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Using Causal Forests to Predict Treatment Heterogeneity: An Application to Summer Jobs

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Cited by:

  1. Lechner, Michael, 2018. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," IZA Discussion Papers 12040, Institute of Labor Economics (IZA).
  2. 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.
  3. Carlana, Michela & La Ferrara, Eliana, 2021. "Apart but Connected: Online Tutoring and Student Outcomes during the COVID-19 Pandemic," IZA Discussion Papers 14094, Institute of Labor Economics (IZA).
  4. Andrew Shipilov & Yeonsin Ahn & Henrich Greve & Tim Rowley, 2024. "The impact of governance practices on firm outcomes: a machine-learning exploration," Journal of Organization Design, Springer;Organizational Design Community, vol. 13(2), pages 45-64, June.
  5. Badruddoza, Syed & Amin, Modhurima & McCluskey, Jill, 2019. "Assessing the Importance of an Attribute in a Demand SystemStructural Model versus Machine Learning," Working Papers 2019-5, School of Economic Sciences, Washington State University.
  6. Diogo G. C. Britto & Paolo Pinotti & Breno Sampaio, 2022. "The Effect of Job Loss and Unemployment Insurance on Crime in Brazil," Econometrica, Econometric Society, vol. 90(4), pages 1393-1423, July.
  7. Mesplé-Somps, Sandrine & Nilsson, Björn, 2023. "Role models, aspirations and desire to migrate," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 819-839.
  8. Michael C Knaus & Michael Lechner & Anthony Strittmatter, 2021. "Machine learning estimation of heterogeneous causal effects: Empirical Monte Carlo evidence," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 134-161.
  9. Hayakawa, Kazunobu & Keola, Souknilanh & Silaphet, Korrakoun & Yamanouchi, Kenta, 2022. "Estimating the impacts of international bridges on foreign firm locations: a machine learning approach," IDE Discussion Papers 847, Institute of Developing Economies, Japan External Trade Organization(JETRO).
  10. Chang Cai & Sandy Dall’Erba, 2021. "On the evaluation of heterogeneous climate change impacts on US agriculture: does group membership matter?," Climatic Change, Springer, vol. 167(1), pages 1-23, July.
  11. Hashibul Hassan & Asad Islam & Abu Siddique & Liang Choon Wang, 2024. "Telementoring and Homeschooling During School Closures: a Randomised Experiment in Rural Bangladesh," The Economic Journal, Royal Economic Society, vol. 134(662), pages 2418-2438.
  12. 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.
  13. Naguib, Costanza, 2019. "Estimating the Heterogeneous Impact of the Free Movement of Persons on Relative Wage Mobility," Economics Working Paper Series 1903, University of St. Gallen, School of Economics and Political Science.
  14. Burgess, Simon & Metcalfe, Robert & Sadoff, Sally, 2021. "Understanding the response to financial and non-financial incentives in education: Field experimental evidence using high-stakes assessments," Economics of Education Review, Elsevier, vol. 85(C).
  15. Jeffrey Smith, 2022. "Treatment Effect Heterogeneity," Evaluation Review, , vol. 46(5), pages 652-677, October.
  16. Ying Deng & Qianqian Yue & Xin Zhao, 2024. "What Does Air Quality Information Disclosure Deliver and to Whom? Evidence from the Ambient Air Quality Standard (2012) Program in China," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(11), pages 2859-2887, November.
  17. Michael Lechner & Jana Mareckova, 2024. "Comprehensive Causal Machine Learning," Papers 2405.10198, arXiv.org.
  18. Buhl-Wiggers, Julie & Kerwin, Jason T. & Muñoz-Morales, Juan & Smith, Jeffrey & Thornton, Rebecca, 2024. "Some children left behind: Variation in the effects of an educational intervention," Journal of Econometrics, Elsevier, vol. 243(1).
  19. 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.
  20. Jau-er Chen & Chien-Hsun Huang & Jia-Jyun Tien, 2021. "Debiased/Double Machine Learning for Instrumental Variable Quantile Regressions," Econometrics, MDPI, vol. 9(2), pages 1-18, April.
  21. Paul S. Clarke & Annalivia Polselli, 2023. "Double Machine Learning for Static Panel Models with Fixed Effects," Papers 2312.08174, arXiv.org, revised Dec 2024.
  22. J. Michelle Brock & Ralph De Haas, 2023. "Discriminatory Lending: Evidence from Bankers in the Lab," American Economic Journal: Applied Economics, American Economic Association, vol. 15(2), pages 31-68, April.
  23. Ziwei Cong & Jia Liu & Puneet Manchanda, 2021. "The Role of "Live" in Livestreaming Markets: Evidence Using Orthogonal Random Forest," Papers 2107.01629, arXiv.org, revised Sep 2022.
  24. Kayo Murakami & Hideki Shimada & Yoshiaki Ushifusa & Takanori Ida, 2022. "Heterogeneous Treatment Effects Of Nudge And Rebate: Causal Machine Learning In A Field Experiment On Electricity Conservation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1779-1803, November.
