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Weather-Based Adverse Selection And The U.S. Crop Insurance Program: The Private Insurance Company Perspective

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  • Ker, Alan P.
  • McGowan, Pat
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    Abstract

    Surprisingly, investigations of adverse selection have focused only on farmers. Conversely, this article investigates if insurance companies, not farmers, can generate excess rents from adverse selection activities. Currently political forces fashioning crop insurance as the cornerstone of U.S. agricultural policy make our analysis particularly topical. Focusing on El Nino/La Nina and winter wheat in Texas, we simulate out-of-sample reinsurance decisions during the 1978 through 1997 crop years while reflecting the realities imposed by the risk-sharing arrangement between the insurance companies and the federal government. The simulations indicate that economically and statistically significant excess rents may be garnered by insurance companies through weather-based adverse selection.

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    Bibliographic Info

    Article provided by Western Agricultural Economics Association in its journal Journal of Agricultural and Resource Economics.

    Volume (Year): 25 (2000)
    Issue (Month): 02 (December)
    Pages:

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    Handle: RePEc:ags:jlaare:30907

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    Web page: http://waeaonline.org/
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    Keywords: Risk and Uncertainty;

    References

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    1. John C. Quiggin & Giannis Karagiannis & J. Stanton, 1993. "Crop Insurance And Crop Production: An Empirical Study Of Moral Hazard And Adverse Selection," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 37(2), pages 95-113, 08.
    2. Ker, Alan P. & Coble, Keith H., 1998. "On Choosing A Base Coverage Level For Multiple Peril Crop Insurance Contracts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, Western Agricultural Economics Association, vol. 23(02), December.
    3. Baquet, Alan E. & Skees, Jerry R., 1994. "Group Risk Plan Insurance: An Alternative Management Tool for Farmers," Choices, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 9(1).
    4. Kennedy, P., 1993. "Randomization Tests in Econometrics," Discussion Papers dp93-08, Department of Economics, Simon Fraser University.
    5. Mario J. Miranda & Joseph W. Glauber, 1997. "Systemic Risk, Reinsurance, and the Failure of Crop Insurance Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 79(1), pages 206-215.
    6. Jerry R. Skees & J. Roy Black & Barry J. Barnett, 1997. "Designing and Rating an Area Yield Crop Insurance Contract," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 79(2), pages 430-438.
    7. Goodwin, Barry K., 1994. "Premium Rate Determination In The Federal Crop Insurance Program: What Do Averages Have To Say About Risk?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, Western Agricultural Economics Association, vol. 19(02), December.
    8. Goodwin, Barry K. & Ker, Alan P., 1998. "Revenue Insurance: A New Dimension in Risk Management," Choices, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 13(4).
    9. Keith H. Coble & Thomas O. Knight & Rulon D. Pope & Jeffery R. Williams, 1996. "Modeling Farm-Level Crop Insurance Demand with Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 78(2), pages 439-447.
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    Cited by:
    1. Martin, Steven W. & Barnett, Barry J. & Coble, Keith H., 2001. "Developing And Pricing Precipitation Insurance," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, Western Agricultural Economics Association, vol. 26(01), July.
    2. Deryugina, Tatyana, 2012. "Does Selection in Insurance Markets Always Favor Buyers?," MPRA Paper 53583, University Library of Munich, Germany.
    3. Tolhurst, Tor & Ker, Alan P., 2013. "On Technological Change in Crop Yields," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C., Agricultural and Applied Economics Association 151269, Agricultural and Applied Economics Association.
    4. David Ubilava & Matt Holt, 2013. "El Niño southern oscillation and its effects on world vegetable oil prices: assessing asymmetries using smooth transition models," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(2), pages 273-297, 04.

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