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Type of Publication: | Journal article |
Publication status: | Published |
Author: | Pohlmeier, Winfried; Seiberlich, Ruben; Uysal, Selver Derya |
Year of publication: | 2016 |
Published in: | Computational Statistics & Data Analysis ; 100 (2016). - pp. 512-525. - ISSN 0167-9473. - eISSN 1872-7352 |
DOI (citable link): | https://dx.doi.org/10.1016/j.csda.2014.09.015 |
Summary: |
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.
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Subject (DDC): | 330 Economics |
Bibliography of Konstanz: | Yes |
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POHLMEIER, Winfried, Ruben SEIBERLICH, Selver Derya UYSAL, 2016. A simple and successful shrinkage method for weighting estimators of treatment effects. In: Computational Statistics & Data Analysis. 100, pp. 512-525. ISSN 0167-9473. eISSN 1872-7352. Available under: doi: 10.1016/j.csda.2014.09.015
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