The Efficient Deployment of Police Resources: Theory and New Evidence from a Randomized Drunk Driving Crackdown in India

88 Pages Posted: 7 Oct 2019

See all articles by Abhijit V. Banerjee

Abhijit V. Banerjee

Massachusetts Institute of Technology (MIT) - Department of Economics

Esther Duflo

Massachusetts Institute of Technology (MIT) - Department of Economics; Abdul Latif Jameel Poverty Action Lab (J-PAL); National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR); Bureau for Research and Economic Analysis of Development (BREAD)

Daniel Keniston

Yale University; Yale University - Cowles Foundation; National Bureau of Economic Research (NBER); The International Growth Centre; Abdul Latif Jameel Poverty Action Lab (J-PAL)

Multiple version iconThere are 2 versions of this paper

Date Written: September 2019

Abstract

Should police activity should be narrowly focused and high force, or widely dispersed but of moderate intensity? Critics of intense "hot spot" policing argue it primarily displaces, not reduces, crime. But if learning about enforcement takes time, the police may take advantage of this period to intervene intensively in the most productive location. We propose a multi-armed bandit model of criminal learning and structurally estimate its parameters using data from a randomized controlled experiment on an anti-drunken driving campaign in Rajasthan, India. In each police station, sobriety checkpoints were either rotated among 3 locations or fixed in the best location, and the intensity of the crackdown was cross-randomized. Rotating checkpoints reduced night accidents by 17%, and night deaths by 25%, while fixed checkpoints had no significant effects. In structural estimation, we show clear evidence of driver learning and strategic responses. We use these parameters to simulate environment-specific optimal enforcement policies.

Keywords: Choice Modeling, Crime Prevention, Illegal behavior, Information Acquisition, law enforcement, Learning Models

Suggested Citation

Banerjee, Abhijit V. and Duflo, Esther and Keniston, Daniel, The Efficient Deployment of Police Resources: Theory and New Evidence from a Randomized Drunk Driving Crackdown in India (September 2019). CEPR Discussion Paper No. DP13981, Available at SSRN: https://ssrn.com/abstract=3464508

Abhijit V. Banerjee (Contact Author)

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

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Esther Duflo

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Daniel Keniston

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