Research

Published and Accepted Work:

Debiased Machine Learning for Conditional Average Treatment Effects and Other Causal Functions (with Victor Chernozhukov)  Econometrics Journal, 24(2), May 2021, 264-289  DOI  | arXiv | R Code |  Kaggle Notebook  |   CATE for the Treated (Kaggle notebook)    

Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models (with Denis Nekipelov and Vasilis Syrgkanis) Econometrics Journal, forthcoming  DOI | arXiv | Replication Code

 Estimation and Inference on Heterogeneous Treatment Effects in High-Dimensional Dynamic Panels (with Matt Goldman, Victor Chernozhukov, Matt Taddy) arXiv | R Code | Kaggle Notebook 

Quantitative Economics, forthcoming

Debiased Machine Learning of Set-Identified Linear Models [September 2021] arXiv | R Code   

Journal of Econometrics, forthcoming

Generalized Lee Bounds  arXiv  Youtube  Slides R package  Journal of Econometrics

Working papers:

Aggregated Intersection Bounds and Aggregated Minimax Values arXiv 

Inference for average welfare in high-dimensional state space (with Victor Chernozhukov and Whitney Newey) 

Machine Learning for Dynamic Discrete Choice (Partial Identification)