Scholars have presented concerns about potential for racial bias in risk assessments as a result of the inclusion of static factors, such as criminal history in risk assessments. The purpose of this study was to examine the extent to which static factors add incremental validity to the dynamic factors in criminogenic risk assessments. This study examined the Youth Level of Service/Case Management Inventory (YLS/CMI) in a sample of 1,270 youth offenders from a medium-sized Midwestern county between June 2004 and November 2013. Logistic regression was used to determine the predictive validity of the YLS/CMI and the individual contribution of static and dynamic domains of the assessment. Results indicated that the static domain differentially predicted recidivism for Black and White youth. In particular, the static domain was a significant predictor of recidivism for White youth, but this was not the case for Black youth. The dynamic domain significantly predicted recidivism for both Black and White offenders, and static risk factors improved prediction of recidivism for White youth, but not for Black youth.
Nowcasting US GDP Using Tree-Based Ensemble Models and Dynamic Factors
