Commuting Variability by Wage Groups in Baton Rouge, 1990–2010

Abstract

Residential segregation recently has shifted to more class/income-based in the United States, and neighborhoods are undergoing significant changes such as commuting patterns over time. To better understand the commuting inequality across neighborhoods of different income levels, this research analyzes commuting variability (in both distance and time) across wage groups as well as stability over time using the CTPP data 1990-2010 in Baton Rouge. In comparison to previous work, commuting distance is estimated more accurately by Monte Carlo simulation of individual trips to mitigate aggregation error and scale effect. The results based on neighborhood's mean wage rate indicate that commuting behaviors vary across areas of different wage rates and such variability is captured by a convex shape. Affluent neighborhoods tended to commute more but highest-wage neighborhoods retreated for less commuting. This trend remains relatively stable over time despite an overall transportation improvement in general. A complementary analysis based on the distribution of wage groups is conducted to gain more detailed insights and uncovers the lasting poor mobility (e.g., fewer location and transport options) of the lowest-wage workers in 1990-2010.

Commuting and Sleep: Results From the Hispanic Community Health Study/Study of Latinos Sueño Ancillary Study

“…Studies suggest that lower SES or undocumented legal status is associated with less job accessibility and longer commute times to jobs. 47–49 At the workplace level, individual workplace policy changes that allow for tele- and video-commuting, flexible hours, and later start-times (to avoid rush hour) may shorten individual workers’ commute times. At a societal level, interventions to reduce commute time may include increased investments in public transportation, more quality housing near job-rich centers to counter the effects of urban sprawl, 50 modifying urban design to improve highway infrastructure, 51 and making more affordable and accessible public parking.…”

The Changes of Urban Structure and Commuting: An Application to Metropolitan Statistical Areas in the United States

“…However, variances of commuting time and/or distances among different wages are important factors to understand the link between urban structure and commuting time and/or distance. Previous literature, by and large, came to a consensus that low-income commuters travel shorter distance than those with higher incomes (Hu, Wang, and Wilmot 2016; Kim et al 2012; Li 2010; Niedzielski and Boschmann 2014; Sultana 2002; E Wang, Song, and Xu 2011), while opinions diverged on the link between income and commuting time (Blumenberg and Manville 2004; Sermons and Koppelman 2001; D Wang and Chai 2009). Other perspectives, involving the role of urban structure in shaping commuting patterns for different occupations, genders, races, and commuting modes, also attract research interests (Crane 2007; Horner and Mefford 2007; Ibipo 1995; Kwan and Kotsev 2015; Kawase 2004; Kim et al 2012; Mauch and Taylor 1997; McLafferty 1997; Murphy 2009; O’Kelly, Niedzielski, and Gleeson 2012; Sang, O’Kelly, and Kwan 2011; Waddell 1992).…”

Analysis of Spatial Mismatch and Equity using Commuting and Labor Sheds: Trends in Indiana

“…In relation to income, empirical evidence shows that high-income groups tend to have longer commutes. For instance, Wang, cited in Hu et al ( 32 ), found that wealthier areas presented longer commutes until an income threshold after which commuting will decline. A similar pattern was found by Chacon-Hurtado et al for a county in Indiana ( 33 ).…”

“…These trends are different when looking at travel times given that they tend to become stable over a time period ( 15 ). Nonetheless, studies (such as Wang, cited in Hu et al [ 32 ]) found that travel distances tend to be more sensitive to wages. Therefore, the use of distance could help uncover differences in the burden of travel for different socio-demographic groups.…”