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On propensity score matching with a diverging number of matches

Yihui He, Fang Han

arXiv 22 Oct 2023 · Mathematics — Statistics Theory · publishedBiometrika (2024) · 1 citations (OpenAlex)

arXiv:2310.14142 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper reexamines Abadie and Imbens (2016)'s work on propensity score matching for average treatment effect estimation. We explore the asymptotic behavior of these estimators when the number of nearest neighbors, $M$, grows with the sample size. It is shown, hardly surprising but technically nontrivial, that the modified estimators can improve upon the original fixed-$M$ estimators in terms of efficiency. Additionally, we demonstrate the potential to attain the semiparametric efficiency lower bound when the propensity score achieves "sufficient" dimension reduction, echoing Hahn (1998)'s insight about the role of dimension reduction in propensity score-based causal inference.

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47
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Abadie, A. and Imbens, G. W (2016) Matching on the estimated propensity score1.000498100%
2Hahn, J (1998) On the role of the propensity score in efficient semiparametric estimation of average treatment effects1.00074100%
3Abadie, A. and Imbens, G. W (2006) Large sample properties of matching estimators for average treatment effects0.81142100%
4Andreou, E. and Werker, B. J (2012) An alternative asymptotic analysis of residual-based statistics0.81142100%
5Lin, Z., Ding, P., and Han, F (2023) Estimation based on nearest neighbor matching: from density ratio to average treatment effect self0.64441100%
6Le Cam, L. and Yang, G. L (2000) Asymptotics in Statistics: Some Basic Concepts (2nd ed.)0.51121100%
7Abadie, A. and Imbens, G. W (2011) Bias-corrected matching estimators for average treatment effects0.51121100%
8Abadie, A. and Imbens, G. W (2012) A martingale representation for matching estimators0.51121100%
9Lin, Z. and Han, F (2022) On regression-adjusted imputation estimators of the average treatment effect self0.51121100%
10van der Vaart, A. W (1998) Asymptotic Statistics0.51121100%

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arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1On the consistency of bootstrap for matching estimators0.40511
2On the limiting variance of matching estimators0.40511