My arXiv page.
Publicly available code.
ORCID: ORCID iD icon 0000-0002-2482-7796

Working papers

Goldsmith-Pinkham, Paul, Hull, Peter, & Kolesár, Michal. 2024 (Feb.). Contamination Bias in Linear Regressions. Revision requested, American Economic Review. [ Stata code | R code | arXiv | NBER version | .pdf ]

Kolesár, Michal, Müller, Ulrich, & Roelsgaard, Sebastian T. 2024 (Jan.). The Fragility of Sparsity. [ arXiv | .pdf ]

Armstrong, Tim, Kolesár, Michal, & Kwon, Soonwoo. 2023 (Aug.). Bias-Aware Inference in Regularized Regression Models. Revision requested, Quantitative Economics. [ arXiv | .pdf ]

Evdokimov, Kirill, & Kolesár, Michal. 2018 (Jan.). Inference in Instrumental Variable Regression Analysis with Heterogeneous Treatment Effects. [ .pdf ]

Kolesár, Michal. 2013 (Nov.). Estimation in an Instrumental Variables Model With Treatment Effect Heterogeneity. Under revision. [ .pdf ]

Published or Forthcoming

Dong, Yingying, & Kolesár, Michal. 2023. When Can We Ignore Measurement Error in the Running Variable? Journal of Applied Econometrics, 38(5), 735--750. [ DOI | replication files | arXiv | .pdf ]

Angrist, Joshua, & Kolesár, Michal. 2022. One Instrument to Rule Them All: The Bias and Coverage of Just-ID IV. Journal of Econometrics, forthcoming(Dec.). [ DOI | arXiv | NBER version | .pdf ]

Armstrong, Tim, Kolesár, Michal, & Plagborg-Møller, Mikkel. 2022. Robust Empirical Bayes Confidence Intervals. Econometrica, 90(6), 2567--2602. [ DOI | Stata code | Matlab code | R code | supplement | arXiv | .pdf ]

Hull, Peter, Kolesár, Michal, & Walters, Christopher R. 2022. Labour by Design: Contributions of David Card, Joshua Angrist, and Guido Imbens. Scandinavian Journal of Economics, 124(3), 603--645. Invited article. [ DOI | arXiv | .pdf ]

Armstrong, Tim, & Kolesár, Michal. 2021a. Finite-Sample Optimal Estimation and Inference on Average Treatment Effects Under Unconfoundedness. Econometrica, 89(3), 1141--1177. [ DOI | R code | supplement | arXiv | .pdf ]

Armstrong, Tim, & Kolesár, Michal. 2021b. Sensitivity Analysis Using Approximate Moment Condition Models. Quantitative Economics, 12(1), 77--108. [ DOI | R code | supplement | arXiv | .pdf ]

Armstrong, Tim, & Kolesár, Michal. 2020. Simple and Honest Confidence Intervals in Nonparametric Regression. Quantitative Economics, 11(1), 1--39. [ DOI | Stata code | R code | supplement | arXiv | .pdf ]

Adão, Rodrigo, Kolesár, Michal, & Morales, Eduardo. 2019. Shift-Share Designs: Theory and Inference. Quarterly Journal of Economics, 134(4), 1949--2010. [ DOI | Stata code | Matlab code | R code | supplement | arXiv | NBER version | .pdf ]

Kolesár, Michal, & Rothe, Christoph. 2018. Inference in Regression Discontinuity Designs with a Discrete Running Variable. American Economic Review, 108(8), 2277--2304. [ DOI | Stata code | R code | arXiv ]

Kolesár, Michal. 2018. Minimum Distance Approach to Inference with Many Instruments. Journal of Econometrics, 204(1), 86--100. [ DOI | R code | supplement | arXiv | .pdf ]

Armstrong, Tim, & Kolesár, Michal. 2018b. A Simple Adjustment for Bandwidth Snooping. Review of Economic Studies, 85(2), 732--765. [ DOI | R code | supplement | arXiv | .pdf ]

Armstrong, Tim, & Kolesár, Michal. 2018a. Optimal Inference in a Class of Regression Models. Econometrica, 86(2), 655--683. [ DOI | Stata code | R code | supplement | arXiv | .pdf ]

Imbens, Guido W., & Kolesár, Michal. 2016. Robust Standard Errors in Small Samples: Some Practical Advice. Review of Economics and Statistics, 98(4), 701--712. [ DOI | replication files | R code | NBER version | .pdf ]

Kolesár, Michal, Chetty, Raj, Friedman, John N., Glaeser, Edward, & Imbens, Guido W. 2015. Identification and Inference with Many Invalid Instruments. Journal of Business and Economic Statistics, 33(4), 474--484. [ DOI | NBER version | .pdf ]

Barrios, Thomas, Diamond, Rebecca, Imbens, Guido W., & Kolesár, Michal. 2012. Clustering, Spatial Correlations and Randomization Inference. Journal of the American Statistical Association, 107(498), 578--591. [ DOI | NBER version | .pdf ]