Predictive Enforcement
We study law enforcement guided by data-informed predictions of “hot spots” for likely criminal offenses. Such “predictive” enforcement could lead to data being selectively and disproportionately collected from neighbourhoods targeted for enforcement by the prediction. Predictive enforcement that fails to account for this endogenous “datafication” may lead to the over-policing of traditionally high-crime neighbourhoods and performs poorly, in particular, in some cases as poorly as if no data were used. Endogenizing the incentives for criminal offenses identifies additional deterrence benefits from the informationally efficient use of data.
Date:
26 April 2024, 14:15
Venue:
Manor Road Building, Manor Road OX1 3UQ
Venue Details:
Seminar Room G or https://zoom.us/j/93867615769?pwd=T1NsTEVwNE40R3pEVW9yTlBicG1mdz09
Speaker:
Yeon-Koo Che (Columbia University)
Organising department:
Department of Economics
Part of:
Nuffield Economic Theory Seminar
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Edward Clark
