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Exploring the connections among job accessibility, employment, income, and auto ownership using structural equation modeling

Author

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  • Gao, Shengyi
  • Mokhtarian, Patricia L
  • Johnston, Robert A.

Abstract

Using structural equation modeling, this study empirically examines the connections between job accessibility, workers per capita, income per capita, and autos per capita at the aggregate level with year 2000 census tract data in Sacramento County, CA. Under the specification of the conceptual model, the model implied covariance matrix exhibits a reasonably good fit to the observed covariance matrix. The direct and total effects are largely consistent with theory and/or with empirical observations across a variety of geographic contexts. It is demonstrated that structural equation modeling is a powerful tool for capturing the endogeneity among job accessibility, employment, income, and auto ownership.

Suggested Citation

  • Gao, Shengyi & Mokhtarian, Patricia L & Johnston, Robert A., 2007. "Exploring the connections among job accessibility, employment, income, and auto ownership using structural equation modeling," Institute of Transportation Studies, Working Paper Series qt30v177dx, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt30v177dx
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    Cited by:

    1. Sabreena Anowar & Naveen Eluru & Luis F. Miranda-Moreno, 2014. "Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review," Transport Reviews, Taylor & Francis Journals, vol. 34(4), pages 441-473, July.
    2. Jen-Jia Lin & Chi-Hau Chen & Tsung-Yu Hsieh, 2016. "Job accessibility and ethnic minority employment in urban and rural areas in Taiwan," Papers in Regional Science, Wiley Blackwell, vol. 95(2), pages 363-382, June.

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    Keywords

    Engineering; UCD-ITS-RR-07-42;

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