Optimal Screening in Experiments with Partial Compliance
Econometrics
2025-12-11 v1
Abstract
This note studies optimal experimental design under partial compliance when experimenters can screen participants prior to randomization. Theoretical results show that retaining all compliers and screening out all non-compliers achieves three complementary aims: (i) the Local Average Treatment Effect is the same as the standard 2SLS estimator with no screening; (ii) median bias is minimized; and (iii) statistical power is maximized. In practice, complier status is unobserved. We therefore discuss feasible screening strategies and propose a simple test for screening efficacy. Future work will conduct an experiment to demonstrate the feasibility and advantages of the optimal screening design.
Keywords
Cite
@article{arxiv.2512.09206,
title = {Optimal Screening in Experiments with Partial Compliance},
author = {Christopher Carter and Adeline Delavande and Mario Fiorini and Peter Siminski and Patrick Vu},
journal= {arXiv preprint arXiv:2512.09206},
year = {2025}
}