Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-11T02:57:03.792Z Has data issue: false hasContentIssue false
  • English
  • Français

Technology Adoption and Off-Farm Household Income: The Case ofHerbicide-Tolerant Soybeans

Published online by Cambridge University Press:  28 April 2015

Jorge Fernandez-Cornejo ,
Chad Hendricks  and
Ashok Mishra
Jorge Fernandez-Cornejo
Affiliation:
Economic Research Service (ERS), U.S. Department of Agriculture
Chad Hendricks
Affiliation:
ERS
Ashok Mishra
Affiliation:
Economic Research Service (ERS), U.S. Department of Agriculture
Get access Rights & Permissions [Opens in a new window]

Abstract

We model the interaction of off-farm work and adoption of agriculturaltechnologies and the impact of adopting these technologies on farm householdincome from on farm and off-farm sources after controlling for suchinteraction, and estimate the model for the case of adoption ofherbicide-tolerant (HT) soybeans using a nationwide survey of soybean farmsfor 2000. We find that adoption of HT soybeans is positively andsignificantly related to off-farm household income for U.S. soybean farmers,after controlling for other factors. In addition, while on-farm householdincome is not significantly related to adoption, total household incomeincreases significantly with adoption.

Keywords

agricultural household modelbiotechnologyherbicide tolerant soybeansoff-farm incometechnology adoptionO33Q12
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 37 , Issue 3 , December 2005 , pp. 549 - 563
Copyright
Copyright © Southern Agricultural Economics Association 2005

