Mostly harmless simulations? On the internal validity of empirical Monte Carlo studies
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DOI: 10.1920/wp.cem.2013.6413
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- Advani, Arun & Kitagawa, Toru & Sloczynski, Tymon, 2018. "Mostly Harmless Simulations? On the Internal Validity of Empirical Monte Carlo Studies," IZA Discussion Papers 11862, Institute of Labor Economics (IZA).
- Arun Advani & Toru Kitagawa & Tymon Sloczynski, 2018. "Mostly Harmless Simulations? On the Internal Validity of Empirical Monte Carlo Studies," Working Papers 124, Brandeis University, Department of Economics and International Business School.
- Arun Advani & Toru Kitagawa & Tymon Sloczynski, 2018. "Mostly harmless simulations? On the internal validity of empirical Monte Carlo studies," CeMMAP working papers CWP56/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Arun Advani & Tymon Sloczynski, 2013. "Mostly harmless simulations? On the internal validity of empirical Monte Carlo studies," CeMMAP working papers CWP64/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Advani, Arun & Sloczynski, Tymon, 2013. "Mostly Harmless Simulations? On the Internal Validity of Empirical Monte Carlo Studies," IZA Discussion Papers 7874, Institute of Labor Economics (IZA).
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Citations
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Cited by:
- Lechner, Michael, 2018.
"Modified Causal Forests for Estimating Heterogeneous Causal Effects,"
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- Lechner, Michael, 2019. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," CEPR Discussion Papers 13430, C.E.P.R. Discussion Papers.
- Lechner, Michael, 2019. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," Economics Working Paper Series 1901, University of St. Gallen, School of Economics and Political Science.
- Michael Lechner, 2018. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," Papers 1812.09487, arXiv.org, revised Jul 2019.
- Martin Huber & Michael Lechner & Giovanni Mellace, 2016.
"The Finite Sample Performance of Estimators for Mediation Analysis Under Sequential Conditional Independence,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 139-160, January.
- Huber, Martin & Mellace, Giovanni & Lechner, Michael, 2014. "The finite sample performance of estimators for mediation analysis under sequential conditional independence," Economics Working Paper Series 1415, University of St. Gallen, School of Economics and Political Science, revised Nov 2014.
- Pei‐An Liao & Hung‐Hao Chang & Yi‐Ju Su, 2020. "Cash transfer program and child underweight—Empirical evidence from a causal mediation analysis," Agricultural Economics, International Association of Agricultural Economists, vol. 51(2), pages 291-303, March.
- Tymon Słoczyński, 2015.
"The Oaxaca–Blinder Unexplained Component as a Treatment Effects Estimator,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(4), pages 588-604, August.
- Tymon Sloczynski, 2012. "The Oaxaca-Blinder unexplained component as a treatment effects estimator," Working Papers 61, Department of Applied Econometrics, Warsaw School of Economics.
- Słoczyński, Tymon, 2013. "The Oaxaca–Blinder Unexplained Component as a Treatment Effects Estimator," MPRA Paper 50660, University Library of Munich, Germany.
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More about this item
JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
Statistics
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