Mostly Harmless Simulations? Using Monte Carlo Studies for Estimator Selection
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- Arun Advani & Toru Kitagawa & Tymon Słoczyński, 2019. "Mostly harmless simulations? Using Monte Carlo studies for estimator selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 893-910, September.
- Advani, Arun & Kitagawa, Toru & Słoczyński, Tymon, 2019. "Mostly Harmless Simulations? Using Monte Carlo Studies for Estimator Selection," The Warwick Economics Research Paper Series (TWERPS) 1192, University of Warwick, Department of Economics.
- Arun Advani & Toru Kitagawa & Tymon S{l}oczy'nski, 2018. "Mostly Harmless Simulations? Using Monte Carlo Studies for Estimator Selection," Papers 1809.09527, arXiv.org, revised Apr 2019.
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Cited by:
- Lechner, Michael, 2018.
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- Michael Lechner, 2018. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," Papers 1812.09487, arXiv.org, revised Jul 2019.
- Harsh Parikh & Carlos Varjao & Louise Xu & Eric Tchetgen Tchetgen, 2022. "Validating Causal Inference Methods," Papers 2202.04208, arXiv.org, revised Jul 2022.
- Tymon Sloczynski & S. Derya Uysal & Jeffrey M. Wooldridge & Derya Uysal, 2022.
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- Tymon S{l}oczy'nski & S. Derya Uysal & Jeffrey M. Wooldridge, 2022. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," Papers 2204.07672, arXiv.org, revised Feb 2024.
- Sloczynski, Tymon & Uysal, Derya & Wooldridge, Jeffrey M., 2022. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," IZA Discussion Papers 15241, Institute of Labor Economics (IZA).
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- Susan Athey & Guido W. Imbens & Jonas Metzger & Evan M. Munro, 2019. "Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations," NBER Working Papers 26566, National Bureau of Economic Research, Inc.
- Arun Advani & Toru Kitagawa & Tymon Słoczyński, 2019.
"Mostly harmless simulations? Using Monte Carlo studies for estimator selection,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 893-910, September.
- Arun Advani & Toru Kitagawa & Tymon S{l}oczy'nski, 2018. "Mostly Harmless Simulations? Using Monte Carlo Studies for Estimator Selection," Papers 1809.09527, arXiv.org, revised Apr 2019.
- Advani, Arun & Kitagawa, Toru & Słoczyński, Tymon, 2019. "Mostly Harmless Simulations? Using Monte Carlo Studies for Estimator Selection," The Warwick Economics Research Paper Series (TWERPS) 1192, University of Warwick, Department of Economics.
- Advani, Arun & Kitagawa, Toru & Sloczynski, Tymon, 2019. "Mostly Harmless Simulations? Using Monte Carlo Studies for Estimator Selection," CAGE Online Working Paper Series 411, Competitive Advantage in the Global Economy (CAGE).
- Lombardi, Stefano & van den Berg, Gerard J. & Vikström, Johan, 2020.
"Empirical Monte Carlo evidence on estimation of Timing-of-Events models,"
Working Paper Series
2020:26, IFAU - Institute for Evaluation of Labour Market and Education Policy, revised 05 Jan 2021.
- Lombardi, Stefano & van den Berg, Gerard J. & Vikström, Johan, 2021. "Empirical Monte Carlo Evidence on Estimation of Timing-of-Events Models," IZA Discussion Papers 14015, Institute of Labor Economics (IZA).
- Tymon Sloczynski & S. Derya Uysal & Jeffrey M. Wooldridge & Derya Uysal, 2022.
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- Tymon Sloczynski & Derya Uysal & Jeffrey Wooldridge, 2023. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," Rationality and Competition Discussion Paper Series 424, CRC TRR 190 Rationality and Competition.
- Sloczynski, Tymon & Uysal, Derya & Wooldridge, Jeffrey M., 2022. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," IZA Discussion Papers 15241, Institute of Labor Economics (IZA).
- Derya Uysal, 2023. "Abadie's kappa and weighting estimators of the local average treatment effect," Economics Virtual Symposium 2023 01, Stata Users Group.
- Yiyan Huang & Cheuk Hang Leung & Siyi Wang & Yijun Li & Qi Wu, 2024. "Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators," Papers 2402.18392, arXiv.org, revised Oct 2024.
- Cummins Joseph & Miller Douglas L. & Smith Brock & Simon David, 2024.
"Matching on Noise: Finite Sample Bias in the Synthetic Control Estimator,"
Journal of Econometric Methods, De Gruyter, vol. 13(1), pages 67-95, January.
- Joseph Cummins & Brock Smith & Douglas L. Miller & David Eliot Simon, 2023. "Matching on Noise: Finite Sample Bias in the Synthetic Control Estimator," Working papers 2023-07, University of Connecticut, Department of Economics.
- Florian Gunsilius, 2019. "A path-sampling method to partially identify causal effects in instrumental variable models," Papers 1910.09502, arXiv.org, revised Jun 2020.
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More about this item
Keywords
empirical Monte Carlo studies; program evaluation; selection on observables; treatment effects JEL Classification: C15; C21; C25; C52;All these keywords.
JEL classification:
- C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
- J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
- J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2019-04-22 (Econometrics)
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