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

Carrington, W.G., Eltinge, J.L., and McCue, K.. An Economist's Primer on Survey Samples. Center for Economic Studies, U.S. Bureau of the Census CES 00-15, October 2000. http://148.129.75.160/paper.php?paper= 101613 Google Scholar
Duffy, M. “Who Benefits from Biotechnology?” Paper presented at the American Seed Trade Association meeting, Chicago, IL, December 5-7, 2001.Google Scholar
Fernandez-Cornejo, J., Beach, E.D., and Huang, Wen-Yuan. “The Adoption of IPM Techniques by Vegetable Growers in Florida, Michigan, and Texas.” Journal of Agricultural and Applied Economics 1(1994):158–72.Google Scholar
Fernandez-Cornejo, J., Klotz-Ingram, C., and Jans, S.. “Farm-Level Effects of Adopting Herbicide-Tolerant Soybeans in the U.S.A.” Journal of Agricultural and Applied Economics 34(1)(2002): 149–63.Google Scholar
Fernandez-Cornejo, J., and McBride, W.D.. Adoption of Bioengineered Crops. Agricultural Economic Report No. 810. U.S. Department of Agriculture, ERS, Washington, DC, 2002.Google Scholar
Geweke, J., Keane, M., and Runkle, D.. “Alternative Computational Approaches to Inference in the Multinomial Probit Model.” Review of Economics and Statistics 76(4)(1994):609–32.Google Scholar
Gianessi, L.P., and Carpenter, J.E.. Agricultural Biotechnology: Insect Control Benefits. National Center for Food and Agricultural Policy, Washington, DC. 1999. http://www.bio.org/food&ag/ncfap.htm.Google Scholar
Goodwin, B.K., and Holt, M.T.. “Parametric and Semiparametric Modeling of the Off-Farm Labor Supply of Agrarian Households in Transition Bulgaria. American Journal of Agricultural Economics 84(2002): 184–209.Google Scholar
Goodwin, B.K., and Mishra, A.K., “Farming Efficiency and the Determinants of Multiple Job Holding by Farm Operators.” American Journal of Agricultural Economics 86(2004):722–29.Google Scholar
Greene, W.H. Econometric Analysis, 3rd ed. Upper Saddle River, NJ: Prentice-Hall, 1997.Google Scholar
Hoppe, R.A., Perry, J., and Banker, D.. “ERS Farm Typology: Classifying a Diverse Ag. Sector.” Agricultural Outlook, AGO-266, Department of Agriculture, ERS, Washington, DC. 1999.Google Scholar
Huffman, W.E. “Farm and Off-Farm Work Decisions: The Role of Human Capital.” Revue of Economics and Statistics 62(1)(1980): 14–23.Google Scholar
Huffman, W.E. “Agricultural Household Models: Survey and Critique.” Multiple Job Holding Among Farm Families. Hallberg, M.C., Findeis, J.L., and Lass, D.A., eds. Ames: Iowa State University Press, 1991.Google Scholar
Huffman, W.E., and Lange, M.D.. “Off-Farm Work Decisions of Husbands and Wives: Joint Decision Making.” Revue of Economics and Statistics 71 (1989) :471–80.Google Scholar
Huffman, W.E., and El-Osta, H.. Off-Farm Work Participation, Off-Farm Labor Supply and Off-Farm Labor Demand of U.S. Farm Operators. Staff paper 290. Ames: Iowa State University, 1997.Google Scholar
Kimhi, A. “Quasi Maximum Likelihood Estimation of Multivariate Probit Models: Farm Couples' Labor Participation.” American Journal of Agricultural Economics 76(1994):828–35.Google Scholar
Kimhi, A. “Family Composition and Off-Farm Participation Decisions in Israeli Farm Households.” American Journal of Agricultural Economics 86(2004):502–12.Google Scholar
Kott, P.S., and Stukel, D.M.. “Can the Jackknife Be Used With a Two-Phase Sample?” Survey Methodology 23(2)(1997):81–89.Google Scholar
Kott, P.S. Using the Delete-A-Group Jackknife Variance Estimator in NASS Surveys. RD Research Report RD-98-01, Washington, DC. USDA, NASS, 1998.Google Scholar
Lass, D.A., Findeis, J.L., and Hallberg, M.C.. “Off-Farm Labor Employment Decisions by Massachusetts Farm Households.” Northeastern Journal of Agricultural and Resource Economics 18(1989): 149–59.Google Scholar
Lass, D.A., and Gempesaw, C.M. II. “The Supply of Off-Farm Labor: A Random Coefficients Approach.” American Journal of Agricultural Economics 74(1992):400–11.Google Scholar
Maddala, G.S. Limited-Dependent and Qualitative Variables in Econometrics. Cambridge, UK: Cambridge University Press, 1983.Google Scholar
Mishra, A.K., El-Osta, H.S., Morehart, M.J., Johnson, J.D., and Hopkins, J.W.. Income, Wealth, and the Economic Weil-Being of Farm Households. Agricultural Economic Report 812. U.S. Department of Agriculture, ERS, Washington, DC., 2002.Google Scholar
Rust, K. “Variance Estimation for Complex Estimators in Sample Surveys.” Journal of Official Statistics (1)(1985):381–97.Google Scholar
Singh, I., Squire, L., and Strauss, J.. (Eds.), Agricultural Household Models: Extensions, Applications, and Policy. Baltimore, MD: Johns Hopkins University Press, 1986.Google Scholar
Smith, K.R. “Does Off-Farm Work Hinder ‘Smart’ Farming?” Agricultural Outlook AGO-294, (2002):28–30.Google Scholar
Stefanides, Z., and Tauer, L.W.. “The Empirical Impact of Bovine Somatropin on a Group of New York Dairy Farms.” American Journal of Agricultural Economics 81(1999):95–102.Google Scholar
Tokle, J.G., and Huffman, W.E.. “Local Economic Conditions and Wage Labor Decisions of Farm and Rural Nonfarm Couples.” American Journal of Agricultural Economics 73(1991):52–70.Google Scholar
U.S. Department of Agriculture, Economic Research Service. Agricultural Resource Management Survey (ARMS). Briefing Room. March 11, 2003. http://www.ers.usda.gov/Briefing/ARMS/ Google Scholar
U.S. Department of Agriculture, National Agricultural Statistics Service. Prospective Plantings. Washington, DC., March 31, 2003, pp. 20–21. http://usda.mannlib.cornell.edu/reports/nassr/field/pcp-bbp/pspl0303.txt Google Scholar