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L2-Boosting for Economic Applications

Ye Luo¹; Martin Spindler²

¹ Department of Economics, University of Florida, PO Box 117140, Gainesville, FL 32611 (e-mail: ) · ² Hamburg Business School, University of Hamburg, Hamburg Center for Health Economics (hche), Moorweidenstrasse 18, 20148 Hamburg, Germany and Max Planck Society (e-mail: )

We present the L2Boosting algorithm and two variants, namely post-Boosting and orthogonal Boosting. Building on results in Ye and Spindler (2016), we demonstrate how boosting can be used for estimation and inference of low-dimensional treatment effects. In particular, we consider estimation of a treatment effect in a setting with very many controls and in a setting with very many instruments. We provide simulations and analyze two real applications. We compare the results with Lasso and find that boosting performs quite well. This encourages further use of boosting for estimation of treatment effects in high-dimensional settings.

DOI

10.1257/aer.p20171040

Volume

107 (5)

Pages

270-273

Language

en

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