A Simple and Successul Method to Shrink the Weight

We propose a simple way to improve the efficiency of the average treatment effect on propensity score based estimators. As the weights become arbitrarily large for the propensity scores being close to one or zero, we propose to shrink the propensity scores away from these boundaries. Using a comprehensive Monte Carlo study we show that this simple method substantially reduces the mean squared error of the estimators in finite samples.

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Year of publication:	2013-03-23
Authors:	Pohlmeier, Winfried ; Seiberlich, Ruben R. ; Uysal, S. Derya
Institutions:	Fachbereich Wirtschaftswissenschaften, Universität Konstanz
Subject:	Econometric evaluation \| propensity score \| penalizing \| shrinkage \| average treatment effect

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Extent:	application/pdf
Series:	Working Paper Series of the Department of Economics, University of Konstanz.
Type of publication:	Book / Working Paper
Notes:	Number 2013-05 41 pages
Classification:	C14 - Semiparametric and Nonparametric Methods ; C21 - Cross-Sectional Models; Spatial Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010632916