Limit theorems of matching estimators with a fixed number of matches
Statistics Theory
2026-05-21 v2 Econometrics
Statistics Theory
Abstract
This paper re-examines the limit theorems of Abadie and Imbens for nearest-neighbor matching estimators of average treatment effects with a fixed number of matches. We establish, for the first time, a non-normalized central limit theorem (CLT) with an explicitly calculated limiting variance. The key ingredients are to prove the convergence of the normalizing statistic appearing in the CLT of Abadie and Imbens to its mean, and to calculate the closed form of the limit of this mean. The former closes a gap in the argument of an unpublished work (Abadie and Imbens, 2002), while the latter resolves a question raised in Abadie and Imbens (2006).
Keywords
Cite
@article{arxiv.2411.05758,
title = {Limit theorems of matching estimators with a fixed number of matches},
author = {Songliang Chen and Fang Han},
journal= {arXiv preprint arXiv:2411.05758},
year = {2026}
}
Comments
In this version, we close a gap in the original submission