A finite mixture of bivariate Poisson regression models with an application to insurance ratemaking

Lluís Bermúdez and Dimitris Karlis

Computational Statistics & Data Analysis, 2012, vol. 56, issue 12, 3988-3999

Abstract: Bivariate Poisson regression models for ratemaking in car insurance have been previously used. They included zero-inflated models to account for the excess of zeros and the overdispersion in the data set. These models are now revisited in order to consider alternatives. A 2-finite mixture of bivariate Poisson regression models is used to demonstrate that the overdispersion in the data requires more structure if it is to be taken into account, and that a simple zero-inflated bivariate Poisson model does not suffice. At the same time, it is shown that a finite mixture of bivariate Poisson regression models embraces zero-inflated bivariate Poisson regression models as a special case. Finally, an EM algorithm is provided in order to ensure the models’ ease-of-fit. These models are applied to an automobile insurance claims data set and it is shown that the modeling of the data set can be improved considerably.

Keywords: Zero-inflation; Overdispersion; EM algorithm; Automobile insurance; A priori ratemaking (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:56:y:2012:i:12:p:3988-3999

DOI: 10.1016/j.csda.2012.05.016

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