723 citations · 5.4k across the 110 of their papers we have counts for
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An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls
Victor Chernozhukov, Kaspar Wüthrich, Yinchu Zhu
We introduce new inference procedures for counterfactual and synthetic control methods for policy evaluation. We recast the causal inference problem as a counterfactual prediction…
Simultaneous Confidence Intervals for High-dimensional Linear Models with Many Endogenous Variables
Alexandre Belloni, Christian Hansen, Whitney Newey
High-dimensional linear models with endogenous variables play an increasingly important role in recent econometric literature. In this work we allow for models with many endogenous…
Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India
Victor Chernozhukov, Mert Demirer, Esther Duflo +1
We propose strategies to estimate and make inference on key features of heterogeneous effects in randomized experiments. These key features include best linear predictors of the ef…
Detailed proof of Nazarov's inequality
Victor Chernozhukov, Denis Chetverikov, Kengo Kato
The purpose of this note is to provide a detailed proof of Nazarov's inequality stated in Lemma A.1 in Chernozhukov, Chetverikov, and Kato (2017, Annals of Probability).
Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models
Victor Chernozhukov, Iván Fernández-Val, Whitney Newey +2
Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modelling of complex structural relationships. However,…
Identification of hedonic equilibrium and nonseparable simultaneous equations
Victor Chernozhukov, Alfred Galichon, Marc Henry +1
This paper derives conditions under which preferences and technology are nonparametrically identified in hedonic equilibrium models, where products are differentiated along more th…
Pivotal Estimation via Self-Normalization for High-Dimensional Linear Models with Error in Variables
Alexandre Belloni, Abhishek Kaul, Mathieu Rosenbaum
We propose a new estimator for the high-dimensional linear regression model with observation error in the design where the number of coefficients is potentially larger than the sam…
Nonseparable Multinomial Choice Models in Cross-Section and Panel Data
Victor Chernozhukov, Iván Fernández-Val, Whitney Newey
Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze identification of binary and multinomial choice models…
Confidence Bands for Coefficients in High Dimensional Linear Models with Error-in-variables
Alexandre Belloni, Victor Chernozhukov, Abhishek Kaul
We study high-dimensional linear models with error-in-variables. Such models are motivated by various applications in econometrics, finance and genetics. These models are challengi…
Debiased Machine Learning of Conditional Average Treatment Effects and Other Causal Functions
Vira Semenova, Victor Chernozhukov
This paper provides estimation and inference methods for the best linear predictor (approximation) of a structural function, such as conditional average structural and treatment ef…
Double/Debiased/Neyman Machine Learning of Treatment Effects
Victor Chernozhukov, Denis Chetverikov, Mert Demirer +3
Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, and Newey (2016) provide a generic double/de-biased machine learning (DML) approach for obtaining valid inferential statements ab…