higher than in the Western Hemisphere. This gives $320/ha as a value for variable inputs

in the European Union.

The Rest of the World is even more diverse than the EU. China is the biggest

producer of corn in this region. In approximating the cost of producing corn in this region

it should be kept in rnind that even if the corn budget for most of the countries were

available, it would not reflect the cost of inputs precisely as a resdt of currency

differences. Using purchasing power parity exchange rates is one way around this

problem. It should be mentioned that smaller f m e r s in less developed regions have very

low productivity so it would be possible to have corn fiom China or Indonesia that costs

more to produce than the same amount of corn fiom the US or Canada.

Given the facts mentioned above, an official Thai corn budget is used to estimate

the production costs for corn in the Rest of the World. The Thai budget reflects costs 30

percent less than the corn budget for the Western Hemisphere. Its nominal value is

$200US/ha.

4.4 6 Cost of Seed

In the Western Hernisphere the price of traditional seed is assumed to be $77/ha,

There are older, lower yielding varieties that are lower priced but they are less popular.

Many f m e r s find that the increased yield is worth the seed price premiurn in both

regular and Bt seeds. Estimates of the cost of Bt seed over and above regular seed are

fiom $15 - 30/hectar, with $20/ha being a common figure quoted. This study dso

assumes mark-up of $20/ha.

The price of seed corn varies across the EU. In France seed cos& the same as in

the US. The prices in Italy, Spain and Portugal are about 20-30 percent higher8 .

Therefore, the cost of seed in the EU is considered to be 10 percent higher than in the

Western Hemisphere.

By the same token, the mark-up on Bt seed is considered to be 10 percent higher

than in the WH, although it is alrnost a hypotheticai assumption, given that the planting

of penetically modified corn is not ailowed in the EU. Even the EU-approved varieties

are approved only for import, not for planting.

Given the lack of uniform data for the ROW, the cost of seed is considered to be

about 30 percent lower than in the WH. Its value is assurned to be $50/ha. Mark-up on Bt

corn is also considered to be 30percent less than in the WH. Its value is assumed to be

$1 3 US/ha.

--- -

' Madjarac S. 2000. Personal communication

4.4.7 Corn Price

The Chicago spot price for 1995' is used as a base value for the Western

Hemisphere or world price. Its average value for the year in question is $109.445 USlt

(USDA 1996)-

The European corn price is a weighted average of selling corn prices in the

individual EU1 5 countries that have a corn markets (Appendix B). Its value for 1995 is

$200.21/t. In the mode1 the WH and EU prices are related based on these values.

The Chicago spot price for 1995 ($109.445 USlt) is used as a baseline price for

the third region (the Rest of the World). This is due to the fact that the Chicago spot price

is used as a reference price worldwide (except for in the EU).

Calendar year

=able 4.2: Overview of 1995 Data Used in EmpVical Analysis

I 1 1

DEMANDFOR 1 70,645,000 t 1 8,225,000 t 1 94,655,000 t FOOD 1 f 1

VARIABLE WESTERN EEMISPHERE

EUROPEAN UNION

REST OF THE WORLD

1 I I

DEMANDFOR 1 176,390,000 t FEED

IELASTICITY OF FOOD DEMAND ELASTICITY OF FEED DEMAND

SUPPLY

24,543,000 t 1 168,117,000 t

I I 1

-0.1

-0.4

265,252,000 t

SUPPLY YLELD

O -5 ELASTICZTY OF 1 0.5

AVEAGE YIELD DECREASE DUE

TO ECB CASH COST OF OTKER rN-PUTS

-0.1

-0.6

29,224,000 t

0.5

4.716

COST OF SEED

-0.2

-0.6

222,644,000 t

3 S3percent

29 1.5 $US/ha

MARK-UP FOR BT CORN SEED

PRICE

7.841

77 $US/ha

2.999

3 S3percent

320.6 $US/ha

Avg 20 $US/ha

109.445 $US/t

2.53percent

200 $US/ha

84.7 $US/ha 50 $US/ha

Avg 22 $US/ha

200.21 $US/t

Avg 13 $US/ha

109.445 $US/ha

73

CHAPTER 5: SCENARIOS AND RESULTS

5.1 INTRODUCTION

Eleven counter factual policy scenarios are constructed to capture the essence of

world corn trade under dBerent potentiai situations. Ali of the scenarios are considered

to be "WTO legai". That means that in the case of a European ban on corn imports, a

possible cornplaint by the Western Hemisphere to the WTO is not taken into account,

although it wodd probably happen. Possible retaliatory measures taken by the Western

Hemisphere do not enter the model.

The grouping of the poIicy scenarios is based on the similarity of policies - or

consumer responses - behind them. A detailed description of the scenarios is given in

Table 5.1. Three additional scenarios that are variations of scenarios 5,6 and 9 are

described in Appendix D.

Table 5.1: Overview of Policy Scenarios

SCENAEUO (DUE TO USE OF BT

1 (pre-GMO)

WH: 0'" EU: O ROW: O

2 (all-GMO)

WH- 3.53percent EU: 3.53percent ROW: 2.53percent

3 (only WH GMO)

I 6 I WH: 3.53percent

WH: 3.53percent " L

EU: O ROW: 2.53percent

4 (technology for fiee)

WH: 353percent z$-?g"nt

I 8 1 WH: 3.53percent

7 (EU ban)

WH: 333percent EU: O ROW: 2.53percent

1 9 ( WH: 3.53percent

(EU ban + backlash in 1 W H ~ ~ R O W ) " 2.53persent

(WH produces, EU and 1 ROW cons backiash)

I

11 1 WH: 3.53percent o f feed

" 10

(WH "island" ) WH: 3.53percent EU: O ROW: O

DEMAND DECREASE AFFECTED

(segregation)

WH: O EU: O Free Trade" ROW: O

EU: O Free T n d e ROW: O

WH: O EU: O Free Trade ROW: O

demand EU: 3.53percent o f feed

WH: O EU: O ROW: O

; demand

Free T n d e

EU: 20percent o f food I Free Trade demand ROW:

EU: 20percent o f food and Free Tnde feed d.

EU: O ROW: O

EU ban on corn imports

WH: IOpercent of food demand EU ban on corn imporrs EU: O ROW: lopercent o f food WH: O EU: 1 Opercent o f food and I Free Trade feed d. R0W:lOpercent o f food and 1 V?H: O 1 EU: O ROW: O

WH docs not trade with two other regions

WH: O EU: O ROW: O

Food sel f-su ficient

10 Planting o f GMOs is not allowed if yield increase is zero IL "Free Trade" assumes EU tariff on irnported corn is maintained

5.2 DESCRIPTION OF SCENARIOS AND RESULTS

In this section, the results fiom five groupings of the scenarios described in Tabie

5.1 are presented .

5.2.1 Scenarios 1,2,3 and 4: No Consumer Backlash, Free Trade

Scenario 1 is the pre-GMO scenario. It depicts the situation in 1995. None of the

regions produces GMOs and ''fiee trade" in corn among the Western Hemisphere,

European Union and Rest of the World is assumed. The term "fkee trade" actually means

trade where tariffs are the only border measure: there is no ban on imports and exports

but the EU does have a tariff (levy) on imported corn. The cash costs of production are

based on the Ontario Corn Budget data and the assumed mark-up on Bt seed is $20/ha.

