Roundtable: Regression Discontinuity Design in Shaping Future Justice Policy

Session Submission Type: Roundtable Session

Abstract/Description

This roundtable session aims to explore the potential for greater use of the Regression Discontinuity Design (RDD) to rigorously evaluate justice policies and interventions. RDD is a quasi-experimental approach that capitalizes on the assignment to treatment and control conditions based on a cutoff score or threshold on a numeric variable. RDD offers a powerful approach, especially in situations in which ethical or practical constraints preclude randomization. The session will commence with an introduction to the RDD methodology, emphasizing its unique ability to yield causal inferences by comparing outcomes for individuals just above and below an established threshold. We will review the major categories of RDD studies that have been used in the justice literature, including studies based on risk assessment tools for offenders, studies based on juvenile/adult cutoffs for sentencing, and spatial discontinuity studies. Participants will engage in a critical discussion of the method’s strengths, limitations, challenges, and relevance to policy formation. The roundtable will conclude by illustrating a roadmap for incorporating RDD in future justice policy research, encouraging evidence-based reforms that are both effective and equitable. The session is designed to foster dialogue among researchers, practitioners, and policymakers who are committed to developing data-driven criminal justice policies and interventions.

Sub Unit

• Area XIV. Roundtables

Chair

• Trent Baskerville, WestEd Justice & Prevention Research Center

Discussants

• Trevor Fronius, WestEd

• Ojmarrh Mitchell, University of California, Irvine

• Sean Tanner, WestEd

• Steven Belenko, Temple University

• Shawn David Bushway, University at Albany