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Using Non-Contemporaneous Data to Specify Risk Programming Models

Published online by Cambridge University Press:  10 May 2017

Bernard V. Tew ,
Wesley N. Musser  and
G. Scott Smith
Bernard V. Tew
Affiliation:
Department of Agricultural Economics and Department of Finance, University of Kentucky
Wesley N. Musser
Affiliation:
Department of Agricultural Economics and Rural Sociology, Pennsylvania State University
G. Scott Smith
Affiliation:
Department of Agricultural Economics, University of Georgia
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Abstract

Specification of the variance-covariance matrix holds continuing interest for agricultural economists considering risk programming applications. This research examines alternative expected value-variance (E-V) frontiers constructed using contemporaneous and non-contemporaneous data and two statistical assumptions concerning crop prices and yields. Empirical examples from two locations for different crops illustrate the various assumptions. Considerable differences in the E-V efficient frontiers occur in both empirical settings.

Type
Articles
Information
Northeastern Journal of Agricultural and Resource Economics , Volume 17 , Issue 1 , April 1988 , pp. 30 - 35
Copyright
Copyright © 1988 Northeastern Agricultural and Resource Economics Association 

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Footnotes

The authors would like to express their appreciation to Jerry R. Skees for his help in compiling data for the Kentucky sample.

References

Adams, Richard M., Menkhaus, Dale J., and Woolery, Bruce A. “Alternative Parameter Specification in E-V Analysis: Implications for Farm Land Decision Making.” Western Journal of Agricultural Economics 5 (1980):13–20.Google Scholar
Anderson, Jock R., Dillon, John J. and Hardaker, Brian. Agricultural Decision Analysis. Ames, IA: Iowa State University Press, 1977.Google Scholar
Boggess, William G., Lynne, Gary D., Jones, James W., and Swaney, Dennis P. “Risk-Return Assessment of Irrigation Decisions in Humid Regions.” Southern Journal of Agricultural Economics 15 (1983):135–43.Google Scholar
Bohrnstedt, George W. and Goldberger, Arthur S. “On Exact Covariances of Products of Random Variables.” American Statistics Association Journal 64 (1969):1439–42.Google Scholar
Burt, Oscar R. and Finley, R. M. “Statistical Analysis of Identities in Random Variables.” American Journal of Agricultural Economics 50 (1968):734–44.Google Scholar
Carter, H. O. and Dean, G. W. “Income, Price, and Yield Variability for Principal California Crops and Cropping Systems.” Hilgardia 30 (1960):175–218.Google Scholar
Debertin, D. L., Moore, C. L. Jr., Bradford, G. L., and Jones, L. D. Kash Profits. Dept. of Agricultural Economics, University of Kentucky, Lexington, 1976.Google Scholar
Dillon, John L. The Analysis of Response in Crop and Livestock Production. Second Edition. New York, New York: Pergamon Press, 1977.Google Scholar
Dixon, Bruce and Barry, Peter J., “Portfolio Analysis Considering Estimation Risk and Imperfect Markets.” Western Journal of Agricultural Economics 8 (1983):103–11.Google Scholar
Freund, R. S. “The Introduction of Risk into a Programming Model.” Econometrica 24 (1956):253–64.Google Scholar
Goodman, Leo A. “On the Exact Variance of Products.” American Statistics Association Journal 55 (1960):708–13.Google Scholar
Georgia Crop Reporting Service. Georgia Agricultural Facts. Athens, Georgia 1982.Google Scholar
Klinefelter, D. A., Sonka, S. T., and Baker, C. B. “Selection and Screening of Marketing Option for Risk Evaluation.” Risk Analysis in Agriculture: Research and Educational Developments. Dept. of Agr. Econ., University of Illinois, AE-4492, 1980.Google Scholar
Lin, W., Dean, G., and Moore, C. “An Empirical Test of Utility Versus Profit Maximization.” American Journal of Agricultural Economics 56 (1974):497–508.Google Scholar
McSweeny, W. T., Kenyon, D. E., and Kramer, R. A. “Uncertainty in Risk Programming.” American Journal of Agricultural Economics 69 (1987):87–96.Google Scholar
Musser, Wesley N., Mapp, Harry P., and Barry, Peter J. “Applications I: Risk Programming.” Risk Management in Agriculture. Barry, Peter J., editor. Ames, Iowa. Iowa State University Press, 1984.Google Scholar
Musser, W. N., and Musser, L. M. “Psychological Perspectives on Risk Analysis.” Risk Management in Agriculture. Barry, P. J., editor. Ames, IA: IA State Univ. Press, 1984, p. 82–94.Google Scholar
Musser, Wesley N. and Tew, Bernard V. “Uses of Biophysical Simulation in Production Economics.” Southern Journal of Agricultural Economics 16 (1984):77–86.Google Scholar
Musser, Wesley N. and Stamoulis, Kostas G. “Evaluating the Food and Agricultural Act of 1977 with Firm Quadratic Risk Programming.” American Journal of Agricultural Economics 63 (1981):447–56.Google Scholar
Peck, A. E. “Hedging and Income Stability: Concepts, Implications, and an Example.” American Journal of Agricultural Economics 75 (1975):410–30.Google Scholar
Persaud, T. and Mapp, Harry P. “Effects of Alternative Measures of Dispersion in Risk-Efficient Farm Plans in a MOTAD Framework.” Paper presented at the A.A.E.A. Meetings, Pullman, Washington, 1979.Google Scholar
Schurle, Bryan and Erven, Bernard L. “Sensitivity of Efficient Frontiers Developed for Farm Enterprise Choice Decisions.” American Journal of Agricultural Economics 61 (1979):506–11.Google Scholar
Tew, Bernard V. and Boggess, William G. “Risk-Return Assessment of Irrigation Decisions in Humid Regions: An Extension.” Southern Journal of Agricultural Economics 16 (1984):159–160.Google Scholar
Tew, Bernard V. An Expected Value-Variance Analysis of Alternative Production Systems: A Study of Irrigation Schedules in the Georgia Coastal Plain. Unpublished Ph.D. Dissertation. University of Georgia. Athens, 1984.Google Scholar
Young, Douglas L. “Risk Concepts and Measures for Decision Analysis.” Risk Management in Agriculture. Barry, Peter J., editor. Ames, Iowa. Iowa State University Press, 1984.Google Scholar
Young, D. L. “Evaluating Procedures for Computing Objective Risk from Historical Time Series.” Risk Analysis in Agriculture: Research and Educational Development. Univ. of Ill., Dept. Agr. Econ. AE-4492, 1980.Google Scholar