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An Assessment of the Canadian Federal-Provincial Crop Production Insurance Program under Future Climate Change Scenarios in Ontario

  • Li, Shuang
  • Ker, Alan P.
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    Research and observations indicate climate change has and will have an impact on Ontario field crop production. Little research has been done to forecast how climate change might influence the Canadian Federal-Provincial Crop Insurance program, including its premium rates and reserve fund balances, in the future decades. This paper proposes using a mixture of two normal yield probability distribution model to model crop yield conditions under hypothetical climate change scenarios. Then superimposes Crop Insurance premium rate and reserve fund balance calculations onto the yield model to forecast their trends and fluctuation situations in the future decades. We find under the scenarios where climate change alters the probability of a lower yield year occurring and where climate change alters yield averages, both have more significant impacts on premium rates and reserve fund balances, compared to the scenarios where climate change alters yield variations. The results of this research will help Agricorp Ltd. identify the likely frequency and magnitude of both insurance premium rate fluctuations and reserve fund balance fluctuations under different climate change scenarios. Therefore the results can be used to help Agricorp Ltd. identify and forecast both premium rate fluctuation risk and reserve fund liquidity risk.

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    Paper provided by Agricultural and Applied Economics Association in its series 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. with number 151213.

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    Date of creation: 2013
    Date of revision:
    Handle: RePEc:ags:aaea13:151213
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    1. 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.
    2. Alan P. Ker & Barry K. Goodwin, 2000. "Nonparametric Estimation of Crop Insurance Rates Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(2), pages 463-478.
    3. Bruce A. McCarl & Xavier Villavicencio & Ximing Wu, 2008. "Climate Change and Future Analysis: Is Stationarity Dying?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(5), pages 1241-1247.
    4. Gallagher, Paul W., 1987. "U.S. Soybean Yields: Estimation and Forecasting with Non-Symmetric Disturbances," Staff General Research Papers 10779, Iowa State University, Department of Economics.
    5. Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
    6. Weninger, Quinn & Just, Richard E., 1999. "Are Crop Yields Normally Distributed?," Staff General Research Papers 5064, Iowa State University, Department of Economics.
    7. Nayak, Govindaray & Turvey, Calum G., 1999. "Empirical Issues In Crop Reinsurance Decisions," 1999 Annual meeting, August 8-11, Nashville, TN 21612, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Barnwal, Prabhat & Kotani, Koji, 2013. "Climatic impacts across agricultural crop yield distributions: An application of quantile regression on rice crops in Andhra Pradesh, India," Ecological Economics, Elsevier, vol. 87(C), pages 95-109.
    9. Tack, Jesse B. & Harri, Ardian & Coble, Keith H., 2012. "More than Mean Effects: Modeling the Effect of Climate on the Higher Order Moments of Crop Yields," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 123330, Agricultural and Applied Economics Association.
    10. Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
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