Allegations of racially biased policing are a contentious issue in many communities. Processes that flag potential problem officers have become a key component of risk management systems at major police departments. We present a statistical method to flag potential problem officers by blending three methodologies that are the focus of active research efforts: propensity score weighting, doubly robust estimation, and false discovery rates. Compared with other systems currently in use, the proposed method reduces the risk of flagging a substantial number of false positives by more rigorously adjusting for potential confounders and by using the false discovery rate as a measure to flag officers.We apply the methodology to data on 500,000 pedestrian stops in New York City in 2006. Of the nearly 3,000 New York City Police Department officers regularly involved in pedestrian stops, we flag 15 officers who stopped a substantially greater fraction of black and Hispanic suspects than our statistical benchmark predicts.
Reprinted with permission from Journal of the American Statistical Association, Volume 104, Number 486, pp. 661–668. Copyright © 2009 American Statistical Association.
Originally published in: Journal of the American Statistical Association, pp. 661-668, June 2009, Vol. 104, No. 486.
This report is part of the RAND Corporation reprint series. The Reprint was a product of the RAND Corporation from 1992 to 2011 that represented previously published journal articles, book chapters, and reports with the permission of the publisher. RAND reprints were formally reviewed in accordance with the publisher's editorial policy and compliant with RAND's rigorous quality assurance standards for quality and objectivity. For select current RAND journal articles, see External Publications.
Permission is given to duplicate this electronic document for personal use only, as long as it is unaltered and complete. Copies may not be duplicated for commercial purposes. Unauthorized posting of RAND PDFs to a non-RAND Web site is prohibited. RAND PDFs are protected under copyright law. For information on reprint and linking permissions, please visit the RAND Permissions page.
The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.