Road Fatalities, Health Service Quality, and Motorization Level: Empirical Analysis Using Aggregate Country-Level Data
Crash causes, Demographics, Fatalities, Geography, Highway safety, Mathematical models, Policy making, Regression analysis, Safety, Socioeconomic factors, Traffic characteristics, Traffic law enforcement, Traffic volume
This paper uses aggregate data from the World Health Organization (WHO) and International Road Federation (IRF) to identify the relationship between road traffic safety, health service levels, motorization level, and associated factors. To do this, two alternative modeling specifications are used: a system of seemingly unrelated regression equations (SURE) to model the fatality rate, the number of hospital beds and registered vehicles per capita, and separately estimated regression models for the fatality rate, the number of hospital beds and registered vehicles per capita. The results suggest that a number of socio-economic factors, government laws and policies and their enforcement level, and traffic and geographic characteristics, are significantly related to the three response variables. The paper shows, using appropriate statistical tests, that the SURE model is statistically superior to the separately estimated regression models. The model findings are exploratory, but can be helpful to road and safety agencies who, for policy-making purposes, seek to identify the extent to which traffic and motorization levels, regional geographic characteristics, and most importantly, existing traffic laws and policies influence traffic fatalities.
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Citation / Publisher Attribution
Presented at the Transportation Research Board 90th Annual Meeting on January, 2011 in Washington, D.C.
Scholar Commons Citation
Ahmed, Anwaar; Anastasopoulos, Panagiotis; Islam, Mouyid B.; and Labi, Samuel, "Road Fatalities, Health Service Quality, and Motorization Level: Empirical Analysis Using Aggregate Country-Level Data" (2011). CUTR Faculty and Staff Publications. 97.