Crime is often a group activity, especially among youth. Yet crime-prevention experiments typically ignore the possibility of peer spillovers, which could lead intent-to-treat estimates to either over- or under-state the true impact of a program. Since many more individuals are indirectly treated via their peers than are directly treated, accounting for such spillovers has the potential to substantially change assessments of the overall effect of these programs. Our study will rigorously measure peer spillovers from treatment in four existing crime-prevention experiments. The results will improve our understanding of a set of influential RCTs (and potentially many others), expand our knowledge of how people affect each other's criminal decision-making, and provide guidance to policymakers about how to leverage peer effects to maximize future program impacts.
The study will combine four existing randomized controlled trials that reduced violence in Chicago (total N > 12,000) with multiple administrative measures of social networks (N > 1 million) to estimate how changes in individual criminal behavior spread through connected populations. Using the random variation in exposure to treated peers induced by randomization, we will estimate the causal effect of different kinds of exposure. Totaling these estimates across the entire sample will provide a more complete understanding of the interventions' net effects, and allow us to calculate how biased impact estimates are if they ignore social spillovers onto controls. We will then use heterogeneity in these peer effect estimates to better understand and model how social interactions generate decisions about crime, allowing us to estimate which targeting strategies would be most effective in maximizing the social impact of an intervention.
The study will be a secondary analysis expanding on 4 existing RCTs:
• Becoming a Man
• One Summer Chicago Plus 2012 (AEARCTR-0002222)
• One Summer Chicago Plus 2013 (AEARCTR-0001472)
• Rapid Employment and Development Initiative (https://osf.io/ap8fj/)