ABSTRACT
INTRODUCTION: We develop a methodology to use FARS data as an alternative to NOPUS in estimating seat belt usage. The advantages of using FARS over NOPUS are that (i) FARS is broader because it contains more variables relevant for policy analysis, (ii) FARS allows for easy multivariate regression analysis, and finally, (iii) FARS data is more cost-effective. METHODOLOGY: We apply a binary logit model in our analysis to determine the likelihood of seat belt usage given various occupant, vehicle, and built environment characteristics. Using FARS data, we derive coefficient estimates for categories such as vehicle occupants' age and night time seat belt use that observational surveys like NOPUS cannot easily provide. RESULTS: Our results indicate that policies should focus on passengers (as opposed to drivers), male and young vehicle occupants, and that law enforcement should focus on pick-up trucks, rural roads, and nights. We find evidence that primary seat belt laws are effective. CONCLUSIONS: Although this is primarily a methodological paper, we present and discuss our results in the context of public policy so that our findings are relevant for road safety practitioners, researchers, and policymakers.
Subject(s)
Automobile Driving/legislation & jurisprudence , Law Enforcement , Motor Vehicles , Public Policy , Risk-Taking , Safety/legislation & jurisprudence , Seat Belts/statistics & numerical data , Adolescent , Adult , Aged , Cost-Benefit Analysis , Environment , Female , Humans , Male , Multivariate Analysis , Probability , Regression Analysis , Seat Belts/legislation & jurisprudence , Surveys and Questionnaires , Young AdultABSTRACT
This paper aims to account for important factors influencing bicycle use and focuses in particular on differences between 20 selected German municipalities with considerable variation in their bicycle mode share. Using data from the nation-wide survey Mobility in Germany 2002, a mode choice model for bicycling is developed. In an extension to previous research, social network or spillover effects as a measure of the city's bicycling culture are also taken into account. These effects are modelled using an instrumental variable approach. It is shown that social network effects increase the probability of cycling for shopping and recreational trip purposes, but not for school, work or errands. Furthermore, it is found that cycling infrastructure matters only for shopping and errand trips. Finally, commuting trips by bicycle seem to be largely independent of any policy variables.
Subject(s)
Bicycling , Interpersonal Relations , Physical Fitness , Social Support , Urban Health , Bicycling/education , Bicycling/history , Bicycling/physiology , Bicycling/psychology , Environment , Germany/ethnology , History, 21st Century , Interpersonal Relations/history , Physical Fitness/history , Physical Fitness/physiology , Physical Fitness/psychology , Transportation/history , Urban Health/history , Urban Population/historyABSTRACT
INTRODUCTION: In this paper, we show that FARS data can be a comparable alternative to observational NOPUS data in estimating seat belt use in the United States once we correct for sample selection bias. RESULTS: Based on assumptions of independence for seatbelt choice, we establish a lower and upper bound for seatbelt usage rates, and find that once we correct for sample selection bias, the seatbelt usage estimates from the corrected FARS emerge at least as a comparable alternative to NOPUS estimates. IMPACT ON INDUSTRY: This implies that researchers can use corrected FARS to complement NOPUS, thus being able to utilize the rich cross-sectional details available in FARS data to analyze various relevant research questions.
