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Racial Profiling? Detecting Bias Using Statistical Evidence

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  • Nicola Persico

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    (Department of Economics, New York University, New York, New York 10012)

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    Abstract

    We review the economics literature that deals with identifying bias, or taste for discrimination, using statistical evidence. A unified model is developed that encompasses several different strategies studied in the literature. We also discuss certain more theoretical questions concerning the proper objective of discrimination law.

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    File URL: http://www.annualreviews.org/doi/abs/10.1146/annurev.economics.050708.143307
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    Bibliographic Info

    Article provided by Annual Reviews in its journal Annual Review of Economics.

    Volume (Year): 1 (2009)
    Issue (Month): 1 (05)
    Pages: 229-254

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    Handle: RePEc:anr:reveco:v:1:y:2009:p:229-254

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    Related research

    Keywords: discrimination; identification; bias;

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    Cited by:
    1. Decio Coviello & Nicola Persico, 2013. "An Economic Analysis of Black-White Disparities in NYPD's Stop and Frisk Program," NBER Working Papers 18803, National Bureau of Economic Research, Inc.
    2. Anbarci, Nejat & Lee, Jungmin, 2014. "Detecting racial bias in speed discounting: Evidence from speeding tickets in Boston," International Review of Law and Economics, Elsevier, vol. 38(C), pages 11-24.
    3. Debopam Bhattacharya & Shin Kanaya & Margaret Stevens, 2014. "Are University Admissions Academically Fair?," CREATES Research Papers 2014-06, School of Economics and Management, University of Aarhus.
    4. Dragan Ilić, 2013. "Marginally discriminated: the role of outcome tests in European jurisdiction," European Journal of Law and Economics, Springer, vol. 36(2), pages 271-294, October.
    5. Brock, William A. & Cooley, Jane & Durlauf, Steven N. & Navarro, Salvador, 2012. "On the observational implications of taste-based discrimination in racial profiling," Journal of Econometrics, Elsevier, vol. 166(1), pages 66-78.
    6. Bhattacharya, Debopam, 2013. "Evaluating treatment protocols using data combination," Journal of Econometrics, Elsevier, vol. 173(2), pages 160-174.

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