The number of cars in a household has an important effect on its travel behavior (e.g., choice of number of trips, mode to work and non-work destinations), hence car ownership modeling is an essential component of any travel demand forecasting effort. In this paper we report on a random effects multinomial probit model of car ownership level, estimated using longitudinal data collected in the Netherlands. A Bayesian approach is taken and the model is estimated by means of a modification of the Gibbs sampling with data augmentation algorithm considered by McCulloch and Rossi (1994). The modification consists in performing, after each Gibbs sampling cycle, a Metropolis step along a direction of constant likelihood. An examination of the simulation output illustrates the improved performance of the resulting sampler.

}, keywords = {car ownership, longitudinal data, Multinomial probit model}, isbn = {978-0-387-94990-1}, doi = {10.1007/978-1-4612-2290-3_13}, url = {http://dx.doi.org/10.1007/978-1-4612-2290-3_13}, author = {Nobile, Agostino and Bhat, Chandra R. and Pas, Eric I.}, editor = {Gatsonis, Constantine and Hodges, JamesS. and Kass, RobertE. and McCulloch, Robert and Rossi, Peter and Singpurwalla, NozerD.} }