Peter D. Loeb

International travel to the United States: An econometric evaluation

Abstract This paper investigates the effects of real per capita income, exchange rates, and relative prices on the exports of travel services from the United States to seven foreign countries. In addition, the study evaluates the effects of real income, exchange rates, and relative prices on the total level of U.S. receipts from foreign travel. The analysis is conducted via regression techniques.

Cognitive dissonance and utility maximization: A general framework☆

Abstract Neoclassical theory of utility maximization assumes irrational behavior to be unsystematic and therefore impossible to model. Recent advances in behavioral decision theory suggests irrationality may be systematic. In line with these and earlier findings from the theory of cognitive dissonance, a simple descriptive model of utility maximization is developed with the added feature of an information filter. The model is then used to explain a few ‘irrational’ micro and macro behaviors.

The effectiveness of seat belt legislation in reducing various driver-involved injury rates in California.

This study makes use of econometric models to examine the impact of seat belt laws on various driver-involved injury rates in California in both single- and multiple-vehicle accidents. The study makes use of a large data set from the U.S. D.O.T. State Traffic Accident Files and accounts for the general impact of seat belt laws as well as their dynamic effects on injury rates. The models adjust for a wide range of additional contributing factors to injury rates, including the influence of unemployment rates, speed limits, companion effects, and others. Robust results are obtained for the efficacy of seat belt legislation on reducing (moderate to fatal) injury rates in California.

THE EFFECTIVENESS OF SEAT BELT LEGISLATION IN REDUCING DRIVER-INVOLVED INJURY RATES IN MARYLAND

Abstract This study makes use of econometric models to evaluate the effect of the Maryland seat belt law (SBL) on various driver-involved injury rates. Models are developed for various types of injuries using a large data set from the US Department of Transportations State Traffic Accident Files. Models are normalized for vehicle damage levels and account for the general impact of the SBL in Maryland as well as its dynamic effects. The models also account for seasonal factors, unemployment rates, companion effects and other relevant factors. The analysis is conducted for single vehicle accidents, multiple vehicle accidents, as well as their combination. The results indicate that the effectiveness of Marylands SBL vary depending on the type of injury rates examined.

Research and Development in the Pharmaceutical Industry-A Specification Error Approach

IN recent years, much economic research has been devoted to the investigation of the determinants of Research and Development (R & D) and to the testing of the Schumpeterian hypothesis that R & D is related to firm size.* This study investigates the relationship between R & D and size in the pharmaceutical industry. Unlike many other studies in the literature, this investigation is based on time series data, covering the period 1961 through 1972. Four well-̂ known models are tested using classical linear regression analysis as the estimation technique. The models are variations of:

The impact of cell phones on motor vehicle fatalities

This article 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 article 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 nonmonotonic 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.

International travel to the United States

Abstract This paper investigates the effects of real per capita income, exchange rates, and relative prices on the exports of travel services from the United States to seven foreign countries. In addition, the study evaluates the effects of real income, exchange rates, and relative prices on the total level of U.S. receipts from foreign travel. The analysis is conducted via regression techniques.

Understanding the cell phone effect on vehicle fatalities: a Bayesian view

This article examines the potential effect of various factors on motor vehicle fatality rates using a rich set of panel data and classical regression analysis combined with Bayesian Extreme Bounds Analysis (EBA), Bayesian Model Averaging (BMA) and Stochastic Search Variable Selection (SSVS) procedures. The variables examined in the models include traditional motor vehicle and socioeconomic factors. In addition, the models address the effects of cell phone usage on such accidents. The use of both classical and Bayesian techniques diminish the model and parameter uncertainties which afflict more conventional modelling methods which rely on only one of the two methods.

Sturdy inference and the amelioration potential for driverless cars: The reduction of motor vehicle fatalities due to technology

Abstract Motor vehicle crashes continue to result in a large number of fatalities each year and represent the leading cause of death for young persons. This study is the first to examine specifically the effects of a set of focus variables thought to be major contributors to motor vehicle fatalities including distractions caused by, for example, cell phones, suicidal propensities among others using a newly developed Bayesian technique designed to measure the \sturdiness of the results. The analysis is conducted using a rich panel data set for the period 1980–2010 by the State and the District of Columbia which includes motor vehicle, economic, and driver-related variables. As mentioned, the analysis makes use of a new Bayesian statistic developed by Leamer, that is, S-values. This statistic summarizes both estimation uncertainty and model ambiguity by considering millions of potential models of motor vehicle fatalities. Once the major factors of motor vehicle fatalities are unambiguously determined and their influences measured, the study considers the ameliorating potential of driverless cars on such fatalities as well as their costs to society. In particular, the ability of driverless cars with, for example, their self-braking capacity, to reduce the number of crashes, and their associated fatalities and injuries in a significant manner is examined. In addition, they may offer individuals the ability to use cell phones for calls and texting while not enhancing risks to vehicle occupants and pedestrians. Obviously, they may also serve in place of a designated driver should alcohol use be an issue. However, the ability of driverless vehicles to provide safe transportation is not without costs. These include developing and maintaining reliable computer systems and sensors along with back-up systems while addressing legal and possible environmental issues. We conclude that driverless cars offer the potential to ameliorate motor vehicle fatalities due to distractions, such as with the use of cell phones, alcohol use, and suicidal propensities. In addition, modernization of the vehicle fleet is expected to reduce motor vehicle fatalities since newer vehicles are expected to incorporate technologies which may be life saving.

The comparative performance of the iterative instrumental variables estimator using structural and predictive criteria

The purpose of this paper is to give experimental evidence on the small-sample properties of the iterative instrumental variables estimator originally proposed byLyttkens [1970], relative to the more conventional methods including ordinary least squares, limited information single equation maximum likelihood and three stage least squares.