Economic and environmental impacts of Herbicide Tolerant maize cultivation in the EU: a modelling assessment

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Economic and environmental impacts of Herbicide Tolerant maize cultivation in the EU: a modelling assessment Pascal Tillie and Emilio Rodriguez-Cerezo European Commission - Joint Research Centre Contact: pascal.tillie@ec.europa.eu www.jrc.ec.europa.eu Serving society Stimulating innovation Supporting legislation

Impact of HT maize: an ex-ante evaluation Weed control in the EU context Methodology of the study Economic model Methodology for the environmental assessment Simulation scenarios Results Discussion 2

Weed control in maize in the EU Weed control is an important determinant of maize yield Triple challenge in the EU: Declining number of authorized active ingredients (Reg 1107/2009), new directive on Endocrine Disruptors to come Greening of the CAP Development of weed resistance but no new Mode of Actions GM HT maize for the EU? NK603 received a positive risk assessment report by EFSA, but the petition for cultivation was withdrawn by the applicant High adoption throughout the world However, after a decade of adoption some users of the technology are experiencing weed resistance 3

Objective of the paper Provide an ex-ante assessment of the potential impacts of the introduction of a GMHT maize for the EU agricultural sector with both economic and environmental considerations taken into account heterogeneity of farms included and taking into account the possible changes in practices due to weed resistance development 3 scenarios with different: Weed control strategy Technology pricing strategy 4

Impact of HT maize: an ex-ante evaluation Weed control in the EU context Methodology of the study Economic model Methodology for the environmental assessment Simulation scenarios Results Discussion 5

Methodology: the economic model (1) Stochastic partial budgeting model to tackle heterogeneity and price biases Average farmer do not exist, but heterogeneity does Adoption rate ρ: where ν represents farmer s individual valuation of the technology θ represents the price of the technology and f(v) is the pdf of v in the farmers population Average profit for adopters π : where f α (v) is the pdf of v in the adopters population f () v dv ( v ) f ( v) dv a (Demont et al. 2008) Endogenous price for the technology provider: where λ is land ( ) ( c) ( c)(1 F( )) in adopt tot c is LT marginal cost (Dillen et al. 2009) 6

Methodology: the economic model (2) How to elicit f(v)? Under the assumption of profit maximizing farmers and considering only pecuniary benefits: v ( p y ) h k ( p y ) h k c c c c g g g g And with p c = p g ; y c = y g and k c = k g With h the cost of herbicide treatments; y yield k other costs c for conventional, g for GM v hc h g 7

Methodology: the environmental impact Assessment of environmental and health impacts of herbicide Quantity of Active Ingredients / unit of land Indicators Exposure-toxicity Ratio (ETR) (eg. POCER) Non-ETR indicators (eg. EIQ) The EIQ indicator Most widely used, developed at Cornell University (Kovach et al. 1992) EIQ={C[(DT*5)+(DT*P)]+[(C*((S+P)/2)*SY)+(L)]+[(F*R)+(D*((S+ P)/2)*3)+(Z*P*3)+(B*P*5)]}/3 One EIQ value for each AI Data on rate of application lead to "field-use rating EIQ": FieldEIQ EIQai. Rt ai ai 8

Methodology: the data A 2009-farm survey to maize growers Telephone-based 7 EU countries (CZ, DE, ES, FR, HU, PT, RO) CZ DE ES FR HU PT RO Number of interviews 55 100 249 101 104 54 102 Utilised agricultural area (per farm in survey) ha 1687 155 91 140 373 43 428 Std dev 1279 236 122 83 813 67 661 Utilised agricultural area a 89 45 6 23 52 13 4 (per farm in country) Area cultivated with maize per farm in 2009 ha 230 33 37 37 117 32 101 Std dev 192 27 48 36 241 65 244 Grain maize yield tonnes/ha 9,9 10,4 10,6 9,6 10,0 8,7 5,8 Std dev 4,3 2,1 2,7 2,8 4,2 4,6 3,4 9

Impact of HT maize: an ex-ante evaluation Weed control in the EU context Methodology of the study Economic model Methodology for the environmental assessment Simulation scenarios Results Discussion 10

Weed control strategies in maize cultivation Potential herbicide programs for GMHT maize in the Europe Program name Description Active ingredient Rate of application (g of AI/ha) EIQ of AI EIQ field-use rating per AI Total EIQ field-use rating of program Estimated cost of the herbicide program ( /ha) Program A Only glyphosate Two glyphosate applications Glyphosate 2160 15,33 33,11 33,11 18-22 Option 1 TBA 375 42 15,75 Program B Pre + Gly Pre-emergence residual (low rate) and glyphosate S-metachlor 625 22 13,75 Glyphosate 1080 15,33 16,56 46,06 48-52 Program C EarlyPost + Gly Tank mix of postemergence residual and glyphosate then glyphosate Mesotrione 100 18,67 1,87 Glyphosate 2160 15,33 33,11 34,98 53-57 Option 2 Program D Gly + Post Glyphosate + tank mix of glyphosate and dicamba Glyphosate 2160 15,33 33,11 Dicamba 240 26,33 6,32 39,43 43-47 Based on Dewar 2009 and expert opinions 11

The scenario for weed control 3 scenarios to account for: Change in weed management practices over time Different strategy for the monopolistic pricing decision Scenario 1: short run scenario Herbicide program for GMHT maize based on glyphosate (option 1) Uniform technology price (exogenous) Scenario 2: mid-term scenario Farmers switch to a diversified chemical weed management program (option 2) Uniform technology price (exogenous) Scenario 3: long-term scenario Diversified weed management program (option 2) Third degree price discrimination (on spatial attribute) (endogenous) 12

Impact of HT maize: an ex-ante evaluation Weed control in the EU context Methodology of the study Economic model Methodology for the environmental assessment Simulation scenarios Results and discussion Some policy recommendation 13

Results Baseline: current weed control practices of EU farmers (conventional maize) Rate of herbicide application (g of active ingredient / ha) Cost of herbicide treatment ( /ha) Field-use rating EIQ/ha Preemergence Postemergence CZ DE ES FR HU PT RO 2531 1166 3273 1331 1462 1505 1534 614 795 1074 396 511 470 792 Average 45 75 70 72 65 67 124 Std dev 25 44 57 34 51 57 71 Average 62 24 59 22 20 43 34 Std dev 43 22 30 20 29 22 21 Average use of AI: 2.15 kg / ha in PRE + 0.72kg / ha in POST Average EIQ: 37.7 EIQ / ha Average expenditure: about 70 /ha 14

Results: Scenario 1 Adoption of GMHT maize and economic impacts 15

Results: Scenario 2 Adoption of GMHT maize and economic impacts 16

Results: Scenario 3 Adoption of GMHT maize, endogenous technology fee and economic impacts 17

Results: Scenario 1 Environmental impacts 18

Results: Scenario 2 & 3 Environmental impacts 19

Results: summary Results should not be over over-interpreted The big picture is that GMHT could be profitable for many farmers in the EU, especially in the short run Two groups of countries ES, PT and CZ: most farmers would realize both economic and environmental benefits of technology, even in the longer run FR, DE and HU: only fraction of adopters would experience a decrease in EIQ The adoption of resistance management strategies is not in contradiction with economic attractiveness 20

Impact of HT maize: an ex-ante evaluation Weed control in the EU context Methodology of the study Economic model Methodology for the environmental assessment Simulation scenarios Results and discussion Some policy recommendation 21

Policy recommendations The behaviour by farmers will determine sustainability of the technology Literature shows that farmers are often short-sighted Weed resistance evolves fast=> shift towards alternative programs (less profitable and less environmental friendly) Farmers have to be guided to reduce the pressure towards resistance build up Management guidelines (rotation, mechanical control, ) Efficient extension services educating the farmers about the long term effects 22

Future research Make the decision of farmers dynamic based on the probability of weed resistance to evolve in the future following their own past practices Dynamic programming Heterogeneous risk adversity Incorporate other changes induced by the introduction of GMHT maize Flexibility and easiness of weed control 23

24

Thanks for your attention! 25