Efficient Estimation of Copula Mixture Models: An Application to the Rating of Crop Revenue Insurance

Abstract

The association between prices and yields are of paramount importance to the crop insurance programs. Proper estimation of the association is highly desirable. Copulas are one such method to measure the dependence structure. Five single parametric copulas, a nonparametric copula and their fifteen different combinations taking a mixture of two different copulas at a time have been used in the crop insurance rating analysis. Using data of corn from 1973-2009 for 602 counties in the Mid-West area two different efficient methods have been proposed to generate the optimal mixtures using the cross validation approach. A resampling technique is used to check for the significance of the expected indemnities.

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Cite this paper

@inproceedings{Ghosh2011EfficientEO, title={Efficient Estimation of Copula Mixture Models: An Application to the Rating of Crop Revenue Insurance}, author={Somali Ghosh and Joshua D. Woodard and Dmitry V. Vedenov}, year={2011} }