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arXiv · 2404.18786

Randomization-based confidence sets for the local average treatment effect

P. M. Aronow·Haoge Chang·Patrick Lopatto
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Abstract

We consider the problem of generating confidence sets in randomized experiments with noncompliance. We show that a refinement of a randomization-based procedure proposed by Imbens and Rosenbaum (2005) has desirable properties. Namely, we show that using a studentized Anderson--Rubin-type statistic as a test statistic yields confidence sets that are finite-sample exact under treatment effect homogeneity, and remain asymptotically valid for the Local Average Treatment Effect when the treatment effect is heterogeneous. We provide a uniform analysis of this procedure and efficient algorithms to construct the confidence set.

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P. M. Aronow, Haoge Chang, Patrick Lopatto. 2024-04-29. Randomization-based confidence sets for the local average treatment effect. https://arxiv.org/abs/2404.18786

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