Comparing immigrant commute travel adaptation across and within racial/ethnic groups

Lingqian Hu, Nicholas J. Klein and Michael J. Smart

Transport Policy, 2021, vol. 110, issue C, 112-122

Abstract: This research investigates differences in the adaptation process of immigrant commute distance and commute mode across and within three racial/ethnic groups—white, Hispanic, and Asian—in the United States to explore policies that facilitate immigrant travel in an efficient and sustainable way. A two-step analysis is conducted: the first step uses all US-born as the reference group, and the second step uses US-born of the same race/ethnicity as the reference. The second step overcomes a potential problem in existing research on immigrant travel adaptation: When all US-born are used as the reference group, the statistics mainly reflect the travel behavior of US-born white people, masking intrinsic travel differences among US-born racial/ethnic groups. Based on multi-level regression analysis of the 2017 National Household Travel Survey (NHTS) data, our results support existing findings of initial difference but eventual convergence of immigrant commute behavior with US-born, while highlighting white immigrants' persistence and Hispanic immigrants' low propensity in using non-automobile modes. Comparison results based on the two reference groups suggest that segmented assimilation due to racial/ethnic group membership is limited. Still, nuanced findings denote distinctive spatial mechanisms that affect immigrant and US-born Asians and highlight the short time window after immigrants' arrival in the U.S. during which policies might contribute to a continuation of their sustainable travel patterns.

Keywords: Transit; Walking/biking; National household travel survey; Acculturation; Segmented assimilation (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:trapol:v:110:y:2021:i:c:p:112-122

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DOI: 10.1016/j.tranpol.2021.05.024

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