Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-08T09:24:42.732Z Has data issue: false hasContentIssue false
  • English
  • Français

Revisiting the Impact of Bt Corn Adoption by U.S. Farmers

Published online by Cambridge University Press:  15 September 2016

Jorge Fernandez-Cornejo  and
Seth Wechsler
Jorge Fernandez-Cornejo
Affiliation:
Economic Research Service, U.S. Department of Agriculture, in Washington, D.C.
Seth Wechsler
Affiliation:
Department of Agricultural and Resource Economics at the University of Maryland in College Park, Maryland
Get access

Abstract

This study examines the impact of adopting Bt corn on farm profits, yields, and insecticide use. The study employs an econometric model that corrects for self-selection and simultaneity. The model is estimated using nationwide farm-level survey data for 2005. Regression analysis confirms that Bt adoption is associated with increased variable profits, yields, and seed demand. However, the results of this analysis suggest that Bt adoption is not significantly related to insecticide use. This result may be due to the fact that insect infestation levels were lower in 2005 than they were in previous years.

Keywords

genetically engineered cominsect resistanceBt corninsecticide usetechnology adoptionyields
Type
Contributed Papers
Information
Agricultural and Resource Economics Review , Volume 41 , Issue 3 , December 2012 , pp. 377 - 390
Copyright
Copyright © 2012 Northeastern Agricultural and Resource Economics Association 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Baute, T.S., Sears, M.K., and Schaafsma, A.W. 2002. “Use of Transgenic Bacillus thuringiensis Berliner Corn Hybrids to Determine the Direct Economic Impact of the European Com Borer (Lepidoptera: Crambidae) on Field Corn in Eastern Canada.” Journal of Economic Entomology 95(1): 57–64.Google Scholar
Cappellari, L., and Jenkins, S. 2003. “Multivariate Probit Regression Using Simulated Maximum Likelihood.” Stata Journal 3(3): 278–294.Google Scholar
Diewert, W.E. 1974. “Applications of Duality Theory.” In Intriligator, M. and Kendrick, D., eds., Frontiers of Quantitative Economics (Vol. II). Amsterdam: North-Holland.Google Scholar
Diewert, W.E., and Ostensoe, L. 1988. “Flexible Functional Forms and Global Curvature Conditions.” In Barnett, W., Berndt, E., and White, H., eds., Dynamic Econometric Modeling. Boston: Cambridge University Press.Google Scholar
Dillehay, B.L., Roth, G.W., Calvin, D.D., Karatochvil, R.J., Kuldau, G.A., and Hyde, J.A. 2004. “Performance of Bt Corn Hybrids, Their Near Isolines, and Leading Corn Hybrids in Pennsylvania and Maryland.” Agronomy Journal 96(204): 818–824.Google Scholar
Duffy, M. 1999. “Does Planting GMO Seed Boost Farmers’ Profits?” Leopold Letter 11, Iowa State-Leopold Center for Sustainable Agriculture, Ames, Iowa. Available at http://www.leopold.iastate.edu/news/leopold-letter/1999/fall/does-planting-gmo-seed-boost-farmers-profits (accessed May 18, 2012).Google Scholar
Duffy, M. 2001. “Who Benefits from Biotechnology?” Paper presented at the 2001 American Seed Trade Association meeting, Chicago, IL. Available at http://www2.econ.iastate.edu/faculty/duffy/Pages/biotechpaper.pdf (accessed May 18, 2012).Google Scholar
Fang, M., Motavalli, P.P., Kremer, R.J., and Nelson, K.A. 2007. “Assessing Changes in Soil Microbial Communities and Carbon Mineralization in Bt and non-Bt Corn Residue-Amended Soils.” Applied Soil Ecology 37(1): 150–160.Google Scholar
Feder, G., Just, R., and Zilberman, D. 1985. “Adoption of Agricultural Innovations in Developing Countries: A Survey.” Economic Development and Cultural Change 33(2): 255–298.Google Scholar
Fernandez-Cornejo, J. 1996. “The Microeconomic Impact of IPM Adoption: Theory and Adoption.” Agricultural and Resource Economics Review 25(2): 149–160.Google Scholar
Fernandez-Cornejo, J., Hendricks, C., and Mishra, A. 2005. “Technology Adoption and Off-Farm Household Income: The Case of Herbicide-Tolerant Soybeans.” Journal of Agricultural and Applied Economics 37(2): 549–563.Google Scholar
Fernandez-Cornejo, J., Klotz-Ingram, C., and Jans, S. 2002. “Farm-Level Effects of Adopting Herbicide-Tolerant Soybeans in the U.S.A.” Journal of Agricultural and Applied Economics 34(1): 149–163.Google Scholar
Fernandez-Cornejo, J., and Li, J. 2005. “The Impacts of Adopting Genetically Engineered Crops in the USA.” Paper presented at the American Agricultural Economics Association meetings, July 24-27.Google Scholar
Fernandez-Cornejo, J., and McBride, W. 2002. “Adoption of Bioengineered Crops.” Agricultural Economic Report No. 810, Economic Research Service, U.S. Department of Agriculture, Washington, D.C.Google Scholar
