Background: Access to quality public transportation is critical for employment, especially for low-income and minority populations. This research contributes to previous work on equity analysis of the U.S. public transportation system by covering the 45 largest Metropolitan Statistical Areas (MSAs) and their counties.
Objective: This study analyzes job accessibility of transit commuters in the 45 largest MSAs to assess the existing differences in accessibility between Census-defined socioeconomic status (SES) categories.
Method: 2014 Census demographic data were matched to a previously published 2014 dataset of transit job accessibility at the Census Block Group level. Transit equality and justice analyses were performed based on population-weighted mean job accessibility and SES variables.
Results: The findings suggest that within individual MSAs, the low-income populations and people of color have the highest transit job accessibility. However, in certain MSAs with high job accessibility, such as New York, Washington, D.C., Chicago, and Houston, there is a significantly disproportionate access to public transportation based on income. Variables such as income, and the use of personal vehicle, are found to have a statistically significant negative impact on job accessibility in almost all MSAs. The percentage of White workers has a significant impact on job accessibility in upper-mid-density MSAs and high-density MSAs. The percentage of the population with limited English speaking ability is not a significant determinant of job accessibility except in lower-mid-density MSAs. Disparities by income are greater than disparities by race. Racial disparities increase by MSA size and density controlling for income. The findings suggest that planning for public transportation should take into account risks, benefits, and other equally important aspects of public transportation such as frequency, connectivity, and quality of service. / Master of Urban and Regional Planning / In recent years, there has been a shift in focus from encouraging mobility to encouraging accessibility, along with the provision of more sustainable travel options (e.g., walking, cycling, public transport). Access to quality public transportation is critical for employment, especially for low-income and minority populations. This research contributes to previous work on equity analysis of the U.S. public transportation system by covering the 45 largest Metropolitan Statistical Areas (MSAs) and their counties. This study analyzes job accessibility of transit commuters to assess the existing differences in accessibility in terms of income, race, ability to speak English, etc. Transit equality and justice analyses were performed based on population-weighted mean job accessibility and SES variables. The findings suggest that within individual MSAs, the low-income populations and people of color have the highest transit job accessibility. However, in certain MSAs with high job accessibility, such as New York, Washington, D.C., Chicago, and Houston, there is a significantly disproportionate access to public transportation based on income. Variables such as income, and the use of personal vehicle, are found to have a statistically significant negative impact on job accessibility in almost all MSAs. The percentage of White workers has a significant impact on job accessibility in upper-mid-density MSAs and high-density MSAs. The percentage of the population with limited English speaking ability is not a significant determinant of job accessibility except in lower-mid-density MSAs. The findings suggest that planning for public transportation should take into account risks, benefits, and other equally important aspects of public transportation such as frequency, connectivity, and quality of service.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/84512 |
| Date | 09 May 2017 |
| Creators | Jeddi Yeganeh, Armin |
| Contributors | Public and International Affairs, Hankey, Steven C., Sanchez, Thomas W., Hall, Ralph P. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | Creative Commons Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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