Building Criminal Capital behind Bars: Peer Effects in Juvenile Corrections^*

Abstract

This paper analyzes the influence that juvenile offenders serving time in the same correctional facility have on each other's subsequent criminal behavior. The analysis is based on data on over 8,000 individuals serving time in 169 juvenile correctional facilities during a two-year period in Florida. These data provide a complete record of past crimes, facility assignments, and arrests and adjudications in the year following release for each individual. To control for the nonrandom assignment to facilities, we include facility and facility-by-prior-offense fixed effects, thereby estimating peer effects using only within-facility variation over time. We find strong evidence of peer effects for burglary, petty larceny, felony and misdemeanor drug offenses, aggravated assault, and felony sex offenses. The influence of peers primarily affects individuals who already have some experience in a particular crime category. We also find evidence that the predominant types of peer effects differ in residential versus nonresidential facilities; effects in the latter are consistent with network formation among youth serving time close to home.

Covenants without the Sword? Comparing Prison Self-Governance Globally

“…When inmates return to the community, prison influences come with them. Some inmates build criminal networks and social capital that increases post-release criminality (Bayer et al 2009). Gangs that rise to power behind bars wield tremendous influence on the outside (Denyer Willis 2015;Skarbek 2011;Lessing 2015).…”

An Overview of Social Networks and Economic Applications

“…They 9 Taking advantage of randomized programs in the field has proven to be a useful strategy in identifying various peer effects, not only operating through preference interactions but also through the diffusion of information. For example, see Duflo and Saez (2003) and Bayer, Hjalmarsson, and Pozen (2009 then tracked what fraction of the doctors in each of these three groups had prescribed the drug at least once. Essentially their finding was that the most highly connected group (named by three or more other doctors) had the greatest fraction who had prescribed the drug by each date, and the second most highly connected group was second, and the unconnected group lagged behind in the fraction that had prescribed the drug.…”

Educational Outcomes After Serving with Electronic Monitoring: Results from a Natural Experiment

“…Empirical studies have documented causal peer effects and specialization among inmates (e.g. Bayer et al 2009;Damm and Gorinas 2013;Stevenson 2014), which suggests that offenders in house arrest with electronic surveillance who have fewer interactions with other criminals and more contact with pro-social peers (like family) would be less likely to reoffend. In regards to educational outcomes, this would imply that offenders serving with EM with lower recidivism rates are less likely to drop out and have a higher chance of achieving better educational results.…”