Modified Causal Forests for Estimating Heterogeneous Causal Effects

Citations

Cited by:

1. Krishna Neupane & Prem Sapkota & Ujjwal Prajapati, 2026. "Beyond the Numbers: Causal Effects of Financial Report Sentiment on Bank Profitability," Papers 2602.17851, arXiv.org.
2. Enzo Brox & Michael Lechner, 2024. "Teamwork and Spillover Effects in Performance Evaluations," Papers 2403.15200, arXiv.org.
3. Daniel Goller, 2023. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Annals of Operations Research, Springer, vol. 325(1), pages 649-679, June.
   • Goller, Daniel, 2020. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Economics Working Paper Series 2013, University of St. Gallen, School of Economics and Political Science.
   • Daniel Goller, 2020. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Papers 2008.07165, arXiv.org.
4. Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Sciences Po Economics Publications (main) hal-03455978, HAL.
   • Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Post-Print hal-03098058, HAL.
   • Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03098058, HAL.
   • Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," PSE-Ecole d'économie de Paris (Postprint) hal-03098058, HAL.
   • Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Working Papers hal-03455978, HAL.
   • Fougère, Denis & Jacquemet, Nicolas, 2020. "Policy Evaluation Using Causal Inference Methods," IZA Discussion Papers 12922, IZA Network @ LISER.
   • Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Sciences Po Economics Publications (main) hal-03098058, HAL.
   • Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03455978, HAL.
5. Patrick Rehill, 2024. "How do applied researchers use the Causal Forest? A methodological review of a method," Papers 2404.13356, arXiv.org, revised Dec 2024.
6. 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," IZA Discussion Papers 12526, IZA Network @ LISER.
   • 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, 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].
7. Patrick Rehill, 2025. "How Do Applied Researchers Use the Causal Forest? A Methodological Review," International Statistical Review, International Statistical Institute, vol. 93(2), pages 288-316, August.
8. Michael Zimmert & Michael Lechner, 2019. "Nonparametric estimation of causal heterogeneity under high-dimensional confounding," Papers 1908.08779, arXiv.org.
9. Nora Bearth & Michael Lechner & Jana Mareckova & Fabian Muny, 2025. "Fairness-Aware and Interpretable Policy Learning," Papers 2509.12119, arXiv.org.
10. Gabriel Okasa & Kenneth A. Younge, 2022. "Sample Fit Reliability," Papers 2209.06631, arXiv.org.
11. Cockx, Bart & Lechner, Michael & Bollens, Joost, 2023. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Labour Economics, Elsevier, vol. 80(C).
    • Cockx, Bart & Lechner, Michael & Bollens, Joost, 2019. "Priority to Unemployed Immigrants? A Causal Machine Learning Evaluation of Training in Belgium," IZA Discussion Papers 12875, IZA Network @ LISER.
    • 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).
    • Bart Cockx & Michael Lechner & Joost Bollens, 2020. "Priority of Unemployed Immigrants? A Causal Machine Learning Evaluation of Training in Belgium," CESifo Working Paper Series 8297, CESifo.
    • 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).
    • Bart Cockx & Michael Lechner & Joost Bollens, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 20/998, Ghent University, Faculty of Economics and Business Administration.
    • Lechner, Michael & Cockx, Bart & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," CEPR Discussion Papers 14270, Centre for Economic Policy Research.
    • Cockx, Bart & Lechner, Michael & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," ROA Research Memorandum 006, Maastricht University, Research Centre for Education and the Labour Market (ROA).
    • 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.
    • Bart Cockx & Michael Lechner & Joost Bollens, 2019. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Papers 1912.12864, arXiv.org, revised Dec 2022.
12. Steffen Mink & Daria Loginova & Stefan Mann, 2024. "Wolves' contribution to structural change in grazing systems among swiss alpine summer farms: The evidence from causal random forest," Journal of Agricultural Economics, Wiley Blackwell, vol. 75(1), pages 201-217, February.
13. Michael C Knaus, 2022. "Double machine learning-based programme evaluation under unconfoundedness [Econometric methods for program evaluation]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 602-627.
    • Michael C. Knaus, 2020. "Double Machine Learning based Program Evaluation under Unconfoundedness," Papers 2003.03191, arXiv.org, revised Jun 2022.
    • Knaus, Michael C., 2020. "Double Machine Learning based Program Evaluation under Unconfoundedness," Economics Working Paper Series 2004, University of St. Gallen, School of Economics and Political Science.
