A Joint Flexible Econometric Model System of Household Residential Location and Vehicle Fleet Composition/Usage Choices
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Modeling the interaction between the built environment and travel behavior is of much interest totransportation planning professionals due to the desire to curb vehicular travel demand throughmodifications to built environment attributes. However, such models need to take into accountself-selection effects in residential location choice, wherein households choose to reside inneighborhoods and built environments that are conducive to their lifestyle preferences andattitudes. This phenomenon, well-recognized in the literature, calls for the specification andestimation of joint models of multi-dimensional land use and travel choice processes. However,the estimation of such model systems that explicitly account for the presence of unobservedfactors that jointly impact multiple choice dimensions is extremely complex and computationallyintensive. This paper presents a joint GEV-based logit regression model of residential locationchoice, vehicle count by type choice, and vehicle usage (vehicle miles of travel) using a copulabased framework that facilitates the estimation of joint equations systems with error dependencestructures within a simple and flexible closed-form analytic framework. The model system isestimated on a sample derived from the 2000 San Francisco Bay Area Household Travel Survey.Estimation results show that there is significant dependency among the choice dimensions andthat self-selection effects cannot be ignored when modeling land use-travel behavior interactions.
At the time of publication N. Eluru, and C.R. Bhat were at the University of Texas at Austin; and R.M. Pendyala and K.C. Konduri were at Arizona State University.