Centre for Agricultural and Food Economics , K.U. Leuven

Centre for Agricultural and Food Economics, K.U.LeuvenCentre for Agricultural and Food Economics, K.U.Leuven

GMO’s in Food: Economic Impact on Various Stakeholders in the EU and in

the WorldThis presentation can be downloaded at

http://www.biw.kuleuven.be/aee/clo/euwab.htmEmail: [email protected]

Koen DillenErik MathijsEric Tollens

Course ‘Social and Ethical Aspects of Biotechnology’, VUB, Brussels, 29 November 2007.

IntroductionIntroduction GM experience gap EU vs. ROW EU has chosen the option to wait through the

1998 moratorium and current coexistence regulation process, postponing release

This option has a value and a cost, i.e. potential welfare effects forgone

The trade-off of both needs to be assessed – in order to know the ex post implications of

our decision in the past, i.e. 1998– in order to know the ex ante implications of

future decisions to be taken

IntroductionIntroduction

Global Case StudiesGlobal Case Studies

EU Case StudiesEU Case Studies

MethodologyMethodology

DataData

ResultsResults

DiscussionDiscussion

IntroductionIntroductionSystemic Approach is Needed:Systemic Approach is Needed:





DataData

ResultsResults


GOVERNMENTGOVERNMENT

FARMERSFARMERS

MARKETING SYSTEMMARKETING SYSTEM

CONSUMERSCONSUMERS

Research Expenditures Regulatory ApprovalIPR Legislation

Labelling Policy Trade Regulation

ENVIRONMENTENVIRONMENT

ACTIVISTS, LOBBY GROUPS, MEDIA


INPUT SUPPLIERSINPUT SUPPLIERSbiotechnology seeds,

pesticides, ...technology fee, contract

GMO crops or GMO fed livestock productscontract

marketing GM products

environmental benefits and risks

Downstream

Upstream

IntroductionIntroduction Most of the recent agbiotech innovations

have been developed by private sector (upstream), mostly because of very stringent regulations and as such high costs for legislation

Therefore, the central focus of societal interest is not on the ROR of R&D, but on distribution of benefits among stakeholders in the technology diffusion chain

But what are the « benefits » and « costs » arising from GM crops?





DataData

ResultsResults


IntroductionIntroduction4 Quadrants of Research in B/C Analyses:4 Quadrants of Research in B/C Analyses:

Scope

Reversibility

Private

Social

Reversible

Quadrant 1

Private Reversible Benefits (PRB) Private Reversible Costs (PRC)

Net Private Reversible Benefits (W): W = PRB-PRC

EUWABSIM (Demont and Tollens, 2003)

Quadrant 2

Social Reversible Benefits (SRB)

Social Reversible Costs (SRC)

Irreversible

Quadrant 3

Private Irreversible Benefits (PIB)

Private Irreversible Costs (PIC)

Quadrant 4

Social Irreversible Benefits (R)

Social Irreversible Costs (I)

• gene flow, outcrossing and weediness

• development of resistance (insects, weeds)

• decline biodiversity (less varieties)

• impacts on non-target species (lepidopteran, birds,

wildlife, …)

• health benefits (Bt

crops)• fixed cost

engendered by e.g. identity preservation

system on the farm

• ethical cons, perception of

non-sustainable and non

environment-friendly

agriculture• decline

of environme

ntal externalities due to

less pesticide

use

• ethical pros, perception of

sustainable and environment-friendly

agriculture• less damage on honey bees due to less pesticide use

• increase biodiversity in field (herbicide tolerant

beet)

• yield increase• pest control cost decline

• labour savings• non-pecuniary benefits like management savings

and ease of use• market effects like price

declines and consumer surplus

• technology fee• other variable costs associated

with the introduction of

GM crops (irrigation)

• market effects like price declines


EUWAB-project (European Union Welfare effects of Agricultural Biotechnology)

Pre-coexistence (although some work on coexistence as well)

What have we learned so far from ex post and ex ante agbiotech impact assessments in the EU?





