Research

Working Papers:

10.  Kirill Ponomarev and Vira Semenova.
On the Lower Confidence Band for the Optimal Welfare in Policy Learning.  arXiv
Revision Requested, Quantitative Economics

9. Victor Chernozhukov, Whitney K. Newey, and Vira Semenova.
Welfare Analysis in Dynamic Models.  arXiv

8. Vira Semenova and Gevorg Khandamiryan.
Kernel Smoothing for Conditional Linear Programs. Draft  

7.  Yaroslav Korobka and Vira Semenova.

Debiased Inference for Bounding Wage Inequality with Many Controls Draft 

supersedes arXiv 1808.02569, Chapter 4, August 2018

Published and Forthcoming Work

1. Vira Semenova and Victor Chernozhukov.
   Debiased Machine Learning for Conditional Average Treatment Effects and Other Causal Functions.
   The Econometrics Journal, 24(2), May 2021, 264–289. arXiv  Replication Files
     

2. Denis Nekipelov, Vira Semenova, and Vasilis Syrgkanis.
   Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models.
   The Econometrics Journal, 25(1), January 2022, 233–255. arXiv Replication Code 

3. Vira Semenova, Matthew Goldman, Victor Chernozhukov, and Matt Taddy.
   Inference on Heterogeneous Treatment Effects in High-Dimensional Dynamic Panels with Weak Dependence.
   Quantitative Economics, 14(2), May 2023, 471–510. arXiv  Replication Code

4. Vira Semenova.
   Debiased Machine Learning of Set-Identified Linear Models.
   The Journal of Econometrics, 235(2), August 2023, 1725–1746.  arXiv Replication Code

5. Vira Semenova.
   Generalized Lee Bounds.
   The Journal of Econometrics, 251, September 2025, 106055.  arXiv Replication Code 

6. Gevorg Khandamiryan and Vira Semenova. 

Adaptive Estimation of Aggregated Values of Conditional Linear Programs.
The Review of Economics and Statistics, accepted.   arXiv  Replication Code  

supersedes arXiv 2303.00982, March 2023, and later versions