Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence
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- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," CEPR Discussion Papers 13402, C.E.P.R. Discussion Papers.
- Michael C. Knaus & Michael Lechner & Anthony Strittmatter, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," Papers 1810.13237, arXiv.org, revised Dec 2018.
- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," IZA Discussion Papers 12039, Institute of Labor Economics (IZA).
References listed on IDEAS
- Stefanie Behncke & Markus Frölich & Michael Lechner, 2010. "A Caseworker Like Me - Does The Similarity Between The Unemployed and Their Caseworkers Increase Job Placements?," Economic Journal, Royal Economic Society, vol. 120(549), pages 1430-1459, December.
- Bell, Stephen H. & Orr, Larry L., 2002. "Screening (and creaming?) applicants to job training programs: the AFDC homemaker-home health aide demonstrations," Labour Economics, Elsevier, vol. 9(2), pages 279-301, April.
- Sokbae Lee & Ryo Okui & Yoon†Jae Whang, 2017.
"Doubly robust uniform confidence band for the conditional average treatment effect function,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1207-1225, November.
- Sokbae (Simon) Lee & Ryo Okui & Yoon-Jae Whang, 2016. "Doubly robust uniform confidence band for the conditional average treatment effect function," CeMMAP working papers CWP03/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Lee, Sokbae & Okui, Ryo & Whang, Yoon-Jae, 2017. "Doubly robust uniform confidence band for the conditional average treatment effect function," LSE Research Online Documents on Economics 86852, London School of Economics and Political Science, LSE Library.
- Sokbae Lee & Ryo Okui & Yoon-Jae Whang, 2016. "Doubly Robust Uniform Confidence Band For The Conditional Average Treatment Effect Function," KIER Working Papers 931, Kyoto University, Institute of Economic Research.
- Sokbae Lee & Ryo Okui & Yoon-Jae Whang, 2016. "Doubly Robust Uniform Confidence Band for the Conditional Average Treatment Effect Function," Papers 1601.02801, arXiv.org, revised Oct 2016.
- Lechner, Michael & Wunsch, Conny, 2013.
"Sensitivity of matching-based program evaluations to the availability of control variables,"
Labour Economics, Elsevier, vol. 21(C), pages 111-121.
- Lechner, Michael & Wunsch, Conny, 2011. "Sensitivity of Matching-Based Program Evaluations to the Availability of Control Variables," IZA Discussion Papers 5553, Institute of Labor Economics (IZA).
- Lechner, Michael & Wunsch, Conny, 2011. "Sensitivity of matching-based program evaluations to the availability of control variables," CEPR Discussion Papers 8294, C.E.P.R. Discussion Papers.
- Lechner, Michael & Wunsch, Conny, 2011. "Sensitivity of matching-based program evaluations to the availability of control variables," Economics Working Paper Series 1105, University of St. Gallen, School of Economics and Political Science.
- Baqun Zhang & Anastasios A. Tsiatis & Eric B. Laber & Marie Davidian, 2012. "A Robust Method for Estimating Optimal Treatment Regimes," Biometrics, The International Biometric Society, vol. 68(4), pages 1010-1018, December.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018.
"Double/debiased machine learning for treatment and structural parameters,"
Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2017. "Double/Debiased Machine Learning for Treatment and Structural Parameters," NBER Working Papers 23564, National Bureau of Economic Research, Inc.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers CWP28/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Grimmer, Justin & Messing, Solomon & Westwood, Sean J., 2017. "Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods," Political Analysis, Cambridge University Press, vol. 25(4), pages 413-434, October.
- Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
- Miruna Oprescu & Vasilis Syrgkanis & Zhiwei Steven Wu, 2018. "Orthogonal Random Forest for Causal Inference," Papers 1806.03467, arXiv.org, revised Sep 2019.
- Susan Athey & Julie Tibshirani & Stefan Wager, 2016.
"Generalized Random Forests,"
Papers
1610.01271, arXiv.org, revised Apr 2018.
- Athey, Susan & Tibshirani, Julie & Wager, Stefan, 2017. "Generalized Random Forests," Research Papers 3575, Stanford University, Graduate School of Business.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014.
"High-Dimensional Methods and Inference on Structural and Treatment Effects,"
Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Shuai Chen & Lu Tian & Tianxi Cai & Menggang Yu, 2017. "A general statistical framework for subgroup identification and comparative treatment scoring," Biometrics, The International Biometric Society, vol. 73(4), pages 1199-1209, December.
