Addressing the joint occurrence of self-selection and simultaneity biases in the estimation of program effects based on cross-sectional observational surveys: case study of travel behavior effects in carsharing

We estimate the effect of carsharing on travel behavior (specifically, household vehicle holdings, frequency of transit usage, and frequency of biking and walking) using data from the 2011–2012 California Household Travel Survey (CHTS). The effect of carsharing on vehicle ownership is a dynamic process that plays out over a period of time—past ownership influences enrollment decisions, which in turn influence holdings in a later period. Representing this process using cross-sectional data conflates causal effects with simultaneity bias. Further, members and non-members differ in various observed and unobserved ways—demographics, built environment of residential and workplace location, and attitudes—raising the potential for self-selection bias in comparing travel behavior between the two groups given the observational nature of the data. Drawing on established methods for dealing with each bias individually, we develop a method to help control for this joint occurrence of self-selection and simultaneity biases. Restricting the analysis to employed respondents residing in the San Francisco Bay Area, we find that 80% of the observed difference of 0.9 units in average vehicle holdings between carsharing non-members and members may be explained by the biases listed above. The remaining difference of 0.17 units reflects the estimated effect of carsharing, which is the equivalent of shedding one vehicle by about one out of every six households whose member(s) are enrolled in carsharing. The effect on transit usage and walking and biking frequency is positive, albeit small and statistically non-significant. We identify factors that may affect the internal and external validity of our results. Our methods cannot completely replace randomized experiments or panel data. However, the methods used here provide a way to help control for the joint occurrence of self-selection and simultaneity biases, and provide a ballpark estimate of causal effects, for large-scale, general-purpose, cross-sectional datasets such as the CHTS.

• Record URL:
  https://doi.org/10.1007/s11116-017-9791-1
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00494488
• Supplemental Notes:
  • Copyright © 2019, Springer Science+Business Media New York. The contents of this paper reflect the views of the authors and do not necessarily reflect the official views or policies of the Transportation Research Board or the National Academy of Sciences.
• Authors:
  • Mishra, Gouri
  • 0000-0002-8949-9316
  • Mokhtarian, Patricia L
  • Clewlow, Regina R
  • Widaman, Keith F
• Publication Date: 2019-2

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 95-123
• Serial:
  • Transportation
  • Volume: 46
  • Issue Number: 1
  • Publisher: Springer
  • ISSN: 0049-4488
  • EISSN: 1572-9435
  • Serial URL: http://link.springer.com/journal/11116

Subject/Index Terms

• TRT Terms: Automobile ownership; Bicycling; Case studies; Mode choice; Ownership; Public transit; Travel behavior; Travel surveys; Vehicle sharing; Walking
• Identifier Terms: California Household Travel Survey
• Uncontrolled Terms: Program evaluation; Self-selection; Simultaneity
• Geographic Terms: San Francisco Bay Area
• Subject Areas: Highways; Pedestrians and Bicyclists; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01706591
• Record Type: Publication
• Files: TRIS
• Created Date: May 28 2019 4:54PM