Elicitation of Subjective Crop Yield PDF for DSS Implementation
The aim of this research is to establish the persistence of annual crop yield point values subjective estimates, and the coherence and reliability of subjective crop yield probability density functions (PDF) elicited from a series of interviews carried out on a wide group of farmers, and then to determine whether they should be included or not in a decision support system (DSS). Three different elicitation techniques were used: a) The Two Step PDF estimation method b) Triangular distribution c) Beta distribution Although the results are noteworthy, further studies should be carried out to perfect the aforementioned techniques before crop yield PDF's are used in decision making processes.
|Date of creation:||2005|
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- Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
- Pease, James W., 1992. "A Comparison Of Subjective And Historical Crop Yield Probability Distributions," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 24(02), December.
- Richard E. Just & Quinn Weninger, 1999.
"Are Crop Yields Normally Distributed?,"
American Journal of Agricultural Economics,
Agricultural and Applied Economics Association, vol. 81(2), pages 287-304.
- Robert K. Kaufmann & Seth E. Snell, 1997. "A Biophysical Model of Corn Yield: Integrating Climatic and Social Determinants," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 178-190.
- Norris, Patricia E. & Kramer, Randall A., 1990. "The Elicitation of Subjective Probabilities with Applications in Agricultural Economics," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 58, December.
- Octavio A. Ram�rez, 1997. "Estimation and Use of a Multivariate Parametric Model for Simulating Heteroskedastic, Correlated, Nonnormal Random Variables: The Case of Corn Belt Corn, Soybean, and Wheat Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 191-205.
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