Mixed poisson regression models with varying dispersion arising from non-conjugate mixing distributions

George Tzougas, Natalia Hong and Ryan Ho

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: In this article we present a class of mixed Poisson regression models with varying dispersion arising from non-conjugate to the Poisson mixing distributions for modelling overdispersed claim counts in non-life insurance. The proposed family of models combined with the adopted modelling framework can provide sufficient flexibility for dealing with different levels of overdispersion. For illustrative purposes, the Poisson-lognormal regression model with regression structures on both its mean and dispersion parameters is employed for modelling claim count data from a motor insurance portfolio. Maximum likelihood estimation is carried out via an expectation-maximization type algorithm, which is developed for the proposed family of models and is demonstrated to perform satisfactorily.

Keywords: claim frequency; EM algorithm; non-life insurance; regression structures on the mean and dispersion parameters (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Pages: 13 pages
Date: 2022-01-01
New Economics Papers: this item is included in nep-ecm, nep-ias and nep-ore
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Published in Algorithms, 1, January, 2022, 15(1). ISSN: 1999-4893

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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:113616

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