Limit theorems of matching estimators with a fixed number of matches

Fuente: arXiv
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Main Authors: Chen, Songliang, Han, Fang
Format: Preprint
Published: 2024
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author Chen, Songliang
Han, Fang
author_facet Chen, Songliang
Han, Fang
contents 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 The former closes a gap in the argument of an unpublished work (Abadie and Imbens, 2002), while the latter resolves a question raised in Abadie and Imbens (2006).
format Preprint
id arxiv_https___arxiv_org_abs_2411_05758
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Limit theorems of matching estimators with a fixed number of matches
Chen, Songliang
Han, Fang
Statistics Theory
Econometrics
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 The former closes a gap in the argument of an unpublished work (Abadie and Imbens, 2002), while the latter resolves a question raised in Abadie and Imbens (2006).
title Limit theorems of matching estimators with a fixed number of matches
topic Statistics Theory
Econometrics
url https://arxiv.org/abs/2411.05758