Ensemble Methods for Causal Effects in Panel Data Settings
- (pp. 65-70)
Abstract
In many prediction problems researchers have found that combinations of prediction methods ("ensembles") perform better than individual methods. In this paper we apply these ideas to synthetic control type problems in panel data. Here a number of conceptually quite different methods have been developed. We compare the predictive accuracy of three methods with an ensemble method and find that the latter dominates. These results show that ensemble methods are a practical and effective method for the type of data configurations typically encountered in empirical work in economics, and that these methods deserve more attention.Citation
Athey, Susan, Mohsen Bayati, Guido Imbens, and Zhaonan Qu. 2019. "Ensemble Methods for Causal Effects in Panel Data Settings." AEA Papers and Proceedings, 109: 65-70. DOI: 10.1257/pandp.20191069Additional Materials
JEL Classification
- C23 Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
- C33 Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models