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Statistical (and Racial) Discrimination, 'Banning the Box', and Crime Rates

15 Pages Posted: 27 Mar 2017 Last revised: 28 Mar 2017

Murat C. Mungan

George Mason University - Antonin Scalia Law School, Faculty

Date Written: March 25, 2017

Abstract

This article presents law enforcement models where employers engage in statistical discrimination, and the visibility of criminal records can be adjusted through policies (such as ban the box campaigns). I show that statistical discrimination leads to an increase in crime rates under plausible conditions. This suggests that societies in which membership to disadvantaged groups is salient (e.g. through greater racial or religious heterogeneity) are, ceteris paribus, likely to have higher crime rates. Attempting to fix the negative impacts of statistical discrimination through policies that reduce the visibility of criminal records increases crime rates further. Moreover, such policies cause a greater negative effect for law abiding members of the disadvantaged group than members of the statistically favored group.

Keywords: Statistical discrimination, ban the box, crime, deterrence, racial heterogeneity.

JEL Classification: K00, K14, K42

Suggested Citation

Mungan, Murat C., Statistical (and Racial) Discrimination, 'Banning the Box', and Crime Rates (March 25, 2017). George Mason Law & Economics Research Paper No. 17-13. Available at SSRN: https://ssrn.com/abstract=2940743 or http://dx.doi.org/10.2139/ssrn.2940743

Murat C. Mungan (Contact Author)

George Mason University - Antonin Scalia Law School, Faculty ( email )

3301 Fairfax Drive
Arlington, VA 22201
United States

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