Al1 costs are per hectare and in US dollars. The cash cost of growing corn in the EU is

assumed to be about 10percent higher, and for the ROW about 3Opercent lower than in

the WH.

In scenarios 2,3 and 4 there is no consumer backlash against products of

biotechnology and fkee trade in GMOs among the three regions is assumed. The

difference between the three scenarios in this group is in the way the new technology is

introduced. In scenario 2, al1 three regions adopt and purchase Bt technology. In scenario

3 , only the WH adopts and buys Bt technology. In scenario 4, al1 three regions adopt and

are assumed to be able to purchase Bt technology for fiee. The purpose of scenario 4 is to

see how the costs and benefits change if Bt technology was provided by public research

and development. The yieId increase due to the use of biotechnology in the Western

Hemisphere and Europe is 3.53 percent and in the Rest of the World it is 2.53 percent.

The increase in cash costs in al1 GMO scenarios is 30 percent of the additional cost of Bt

corn seed. This is based on the fact that the probability of having European Corn Borer

infestation is about 25 percent in the US. Since fanners are risk averse more than 25

percent of the total corn acreage wiil be planted to Bt corn in fact, this study assumes 30

percent. It is important to point out that that the Bt gene in corn is not a trait that is

profitable for al1 fme r s . Therefore, there will always be a significant area of corn

planted with non-Bt hybrids. This yie1d increase assumption holds for al1 of the scenarios

where Bt corn is being produced.

The results for each scenario are reported in detail in Appendix C. The simulation

results for scenario 1 give the base values - demands for food and feed, profit, supply,

production and net trade that were used to constnict the synthetic demand equations.

Since these numbers represent a true market situation in 1995, they shodd be put into

perspective. Here are a couple of comparisons- The demand for food in the Western

Hemisphere (70 million tomes) is less than one-half the demand for feed (176 million

tonnes) in the same region. The demand for food in Europe is about 1/9 (8 million

tomes) the demand for food in the WH. The demand for feed in the EU (25 million

tomes) is about 117 the demand for feed in the WH. The Rest of the World is the largest

demand region with food demand equaling 95 million tonnes, while feed demand in the

sarne region is 168 million tomes.

77

Figure 5.1: Cornparison of Market Sizes in the Three Regions (Base Scenario)

Although the Western Hemisphere is not the biggest region it has the largest

values of consumers' and producers' surplus and total welfare. The WH producers'

surplus is eight billion dollars, consurners' surplus is 63 billion dollars and total welfare

is 71 billion dollars. In the EU, producers' surplus is about four and consumers' surplus

about 12 billion dollars. From the fact that EU corn f m e r s produce about 1/9 the corn as

WH b e r s and have producers' surplus equal to 1/2 their WH counterparts, it is

obvious that producers' surplus (return to fixed factors of production) per hectare is much

higher in Europe ($1 158ha) than in the Americas ($148/ha) or in the Rest of the World

($785a). Producers in the ROW - the biggest region - have only about $5.8 billion in

producers' surplus, and consumers' surplus in this region is $41 billion. A detailed

breakdown of costs and revenues for each region are reported in Table 5.2. The profit per

hectare is multiplied by the quantity of land planted to yield the producer surplus figures

reported here.

Table 5.2: The Structure of Economic Welfare in the Three Regions for Scenario 1

1 WH EU ROW 1

Yield (Tlha)

The acceptance of GMOs by al1 regions (scenario 2) lowers the price in the

Western Hemisphere (the world price) by $3.1 per tome ($106.34) which is about

2.8percent lower than the base scenario. In scenarÏo 3, where only one region (WH)

produces GMOs the price goes up compared to scenario 2 (to $107.55) but is still lower

than under the base scenario. This is due to the fact that in scenario 3 the increase in

supply is less than in scenario 2 . Direct beneficiaries of this fact are producers in the

Western Hemisphere for which this is the best of ail scenarios, with producers' surplus

equaling $8.55 billion. It is interesting that for WH producers the next best set of

assumptions is scenario 1 or the pre-GMO situation. It is even better than the cctechnoIogy

for fiee" scenario (scenario 4) when al1 countries adopt GMOs. A sumrnary of the

welfare resdts by regions and scenarios is given in Tables 5.8 - 5.13.

In scenario 4 where it is assumed Bt technology is given to f m e r s for fkee, the

world pnce goes down 3.8 percent compared to the base scenario ($105.3). Although

hypothetical because biotechnology has already been developed using private research

4.7 16

Gross Revenue ($US/ha)

Cost of Other Inputs ($US/ha)

($Usha) Gross Margin

($Usha)

516.17

29 1 .50

1567.84

320.60

7.83 1

328.13

200

147.66

2.998

1162.54 78.13

and deveIopment, scenarïo 4 gives severd interesting results. They are significant since

they underline the difference that public research makes when compared with pnvately

fimded investment in new technology. The ccTechnology for fiee" scenario gives the best

overall (total welfkre) results for both the Western Hemisphere and the European Union,

An interesting implication of this scenario is that the destiny of transgenics might have

been different had they been developed by public institutions - Le. universities. Scenario

4 is also the best scenario for consurners' surplus values in the EU and Rest of the World.

It is worth mentioning again that the fkee technology assumption has more

theoretical than practical value. If this scenario is elirninated fiom the analysis because of

its inapplicability to the present situation regarding investments in biotech, the situation is

as follows: The best value of total welfare for the Western Hemisphere is given by

scenario 3 (only the WH adopts Bt corn), and the best value of total welfare in the

European Union is given by scenarîo 2 (everyone adopts Bt corn). The paradoxical resuit

for the EU foIlows from the fact that the EU is a net importer. Table 5.3 summarizes

prices for each region for scenarios 1 to 4.

Table 5.3: Regional Price Variations for Scenarios 1,2,3 and 4

Scenario

1 (pre-GMO)

2 (al 1-GMO)

3 (only WH GMO)

4 (technology for free)

WH price

*Numbers in brackets represent the change f?om base @re-GMO scenario)

109.45

106.34 (-2.85)* 107.55 (-1 -74) 105.3 1 (-3.79)

EU prîce RO W price

200.15

197.10 (-1 -5s) 198.3 1 (-0.95) 196.07 (-2.07)

1 09.45

106.34 (-2.85) 107.55 (- 1.74) 105.3 1 (-3 -79)

5.2-2 Scenarios 5 and 6: Corn Demand Falls in the EU

In these scenarios, the Western Hemisphere and the Rest of the World produce

transgenic corn and corn yields increase in these two regions by 3.53 percent and 2.53

percent respectively. In scenarios 5 and 6, consumers in the EU react negatively to the

introduction of biotechnology, and European f m e r s do not produce Bt corn. Since corn

is imported fiom the WH fieely (dthough there is a EU taria, European food demand

fdls 20 percent (1.645 mm) in scenario 5 and European food and feed demand fa11 20

percent (1 -645 mmt and 4.909 mmt respectively) in scenario 6.

In scenario 5, the pnce in the Western Hemisphere decreases 2.8 percent relative

to the base ($106.34) which is the same value as in scenarîo 2. The value of producers'

surplus in the WH is $8.05 billion, again the same as in scenario 2, and 3 percent below

the pre-GMO scenario. Producers' surplus in the EU decreases 3- 1 percent compared to

the base. The ROW producers lose 9.8 percent compared to the pre-GMO scenario. Total

welfare goes up in the WH (0.7 percent) and ROW (0.5 percent) and falls silbstantially in

the EU ( 18.3 percent) due to the huge fdl in food demand in this region. Scenario 5, as a

result of the food demand cuve shift in the EU gives tbe smallest value for consumers'

surplus for food in the European Union.

in Scenario 6, when both EU food and feed demand shift down M e r decreases

the corn price to $105.90. The value of producers' surplus in al1 three regions represents

the continuation of the results s h o w in scenario 5. It M e r decreases to $7.88 billion in

the Western Hemisphere, which is 5.1 percent lower than in the pre-GMO scenario.

Producers' welfare in Europe decreases 3.6 percent compared to the base scenario, and in

the Rest of the World prodücers' surplus decreases 12.2 percent compared to the base.

The consumers' surplus values for the WH and ROW rise fiuther (due to the fdl in the

world price) but fall for the EU. Scenario 6 gives the lowest values for consumers'

surplus and total welfare in Europe. The regional prices for scenarios 5 and 6 are

surnmarized in Table 5.4.

Table 5.4: Regionai Price Variations for Scenarios 5 and 6

Scenario

5.2.3 Scenarios 7,8 and 10: One of the Regions 1s Isolateci

In scenario 7 anti-GMO sentiment in Europe is so strong that the EU Government

introduces a ban on corn trade with the two other regions. The Western Hemisphere and

the Rest of the World still produce GMOs and the EU does not. In scenario 8, consumers

in the WH and ROW dso adopt negative attitudes towards transgenics (although these

two regions continue to produce Bt corn), so the demand for food in the two regions

decreases 10 percent. In simulating scenarios 7 and 8 the link between the EU and world

(WH and ROW) price is removed, so the EU price is an autarky pnce (no trade).

In scenario 10, neither Europe nor the Rest of the World produce Bt corn due to

consumer backlash. These two regions trade arnong themselves and the Western

Hemisphere is isolated because it is the only region that produces GMOs. The American

pRce is now an autarlq price. The European price is linked to the ROW price. The

"shock" is simulated by setting net trade equal to zero in the Western Hemisphere.

5 (food d. faIIs in EU)

6 (both d. fail in EU)

WH pnce

"Numbers in brackets represent the change &om base (pre-GMO scenario)

106-34 (-2,85)* 105.90 (-3 -24)

EU price RO W price

197.10 (-1 -55) 196.66 (-1 -77)

106.34 (-2.85) 105.90 (-3.24)

In scenario 7, the world price is $106.17. The EU price, which is now

independent fiom the world price, is $2 17.16. Producers' surplus does not change

significantly in the WH and R û W compared to its level in scenarios 5 and 6. Europe has

the greatest producers' surplus (1 7.6 percent compared to the base scenario) lmder this

and scenario 8. Producers' surplus is greater than $5 billion in the EU due to the high

autarky price, which is 8.5 percent higher than the pre-GMO price.

In scenario 8, the world pnce is $104.70, due to the fa11 in food demand in the

WH and ROW. The EU price remains unchanged compared to scenario 7. Scenario 8

gives the second lowest value of producers' surplus in the Western Hemisphere and the

lowest value of consumers' surplus (10 percent lower than in scenario 1) and total

welfare in the region (also 10percent lower than the base), The low value of producers'

surplus is due to the iow price and the low value of consumers' surplus is due to the

assumed shift in demand. The value of total welfare in the Arnericas is about $64 billion.

The lowest world price that the mode1 gives is obtained for scenario when the WH

is isolated (scenario 10). It is $96.7 1, or 1 1.6 percent lower than the pre-GMO price. Not

s~rprisingly the value of producers' surplus in the Western Hemisphere is 46 percent

smaller than under scenario 1. The value of total welfare in the Americas is 0.9 percent

($0.6 billion) lower than under the base assumptions. Producers' surplus in the EU is 10

percent larger than in the pre-GMO scenario due to the high European price ($210.02).

The most interesthg outcome of scenario 10 is in the ROW region. Due to the ban

imposed on trade with the WH, the Rest of the World becomes a net exporter of corn, the

only scenario where this happens. The jump in producers' surplus in the ROW is huge

equaling more than 60 percent (or $3.5 billion). Not surprisingly this set of assumptions

gives the largest total welfare in the region- Its value is about $48 biIIion which is an

increase of 2.2 percent compared to scenario 1 ($47 billion). The change in consumers'

surplus in the WH is positive (due to the low prÏce) and negative in the ROW and EU

compared to their base values, since the latter two regions have higher prices in scenario

10 than under the base scenario.

Table 5.5: Regional Price Variations for Scenarios 7,s and 10

I Scenario

7 (EU ban)

8 (EU ban+-backiash)

10

5-24 Scenario 9: Demand Falls in the European Union and in the Rest of the WorZd

(onIy WH GMO)

In Scenario 9, ody the W H produces GMOs. The EU and ROW do not produce

WH price

106.17 (-2.99)* 104.70 (-4.3 5) 96.7 1

GMOs but they are present on their markets because of fiee trade with the Western

I *Numbers in brackets represent the change fi-orn base (pre-GMO scenario)

(-1 1.64)

Hernisphere- As a result of consumer concerns about GMOs, both food and feed demand

EU price

217.16 (8 -46) 217.16 (8 -46) 2 10.02

in Europe and the Rest of the World fidl by 10 percent.

RO W price

106.17 (-2.99) 104.70 (-4.3 5 ) 1 19.26

(4.90)

This simulation generates a world price of $104.90. This is the lowest world price

(8-96)

under any of the fiee trade scenarios. It is 4.16 percent lower than the 1995 price. Despite

the low price and the 10 percent fd l in producers' surplus, this scenario still gives a total

welfare value that is 0.4 percent greater than the pre-GMO welfare in the WH given the

large increase in consumers' surplus. Producers' surplus and total welfare in both other

regions fall in scenario 9. Scenario 10 is the worst case scenario for al1 parties in the Rest

of the World. The low value of consumers' surplus is due to the f d in both food and feed

demand for corn, while the small value of producers' surplus is a result of the lower

world price.

Table 5.6: Regional Pnce Variations for Scenario 9

Scenario

5.2.5 Scenario I I : Labeling Scenario

This is a crop segregation scenario. It is assumed that each region segregates

GMOs fiom non-GMOs. Food demand in each of the regions is satisfied £tom local non-

GMO supplies. Feed demand is satisfied with products that are GMO and this part of

corn production gets traded. The cost of segregation is assumed to be 15 percent of the

corn price. Producers in ail three regions are assumed to receive $5 per tonne as an

incentive (price premium) to produce non-GMOs. There are separate prices for GMOs

and non-GMOs. Producers' surplus now consists of two separate components - surplus

arising due to sales of GMO and non-GMO corn- The food part of consumers' s q l u s is

fi-om consurnption of non-GMO corn, while the feed part represents consumption of

GMO corn in each of the regions.

