Using propensity score matching technique to address self-selection in transit-oriented development (TOD) areas

Many studies have investigated the effects of transit-oriented development (TOD) on travel behavior, especially on transit ridership. However, most studies do not explicitly and effectively address the issue of residential self-selection in their analyses. The aim of this paper is to use cross-sectional data and propensity score matching (PSM) technique to quantify the contribution of residential self-selection to the analysis of mode choice in TOD areas across the metropolitan areas of Washington, D.C. and Baltimore, MD. The authors use PSM because it does not make substantive assumptions to the structure of the self-selection problem (e.g., explicit modeling of outcome and treatment). The results of PSM indicate that, even though the self-selection effect is considerable in the analysis of mode choice in TOD areas (about 7.65% in Washington, D.C. and 5.05% in Baltimore), living in TOD still has a significant impact on encouraging transit and other active modes of transportation.

[1]  R. Cervero Transit-Oriented Development's Ridership Bonus: A Product of Self-Selection and Public Policies , 2006 .

[2]  Arefeh A. Nasri,et al.  The analysis of transit-oriented development (TOD) in Washington, D.C. and Baltimore metropolitan areas , 2014 .

[3]  Xinyu Cao,et al.  The Influences of Light Rail Transit on Transit Use: An Exploration of Station Area Residents along the Hiawatha Line in Minneapolis , 2013 .

[4]  Subrat Mahapatra,et al.  Effects of Transit-Oriented Development on Trip Generation, Distribution, and Mode Share in Washington, D.C., and Baltimore, Maryland , 2014 .

[5]  D. Chatman Does TOD Need the T? , 2013 .

[6]  P. Calthorpe The Next American Metropolis: Ecology, Community, and the American Dream , 1993 .

[7]  Xinyu Cao,et al.  Examining the impacts of residential self-selection on travel behavior: A focus on methodologies , 2008 .

[8]  Xiao-shu Cao,et al.  The association between transit access and auto ownership: evidence from Guangzhou, China , 2016 .

[9]  J. Scheiner,et al.  Travel mode choice: affected by objective or subjective determinants? , 2007 .

[10]  P. Mokhtarian,et al.  Self-Selection in the Relationship between the Built Environment and Walking: Empirical Evidence from Northern California , 2006 .

[11]  Q. Shen,et al.  Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city , 2016 .

[12]  Myoung‐jae Lee Micro-Econometrics for Policy, Program, and Treatment Effects , 2005 .

[13]  D. Rubin,et al.  The central role of the propensity score in observational studies for causal effects , 1983 .

[14]  Lorenzo Moreno,et al.  Propensity Score Matching , 2008 .

[15]  Patricia L. Mokhtarian,et al.  Viewpoint: Quantifying residential self-selection effects: A review of methods and findings from applications of propensity score and sample selection approaches , 2016 .

[16]  Steven Spears,et al.  Changes in Transit Use and Service and Associated Changes in Driving Near a New Light Rail Transit Line , 2015 .

[17]  Mark R. Stevens,et al.  Does Compact Development Make People Drive Less? , 2017 .

[18]  Kelly J. Clifton,et al.  Evaluating neighborhood accessibility: possibilities and practicalities , 2001 .

[19]  H. Lund Reasons for Living in a Transit-Oriented Development, and Associated Transit Use , 2006 .

[20]  Xinyu Cao,et al.  Exploring Causal Effects of Neighborhood Type on Walking Behavior Using Stratification on the Propensity Score , 2010 .

[21]  R. Cervero,et al.  Effects of TOD on Housing, Parking, and Travel , 2008 .

[22]  Reid Ewing,et al.  Travel and the Built Environment: A Synthesis , 2001 .

[23]  Susan L Handy,et al.  The Influences of the Built Environment and Residential Self-Selection on Pedestrian Behavior: Evidence from Austin, TX , 2005 .

[24]  Yingling Fan,et al.  Exploring the Influences of Density on Travel Behavior Using Propensity Score Matching , 2012 .

[25]  Mariela Alfonzo,et al.  Evaluation of the California Safe Routes to School legislation: urban form changes and children's active transportation to school. , 2005, American journal of preventive medicine.

[26]  G. Ridgeway,et al.  Neighborhood design and walking trips in ten U.S. metropolitan areas. , 2007, American journal of preventive medicine.

[27]  Reid Ewing,et al.  Travel and the Built Environment , 2010 .

[28]  Yingling Fan,et al.  Exploring the connections among residential location, self-selection, and driving: Propensity score matching with multiple treatments , 2010 .

[29]  Xinyu Cao,et al.  Examining the Impacts of Residential Self‐Selection on Travel Behaviour: A Focus on Empirical Findings , 2009 .

[30]  Kamruzzaman,et al.  Investigating the Link between Transit Oriented Development and Sustainable Travel Behavior in Brisbane: A Case-Control Study , 2014 .

[31]  D. Chatman Estimating the effect of land use and transportation planning on travel patterns: Three problems in controlling for residential self-selection , 2014 .

[32]  Mohan M. Venigalla,et al.  Measuring Travel Behavior and Transit Trip Generation Characteristics of Transit-Oriented Developments , 2013 .

[33]  H. Meurs,et al.  Spatial structure and mobility , 2001 .

[34]  Chandra R. Bhat,et al.  A Comprehensive Analysis of Built Environment Characteristics on Household Residential Choice and Auto Ownership Levels , 2007 .

[35]  D. Chatman Deconstructing development density: Quality, quantity and price effects on household non-work travel , 2008 .

[36]  Kiyoshi Takami,et al.  Connection between Built Environment and Travel Behavior , 2014 .

[37]  Xinyu Cao,et al.  Impacts of the Built Environment and Residential Self-Selection on Nonwork Travel: Seemingly Unrelated Regression Approach , 2006 .

[38]  Ming Zhang Can Transit-Oriented Development Reduce Peak-Hour Congestion? , 2010 .

[39]  Petter Næss Tempest in a teapot: The exaggerated problem of transport-related residential self-selection as a source of error in empirical studies , 2014 .

[40]  Arefeh A. Nasri,et al.  How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in US cities , 2012 .

[41]  Michael N. Bagley,et al.  The impact of residential neighborhood type on travel behavior: A structural equations modeling approach , 2001 .

[42]  Susan L Handy,et al.  Correlation or causality between the built environment and travel behavior? Evidence from Northern California , 2005 .

[43]  Peter C Austin,et al.  A comparison of 12 algorithms for matching on the propensity score , 2013, Statistics in medicine.

[44]  Christopher E. Ferrell,et al.  TRANSIT-ORIENTED DEVELOPMENT IN THE UNITED STATES: EXPERIENCES, CHALLENGES, AND PROSPECTS , 2004 .

[45]  Daniel G. Chatman,et al.  How the built environment influences non-work travel : theoretical and empirical essays , 2005 .

[46]  Robert Cervero,et al.  TRANSIT-BASED HOUSING IN CALIFORNIA: EVIDENCE ON RIDERSHIP IMPACTS , 1994 .