Does Selective Crime Reporting Influence Our Ability to Detect Racial Discrimination in the Nypd’s Stop-and-Frisk Program?

Steven Lehrer () and Louis-Pierre Lepage

A chapter in The Econometrics of Complex Survey Data, 2019, vol. 39, pp 259-286 from Emerald Group Publishing Limited

Abstract: Prior analyses of racial bias in the New York City’s Stop-and-Frisk program implicitly assumed that potential bias of police officers did not vary by crime type and that their decision of which type of crime to report as the basis for the stop did not exhibit any bias. In this paper, we first extend the hit rates model to consider crime type heterogeneity in racial bias and police officer decisions of reported crime type. Second, we reevaluate the program while accounting for heterogeneity in bias along crime types and for the sample selection which may arise from conditioning on crime type. We present evidence that differences in biases across crime types are substantial and specification tests support incorporating corrections for selective crime reporting. However, the main findings on racial bias do not differ sharply once accounting for this choice-based selection.

Keywords: Misclassification; selective reporting; racial discrimination; hit rates test; selection correction; criminal activity (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-905320190000039015

DOI: 10.1108/S0731-905320190000039015

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