IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/7tazd.html
   My bibliography  Save this paper

Breaking the chain: How arrests reduce the probability of near repeat crimes

Author

Listed:
  • Wheeler, Andrew Palmer

    (University of Texas at Dallas)

  • Riddell, Jordan R.
  • Haberman, Cory P.

Abstract

Objectives: Near repeat patterns have been identified for a host of different crimes, but effective strategies to reduce near repeats have had more variable results. This study identifies near repeat crime patterns in Dallas, Texas and examines the effects of an arrest on reducing the probability of future crime. Method: Using open source crime data from the Dallas Police Department from July 2014 through June 2018, we identified near repeat patterns for shootings, interpersonal robberies, residential burglaries, and thefts from motor vehicles. Logistic regression models were used to test the effect of an arrest on reducing near repeat crimes; controls for geographic, demographic, and temporal factors were included in each model. Results: Near repeat calculations suggest violent crime clustered closely in time and space, with property crime dispersed over larger spatial and temporal dimensions. Across all four crime types, findings suggest arrests resulted in 20% to 40% reductions in a near repeat follow up crime. Conclusions: In line with past research on shootings, arrests reduced the likelihood of subsequent crimes. This suggests policing strategies to increase arrests may be a fruitful way to reduce near repeat crime patterns. Code to replicate the analysis can be found at: https://www.dropbox.com/sh/72q0i7wm60ndqve/AABgFB8zwGHG6xjExvaD01EGa?dl=0.

Suggested Citation

  • Wheeler, Andrew Palmer & Riddell, Jordan R. & Haberman, Cory P., 2019. "Breaking the chain: How arrests reduce the probability of near repeat crimes," SocArXiv 7tazd, Center for Open Science.
    • Handle: RePEc:osf:socarx:7tazd
    DOI: 10.31219/osf.io/7tazd
    as

    Download full text from publisher

    File URL: https://osf.io/download/5d39f6d3847d2f0019eed3e6/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/7tazd?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
    ---><---

    References listed on IDEAS

    as
    1. Michael D. Porter, 2016. "A Statistical Approach to Crime Linkage," The American Statistician, Taylor & Francis Journals, vol. 70(2), pages 152-165, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alex Chohlas-Wood & E. S. Levine, 2019. "A Recommendation Engine to Aid in Identifying Crime Patterns," Interfaces, INFORMS, vol. 49(2), pages 154-166, March.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:osf:socarx:7tazd. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: OSF (email available below). General contact details of provider: https://arabixiv.org .

    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.