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Final Technical Report: Neighborhoods, Recidivism, and Employment Among Returning Prisoners

NCJ Number
Date Published
October 2011
132 pages
This study examined the influence of community context on the labor-market outcomes and recidivism of former prisoners paroled in Michigan during 2003.
The study found that the features of the neighborhoods in which parolees lived were strong predictors of recidivism and labor-market outcomes; however, no simple answer could be provided for the question of what neighborhood characteristics make "risky" environments for parolees. Neighborhood socioeconomic composition was a strong predictor of labor-market outcomes, since paroles who lived in disadvantaged neighborhoods had difficulty in obtaining employment and escaping poverty. For recidivism, the most robust protective factor was living in a residentially stable neighborhood; and the most robust predictor of risk for recidivism was living in neighborhoods with higher densities of young people. From a policy perspective, these findings suggest that parole outcomes might be improved by using a careful evaluation of a parolee's neighborhood context when approving new residences, the placement of institutional housing for former prisoners in more advantaged neighborhoods, and inclusion of neighborhood context in risk assessment so as to improve the targeting of services to former prisoners living in high-risk neighborhoods. Also, caseload size and the intensity of supervision and services should take into account the characteristics of the neighborhoods in which parolees live. The analysis considered the link between baseline neighborhood characteristics (first post-prison neighborhood) and cumulative exposure to neighborhood conditions during time on parole. The analysis of baseline neighborhood characteristics was based on the full population of 11,064 people released on parole in Michigan in 2003; and the analysis of time-varying neighborhood characteristics was based on a sample of 1,848. 20 tables, 6 figures, 73 references, and appended sampling methods

Date Published: October 1, 2011