Crime variability, peer effects, and economic inequality in social networks

Abstract

A large fraction of the variance in aggregate crime rates cannot be explained by observable socioeconomic conditions. Social determinants of crime may drive the unexplained variation, but economic models of social influence so far emphasize the intensity of criminal effort, not the decision of whether to participate in crime. This article develops a model of criminal participation as a supermodular game, based on the theory of differential association. Simulations relate the structural characteristics of social networks to supportable patterns of crime in equilibrium. Denser and more unevenly connected networks show wider variation in aggregate crimes, but wage inequality in the formal sector reduces the variance. Additionally, average crimes rates are a single-peaked function of wage inequality. This feature suggests future cross-sectional studies of crime rates and income inequality should treat inequality as a quadratic function within a regression model.