Michal Kolesar

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1 Similar Profiles

1 Finished
1 Active

Collaborative Research: Honest and Robust Inference with High Dimensional Data
Kolesar, M. (PI)
NSF - National Science Foundation
4/1/21 → 3/31/26
Project: Research project
Collaborative Research: Honest Inference and Efficiency Bounds for Nonparametric Regression and Approximate Moment Condition Models
Kolesar, M. (PI)
NSF - National Science Foundation
9/15/16 → 8/31/19
Project: Research project

14 Article
1 Review article

Contamination Bias in Linear Regressions
Goldsmith-Pinkham, P., Hull, P. & Kolesár, M., Dec 2024, In: American Economic Review. 114, 12, p. 4015-4051 37 p.
Research output: Contribution to journal › Article › peer-review

Open Access
4 Scopus citations
One instrument to rule them all: The bias and coverage of just-ID IV
Angrist, J. & Kolesár, M., Mar 2024, In: Journal of Econometrics. 240, 2, 105398.
Research output: Contribution to journal › Article › peer-review

Open Access
13 Scopus citations
When can we ignore measurement error in the running variable?
Dong, Y. & Kolesár, M., Aug 2023, In: Journal of Applied Econometrics. 38, 5, p. 735-750 16 p.
Research output: Contribution to journal › Article › peer-review

Open Access
5 Scopus citations
Labor by design: contributions of David Card, Joshua Angrist, and Guido Imbens*
Hull, P., Kolesár, M. & Walters, C., Jul 2022, In: Scandinavian Journal of Economics. 124, 3, p. 603-645 43 p.
Research output: Contribution to journal › Article › peer-review

Open Access
4 Scopus citations
Robust Empirical Bayes Confidence Intervals
Armstrong, T. B., Kolesár, M. & Plagborg-Møller, M., Nov 2022, In: Econometrica. 90, 6, p. 2567-2602 36 p.
Research output: Contribution to journal › Article › peer-review

Open Access
13 Scopus citations

Michal Kolesar

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

Collaborative Research: Honest and Robust Inference with High Dimensional Data

Collaborative Research: Honest Inference and Efficiency Bounds for Nonparametric Regression and Approximate Moment Condition Models

Contamination Bias in Linear Regressions

One instrument to rule them all: The bias and coverage of just-ID IV

When can we ignore measurement error in the running variable?

Labor by design: contributions of David Card, Joshua Angrist, and Guido Imbens*

Robust Empirical Bayes Confidence Intervals

Michal Kolesar

Fingerprint

Collaborations and top research areas from the last five years

Projects

Collaborative Research: Honest and Robust Inference with High Dimensional Data

Collaborative Research: Honest Inference and Efficiency Bounds for Nonparametric Regression and Approximate Moment Condition Models

Research output

Contamination Bias in Linear Regressions

One instrument to rule them all: The bias and coverage of just-ID IV

When can we ignore measurement error in the running variable?

Labor by design: contributions of David Card, Joshua Angrist, and Guido Imbens*

Robust Empirical Bayes Confidence Intervals