| Inference on treatment effects after selection among high-dimensional controls A Belloni, V Chernozhukov, C Hansen The Review of Economic Studies 81 (2), 608-650, 2014 | 1029 | 2014 |
| Sparse models and methods for optimal instruments with an application to eminent domain A Belloni, D Chen, V Chernozhukov, C Hansen | 747 | 2011 |
| Least Squares after Model Selection in High-Dimensional Sparse Models A Belloni, V Chernozhukov Cambridge, MA: Dept. of Economics, MIT, 2009 | 578* | 2009 |
| Square-root lasso: pivotal recovery of sparse signals via conic programming A Belloni, V Chernozhukov, L Wang Biometrika 98 (4), 791-806, 2011 | 561 | 2011 |
| 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 | 545 | 2014 |
| ℓ1-penalized quantile regression in high-dimensional sparse models A Belloni, V Chernozhukov The Annals of Statistics 39 (1), 82-130, 2011 | 493 | 2011 |
| Program evaluation and causal inference with high‐dimensional data A Belloni, V Chernozhukov, I Fernández‐Val, C Hansen Econometrica 85 (1), 233-298, 2017 | 318* | 2017 |
| Inference for high-dimensional sparse econometric models A Belloni, V Chernozhukov, C Hansen arXiv preprint arXiv:1201.0220, 2011 | 173 | 2011 |
| Optimizing product line designs: Efficient methods and comparisons A Belloni, R Freund, M Selove, D Simester Management Science 54 (9), 1544-1552, 2008 | 156 | 2008 |
| Uniform post-selection inference for least absolute deviation regression and other Z-estimation problems A Belloni, V Chernozhukov, K Kato Biometrika 102 (1), 77-94, 2015 | 155* | 2015 |
| Some new asymptotic theory for least squares series: Pointwise and uniform results A Belloni, V Chernozhukov, D Chetverikov, K Kato Journal of Econometrics 186 (2), 345-366, 2015 | 142 | 2015 |
| Pivotal estimation via square-root lasso in nonparametric regression A Belloni, V Chernozhukov, L Wang The Annals of Statistics 42 (2), 757-788, 2014 | 131* | 2014 |
| Conditional quantile processes based on series or many regressors A Belloni, V Chernozhukov, I Fernandez-Val | 125* | 2011 |
| Honest confidence regions for a regression parameter in logistic regression with a large number of controls A Belloni, V Chernozhukov, Y Wei cemmap working paper, 2013 | 117* | 2013 |
| Inference in high-dimensional panel models with an application to gun control A Belloni, V Chernozhukov, C Hansen, D Kozbur Journal of Business & Economic Statistics 34 (4), 590-605, 2016 | 107 | 2016 |
| High dimensional sparse econometric models: An introduction A Belloni, V Chernozhukov Inverse Problems and High-Dimensional Estimation, 121-156, 2011 | 98 | 2011 |
| Bundle relaxation and primal recovery in unit commitment problems. The Brazilian case A Belloni, ALDS Lima, MEP Maceira, CA Sagastizábal Annals of Operations Research 120 (1), 21-44, 2003 | 92 | 2003 |
| On the computational complexity of MCMC-based estimators in large samples A Belloni, V Chernozhukov The Annals of Statistics 37 (4), 2011-2055, 2009 | 77 | 2009 |
| Escaping the local minima via simulated annealing: Optimization of approximately convex functions A Belloni, T Liang, H Narayanan, A Rakhlin Conference on Learning Theory, 240-265, 2015 | 68 | 2015 |
| Linear and conic programming estimators in high dimensional errors‐in‐variables models A Belloni, M Rosenbaum, AB Tsybakov Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2017 | 67 | 2017 |
Victor ChernozhukovProfessor, Department of Economics + Center for Statistics and Data Science, MITVerified email at mit.edu
