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An Evaluation of Expected Value and Expected Value-Variance Criteria in Achieving Risk Efficiency in Crop Selection

Published online by Cambridge University Press:  10 May 2017

Donald W. Reid  and
Bernard V. Tew
Donald W. Reid
Affiliation:
Department of Agricultural Economics, University of Georgia
Bernard V. Tew
Affiliation:
Department of Agricultural Economics and Department of Finance, University of Kentucky
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Abstract

This article evaluates the performance of expected value and expected value-variance criteria in achieving risk efficiency in crop selection. Results indicate that the expected returns criterion achieves risk efficiency in many situations because of constraints. However, in the absence of many constraints the expected returns criterion performs poorly except when highly mean-dominant activities are present. The expected value-variance criterion achieves a high degree of risk efficiency for all situations examined. This result implies that criteria more complex than expected value-variance are not necessary for crop selection analysis, given empirical returns distributions.

Keywords

expected returnsexpected value-variancerisk efficiencyrisk aversion
Type
Articles
Information
Northeastern Journal of Agricultural and Resource Economics , Volume 16 , Issue 2 , October 1987 , pp. 93 - 101
Copyright
Copyright © 1987 Northeastern Agricultural and Resource Economics Association 

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Footnotes

Senior authorship is equally shared.

References

Bessler, David A. “Aggregated Personalistic Beliefs on Yields of Selected Crops Estimated Using ARIMA Processes.” American Journal of Agricultural Economics 62 (1980):666–74.Google Scholar
Brink, Lars, and McCarl, Bruce. “The Tradeoff Between Expected Return and Risk Among Cornbelt Farmers.” American Journal of Agricultural Economics 60 (1978):259–63.Google Scholar
Buccola, Steven T. “Testing for Nonnormality in Farm Net Returns.” American Journal of Agricultural Economics 68 (1986):334–43.Google Scholar
Buckley, A. An Alternative Implementation of Goldfarb's Minimization Algorithm, Atomic Energy Research Establishment, Harwell Report TP544, 1973.Google Scholar
Chou, Chia-Jen, Musser, Wesley N., and Miller, Bill R. “Agricultural Labor Availability and Optimum Machinery Size on a Representative Farm in Georgia.” Selected paper Southern Agricultural Economics Association, Orlando, Florida, 1982.Google Scholar
Collender, Robert N., and Zilberman, David. “Land Allocation Under Uncertainty for Alternative Specifications of Return Distributions.” American Journal of Agricultural Economics 67 (1985):779–93.Google Scholar
Day, Richard H. “Probability Distributions of Field Crop Yields.” Journal of Farm Economics 47 (1965):713–41.Google Scholar
Fishburn, P. C. “Convex Stochastic Dominance with Continuous Distribution Functions.” Journal of Economic Theory 7 (1974):143–58.Google Scholar
Goldfarb, D. “Extension of Davidson's Variable Metric Algorithm to Maximize Under Linear Inequality and Equality Constraints.” SIAM Journal of Applied Mathematics 17 (1969):739–64.Google Scholar
Hadar, J., and Russell, W. R. “Rules for Ordering Uncertain Prospects.” American Economic Review 59 (1969):25–34.Google Scholar
Hanoch, G., and Levy, H. “The Efficiency Analysis of Choices Involving Risk.” Review of Economic Studies 36 (1969):335–46.Google Scholar
Heady, Earl O. “Diversification in Resource Allocation and Minimization of Income Variability.” Journal of Farm Economics 34 (1952):482–96.Google Scholar
King, Robert P., and Oamek, George E. “Risk Management by Colorado Dryland Wheat Farmers and the Elimination of the Disaster Assistance Program.” American Journal of Agricultural Economics 65 (1983):247–55.Google Scholar
Kroll, Yoram, Levy, Haim, and Markowitz, Harry M. “Mean-Variance Versus Direct Utility Maximization.” Journal of Finance 39 (1984):47–61.Google Scholar
Lambert, David K., and McCarl, Bruce A. “Risk Modeling Using Direct Solution of the Expected Utility Function.” American Journal of Agricultural Economics 67 (1985):846–852.Google Scholar
Lee, John, Brown, Deborah J., and Lovejoy, Stephen. “Stochastic Efficiency versus Mean-Variance Criteria as Predictions of Adoption of Reduced Tillage.” American Journal of Agricultural Economics 67 (1985):839–45.Google Scholar
Lehman, E. L. “Ordering Families of Distributions.” Annals of Mathematical Statistics 26 (1985):399–419.Google Scholar
Lin, William W., and Moore, Charles V. “Bernoullian Utility Functions: Alternative Uses and Estimating Procedures,” in Market Risks in Agriculture: Concepts, Methods and Policy Issues, Proceedings of the Western Regional Research Project, W-149, 1978.Google Scholar
McSweeny, William T., Kenyon, David E., and Kramer, Randall A. “Toward an Appropriate Measure of Uncertainty in a Risk Programming Model.” American Journal of Agricultural Economics 69 (1987):87–96.Google Scholar
Meyer, Jack. “Choice Among Distributions.” Journal of Economic Theory 14 (1977):32–6.Google Scholar
Moss, Robert B., and Saunders, Fred B. Costs and Returns for Selected Crop Enterprises at the Southwest Georgia Branch Station, 1978–80 with Comparisons for the 18-year Period, 1963–80. Georgia Agriculture Experiment Station Research Report 398, 1982.Google Scholar
Perry, Charles E., and Saunders, Fred B. Costs and Returns for Selected Crop Enterprises at the Southeast Georgia Branch Station, 1978–80 with Comparisons for the 18-year Period, 1963–80. Georgia Agriculture Experiment Station Research Report 397, 1982.Google Scholar
Pulley, L. B. “A General Mean-Variance Approximation to Expected Utility for Short Holding Periods.” Journal of Financial and Quantitative Analysis 16 (1981):361–73.Google Scholar
Quirk, J. P., and Saposnik, R. “Admissibility and Measurable Utility Functions.” Review of Economic Studies 29 (1962):140–46.Google Scholar
Reid, Donald W., and Tew, Bernard V. “Mean-Variance Versus Expected Utility Maximization: A Comment.” Journal of Finance 41 (1986):1177–79.Google Scholar
Tsaing, S. C. “The Rationale of the Mean-Standard Deviation Analysis, Skewness Preference, and the Demand for Money.” American Economic Review 62 (1972):354–71.Google Scholar
Yassour, Joseph, Zilberman, David, and Rausser, Gordon C. “Optimal Choices Among Alternative Technologies with Stochastic Yield.” American Journal of Agricultural Economics 63 (1981):718–23.Google Scholar