Working Paper: CEPR ID: DP8772
Authors: Xiaodong Liu; Eleonora Patacchini; Yves Zenou; Lungfei Lee
Abstract: We analyze delinquent networks of adolescents in the United States. We develop a dynamic network formation model showing who the key player is, i.e. the criminal who once removed generates the highest possible reduction in aggregate crime level. We then structurally estimate our model using data on criminal behaviors of adolescents in the United States (AddHealth data). Compared to other criminals, key players are more likely to be a male, have less educated parents, are less attached to religion and feel socially more excluded. We also find that, even though some criminals are not very active in criminal activities, they can be key players because they have a crucial position in the network in terms of betweenness centrality.
Keywords: Bonacich Centrality; Crime; Policies; Dynamic Network Formation
JEL Codes: A14; D85; K42; Z13
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| characteristics influencing criminal decision (K14) | type of crime (K42) |
| gender and racial differences (J71) | characteristics influencing criminal decision (K14) |
| key players (Z22) | aggregate crime (K42) |
| removal of a key player (J63) | aggregate crime (K42) |
| peer delinquent activity (K42) | individual delinquent behavior (K42) |