DataData

ResultsResults







DataData

ResultsResults


Table 1: Global welfare distribution of the first generation of transgenic crops Country Crop Year Adoption Welfare Welfare distribution

(%) (m$) Domestic farmers

Innovators Domestic consumers

Net ROW

USA Bt cotton 1996 14% 134 43% 47% 6% 4% USA Bt cotton 1996 14% 240 59% 26% 9% 6% USA Bt cotton 1997 20% 190 43% 44% 7% 6% USA Bt cotton 1998 27% 213 46% 43% 7% 4% USAa Bt cotton 1996-98 20% 151 22% 46% 14% 18% USAb Bt cotton 1997 20% 213 29% 35% 14% 22% USAc Bt cotton 1997 20% 301 39% 25% 17% 19% USA HT cotton 1997 11% 232 4% 6% 57% 33% USAd HT soyb. 1997 17% 1,062 76% 10% 4% 9% USAe HT soyb. 1997 17% 437 29% 25% 17% 28% USA HT soyb. 1999 56% 804 19% 45% 10% 26% USA HT soyb. 1997 17% 308 20% 68% 5% 6% Canadaf HT canola 2000 54% 209 19% 67% 14% . Argentina HT soyb. 2001 90% 1,230 25% 34% 0.3% 41% Argentina Bt cotton 2001 5% 0.4 21% 79% . . China Bt cotton 1999 11% 95 83% 17% 0%g . India Bt cotton 2002 7% 6.2 67% 33% 0%g . Mexico Bt cotton 1998 15% 2.8 84% 16% . . South Africah Bt cotton 2000 75% 0.1 58% 42% . . South Africai Bt cotton 2001 80% 1.2 67% 33% 0%g 0%

Global Case StudiesGlobal Case Studies Farmers capture sizeable gains Size and distribution of welfare effects of the

first generation of GE crops are function of:1. Adoption rate2. Crop3. Biotech trait4. Geographical region5. Year6. National policies and IPR protection7. Assumptions and underlying dataset

On average, domestic farmers and consumers extract 2/3 of the benefits while 1/3 is captured by the seed industry





DataData

ResultsResults


Table 1: Global welfare distribution of the first generation of transgenic crops Country Crop Year Adoption Welfare Welfare distribution

(%) (m$) Domestic farmers

Innovators Domestic consumers

Net ROW

USA Bt cotton 1996 14% 134 43% 47% 6% 4% USA Bt cotton 1996 14% 240 59% 26% 9% 6% USA Bt cotton 1997 20% 190 43% 44% 7% 6% USA Bt cotton 1998 27% 213 46% 43% 7% 4% USAa Bt cotton 1996-98 20% 151 22% 46% 14% 18% USAb Bt cotton 1997 20% 213 29% 35% 14% 22% USAc Bt cotton 1997 20% 301 39% 25% 17% 19% USA HT cotton 1997 11% 232 4% 6% 57% 33% USAd HT soyb. 1997 17% 1,062 76% 10% 4% 9% USAe HT soyb. 1997 17% 437 29% 25% 17% 28% USA HT soyb. 1999 56% 804 19% 45% 10% 26% USA HT soyb. 1997 17% 308 20% 68% 5% 6% Canadaf HT canola 2000 54% 209 19% 67% 14% . Argentina HT soyb. 2001 90% 1,230 25% 34% 0.3% 41% Argentina Bt cotton 2001 5% 0.4 21% 79% . . China Bt cotton 1999 11% 95 83% 17% 0%g . India Bt cotton 2002 7% 6.2 67% 33% 0%g . Mexico Bt cotton 1998 15% 2.8 84% 16% . . South Africah Bt cotton 2000 75% 0.1 58% 42% . . South Africai Bt cotton 2001 80% 1.2 67% 33% 0%g 0%

UpstreamAverage

= 37%

Global Case StudiesGlobal Case Studies Hence, benefit sharing seems to

follow a general rule of thumb:1/3 upstream vs. 2/3 downstream (Demont, Dillen et al.) IntroductionIntroduction




