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Spatio-Temporal Modeling Of Agricultural Yield Data With An Application To Pricing Crop Insurance Contracts

  • Ozaki, Vitor Augusto
  • Ghosh, Sujit K.
  • Goodwin, Barry K.
  • Shirota, Ricardo

This article focuses on the modeling of agricultural yield data using hierarchical Bayesian models. In recovering the generating process of these data, we consider the temporal, spatial and spatio-temporal relationships pertinent to the prediction and pricing of insurance contracts based on regional crop yields. A county-average yield data set was analyzed for the State of Paraná, Brazil for the period of 1990 through 2002. The choice of the best model from among the several non-nested models considered was based on the posterior predictive criterion. The methodology used in this article proposes improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations of limited data. These conditions are frequently encountered, especially at the individual level.

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File URL: http://purl.umn.edu/19142
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Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2005 Annual meeting, July 24-27, Providence, RI with number 19142.

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Date of creation: 2005
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Handle: RePEc:ags:aaea05:19142
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  1. Weninger, Quinn & Just, Richard E., 1999. "Are Crop Yields Normally Distributed?," Staff General Research Papers 5064, Iowa State University, Department of Economics.
  2. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer, vol. 43(1), pages 1-20, March.
  3. Goodwin, Barry K. & Mahul, Olivier, 2004. "Risk modeling concepts relating to the design and rating of agricultural insurance contracts," Policy Research Working Paper Series 3392, The World Bank.
  4. Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
  5. Alan P. Ker & Barry K. Goodwin, 2000. "Nonparametric Estimation of Crop Insurance Rates Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(2), pages 463-478.
  6. Akerlof, George A, 1970. "The Market for 'Lemons': Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, MIT Press, vol. 84(3), pages 488-500, August.
  7. Rothschild, Michael & Stiglitz, Joseph E, 1976. "Equilibrium in Competitive Insurance Markets: An Essay on the Economics of Imperfect Information," The Quarterly Journal of Economics, MIT Press, vol. 90(4), pages 630-49, November.
  8. Alan P. Ker & Keith Coble, 2003. "Modeling Conditional Yield Densities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 291-304.
  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. Zanini, Fabio C. & Sherrick, Bruce J. & Schnitkey, Gary D. & Irwin, Scott H., 2001. "Crop Insurance Valuation Under Alternative Yield Distributions," 2001 Conference, April 23-24, 2001, St. Louis, Missouri 18953, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
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