Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-23T23:10:58.841Z Has data issue: false hasContentIssue false
  • English
  • Français

Impacts of the Adoption of Genetically Engineered Crops on Farm Financial Performance

Published online by Cambridge University Press:  28 April 2015

William D. McBride  and
Hisham S. El-Osta
William D. McBride
Affiliation:
USDA, Economic Research Service, Washington, D.C.
Hisham S. El-Osta
Affiliation:
USDA, Economic Research Service, Washington, D.C.
Get access Rights & Permissions [Opens in a new window]

Abstract

The rapid adoption of genetically engineered (GE) crops by U.S. farmers suggests that these technologies have been perceived to improve farm financial performance. This study develops and applies an econometric model to data from corn and soybean producers in order to evaluate the financial impacts of the adoption of GE crops. Results indicate that the adoption of GE crops has had a limited impact on financial performance that varies by crop, type of technology, type of farm, and region of the nation. Factors other than the financial impacts appear to be important reasons for the rapid adoption of GE crops.

Keywords

Btcornfarm financial performancegenetically engineered cropsherbicide-tolerantsoybeanstechnology adoption
Type
Original Articles
Information
Journal of Agricultural and Applied Economics , Volume 34 , Issue 1 , April 2002 , pp. 175 - 191
Copyright
Copyright © Southern Agricultural Economics Association 2002

