Using a Satisficing Model of Experimenter Decision-Making to Guide Finite-Sample Inference for Compromised Experiments
This paper presents a simple decision-theoretic economic approach for analyzing social experiments with compromised random assignment protocols that are only partially documented. We model administratively constrained experimenters who satisfice in seeking covariate balance. We develop design-based small-sample hypothesis tests that use worst-case (least favorable) randomization null distributions. Our approach accommodates a variety of compromised experiments, including imperfectly documented re-randomization designs. To make our analysis concrete, we focus much of our discussion on the influential Perry Preschool Project. We reexamine previous estimates of program effectiveness using our methods. The choice of how to model reassignment vitally affects inference.
Published Versions
James J Heckman & Ganesh Karapakula, 2021. "Using a satisficing model of experimenter decision-making to guide finite-sample inference for compromised experiments [Sampling-based versus design-based uncertainty in regression analysis]," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 1-39. citation courtesy of