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On the observational implications of taste-based discrimination in racial profiling

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Author Info

  • Brock, William A.
  • Cooley, Jane
  • Durlauf, Steven N.
  • Navarro, Salvador

Abstract

This paper contributes to a growing literature that attempts to determine whether disparities in police stops and searches of potential criminals of different races stem from taste-based discrimination. The key challenge in making this evaluation is that police officers have more information than the econometrician and thus racial disparities in police behavior may result from these unobservable factors rather than discrimination. We develop a general equilibrium model of police and potential criminal behavior that encompasses key models in the literature. We highlight the assumptions needed for existing methods of detecting racial discrimination to hold. In particular, we show that when there are increasing costs to search, existing tests for discrimination can give incorrect results. Given the potential importance of these costs, we then propose some alternate methods for detecting racial bias in police behavior.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 166 (2012)
Issue (Month): 1 ()
Pages: 66-78

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Handle: RePEc:eee:econom:v:166:y:2012:i:1:p:66-78

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Web page: http://www.elsevier.com/locate/jeconom

Related research

Keywords: Racial profiling; Discrimination; Identification;

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References

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  1. Durlauf,S.N., 2005. "Assessing racial profiling," Working papers 2, Wisconsin Madison - Social Systems.
  2. 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, 06.
  3. Sarath Sanga, 2009. "Reconsidering Racial Bias in Motor Vehicle Searches: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 117(6), pages 1155-1159, December.
  4. Shamena Anwar & Hanming Fang, 2004. "An Alternative Test of Racial Prejudice in Motor Vehicle Searches: Theory and Evidence," Cowles Foundation Discussion Papers 1464, Cowles Foundation for Research in Economics, Yale University.
  5. John Knowles & Nicola Persico & Petra Todd, 1999. "Racial Bias in Motor Vehicle Searches: Theory and Evidence," NBER Working Papers 7449, National Bureau of Economic Research, Inc.
  6. Charles F. Manski, 2006. "Search Profiling With Partial Knowledge of Deterrence," Economic Journal, Royal Economic Society, vol. 116(515), pages F385-F401, November.
  7. Dhammika Dharmapala & Stephen L. Ross, 2003. "Racial Bias in Motor Vehicle Searches: Additional Theory and Evidence," Working papers 2003-12, University of Connecticut, Department of Economics, revised Dec 2003.
  8. William A. Brock, 2006. "Profiling Problems With Partially Identified Structure," Economic Journal, Royal Economic Society, vol. 116(515), pages F427-F440, November.
  9. 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.
  10. Nicola Persico, 2009. "Racial Profiling? Detecting Bias Using Statistical Evidence," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 229-254, 05.
  11. James J. Heckman, 1998. "Detecting Discrimination," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 101-116, Spring.
  12. Jeffrey Grogger & Greg Ridgeway, 2005. "Testing for Racial Profiling in Traffic Stops from Behind a Veil of Darkness," Working Papers 0507, Harris School of Public Policy Studies, University of Chicago.
  13. Kerwin Kofi Charles & Jonathan Guryan, 2008. "Prejudice and Wages: An Empirical Assessment of Becker's The Economics of Discrimination," Journal of Political Economy, University of Chicago Press, vol. 116(5), pages 773-809, October.
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Cited by:
  1. Bhattacharya, Debopam, 2013. "Evaluating treatment protocols using data combination," Journal of Econometrics, Elsevier, vol. 173(2), pages 160-174.

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