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Forecasting the Adoption of GM Oilseed Rape: Evidence from a Discrete Choice Experiment in Germany
Authors:Gunnar Breustedt  Jörg Müller‐Scheeßel  Uwe Latacz‐Lohmann
Affiliation:The authors are with the Department of Agricultural Economics, Christian‐Albrechts‐University, Kiel, Germany. Uwe Latacz‐Lohmann also holds an adjunct appointment in the School of Agricultural and Resource Economics at the University of Western Australia. E‐mail: for correspondence. Thanks are extended to Henrika Meyer‐Schatz for designing and running the choice experiment as part of her MSc. thesis. The authors are grateful to two anonymous reviewers and to the Journal's editors for helpful comments and suggestions on an earlier draft of the paper.
Abstract:This paper explores farmers’ willingness to adopt genetically modified (GM) oilseed rape prior to its commercial release and estimates the ‘demand’ for the new technology. The analysis is based upon choice experiments with 202 German arable farmers. A multinomial probit estimation reveals that GM attributes such as gross margin, expected liability from cross pollination, or flexibility in returning to conventional oilseed rape significantly affect the likelihood of adoption. Neighbouring farmers’ attitudes towards GM cropping and a number of farmer and farm characteristics were also found to be significant determinants of prospective adoption. Demand simulations suggest that adoption rates are very sensitive to the profit difference between GM and non‐GM rape varieties. A monopolistic seed price would substantially reduce demand for the new technology. A monopolistic seed supplier would reap between 45% and 80% of the GM rent, and the deadweight loss of the monopoly would range between 15% and 30% of that rent. The remaining rent for farmers may be too small to outweigh possible producer price discounts resulting from the costs of segregating GM and non‐GM oilseed rape along the supply chain.
Keywords:Adoption forecast  choice experiment  genetically modified oilseed rape  multinomial probit  technology adoption  C42  C81  Q12  Q16
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