    • Knaus, Michael C., 2020. "Double Machine Learning Based Program Evaluation under Unconfoundedness," IZA Discussion Papers 13051, IZA Network @ LISER.
14. Paul S. Clarke & Annalivia Polselli, 2023. "Double Machine Learning for Static Panel Models with Fixed Effects," Papers 2312.08174, arXiv.org, revised Dec 2024.
15. Daniel Boller & Michael Lechner & Gabriel Okasa, 2025. "The effect of sport in online dating: evidence from causal machine learning," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-13, December.
    • Daniel Boller & Michael Lechner & Gabriel Okasa, 2021. "The Effect of Sport in Online Dating: Evidence from Causal Machine Learning," Papers 2104.04601, arXiv.org.
    • Boller, Daniel & Lechner, Michael & Okasa, Gabriel, 2021. "The Effect of Sport in Online Dating: Evidence from Causal Machine Learning," IZA Discussion Papers 14259, IZA Network @ LISER.
    • Boller, Daniel & Lechner, Michael & Okasa, Gabriel, 2021. "The Effect of Sport in Online Dating: Evidence from Causal Machine Learning," Economics Working Paper Series 2104, University of St. Gallen, School of Economics and Political Science.
16. Goller, Daniel & Lechner, Michael & Pongratz, Tamara & Wolff, Joachim, 2025. "Active labor market policies for the long-term unemployed: New evidence from causal machine learning," Labour Economics, Elsevier, vol. 94(C).
    • Daniel Goller & Tamara Harrer & Michael Lechner & Joachim Wolff, 2021. "Active labour market policies for the long-term unemployed: New evidence from causal machine learning," Papers 2106.10141, arXiv.org, revised May 2023.
    • Goller, Daniel & Harrer, Tamara & Lechner, Michael & Wolff, Joachim, 2021. "Active labour market policies for the long-term unemployed: New evidence from causal machine learning," Economics Working Paper Series 2108, University of St. Gallen, School of Economics and Political Science.
    • Goller, Daniel & Harrer, Tamara & Lechner, Michael & Wolff, Joachim, 2021. "Active Labour Market Policies for the Long-Term Unemployed: New Evidence from Causal Machine Learning," IZA Discussion Papers 14486, IZA Network @ LISER.
17. Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
18. Nora Bearth & Nadja van 't Hoff & Torben S. D. Johansen, 2026. "Group-Level Treatment Effect Heterogeneity in Difference-in-Differences: A Balanced Approach," Papers 2606.24785, arXiv.org.
19. Kleifgen, Eva & Lang, Julia, 2022. "Should I Train Or Should I Go? Estimating Treatment Effects of Retraining on Regional and Occupational Mobility," VfS Annual Conference 2022 (Basel): Big Data in Economics 264069, Verein für Socialpolitik / German Economic Association.
20. Elena Denisova-Schmidt & Martin Huber & Elvira Leontyeva & Anna Solovyeva, 2021. "Combining experimental evidence with machine learning to assess anti-corruption educational campaigns among Russian university students," Empirical Economics, Springer, vol. 60(4), pages 1661-1684, April.
    • Denisova-Schmidt, Elena & Huber, Martin & Leontyeva, Elvira & Solovyeva, Anna, 2017. "Combining experimental evidence with machine learning to assess anti-corruption educational campaigns among Russian university students," FSES Working Papers 487, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
21. Michael Lechner, 2023. "Causal Machine Learning and its use for public policy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-15, December.
22. Michael Lechner & Gabriel Okasa, 2025. "Random Forest estimation of the ordered choice model," Empirical Economics, Springer, vol. 68(1), pages 1-106, January.
    • Lechner, Michael & Okasa, Gabriel, 2019. "Random Forest Estimation of the Ordered Choice Model," Economics Working Paper Series 1908, University of St. Gallen, School of Economics and Political Science.
    • Michael Lechner & Gabriel Okasa, 2019. "Random Forest Estimation of the Ordered Choice Model," Papers 1907.02436, arXiv.org, revised Sep 2022.
23. Faltings, Richard & Krumer, Alex & Lechner, Michael, 2019. "Rot-Jaune-Verde. Language and Favoritism: Evidence from Swiss Soccer," Economics Working Paper Series 1915, University of St. Gallen, School of Economics and Political Science.
24. Patrick Rehill & Nicholas Biddle, 2024. "Heterogeneous treatment effect estimation with high-dimensional data in public policy evaluation -- an application to the conditioning of cash transfers in Morocco using causal machine learning," Papers 2401.07075, arXiv.org, revised Mar 2024.
25. Ogundari, Kolawole, 2021. "A systematic review of statistical methods for estimating an education production function," MPRA Paper 105283, University Library of Munich, Germany.
26. Daria Loginova & Stefan Mann, 2023. "Measuring stability and structural breaks: Applications in social sciences," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 302-320, April.
27. Riccardo Di Francesco, 2024. "Aggregation Trees," Papers 2410.11408, arXiv.org, revised Oct 2025.