Unbiased Regression-Adjusted Estimation of Average Treatment Effects in Randomized Controlled Trials

Alberto Abadie, Mehrdad Ghadiri, Ali Jadbabaie and Mahyar JafariNodeh

Papers from arXiv.org

Abstract: This article introduces a leave-one-out regression adjustment (LOORA) for estimating average treatment effects in randomized controlled trials. In finite samples, LOORA removes the bias of conventional regression adjustment and yields exact variance formulas for regression-adjusted Horvitz-Thompson and difference-in-means estimators. Ridge regularization curbs the influence of high-leverage observations, improving stability and precision in small samples. In large samples, LOORA matches the variance of the regression-adjusted estimator in Lin (2013) while remaining exactly unbiased. Two within-subject experimental applications, each providing a realistic joint distribution of potential outcomes as ground truth, show that LOORA removes substantial bias and achieves confidence interval coverage close to the nominal level.

Date: 2025-11, Revised 2026-05
New Economics Papers: this item is included in nep-ecm and nep-exp
References: Add references at CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2511.03236 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2511.03236

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().