Hostname: page-component-848d4c4894-4rdrl Total loading time: 0 Render date: 2024-06-25T01:11:55.819Z Has data issue: false hasContentIssue false

Impact of Risk Preferences on Crop Rotation Choice

Published online by Cambridge University Press:  15 September 2016

Leigh J. Maynard
Affiliation:
Department of Agricultural Economics and Rural Sociology, the Pennsylvania State University
Jayson K. Harper
Affiliation:
Department of Agricultural Economics and Rural Sociology, the Pennsylvania State University
Lynn D. Hoffman
Affiliation:
Department of Agronomy, the Pennsylvania State University
Get access

Abstract

Stochastic dominance analysis of five crop rotations using twenty-one years of experimental yield data returned results consistent with Pennsylvania cropping practices. The analysis incorporated yield risk, output price risk, and rotational yield effects. A rotation of two years corn and three years alfalfa hay dominated for approximately risk neutral and risk averse preferences, as did participation in government programs under the 1990 Farm Bill. Crop rotation selection appeared to impact net revenues more than the decision to participate in government programs.

Type
Articles
Copyright
Copyright © 1997 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

The Agronomy Guide, 1993-1994. 1993. University Park, Pa.: Penn State Cooperative Extension.Google Scholar
Agricultural Stabilization and Conservation Service (ASCS). 1994. Office staff, personal communication. Bellefonte, Pa.Google Scholar
Brown, W.J. 1987. “A Risk Efficiency Analysis of Crop Rotations in Saskatchewan.” Canadian Journal of Agricultural Economics 35: 333–55.CrossRefGoogle Scholar
Cochran, M.J. 1982. “Selection of Optimal Pest Management Strategies Under Uncertainty: A Case Study in Apple Production.” Ph.D. dissertation, Michigan State University.Google Scholar
Cochran, M.J. 1986. “Stochastic Dominance: The State of the Art in Agricultural Economics.” In An Economic Analysis of Risk Management Strategies for Agricultural Production Firms. Proceedings of a seminar sponsored by Southern Regional Project S-180. Pullman, Wash.: Washington State University.Google Scholar
Duffy, P.A., and Taylor, C.R. 1994. “Effects on a Corn-Soybean Farm of Uncertainty about the Future of Farm Programs.” American Journal of Agricultural Economics 76: 141–52.Google Scholar
Ford, B.P., Musser, W.N., and Yonkers, R.D. 1993. “Measuring Historical Risk in Quarterly Milk Prices.” Agricultural and Resource Economics Review 22: 2026.CrossRefGoogle Scholar
Hammond, J.S. 1974. “Simplifying the Choice between Uncertain Prospects Where Preference Is Nonlinear.” Management Science 20: 1047–72.CrossRefGoogle Scholar
Harper, J.K., Williams, J.R., Burton, R.O. Jr., and Kelley, K.W. 1991. “Effect of Risk Preferences on Incorporation of Double-Crop Soybeans into Traditional Rotations.” Review of Agricultural Economics 13: 185200.Google Scholar
King, R.P., and Oamek, G.E. 1983. “Risk Management by Colorado Dryland Wheat Farmers and the Elimination of the Disaster Assistance Program.” American Journal of Agricultural Economics 65: 247–55.Google Scholar
King, R.P., and Robison, L.J. 1981. “An Interval Approach to Measuring Decision Maker Preferences.” American Journal of Agricultural Economics 63: 510–20.Google Scholar
Kurtz, L.T., Boone, L.V., Peck, T.R., and Hoeft, R.G. 1984. “Crop Rotations for Efficient Nitrogen Use.” In Nitrogen and Crop Production, ed. Hauck, R.D. Madison, Wise.: American Society of Agronomy, Inc., Crop Science Society of America, Inc., Soil Science Society of America, Inc.Google Scholar
