University of California Transportation Center
New Methods for Modeling and Estimating the Social Costs of Motor Vehicle Use
- Author(s): Steimetz, Seiji Sudhana Carl
- et al.
The body of this dissertation comprises two standalone essays, presented in two respective chapters.
Chapter One develops estimates of how motorists value their travel-time savings and characterizes the degree of heterogeneity in these values by observable traits. These estimates are obtained by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested travel. They are generated, however, in an empirical setting where several key observations are missing. To overcome this, Rubin’s Multiple Imputation Method is employed to produce consistent estimates and valid statistical inferences. These estimates are then compared to those produced in a “single imputation” scenario to illustrate the potential hazards of single imputation methods when multiple imputation methods are warranted. A preferred model suggests that the median commuter is willing to pay $30 to save an hour of travel time. However, taking observed heterogeneity into account, median estimates range from $7 to $65 according to varying, observable motorist characteristics.
Chapter Two develops a theoretical framework for jointly modeling the marginal external accident and travel-delay costs of driving. The framework explicitly accounts for the optimal tradeoffs that motorists make between accident risk and risk-reducing effort. Accident and travel-delay externalities are decomposed into components that correspond to physical accident risk, efforts to offset this risk, and their effects on travel times. An empirical model is developed from this framework, suggesting that joint external costs are $1.80 per vehicle-mile and external accident costs are $0.80 per vehicle-mile during a typical peak-period commute. The analysis does not require observations on accident rates and illustrates how the commonly-adopted approach to modeling accident externalities tends to understate these costs.