JOURNAL ARTICLE
The effects of immigration enforcement on traffic stops: Changing driver or police behavior?
Published In: Criminology & Public Policy, 2023, v. 22, n. 3. P. 457 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: van Tiem, Britte 3 of 3
Abstract
Research Summary: This research asks whether jail‐based immigration enforcement leads to the profiling of Hispanics by municipal police. I leverage a natural experiment to examine the effects of 287(g) jail partnerships on traffic stops and arrests by municipal police in North Carolina in the late 2000s. I find that stops of Hispanic drivers fell in the wake of 287(g) agreements, and show that this fall was driven by changes in Hispanic road use. While I cannot unambiguously disentangle police and driver behavior, I find no evidence that municipal police officers increased pretextual stops and arrests of Hispanic drivers. Policy Implications: While there is existing evidence of racial profiling under 287(g) agreements by sheriff's deputies, this behavior does not appear to have extended to nonsignatory municipal police agencies. Despite this, the signing of 287(g) agreements appears to have prompted Hispanic outmigration and changes in driving behavior, adding to a growing body of evidence on the ripple effects of local‐federal immigration enforcement partnerships in Hispanic communities. This serves as a reminder that changes in demographic composition of the immigrant population may mediate the effects of immigration enforcement efforts on other outcomes. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Criminology & Public Policy. 2023/08, Vol. 22, Issue 3, p457
- Document Type:Article
- Subject Area:Law
- Publication Date:2023
- ISSN:1538-6473
- DOI:10.1111/1745-9133.12625
- Accession Number:169828928
- Copyright Statement:Copyright of Criminology & Public Policy is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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