An Alternative Explanation for Short Commutes Among Low-Wage Workers

Keywords: commute, low-wage jobs, transportation equity, job accessibility, labor markets
Session Type: Virtual Paper Abstract
Day: Monday
Session Start / End Time: 2/28/2022 02:00 PM (Eastern Time (US & Canada)) - 2/28/2022 03:20 PM (Eastern Time (US & Canada))
Room: Virtual 41

Abstract

Studies have consistently shown that low-wage workers have, on average, shorter commutes. This fits the neoclassical urban economists’ framework that individuals choose longer commutes for higher wages because it compensates for higher transportation costs and greater amenities. However, what if short commutes reflect constrained choices, or structural barriers to longer commutes to higher wage jobs? Preston and McLafferty (2019) showed that Latinx men and women, Asian men and women, and white women are more likely to have short commutes to low-wage jobs than white men. Nelson (1986), England (1993), and Hanson and Pratt (1995) wrote that women have shorter commutes not because of lower wages, but due to the gendered division of household labor and occupational segregation. Similarly, I argue that low-wage workers are more likely to have short commutes because low-wage jobs are more spatially distributed and low-wage workers are more likely to experience housing instability, in addition to greater transportation barriers. I use Longitudinal Employer-Household Dynamics (LEHD) Workplace Area Characteristics (WAC) data to calculate the Moran’s I by industry. Then, I regress commute time (American Community Survey, ACS) on this measure controlling for wages, gender, race, household composition, housing tenure, length of residence, and mode of transportation. I consider interaction effects between the spatial distribution measure and wages as well, as I expect the relationship between workplace location and commuting to vary by wages. Finally, I include neighborhood-level characteristics, including racial composition and median home values, in a multilevel model to estimate both between and within group effects.