Examining the Impacts of Residential Self-selection on Travel Behavior: Methodologies and Empirical Findings

Principal Investigator:

Jason Cao, Assistant Professor , Humphrey School of Public Affairs

Project Summary:

Numerous studies have found that suburban residents drive more and walk less than residents in traditional neighborhoods. What is less well understood is the extent to which the observed patterns of travel behavior can be attributed to the residential built environment itself, as opposed to the prior self-selection of residents into a built environment that is consistent with their predispositions toward certain travel modes and land use configurations. To date, most studies addressing this attitudinal self-selection issue fall into nine categories: direct questioning, statistical control, instrumental variables models, sample selection models, propensity score, joint discrete choice models, structural equations models, mutually-dependent discrete choice models, and longitudinal designs. This project reviewed and evaluated these alternative approaches. Virtually all of the 38 empirical studies reviewed found a statistically significant influence of the built environment remaining after self-selection was accounted for. However, the practical importance of that influence was seldom assessed. Although time and resource limitations are recognized, the research team recommend usage of longitudinal structural equations modeling with control groups, a design which is strong with respect to all causality requisites.

Project Details: