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Can Crop Insurance Premiums be Reliably Estimated?

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  • Ramirez, Octavio A.
  • Carpio, Carlos E.
  • Rejesus, Roderick M.

Abstract

The objective of this paper is to compare the accuracy of crop insurance rating methods based on historical liability and indemnity data (similar to the procedure currently used by the Risk Management Agency) and “yield distribution” approaches. Estimated rates are compared to “true” rates using empirically-grounded simulation procedures that take into account common data availability constraints. Simulation results suggest that farm and county level rate estimates using the “yield distribution” approach are significantly more accurate than those based on historical indemnity and liability records.

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Bibliographic Info

Paper provided by Agricultural and Applied Economics Association in its series 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin with number 49465.

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Date of creation: 30 Apr 2009
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Handle: RePEc:ags:aaea09:49465

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Keywords: crop insurance premiums; non-normal distributions; simulation methods; Agribusiness; Agricultural Finance; Risk and Uncertainty;

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References

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  1. Harwood, Joy L. & Heifner, Richard G. & Coble, Keith H. & Perry, Janet E. & Somwaru, Agapi, 1999. "Managing Risk in Farming: Concepts, Research, and Analysis," Agricultural Economics Reports 34081, United States Department of Agriculture, Economic Research Service.
  2. Ramirez, Octavio A. & McDonald, Tanya U., 2007. "An Empirically-Grounded Comparison of the Johnson System versus the Beta as Crop Yield Distribution Models," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 9814, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  3. Carriquiry, Miguel A. & Babcock, Bruce A. & Hart, Chad E., 2008. "Using a Farmer's Beta for Improved Estimation of Expected Yields," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 33(01), April.
  4. Lu, Yue & Ramirez, Octavio A. & Rejesus, Roderick M. & Knight, Thomas O. & Sherrick, Bruce J., 2008. "Empirically Evaluating the Flexibility of the Johnson Family of Distributions: A Crop Insurance Application," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 37(1), April.
  5. 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.
  6. 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.
  7. Ramirez, Octavio A. & McDonald, Tanya U. & Carpio, Carlos E., 2010. "A Flexible Parametric Family for the Modeling and Simulation of Yield Distributions," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 42(02), May.
  8. Bruce J. Sherrick & Fabio C. Zanini & Gary D. Schnitkey & Scott H. Irwin, 2004. "Crop Insurance Valuation under Alternative Yield Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 406-419.
  9. 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(02), December.
  10. 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.
  11. Octavio A. Ram�rez, 1997. "Estimation and Use of a Multivariate Parametric Model for Simulating Heteroskedastic, Correlated, Nonnormal Random Variables: The Case of Corn Belt Corn, Soybean, and Wheat Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 191-205.
  12. Joseph W. Glauber, 2004. "Crop Insurance Reconsidered," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(5), pages 1179-1195.
  13. Barry J. Barnett & Dmitry V. Vedenov, 2007. "Is There a Viable Market for Area-Based Crop Insurance?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(2), pages 508-519.
  14. Octavio A. Ram�rez & Tanya McDonald, 2006. "Ranking Crop Yield Models: A Comment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(4), pages 1105-1110.
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Citations

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Cited by:
  1. Octavio A. Ramirez & Carlos A. Carpio, 2012. "Premium estimation inaccuracy and the actuarial performance of the US crop insurance program," Agricultural Finance Review, Emerald Group Publishing, vol. 72(1), pages 117-133, March.
  2. O'Connor, Claire, 2013. "Soil Matters: How the Federal Crop Insurance Program should be reformed to encourage low-risk farming methods with high-reward environmental outcomes," 2013 AAEA: Crop Insurance and the Farm Bill Symposium, October 8-9, Louisville, KY 156789, Agricultural and Applied Economics Association.
  3. Ramirez, Octavio & Colson, Greg, 2013. "Premium Estimation Inaccuracy and the Distribution of Crop Insurance Subsidies," SCC-76 Meeting, March 14-16, 2013, Pensacola, Florida 152130, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.
  4. Ramirez, Octavio & Colson, Gregory, 2013. "Premium Estimation Inaccuracy and the Distribution of Crop Insurance Subsidies across Participating Producers," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149690, Agricultural and Applied Economics Association.

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