Love, R.O., and Robison, L.J. 1984. “An Empirical Analysis of the Intertemporal Stability of Risk Preference.” Southern Journal of Agricultural Economics 16: 159–66.Google Scholar
McCarl, B.A. 1990. “Generalized Stochastic Dominance: An Empirical Examination.” Southern Journal of Agricultural Economics 22: 4955.Google Scholar
Meyer, J. 1977. “Choice among Distributions.” Journal of Economic Theory 14: 326–36.Google Scholar
Musser, W.N. 1994. “Progress in Risk Analysis in Regional Projects.” Paper presented at 1994 meeting of Regional Research Project S-232, Gulf Shores State Park, Al, March 24-26.Google Scholar
Musser, W.N., Alexander, V.J., Tew, B.V., and Smittle, D.A. 1985. “A Mathematical Programming Model for Vegetable Rotations.” Southern Journal of Agricultural Economics 17: 169–76.Google Scholar
Musser, W.N., and Stamoulis, K.G. 1981. “Evaluating the Food and Agriculture Act of 1977 with Firm Quadratic Risk Programming.” American Journal of Agricultural Economics 63: 447–56.CrossRefGoogle Scholar
Novak, J.L., Mitchell, C.C. Jr., and Crews, J.R. 1990. “Risk and Sustainable Agriculture: A Target-MOTAD Analysis of the 92-Year Old Rotation.’Southern Journal of Agricultural Economics 22: 145–52.Google Scholar
Pennsylvania Agricultural Statistics Service. 1970-90. Keystone Ag Digest. Harrisburg, Pa.Google Scholar
Pennsylvania Agricultural Statistics Service. 1993. Keystone Ag Digest 93, no. 2. Harrisburg, Pa.Google Scholar
Raskin, R., and Cochran, M.J. 1986a. “Interpretations and Transformations of Scale for the Pratt-Arrow Absolute Risk Aversion Coefficient: Implications for Generalized Stochastic Dominance.” Western Journal of Agricultural Economics 11: 204–10.Google Scholar
Raskin, R., and Cochran, M.J. 1986b. “A User's Guide to the Generalized Stochastic Dominance Program for the IBM PC.” Fayetteville: University of Arkansas.Google Scholar
Spurlock, S.R., and Laughlin, D.H. 1987. “Mississippi State Budget Generator User's Guide, Version 2.0.Agricultural Economics Technical Publication No. 64. Mississippi State: Mississippi State University.Google Scholar
Tauer, L. 1986. “Risk Preferences of Dairy Farmers.” North Central Journal of Agricultural Economics 8: 715.CrossRefGoogle Scholar
U.S. Department of Agriculture (USDA). 1970-92. Annual Price Summary, Washington, D.C.: Agricultural Statistics Board, National Agricultural Statistics Service.Google Scholar
U.S. Department of Agriculture (USDA). 1990. “The 1990 Farm Act and the 1990 Budget Reconciliation Act: How U.S. Farm Policy Mechanisms Will Work Under New Legislation.” Washington, D.C.: Economic Research Service. December.Google Scholar
U.S. Department of Agriculture (USDA). 1994. Agricultural Outlook. Washington, D.C.: Economic Research Service. January-February.Google Scholar
Williams, J.R., Harper, J.K., and Barnaby, G.A. 1990. “Government Program Impacts on the Selection of Crop Insurance in Northeastern Kansas.” North Central Journal of Agricultural Economics 12: 207–21.Google Scholar
Williams, J.R., Carriker, G.L., Barnaby, G.A., and Harper, J.K. 1993. “Crop Insurance and Disaster Assistance Designs for Wheat and Grain Sorghum.” American Journal of Agricultural Economics 75: 435–47.Google Scholar
Wilson, P.N., and Eidman, V.R. 1983. “An Empirical Test of the Interval Approach for Estimating Risk Preferences.” Western Journal of Agricultural Economics 8: 170–82.Google Scholar
Zacharias, T.P., and Grube, A.H. 1984. “An Economic Evaluation of Weed Control Methods Used in Combination with Crop Rotation: A Stochastic Dominance Approach.” North Central Journal of Agricultural Economics 6: 113–20.Google Scholar