The Racial Composition Of Road Users, Traffic Citations, And Police Stops

Wenfei Xu, Michael Smart, Nebiyou Tilahun, Sajad Askari, Zachary Dennis, Houpu Li and David Levinson
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David Levinson: TransportLab, School of Civil Engineering, University of Sydney

Working Papers from University of Minnesota: Nexus Research Group

Abstract: This paper exploits the potential of Global Positioning System datasets sourced from mobile phones to estimate the racial composition of road users, leveraging data from their respective Census block group. The racial composition data encompasses approximately 46 million trips in the Chicago metropolitan region. The research focuses on the relationship between camera tickets and racial composition of drivers vs. police stops for traffic citations and the racial composition in these locations. Black drivers exhibit a higher likelihood of being ticketed by automated speed cameras and of being stopped for moving violations on roads, irrespective of the proportion of White drivers present. The research observes that this correlation attenuates as the proportion of White drivers on the road increases. The citation rate measured by cameras better matches the racial composition of road users on the links with cameras than do stops by police officers. This study therefore presents an important contribution to understanding racial disparities in moving violation stops, with implications for policy interventions and social justice reforms.

Keywords: transportation; road transport (search for similar items in EconPapers)
JEL-codes: R40 (search for similar items in EconPapers)
Date: 2024
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Published in Proceedings of the National Academy of Sciences 121 (24) e2402547121

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https://doi.org/10.1073/pnas.2402547121 Published version landing page, 2024 (text/html)

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Persistent link: https://EconPapers.repec.org/RePEc:nex:wpaper:paper-2024-18

DOI: 10.1073/pnas.2402547121

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