- Michael Gerfin & Michael Lechner, 2002.
"A Microeconometric Evaluation of the Active Labour Market Policy in Switzerland,"
Economic Journal, Royal Economic Society, vol. 112(482), pages 854-893, October.
- Gerfin, Michael & Lechner, Michael, 2000. "Microeconometric Evaluation of the Active Labour Market Policy in Switzerland," IZA Discussion Papers 154, Institute of Labor Economics (IZA).
- Gerfin, Michael & Lechner, Michael, 2001. "A Microeconometric Evaluation of Active Labour Market Policy in Switzerland," CEPR Discussion Papers 2993, C.E.P.R. Discussion Papers.
- Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003.
"Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score,"
Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
- Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.
- Guido Imbens, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometric Society World Congress 2000 Contributed Papers 1166, Econometric Society.
- Lechner, Michael & Smith, Jeffrey, 2007.
"What is the value added by caseworkers?,"
Labour Economics, Elsevier, vol. 14(2), pages 135-151, April.
- Lechner, Michael & Smith, Jeffrey, 2003. "What is the Value Added by Caseworkers?," CEPR Discussion Papers 3825, C.E.P.R. Discussion Papers.
- Lechner, Michael & Smith, Jeffrey A., 2003. "What is the Value Added by Caseworkers?," IZA Discussion Papers 728, Institute of Labor Economics (IZA).
- Michael Lechner & Jeffrey Smith, 2003. "What is the Value Added by Caseworkers?," University of St. Gallen Department of Economics working paper series 2003 2003-05, Department of Economics, University of St. Gallen.
- Michael Lechner & Jeffrey Smith, 2003. "What is the Value Added by Caseworkers?," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20031, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
- Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
- Stefanie Behncke & Markus Frölich & Michael Lechner, 2010.
"Unemployed and their caseworkers: should they be friends or foes?,"
Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 67-92, January.
- Behncke, Stefanie & Frölich, Markus & Lechner, Michael, 2007. "Unemployed and Their Caseworkers: Should They Be Friends or Foes?," IZA Discussion Papers 3149, Institute of Labor Economics (IZA).
- Stefanie Behncke & Markus Fröhlich & Michael Lechner, 2007. "Unemployed and their Caseworkers: Should they be Friends or Foes?," University of St. Gallen Department of Economics working paper series 2007 2007-45, Department of Economics, University of St. Gallen.
- Behncke, Stefanie & Frölich, Markus & Lechner, Michael, 2007. "Unemployed and Their Caseworkers: Should They Be Friends or Foes?," CEPR Discussion Papers 6558, C.E.P.R. Discussion Papers.
- S. A. Murphy, 2003. "Optimal dynamic treatment regimes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 331-355, May.
- Leeb, Hannes & Pötscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(1), pages 21-59, February.
- Farrell, Max H., 2015. "Robust inference on average treatment effects with possibly more covariates than observations," Journal of Econometrics, Elsevier, vol. 189(1), pages 1-23.
- Michael Lechner & Anthony Strittmatter, 2019.
"Practical procedures to deal with common support problems in matching estimation,"
Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 193-207, February.
- Lechner, Michael & Strittmatter, Anthony, 2014. "Practical Procedures to Deal with Common Support Problems in Matching Estimation," Economics Working Paper Series 1410, University of St. Gallen, School of Economics and Political Science.
- Lechner, Michael & Strittmatter, Anthony, 2017. "Practical Procedures to Deal with Common Support Problems in Matching Estimation," IZA Discussion Papers 10532, Institute of Labor Economics (IZA).
- Djebbari, Habiba & Smith, Jeffrey, 2008.
"Heterogeneous impacts in PROGRESA,"
Journal of Econometrics, Elsevier, vol. 145(1-2), pages 64-80, July.
- Djebbari, Habiba & Smith, Jeffrey A., 2008. "Heterogeneous Impacts in PROGRESA," IZA Discussion Papers 3362, Institute of Labor Economics (IZA).
- Anthony Strittmatter, 2018.
"What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?,"
Papers
1812.06533, arXiv.org, revised Mar 2019.
- Strittmatter, Anthony, 2019. "What is the Value Added by using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203499, Verein für Socialpolitik / German Economic Association.
