Determinants of motor vehicle fatalities using classical specification testing and Bayesian sensitivity methods

This paper uses classical regression methods along with Bayesian Extreme Bounds Analysis (EBA) to addresses the effect of cell phones on motor vehicle fatality rates so as to examine the potential of net life-taking and life-saving effects. The models adjust for a time trend (YEAR), the maximum blood alcohol concentration legislation (BAC) required for drunk driving arrests, annual inspection (ANNUAL), the maximum posted rural speed limit (SPEED_RU),a dummy variable indicating the presence of a seat belt law (BELT), per capita consumption of beer (BEER), the minimum legal drinking age (MLDA), the percentage of males aged 16-24 relative to the population of age 16 and over (YOUNG), and various measures of cell phone subscribers (CELL, CELLSQ, CELLCUBE). The measures of cell phones are allowed to enter the model in a nonlinear manner so as to examine the potential of non-monotonic effects of cell phones on motor vehicle fatality rates as suggested by Loeb et al. (forthcoming). The models are estimated using panel data for all fifty states and the District of Columbia for the years 1980 to 2004. The classical and Bayesian estimates correspond well with each other.