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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

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.

Suggested Citation

  • Ker, Alan P. & McGowan, Pat, 2000. "Weather-Based Adverse Selection And The U.S. Crop Insurance Program: The Private Insurance Company Perspective," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-25, December.
    • Handle: RePEc:ags:jlaare:30907
    DOI: 10.22004/ag.econ.30907
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    References listed on IDEAS

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    1. Goodwin, Barry K. & Ker, Alan P., 1998. "Revenue Insurance: A New Dimension in Risk Management," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 13(4), pages 1-4.
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    5. Kennedy, Peter E, 1995. "Randomization Tests in Econometrics," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 85-94, January.
    6. 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, vol. 19(2), pages 1-14, December.
    7. 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.
    8. Baquet, Alan E. & Skees, Jerry R., 1994. "Group Risk Plan Insurance: An Alternative Management Tool for Farmers," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 9(1), pages 1-4.
    9. 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, vol. 23(2), pages 1-18, December.
    10. 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, vol. 79(1), pages 206-215.
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    Citations

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    Cited by:

    1. Deryugina, Tatyana, 2012. "Does Selection in Insurance Markets Always Favor Buyers?," MPRA Paper 53583, University Library of Munich, Germany.
    2. Bruno Larue & Alan P. Ker, 2024. "Climate change, production and trade in apples," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 72(3), pages 325-346, September.
    3. Quaye, Leonard-Allen A. & Stewart, Shamar L. & Holt, Matthew T., 2024. "Exploring the Dynamics of Commodity Prices and Weather Anomalies using a STAR model," 2024 Annual Meeting, July 28-30, New Orleans, LA 343706, Agricultural and Applied Economics Association.
    4. Ubilava, David & holt, Matt, 2013. "El Ni~no 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 1-25.
    5. Chen, Shu-Ling, 2011. "Modeling Temperature Dynamics for Aquaculture Index Insurance In Taiwan: A Nonlinear Quantile Approach," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 104229, Agricultural and Applied Economics Association.
    6. Shaik, Saleem & Coble, Keith H. & Knight, Thomas O., 2005. "Revenue Crop Insurance Demand," 2005 Annual meeting, July 24-27, Providence, RI 19319, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Carriquiry, Miguel A. & Osgood, Daniel E., 2006. "Index Insurance, Production Practices, and Probabilistic Climate Forecasts," 2006 Annual meeting, July 23-26, Long Beach, CA 21463, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Alberto Garrido & David Zilberman, 2008. "Revisiting the demand for agricultural insurance: the case of Spain," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 68(1), pages 43-66, May.
    9. Jesse B. Tack & David Ubilava, 2015. "Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 245-257, March.
    10. A. Ford Ramsey & Barry K. Goodwin, 2019. "Value-at-Risk and Models of Dependence in the U.S. Federal Crop Insurance Program," JRFM, MDPI, vol. 12(2), pages 1-21, April.
    11. A Ford Ramsey, 2020. "Probability Distributions of Crop Yields: A Bayesian Spatial Quantile Regression Approach," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 220-239, January.
    12. Keith H. Coble & Robert Dismukes & Joseph W. Glauber, 2007. "Private Crop Insurers and the Reinsurance Fund Allocation Decision," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(3), pages 582-595.
    13. Fujin Yi & Mengfei Zhou & Yu Yvette Zhang, 2020. "Value of Incorporating ENSO Forecast in Crop Insurance Programs," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 439-457, March.
    14. Tor N. Tolhurst & Alan P. Ker, 2015. "On Technological Change in Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 137-158.
    15. Yong Liu & Alan P. Ker, 2021. "Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policies," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 231-257, March.
    16. Liu, Y. & Ker, A., 2018. "Is There Too Much History in Historical Yield Data," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277293, International Association of Agricultural Economists.
    17. Ker, Alan. P & Tolhurst, Tor & Liu, Yong, 2015. "Rating Area-yield Crop Insurance Contracts Using Bayesian Model Averaging and Mixture Models," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205211, Agricultural and Applied Economics Association.
    18. Yong Liu & A. Ford Ramsey, 2023. "Incorporating historical weather information in crop insurance rating," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(2), pages 546-575, March.
    19. Nathan D. DeLay & Hayley H. Chouinard & Cory G. Walters & Philip R. Wandschneider, 2020. "The influence of crop insurance agents on coverage choices: The role of agent competition," Agricultural Economics, International Association of Agricultural Economists, vol. 51(4), pages 623-638, July.
    20. 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, vol. 26(1), pages 1-14, July.
    21. A. Ford Ramsey & Yong Liu, 2023. "Linear pooling of potentially related density forecasts in crop insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(3), pages 769-788, September.
    22. Christopher N. Boyer & B. Wade Brorsen & Emmanuel Tumusiime, 2015. "Modeling skewness with the linear stochastic plateau model to determine optimal nitrogen rates," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 1-10, January.
    23. Ker, Alan P. & Ergun, A. Tolga, 2003. "On The Revelation Of Asymmetric Information Of The Private Insurance Companies In The Us Crop Insurance Program," 2003 Annual meeting, July 27-30, Montreal, Canada 21898, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    24. Miguel A. Carriquiry & Walter E. Baethgen, 2016. "Seasonal Climate Forecasts and Agricultural Risk Management: Implications for Insurance Design," Documentos de Trabajo (working papers) 16-03, Instituto de Economía - IECON.

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