L2-Boosting for Economic Applications
- (pp. 270-73)
Abstract
We present the L2-Boosting 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.Citation
Luo, Ye, and Martin Spindler. 2017. "L2-Boosting for Economic Applications." American Economic Review, 107 (5): 270-73. DOI: 10.1257/aer.p20171040Additional Materials
JEL Classification
- C21 Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
- C51 Model Construction and Estimation