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http://dx.doi.org/10.5351/KJAS.2014.27.1.147

An Analysis on the Gender Differences in the Level of Accident Risk using Generalized Linear and Heckman Methods  

Kim, DaeHwan (Department of Economics, Dong-A University)
Park, HwaGyu (Department of Health Administration and Management, Soonchunhyang University)
Publication Information
The Korean Journal of Applied Statistics / v.27, no.1, 2014 , pp. 147-157 More about this Journal
Abstract
Women's roles have changed substantially in economically developed countries; subsequently, the ratio of female drivers has also increased. In such countries, there has been considerable interest in assessing gender differences in vehicle accident risks and reasons to explain the gender differences. This study investigates the gender differences in vehicle accident risk based on 500,000 drivers randomly selected from a population sample. A Heckman model is used for accident damage and a negative binomial model is used for the accident frequency. Empirical results show that male drivers are 8.3% riskier than female drivers in terms of accident damage; however, female drivers are 113% risker than male drivers in term of accident frequency. We can implement more practical policies to reduce vehicle accidents if we can understand the reasons for the gender differences.
Keywords
Female drivers; vehicle accidents; Heckman model; negative binomial model;
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