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MODEL OF THE NUMBER OF LOSSES IN AUTOMOBILE INSURANCE - EMPIRICAL ANALYSIS WITH PANEL DATA FROM POLISH MARKET

100%
Witkowski B.
Roczniki Kolegium Analiz Ekonomicznych
|
2008
|
vol. 18
147-164
EN
The aim of the article is to discuss a model used to determine the number of losses in automobile insurance. The model is based on panel data. Although the aim is to model the number of losses, due to hunger for bonus not all the losses are revealed. Thus the data on the number and also the value of claims are used. Common use of these two types of data enables estimation of the true number of losses that occur (not just those that are claimed). This is done with the use of true data from the Polish market. The discussion of particular factors that influence the severity of losses (moral hazard, hunger for bonus, observed and unobserved characteristics of the insured) is included.
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The econometric analysis of claim frequency in the automobile insurance portfolio - panel data analysis

100%
Witkowski B.
Roczniki Kolegium Analiz Ekonomicznych
|
2005
|
vol. 14
103-128
EN
The goal of this article is to apply panel data approach to the analysis of claim frequency in automobile insurance. The model which is constructed estimates the influence of particular characteristics of the insured on their insurance loss number, but it also enables identification of the hunger for bonus effect. Panel data approach allows for identification of drivers' individual effects that influence their driving quality, but cannot be quantified directly, such as for example tendency to drive fast. This is done thanks to repetitive observation of the same individuals. Having information on their number of losses claimed in different bonus-malus system classes, it is possible to separate their individual skills from the hunger for bonus phenomenon, as well as identify the scale of the latter, which differs in particular classes. Chapter one is an introduction. In chapter two main benefits from the use of panel data have been described. Recent publications considering the topic are mentioned as well, with emphasis on the differences between other authors' approaches and this one. Chapter three contains a brief description of the methods applied, which are Poisson regression mixed models. In chapter four the basic model is adjusted to the conditions of hunger for bonus and it is shown, how this phenomenon is identified. In chapter five empirical analysis based on the real market data of approximately 21 thousand observations is done. The model is estimated and the conclusions are discussed with a short simulation study of the insurance company financial state.
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