Citation

Benlagha N, Charfeddine L. Accid. Anal. Prev. 2020; 136: e105411.

Affiliation

Department of Finance and Economics, College of Business and Economics, Qatar University. P.O.X 2713, Doha, Qatar. Electronic address: lcharfeddine@qu.edu.qa.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.aap.2019.105411

PMID

31911400

Abstract

Road accident fatalities and accident severity costs have become top priorities and concerns for Chinese policymakers. Understanding the principal factors that explain accident severity is considered to be the first step towards the adequate design of an accident prevention strategy. In this paper, we examine the contribution of various types of factors (vehicle, driver and others) in explaining accident severity in China. Unlike previous studies, the analysis gives a particular focus on fatal accidents. Using a large sample of 405,177 observations for 4-wheeled vehicles in the year 2017 and various statistical and econometrics approaches (e.g., OLS, quantile regression and extreme value theory), the results show that the factors explaining the severity of accidents differs significantly between normal and extreme severity accidents, e.g. across quantiles. Interestingly, we find that the gender factor is only significant for fatal accidents. In particular, the analysis shows that male drivers have an increased likelihood of extreme risk taking. On the basis of these empirical findings, a new ratemaking approach that aims to improve road safety and prevention is discussed and proposed.

Copyright © 2019 Elsevier Ltd. All rights reserved.

Language: en

Keywords

Accident severity; China; Extreme value theory; Fatal accidents; Prevention strategy; Quantile regression