Working Paper: CEPR ID: DP14850
Authors: Paolo Pinotti
Abstract: I review recent developments in the economic analysis of crime, focusing in particular on organized crime and corruption. I first discuss the main challenges to the empirical identification of causal relationships -- namely, measurement error due to endogenous reporting of crime and the fact that randomized controlled trials are rarely an option when studying crime. I then discuss recent advancements made possible by the combination of detailed micro-data and quasi-experimental methods.
Keywords: Economics of crime; Measurement error; Identification; Quasi-experiments
JEL Codes: K42
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| harsher sanctions (F51) | crime (K42) |
| higher probabilities of arrest (K42) | crime (K42) |
| increased legitimate earning opportunities (J68) | crime (K42) |
| police presence (J45) | crime (K42) |
| expected prison sentences (K40) | recidivism (K14) |
| crime elasticity concerning police force size (K42) | crime (K42) |