Self-selection in Home Choice: Use of Treatment Effects in Evaluating the Relationship between the Built Environment and Travel Behavior

The issue of self-selection’s role in shaping travel patterns, by impacting one’s home location choice, is a critical question. Developers, planners and policymakers regularly debate to what extent the built environment and land use patterns can alleviate roadway congestion, greenhouse gas emissions and myriad other urban problems. This study illustrates the use of Heckman’s (1976, 1979) latent index model to ascertain travel impacts of neighborhood type in Austin, Texas. Under this approach, self-selection is formulated as sample selection bias in receiving a treatment. Here, treatment is defined to be one’s residence in a suburban or rural zone, rather than Austin’s central business district and nearby urban zones. This treatment/no-treatment approach is a meaningful advance in models of self-selection effects, and requires estimation of three straightforward models. Model results suggest that the great majority (90%) of differences in vehicle-miles-traveled between central/CBD and suburban/rural locations is due to the treatment itself, rather than self-selection of such treatment (by households that wish to meet special travel needs).