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Economic model of transgenic crop adoption

Economic model of transgenic crop adoption. Ian McFarlane, Julian Park, Graziano Ceddia. Background:. Previous research in this area The AMIGA* Project University of Reading’s involvement Economic model.

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Economic model of transgenic crop adoption

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  1. Economic model of transgenic crop adoption Ian McFarlane, Julian Park, GrazianoCeddia

  2. Background: Previous research in this area The AMIGA* Project University of Reading’s involvement Economic model *Assessing and Monitoring Impacts of Genetically modified plants on Agro-ecosystems

  3. Model features: • Dynamic 5-year simulation • EU divided into 5 Regions • Crops selected from menu of crops for given Region • Potential Yield of crop recalculated each month as a function of: • Weed Pressure • Pest Pressure Risk (stochastic) • Field Management • (future option: Climate Change effects)

  4. Regions:

  5. Regions: [These regions are defined in the AMIGA work program]

  6. EU Regions: • For the AMIGA work packages, four regions were selected based on the Natura 2000* approach (Boreal, Atlantic, Continental, Mediterranean) • The fifth region (Balkans), includes two countries that belong to four Natura different zones. *Natura 2000 is an EU wide network of nature protection areas established under the 1992 Habitats Directive.

  7. Crops by Region: ‘000 ha year: 2008 [Eurostat]

  8. Model data: • Crop hectares (by Member State) from Eurostat • Regional features (e.g. incidence of pests) • Economic variables (includes GM seed price policies) • Farm management costs • Data input via set of spreadsheets • Calculations performed in VBA (Visual Basic for Excel App) • Data output into new sheets in new workbooks

  9. Rotations In proportion to hectares cultivated by region in 2009 [Eurostat]

  10. Model schematic

  11. Model details: Weed Pressure Function of : • previous cultivar on this plot • Herbicide application(s)

  12. Model details: Pest Pressure Function of: • Previous application(s) of pesticide • Random occurrence of pest pressure • Current pest management policy

  13. Model details: Field Management Function of: • Tillage policy • Fertiliser application(s) • Previous cultivar

  14. Economic Model Loop in one month steps for each: year > region > plot > crop

  15. Model interface:VBA User Form for initialisation

  16. Economic variables • Seed cost • Crop value • Pest control cost(s) • Weed control cost(s) • Fertiliser cost • Labour cost • Coexistence cost

  17. Result format:

  18. Key Challenges Yield data for GM crops in the EU Estimating weed and pest pressures Price estimates for GM products in the EU Assumptions about typical rotations Crop (event) availability in the future [Include findings from sister groups in the project]

  19. References: Brookes G. (2012) European arable crop profit marginsGBC Ltd Eurostat: Crops products [apro_cpp_crop] http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=apro_cpp_crop Farm Accountancy Data Network (FADN) http://circa.europa.eu/Public/irc/agri/rica/ library?l=/micro-economic_analyses/standard_results John Nix Farm Management Pocketbook (42ndedn) http://www.thepocketbook.biz/ ------------------ Gomez-Barbero M., et al (2008) Adoption and performance of the first GM crop introduced in EU agriculture: Bt maize in Spain. JRC-IPTS Report 22778 Park J., et al (2011) The impact of the EU regulatory constraint of transgenic crops on farm income. New Biotechnology, 28(4), 396-406

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