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

Aldrich, J. and Nelson, F.D.. Linear Probability, Logit, and Probit Models. Sage University Paper Series on Quantitative Applications in the Social Sciences, 07-45. Sage Publications: Beverly Hills and London. 1984.CrossRefGoogle Scholar
Amemiya, T. “Qualitative Response Models: A Survey.” Journal of Economic Literature 19(December 1981):1483–1536.Google Scholar
Arnold, J.C., Shaw, D.R., and Medlin, C.R.. “Roundup Ready® Programs Versus Conventional Programs: Efficiacy, Varietal Performance, and Economics.” Proceedings of the Southern Weed Science Society 1998. pp. 272–73.Google Scholar
Bard, S.K. and Barry, P.J.. “Developing a Scale for Assessing Farmers Risk Attitudes.” Unpublished manuscript, Center for Farm and Rural Business Finance, University of Illinois, Urbana, IL, November 1998.Google Scholar
Burrows, T. M. “Pesticide Demand and Integrated Pest Management: A Limited Dependent Variable Analysis.” American Journal of Agricultural Economics 65(November 1983):806–10.CrossRefGoogle Scholar
Carpenter, J. and Gianessi, L.. “Herbicide-Tolerant Soybeans: Why Growers are Adopting Roundup Ready Varieties.” AgBioForum. 2(1999):65–72.Google Scholar
Couvillion, W.C., Kari, F., Hudson, D., and Allen, A.. A Preliminary Economic Assessment of Roundup Ready Soybeans in Mississippi. Mississippi State University, Research Report 2000-005, May 2000.Google Scholar
Dubman, R.W. Variance Estimation with USDA's Farm Costs and Returns Surveys and Agricultural Resource Management Study Surveys. U.S. Department of Agriculture, Economic Research Service, Staff Paper AGES 00-01, April 2000.Google Scholar
El-Osta, H.S. and Johnson, J.D.. Determinants of Financial Performance of Commercial Dairy Farms. U.S. Department of Agriculture, Economic Research Service, Technical Bulletin Number 1859, 1998.Google Scholar
Feder, G. and Umali, D.L.. “The Adoption of Agricultural Innovations: A Review.” Technological Forecasting and Social Change 43(1993): 215–239.CrossRefGoogle Scholar
Feder, G., Just, R. J., and Zilberman, D.. “Adoption of Agricultural Innovations in Developing Countries: A Survey.” Economic Development and Cultural Change 2(1985):255–98.CrossRefGoogle Scholar
Fernandez-Cornejo, J. and McBride, W.D.. Genetically Engineered Crops for Pest Management in U.S. Agriculture: Farm-Level Effects. U.S. Department of Agriculture, Economic Research Service, Agricultural Economic Report No. 786, 2000.Google Scholar
Fernandez-Cornejo, J. and Jans, S.. Pest Management in U.S. Agriculture. U.S. Department of Agriculture, Economic Research Service, Agricultural Handbook No. 717, 1999.Google Scholar
Fernandez-Cornejo, J., Klotz-Ingram, C., and Jans, S.. “Farm-Level Effects of Adopting Genetically Engineered Crops in the U.S.A.” NE-165 Conference Proceedings, Transitions in Agbio-tech: Economics of Strategy and Policy, edited by Lesser, William H., 2000, pp. 57–74.Google Scholar
Fernandez-Cornejo, J., and Klotz-Ingram, C.. “Economic, Environmental, and Policy Impacts of Using Genetically Engineered Crops for Pest Management.” Paper presented at the Northeastern Agricultural and Resource Economics Association meetings, Ithaca, NY, June 1998.Google Scholar
Fernandez-Cornejo, J. “The Microeconomic Impact of IPM Adoption: Theory and Application.” Agricultural Resources Economic Review 25(October 1996): 149–60.Google Scholar
Ferrell, J.A., Witt, W.W., and Slack, C.H.. “Integrating Glyphosate into Corn Weed Management Strategies.” Proceedings of the Southern Weed Science Society 1999. pp. 27–28.Google Scholar
Graeber, J.V., Nafziger, E.D., and Mies, D.W.. “Evaluation of Transgenic, Bt-Containing Corn Hybrids.” Journal of Production Agriculture 12(1999):659–663.CrossRefGoogle Scholar
Haden, K.L. and Johnson, L.A.. “Factors Which Contribute to Financial Performance of Selected Tennessee Dairies.” Southern Journal of Agricultural Economics 21(1989):104–112.Google Scholar
Heckman, J.J. “Sample Selection Bias as a Specification Error.” Econometrica 47(1979): 153–61.CrossRefGoogle Scholar
Heckman, J.J. “The Common Structure of Statistical Models of Truncation, Sample Selection, and Limited Dependent Variables and a Simple Estimator for Such Models.” Annals of Economic and Social Measurement 5(1976):475–91.Google Scholar
Hyde, J., Martin, M.A., Preckel, P.V., Edwards, C.R., and Dobbins, C.L.. “Estimating the Value of Bt Corn: A Multi-State Comparison.” Paper presented at the American Agricultural Economics Association meetings, Tampa, FL. July-Aug. 2000.Google Scholar
Hyde, J., Martin, M.A., Preckel, P.V., and Edwards, C.R.. “The Economics of Bt Corn: Valuing Protection from the European Corn Boer.” Review of Agricultural Economics 21(1999):442–454.Google Scholar
Lauer, J. and Wedberg, J.. “Grain Yield of Initial Bt Corn Hybrid Introductions to Farmers in the Northern Corn Belt.” Journal of Production Agriculture 12(1999):373–376.Google Scholar
Lee, L. “Generalized Econometric Models with Selectivity Bias.” Econometrica 51(1983):507–12.Google Scholar
Maddala, G.S. Limited-Dependent and Qualitative Variables in Econometrics. Cambridge University Press, 1983.Google Scholar
Malik, J.M., Barry, G.F., and Kishore, G.M.. “The Herbicide Glyphosate.” BioFactors (1989):17–25.Google ScholarPubMed
Marra, M., Carlson, G., and Hubbell, B.. Economic Impacts of the First Crop Biotechnologies. Internet site: http://www.ag.econ.ncsu.edu/faculty/marra/online.html (Accessed April 4, 2001).Google Scholar
Maumbe, B. M., and Swinton, S. M.. “Why Do Smallholder Cotton Growers in Zimbabwe Adopt IPM? The Role of Pesticide-Related Health Risks and Technology Awareness” Paper presented at the American Agricultural Economics Association meetings, Tampa, FL. July-Aug. 2000.Google Scholar
McBride, W.D. and Brooks, N.. “Survey Evidence on Producer Use and Costs of Genetically Modified Seed.” Agribusiness 16(2000):6–20.Google Scholar
Mishra, A.K., El-Osta, H.S., and Johnson, J.D.. “Factors Contributing to Earnings Success of Cash Grain Farms.” Journal of Agricultural and Applied Economics 31(1999):623–637.Google Scholar
Nelson, F. D., and Olson, L.. “Specification and Estimation of a Simultaneous Equation Model with Limited Dependent Variables.” International Economic Review 19(1978):695–709.Google Scholar
Owen, M.D.K. “Midwest Experience with Herbicide-resistant Crops.” Proceedings of the Western Society of Weed Science, 1997, pp. 9–11.Google Scholar
Pike, D.R. Personal communication, University of Illinois, August 1999.Google Scholar
Reddy, K.N. and Whiting, K.. “Comparison of Weed Control in Roundup Ready, STS, and Conventional Soybeans.” Proceedings of the Southern Weed Science Society, 1999, pp. 210.Google Scholar
Rice, M.E. and Pilcher, C.D.. “Potential Benefits and Limitations of Transgenic Bt Corn for Management of the European Corn Borer (Lepidop-tera: Crambidae).” American Entomologist 44(1998):75–78.Google Scholar
Roberts, R.K., Pendergrass, R., and Hayes, R.M.. “Economic Analysis of Alternative Herbicide Regimes on Roundup Ready Soybeans.” Journal of Production Agriculture 12(1999):449–454.CrossRefGoogle Scholar
Rogers, E. Diffusion of Innovations, 4th Edition. New York: Free Press, 1995.Google Scholar
Seger, D.J. and Lins, D.A.. “Cash Versus Accrual Measures of Farm Income.” North Central Journal of Agricultural Economics 8(1986): 219–226.Google Scholar
U.S. Department of Agriculture, Economic Research Service. Internet site: http://www.ers.usda.gov/data/costsandretums/ (Accessed April 12, 2001).Google Scholar
U.S. Department of Agriculture, National Agricultural Statistics Service. Prospective Plantings Cr Pr 2-4. March 2000.Google Scholar
U.S. Department of Agriculture, National Agricultural Statistics Service. Agricultural Prices—1998 Summary Pr 1-3. July 1999.Google Scholar
Zepeda, L. “Simultaneity of Technology Adoption and Productivity.” Journal of Agricultural and Resource Economics 19(1994)1:46–57.Google Scholar