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A simple and successful shrinkage method for weighting estimators of treatment effects

Winfried Pohlmeier (), Ruben Seiberlich () and Selver Derya Uysal

Computational Statistics & Data Analysis, 2016, vol. 100, issue C, 512-525

Abstract: A simple shrinkage method is proposed to improve the performance of weighting estimators of the average treatment effect. As the weights in these estimators can become arbitrarily large for the propensity scores close to the boundaries, three different variants of a shrinkage method for the propensity scores are analyzed. The results of a comprehensive Monte Carlo study demonstrate that this simple method substantially reduces the mean squared error of the estimators in finite samples, and is superior to several popular trimming approaches over a wide range of settings.

Keywords: Average treatment effect; Econometric evaluation; Penalizing; Propensity score; Shrinkage (search for similar items in EconPapers)
Date: 2016
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Working Paper: A Simple and Successsful Shrinkage Method for Weighting Estimators of Treatment Effects (2014) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:100:y:2016:i:c:p:512-525

DOI: 10.1016/j.csda.2014.09.015

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