DataData

ResultsResults


GOVERNMENTGOVERNMENT

FARMERSFARMERS

MARKETING SYSTEMMARKETING SYSTEM

CONSUMERSCONSUMERS

Research Expenditures Regulatory ApprovalIPR Legislation

Labelling Policy Trade Regulation

ENVIRONMENTENVIRONMENT



INPUT SUPPLIERSINPUT SUPPLIERSbiotechnology seeds,

pesticides, ...technology fee, contract

GMO crops or GMO fed livestock productscontract

marketing GM products

environmental benefits and risks

Downstream

Upstream

Global Case StudiesGlobal Case Studies This 2:1 rule of thumb seems to be

valid for both industrial and developing countries

Typical for large exporting countries: international trade of both the innovation (multinationals) and the commodity international spillover effects possibility of immiserising growth (Bhagwati, 1958)





DataData

ResultsResults


EU Case StudiesEU Case Studies De facto moratorium on GM crops: October 1998

– May 2004 (Syngenta Bt 11 maize) 1998-2002: Adoption stagnated at 25,000 ha Bt

maize in Spain, doubled afterwards 2007: 6 Bt maize growing EU Member States:

Spain, Portugal, France, Czech Republic, Germany, Slovakia (but still only MON810)

De facto moratorium and the postponement nowadays implies a cost to society = deadweight cost or benefits foregone of GM crops

But we need a representative EU case study to show this!





DataData

ResultsResults


GM crops in EUGM crops in EUHectares 2005 2006 2007Spain 53,225 53,667 75,148

France 492 5000 21,174

Czech Republic

150 1,290 5,000

Portugal 750 1,250 4,500

Germany 400 950 2,685

Slovakia 30 900

Romania 110,000 90,000 350

Poland 100 320

TOTAL 62,187 110,077





DataData

ResultsResults


EU Case StudiesEU Case StudiesPreferable conditions of a good EU case study:1. Crop representative for EU agriculture 2. Crop problem representative for EU agriculture3. Important EU export commodity (spillover)4. Acceptance of GM variety realistic5. GM variety near commercialization6. Some impact data available, e.g. field trials

Sugar beet fullfills most criteriaAnd we have ex post impact evidence from Spain





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ResultsResults







DataData

ResultsResults


Table 1: Accordance of selected EU case studies on the impact of GE crops with criteria Crop

Criterion HT sugar beet Bt maize

1. Representativeness of the crop +++ grown in all EU regions

+ grain maize more important in southerly

regions 2. Representativeness of the pest +++

weed control is crucial to profitability

+ corn borers more important in southerly

regions 3. Representativeness of trade +++

EU provides 20% of global trade

– EU-15 and EU-25 are net importers of

maize, only internal EU trade 4. Availability of genetic resources +++

presence of wild relatives, e.g. sea beet

– no wild relatives in Europe,

primary centre of origin is Mexico 5. Realistic acceptance –

main impediments are manufacturers

+++ widely accepted in Spain, entirely used for animal feed, no labelling required

6. Realistic commercialisation ++ registrations are

pending

+++ already commercialised in Spain, France, Germany, Portugal and the Czech Republic

7. Availability of impact data + research capacity has declined since 2001

+ very little data publicly available






DataData

ResultsResults

DiscussionDiscussion 0

10

20

30

40

50

60

70

80

90

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

Maize Sugar beet

Figure 1: Evolution of the number of field trials of maize and sugar beet in the EU-25 Source: SNIF database (European Commission, 2006a)

EU Case StudiesEU Case Studies1. Bt maize resistant against European corn borer

(ECB) [Ostrinia nubilalis (Hübner)] and Mediterranean corn borer (MCB) [Sesamia nonagrioides (Lefebvre)] in Spain (Demont and Tollens, 2004b)

