International Fellows

Victor Chernozhukov

MIT

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Selected Publications

Working Paper
Single market non-parametric identification of multi-attribute hedonic equilibrium models

This paper derives conditions under which preferences and technology are nonparametrically identified in hedonic equilibrium models, […]

Victor Chernozhukov, Alfred Galichon, Marc Henry, Brendan Pass
11 June 2019 | CWP27/19
LASSO-Driven Inference in Time and Space

We consider the estimation and inference in a system of high-dimensional regression equations allowing for temporal […]

Victor Chernozhukov, Wolfgang Härdle, Chen Huang, Weining Wang
29 April 2019 | CWP20/19

Previous version

LASSO-driven inference in time and space
Victor Chernozhukov, Wolfgang Härdle, Chen Huang, Weining Wang
20 June 2018 | CWP36/18
Best linear approximations to set identified functions: with an application to the gender wage gap

This paper provides inference methods for best linear approximations to functions which are known to lie […]

Arun Chandrasekhar, Victor Chernozhukov, Francesca Molinari, Paul Schrimpf
18 February 2019 | CWP09/19

Previous version

Inference for best linear approximations to set identified functions
Arun Chandrasekhar, Victor Chernozhukov, Francesca Molinari, Paul Schrimpf
17 December 2012 | CWP43/12
Network and panel quantile effects via distribution regression

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

Victor Chernozhukov, Ivan Fernandez-Val, Martin Weidner
12 December 2018 | CWP70/18

Latest version

Network and Panel Quantile Effects Via Distribution Regression
Victor Chernozhukov, Ivan Fernandez-Val, Martin Weidner
15 June 2020 | CWP27/20

Previous version

Network and panel quantile effects via distribution regression
Victor Chernozhukov, Ivan Fernandez-Val, Martin Weidner
22 March 2018 | CWP21/18
Distribution regression with sample selection, with an application to wage decompositions in the UK

We develop a distribution regression model under endogenous sample selection. This model is a semiparametric generalization […]

Victor Chernozhukov, Ivan Fernandez-Val, Siyi Luo
29 November 2018 | CWP68/18
Inference on causal and structural parameters using many moment inequalities

This paper considers the problem of testing many moment inequalities where the number of moment inequalities, […]

Victor Chernozhukov, Denis Chetverikov, Kengo Kato
18 October 2018 | CWP60/18

Previous version

Testing many moment inequalities
Victor Chernozhukov, Denis Chetverikov, Kengo Kato
26 August 2016 | CWP42/16
Simultaneous inference for Best Linear Predictor of the Conditional Average Treatment Effect and other structural functions

This paper provides estimation and inference methods for a structural function, such as Conditional Average Treatment […]

Victor Chernozhukov, Vira Semenova
4 July 2018 | CWP40/18
Plug-in regularized estimation of high dimensional parameters in nonlinear semiparametric models

We develop a theory for estimation of a high-dimensional sparse parameter defined as a minimizer of […]

Victor Chernozhukov, Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis
4 July 2018 | CWP41/18
LASSO-driven inference in time and space

We consider the estimation and inference in a system of high-dimensional regression equations allowing for temporal […]

Victor Chernozhukov, Wolfgang Härdle, Chen Huang, Weining Wang
20 June 2018 | CWP36/18

Latest version

LASSO-Driven Inference in Time and Space
Victor Chernozhukov, Wolfgang Härdle, Chen Huang, Weining Wang
29 April 2019 | CWP20/19
High-dimensional econometrics and regularized GMM

This chapter presents key concepts and theoretical results for analyzing estimation and inference in high-dimensional models. […]

Alexandre Belloni, Victor Chernozhukov, Denis Chetverikov, Christian Hansen, Kengo Kato
12 June 2018 | CWP35/18
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