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Efficiency Criteria and Risk Aversion: An Empirical Evaluation
Published online by Cambridge University Press: 28 April 2015
Abstract
A conceptual link among mean-variance (EV), stochastic dominance (SD), mean-risk (ET), and Gini mean difference (EG) is established for determining risk efficient decision sets. The theoretical relations among the various efficiency criteria are then empirically demonstrated with a soybean and wheat double-crop simulation model. Empirical results associated with extended Gini mean difference (EEG) and extended mean-absolute Gini (EEΓ) for risk analysis are encouraging.
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- Copyright © Southern Agricultural Economics Association 1988
References
Atwood, J.“Demonstration of the Use of Lower Partial Moments to Improve Safety-First Probability Limits.” Amer. J. Agr. Econ., 67 (1985):787–793.CrossRefGoogle Scholar
Baumol, W.J.. “An Expected Gain-Confidence Limit Criterion for Portfolio Selection.” Mgt. Sci., 10 (1963):174–182.CrossRefGoogle Scholar
Bawa, V.S., Bodurtha, J.N. Jr, Rao, M.R., and Suri, H.L.. “On Determination of Stochastic Dominance Optimal Sets.” J. Finance., 40 (1985):417–431.CrossRefGoogle Scholar
Bey, R.P.. “Estimating the Optimal Stochastic Dominance Efficient Set with a Mean-Semivariance Algorithm.” J. Financial Quantitative Analysis, 14 (1979):1059–1070.CrossRefGoogle Scholar
Bey, R.P., and Howe, K.M.. “Gini's Mean Difference and Portfolio Selection: An Empirical Evaluation.” J. Financial Quantitative Analysis, 19 (1984):329–338.CrossRefGoogle Scholar
Boisvert, R.N.. “The Role of Alternative Risk Programming Models in Empirical Research.” In Risk Analysis for Agricultural Production Firms: Concepts, Information Requirements and Policy Issues. Southern Regional Project S-180 Proceedings, Charleston, South Carolina, 1985.Google Scholar
Buccola, S.T., and Subaei, A.. “Mean-Gini Analysis, Stochastic Efficiency and Weak Risk Aversion.” Australian J. Agr. Econ., 28 (1984):77–86.Google Scholar
Clements, A.M., Mapp, H.P., and Eidman, V.R.. A Procedure for Correlating Events in Farm Firm Simulation Models. Oklahoma Agricultural Experiment Station Bulletin T-131,1971.Google Scholar
Cochran, M.J.. “Stochastic Dominance: The State of the Art in Agricultural Economics.” Unpublished manuscript, Department of Agricultural Economics, University of Arkansas, 1986.Google Scholar
Cochran, M.J., Robinson, L.J., and Lodwick, W.. “Improving the Efficiency of Stochastic Dominance Techniques Using Convex Set Stochastic Dominance.” Amer. J. Agr. Econ., 67 (1985):289–295.CrossRefGoogle Scholar
Dybvig, P.H, and Ross, S.A.. “Portfolio Efficient Sets.” Econometrica, 50 (1982):1525–1546.CrossRefGoogle Scholar
Fishburn, P.C. “Convex Stochastic Dominance with Continuous Distribution Function.” J. Econ. Theory, 7 (1974):143–158.CrossRefGoogle Scholar
Fishburn, P.C.. “Mean-Risk Analysis with Risk Associated with Below-Target Returns.” Amer. Econ. Rev., 67 (1977):116–126.Google Scholar
Gini, C.“On the Measure of Concentration with Special Reference to Income and Wealth.”Abstracts of papers presented at the Cowles Commission Research Conference on Economics and Statistics. Colorado Springs: Colorado College Press, 1936.Google Scholar
Lerman, R.I., and Yitzhaki, S.. “A Note on the Calculation and Interpretation of the Gini Index.” Economics Letters, 15 (1984):363–368.CrossRefGoogle Scholar
Levy, H.“Stochastic Dominance Among Log-Normal Prospects.” International Econ. Rev. 14 (1973):601–614.CrossRefGoogle Scholar
Levy, H., and Hanoch, G.. “Relative Effectiveness of Efficiency Criteria for Portfolio Selection.”J. Financial Quantitative Analysis, 5 (1970):63–76.CrossRefGoogle Scholar
Pope, R.D., and Ziemer, R.F.. “Stochastic Efficiency, Normality, and Sampling Errors in Agricultural Risk Analysis.” Amer. J. Agr. Econ., 66 (1984):31–40.CrossRefGoogle Scholar
Porter, R.B. “Semivariance and Stochastic Dominance: A Comparison.” Amer. Econ. Rev., 64 (1974):200–204.Google Scholar
Rawls, J.A Theory of Justice. Cambridge, Mass.: Harvard University Press, 1971.CrossRefGoogle Scholar
Selley, R.“Decision Rules in Risk Analysis.” In Risk Management in Agriculture.Ed. Barry, Peter. Ames, Iowa: Iowa State University Press, 1984.Google Scholar
Shalit, H., and Yitzhaki, S.. “Mean-Gini Portfolio Theory, and the Pricing of Risky Assets.” J. Finance, 39 (1984):1449–1468.Google Scholar
Stuart, A.“The Correlation Between Variate-Values and Ranks in Samples From a Continuous Distribution.” British J. Statistical Psychology, 1954.CrossRefGoogle Scholar
Wetzstein, M.E., Edwards, D.M.Musser, W.N., and McClendon, R.W.. An Economic Simulation of Risk Efficiency Among Alternative Double-Crop Machinery Selections. University of Georgia Agricultural Experiment Station Research Bulletin No. 342, December 1986.Google Scholar
Yitzhaki, S.“On an Extension of the Gini Inequality Index.” International Econ. Rev., 24 (1983):617–628.CrossRefGoogle Scholar
Yitzhaki, S.“Stochastic Dominance, Mean Variance, and Gini's Mean Difference.” Amer. Econ. Rev., 72 (1982):178–185.Google Scholar
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