Gates, R. 2006. “A Mata Geweke-Hajivassiliou-Keane Multivariate Normal Simulator.” Stata Journal 6(2): 190–213.CrossRefGoogle Scholar
Geweke, J. 1989. “Bayesian Inference in Econometric Models Using Monte Carlo Integration.” Econometrica 57(6): 1317–1339.CrossRefGoogle Scholar
Greene, W. 1997. Econometric Analysis (3rd edition). Upper Saddle River, NJ: Prentice-Hall.Google Scholar
Hajivassiliou, V., and McFadden, D. 1998. “The Method of Simulated Scores for the Estimation of LDV Models.” Econometrica 66(4): 863–896.Google Scholar
Heckman, J. 1979. “Sample Selection Bias as a Specification Error.” Econometrica 47(1): 153–161.Google Scholar
Hutchinson, W.D., Burkness, E.C., Hellmich, R.L., Kaster, L.V., Hunt, T.E., Wright, R.J., Pecinovsky, K., Rabaey, T.L., Flood, B.R., Raun, E.S., Mitchell, P.D., Moon, R.D., Leslie, T.W., Fleischer, S.J., Abrahamson, M., Hamilton, K.L., Steffey, K.L., and Gray, M.E. 2010. “Areawide Suppression of European Corn Borer with BT Maize Reaps Savings to Non-Bt Maize Growers.” Science 330(6001): 222–225.Google Scholar
Hyde, J., Martin, M., Preckel, P., and Edwards, R. 1999. “The Economics of Bt Com: Valuing Protection from the European Corn Borer.” Review of Agricultural Economics 21(2): 442–454.Google Scholar
Keane, M.P. 1992. “A Note on Identification in the Multinomial Probit Model.” Journal of Business and Economics Statistics 10(2): 193–200.Google Scholar
Keane, M.P. 1994. “A Computationally Practical Simulation Estimator for Panel Data.” Econometrica 62(1): 95–116.Google Scholar
Kott, P.S. 1998. “Using the Delete-a-Group Jackknife Variance Estimator in NASS Surveys.” Research Report No. RD-98-01, National Agricultural Statistics Service, U.S. Department of Agriculture, Washington, D.C.Google Scholar
Kramer, M. 2005. “R2 Statistics for Mixed Models.” In Boyer, J.E. Jr., ed., Proceedings of the 17th Annual Kansas State University Conference on Applied Statistics in Agriculture. Manhattan, KS: Kansas State University Press.Google Scholar
Maddala, G.S. 1983. Limited Dependent and Qualitative Variables in Econometrics. Cambridge, UK: Cambridge University Press.Google Scholar
Magee, L. 1990. “R2 Measures Based on Wald and Likelihood Ratio Joint Significance Tests.” American Statistician 44(3): 250–253.Google Scholar
Matuschke, I., and Qaim, M. 2009. “The Impact of Social Networks on Hybrid Seed Adoption in India.” Agricultural Economics 40(5): 493–505.Google Scholar
McBride, W., and El-Osta, H. 2003. “Impacts of the Adoption of Genetically Engineered Crops on Farm Financial Performance.” Journal of Agricultural and Applied Economics 34(1): 175–191.Google Scholar
Mitchell, P., Hurley, T., and Rice, M. 2004. “Is Bt Corn Really a Drag? Bt Corn Yield Drag and Yield Variance.” Faculty Paper Series No. FP 04-01, Department of Agricultural Economics, Texas A&M University, College Station, Texas.Google Scholar
Mungai, N.W., Motavalli, P.P., Nelson, K.A., and Kremer, R.J. 2005. “Differences in Yields, Residue Composition and N Mineralization Dynamics of Bt and non-Bt Maize.” Nutrient Cycling in Agroecosystems 73(1): 101–109.Google Scholar
National Research Council (NRC). 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, D.C.: The National Academies Press.Google Scholar
Pilcher, C.D., and Rice, M.E. 1998. “Management of European Corn Borer (Lepidoptera: Crambidae) and Corn Root-worms (Coleoptera: Chrysomelidae) with Transgenic Com: A Survey of Farmer Perceptions.” American Entomologist 44(1): 36–44.Google Scholar
Pilcher, C.D., Rice, M.E., Higgins, R.A., Steffey, K.L., Hellmich, R.L., Witowski, J., Calvin, D., Ostlie, K.R., and Gray, M. 2002. “Biotechnology and the European Corn Borer: Measuring Historical Farmer Perceptions and Adoption of Transgenic Bt Corn as a Pest Management Strategy.” Journal of Economic Entomology 95(5): 878–892.Google Scholar
Roodman, D. 2009. “Estimating Fully Observed Recursive Mixed-Process Models with cmp.” Working Paper No. 168, Center for Global Development, Washington, D.C.Google Scholar
U.S. Department of Agriculture. 2002. “Agricultural Chemical Usage 2002 Field Crops Summary.” National Agricultural Statistics Service, U.S. Department of Agriculture, Washington, D.C. Google Scholar
U.S. Department of Agriculture. 2006. “Agricultural Chemical Usage 2006 Field Crops Summary.” National Agricultural Statistics Service, U.S. Department of Agriculture, Washington, D.C. Google Scholar
Wilson, T., Rice, M., Tollefson, J., and Pilcher, C. 2005. “Transgenic Corn for Control of the European Corn Borer and Corn Rootworms: A Survey of Midwestern Farmers’ Practices and Perceptions.” Journal of Economic Entomology 98(2): 237–247.Google Scholar