Viewpoint: Quantifying residential self-selection effects: A review of methods and findings from applications of propensity score and sample selection approaches


  • Patricia L. Mokhtarian Georgia Institute of Technology
  • David van Herick University of California, Davis



transport, land use, residential self-selection


The phenomenon whereby individuals self-select into their residential environment based on previously determined preferences for how to travel is known as residential self-selection (RSS). Numerous studies have investigated the influence of RSS on the estimated effect of the built environment on travel behavior. However, surprisingly few have actually quantified its effect in terms of partitioning the total influence of the built environment (BE) on travel behavior into a component attributable to RSS and one attributable to the built environment itself. This paper reviews 10 analyses (found in seven studies) that have quantified the proportion of the total influence of the built environment that is due to the BE itself (which we call the BEP), using either propensity-score or sample-selection approaches to control for RSS. After first outlining the basics of each approach, we then explain the various methods used to compute the BEP, followed by a discussion of the empirical results. The estimated BEPs vary widely, ranging from 34 percent to 98 percent. A number of reasons for these disparities are suggested, but there is considerable divergence in estimates even when many of these factors are held constant. Additional research is called for to better understand the circumstances under which the BEP is higher or lower.

Author Biographies

Patricia L. Mokhtarian, Georgia Institute of Technology

Professor, School of Civil and Environmental Engineering

David van Herick, University of California, Davis

PhD candidate, Department of Civil and Environmental Engineering


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How to Cite

Mokhtarian, P. L., & van Herick, D. (2016). Viewpoint: Quantifying residential self-selection effects: A review of methods and findings from applications of propensity score and sample selection approaches. Journal of Transport and Land Use, 9(1).