2. Herbicide tolerant (HT) sugar beet in the former EU-25 (Dillen,Demont and Tollens, 2007)

3. Bt maize resistant against ECB in Hungary /Czech Republic(Demont et al., 2007)

4. Bt maize resistant against Western corn rootworm (WCR) [Diabrotica virgifera virgifera LeConte] in Hungary/Czech

5. Herbicide tolerant maize in Hungary/Czech6. Herbicide tolerant sugar beet in Hungary/Czech7. Herbicide tolerant oilseed rape in

Hungary/czech





DataData

ResultsResults


BtBt Maize in Spain Maize in Spain





DataData

ResultsResults



2 corn borers important losses in Spanish maize production: 9% on average

Syngenta 2 Bt maize varieties: Compa CB & Jordi CB

Today: only MON810 varieties Government 20.000 ha limit

= 5,2% adoption (in this period) Analyze 1998-2003





DataData

ResultsResults



1. Farm level analysis: - standard damage abatement function- damage = stochastic (lognormal)- calibrated on real corn borer damage data

2. Aggregation to national level- Alston, Norton & Pardey (1995) (ANP)- small, open economy- Oehmke & Crawford (2002) & Qaim (2003) (OCQ)





DataData

ResultsResults



HT Sugar BeetsHT Sugar Beets

BtBt Maize Maize

EnvironmentEnvironment

ConclusionConclusion


Table 1: Economic impact of Bt maize on Spanish agriculture and the seed industry, 1998-2003 Year

1998

1999

2000

2001

2002

2003 Average

1998-2003 Aggregated value 2004

Adoption (%) 4.8% 7.6% 4.6% 5.0% 5.4% 6.8% 5.7% 5.7% Bt maize adopters (€/ha) 50.5 50.6 47.9 46.8 45.1 45.7 47.8 415.5 Agriculture (m€) 1.1 1.5 1.0 1.2 1.1 1.5 1.2 10.5 Seed industry (m€) 0.5 0.7 0.5 0.6 0.6 0.8 0.6 5.2 Total impact (m€) 1.6 2.2 1.4 1.8 1.7 2.2 1.8 15.8 Agriculture share (%) 67.9% 67.9% 66.7% 66.2% 65.3% 65.6% 66.6% 66.8% Seed industry share (%) 32.1% 32.1% 33.3% 33.8% 34.7% 34.4% 33.4% 33.2%

Herbicide Tolerant Sugar BeetsHerbicide Tolerant Sugar Beets Effective weed control = crucial Yield losses up to 100% due to weed

competition Glyphosate and Glufosinate-ammonium

= broad-spectrum post-emergence herbicides, low toxicity

Introduction of genes from soil bacteria in beet genome Roundup Ready ™ (Monsanto)

Broad-spectrum weed control Less applications Less volume active ingredient More flexibility in timing





DataData

ResultsResults


Herbicide Tolerant Sugar BeetsHerbicide Tolerant Sugar Beets1. Farm level analysis:

- assume standard HT replacement programs - compare costs with observed programs-model the heterogeneity among farmers-some farmers rationaly decide to adopt, others not choose not to-calculate the optimal technology fee





DataData

ResultsResults


f(hc)

hc)( cgg nnah gw

g

maxmin

Herbicide Tolerant Sugar BeetsHerbicide Tolerant Sugar Beets

Uniform monopolistic price setting

Part of monopolistic rent accrues to farmers

Third degree price discrimination preferable->Bt-maize, Bt cotton


Global Case Global Case StudiesStudies

EU Case EU Case StudiesStudies


DataData

ResultsResults


Herbicide Tolerant Sugar Herbicide Tolerant Sugar BeetsBeets Data: ex ante

- No adoption of the new technology- No farm level impact data, only field trials- Assumptions: 1. Yield impact

2. Form of the density curve- Sources: expert opinions, literature, economic theory, national surveys, Eurostat- Stochastic simulation (monte carlo)





DataData

ResultsResults


Year Benchmark 1996/97 1997/98 1998/99 1999/00 2000/01 2001/02 2002/03 2003/04 2004/05 1996/97

