We estimate how motorists value their time savings and characterize the degree of heterogeneity in these values by observable traits. We obtain these estimates by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested...

This paper explores the impact of residential density on households’ vehicle type and usage choices using the 2001 National Household Travel Survey (NHTS). Attempts to quantify the effect of urban form on households’ vehicle choice and utilization often encounter the problem of...

Modern panel surveys frequently suffer from high and likely non-ignorable attrition, and transportation surveys suffer from poor travel time estimates. This paper examines new methods for adjusting forecasts and model estimates to account for these problems. The methods we describe are...

This paper reports results from evaluations of two recent road pricing demonstrations in Southern California. These demonstration projects provide particularly useful opportunities for measuring commuters’ values of time and reliability. Unlike most revealed preference studies of value of...

Rubin (1987) has proposed multiple imputations as a general method for estimation in the presence of missing data. Rubin’s results only strictly apply to Bayesian models, but Schenker and Welsh (1988) directly prove the consistency  multiple imputations inference~ when there are...

We estimate how motorists value their time savings and characterize the degree of heterogeneity in these values by observable traits. We obtain these estimates by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to...

The vehicle choice model developed here is one component in a micro-simulation demand forecasting system being designed to produce annual forecasts of new and used vehicle demand by vehicle type and geographic area in California. The system will also forecast annual vehicle miles traveled for...

This chapter demonstrates a new methodology for correcting panel data models for attrition bias. The method combines Rubin's Multiple Imputations technique with Manski and Lerman's Weighted Exogenous Sample Maximum Likelihood Estimator (WESMLE). Simple Hausman tests for the presence of attrition...

Recent survey validation studies suggest that measurement error in earnings data is pervasive and violates classical measurement error assumptions, and therefore may bias estimation of cross-section and longitudinal earnings models. We model the structure of earnins measurements error using data...

Recent survey validation studies suggest that measurement error in earnings data is pervasive and violates classical measurement error assumptions, and therefore may bias estimation of cross-section and longitudinal earnings models. We model the structure of earnings measurement error using data...