On propensity score matching with a diverging number of matches

Yihui He and Fang Han

Biometrika, 2024, vol. 111, issue 4, 1421-1428

Abstract: This paper re-examines the work of Abadie & Imbens (2016) on propensity score matching for average treatment effect estimation. We explore the asymptotic behaviour of these estimators when the number of nearest neighbours, M, grows with the sample size. It is shown, while not 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 admits some special structures, echoing the insight of Hahn (1998).

Keywords: Diverging-M asymptotics; Le Cam’s discretization device; Le Cam’s third lemma; Semiparametric efficiency (search for similar items in EconPapers)
Date: 2024
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