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

Shengyi Gao, Patricia Mokhtarian and Robert A. Johnston

Institute of Transportation Studies, Working Paper Series from Institute of Transportation Studies, UC Davis

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.

Keywords: Engineering; UCD-ITS-RR-07-42 (search for similar items in EconPapers)
Date: 2007-09-01
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Exploring the connections among job accessibility, employment, income, and auto ownership using structural equation modeling (2008)
Working Paper: Exploring the connections among job accessibility, employment, income, and auto ownership using structural equation modeling (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:cdl:itsdav:qt30v177dx

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