Low-Wage Workers & Commuting: The Social, Spatial, and Temporal Patterns of Employment in Los Angeles

Commute patterns can reflect multiple dimensions of urban inequality, primarily access to housing, jobs, and transportation. Researchers have sought to understand and predict commute behavior to identify and address such inequities, especially among disadvantaged workers and communities. In this dissertation, I analyzed the relationship between commute duration and the social, spatial, and temporal patterns of low-wage jobs. In particular, I examined the heterogeneity of low-wage jobs, in terms of whether they offer full-employment or employer-sponsored health insurance, as well as their spatial and temporal distribution; whether and how it relates to commute durations; and compared these aspects with high-wage workers. This research advances what we know about low-wage workers and commuting by centering the analysis on low-wage jobs – as opposed to workers. I used the Integrated Public Use Microdata Sample (IPUMS) American Community Survey (ACS) 1-year data for 2019, before the onset of the COVID-19 pandemic in March 2020. I focused my analyses on the five-county Los Angeles Metropolitan Area – Los Angeles, Orange, Ventura, Riverside, and San Bernardino. I applied ordinary least squares regression models in the first and third chapters, and multi-level models in the second chapter to predict commute times among low-wage workers, and compared them to high-wage workers. I found that employment characteristics are significant predictors of commute patterns among low-wage workers. Improving job quality could reduce the commute burden of many low-wage workers – instead of engaging in long commutes to jobs that offer wage and employment security, low-wage workers could engage in short commutes to more spatially accessible, consumer-oriented service sector jobs. The second empirical chapter contributes to the literature on low-wage workers and commuting by estimating the effects of the industry of employment, since labor and employment policies more often address industries, e.g., sector-based minimum wage increases, and industry-level regulations have more coverage. Finally, low-wage workers who commute during rush hour have longer commute times than low-wage workers who commute during off-peak hours, while high-wage workers have the opposite relationship, which suggests that high-wage workers have greater residential mobility and location selection, while low-wage workers experience spatial mismatch. The results of these studies suggest that more equitable transportation planning can be informed by labor markets, or how better labor and employment policies can inform transportation planning.