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Elicitation of Subjective Crop Yield PDF for DSS Implementation

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  • Clop-Gallart, M. Merce
  • Juarez-Rubio, Francisco

Abstract

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.

Suggested Citation

  • Clop-Gallart, M. Merce & Juarez-Rubio, Francisco, 2005. "Elicitation of Subjective Crop Yield PDF for DSS Implementation," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24561, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae05:24561
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    File URL: http://purl.umn.edu/24561
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    References listed on IDEAS

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    1. C. Robert Taylor, 1990. "Two Practical Procedures for Estimating Multivariate Nonnormal Probability Density Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(1), pages 210-217.
    2. 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.
    3. Octavio A. Ramírez, 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.
    4. Charles B. Moss & J. S. Shonkwiler, 1993. "Estimating Yield Distributions with a Stochastic Trend and Nonnormal Errors," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(4), pages 1056-1062.
    5. 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.
    6. 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.
    7. 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.
    8. David A. Bessler, 1980. "Aggregated Personalistic Beliefs on Yields of Selected Crops Estimated Using ARIMA Processes," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 62(4), pages 666-674.
    9. 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.
    10. Pease, James W., 1992. "A Comparison of Subjective and Historical Crop Yield Probability Distributions," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 24(02), pages 23-32, December.
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