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Crime is Terribly Revealing: Information Technology and Police Productivity

67 Pages Posted: 22 Jun 2017  

Giovanni Mastrobuoni

University of Torino - Collegio Carlo Alberto; University of Essex - Department of Economics; IZA

Date Written: February 20, 2017

Abstract

An increasing number of police departments use information technology to optimize their patrolling strategies. Quasi-random assignment of individual crimes to predictive policing leads to a sizable increase in clearances. Detailed information on individual crime incidents coupled with offender-level identifiers shed light on the mechanisms behind the productivity improvements. Patterns with respect to type of victims, location, time of the offence, and frequency of offending are revealed.

Auxiliary city-level data show that the introduction of predictive policing coincides with a large negative trend-discontinuity in crime. The benefit-cost ratio of this IT innovation appears to be large.

Keywords: predictive policing, IT, police, crime, quasi-experiment

JEL Classification: O33, K42, L23, H1, H41

Suggested Citation

Mastrobuoni, Giovanni, Crime is Terribly Revealing: Information Technology and Police Productivity (February 20, 2017). Available at SSRN: https://ssrn.com/abstract=2989914 or http://dx.doi.org/10.2139/ssrn.2989914

Giovanni Mastrobuoni (Contact Author)

University of Torino - Collegio Carlo Alberto ( email )

Piazza Arbarello 8
Torino, Torino 10122
Italy

HOME PAGE: http://www.carloalberto.org/people/faculty/assistant-professors-and-chairs/mastrobuoni/

University of Essex - Department of Economics ( email )

Wivenhoe Park
Colchester CO4 3SQ
United Kingdom

IZA ( email )

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