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Article

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2012-12

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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/106474

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

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https://doi.org/10.1016/j.csda.2012.05.016

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.

Subject

Inflació, Anàlisi de regressió, Assegurances d'accidents, Variables (Matemàtica)

Subject (English)

Inflation, Regression analysis, Accident insurance, Variables (Mathematics)

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Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)

Citation

BERMÚDEZ, Lluís and KARLIS, Dimitris. A finite mixture of bivariate Poisson regression models with an application to insurance ratemaking. Computational Statistics & Data Analysis. 2012. Vol. 56, num. 12, pags. 3988-3999. ISSN 0167-9473. [consulted: 14 of August of 2026]. Available at: https://hdl.handle.net/2445/106474

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