| Double/debiased machine learning for treatment and structural parameters V Chernozhukov, D Chetverikov, M Demirer, E Duflo, C Hansen, ... The econometrics journal 21 (1), C1-C68, 2018 | 3811* | 2018 |
| Inference on treatment effects after selection among high-dimensional controls A Belloni, V Chernozhukov, C Hansen Review of Economic Studies 81 (2), 608-650, 2014 | 2006 | 2014 |
| Plausibly exogenous TG Conley, CB Hansen, PE Rossi Review of Economics and Statistics 94 (1), 260-272, 2012 | 1371 | 2012 |
| An IV model of quantile treatment effects V Chernozhukov, C Hansen Econometrica 73 (1), 245-261, 2005 | 1307 | 2005 |
| Sparse models and methods for optimal instruments with an application to eminent domain A Belloni, D Chen, V Chernozhukov, C Hansen Econometrica 80 (6), 2369-2429, 2012 | 1234 | 2012 |
| High-dimensional methods and inference on structural and treatment effects A Belloni, V Chernozhukov, C Hansen Journal of Economic Perspectives 28 (2), 29-50, 2014 | 1103 | 2014 |
| Instrumental quantile regression inference for structural and treatment effect models V Chernozhukov, C Hansen Journal of Econometrics 132 (2), 491-525, 2006 | 748 | 2006 |
| Instrumental variable quantile regression: A robust inference approach V Chernozhukov, C Hansen Journal of Econometrics 142 (1), 379-398, 2008 | 662 | 2008 |
| Program evaluation and causal inference with high‐dimensional data A Belloni, V Chernozhukov, I Fernandez‐Val, C Hansen Econometrica 85 (1), 233-298, 2017 | 563 | 2017 |
| Generalized least squares inference in panel and multilevel models with serial correlation and fixed effects CB Hansen Journal of Econometrics 140 (2), 670-694, 2007 | 469 | 2007 |
| Pre-event trends in the panel event-study design S Freyaldenhoven, C Hansen, JM Shapiro American Economic Review 109 (9), 3307-3338, 2019 | 456 | 2019 |
| Estimation with many instrumental variables C Hansen, J Hausman, W Newey Journal of Business & Economic Statistics 26 (4), 398-422, 2008 | 418 | 2008 |
| Asymptotic properties of a robust variance matrix estimator for panel data when T is large CB Hansen Journal of Econometrics 141 (2), 597-620, 2007 | 403 | 2007 |
| Inference with dependent data using cluster covariance estimators CA Bester, TG Conley, CB Hansen Journal of Econometrics 165 (2), 137-151, 2011 | 335 | 2011 |
| The reduced form: A simple approach to inference with weak instruments V Chernozhukov, C Hansen Economics Letters 100 (1), 68-71, 2008 | 292 | 2008 |
| Quantile Models with Endogeneity CB Hansen, V Chernozhukov Annual Review of Economics 5 (1), 2013 | 281* | 2013 |
| Post-selection and post-regularization inference in linear models with many controls and instruments V Chernozhukov, C Hansen, M Spindler American Economic Review 105 (5), 486-490, 2015 | 264 | 2015 |
| lassopack: Model selection and prediction with regularized regression in Stata A Ahrens, CB Hansen, ME Schaffer The Stata Journal 20 (1), 176-235, 2020 | 263 | 2020 |
| The effects of 401 (k) participation on the wealth distribution: an instrumental quantile regression analysis V Chernozhukov, C Hansen Review of Economics and statistics 86 (3), 735-751, 2004 | 253 | 2004 |
| Valid post-selection and post-regularization inference: An elementary, general approach V Chernozhukov, C Hansen, M Spindler Annu. Rev. Econ. 7 (1), 649-688, 2015 | 238 | 2015 |
Victor ChernozhukovProfessor, Department of Economics + Center for Statistics and Data Science, MIT;Verified email at mit.edu
