Abstract
This paper estimates the impact of police presence on crime using a unique database that tracks the exact location of Dallas Police Department patrol cars throughout 2009. To address the concern that officer location is often driven by crime, my instrument exploits police responses to calls outside their allocated coverage beat. This variable provides a plausible shift in police presence within the abandoned beat that is driven by the police goal of minimizing response times. I find that a 10% decrease in police presence at that location results in a 7% increase in crime. This result sheds light on the black box of policing and crime and suggests that routine changes in police patrol can have a significant impact on criminal behavior.
| Original language | American English |
|---|---|
| Pages (from-to) | 280-293 |
| Number of pages | 14 |
| Journal | Review of Economics and Statistics |
| Volume | 103 |
| Issue number | 2 |
| DOIs | |
| State | Published - 14 May 2021 |
| Externally published | Yes |
Bibliographical note
Funding Information:I thank the Police Foundation for providing me with the data for this study. This work would not have been possible without the help of Elizabeth Groff and Greg Jones. I also thank Lieutenant Rupert Emison and Lieutenant Scott Bratcher for providing insight and information on the Dallas Police Department. I am very grateful for the GIS assistance provided by Adi Ben-Nun, Nir Horvitz, Elka Gotfyrd, and Ruthie Harari-Kremer at the Hebrew University Center for Computational Geography. This research was supported by the Israel Science Foundation (grant 0610114502). A supplemental appendix is available online at https://doi.org/10.1162/
Funding Information:
I thank the Police Foundation for providing me with the data for this study. This work would not have been possible without the help of Elizabeth Groff and Greg Jones. I also thank Lieutenant Rupert Emison and Lieutenant Scott Bratcher for providing insight and information on the Dallas Police Department. I am very grateful for the GIS assistance provided by Adi Ben-Nun, Nir Horvitz, Elka Gotfyrd, and Ruthie Harari-Kremer at the Hebrew University Center for Computational Geography. This research was supported by the Israel Science Foundation (grant 0610114502).
Publisher Copyright:
© 2019 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
