723 citations · 852 across the 39 of their papers we have counts for
14 papers · 1 filter
Debiasing and -tests for synthetic control inference on average causal effects
Victor Chernozhukov, Kaspar Wuthrich, Yinchu Zhu
We propose a practical and robust method for making inferences on average treatment effects estimated by synthetic controls. We develop a -fold cross-fitting procedure for bias…
Inference for Heterogeneous Effects using Low-Rank Estimation of Factor Slopes
Victor Chernozhukov, Christian Hansen, Yuan Liao +1
We study a panel data model with general heterogeneous effects where slopes are allowed to vary across both individuals and over time. The key dimension reduction assumption we emp…
Closing the U.S. gender wage gap requires understanding its heterogeneity
Philipp Bach, Victor Chernozhukov, Martin Spindler
In 2016, the majority of full-time employed women in the U.S. earned significantly less than comparable men. The extent to which women were affected by gender inequality in earning…
Distribution Regression with Sample Selection, with an Application to Wage Decompositions in the UK
Victor Chernozhukov, Iván Fernández-Val, Siyi Luo
We develop a distribution regression model under endogenous sample selection. This model is a semi-parametric generalization of the Heckman selection model. It accommodates much ri…
Valid Simultaneous Inference in High-Dimensional Settings (with the hdm package for R)
Philipp Bach, Victor Chernozhukov, Martin Spindler
Due to the increasing availability of high-dimensional empirical applications in many research disciplines, valid simultaneous inference becomes more and more important. For instan…
Automatic Debiased Machine Learning of Causal and Structural Effects
Victor Chernozhukov, Whitney K Newey, Rahul Singh
Many causal and structural effects depend on regressions. Examples include policy effects, average derivatives, regression decompositions, average treatment effects, causal mediati…