Traffic Violations and Insurance Data: a note on the role of age, gender, annual mileage and vehicle brand
AbstractRisky driving behavior is regarded as being one of the best predictors of traffic accidents. Traffic violations certainly signal risky driving behavior, but the analysis of the linkage of traffic violations, individual and vehicle characteristics and annual mileage has so far been hampered by the difficulty of gaining access to appropriate disaggregate data. The contribution of this paper is that it sets out and explores a rich data set in order to study traffic violations, including both accident involved and accident-free individuals. The data set comprises all insurance policies from Sweden’s largest automobile insurance company covering several years, in total 9.3 million observations, as well as information on fines and convictions for traffic violations. This implies that the methodological issues associated with self-reported violations and only accident involved individuals are disused. The first purpose is to establish the role of age and gender in traffic violations. The second purpose is to make a first attempt to establish whether vehicle owners of status brands are more likely to commit traffic violations. The results support previous findings as well as confirm the association between owners of status brands and traffic violations. The main conclusion is that insurance data provides a viable option when studying behavior, but it also raises new methodological issues
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Bibliographic InfoPaper provided by Swedish National Road & Transport Research Institute (VTI) in its series Working Papers with number 2011:3.
Length: 35 pages
Date of creation: 03 Feb 2011
Date of revision:
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Postal: VTI, Transport Economics, P.O. Box 6056, SE-171 06 Solna, Sweden
Phone: +46-13-20 40 00
Fax: +46-13-14 14 36
Web page: http://www.vti.se/tek
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Insurance; asymmetric information; accidents; traffic violations; automobile brand;
Find related papers by JEL classification:
- D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
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