Predictive Policing in a Developing Country: Evidence from Two Randomized Controlled Trials.

Objectives: The paper studies the impact of predictive policing on crime in a developing country. It also assesses the impact of different police trainings. Method: We analyze a randomized controlled trial conducted in Montevideo, Uruguay to assess the implementation of a predictive policing software developed in the United States. Half of the precincts were randomly assigned to the software and half to the local crime analysts (status quo). The second experiment allocated randomly a specially trained police force to targeted patrol areas per shift and day. Results: No statistically significant differences were found in crime outcomes between the precincts assigned to the foreign predictive software and those assigned to local crime analysts. On the second experiment, given determined targeted places, the specially trained task force showed more compliance with the assigned patrol sites (20% more patrol time) and a greater potential for reducing crime (reduction of 30% in robberies only during high crime shifts in comparison to the control group (no special training). There is also evidence of a diffusion of benefits to adjacent areas. Conclusions: The implementation of an international predictive policing software did not outperform local crime analysts in terms of crime reduction. Local crime analysts are more cost-effective. Given determined targeted places, a modest increase in police dosage of a specially trained police force could reduce crime in high-crime times. In developing countries new policing technologies and training require a deep understanding of the context to channel limited resources in the most efficient way. [ABSTRACT FROM AUTHOR]