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

# metadata.dc.description.abstract[].value
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.

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

# metadata.dc.source[].value
Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)

# metadata.dc.title[].value
A finite mixture of bivariate Poisson regression models with an application to insurance ratemaking