Association for Public Policy Analysis & Management

Panel: Regression Discontinuity Designs (RDDs): Extensions to Reduce Bias and Increase Precision

(Tools of Analysis: Methods, Data, Informatics and Research Design)

Regression discontinuity designs (RDDs) are increasingly used in public policy analysis to evaluate the effects of programs and interventions. For example, the U.S. Department of Education (ED) commissioned two large-scale evaluations of education interventions that use an RDD to calculate impacts on student outcomes—The Impact Evaluation of Title I Supplemental Educational Services and the Impact Evaluation of School Improvement Grants (SIG). This panel discusses three extensions of RDDs: (1) calculating standard errors using a new bootstrapping method, (2) adding a pretest or nonequivalent comparison group, and (3) analyzing multiple assignment variables in the context of optimal bandwidth selection. This panel directly relates to the conference theme of evidence-based policy because the first paper was written as part of ED’s large-scale evaluation of SIG, and all three papers explore methods that can reduce bias and increase precision, thereby increasing the usefulness of RDDs in calculating impacts of programs and interventions.