This study examined the correlates of sentence severity for convicted sex offenders under sentencing guidelines, contrasted with individuals convicted of non-sexual, violent offenses.
Drawing on 7 years of data from the Pennsylvania Commission on Sentencing, the study used a logit-negative binomial hurdle model to examine the predictors of incarceration and sentence length, and an accompanying Oaxaca-Blinder decomposition of the gap in sentencing outcomes between the groups. The study then implemented a quantile regression framework to examine variation in effects across the distribution of sentence lengths. All analyses were contrasted with a matched sample of violent offenders to consider the extent to which estimated associations were unique to sex offenders. The analyses suggest several predictors of sentence severity for sex offenders, and that these predictors vary between the incarceration and sentence length decisions. In comparing effects for sex and matched violent offenders, divergent effects were observed for both case and offender characteristics. An Oaxaca-Blinder decomposition suggests that differences in the coefficient estimates accounted for less than one-fifth of the gap in average sentencing outcomes between sex and violent offenders. Subsequent quantile regressions indicate that these effects varied considerably over the sentence length distribution in ways that are not captured or obscured by the hurdle models. The study determined that predictors of sentence severity for sex offenders and points of divergence from violent offenders were congruent with the notion that judges utilize crime-specific stereotypes in arriving at sentencing decisions. Further, the application of quantile regression following point-based estimation can reveal meaningful patterns in sentencing disparities. (publisher abstract modified)
Report (Grant Sponsored)
Date Published: January 1, 2018