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The sorted effects method: discovering heterogeneous effects beyond their averages

Citations

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Cited by:

  1. Matthew A. Masten & Alexandre Poirier & Muyang Ren, 2025. "A General Approach to Relaxing Unconfoundedness," Papers 2501.15400, arXiv.org.
  2. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
  3. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers 61/17, Institute for Fiscal Studies.
  4. 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).
  5. Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
  6. Tsionas, Mike, 2022. "Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries," International Journal of Production Economics, Elsevier, vol. 249(C).
  7. Diego Marino Fages, 2023. "Migration and trust: Evidence on assimilation from internal migrants," Discussion Papers 2023-08, Nottingham Interdisciplinary Centre for Economic and Political Research (NICEP).
  8. Victor Chernozhukov & Iván Fernández‐Val & Ye Luo, 2018. "The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages," Econometrica, Econometric Society, vol. 86(6), pages 1911-1938, November.
  9. Andrew Baker & Brantly Callaway & Scott Cunningham & Andrew Goodman-Bacon & Pedro H. C. Sant'Anna, 2025. "Difference-in-Differences Designs: A Practitioner's Guide," Papers 2503.13323, arXiv.org, revised Jun 2025.
  10. Sallin, Aurelién, 2021. "Estimating returns to special education: combining machine learning and text analysis to address confounding," Economics Working Paper Series 2109, University of St. Gallen, School of Economics and Political Science.
  11. Kroczek, Martin & Kugler, Philipp, 2022. "Heterogeneous Effects of Monetary and Non-Monetary Job Characteristics on Job Attractiveness in Nursing," VfS Annual Conference 2022 (Basel): Big Data in Economics 264108, Verein für Socialpolitik / German Economic Association.
  12. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
  13. Michael Zimmert & Michael Lechner, 2019. "Nonparametric estimation of causal heterogeneity under high-dimensional confounding," Papers 1908.08779, arXiv.org.
  14. Daniel Jacob, 2019. "Group Average Treatment Effects for Observational Studies," Papers 1911.02688, arXiv.org, revised Mar 2020.
  15. 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.
  16. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
  17. Xiaohong Chen & Wayne Yuan Gao, 2025. "Semiparametric Learning of Integral Functionals on Submanifolds," Cowles Foundation Discussion Papers 2450, Cowles Foundation for Research in Economics, Yale University.
  18. Chi Zhang & Xiangdan Piao & Shunsuke Managi, 2023. "Work Hour Mismatch on Life Evaluation: Full Heterogeneity and Individual- and Country-Level Characteristics of the Most and Least Affected Workers," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 170(2), pages 637-674, November.
  19. Florent Dubois & Christophe Muller, 2022. "Residential segregation matters to racial income gaps: Evidence from South Africa," AMSE Working Papers 2205, Aix-Marseille School of Economics, France.
  20. Strittmatter, Anthony & Wunsch, Conny, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," IZA Discussion Papers 14128, Institute of Labor Economics (IZA).
  21. Deschenes, Olivier & Malloy, Christopher & McDonald, Gavin, 2023. "Causal effects of Renewable Portfolio Standards on renewable investments and generation: The role of heterogeneity and dynamics," Resource and Energy Economics, Elsevier, vol. 75(C).
  22. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Causal Machine-Learning Approach," Papers 2103.10251, arXiv.org, revised Sep 2021.
  23. Yuehao Bai, 2022. "Optimality of Matched-Pair Designs in Randomized Controlled Trials," Papers 2206.07845, arXiv.org.
  24. Sookyo Jeong & Hongseok Namkoong, 2020. "Assessing External Validity Over Worst-case Subpopulations," Papers 2007.02411, arXiv.org, revised Feb 2022.
  25. Laub, Natalie & Boockmann, Bernhard & Kroczek, Martin, 2023. "Tightening Access to Early Retirement: Who Can Adapt?," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277625, Verein für Socialpolitik / German Economic Association.
  26. 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.
  27. Nora Bearth & Michael Lechner, 2024. "Causal Machine Learning for Moderation Effects," Papers 2401.08290, arXiv.org, revised Jan 2025.
  28. Florent Dubois & Christophe Muller, 2022. "Residential segregation matters to racial income gaps," Working Papers hal-03622711, HAL.
