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Victor Chernozhukov
Victor Chernozhukov
Professor, Department of Economics + Center for Statistics and Data Science, MIT;
Zweryfikowany adres z mit.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Double/De-Biased Machine Learning for Treatment and Causal Parameters
V Chernozhukov, D Chetverikov, M Demirer, E Duflo, C Hansen, ...
Econometrics Journal; 2018; arXiv preprint arXiv:1608.00060, 2016
3301*2016
Inference on treatment effects after selection amongst high-dimensional controls
A Belloni, V Chernozhukov, C Hansen
The Review of Economic Studies 2013; ArXiv 2011, 2011
19632011
Inference on counterfactual distributions
V Chernozhukov, I Fernandez-Val, B Melly
Econometrica, 2013 (ArXiv 2009) 81 (6), 2205–2268, 2009
1380*2009
Optimal Targeted Lockdowns in a Multi-Group SIR Model
D Acemoglu, V Chernozhukov, I Werning, MD Whinston
American Economic Review: Insights, 2021
1298*2021
An IV model of quantile treatment effects
V Chernozhukov, C Hansen
Econometrica, 245-261, 2005
12952005
Sparse models and methods for optimal instruments with an application to eminent domain
A Belloni, D Chen, V Chernozhukov, C Hansen
Econometrica 2012 (ArXiv 2010) 80 (6), 2369-2429, 2010
12422010
High-Dimensional Methods and Inference on Structural and Treatment Effects
A Belloni, V Chernozhukov, C Hansen
The Journal of Economic Perspectives 28 (2), 29-50, 2014
10932014
An MCMC approach to classical estimation
V Chernozhukov, H Hong
Journal of econometrics 115 (2), 293-346, 2003
10032003
Least squares after model selection in high-dimensional sparse models
A Belloni, V Chernozhukov
Bernoulli 2013 (ArXiv 2009) 19 (2), 521-547, 2013
8982013
Estimation and confidence regions for parameter sets in econometric models
V Chernozhukov, H Hong, E Tamer
Econometrica 75 (5), 1243–1284, 2007
870*2007
Square-root lasso: pivotal recovery of sparse signals via conic programming
A Belloni, V Chernozhukov, L Wang
Biometrika 2011 (ArXiv 2010) 98 (4), 791-806, 2011
7682011
ℓ1-penalized quantile regression in high-dimensional sparse models
A Belloni, V Chernozhukov
The Annals of Statistics 2011 (Arxiv 2009) 39 (1), 82-130, 2011
7542011
Instrumental quantile regression inference for structural and treatment effect models
V Chernozhukov, C Hansen
Journal of Econometrics 132 (2), 491-525, 2006
7352006
Instrumental variable quantile regression: A robust inference approach
V Chernozhukov, C Hansen
Journal of Econometrics 142 (1), 379-398, 2008
717*2008
Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments
V Chernozhukov, M Demirer, E Duflo, I Fernandez-Val
Econometrica (to appear); arXiv preprint arXiv:1712.04802, 2024
673*2024
Quantile and probability curves without crossing
V Chernozhukov, I Fernandez-Val, A Galichon
Econometrica, 1093-1125, 2010
6482010
Double/debiased/neyman machine learning of treatment effects
V Chernozhukov, D Chetverikov, M Demirer, E Duflo, C Hansen, ...
American Economic Review 107 (5), 261-65, 2017
6142017
GAUSSIAN APPROXIMATIONS AND MULTIPLIER BOOTSTRAP FOR MAXIMA OF SUMS OF HIGH-DIMENSIONAL RANDOM VECTORS
V Chernozhukov, D Chetverikov, K Kato
Annals of Statistics, 2013 (ArXiv 2013) 41 (6), 2786-2819, 2013
6052013
Quantile regression under misspecification, with an application to the US wage structure
J Angrist, V Chernozhukov, I Fernandez-Val
Econometrica 72 (2), 539–563, 2007
5912007
Intersection bounds: estimation and inference
V Chernozhukov, S Lee, AM Rosen
Econometrica 81, 667-736, 2013
5662013
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Prace 1–20