The world price of GMO or non-segïegated corn is $106.34, and the price of non-

GMO or segregated corn is $127.08. What is particularly interesthg about scenario 1 1 is

that it gives the third Iargest value of total welfare in al1 three regions. Given that the

scenarios that give the two best values of total welfare differ across the regions, scenario

9 (WH 'Wanci")

WH price

*Numbers in brackets represent the change fiom base (pre-GMO scenario)

104.90 (-4.16)*

EU price RO W price

195.66 (-2.28)

f 04-90 (-4.16)

1 1 couid represent a compromise as the best possible outcome for al1 regions at once.

This scenario also gives the third and second best values of producers' surplus in the

Western Hemisphere and Rest of the World, respectively. For consumers in Europe it

gives the second best resdt.

Table 5.7: Regional Blend Price Variations for Scenario 11

Scenario

TabIe 5.8: Regional non-GMO Price Variations for Scenario 11

(segregation)

WH price

* Numbers in brackets represent the change fkom base @re-GMO scenario) (-2.85)*

Scenario

EU pBce

11 (segregation)

RO W price

(-1 -55)

WH price

(-2.8 5)

* Numbers in brackets represent the change f?om base (pre-GMO scenario)

127.08 (16.10)*

EU price RO W price

229.33 (1 4.54)

127.08 (16.10)

Table 5.9: Welfare Results in Western Hemisphere (billion dollars)

Scenatio Consumers' Consumers' Consumers' Producers'

Surplus Surplus Surplus Surplus Welfa re (food) 1 (feed) 1 (total) t 38.660 1 24.131 1 62.792 8.308 71 .O99 1

Table 5.10: Percentage Changes Compared to pre-GMO Scenario (Scenario 1) in WH

Welfare 1 1 (food) 1 (feed)

2 1 0.57 1 2.29

Scenario Consumers'

Surplus (total) 1 1.23 1 -3.02

Producers' Surplus

Consumers' Surplus

0.73

Consumers' Surplus

Table 5.11: Welfare Results in European Union (billion dollars)

Table 5.12: Percentage Change Compared to pre-GMO Scenario (Scenario 1) in EU

Scenario Consurners'

Surplus (total) 12.328

Scenario

1 2 1 8.259 14.171 f 12.431

Consumers' Surplus (food)

Produœrs' SurpIus

4.339

Consumers' Surplus (feed)

1 8.234

Consumers' Surplus

Revenue 1 -36.98 1 0.87 1 1 (food) 1 (feed) 1 (total) 1

4.471 4.095

2 1 0-31

0.148 1 17.050

Tariff Revenue 0.235

Welfare

16.902

Consurners' Surplus

1.88 1 0.83

Tariff

3.05

Consurners' Surplus Welfare

Producers' Surplus

Table 5.13: Welfare Results in Rest of the WorId (billion dollars)

Table 5.14: Percentage Changes Compared to pre-GMO Scenario (Scenario 1) in ROW

1 Scenano Surplus Surplus Welfare i (food) 1 (feed) 1 2 I 1.14 3.44 I 2.00 I -9.76 I 0.55

Scenarïo

1 2

Consumerç' Surplus (food) 25.900 26.195

Consumerç' Surplus (feed) 15.333

Consumers' Surplus (total)

15.861 142,056 1 5.236 47.292

Producers' Surplus Welfare

41.232 1 5.803 47.035

CHAPTER 6: SUMMARY AND CONCLUSIONS

6.1 INTRODUCTION

Based on the results of the simulations, this chapter provides a srimmary of the best

and least desirable outcornes in each of the regions. From these, recommendations to

Canadian fanriers and policy rnakers are made. Finally, some limitations of the mode1 are

highiighted dong with some recomrnendations for M e r research.

6.2 SUMMARY OF RESULTS BY REGIONS

The following three subsections summarize the results of this study for the Western

Hemisphere, European Union and Rest of the World , respectively.

6.2.1 Western Hemisphere

In the Western hemisphere producers' surplus is greatest when WH producers are

early adopters of Bt technology and consumers in al1 three regions do not object to the

products of biotechnology (scenario 3). Given that it can be argued that this scenario does

not describe the present situation, several other results are provided.

The second best resült for producers in the WH is the pre-GMO situatioa

(scenario 1). The third best result is scenario I 1, or the labeling scenario, which assumes

that non-GMO corn is segregated fiom GMO hybrids in al1 three regions.

The largest value of total weifare in the Western Hemisphere is achieved when

technology is given away (scenario 4). Therefore, if biotechnology had been developed

by public institutions (Universities) this would be the best solution for al1 parties in the

WH. Since this is not the case, it is worthwhile to present two other results that give high

values for total welfare. The second best overall outcome is scenario 3 (WH first adopter

of technoiogy) and the third best overall outcome is the Iabeling scenario (1 1).

Consumers in the WH are best off when this region is isolated fiom the two other

regions and the price of corn drops substantially (scenario 10). This scenario is, however,

the worst result fiom the WH producers' point of view.

The worst result in ~verail is achieved when the WH faces a European ban on

corn trade and, at the same time, under consumers ' pressure demand for food corn

decreases in both WH and ROW (scenario 8). An overview of the best and worst results

for the WH region is given in Table 6.1.

Table 6.1: Best and Worst Scenarios (welfare results compared) in WEI

WESTERN HEMISPHERE

SCENARiO WTH HIGHEST VALUE SCENARIO WITH LOWEST VALUE

CONSUMER SURPLUS (FOOD) CONSUMER SURPLUS (FEED) CONSUMER SURPLUS (FO + FE) PRODUCER SUWLUS

TOTAL WELFARE

1 O (WH "isIand")

1 O (WH "island")

1 O (WH "island")

3 (Only WH GMO)

8 (EU ban + backlash in WH and ROW)

3 (only WH GMO)

8 (EU ban + backlash in WH and RO W)

1 O (WH "island")

4 (technology for free)

8 (EU ban + backlash in WH and ROW)

6-2.2 European Union

From the EU producers point of view the most advantageous situation is a ban on

corn irnports (scenarios 7 and 8). Total w e k e and consumers' surplus, however, are

largest when Bt technology is provided at no cost (scenario 4). The second best result for

total welfare is scenario 2 (everybody pays for and adopts biotechnology and there is no

consumer backlash against GMOs). Scena.rio 2 together with the Iabehg scenario (1 1)

give the second best results for EU consurners.

The worst scenario for EU producers is the situation in which the WH produces

Bt corn, the EU does not, but demand for corn fdls in the EU market because of the

presence of transgenic imports in this market (scenario 9). Consumers tum away fiom ai1

corn since there is no labeling to indicate that some corn is GMO-fiee- Total welfare and

consumers' surplus in Europe are smailest when b o t . food and feed demand in this

region decrease by 20 percent (scenarïo 6). Table 6.2 summarizes the best and worst

scenarios for European producers, consurners, and overall welfare.

