The Effect of Incarceration on Re-Offending: Evidence from a Natural Experiment in Pennsylvania
By Dan Nagin, G. M. Snodgrass. 2013
89 citations recorded by the source corpus.
ObjectivesThis paper uses a sample of convicted offenders from Pennsylvania to estimate the effect of incarceration on post-release criminality.MethodsTo do so, we capitalize on a feature of the criminal justice system in Pennsylvania—the county-level randomization of cases to judges. We begin by identifying five counties in which there is substantial variation across judges in the uses of incarceration, but no evidence indicating that the randomization process had failed. The estimated effect of incarceration on rearrest is based on comparison of the rearrest rates of the caseloads of judges with different proclivities for the use of incarceration.ResultsUsing judge as an instrumental variable, we estimate a series of confidence intervals for the effect of incarceration on one year, two year, five year, and ten year rearrest rates.ConclusionsOn the whole, there is little evidence in our data that incarceration impacts rearrest.
Subfields: Sociology and Political Science, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/5ed60c44d784fc48532f9d7fe182baef1bb1a3a6
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In Sociology and Political Science
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Citations in the corpus
- Examining Prison Effects on Recidivism: A Regression Discontinuity Approach (2017, unknown): “…findings, particularly when paired with recent assessments of sanction effects (e.g. Bales & Piquero, 2012; Cochran et al., 2014; Nagin et al., 2009; Nagin & Snodgrass, 2013), are straightforward: The effect of prison on reoffending is unclear and may be null or contribute to more rather than less…”
- ESTIMATION IN AN INSTRUMENTAL VARIABLES MODEL WITH TREATMENT EFFECT HETEROGENEITY (2012, methodology): “For instance, the instruments could be judge indicators as in Aizer and Doyle, Jr. (2011) and Nagin and Snodgrass (2011) to instrument for length of sentence or incarceration.”