Experience Rating in Nonlife Insurance

  • Jean Pinquet


This chapter presents statistical models which lead to experience rating in insurance. Serial correlation for risk variables can receive endogenous or exogenous explanations. The interpretation retained by actuarial models is exogenous and reflects the positive contagion usually observed for the number of claims. This positive contagion can be explained by the revelation throughout time of a hidden features in the risk distributions. These features are represented by fixed effects which are predicted with a random effects model. This chapter discusses identification issues on the nature of the dynamics of nonlife insurance data. Examples of predictions are given for count data models with a constant or time-varying random effects, one or several equations, and for cost-number models on events.


Observed and real contagion Overdispersion Fixed and random effects models Heterogeneity and state dependence Poisson models with random effects Experience rating with an expected value principle or a linear credibility approach 


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© Springer Science + Business media, New York 2013

Authors and Affiliations

  1. 1.Université Paris-Ouest Nanterre La Défense and Ecole PolytechniqueParisFrance

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