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A New Look at Racial Profiling: Evidence from the Boston Police Department

Author

Listed:
  • Kate Antonovics

    (Department of Economics, University of California, San Diego)

  • Brian G. Knight

    (Department of Economics, Brown University)

Abstract

This paper provides new evidence on racial profiling using information on the race of both motorists and officers. Extending the model of Knowles, Persico, and Todd (2001), we develop a new test for distinguishing between preference-based and statistical discrimination. Our test is based on the notion that if search decisions are driven purely by statistical discrimination, then they should be independent of officer race. Our results, by contrast, demonstrate that officers are more likely to search if officer race and driver race differ. We then investigate and rule out two alternative explanations for our findings. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Kate Antonovics & Brian G. Knight, 2009. "A New Look at Racial Profiling: Evidence from the Boston Police Department," The Review of Economics and Statistics, MIT Press, vol. 91(1), pages 163-177, February.
  • Handle: RePEc:tpr:restat:v:91:y:2009:i:1:p:163-177
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    References listed on IDEAS

    as
    1. Joseph G. Altonji & Charles R. Pierret, "undated". "Employer Learning and Statistical Discrimination," IPR working papers 97-18, Institute for Policy Resarch at Northwestern University.
    2. Shamena Anwar & Hanming Fang, 2006. "An Alternative Test of Racial Prejudice in Motor Vehicle Searches: Theory and Evidence," American Economic Review, American Economic Association, vol. 96(1), pages 127-151, March.
    3. John Knowles & Nicola Persico & Petra Todd, 2001. "Racial Bias in Motor Vehicle Searches: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 109(1), pages 203-232, February.
    4. Rubén Hernández-Murillo & John Knowles, 2004. "Racial Profiling Or Racist Policing? Bounds Tests In Aggregate Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(3), pages 959-989, August.
    5. Dharmapala Dhammika & Ross Stephen L, 2004. "Racial Bias in Motor Vehicle Searches: Additional Theory and Evidence," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 3(1), pages 1-23, September.
    6. Donohue, John J, III & Levitt, Steven D, 2001. "The Impact of Race on Policing and Arrests," Journal of Law and Economics, University of Chicago Press, vol. 44(2), pages 367-394, October.
    7. David Bjerk, 2007. "Racial Profiling, Statistical Discrimination, and the Effect of a Colorblind Policy on the Crime Rate," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 9(3), pages 521-545, June.
    8. Jeff Dominitz, 2003. "How Do the Laws of Probability Constrain Legislative and Judicial Efforts to Stop Racial Profiling?," American Law and Economics Review, Oxford University Press, vol. 5(2), pages 412-432, August.
    9. Yatchew, Adonis & Griliches, Zvi, 1985. "Specification Error in Probit Models," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 134-139, February.
    10. Kenneth Arrow, 1971. "The Theory of Discrimination," Working Papers 403, Princeton University, Department of Economics, Industrial Relations Section..
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    JEL classification:

    • K0 - Law and Economics - - General
    • H0 - Public Economics - - General

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