Table 6.2: Best and Worst Scenarios (welfare results compared) in EU

EUROPEAN W O N

I 1 SCENARIO WITH HIGHEST VALUE 1 SCENANO WITH LOWEST VALUE

1 CONSUMER SURPLUS (FOOD) CONSUMER SURPLUS (FEED) CONSUMER SURPLUS (FO + FE) PRODUCER

6.2.3 Rest of the World

The best scenario fiom the ROW producers' point of view and total welfare is

scenario 10, in which the Americas are isolated from trade as the only region that grows

GMOs- Under this set of assumptions the ROW exports corn to the EU.

Consumers surpIus in the region is largest when there is no technology fee to pay

for Bt corn (scenario 4). The absolutely worst scenario for the Rest of the World is

scenario 9, in which demand for both food and feed in the region f d s by 10 percent.

Table 6.3 summarizes the best and worst scenarios for ROW producers, consumers, and

overall welfare.

SURPLUS

TOTAL WELFARE

4 (technology for free)

4 (technology for free)

4 (technology for fkee)

5 (EU-backlash- 1)

6 (EU-backlash-2)

6 (EU-backlash-2)

798 (EU ban)

4 (technology for free)

9 (WH produces GMOs, EU and ROW

backlash)

6 (EU-backlash-2)

Table 6.3: Best and Worst Scenarios (welfare results compared) in ROW

REST OF WORLD

SCENARiO WITH HiGHEST VALUE SCENAEUO WiTH LOWEST VALUE

CONSUMER SURPLUS FOOD)

CONSUMER SURPLUS (FEED)

CONSUMER SURPLUS (FO + FE)

PRODUCER SURPLUS

TOTAL

6.3 LIMITATIONS AND SUGGESTIONS FOR FURTHER RESEARCH

This study has some limitations both in tenns of scope and methods. Thus there are a

nurnber of opportunities for further research. In the first place, the mode1 is very

aggregated, with the worid represented by only three regions. While these three regions

capture the essence of the regional distrib~tion of corn production and trade, a less

aggregated mode1 would provide more detds particdarly about the Rest of the World.

Another problem arises fkom the fact that the choice of parameters, particularly in the

third region (Rest of the World), is problematic due to the lack of available information.

4 (technology for nee)

8 (EU ban + backlash in WH and ROW)

4 (technology for fiee)

1 O (WH "island")

backIash)

WELFARE

9 (WH produces GMOs, EU and ROW

backlash)

9 (WH produces GMOs, EU and ROW

backlash)

9 (WH produces GMOs, EU and ROW

backlash)

9 (WH produces GMOs, EU and ROW

1 O (WH "island")

9 (WH produces GMOs, EU and ROW

bac klash)

One example is that the corn budget for the ROW is based solely on a Thai corn budget.

No doubt costs Vary across this diverse region-

Other limitations of the model corne fiom the "partial equilibrium" nature of the

model. The model does not take into account possible reactions in other sectors of the

economy, especially in the livestock sector.

The study recognizes the fact that there is a probability distribution on the infestation

level (and hence corn yield increases) caused by the European Corn Borer. However, the

specification takes into account only the average yield increases due to the use of Bt corn.

A specification that responded to diffèrent levels of ECB infestation would provide more

precise results-

Some of the problems with the data corne form the fact that transgenics - including

Bt corn - have been around for only about five years and there is no tirne series on the

yield increase due to the use of Bt corn. With better data on the yield effects of Bt

technology and a better indication of consumer response to the new technology, more

accurate welfare andysis would be possible.

6.4 CONCLUSIONS AND RECOMMENDATIONS

In this section, the main conclusions of this study are presented. Given the

diffkulty in selecting parameters for the model, the direction of change and the order of

magnitude of the welfare effects should be given more weight than the actual numerical

values-

The introduction of Bt corn has the potential to increase welfae in al1 three

regions. However, these gains are achieved under different conditions in each region.

Several conclusions seern obvious.

First, the European Union - a sirong opponent of biotechnology - represents a

small market for corn that cannot substantially lower the world price even d e r its

demand for food and feed fa11 by 20 percent. However, the EU is a stronghold of the

consumer movement against transgenics and the perceived risk of consurning transgenic

products. If Europe succeeds in "exporting" consumer concenis into the Rest of the

World the implications are h d for the Western Hemisphere. At worst, the WH

region could h d itself isolated fiom trade with the two other regions. In this case the loss

of producers surplus in the Americas due to the low price caused by the loss of exports is

substantial. Knowing that in the Western Hemisphere producer organizations are very

influential, this possibility could have serious impIications for the agricultural policies of

the main corn producing countries in the region. The rest of the world - which is a huge

market - has the potential to increase its welfare by satiseing its local and the European

demand for non-GMOs.

Second, another interesting resdt is the fact that the "technology for fiee"

(scenario 4) and segregation (scenario I l ) scenarïos are highly ranked in al1 three regions.

Since the "technology for fiee" scenario is not a realistic option, at least for Bt corn,

segregation and labeling (which is the third best scenario in al1 regions) might be a

logical compromise. From the WH producer point of view, segregation is a much better

outcome than the loss of most of its sales on the world market. This scenario, however,

cornes at cost to consumers (15 percent of the corn pnce) that is higher than under any of

the other assumptions.

Given very different interests and the high stakes in the dispute over acceptance

of biotechnology, it is unlikely that this problem will be solved quickly and easily-

However, based on the results of this study, it is possible to make certain

recommendations to faxmers and policy makers.

Given the results of this research, the following recommendations to Cmadian

fanners can be made.

Fust, Canadian farmers are facing markets that increasingly close their borders to

the products of biotechnology, including Bt corn. In order to prevent a situation in which

they cannot sel1 their products overseas, it is important that f m e r s know before seeding

(and before making decisions on whether to grow GMO or traditional corn) who will be

buying their corn. It is also important to be aware of the buyer's policies on the handling

of Bt corn.

- Second, given that segregation and labeling might be a way to overcome the

problems reIated to corn exports, f m e r s should be ready - if needed - to separate GMO

fiom non-GMO corn at dl stages of corn production. By presenring the identity of their

crop, farmers might be able tü capture both the perceived benefits of GM hybrids and the

pice premium that might be offered for non-GMO corn.

Next, recommendations to Canadian policy makers and creators of biotech products

are presented,

There are several possible approaches

non-acceptance of biotechnology products.

that can be taken to deal with the problem of

These include:

Ifwe accept that GMOs are safe (andlor that it is going to be proven in the

next ten years) we still need to find a way to gradually introduce biotech

products into markets that may not understand them.

Even if consumers in certain areas decide not to consume GMOs in the long

run, Canadian f m e r s need to be in a position to satis@ their demand for non-

GMOs.

If consumers in North Amerka (who, according to some surveys, accept

GMOs in two-thirds to three-quarters of cases) become concerned with this

issue, we have to be able to respond.

