Using Symmetric Prediction of Endogenous Subgroups for Causal Inferences About Program Effects Under Robust Assumptions

Abstract

To answer “what works?” questions about policy interventions based on an experimental design, Peck (2003) proposes to use baseline characteristics to symmetrically divide treatment and control group members into subgroups defined by endogenously determined postrandom assignment events. Symmetric prediction of these subgroups in both experimental arms ensures the internal validity of the subgroup impacts estimates but leaves the external validity of the findings in doubt. A final step of the procedure solves for impacts on actual subgroups using a system of equations that is underidentified without further assumptions. We address these assumptions by first extending the methodology to encompass three rather than two endogenous subgroups and then proposing plausible assumptions for deriving impacts for actual endogenous subgroups. We also consider how the first-stage prediction process can be structured to better support the accuracy of the assumptions.