Hostname: page-component-848d4c4894-75dct Total loading time: 0 Render date: 2024-05-14T13:48:11.223Z Has data issue: false hasContentIssue false

A Comparison of Subjective and Historical Crop Yield Probability Distributions

Published online by Cambridge University Press:  28 April 2015

James W. Pease*
Affiliation:
Virginia Polytechnic Institute and State University
Get access

Abstract

Forecast distributions based on historical yields and subjective expectations for 1987 expected crop yields were compared for 90 Western Kentucky grain farms. Different subjective probability elicitation techniques were also compared. In many individual cases, results indicate large differences between subjective and empirical moments. Overall, farmer expectations for 1987 corn yields were below those predicted from their past yields, while soybean expectations were above the historical forecast. Geographical location plays a larger role than crop in comparisons of relative variability of yield. Neither elicitation technique nor manager characteristics have significant effects on the comparisons of the forecasts.

Type
Articles
Copyright
Copyright © Southern Agricultural Economics Association 1992

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

Belsley, D., Kuh, E., and Welsch, R.. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. New York: Wiley, 1980.CrossRefGoogle Scholar
Day, R.Probability Distributions of Field Crop Yields.“ J. Farm Econ., 47(1965):713741.CrossRefGoogle Scholar
Eisgruber, L., and Schuman, L.. “The Usefulness of Aggregated Data in the Analysis of Farm Income Variability and Resource Allocation.J. Farm Econ., 45(1963):587591.CrossRefGoogle Scholar
Gallagher, P.U.S. Corn Yield Capacity and Probability: Estimation and Forecasting with Nonsymmetric Disturbances.” No. Cent J. Agr. Econ., 8(1986): 109122.Google Scholar
Gibbons, J.Nonparametric Methods for Quantitative Analysis. Columbus, OH: American Science Press, 1985.Google Scholar
Ludke, R., Stauss, F., and Gustafson, D.. “Comparison of Five Methods for Estimating Subjective Probability Distributions.Org. Behav. and Hum. Perf., 19(1977):162179.CrossRefGoogle ScholarPubMed
Madansky, A.Prescriptions for Working Statisticians. New York: Springer-Verlag, 1988.CrossRefGoogle Scholar
Tversky, A., and Kahneman, D.. “The Framing of Decisions and the Psychology of Choice.Science, 211(1988):453458.CrossRefGoogle Scholar
Nelson, A.E., and Harris, T.. “Designing an Instructional Package: The Use of Probabilities in Farm Decision Making.Am. J. Agr. Econ., 60(1978):993997.CrossRefGoogle Scholar
Norris, P., and Kramer, R.. “The Elicitation of Subjective Probabilities With Applications in Agricultural Economics.” Rev. Mkt. and Agr. Econ., forthcoming.Google Scholar
Pease, J.Using Psychological Principles to Guide Probability Elicitation.” Paper presented at the annual meeting of the AAEA, East Lansing, Michigan, 1987.Google Scholar
Pease, J., and Black, J. R.. “Estimation of the Probabilities of Alternative Yields Using the ‘Conviction Weights’ Method.” Staff Paper 89-98, Department of Agricultural Economics, Michigan State University, 1989.Google Scholar
Pingali, P., and Carlson, G.. “Human Capital, Adjustments in Subjective Probabilities, and the Demand for Pest Control.Am. J. Agr. Econ., 67(1985):853861.CrossRefGoogle Scholar
Spetzler, C., and Stael von Holstein, C.. “Probability Encoding in Decision Analysis.” Manage. Sci., 22(1975): 340358.CrossRefGoogle Scholar
Tversky, A., and Kahneman, D.. “The Framing of Decisions and the Psychology of Choice.Science, 211(1981):453458.CrossRefGoogle ScholarPubMed
Von Winterfeldt, D., and Edwards, W.. Decision Analysis and Behavioral Research. Cambridge: Cambridge University Press, 1986.Google Scholar