Therefore, it is essential to ensure that Bt corn can be separated fiom its

traditional cornterpart so that CO-mingling of products does not jeopardize exports into

regions that do not accept GMOs. The process of identity preservation shoulci be

adequately regulated. A set of procedures or a protocol that enswes the same standards

are employed fiom fm-to-fmn and fiom elevator-to-eievator are needed in order to

assure acceptable levels of "purity" of non-GMO shipments. This would give a head start

to Canadian farmers in the battle for non-GMO markets.

One of the problems with the products of biotechnology is that consumers do not

see any benefits tiom the GMOs that have only agronornic (input) traits. The way to

popularize transgenics is through the introduction of products with quality (output) traits.

Education of consumers, together with a sensible marketing campaign could help in this

process. For the EU market, however, it would seem that only a break-through innovation

based on biotechnology (like a product that contains cancer-fighting agents) might

significantly improve the acceptance of products of biotechnology. If the EU'S

persistence in maintahhg a ban on hormone treated beef is any indication, they will most

likely ignore any WTO rulings on the GMO issue as well.

A major contribution of this study is that it quantifies the effects of introduction of

Bt corn to the world corn market. By analyzhg credible consumer responses to the Bt

technology the study is able to make usefiil recommendations for Ontario corn producers

and Canadian policy makers. Drawing on the fiamework of Moschini et al., this research

was able to look at Bt corn specificaily. This is the f is t Canadian study that looks at the

trade-related effects of GMO technology on corn. Therefore, the study makes both

ernpirical and policy contributions.

REFERENCES

AgNet (Agriculture Network), 2000a. Electronic newsletter, July 1 (archived at: http://cvww.fmdmail.com/listsaver/a~.

AgNet (Agriculture Network), 2000b. Electronic newsletter, July 1 5 (archived at: http://~~~,frndmail.com/listsaver/amet- 10.

AgNet (Agriculture Network), 2000c. Electronic newsletter, August 23 (archived at:

AgNet (Agriculture Network), 2000d. Electronic newsletter, July 28 (archived at: h~://~~~,findmaiI.com/Iistsaverlaoinet- 10.

Alston, J.M., G. W. Edwards and J.W. Freebaim- 1988. "Market Distortions and Benefits fiom Research". Arnerican journal of Agricultural Economcis 70(2):28 1-28 8.

Alston, J.M., G. W. Norton and P.G. Pardey. 1 995. Science Under Scarciîy - Principles and Pracrices for Agricultural Research Evaluation and Priority Serting. Ithaca: Corne11 University Press.

Agra Europe. 1999. No. 1855: 1-4.

Bessin, R. 1998. "Bt Corn". University of Kentucky Department of Entomology Entfacts. http://cvww.ukv.edu~A~ricultureEntomolo~~/entfacts/flcropslefll8.htrn. Issued May 1996, revised April 1998. As of 1 1/12/2000 at 3 : 1 Opm.

Boadway, R. W. and N. Bruce. 1984. Welfare Economics. New York: Basil Blackwell lnc.

Bode, W.M. and D.D. Calvin. 1990. "Yield-Loss Relationships and Economic Injury Levels for European Corn Bcrer Populations (Lepidoptera: Pyralidae) Infesting Pennsylvania Field Corn". Jozirnal of Economic Entornology 83 : 2 595-1 603.

Brandenburg, F. 1 999. S ecretary Manager of Ontario Soybean Growers' Marketing Board. Personal interview.

Buckwell, A. et al. 1 999. "Economics of Identity Preservarion for Genetically Modified Cropsy'. Final report of a study for Food Biotechnology Communications Initiative.

Bureau, J.C., S. Marette and A. Schiavina. 1998. 'Won-Tarif% Trade Barriers and Consurners' Information: The Case of the EU-US Trade Dispute over Beef". European Review of Agricultural Economics 25.43 7-462,

Choi, J.S. and P.G. Helmberger. 1993. "How Sensitive are Crop Yields to pnce Changes and Farm Programs?" Journal of AgrimZtural and Applied Economics 25(1):237-244.

Debertin, D.L. 1986- AgricuZtural Production Economics. New York: Macmillan Publishing Company-

Environics International. 1999. International Food Safety Survey - Highlights Report.

EUROSTAT. Agricdture Statistical Yearbook 1997. Selling Prices of Corn Products. Pp 158.

FAOSTAT. Database of the United Nations Food and Agriculture Organization. http://cwv.apps.fao-ord AS of 1 1/13/2000 2:30prn,

Gaisford, R.S . and J.D. Richardson. 1996. "North - South Disputes over the Protection of Intellectual Property". Canadian Journal of Economics. V.29, no.0. Special Issue, Part 2S376-38 1.

Gianesi, L.P. and J.E. Carpenter. 1999. "Agricultural Biotechnology: Insect Conbol Benefits". National Center for Food and Agricultural Policy. http://www.bio.ordfood&ag/bioins0 1 .html. As of 1 1/12/2000 355pm.

The Globe and Mail. Sep. 18, 1999. Pp:AlS.

Houck, J.P. 1992. Elements of Agricultural Trade Policies. Prospect Weights: Waveland Press Inc..

Houck, J.P. and P.W- Gallagher. 1976. "The Price Responsiveness of U.S. Corn Yields". Arnericun Journal of AgricziZtural Economics 58(4) part I:73 1 -734.

Houck, J.P. and M.E. Ryan. 1972- "Supply Andysis for Corn in the United States: Impact of Changing Goverment Programs". American Journal of AgricuZturai Economics 54(2): 184- 19 1.

Hyde J., M.A. Martin, P.V. Preckel and C.R. Edwards. 1999. "The Economics of Bt Corn: Vaiuing Protection fiom the European Corn Borer". Review ofAgricuZrziral Economics 2 1 (2):4?2-454.

lnside US Trade. 1 998. US Raises Two Main Complaints Against EU GMO Labeli~zg Rule. V.16, no.38:26-19.

Inside US Trade. 1999. EU Moves to Curb GMO Approvals as US Hints at Possible WTO Action. V.17, no.26:l.

Inside US Trade. 2000. Japan Developing Testing Requirements for GMfoads as of ApriZ 2001. V.18, no.20: 13.

Isaac, G. and P. Phillips. 1999. "The BioSafety Protocol and International Trade in Transgenic Canola: An Economic Assessrnent of the Impact on Canada". Paper presented to the NE- 1 65 Conference: Transitions in Agbiotech: Econornics of Strategy und Policy. Washington, D.C. June 24-25-

,Tames,C. 1999. "Global Status of Commercialized Transgenic Crops: 1999"- ISAAA Briefs No. 12: Preview. ISAAA: Ithaca, New York.

James, C. and A. Krattiger- 1999. Internationai Food policy Research institute (IFPRI). ccBiotecnology for Developing-Country Agriculture: Problems and Opportunnties. The Role of the Private Sector". Focus 2. Brïef 4 of 10.

Klein, K.K., W.A. Kerr and J.E. Hobbs. 1998. 'The Impact of Biotechnology on Agriculturai Markets". Canadian Journal of AgricuZturaZ Econornics. V.46, mo .4:44 1 - 453.