Price effects World sugar price (%) 100% 99.65% 99.59% 99.35% 99.09% 98.92% 98.73% 98.65% 98.49% 98.58% A sugar price (%) 100% 99.99% 99.99% 99.99% 99.99% 99.97% 99.98% 99.97% 99.98% 99.99% B sugar price (%) 100% 99.77% 99.77% 99.73% 99.70% 99.17% 99.48% 99.16% 99.26% 99.56% Welfare effects

Belgium 0.00 2.46 3.61 4.13 5.70 6.72 8.67 8.67 9.02 15.21 Denmark 0.00 1.90 3.23 4.59 6.28 7.75 9.56 9.91 11.04 12.61 Germany 0.00 12.70 18.53 24.46 31.12 39.79 48.13 48.17 49.08 44.21 Greece 0.00 1.82 3.17 3.44 5.47 7.84 8.87 9.51 8.33 5.38 Spain 0.00 9.10 15.47 22.04 30.27 38.07 44.49 44.88 50.76 45.90 France 0.00 5.10 7.40 9.71 11.74 11.50 19.09 15.78 16.84 44.74 Ireland 0.00 1.32 2.09 3.20 4.45 5.08 5.98 6.45 7.13 0.21 Italy 0.00 5.67 9.21 13.64 18.61 22.74 27.09 28.66 34.37 21.91 The Netherlands 0.00 3.71 6.60 10.50 13.88 15.83 20.00 20.27 22.47 34.09 Austria 0.00 1.42 2.09 2.74 3.39 3.93 5.34 5.24 5.15 8.22 Portugal 0.00 0.03 0.83 1.17 1.75 1.90 2.54 2.36 2.96 3.00 Finland 0.00 1.02 1.48 2.57 3.24 4.11 4.83 5.13 5.78 4.94 Sweden 0.00 0.64 1.09 1.58 2.32 2.93 3.45 3.97 4.19 4.88 United Kingdom 0.00 2.62 3.97 4.93 6.03 6.50 9.51 8.56 8.98 13.25 Czech Republic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 15.44 Hungary 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 9.12 Poland 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 58.17 EU-15 producers 0.00 49.51 78.77 108.69 144.25 174.68 217.53 217.54 236.09 341.29 EU-15 consumers 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ROW cane 0.00 -116.46 -115.22 -148.77 -164.49 -238.67 -289.76 -300.04 -296.12 -310.02 ROW beet 0.00 39.56 67.42 89.95 115.36 154.36 161.54 187.03 181.99 175.09 Net ROW producers 0.00 -76.90 -47.80 -58.83 -49.12 -84.31 -128.22 -113.00 -114.14 -134.93 ROW consumers 0.00 148.80 147.01 184.16 202.99 295.45 341.47 335.27 349.94 373.88 Net ROW 0.00 71.90 99.21 125.33 153.86 211.14 213.25 222.27 235.80 238.95 Input suppliers 0.00 75.33 113.68 169.04 233.93 277.06 307.68 352.17 363.58 359.78

Total 0.00 196.75 291.66 403.06 532.05 662.89 738.46 791.98 835.48 940.02

Year 2006/07 2007/08 2008/09 2009/10 2010/11 2011/2012 2012/2013 2013/2014 2014/2015 AGGR Land supply response Price effects

World sugar price (%)

98.33% 98.36% 98.40% 98.40% 98.40% 98.40% 98.40% 98.40% 98.40%

Welfare effects

Belgium 16.50 14.30 14.92 15.26 15.29 15.37 15.50 15.58 15.70 222.73 0.18% Denmark 10.87 8.75 8.32 7.97 7.97 7.96 7.95 7.93 7.92 177.93 -3.11% Germany 45.45 43.54 45.56 46.63 46.76 47.04 47.47 47.73 48.15 887.94 0.20% Greece 5.12 2.35 2.21 2.10 2.11 2.11 2.11 2.11 2.11 115.02 -2.77% Spain 27.00 22.18 21.18 20.35 20.33 20.30 20.26 20.23 20.19 691.01 -3.26% France 56.81 43.62 46.29 47.78 48.02 48.45 49.09 49.51 50.14 603.32 0.29% Ireland 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 63.75 -1.99% Italy 10.83 9.69 9.17 8.75 8.74 8.73 8.72 8.70 8.69 389.45 -2.23% The Netherlands

