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Estimation of crop yield distribution and Insurance Premium using Shrinkage Estimator: A Hierarchical Bayes and Small Area Estimation Approach

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  • Awondo, Sebastain N.
  • Datta, Gauri S.
  • Ramirez, Octavio A.
  • Fonsah, Esendugue Greg
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    Abstract

    Obtaining reliable estimates of insurance premiums is a critical step in risk sharing and risk transfer necessary to ensure solvency and continuity in crop insurance programs. Challenges encountered in the estimation include dealing with aggregation bias from using county level yield averages as well as properly accounting for spatial and temporal heterogeneity. In this study, we associate some of these challenges as classical small area estimation (SAE) problems. We employ a hierarchical Bayes (HB) SAE to obtain design consistent expected county level yields and Group Risk Plan (GRP) premiums for corm farms in Illinois using quasi-simulated data. Preliminary results show little bias (< 10%) in estimated expected county yields in several counties investigated. We found wide variation in GRP, APH and basis risk across counties for similar level of coverage and scale. Results show that farmers could lower their GRP premiums by as much as 30% by carefully choosing a coverage level and scale combination.

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    Bibliographic Info

    Paper provided by Agricultural and Applied Economics Association in its series 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington with number 126778.

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    Date of creation: 2012
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    Handle: RePEc:ags:aaea12:126778

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    Related research

    Keywords: Crop Insurance; Small area estimation; Hierarchical Bayes; Farm Management; Research Methods/ Statistical Methods; Risk and Uncertainty;

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    1. 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.
    2. Roger Claassen & Richard E. Just, 2010. "Heterogeneity and Distributional Form of Farm-Level Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(1), pages 144-160.
    3. 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.
    4. Ozaki, Vitor Augusto & Ghosh, Sujit K. & Goodwin, Barry K. & Shirota, Ricardo, 2005. "Spatio-Temporal Modeling Of Agricultural Yield Data With An Application To Pricing Crop Insurance Contracts," 2005 Annual meeting, July 24-27, Providence, RI 19142, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Sukant K. Misra & Jeannie Nelson, 2003. "Efficient Estimation of Agricultural Time Series Models with Nonnormal Dependent Variables," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 1029-1040.
    6. 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.
    7. Richard E. Just & Rulon D. Pope, 1999. "Implications of Heterogeneity for Theory and Practice in Production Economics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(3), pages 711-718.
    8. Wolfram Schlenker & W. Michael Hanemann & Anthony C. Fisher, 2006. "The Impact of Global Warming on U.S. Agriculture: An Econometric Analysis of Optimal Growing Conditions," The Review of Economics and Statistics, MIT Press, vol. 88(1), pages 113-125, February.
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