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The Influence of Distributional Assumptions on the Calculation of Crop Insurance Premia

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  • Carl H. Nelson

Abstract

Crop insurance premia are shown to be sensitive to the distributional assumptions used in their calculation. Premia calculations based on normal distributions and beta distributions are compared. The normal distribution overstates the probability of loss relative to the beta distribution, and causes premia to be higher. It is argued that use of the normal distribution in crop insurance premia calculation cannot be justified by appealing to a Central Limit Theorem because crop insurance loss events are not independent, and that distributions with flexible representation of skewness would be more appropriate for crop insurance premia calculation.

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  • Carl H. Nelson, 1990. "The Influence of Distributional Assumptions on the Calculation of Crop Insurance Premia," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 12(1), pages 71-78.
    • Handle: RePEc:oup:revage:v:12:y:1990:i:1:p:71-78.
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    File URL: http://hdl.handle.net/10.1093/aepp/12.1.71
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    Cited by:

    1. Clop-Gallart, M. Merce & Juarez-Rubio, Francisco, 2008. "Shape Persistence in Elicited Subjective Crop Yield Probability Density Functions," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44128, European Association of Agricultural Economists.
    2. Douadia Bougherara & Laurent Piet, 2018. "On the role of probability weighting on WTP for crop insurance with and without yield skewness," Working Papers hal-02790605, HAL.
    3. Li, Lisha, 2015. "Three essays on crop yield, crop insurance and climate change," ISU General Staff Papers 201501010800005371, Iowa State University, Department of Economics.
    4. Seyyed Ali Zeytoon Nejad Moosavian & Barry K. Goodwin, 2021. "Flexible modelling of multivariate risks in pricing margin protection insurance: modelling portfolio risks with mixtures of mixtures," Applied Economics, Taylor & Francis Journals, vol. 53(4), pages 411-440, January.
    5. Dhuyvetter, Kevin C. & Kastens, Terry L., 1999. "Linkages Between Crop Insurance and Pre-Harvest Hedging," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 31(1), pages 41-56, April.
    6. Gustafson, Cole R. & Crane, Laurence M. & Fischer, William R., 1995. "Agronomic, Economic, and Demographic Characteristics of Crop Farms in the Great Plains and Corn Belt," Agricultural Economics Reports 23221, North Dakota State University, Department of Agribusiness and Applied Economics.
    7. Zapata, Hector O. & Maradiaga, David Isaias & Pujula, Aude Liliana & Dicks, Michael R., 2011. "Recent Developments in Unit Root Tests and Historical Crop Yields," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103871, Agricultural and Applied Economics Association.
    8. Lanoue, Christopher & Sherrick, Bruce J. & Woodard, Joshua D. & Paulson, Nicholas D., 2010. "Evaluating Yield Models for Crop Insurance Rating," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61761, Agricultural and Applied Economics Association.
    9. Ying-Erh Chen & Barry K Goodwin, 2015. "Policy Design of Multi-Year Crop Insurance Contracts with Partial Payments," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-15, December.
    10. Ramsey, Ford, 2014. "An Application of Kernel Density Estimation via Diffusion to Group Yield Insurance," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170173, Agricultural and Applied Economics Association.
    11. Clop-Gallart, M. Merce & Juarez-Rubio, Francisco, 2005. "Elicitation of Subjective Crop Yield PDF for DSS Implementation," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24561, European Association of Agricultural Economists.
    12. 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.

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