Traffic violations and insurance data: a note on the role of age, gender, annual mileage and vehicle brand
2011 (English)Report (Other (popular science, discussion, etc.))
Risky 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 Swedens 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.
Older version: http://swopec.hhs.se/vtiwps/abs/vtiwps2011_003.htm
Place, publisher, year, edition, pages
Stockholm: Statens väg- och transportforskningsinstitut, 2011. , 35 p.
CTS Working Paper, 2011:3
Insurance, Car, Risk, Risk taking, Offence, Driver, Age, Man, Woman
Försäkring, Bilar, Risk, Risktagande, Lagöverträdelser, Förare, Ålder, Män, Kvinnor
Research subject Road: Traffic safety and accidents, Road: Accident costs
IdentifiersURN: urn:nbn:se:vti:diva-637OAI: oai:DiVA.org:vti-637DiVA: diva2:669332