  29. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iván Fernández‐Val, 2025. "Fisher–Schultz Lecture: Generic Machine Learning Inference on Heterogeneous Treatment Effects in Randomized Experiments, With an Application to Immunization in India," Econometrica, Econometric Society, vol. 93(4), pages 1121-1164, July.
  30. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  31. Marzi, Giacomo & Balzano, Marco, 2025. "Artificial intelligence and the reconfiguration of NPD Teams: Adaptability and skill differentiation in sustainable product innovation," Technovation, Elsevier, vol. 145(C).
  32. Pullabhotla, Hemant K. & Souza, Mateus, 2022. "Air pollution from agricultural fires increases hypertension risk," Journal of Environmental Economics and Management, Elsevier, vol. 115(C).
  33. Bilancini, Ennio & Boncinelli, Leonardo & Di Paolo, Roberto & Menicagli, Dario & Pizziol, Veronica & Ricciardi, Emiliano & Serti, Francesco, 2022. "Prosocial behavior in emergencies: Evidence from blood donors recruitment and retention during the COVID-19 pandemic," Social Science & Medicine, Elsevier, vol. 314(C).
  34. Chernozhukov, Victor & Fernández-Val, Iván & Newey, Whitney K., 2019. "Nonseparable multinomial choice models in cross-section and panel data," Journal of Econometrics, Elsevier, vol. 211(1), pages 104-116.
  35. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.
  36. Ricardo Masini & Marcelo Medeiros, 2025. "Balancing Flexibility and Interpretability: A Conditional Linear Model Estimation via Random Forest," Papers 2502.13438, arXiv.org.
  37. Florent Dubois & Christophe Muller, 2020. "The Contribution of Residential Segregation to Racial Income Gaps: Evidence from South Africa," EconomiX Working Papers 2020-20, University of Paris Nanterre, EconomiX.
  38. Bin Xiong & Qi Sui, 2025. "The effect of digital economy on rural workforce occupation transformation ability: Evidence from China," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-15, December.
  39. Bernhard Boockmann & Martin Kroczek & Natalie Laub, 2023. "Tightening access to early retirement: who can adapt?," IAW Discussion Papers 142, Institut für Angewandte Wirtschaftsforschung (IAW).
  40. Xiaohong Chen & Wayne Yuan Gao, 2025. "Semiparametric Learning of Integral Functionals on Submanifolds," Papers 2507.12673, arXiv.org, revised Oct 2025.
  41. Kroczek, Martin & Kugler, Philipp, 2024. "Heterogeneous effects of monetary and non-monetary job characteristics on job attractiveness in nursing," Labour Economics, Elsevier, vol. 91(C).
  42. 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 Dec 2021.
  43. Zheng Fang, 2021. "A Unifying Framework for Testing Shape Restrictions," Papers 2107.12494, arXiv.org, revised Aug 2021.
  44. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Machine-Learning Approach," Economics working papers 2021-08, Department of Economics, Johannes Kepler University Linz, Austria.
  45. Posel, Dorrit & Oyenubi, Adeola, 2023. "Heterogeneous gender gaps in mental wellbeing: Do women with low economic status face the biggest gender gaps?," Social Science & Medicine, Elsevier, vol. 332(C).
  46. Jun Ma & Vadim Marmer & Zhengfei Yu, 2025. "Inference on the Distribution of Individual Treatment Effects in Nonseparable Triangular Models," Papers 2509.15401, arXiv.org.
  47. Aur'elien Sallin, 2021. "Estimating returns to special education: combining machine learning and text analysis to address confounding," Papers 2110.08807, arXiv.org, revised Feb 2022.
  48. Martin Kroczek & Philipp Kugler, 2022. "Heterogeneous Effects of Monetary and Non-Monetary Job Characteristics on Job Attractiveness in Nursing," IAW Discussion Papers 139, Institut für Angewandte Wirtschaftsforschung (IAW).
  49. Yuri Fonseca & Marcelo Medeiros & Gabriel Vasconcelos & Alvaro Veiga, 2018. "BooST: Boosting Smooth Trees for Partial Effect Estimation in Nonlinear Regressions," Papers 1808.03698, arXiv.org, revised Jul 2020.
  50. Lopez Garcia, Italo & Luoto, Jill E. & Aboud, Frances E. & Fernald, Lia C.H., 2023. "Group Meetings and Boosters to Sustain Early Impacts on Child Development: Experimental Evidence from Kenya," IZA Discussion Papers 16392, Institute of Labor Economics (IZA).
  51. Kai Feng & Han Hong & Denis Nekipelov, 2024. "Statistical Inference of Optimal Allocations I: Regularities and their Implications," Papers 2403.18248, arXiv.org, revised Jun 2025.
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