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Impact of the New Standard Reinsurance Agreement (SRA) on Multi-Peril Crop Insurance (MPCI) Gain and Loss Probabilities


  • Vergara, Oscar
  • Seaquist, Jack
  • Zuba, Gerhard
  • Harrigan, Matthew
  • Lee, Eric


We utilize an agricultural model that uses crop/weather relationships at the county resolution and fits robust distributions that take into account the impact that weather has on crop production. Once the crop insurance policy conditions and prices are applied to the modeled county yield distributions, the portfolio gain and losses can be calculated by aggregating the gain and losses at the county level, state level, regional level and nationwide level. Portfolio losses are computed under the old and new SRA rules and regulations for comparison purposes.

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  • Vergara, Oscar & Seaquist, Jack & Zuba, Gerhard & Harrigan, Matthew & Lee, Eric, 2011. "Impact of the New Standard Reinsurance Agreement (SRA) on Multi-Peril Crop Insurance (MPCI) Gain and Loss Probabilities," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103282, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea11:103282

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    References listed on IDEAS

    1. Roberto Rigobon, 2003. "Identification Through Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 777-792, November.
    2. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    3. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
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    SRA; MPCI; crop insurance; stochastic model; weather peril; probabilities; Crop Production/Industries; Research and Development/Tech Change/Emerging Technologies; Risk and Uncertainty; C; Q;

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