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Weather Derivatives, Spatial Aggregation, and Systemic Risk: Implications for Reinsurance Hedging

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  • Woodard, Joshua D.
  • Garcia, Philip
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    Abstract

    Previous studies identify limited potential efficacy of weather derivatives in hedging agricultural exposures. In contrast to earlier studies which investigate the problem at low levels of aggregation, we find that better weather hedging opportunities may exist at higher levels of spatial aggregation. Aggregating production exposures reduces idiosyncratic risk, leaving a greater proportion of the total risk in the form of systemic weather risk which can be effectively hedged using relatively simple weather derivatives. The aggregation effect suggests that the potential for weather derivatives in agriculture may be greater than previously thought, particularly for aggregators of risk such as reinsurers.

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    Bibliographic Info

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

    Volume (Year): 33 (2008)
    Issue (Month): 01 (April)
    Pages:

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    Handle: RePEc:ags:jlaare:36705

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    Web page: http://waeaonline.org/
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    Related research

    Keywords: crop insurance; hedging; reinsurance; spatial aggregation; systemic risk; weather derivatives; Risk and Uncertainty;

    References

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    1. Mason, Chuck & Hayes, Dermot J. & Lence, Sergio H., 2003. "Systemic Risk in U.S. Crop Reinsurance Programs," Staff General Research Papers 1944, Iowa State University, Department of Economics.
    2. Kevin Dowd & David Blake, 2006. "After VaR: The Theory, Estimation, and Insurance Applications of Quantile-Based Risk Measures," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(2), pages 193-229.
    3. Hayes, Dermot J. & Lence, Sergio H. & Mason, Chuck, 2003. "Could the Government Manage Its Exposure to Crop Reinsurance Risk?," Staff General Research Papers 11287, Iowa State University, Department of Economics.
    4. Dixon, Bruce L. & Hollinger, Steven E. & Garcia, Philip & Tirupattur, Viswanath, 1994. "Estimating Corn Yield Response Models To Predict Impacts Of Climate Change," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 19(01), July.
    5. Richards, Timothy J. & Manfredo, Mark R. & Sanders, Dwight R., 2004. "Pricing Weather Derivatives," Working Papers 28536, Arizona State University, Morrison School of Agribusiness and Resource Management.
    6. Vedenov, Dmitry V. & Barnett, Barry J., 2004. "Efficiency of Weather Derivatives as Primary Crop Insurance Instruments," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(03), December.
    7. 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.
    8. John Duncan & Robert J. Myers, 2000. "Crop Insurance under Catastrophic Risk," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(4), pages 842-855.
    9. Keith H. Coble, 2004. "The joint effect of government crop insurance and loan programmes on the demand for futures hedging," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 31(3), pages 309-330, September.
    10. 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.
    11. Joseph W. Glauber, 2004. "Crop Insurance Reconsidered," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(5), pages 1179-1195.
    12. 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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    Cited by:
    1. Hennessy, David A., 2011. "Modeling Stochastic Crop Yield Expectations with a Limiting Beta Distribution," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 36(1), April.
    2. Chung, Wonho, 2013. "Reducing the Social Cost of Federal Crop Insurance: A Role for US Government Hedging with Weather Derivatives," Journal of Rural Development/Nongchon-Gyeongje, Korea Rural Economic Institute, vol. 36(2), August.
    3. Robert Finger, 2010. "Revisiting the Evaluation of Robust Regression Techniques for Crop Yield Data Detrending," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 205-211.

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