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Matty Demont Promoter: Prof. E. Tollens Jury President: Prof. G. Volckaert

Economic impact of agricultural biotechnology in the European Union: Transgenic sugar beet and maize. Dissertationes de Agricultura, No. 713, Jozef Heuts-auditorium, Landbouwinstituut, Faculteit Bio-ingenieurswetenschappen, Katholieke Universiteit Leuven, 1 September 2006, 16:00pm.

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Matty Demont Promoter: Prof. E. Tollens Jury President: Prof. G. Volckaert

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  1. Economic impact of agricultural biotechnology in the European Union: Transgenic sugar beet and maize Dissertationes de Agricultura, No. 713, Jozef Heuts-auditorium, Landbouwinstituut, Faculteit Bio-ingenieurswetenschappen, Katholieke Universiteit Leuven, 1 September 2006, 16:00pm Matty Demont Promoter: Prof. E. Tollens Jury President: Prof. G. Volckaert Jury Members: Prof. E. Mathijs Prof. J. Swinnen Prof. J. Vanderleyden Prof. J. Wesseler

  2. Introduction:AgBiotech adoption in the world Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  3. Introduction:AgBiotech adoption in the world • Most of the recent agbiotech innovations have been developed by private sector • Therefore, the central focus of societal interest is not on the ROR of R&D, but on distribution of gains among stakeholders in the technology diffusion chain Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  4. Introduction:AgBiotech adoption in the world Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  5. Introduction:AgBiotech adoption in the world Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements Upstream Downstream

  6. Introduction:AgBiotech adoption in the world • Upstream private sector is highly consolidated • Existence of market power and extraction of monopoly rents Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  7. Introduction:AgBiotech adoption in the world • Alston, Norton & Pardey (1995) (ANP) • Moschini & Lapan (1997) • Widely used in agbiotech impact literature Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  8. Introduction:AgBiotech adoption in the world • Farmers capture sizeable gains • Size and distribution of welfare effects of the first generation of GE crops are function of: 1. Adoption rate 2. Crop 3. Biotech trait 4. Geographical region 5. Year 6. National policies (Ch.1) and IPR protection 7. Assumptions and underlying dataset (Ch.4) Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  9. Upstream Average = 37%

  10. Introduction:AgBiotech adoption in the world • However, benefit sharing seems to follow a general rule of thumb: 1/3 upstream vs. 2/3 downstream • This rule of thumb seems to be valid for both industrial and developing countries Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  11. Introduction:AgBiotech adoption in the EU • 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 • 2006: 5 Bt maize growing EU Member States: Spain, Portugal, France, Czech Republic, Germany • De facto moratorium implies a cost to society = deadweight cost or benefits foregone of GM crops Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  12. Introduction:AgBiotech adoption in the EU • We need to know this cost in ex post, but also for future decisions in ex ante Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  13. Introduction:Hypotheses • The first generation of agbiotech innovations could and can significantly contribute to productivity and welfare in EU agriculture • The largest share of total welfare creation is captured downstream (farmers, processors, manufacturers, distributors and consumers) • Conventional benefit-cost analysis cannot capture uncertainty and potential irreversibility regarding environmental effects. It can be extended by a real option approach to assess maximum tolerable levels of irreversible environmental costs that justify a release of these innovations in the EU Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  14. Introduction:Hypotheses 4. Some of the variability of welfare estimates reported in literature can be explained by the modeling of supply shift in conventional equilibrium displacement models Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  15. Introduction:Case studies Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  16. Introduction:Case studies Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  17. Introduction:Case studies Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  18. Introduction:Case studies Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  19. Introduction:Herbicide tolerant (HT) sugar beet in EU-15 Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  20. Introduction:Bt [Bacillus thuringiensis] maize in Spain Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  21. Methodology:Herbicide tolerant (HT) sugar beet in EU-15 • Farm level analysis: - assume standard HT replacement programs - compare costs with observed programs - assume technology pricing (see data) Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  22. Methodology:Herbicide tolerant (HT) sugar beet in EU-15 • Aggregation to the global level through standard methodologies - Alston, Norton & Pardey (1995) (ANP) - 3 regions: EU, ROW beet, ROW cane - Dynamic world price behaviour - Moschini, Lapan & Sobolevsky (2000) (MLS) - Former EU’s CMO sugar - Technology spillovers included - Non-spatial: no intra-EU trade flows - Disaggregated supply: 16 prod. blocks - Aggregate EU demand Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  23. Methodology:Herbicide tolerant (HT) sugar beet in EU-15 • Real option approach (Wesseler & Weichert, 1999): decision to release GM crops in EU is one under flexibility, irreversibility, and uncertainty • Neo-classical decision criterion: benefits ≥ costs • Include an additional ‘safety factor’ to take into account uncertainty & irreversibility • Decision criterion: benefits > costs by a factor, the so-called ‘hurdle rate’ (estimated through historical gross margin series) • Calculate break-even points maximum tolerable costs Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  24. Methodology:Bt [Bacillus thuringiensis] maize in Spain • Farm level analysis: - standard damage abatement function - damage = stochastic (lognormal) - calibrated on real corn borer damage data • Aggregation to national level - Alston, Norton & Pardey (1995) (ANP) - small, open economy - Oehmke & Crawford (2002) & Qaim (2003) (OCQ) Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  25. Data • Ex ante (HT sugar beet in the EU-15) - No adoption of the new technology - No farm level impact data, only field trials - Assumptions: 1. Yield impact 2. Technology pricing - Sources: expert opinions, literature, economic theory, national surveys, Eurostat - Stochastic simulation • Ex post (Bt maize in Spain) - Scarce data sources - Data mining (e.g. corn borer damage) - Sources: literature, national surveys - Stochastic simulation Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  26. Results Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  27. Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  28. Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  29. Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  30. Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  31. Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  32. Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  33. Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  34. Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  35. Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  36. Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  37. Results:Herbicide tolerant (HT) sugar beet in the EU-15 Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  38. Results:Herbicide tolerant (HT) sugar beet in the EU-15 Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  39. Results:Bt [Bacillus thuringiensis] maize in Spain Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  40. Results:Bt [Bacillus thuringiensis] maize in Spain Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  41. Results:Bt [Bacillus thuringiensis] maize in Spain Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  42. Model evaluation 5 methods of supply shift calculation: • CIR = Change in Revenue • ANP = Alston, Norton & Pardey (1995) • ANP1 = ANP with supply elasticity = 1 • OCQ = Oehmke & Crawford (2002) & Qaim (2003) • MLS = Moschini, Lapan & Sobolevsky (2000) Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  43. Model evaluation Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  44. Model evaluation Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements But if  = 0  ANP = ANP1 = OCQ

  45. Model evaluation Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  46. Model evaluation • ANP method seems not robust at first sight Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  47. Model evaluation Let’s have a look at the differences between the 5 methods: Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

  48. Model evaluation • No systematic differences between the models when fed with stochastic market data, except between ANP1 and OCQ Introduction Methodology Data Results Model evaluation Conclusions Acknowledgements

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