The Impact of Cell Phones and BAC Laws on Motor Vehicle Fatality Rates

This paper develops a set of models for the determinants of automobile fatalities with particular attention devoted to the effects of increased cell phone usage. Cell phones have been associated with both life-taking and life-saving properties. However, prior statistical evaluations of the effects of cell phones have led to fragile results. We develop in this paper econometric models using time series data, allowing for polynomial structures of the regressors. The models are evaluated with a set of specification error tests providing reliable estimates of the effects of the various policy and driving related variables evaluated. The statistical results indicate the effect of cell phones is non-monotonic depending on the volume of phones in use, first having a net life-taking effect, then a net life-saving effect, followed finally with a net life-taking effect as the volume of phone use increases.Motor Vehicle Fatalities, Cell Phones, BAC Laws

A Model Connecting Galaxy Masses, Star Formation Rates, and Dust Temperatures Across Cosmic Time

We investigate the evolution of dust content in galaxies from redshifts z=0 to z=9.5. Using empirically motivated prescriptions, we model galactic-scale properties -- including halo mass, stellar mass, star formation rate, gas mass, and metallicity -- to make predictions for the galactic evolution of dust mass and dust temperature in main sequence galaxies. Our simple analytic model, which predicts that galaxies in the early Universe had greater quantities of dust than their low-redshift counterparts, does a good job at reproducing observed trends between galaxy dust and stellar mass out to z~6. We find that for fixed galaxy stellar mass, the dust temperature increases from z=0 to z=6. Our model forecasts a population of low-mass, high-redshift galaxies with interstellar dust as hot as, or hotter than, their more massive counterparts; but this prediction needs to be constrained by observations. Finally, we make predictions for observing 1.1-mm flux density arising from interstellar dust emission with the Atacama Large Millimeter Array.Comment: Accepted for publication in Ap

Resolving Gamma-Ray Burst 000301C with a Gravitational Microlens

The afterglow of the Gamma-Ray Burst (GRB) 000301C exhibited achromatic, short time-scale variability that is difficult to reconcile with the standard relativistic shock model. We interpret the observed light curves as a microlensing event superimposed on power-law flux decays typical of afterglows. In general, a relativistic GRB shock appears on the sky as a thin ring expanding at a superluminal speed. Initially the ring is small relative to its angular separation from the lens and so its flux is magnified by a constant factor. As the ring grows and sweeps across the lens its magnification reaches a maximum. Subsequently, the flux gradually recovers its unlensed value. This behavior involves only three free parameters in its simplest formulation and was predicted theoretically by Loeb & Perna (1998). Fitting the available R-band photometric data of GRB 000301C to a simple model of the microlensing event and a broken power-law for the afterglow, we find reasonable values for all the parameters and a reduced chi^2/DOF parameter of 1.48 compared with 2.99 for the broken power-law fit alone. The peak magnification of ~2 occurred 3.8 days after the burst. The entire optical-IR data imply a width of the GRB ring of order 10% of its radius, similar to theoretical expectations. The angular resolution provided by microlensing is better than a micro-arcsecond. We infer a mass of approximately 0.5 M_Sun for a lens located half way to the source at z_s=2.04. A galaxy 2'' from GRB 000301C might be the host of the stellar lens, but current data provides only an upper-limit on its surface brightness at the GRB position.Comment: to appear in the ApJ Letters, 13 pages, 3 figures (one additional figure included); all data used for the fits available at ftp://cfa-ftp.harvard.edu/pub/kstanek/GRB000301C/ and through WWW at http://cfa-www.harvard.edu/cfa/oir/Research/GRB

Cell phone effect on motor vehicle fatality rates: a Bayesian and classical econometric evaluation

ManuscriptThis paper examines the potential effect of cell phones on motor vehicle fatality rates normalized for other driving related and socioeconomic factors. The model used is nonlinear so as to address both life-taking and life-saving attributes of cell phones. The model is evaluated using classical methods along with Bayesian Extreme Bounds Analysis (EBA). The use of both classical and Bayesian methods diminishes the model and parameter uncertainties which afflict more conventional modeling methods which rely on only one of the two methods. The results indicate the presence of both life-taking and life-saving attributes of cell phones on motor vehicle fatality rates depending on the volume of cell phone subscribers in existence

Sturdy Inference: A Bayesian Analysis of U.S. Motorcycle Helmet Laws

Motorcycle related fatalities continue to be a major concern for public health officials, economists, and policy makers interested in such matters. In 2006, 3% of all motor vehicles registered in the United States were 2-3 wheelers (motorcycle type vehicles), while riders of these vehicles accounted for 11% of vehicle related deaths. Such a disproportionate number of fatalities associated with motorcycles is certainly grounds for concern.Most studies of motorcycle fatalities attribute deaths to the avoidance of wearing helmets and the lack of helmet laws, speed, and alcohol usage. This study makes use of a rich panel data set for the period 1980 to 2010 by state and the District of Columbia to examine these factors and others. It is the first study to differentiate between the effects of universal and partial helmet laws on motorcycle fatalities. It also accounts for the effects of cell phone use, alcohol consumption, and suicidal propensities on these crashes after adjusting for a whole host of socioeconomic and driving related factors. The analysis is conducted using a new Bayesian technique, which examines the sturdiness of regression coefficients. This new method uses statistics referred to as S-values that addresses both estimation and model ambiguity. Results indicate that the variables we focus on, i.e., cell phones, alcohol consumption, and helmet laws affect motorcycle fatalities. Further, universal helmet laws appear to have a larger effect on such fatalities than partial helmet laws

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

Working PaperThis 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