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Residential Self Selection and Rail Commuting: A Nested Logit Analysis

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  • Cervero, Robert
  • Duncan, Michael

Abstract

Past studies show that those living near train stations tend to rail-commute far more often than the typical resident of rail-served cities. Some contend this is largely due to selfselection, marked by those with an affinity to transit riding consciously moving into neighborhoods that are well-served by transit. This article explores the self-selection question by constructing a nested logit model that jointly estimates the probability someone will reside near a rail stop and in turn commute by rail transit, using year-2000 travel data from the San Francisco Bay Area. A multinomial logit model is also used to predict car ownership levels. The research reveals that residential location and commute choice are jointly related decisions among station-area residents. A comparison of odds ratios among those living near and away from transit, controlling for the influences of other factors, suggests that residential self-selection accounts for approximately 40 percent of the rail-commute decision. These findings suggest that supportive zoning should be introduced and barriers to residential mobility should be eliminated to allow the self-selection process to occur naturally through the marketplace.

Suggested Citation

  • Cervero, Robert & Duncan, Michael, 2008. "Residential Self Selection and Rail Commuting: A Nested Logit Analysis," University of California Transportation Center, Working Papers qt72p9n6qt, University of California Transportation Center.
    • Handle: RePEc:cdl:uctcwp:qt72p9n6qt
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    References listed on IDEAS

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    1. Cervero, Robert, 1993. "Ridership Impacts of Transit-Focused Development in California," University of California Transportation Center, Working Papers qt8sr9d86r, University of California Transportation Center.
    2. John Holtzclaw & Robert Clear & Hank Dittmar & David Goldstein & Peter Haas, 2002. "Location Efficiency: Neighborhood and Socio-Economic Characteristics Determine Auto Ownership and Use - Studies in Chicago, Los Angeles and San Francisco," Transportation Planning and Technology, Taylor & Francis Journals, vol. 25(1), pages 1-27, January.
    3. Hensher, David A. & Greene, William H., 2002. "Specification and estimation of the nested logit model: alternative normalisations," Transportation Research Part B: Methodological, Elsevier, vol. 36(1), pages 1-17, January.
    4. Cervero, Robert, 1994. "Transit-based housing in California: evidence on ridership impacts," Transport Policy, Elsevier, vol. 1(3), pages 174-183, June.
    5. Richard Voith, 1991. "Transportation, Sorting and House Values," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 19(2), pages 117-137, June.
    6. Boarnet, Marlon G. & Crane, Randall, 1995. "Public Finance and Transit-Oriented Planning: New Evidence from Southern California," University of California Transportation Center, Working Papers qt4v95x0tm, University of California Transportation Center.
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    Cited by:

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    2. Circella, Giovanni & Alemi, Farzad & Tiedeman, Kate & Handy, Susan & Mokhtarian, Patricia, 2018. "The Adoption of Shared Mobility in California and Its Relationship with Other Components of Travel Behavior," Institute of Transportation Studies, Working Paper Series qt1kq5d07p, Institute of Transportation Studies, UC Davis.
    3. Md. Kamruzzaman & Simon Washington & Douglas Baker & Wendy Brown & Billie Giles-Corti & Gavin Turrell, 2016. "Built environment impacts on walking for transport in Brisbane, Australia," Transportation, Springer, vol. 43(1), pages 53-77, January.
    4. Zhao, Pengjun & Zhang, Yixue, 2018. "Travel behaviour and life course: Examining changes in car use after residential relocation in Beijing," Journal of Transport Geography, Elsevier, vol. 73(C), pages 41-53.
    5. Guang Li & Paat Rusmevichientong & Huseyin Topaloglu, 2015. "The d -Level Nested Logit Model: Assortment and Price Optimization Problems," Operations Research, INFORMS, vol. 63(2), pages 325-342, April.
    6. Renne, John L. & Hamidi, Shima & Ewing, Reid, 2016. "Transit commuting, the network accessibility effect, and the built environment in station areas across the United States," Research in Transportation Economics, Elsevier, vol. 60(C), pages 35-43.
    7. Md. Kamruzzaman & Simon Washington & Douglas Baker & Wendy Brown & Billie Giles-Corti & Gavin Turrell, 2016. "Built environment impacts on walking for transport in Brisbane, Australia," Transportation, Springer, vol. 43(1), pages 53-77, January.

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