213 citations · 311 across the 5 of their papers we have counts for
5 papers
Uniform Inference in High-Dimensional Gaussian Graphical Models
Sven Klaassen, Jannis Kück, Martin Spindler +1
Graphical models have become a very popular tool for representing dependencies within a large set of variables and are key for representing causal structures. We provide results fo…
Estimation and Inference on Heterogeneous Treatment Effects in High-Dimensional Dynamic Panels under Weak Dependence
Vira Semenova, Matt Goldman, Victor Chernozhukov +1
This paper provides estimation and inference methods for a conditional average treatment effects (CATE) characterized by a high-dimensional parameter in both homogeneous cross-sect…
Inference for High-Dimensional Sparse Econometric Models
Alexandre Belloni, Victor Chernozhukov, Christian Hansen
This article is about estimation and inference methods for high dimensional sparse (HDS) regression models in econometrics. High dimensional sparse models arise in situations where…
LASSO Methods for Gaussian Instrumental Variables Models
Alexandre Belloni, Victor Chernozhukov, Christian Hansen
In this note, we propose to use sparse methods (e.g. LASSO, Post-LASSO, sqrt-LASSO, and Post-sqrt-LASSO) to form first-stage predictions and estimate optimal instruments in linear…
Extremal quantile regression
Victor Chernozhukov
Quantile regression is an important tool for estimation of conditional quantiles of a response Y given a vector of covariates X. It can be used to measure the effect of covariates…