Krattîger, A-F. 1997. "lnsect Resistance in Crops: A Case Study of Bacillus Thuringiensis (Bt) and its Transfer to Developing Countries". ISAAA Briefs No. 2. ISAAA: Ithaca, New York

Mason, C.E., M.E. Rice, D.D. Calvin, LW. Van Duyn, W.B. Showers, W.D. Hutchison, J.F. Witkowski, R.A. Higgins, D.W. Onstad and G.P. Dively. 1996. Europeam Corn Borer: Ecoloay and Management. N C R - 327. North Central Regional Extension Publication. Iowa State University.

Melchinger, A.E-, R. Kreps, R. Spath, D. Klein and B. Schulz. 1998. "Evaluartion of Early-Maturing Ewopean Maize Inbreds for Resistance to the European Corm Borer". Euphytica 99: 1 15-125.

Menz, K.M. and P. Pardey. 1983. ccTechnology and US. Corn Yields: Plateaias and Price Responsiveness". American Journal of Agricultural Economics 65(3) 5 5 8-562-

Moschini, G. and H, Lapan. 1997. "Inteilectual Property Rights and the Welfare Effects of Agricultural R& D". Arnerican Journal of AgriculturaZ Economics 79: 1 229- 1242.

Moschini, G., H. Lapan and A. Sobolewsky. 1999. "Trading Technology as well as Final Products: Roundup Ready 0 Soybeans and Welfare Effects in the Soybean Camplex". The paper prepared for the ICABR conference The Shape of the Coming Agricultural Biotechnology Transformation: Strategigrc Invesîment and Policy Approaches f iom an Economic Prospective. University of Rome Tor Vergata, June 17-1 9.

Mussa, M. and S. Rosen. 1978. "Monopoly and Product Quality". Journal of Jconomic Theory 18:301-317.

Nelson et al. 1999. The Econornics and Politics of Genetically Modified OrganrSms in Agriculture: Implications for K/TO 2000. Bulletin 809. Universiv of Illinois Board of Trustees. Urbana-Champaign, Illinois.

Nicholson, W. 1992. Microeconornic Theory - Basic Principles and Exrensions. Orlando: The Dryden Press.

Nielsen, C. and K, Anderson. 2000. GMOs, Tmde Policy, and Welfare in Rich and Poor Countries. Centre for International Economic Studies discussion paper.

OECD. 1997. Historieal Statistics: 1960-1995- 1997 Edition. Pp.23. OECD Statistics Directorate.

Ontario Corn Producer ,200Oa: January. Newsletter, pp 24.

Ontario Corn Producer, 2000b: February. Newsletter, pp 26.

Ostlie, KR., W.D. Hutchison and R.L. Hellmich, 1997. Bt Corn and European Corn Borer: Long-Term Success 77irough Resistance Management. NC-205. North Central Regional Publication- Universiw of Minnesota Extension Service. http://t~~v~e~ensionnumn.edu/Documents/DC7055.html. (Not available on the net anymore).

Rice, M. and CD. Pilcher. 1998. "Potential Benefits and Limitations of Transgenic Bt Corn for Management of the European Corn Borer7'. American Entornologist. Summer'95.

Reed, M.R. and S.K. Riggins. 198 1. "A Disaggregated Analysis of Corn Acreage Response in Kentucky? American Journal ofAgriculfural Econornics 63(4):708-711.

Robinson, C. 1998. "Understanding the Commercial and Regdatory Issues for Genetically Modified and Novel Food Ingredients". Trends in Food Science and Technology 9:83-86.

Ryan, M.E. and ME. Abel. 1972. "Corn Acreage Response and the Set-Aside Prograin". Agricultural Econornics Research 24(4) : 1 02- 1 1 2.

Strategis. Database of Industry Canada. h~://www.strate~is.ic.~c.ca. As of 1 1/13/2000 1 1 :22pm.

The Toronto Star. Aug. 22, 1999.

Thompson, R. L. 198 1. A S w e y of Recent US. Developrnents in International Agricultural Trade Models. USDA-ERS publication: Bibliographies and Literature of Agriculhxe. No. 2 1.

USDA. 1996. Agricultural OutZook. A023 0, ERS, June, pp3 6.

USDA. 1997. Agricultural Outlook A0245, ERS, October, pp5.

USDA. 1999. Agricultural Outlook A0259, ERS, March, pp 18-23.

Whittaker, J.K. and R.L. Bancroft. 1979. "Corn Acreage Response-Function Estimation with Pooled Time-Series and Cross-Sectional Data". Arnerican Journal of Agricultural Economics 61(3):55 1-553.

Willig, RD. 1976. ccConsumers' Surplus Without Apology". The Arnerican Economic Review 66(4):589-597.

World Trade Organization. 1 995. The Sanitary and Phytosanitary Agreement.

Appendix A: OMAFRA Corn Budget - Grain Corn 99

Table Al : Grain Corn f 999

OPERATING EXPENSES Seed (iraditional)

Sarnple Costs ($CA/acre) 47

21 13 74

33 13

12.5 3

23 3 1 21

14 13 20

368.5

Fertilizer: -70 kgha MAP -80kgha Muriate of potash -500 kg/ha of 28-0-0 U.A.N Herbicide: -annual grass control -broadIeaf weed control Insecticide (if needed) Seed Treatment Tractor and Machine expenses: Fuel(3 51) Repairs and Maintenance Crop Insurance Custom Work (Apply Nitrogen) (Chem-Apl., if needed) Interest on operating Total operating expenses:

- Sample Costs ($US/ha) 77

13 8

45

20 8

7.5 2

14 19 13

8.5 8 12

225

Appendix B: EU Selling Price of Corn

Table BI: Corn Prices in Individual EU Countries

Country

EU 15 France I ~ Y

Production (Metnc tomes)

3036821 1

Spain Germany

I

Bela-Lux 471 12 0.15 1 1

12739600 8454200

Greece Austria Portugal

Sources: Production: FAOSTAT database Prices: EUROSTAT Agriculture Statisticai Yearbook

S hare (percent)

1 O0

2590400 23 94565

Nominal exchange rate for 1 995 (Average of daily rates):

Pnce (ecuA00 kg)

4 1.95 27.84

Source: OECD Econornic Outlook

1 3 -49 17.99

8.53 7.88

16.25 14-37 15.1 1

1838799 1473662 766493

16-99 14.88

6.05 4.85 2.52

Appendix C: Detailed Simulation Results

Table Cl: Endogenous Variables in Western Hemisphere

TabIe CS: Percentage Change (compared to base)

DwhfoI (mmQ 70.645 70.856 70.768 70.9 12 70.846 70,874 70.856 63.887 70.939 7 1 -467 69,507

Scenar. I Dwhfo 1

Dwhfel (mmt)

176.386 178.394 177.615 179.06 1 178.394 178.676 178.502 179.453

frwhl ($1

147.69 144.71 150.61 145.65 144.71 142.58 143.89 136.68

179.325 1 84.604 178.394

137.66 97.67 144.71

Table C3: Welfare Results in Western Hemisphere

1 Scenar. 1 CS(fo)WH 1 CS(fe)WH 1 CS(fo+fe) 1 PSWH 1 WELFARE

Table C4: Percentage Change (compared to base)

1 ($ billion) 3 8,660

Scenar.