22.57 18.07 17.14 16.37 16.36 16.35 16.34 16.32 16.30 389.05 -3.17%

Austria 9.40 7.84 8.15 8.31 8.33 8.36 8.42 8.45 8.51 127.25 0.63% Portugal 1.60 0.85 0.81 0.78 0.78 0.78 0.78 0.78 0.77 36.01 -3.64% Finland 4.78 2.68 2.56 2.46 2.45 2.44 2.43 2.42 2.40 78.91 -3.58% Sweden 5.35 4.46 4.23 4.05 4.04 4.04 4.03 4.03 4.02 74.06 -1.99% United Kingdom

14.59 12.10 12.79 13.17 13.22 13.33 13.49 13.60 13.75 209.75 0.30%

Czech Republic

10.68 7.09 6.71 6.40 6.39 6.39 6.38 6.37 6.37 80.30 -4.29%

Hungary 5.90 3.79 3.62 3.48 3.48 3.47 3.46 3.45 3.44 45.07 -2.19% Poland 40.36 32.45 30.84 29.51 29.47 29.41 29.35 29.29 29.23 331.44 -4.06% EU-15 producers

287.81 233.76 234.52 233.37 233.74 234.53 235.78 236.49 237.70 4523.00 -1.20%

EU-15 consumers

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 .

ROW cane -520.77 -478.29 -508.50 -537.68 -548.45 -561.27 -576.74 -589.95 -606.16 -7222.11 -0.37% ROW beet 199.78 190.78 197.62 199.85 198.69 199.95 201.69 202.84 204.53 3460.72 -2.75% Net ROW producers

-320.99 -287.51 -310.88 -337.83 -349.76 -361.32 -375.04 -387.11 -401.63 -3761.38 -0.70%

ROW consumers

601.25 569.38 597.32 629.07 644.44 661.78 682.95 701.22 723.31 8609.72 .

Net ROW 280.26 281.87 286.44 291.24 294.67 300.46 307.91 314.11 321.68 4848.33 . Input suppliers

321.29 306.54 302.39 298.31 294.13 293.57 292.94 292.28 291.61 6068.94 .

Total 889.36 822.17 823.34 822.93 822.55 828.55 836.63 842.88 850.99 15440.27 -0.73%

Welfare distribution

EU-15 producers (%) . 25% 27% 27% 27% 26% 30% 28% 28% 36% EU-15 consumers (%) . 0% 0% 0% 0% 0% 0% 0% 0% 0% Net ROW (%) . 36% 34% 31% 29% 32% 29% 28% 28% 25% Input suppliers (%) . 38% 39% 42% 44% 42% 42% 45% 44% 38%

Total (%) . 100% 100% 100% 100% 100% 100% 100% 100% 100%

Welfare distribution

EU-15 producers (%)

32% 29% 29% 28% 29% 28% 28% 28% 28% 29%

EU-15 consumers (%)

0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

Net ROW (%) 31% 34% 35% 35% 36% 36% 37% 37% 38% 31% Input suppliers (%)

36% 37% 37% 36% 36% 35% 35% 35% 34% 39%

Total (%) 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

BtBt Maize in Hungary Maize in HungaryEuropean Corn Borer (European Corn Borer (Ostrinia nubilalisOstrinia nubilalis Hübner) Hübner)





DataData

ResultsResults


BtBt Maize in Hungary Maize in HungaryWestern Corn Rootworm (Western Corn Rootworm (Diabrotica virgifera virgiferaDiabrotica virgifera virgifera

LeConte)LeConte)





DataData

ResultsResults



LeConte)LeConte)





DataData

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LeConte)LeConte)





DataData

ResultsResults



LeConte)LeConte)





DataData

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LeConte)LeConte)





DataData

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LeConte)LeConte)





