International Fellows

Victor Chernozhukov

MIT

Selected Publications

Semiparametric estimation of structural functions in nonseparable triangular models

This paper introduces two classes of semiparametric triangular systems with nonadditively separable unobserved heterogeneity. They are […]

Victor Chernozhukov, Ivan Fernandez-Val, Whitney K. Newey, Sami Stouli, Francis Vella
8 November 2017 | CWP48/17
Nonseparable multinomial choice models in cross-section and panel data

Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze […]

Victor Chernozhukov, Ivan Fernandez-Val, Whitney K. Newey
27 June 2017 | CWP33/17
Quantreg.nonpar: an R package for performing nonparametric series quantile regression

The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on partially […]

Michael Lipsitz, Alexandre Belloni, Victor Chernozhukov, Ivan Fernandez-Val
6 June 2017 | CWP29/17
Double/debiased machine learning for treatment and structural parameters

We revisit the classic semiparametric problem of inference on a low dimensional parameter θ0 in the […]

Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney K. Newey, James Robins
2 June 2017 | CWP28/17
Generic inference on quantile and quantile effect functions for discrete outcomes

This paper provides a method to construct simultaneous confidence bands for quantile and quantile effect functions […]

Victor Chernozhukov, Ivan Fernandez-Val, Blaise Melly, Kaspar Wüthrich
19 May 2017 | CWP23/17
Confidence bands for coefficients in high dimensional linear models with error-in-variables

We study high-dimensional linear models with error-in-variables. Such models are motivated by various applications in econometrics, […]

Alexandre Belloni, Victor Chernozhukov, Abhishek Kaul
17 May 2017 | CWP22/17
Double machine learning for treatment and causal parameters

Most modern supervised statistical/machine learning (ML) methods are explicitly designed to solve prediction problems very well. […]

Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney K. Newey
27 September 2016 | CWP49/16
Inference in high dimensional panel models with an application to gun control

We consider estimation and inference in panel data models with additive unobserved individual specific heterogeneity in […]

Alexandre Belloni, Victor Chernozhukov, Christian Hansen, Damian Kozbur
15 September 2016 | Journal Article

Previous version

Inference in high dimensional panel models with an application to gun control
Alexandre Belloni, Victor Chernozhukov, Christian Hansen, Damian Kozbur
31 December 2014 | CWP50/14
Conditional quantile processes based on series or many regressors

Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. […]

Alexandre Belloni, Victor Chernozhukov, Denis Chetverikov, Ivan Fernandez-Val
30 August 2016 | CWP46/16

Previous version

Conditional quantile processes based on series or many regressors
Alexandre Belloni, Victor Chernozhukov, Ivan Fernandez-Val
27 May 2011 | CWP19/11
Central limit theorems and bootstrap in high dimensions

In this paper, we derive central limit and bootstrap theorems for probabilities that centered high-dimensional vector […]

Victor Chernozhukov, Denis Chetverikov, Kengo Kato
26 August 2016 | CWP39/16

Previous version

Central limit theorems and bootstrap in high dimensions
Victor Chernozhukov, Denis Chetverikov, Kengo Kato
31 December 2014 | CWP49/14