01055809

Component

Using structural equation modeling, this study empirically examines the causal 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, California. 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 show that job accessibility has a negative effect on autos per capita, autos per capita has a positive effect on workers per capita and income per capita, workers per capita has a positive effect on income per capita and autos per capita, and education attainment has a positive effect on workers per capita, income per capita and autos per capita. Job accessibility has a negative total effect on workers per capita, income per capita and autos per capita. These results are largely consistent with theory and/or with empirical observations across a variety of geographic contexts. They suggest that structural equation modeling is a powerful tool for capturing the endogeneity among job accessibility, employment, income and auto ownership, and has other advantages over linear regression in this context.

01042056

07-1027

English

41p

2007

Transportation Research Board 86th Annual Meeting

CD-ROM

Appendices (1) ; Figures (2) ; References (32) ; Tables (11)

Accessibility; Automobile ownership; Employment; Income; Industrial location; Land use planning; Regression analysis; Residential location; Spatial analysis; Structural equation modeling; Transportation policy; Travel demand

Sacramento County (California)

Data and Information Technology; Highways; Planning and Forecasting; Policy; I21: Planning of Transport Infrastructure

Transportation Research Board Annual Meeting 2007 Paper #07-1027

BTRIS, TRIS, TRB

Feb 8 2007 5:37PM