Abstract
This paper examines the access that neighborhoods have to jobs via public transit, if it varies by race/ethnicity, and what difference it makes in terms of socioeconomic outcomes. Decades of research has argued that important sites of employment are often not located in or are inaccessible to racial/ethnic minority neighborhoods. Here, we examine this proposition and take into account how public transit may play into this process. On the one hand, public transit as a public good may have the power to overcome the liabilities of place. If we can build transportation systems that give all neighborhoods comparable access to jobs, part of the spatial mismatch problem may be corrected. On the other hand, if public transit is built in such a way that certain racial/ethnic groups are benefiting, but not others, access alone is not enough to achieve parity. Using the 2013–2017 American Community Survey and the 2017 Access Across America Transit study, we examine how neighborhood racial/ethnic composition is related to job accessibility and socioeconomic outcomes at the block group level for 49 of the 50 largest metropolitan areas in the United States. We find that Black and Latino neighborhoods have access to fewer jobs via public transit, and that they also have lower median household income and a higher unemployment rate, net of access to jobs. Access to more jobs via mass transit is related to higher incomes in White block group clusters, but has no impact on household incomes in Black and Latino clusters. This suggests that public transit as implemented serves to aggravate existing inequalities and is not currently acting as a policy tool to ameliorate inequality.
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Notes
National Association of City Transportation Officials. 2021. “Transit Street Design Guide: Key Principles.” https://nacto.org/publication/transit-street-design-guide/introduction/principles/.
We recognize that other time frames could be relevant to this analysis, and that it would be optimal to test other time frames as a robustness check for the analysis presented here. However, the 30 min interval was the only time frame at the block group level available from the Access Across America study. Further, from the ACS data at the metropolitan-level, the median commute time for all of the included metropolitan areas ranged from 21.2 to 34.6 suggesting that the 30 min time frame is reasonable.
Because both the average number of jobs and median household income are two positively skewed continuous variables, we also estimated all of these same models (in Tables 2 and 3) using multi-level gamma regression, as a check on this choice of modeling strategy. The results are virtually the same, with only minor differences in the effect sizes.
We also estimated all of the same models without the metropolitan variables included using a series of spatial error models. The conclusions from those results are essentially the same as those presented here with only minor differences in the size of coefficients across all models.
As a check on this choice, we also estimated the same set of models using different percentage sizes from the original sample, as well as multiple sample draws from the original data set. While we found some minor differences in the size of the effects across all models, the conclusions remain unchanged.
For the standardized coefficients discussed here, the coefficient in the table was multiplied by 1795.87 for Black clustering, 1366.47 for Latino clustering, and 2661.79 for White clustering.
We found the same pattern of relationships when using a threshold of 70% and 80% as well. However, using these higher thresholds substantially reduced the sample sizes, especially for the Latino model.
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Acknowledgements
The authors presented this paper at the annual meeting of the American Association of Geographers in 2020. The authors would like to thank Victoria Sisk for her help in finding some key citations for this manuscript.
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Anderson, K.F., Galaskiewicz, J. Racial/Ethnic Residential Segregation, Socioeconomic Inequality, and Job Accessibility by Public Transportation Networks in the United States. Spat Demogr 9, 341–373 (2021). https://doi.org/10.1007/s40980-021-00093-8
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DOI: https://doi.org/10.1007/s40980-021-00093-8