| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP13981 |
| DP13981 The Efficient Deployment of Police Resources: Theory and New Evidence from a Randomized Drunk Driving Crackdown in India | |
| Esther Duflo; Abhijit Banerjee; Daniel Keniston | |
| 发表日期 | 2019-09-03 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | 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. |
| 主题 | Development Economics |
| 关键词 | Learning models Choice modeling Information acquisition Illegal behavior Law enforcement Crime prevention |
| URL | https://cepr.org/publications/dp13981 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/542862 |
| 推荐引用方式 GB/T 7714 | Esther Duflo,Abhijit Banerjee,Daniel Keniston. DP13981 The Efficient Deployment of Police Resources: Theory and New Evidence from a Randomized Drunk Driving Crackdown in India. 2019. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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