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Estimating Crop Yield Insurance Premium Rates

Published online by Cambridge University Press:  10 May 2017

Daniel J. Dudek
Affiliation:
Department of Agricultural and Resource Economics, University of Massachusetts, Amherst
P. Geoffrey Allen
Affiliation:
Department of Agricultural and Resource Economics, University of Massachusetts, Amherst
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Abstract

Insurance rates for crop yield protection programs have traditionally been calculated from county average yields. Where grower acreages and yields are not homogeneous, this approach leads to higher premiums and payouts and greater incidence of adverse selection. With individual grower data a production weighted rate premium calculation method can be used which avoids these problems. Furthermore, the definition of rate classes is not constrained to county boundaries. The additional complication of technical change is addressed and one solution is provided. Results are presented for the cranberry industry.

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Copyright
Copyright © Northeastern Agricultural and Resource Economics Association 

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References

Botts, Ralph R. and Boles, James N., “Use of Normal Curve Theory in Crop Insurance Ratemaking,” Journal of Farm Economics, XL(August 1958): 733–40.Google Scholar
Halcrow, Harold G., “Actuarial Structures for Crop Insurance,” Journal of Farm Economics, XXXI(August 1949): 418–43.Google Scholar
U.S. Department of Agriculture, Farm Income Protection Insurance: A Report to the United States Congress, Farm Income Protection Task Force, (June 1983).Google Scholar
U.S. Government Accounting Office, Analysis of Certain Operations of the Federal Crop Insurance Corporation, CED-81-148 (July, 1981).Google Scholar
Weisberg, Herbert I. and Tomberlin, Thomas J., “A Statistical Perspective on Actuarial Methods for Estimating Pure Premiums from Cross-Classified Data,” The Journal of Risk and Insurance, XLIX(December 1982): 539–63.Google Scholar
Yeh, Martin H. and Wu, Roland Y., “Premium Ratemaking in an All Risk Crop Insurance Program,” Journal of Farm Economics, 48 (December 1966): 1580–86.CrossRefGoogle Scholar
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