IDEAS home Printed from https://ideas.repec.org/a/nat/nathum/v3y2019i8d10.1038_s41562-019-0612-8.html
   My bibliography  Save this article

Causal peer effects in police misconduct

Author

Listed:
  • Edika G. Quispe-Torreblanca

    (Said Business School, University of Oxford
    University of Warwick, Warwick Business School)

  • Neil Stewart

    (University of Warwick, Warwick Business School)

Abstract

We estimate causal peer effects in police misconduct using data from about 35,000 officers and staff from London’s Metropolitan Police Service for the period 2011–2014. We use instrumental variable techniques and exploit the variation in peer misconduct that results when officers switch peer groups. We find that a 10% increase in prior peer misconduct increases an officer’s later misconduct by 8%. As the police are empowered to enforce the law and protect individual liberties, integrity and fairness in policing are essential for establishing and maintaining legitimacy and public consent1–5. Understanding the antecedents of misconduct will help to develop interventions that reduce misconduct.

Suggested Citation

  • Edika G. Quispe-Torreblanca & Neil Stewart, 2019. "Causal peer effects in police misconduct," Nature Human Behaviour, Nature, vol. 3(8), pages 797-807, August.
  • Handle: RePEc:nat:nathum:v:3:y:2019:i:8:d:10.1038_s41562-019-0612-8
    DOI: 10.1038/s41562-019-0612-8
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41562-019-0612-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41562-019-0612-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cubitt, Timothy I.C. & Gaub, Janne E. & Holtfreter, Kristy, 2022. "Gender differences in serious police misconduct: A machine-learning analysis of the New York Police Department (NYPD)," Journal of Criminal Justice, Elsevier, vol. 82(C).
    2. Adams, Ian T. & McCrain, Joshua & Schiff, Daniel S. & Schiff, Kaylyn Jackson & Mourtgos, Scott M., 2022. "Public Pressure or Peer Influence: What Shapes Police Executives' Views on Civilian Oversight?," SocArXiv mdu96, Center for Open Science.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nathum:v:3:y:2019:i:8:d:10.1038_s41562-019-0612-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.