- Strittmatter, Anthony, 2019. "What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," GLO Discussion Paper Series 336, Global Labor Organization (GLO).
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "Inference on Treatment Effects after Selection among High-Dimensional Controlsâ€," Review of Economic Studies, Oxford University Press, vol. 81(2), pages 608-650.
- Edward McFowland III & Sriram Somanchi & Daniel B. Neill, 2018. "Efficient Discovery of Heterogeneous Treatment Effects in Randomized Experiments via Anomalous Pattern Detection," Papers 1803.09159, arXiv.org, revised Jun 2018.
- Guido W. Imbens & Jeffrey M. Wooldridge, 2009.
"Recent Developments in the Econometrics of Program Evaluation,"
Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
- Guido M. Imbens & Jeffrey M. Wooldridge, 2008. "Recent Developments in the Econometrics of Program Evaluation," NBER Working Papers 14251, National Bureau of Economic Research, Inc.
- Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
- Guido Imbens & Jeffrey M. Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Imbens, Guido W. & Wooldridge, Jeffrey M., 2008. "Recent Developments in the Econometrics of Program Evaluation," IZA Discussion Papers 3640, Institute of Labor Economics (IZA).
- Michael Knaus & Michael Lechner & Anthony Strittmatter, 2017.
"Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach,"
Papers
1709.10279, arXiv.org, revised May 2018.
- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," Economics Working Paper Series 1711, University of St. Gallen, School of Economics and Political Science.
- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," CEPR Discussion Papers 12224, C.E.P.R. Discussion Papers.
- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," IZA Discussion Papers 10961, Institute of Labor Economics (IZA).
- Lu Tian & Ash A. Alizadeh & Andrew J. Gentles & Robert Tibshirani, 2014. "A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1517-1532, December.
- Martin Huber & Michael Lechner & Giovanni Mellace, 2017.
"Why Do Tougher Caseworkers Increase Employment? The Role of Program Assignment as a Causal Mechanism,"
The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 180-183, March.
- Huber, Martin & Mellace, Giovanni & Lechner, Michael, 2014. "Why do tougher caseworkers increase employment? The role of programme assignment as a causal mechanism," Economics Working Paper Series 1414, University of St. Gallen, School of Economics and Political Science.
- Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
- Jonathan M.V. Davis & Sara B. Heller, 2017. "Using Causal Forests to Predict Treatment Heterogeneity: An Application to Summer Jobs," American Economic Review, American Economic Association, vol. 107(5), pages 546-550, May.
- Lechner, Michael & Wunsch, Conny, 2013.
"Sensitivity of matching-based program evaluations to the availability of control variables,"
Labour Economics, Elsevier, vol. 21(C), pages 111-121.
- Lechner, Michael & Wunsch, Conny, 2011. "Sensitivity of Matching-Based Program Evaluations to the Availability of Control Variables," IZA Discussion Papers 5553, Institute of Labor Economics (IZA).
- Michael Lechner & Conny Wunsch, 2011. "Sensitivity of Matching-Based Program Evaluations to the Availability of Control Variables," CESifo Working Paper Series 3381, CESifo.
- Lechner, Michael & Wunsch, Conny, 2011. "Sensitivity of matching-based program evaluations to the availability of control variables," CEPR Discussion Papers 8294, C.E.P.R. Discussion Papers.
- Lechner, Michael & Wunsch, Conny, 2011. "Sensitivity of matching-based program evaluations to the availability of control variables," Economics Working Paper Series 1105, University of St. Gallen, School of Economics and Political Science.
- Susan Athey & Guido W. Imbens, 2017.
"The State of Applied Econometrics: Causality and Policy Evaluation,"
Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
- Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
- Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2015.
"Estimating Conditional Average Treatment Effects,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 485-505, October.
- Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2012. "Estimating Conditional Average Treatment Effects," CEU Working Papers 2012_16, Department of Economics, Central European University, revised 20 Jul 2012.
- A. Belloni & V. Chernozhukov & I. Fernández‐Val & C. Hansen, 2017.
"Program Evaluation and Causal Inference With High‐Dimensional Data,"
Econometrica, Econometric Society, vol. 85, pages 233-298, January.
- Alexandre Belloni & Victor Chernozhukov & Ivan Fern'andez-Val & Christian Hansen, 2013. "Program Evaluation and Causal Inference with High-Dimensional Data," Papers 1311.2645, arXiv.org, revised Jan 2018.
- Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers CWP13/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
- Matt Taddy & Matt Gardner & Liyun Chen & David Draper, 2016. "A Nonparametric Bayesian Analysis of Heterogenous Treatment Effects in Digital Experimentation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 661-672, October.
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- Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2019. "Does the Estimation of the Propensity Score by Machine Learning Improve Matching Estimation? The Case of Germany's Programmes for Long Term Unemployed," IZA Discussion Papers 12526, Institute of Labor Economics (IZA).
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- Boolens, Joost & Cockx, Bart & Lechner, Michael, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," CEPR Discussion Papers 14270, C.E.P.R. Discussion Papers.
- Cockx, Bart & Lechner, Michael & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Research Memorandum 015, Maastricht University, Graduate School of Business and Economics (GSBE).
- Cockx, Bart & Lechner, Michael & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Economics Working Paper Series 2001, University of St. Gallen, School of Economics and Political Science.
- Cockx, Bart & Lechner, Michael & Bollens, Joost, 2019. "Priority to Unemployed Immigrants? A Causal Machine Learning Evaluation of Training in Belgium," IZA Discussion Papers 12875, Institute of Labor Economics (IZA).
- Bart Cockx & Michael Lechner & Joost Bollens, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," LIDAM Discussion Papers IRES 2020016, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
- Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Oct 2020.
- Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020.
"Does the estimation of the propensity score by machine learning improve matching estimation? The case of Germany's programmes for long term unemployed,"
Labour Economics, Elsevier, vol. 65(C).
- Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2019. "Does the estimation of the propensity score by machine learning improve matching estimation? The case of Germany’s programmes for long term unemployed," Economics Working Paper Series 1910, University of St. Gallen, School of Economics and Political Science.
- Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2019. "Does the Estimation of the Propensity Score by Machine Learning Improve Matching Estimation? The Case of Germany's Programmes for Long Term Unemployed," IZA Discussion Papers 12526, Institute of Labor Economics (IZA).
- Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020. "Does the estimation of the propensity score by machine learning improve matching estimation? : The case of Germany's programmes for long term unemployed," IAB Discussion Paper 202005, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
- Qingliang Fan & Yu-Chin Hsu & Robert P. Lieli & Yichong Zhang, 2019. "Estimation of Conditional Average Treatment Effects with High-Dimensional Data," Papers 1908.02399, arXiv.org, revised Aug 2020.
- Sant’Anna, Pedro H.C. & Song, Xiaojun, 2019.
"Specification tests for the propensity score,"
Journal of Econometrics, Elsevier, vol. 210(2), pages 379-404.
- Pedro H. C. Sant'Anna & Xiaojun Song, 2016. "Specification Tests for the Propensity Score," Papers 1611.06217, arXiv.org, revised Feb 2019.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018.
"High-dimensional econometrics and regularized GMM,"
CeMMAP working papers
CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
- Marco Caliendo & Stefan Tübbicke, 2020.
"New evidence on long-term effects of start-up subsidies: matching estimates and their robustness,"
Empirical Economics, Springer, vol. 59(4), pages 1605-1631, October.
- Marco Caliendo & Stefan Tübbicke, 2019. "New Evidence on Long-Term Effects of Start-Up Subsidies: Matching Estimates and their Robustness," CEPA Discussion Papers 06, Center for Economic Policy Analysis.
- Caliendo, Marco & Tübbicke, Stefan, 2019. "New Evidence on Long-Term Effects of Start-Up Subsidies: Matching Estimates and Their Robustness," IZA Discussion Papers 12261, Institute of Labor Economics (IZA).
- Martin Huber & Michael Lechner & Giovanni Mellace, 2017.
"Why Do Tougher Caseworkers Increase Employment? The Role of Program Assignment as a Causal Mechanism,"
The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 180-183, March.
- Huber, Martin & Mellace, Giovanni & Lechner, Michael, 2014. "Why do tougher caseworkers increase employment? The role of programme assignment as a causal mechanism," Economics Working Paper Series 1414, University of St. Gallen, School of Economics and Political Science.
More about this item
Keywords
Causal machine learning; conditional average treatment effects; selection-on-observables; Random Forest; Causal Forest; Lasso;All these keywords.
JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
NEP fields
This paper has been announced in the following NEP Reports:- NEP-REG-2019-01-07 (Regulation)
Statistics
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