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Racial Profiling, Statistical Discrimination, and the Effect of a Colorblind Policy on the Crime Rate

Authors


  • David Bjerk, Claremont McKenna College, Department of Economics, Bauer Center, 500 E. Ninth St., Claremont, CA 91711-6400.

  •  Thanks to Seungjin Han, Lance Lochner, Stephen L. Ross, the seminar participants at the University of Western Ontario, the Canadian Public Economics Research Group, and the referees and editors at this journal for their helpful comments and suggestions on earlier drafts. Also, I would like to acknowledge the support of the economics department at McMaster University, as much of this work was done while I was on faculty there.

Abstract

This paper develops a model of racial profiling by law enforcement officers when officers observe both an individual's race as well as a noisy signal of his or her guilt that depends on whether or not a crime has been committed. The model shows that given officers observe such a guilt signal, data regarding the guilt rate among those investigated from each race will not be sufficient for determining whether racially unequal investigation rates are due to statistical discrimination or racial bias on the part of officers. The model also reveals that when racially unequal investigation rates are due to statistical discrimination, imposing a colorblind policy on officers can increase, decrease, or have little effect on the crime rate, depending on specific characteristics of the jurisdiction and the crime in question.

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