Moral Hazard and Learning in the Tunisian Automobile Insurance Market: New Evidence from Dynamic Data

被引:0
|
作者
Imen Karaa
机构
[1] University of Sfax,Economics, Management and Computer Sciences Doctorate School of FSEG Sfax
关键词
moral hazard; learning; auto insurance; dynamic data; random effect; dynamic probit model;
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学科分类号
摘要
The main contribution of this paper is that it empirically studies the existence of asymmetric information in the Tunisian automobile insurance market. It also investigates the possibility of distinguishing moral hazard from adverse selection and asymmetric learning. To this end, we investigate the dynamics of insurance-coverage choices and of the occurrence of automobile claims, considering the bonus–malus mechanism, to identify the source of asymmetric information. Using a recent longitudinal data-set for 2008, 2009 and 2010 from one of the major insurance companies in Tunisia, our empirical results provide evidence for a significant positive correlation between claims occurrence and coverage choice. The results from using parametric and non-parametric tests provide evidence of residual asymmetric information among experienced drivers, while this asymmetry vanishes for beginner drivers. In a dynamic context, our empirical findings provide evidence of moral hazard. However, we do not find evidence of asymmetric learning.
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页码:560 / 589
页数:29
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