Labor Force Participation and Crime Among Severe and Violent Former Prisoners

This grant is funded under NIJ's 2013 Ph.D. Graduate Research Fellowship (GRF) Program, which provides awards to accredited academic universities that offer research-based doctoral degrees in disciplines relevant to NIJ's mission. This project examines the relationship between work and crime among male former prisoners. This study examines whether self-selection bias and unobserved heterogeneity contribute to weak evaluation findings. This study uses data from the Serious and Violent Offender Reentry Initiative (n = 1,697). Men in this sample faced multiple barriers to employment before entering prison, due to extensive criminal records, low educational attainment, and limited work experience. This project employs advanced modeling techniques that increase the ability to draw causal inferences from observational data. First, this study tests whether unobserved heterogeneity and treatment noncompliance contribute to jobs programs weak treatment effects. It uses semi-parametric group modeling and propensity score matching to balance participants and nonparticipants on employment and criminal activity. Lifetime arrest data from administrative records are used to model respondents' prior offending trajectories. Baseline interview data are used to balance respondents on propensity to receive employment services. After balancing respondents within trajectory groups, this study employs duration models to test the effect of three types of employment activities on recidivism. Findings will be of interest to practitioners, policymakers, and academics from multiple disciplines. Results may enhance theoretical explanations of the work-crime relationship. Findings can inform practice by identifying strategies to improve employment programming and to make work pay for former prisoners. Results can inform policies to reduce prisoners' financial stress and increase their incentives to seek work. Second, this study tests whether financial problems mediate the work-crime relationship. Structural equation modeling is used to model mens labor force attachment, job quality, financial challenges, and emotional wellbeing. Models test whether financial problems diminish the crime-reducing effects of employment for men who remain weakly attached to the labor force. Multiple indicators for each latent construct reduce bias due to measurement error. Measures collected at multiple time points capture changes in men's risk factors due to changes in their living conditions and cognitive emotional states. Fixed effects estimation reduces time-invariant unobserved heterogeneity. Proposed dissemination outlets include submission of the dissertation to NIJ, presentations at academic conference presentations, a practitioner-oriented workshop, manuscript submissions to peer-reviewed journal publications, and a web-based tutorial detailing the study's analytic techniques, findings, and implications. ca/ncf