DataData

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LeConte)LeConte)





DataData

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LeConte)LeConte)





DataData

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LeConte)LeConte)





DataData

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LeConte)LeConte)





DataData

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LeConte)LeConte)





DataData

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LeConte)LeConte)





DataData

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WCR in Czech RepublicWCR in Czech Republic






DataData

ResultsResults


Micro-economic level: Develop bio-economic pest damage abatement models Calibrate on real field data (surveys, expert opinions,

literature) Model heterogeneity Pre-coexistence Incorporate uncertaintyMacro-economic level: Model GM crop adoption through partial equilibrium

displacement model (EDM) Incorporate market structure and response Incorporate trade policies Incorporate uncertainty

DataData





DataData

ResultsResults


Ex ante: no adoption data available Data mining, combine different data sources:

– National and international statistics– National and regional farmer surveys– Field trials– Expert opinions– Literature– Assumptions– Economic theory

Importance of modelling data uncertainty and conducting sensitivity and scenario analyses

ResultsResults






DataData

ResultsResults


Total benefits per hectare are fairly robust measure of value or “size” of the innovation

This value is distributed among input industry and farmers (who share it with consumers)

Market power of input industry is constrained by 5 factors:1. Farmer heterogeneity (e.g. Bt maize)2. Uncertainty and irreversibility3. Competition from chemical industry4. Competition within biotechnology industry5. Coexistence regulation (EU)

Immiserising growth unlikely due to:1. Smaller scale & heterogeneous innovation pattern2. Common Agricultural Policy (CAP) protecting farmers against

eroding world prices

(a) (b)

qs-1 qs-1

d d

qmin

qr

d*

Lr

d*d1 d1

Lg

q*

qgqgqr





DataData

ResultsResults


Non-Pecuniary Benefits of HT Crops:

Management Flexibility and Convenience







DataData

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Coexistence, the last hurdle to GM crops?European Commission (2003):

“Coexistence refers to the ability of farmers to make a practical choice between conventional, organic and GM [genetically modified] crop production, in compliance with the legal obligations for labelling and/or purity standards. The adventitious presence of GMOs [genetically modified organisms] above the tolerance threshold set out in Community legislation triggers the need for a crop that was intended to be a non-GMO crop, to be labelled as containing GMOs. This could cause a loss of income, due to a lower market price of the crop or difficulties in selling it. Moreover, additional costs might incur to farmers if they have to adopt monitoring systems and measures to minimise the admixture of GM and non-GM crops. Coexistence is, therefore, concerned with the potential economic impact of the admixture of GM and non-GM crops, the identification of workable management measures to minimise admixture and the cost of these measures.”






DataData

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What is coexistence? A cost or an incentive? Ex-ante measure The right to choose (farmers & consumers) Gene flow, pollen drift, contamination, commingling Coexistence is only relevant

– if there is a significant long-term domestic or international (export) consumer demand for non-GM crops (e.g. not cotton)

– if this demand translates into market signals (e.g. price premiums for non-GM crops)

– if there is a significant farmer demand for cost-reducing transgenic crops (e.g. not ECB-resistant Bt maize in Belgium)

– Costs proportional to economic incentives






DataData

ResultsResults


adoption

co-e

xist

ence

co

sts rupture

point

Coexistence costs borne by 2 incentives:1. Farmer profits of GM crops (“GM rent”)2. Price premium of identity preserved (IP)

crops (“IP rent”)

Phase I Phase II Phase III

clustering, reallocation of land

IP rentseekingGM rents

Coexistence Coexistence measuresmeasures





DataData

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Definitions: Isolation distances = rigid minimum

distance rules between GM and non-GM crop fields of the same species and imposed on GM crop producers

Buffer zones = flexible segregation measures by using field surroundings (which serve as cross-pollination zones) with non-GM crops of the same species, planted on (negotiable between farmers):

• Donor fields (System 1)• Recipient fields (System 2)

and planted and cultivated by• Owner (System a)• Neighbor (System b)

