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How Do NYPD Officers Respond to Terror Threats?

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  • Steven F. Lehrer
  • Louis Pierre Lepage

Abstract

Using data from the New York City Police Department's Stop-and-Frisk program, we evaluate the impact of a specific terrorist attack threat from Al Qaeda on policing behavior in New York City. We find that after the Department of Homeland Security raised the alert level in response to this threat, people categorized as "Other" by the NYPD, including Arabs, were significantly more likely to be frisked and have force used against them yet no more likely to be arrested. These individuals were in turn less likely to be frisked or have force used against them immediately after the alert level returned to its baseline level. Further, evidence suggests that these impacts were larger in magnitude in police precincts that have a higher concentration of mosques. Our results are consistent with profiling by police officers leading to low-productivity stops, but we cannot rule out that it constitutes efficient policing given important differences between deterrence of terrorism versus other crimes.

Suggested Citation

  • Steven F. Lehrer & Louis Pierre Lepage, 2019. "How Do NYPD Officers Respond to Terror Threats?," NBER Working Papers 26438, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:26438
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    1. Mirko Draca & Stephen Machin & Robert Witt, 2011. "Panic on the Streets of London: Police, Crime, and the July 2005 Terror Attacks," American Economic Review, American Economic Association, vol. 101(5), pages 2157-2181, August.
    2. Shi, Lan, 2009. "The limit of oversight in policing: Evidence from the 2001 Cincinnati riot," Journal of Public Economics, Elsevier, vol. 93(1-2), pages 99-113, February.
    3. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    4. Klick, Jonathan & Tabarrok, Alexander, 2005. "Using Terror Alert Levels to Estimate the Effect of Police on Crime," Journal of Law and Economics, University of Chicago Press, vol. 48(1), pages 267-279, April.
    5. Cumby, Robert E & Huizinga, John, 1992. "Testing the Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions," Econometrica, Econometric Society, vol. 60(1), pages 185-195, January.
    6. repec:cai:poeine:pope_1203_0349 is not listed on IDEAS
    7. Decio Coviello & Nicola Persico, 2015. "An Economic Analysis of Black-White Disparities in the New York Police Department's Stop-and-Frisk Program," The Journal of Legal Studies, University of Chicago Press, vol. 44(2), pages 315-360.
    8. Jason Abaluck & Leila Agha & Chris Kabrhel & Ali Raja & Arjun Venkatesh, 2016. "The Determinants of Productivity in Medical Testing: Intensity and Allocation of Care," American Economic Review, American Economic Association, vol. 106(12), pages 3730-3764, December.
    9. Lorraine Mazerolle & Sarah Bennett & Jacqueline Davis & Elise Sargeant & Matthew Manning, 2013. "Legitimacy in Policing: A Systematic Review," Campbell Systematic Reviews, John Wiley & Sons, vol. 9(1), pages -147.
    10. 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.
    11. Steven F. Lehrer & Louis-Pierre Lepage, 2019. "Does Selective Crime Reporting Influence Our Ability to Detect Racial Discrimination in the Nypd’s Stop-and-Frisk Program?," Advances in Econometrics, in: The Econometrics of Complex Survey Data, volume 39, pages 259-286, Emerald Group Publishing Limited.
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    Cited by:

    1. Lepage, Louis-Pierre, 2023. "Discrimination and sorting in the real estate market: Evidence from terrorist attacks and mosques," European Economic Review, Elsevier, vol. 153(C).
    2. Nils Braakmann, 2022. "Does stop and search reduce crime? Evidence from street‐level data and a surge in operations following a high‐profile crime," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1370-1397, July.
    3. Kevin Petersen & David Weisburd & Sydney Fay & Elizabeth Eggins & Lorraine Mazerolle, 2023. "Police stops to reduce crime: A systematic review and meta‐analysis," Campbell Systematic Reviews, John Wiley & Sons, vol. 19(1), March.
    4. Nasreen Nawaz & Omer Saeed, 2022. "An Optimal Crime Control Policy in a Dynamic Setting," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(4), pages 827-880, December.
    5. Michelle Sydes & Lorelei Hine & Angela Higginson & James McEwan & Laura Dugan & Lorraine Mazerolle, 2023. "Criminal justice interventions for preventing radicalisation, violent extremism and terrorism: An evidence and gap map," Campbell Systematic Reviews, John Wiley & Sons, vol. 19(4), December.

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    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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