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Citation |
Anwaar A, Anastasopoulos PC, Ong GP, Labi S, Islam MB. J. Transp. Saf. Secur. 2012; 4(2): 94-115. |
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Copyright |
(Copyright © 2012, Southeastern Transportation Center, and Beijing Jiaotong University, Publisher Informa - Taylor and Francis Group) |
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DOI |
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PMID |
unavailable |
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Abstract |
This paper uses aggregate data from the World Health Organization (WHO) and the International Road Federation (IRF) to identify the relationship between aggregate levels of road traffic safety, health service levels, motorization level, and associated factors. Two alternative modeling specifications are used to estimate the national fatality rate, number of hospital beds, and the number of registered vehicles per capita. The first specification is a system of seemingly unrelated regression equations (SURE) while the second is a set of regression models. The results suggest that a number of socio-economic explanatory factors, government laws and policies and their enforcement levels, and traffic and geographic characteristics, are significantly related to the three response variables. The paper shows that the SURE model is statistically superior to the separately-estimated regression models. The model findings are exploratory, but can still offer preliminary insights to planners to identify the extent to which traffic and motorization levels, regional and geographic characteristics, and most importantly, existing traffic laws and policies can influence traffic fatalities. |