期刊名称：Annals of the Alexandru Ioan Cuza University - Economics
电子版ISSN：2068-8717
出版年度：2015
卷号：62
期号：2
页码：151-168
DOI：10.1515/aicue-2015-0011
语种：English
出版社：Walter de Gruyter GmbH
摘要：Within non-life insurance pricing, an accurate evaluation of claim frequency, also known in theory as count data, represents an essential part in determining an insurance premium according to the policyholder’s degree of risk. Count regression analysis allows the identification of the risk factors and the prediction of the expected frequency of claims given the characteristics of policyholders. The aim of this paper is to verify several hypothesis related to the methodology of count data models and also to the risk factors used to explain the frequency of claims. In addition to the standard Poisson regression, Negative Binomial models are applied to a French auto insurance portfolio. The best model was chosen by means of the log-likelihood ratio and the information criteria. Based on this model, the profile of the policyholders with the highest degree of risk is determined
关键词：claim frequency ; count data models ; Poisson model ; overdispersion ; mixed Poisson models ; negative binomial models ; risk factors
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