ArcView ModellingArcView Modelling Hypothetical adoption of GMHT OSR in Beauce

Blésoise region in Central France Sample square of 100 km² = 6% area GIS dataset of sample square: 1,508 field polygons

covering 4,233 ha Constrained randomization process:

Generate 10 random allocations of GM and non-GM OSR fields in the landscapeSubject to

• OSR planting density = 26% (= 2x regional one)• GM adoption rate = 50%

Represents most stringent scenario of coexistence in a single season

ResultsResults


ArcView ModellingArcView Modelling

AssumptionsAssumptions

Economic IncentivesEconomic Incentives

ResultsResults


The domino-effect caused by rigid coexistence regulations

ResultsResults





ResultsResults



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Domino-effectDomino-effectTable 2 Domino-effect on costs (€/ha) of rigid coexistence regulations in oilseed rape cultivation in Central France Phase OSR

area (ha)

Intended GM OSR

area (ha)

Adoption of GM OSR (%

of the area)

GM-free OSR area (ha)

Coexistence costs (€/ha)

IP price premium

Isolation distance of 50 m 8% 4% 0% Phase 1 1,097 548 (6) 50% (0%) 310 (44) 0 16 (2) 32 (4) Phase 2 1,097 238 (44) 22% (4%) 47 (12) 0 6 (1) 0 Phase 3 1,097 191 (42) 17% (4%) 5.0 (5.6) 0 0.6 (0.6) 0 Phase 4 1,097 186 (38) 17% (3%) 0.4 (1.0) 0 0.1 (0.1) 0 Cumulative 1,097 186 (38) 17% (3%) 362 (38) 0 22 (3) 0 Domino-effect

-66% (7%)

-66% (3%) +17% (6%) +0%

+40% (10%) +0%

Isolation distance of 100 m Phase 1 1,097 548 (6) 50% (0%) 361 (42) 0 18 (2) 37 (4) Phase 2 1,097 187 (42) 17% (4%) 50 (20) 0 7 (2) 0 Phase 3 1,097 136 (34) 12% (3%) 8 (8) 0 1.6 (1.3) 0 Phase 4 1,097 128 (29) 12% (3%) 1 (2) 0 0.2 (0.4) 0 Cumulative 1,097 128 (29) 12% (3%) 420 (25) 0 28 (3) 0 Domino-effect

-77% (5%)

-77% (3%) +17% (9%)

+0% +50% (19%) +0%

Notes: OSR = oilseed rape. Areas and costs are averages, based on 10 random allocations of GM and non-GM OSR fields. Standard deviations are shown between brackets. The domino-effect expresses the relative difference in per cent between the cumulative value and the value in Phase 1. Source: Authors’ calculations based on GIS dataset of the sample square (Pessel et al., 2001).

Conclusion (coexistence)Conclusion (coexistence) Rigid regulations may impose severe burden on GM

crop production in Europe Even under low demand for IP crops, and hence,

low demand for coexistence Costly, not proportional to incentives and hence not

consistent with EC’s objectives Flexible measures are preferable as they are less

costly and proportional to incentives Should be negotiable between adopters and non-

adopters as both farmer segments have economic incentives to ensure coexistence in long-run

Conclusion (coexistence)Conclusion (coexistence) Trade-off between GM and IP rent depends on market

signals from consumers IP incentive only sustainable if consumers

• Have strong & sustainable preferences for non-GM• Are willing to pay significant IP price premiums

Otherwise no coexistence issue strictu sensu and cost = pure regulatory burden

EU policy makers: under absence of clear market signals for IP, we recommend to shift regulatory rigidity from ex ante ex post

To avoid jeopardizing economic incentives for coexistence of GM/non-GM in Europe


System approach needed Case by case Producers capture an important part of

the benefits of transgenic crops: most often between 2/3 and 3/4

Government’s trade policy can influence the impact of biotechnology (e.g. sugar sector)

Coexistence only relevant when 2 incentives are both present at the same time: GM rent & IP rent





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Centre for Agricultural and Food Economics , K.U. Leuven