Integrating Technology Traits and Producer Heterogeneity: A Mixed-Multinomial Model of Genetically Modified Corn Adoption |
| |
| Authors: | Pilar Useche Bradford L Barham Jeremy D Foltz |
| |
| Institution: | Pilar Useche is assistant professor in the Department of Food and Resource Economics and Center for Latin American Studies at the University of Florida. Bradford Barham is professor and Jeremy Foltz is associate professor in the Department of Agricultural and Applied Economics at the University of Wisconsin, Madison. The authors would like to thank without implicating: William Provencher, Michael Carter, Brian Gould, the journal editor, and three anonymous reviewers for valuable comments and suggestions. They also thank seminar and conference participants at UW and at the AAEA meetings for useful comments and discussion, as well as Fred Buttel, Jessica Goldberger, and the Program on Agricultural Technology Studies' Team who collected the data. Funding for this work came from the Illinois-Missouri Biotechnology Alliance (IMBA) and a USDA Hatch grant through the University of Wisconsin. |
| |
| Abstract: | This article proposes a model of technology adoption that integrates demand for individual traits of new technologies with the potential for heterogeneity based on farm and farmer characteristics. The model is applied to recent genetically modified corn adoption data from Minnesota and Wisconsin farmers, using a mixed-multinomial logit (MMNL) model to estimate the effects of traits and farm and farmer characteristics on adoption outcomes. This approach allows explicit recovery of estimates of farmers' shadow prices for individual technology traits. Results show the importance of producer and regional heterogeneity in preferences for seed traits. |
| |
| Keywords: | biotechnology genetically modified crops mixed-multinomial logit technology adoption |
|
|
