A joint econometric analysis of seat belt use and crash-related injury severity.
This paper formulates a comprehensive econometric structure that recognizes two important issues in crash-related injury severity analysis. First, the impact of a factor on injury severity may be moderated by various observed and unobserved variables specific to an individual or to a crash. Second, seat belt use is likely to be endogenous to injury severity. That is, it is possible that intrinsically unsafe drivers do not wear seat belts and are the ones likely to be involved in high injury severity crashes because of their unsafe driving habits. The preceding issues are considered in the current research effort through the development of a comprehensive model of seat belt use and injury severity that takes the form of a joint correlated random coefficients binary-ordered response system. To our knowledge, this is the first instance of such a model formulation and application not only in the safety analysis literature, but in the econometrics literature in general. The empirical analysis is based on the 2003 General Estimates System (GES) data base. Several types of variables are considered to explain seat belt use and injury severity levels, including driver characteristics, vehicle characteristics, roadway design attributes, environmental factors, and crash characteristics. The results, in addition to confirming the effects of various explanatory variables, also highlight the importance of (a) considering the moderating effects of unobserved individual/crash-related factors on the determinants of injury severity and (b) seat belt use endogeneity. From a policy standpoint, the results suggest that seat belt non-users, when apprehended in the act, should perhaps be subjected to both a fine (to increase the chances that they wear seat belts) as well as mandatory enrollment in a defensive driving course (to attempt to change their aggressive driving behaviors).
Eluru
Naveen
N
The University of Texas at Austin, Department of Civil, Architectural & Environmental Engineering, 1 University Station C1761, Austin, TX 78712-0278, United States. naveeneluru@mail.utexas.edu
Bhat
Chandra R
CR
D000063:Accidents, Traffic / Q000517:prevention & control / Q000706:statistics & numerical data*; D000328:Adult; D000367:Age Factors; D000368:Aged; D015982:Bias; D005260:Female; D006801:Humans; D015601:Injury Severity Score; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D015233:Models, Statistical; D009010:Monte Carlo Method; D016017:Odds Ratio; D012622:Seat Belts / Q000706:statistics & numerical data*; D012737:Sex Factors; D013223:Statistics as Topic; D014600:Utilization Review / Q000706:statistics & numerical data; D014947:Wounds and Injuries / Q000145:classification / Q000453:epidemiology*