2

($ billion) 24.131

CS(fo) WH

0.57

CS (fe) WH

2.29

($ billion) 62.792

CS (fo+fe)

1.23

($ billion) 8.308

P S W

-3 -02

($ billion) 7 1,099

WELFARE

0.73

Table C5: Endogenous Variables in European Union

1 Scenar. 1 Deufol 1 Deufel 1 Preul 1 Prodeul 1 Seul ( Nteul 1 Peul 1

Table C6: Percentage Change (compared to base)

1 Scenar. Deufoi Deufel Preul ProdeuI Seul Nteul Peul

Table C7: Welfare Results in European Union

Table CS: Percentage Change (compared to base)

Sc-

1 2 3

4 5 6 7 8 9 10 11

CS (fo)EU ($ billion)

8.234 8.259 8 -249

8 -268 5.290 5 -293 8.095 8.095 6.703 8.153 8.259

CS (fe)EU ($ billion)

4.095 4,171 4.142

4.197 4.171 2.69 1 3 -689 3 -689 3.418 3.858 4.171

Sc.

CS(fo+fe) ($ billion)

12.328 12.43 1 12.391

12.465 9.46 1 7-984 1 1.784 1 1.784 10,121 12.01 1

CS(fo)EU CS(fe)EU

PSWH ($ billion)

4.3 3 9 4.47 1 4.256

4.46 1 4.203 4.184 5.1 03 5.103 4.141 4.776

CS(fo+fe) PSEU

12.43 1 1 4.452

TARIFFR. ($billion)

0.235 O, 148 0.262

0.156 O, 148

O O O

0.038 0.097

TARIFF R.

WELFARE ($ billion)

16.902 17.050 16.908

17.082 13.812 12.168 16.887 16.887 14.299 16.883

0.160

WELFARE

17.043

Table C9: Endogenous Variables in Rest of the World

Table CIO: Percentage Change (compared to base)

Scenar-

1 2 3 4

Drfe 1 (mm0 168.1 12 170.982 169.868 171.936

Drfo 1 (mm9 94.654 95.193 94.984 95.372

Scenar.

3 - 3 4 5 6 7

Prrl ($1

78.15 72.98 72.43 73.69

Drfo 1

0.57 0.3 5 0.76 0.57 0.65 0.60

Prodrl (mmt)

222.602

Drfe 1

1.71 1 .O4 2.27 1.71 1.95 1.80

Sr1 (mm

262.259

Prr 1

-6.62 -7.3 1 -5.70 -6.62 -8.33 -7.27

Ntr 1 ( m a

-48.034 220.552 214.3 11 221.635

Prodr 1

-0.92 -3.72 -0.43 -0.92 -1.84 - 1.27

Pr1 ($1

109.45 -53.493 -58.410 -53.543

260.209 253.968 261.292

106.34 107.55 105.31

Sr1

-0.78 -3.16 -0.37 -0.78 -1.56 -1 .O8

Ntrl

1 1.37 21.60 1 1.47 1 1.37 16.60 13.36

Pr1

-2.85 -1 -74 -3 -79 -2.85 -3 -24 -3 .O0

Table C11: Welfare Results in Rest of the World

TabIe C12: Percentage Change (compared to base)

Scenar.

1 2

CS (fe)R ($ billion)

15.333 15.861

CS(fo)R ($ billion)

25.900 26.195

Scenario

CS (fot fe) ($ billion)

41.232 42.056

CS(fo)R CS (fe)R

PSR ($ billion)

5.803 5.236

CS(fo+fe)

WELFAFE ($ billion)

47.035 47.292

PSR WELFARE

APPENDIX ID: Results of Scenarios 5a, 6a and 9a

Description of Scenarios

Scenarios 5a and 6a differ fiom scenarios 5 and 6 ody in one number. Scenario

5a assumes the decrease in EU food demand is 10 percent (instead of 20 percent in

Scenario 5) and scenario 6a assumes a 10 percent decrease in food and feed demand in

the EU (was 20 percent in scenario 6) .

Scenario 9a differs fkom scenario 9 only in one thing: in scenario 9a the ROW

food demand decreases lopercent while in scenario 9 both food and feed decrease for

The results of scenarios 5a and 6a are al1 in the same direction as scenarios 5 and

6 but the magnitude of change is somewhat smaller because the decrease in demand for

food (and feed) corn is smaller. Ln scenario Sa the world price is 7 cents higher than in

scenario 5. The fall in the pnce in scenario Sa is actually 2.77 percent and in scenario 5 it

is 2.84 percent compared to the base. This illustrates how small the European corn

market is, because even a huge fall in its food demand (fiom 1G to 20 percent) decreases

the world price by only 0.06 percent. Producers' surplus in the WH decreases 2.66

percent in scenario 5a compared to 3.02 percent in scenario 5. The difference in the

percentage change in total welfare in the WH is even srndler: it is only 0.02 percent

larger in scenario 5a. The values for the rest of the world show similar almost negligible

differences. The only region that shows a bigger dif5erence is the EU. In Europe the

difference in price and producers' surplus is also very small - but the total welfare value

is substantidly smaller in scenario 5 due to the fa11 in the consumers' surplus.

The cornparison of scenarios 6 and 6a confimis what was shown in scenarios 5

and 5a. Even 20 percent fd l in food and feed demand (scenario 6) decreases the world

price by a M e r 0.26 percent compared to the IO percent decrease in demand for food

and feed (scenario 6a): the value of the world price under scenario 6 is 3 -24 percent

smaller than under the base, while world price under scenario 6a decreases 2.98 percent

compared to the base. The o d y significant difference is again in the EU because of the

si,anificant decrease in consuners' surplus.

The changes fiom scenario 9a to 9 do have an influence on the world price. Its

value decreases 2.80 percent in scenario 9a and 4.16 percent in scenario 9 when

compared to the base.

Table Dl: Comparison of Welfare Results in Western Hemisphere ($ billion US)

Table D2: Percentage Change to Scenario 1 in WH

Scenario Consumers'

Surplus (food)

1 1 Scenario

Consumers' Surplus (feed)

Constimers' Surplus (food)

Consumers' Surplus (feed)

Consumers' Surplus (total)

Consumers' Surplus (total)

Producers' 1 Surplus welfare 1

Producers' Surplus Welfare

Table D3: Overview of Three Additional Scenarios

HOW TRADE IS AFFECTED SCENALUO

sa

6a

YELD MCREASE (DUE TO USE OF BT

CORN) WH: 3.53percent EU: O ROW: 253percent

9a

CONSUMER DEMAND DECREASE

WH: 3.~3percent EU: O

WH: O EU: LOpercent of food demand

WH: 3.53percent EU: O ROW: O

Free Trade

ROW: 2.53percent , feed d.

ROW: WH: O EU: LOpercent of f w d and Free Trade

ROW: O WH: O EU: Iûpercent of food and feed d R0W:lOpercent of food d.

Free Trade