  25. Engberg, Erik & Görg, Holger & Lodefalk, Magnus & Javed, Farrukh & Längkvist, Martin & Monteiro, Natália & Kyvik Nordås, Hildegunn & Pulito, Giuseppe & Schroeder, Sarah & Tang, Aili, 2023. "AI Unboxed and Jobs: A Novel Measure and Firm-Level Evidence from Three Countries," Ratio Working Papers 370, The Ratio Institute.
  26. Alpino, Matteo & Hauge, Karen Evelyn & Kotsadam, Andreas & Markussen, Simen, 2022. "Effects of dialogue meetings on sickness absence—Evidence from a large field experiment," Journal of Health Economics, Elsevier, vol. 83(C).
  27. 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.
  28. Michael Lechner & Jana Mareckova, 2022. "Modified Causal Forest," Papers 2209.03744, arXiv.org.
  29. Pamela Giustinelli & Matthew D. Shapiro, 2024. "SeaTE: Subjective Ex Ante Treatment Effect of Health on Retirement," American Economic Journal: Applied Economics, American Economic Association, vol. 16(2), pages 278-317, April.
  30. Sandrine Mesplé-Somps and & Björn Nilsson, 2020. "Role models and migration intentions," Working Paper 519bfbde-8d2e-4e86-bd62-0, Agence française de développement.
  31. Tomomi Tanaka, 2019. "Human Capital Development in Ghana," World Bank Publications - Reports 34181, The World Bank Group.
  32. Amin, Modhurima Dey & Badruddoza, Syed & McCluskey, Jill J., 2021. "Predicting access to healthful food retailers with machine learning," Food Policy, Elsevier, vol. 99(C).
  33. Yash Raj Shrestha & Vivianna Fang He & Phanish Puranam & Georg von Krogh, 2021. "Algorithm Supported Induction for Building Theory: How Can We Use Prediction Models to Theorize?," Organization Science, INFORMS, vol. 32(3), pages 856-880, May.
  34. Valente, Marica, 2023. "Policy evaluation of waste pricing programs using heterogeneous causal effect estimation," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
  35. Michael C. Knaus, 2021. "A double machine learning approach to estimate the effects of musical practice on student’s skills," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 282-300, January.
  36. Miller, Steve, 2020. "Causal forest estimation of heterogeneous and time-varying environmental policy effects," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
  37. Achim Ahrens & Alessandra Stampi‐Bombelli & Selina Kurer & Dominik Hangartner, 2024. "Optimal multi‐action treatment allocation: A two‐phase field experiment to boost immigrant naturalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1379-1395, November.
  38. Emma Riley, 2024. "Resisting Social Pressure in the Household Using Mobile Money: Experimental Evidence on Microenterprise Investment in Uganda," American Economic Review, American Economic Association, vol. 114(5), pages 1415-1447, May.
  39. Carter, Michael R. & Tjernström, Emilia & Toledo, Patricia, 2019. "Heterogeneous impact dynamics of a rural business development program in Nicaragua," Journal of Development Economics, Elsevier, vol. 138(C), pages 77-98.
  40. Cevat Giray Aksoy & Christopher S. Carpenter & Ralph De Haas & Mathias Dolls & Lisa Windsteiger, 2023. "Reducing Sexual Orientation Discrimination: Experimental Evidence from Basic Information Treatments," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(1), pages 35-59, January.
  41. Hayakawa, Kazunobu & Keola, Souknilanh & Urata, Shujiro, 2022. "How effective was the restaurant restraining order against COVID-19? A nighttime light study in Japan," Japan and the World Economy, Elsevier, vol. 63(C).
  42. Jau-er Chen & Chen-Wei Hsiang, 2019. "Causal Random Forests Model Using Instrumental Variable Quantile Regression," Econometrics, MDPI, vol. 7(4), pages 1-22, December.
  43. Marianne Bertrand & Bruno Crépon & Alicia Marguerie & Patrick Premand, 2021. "Do Workfare Programs Live Up to Their Promises? Experimental Evidence from Cote D’Ivoire," NBER Working Papers 28664, National Bureau of Economic Research, Inc.
  44. Lundberg, Ian & Brand, Jennie E. & Jeon, Nanum, 2022. "Researcher reasoning meets computational capacity: Machine learning for social science," SocArXiv s5zc8, Center for Open Science.
  45. Thomas Le Barbanchon & Diego Ubfal & Federico Araya, 2023. "The Effects of Working While in School: Evidence from Employment Lotteries," American Economic Journal: Applied Economics, American Economic Association, vol. 15(1), pages 383-410, January.
  46. Costanza Naguib, 2023. "Is the Impact of Opening the Borders Heterogeneous?," Diskussionsschriften dp2312, Universitaet Bern, Departement Volkswirtschaft.
  47. Jonathan M.V. Davis & Sara B. Heller, 2017. "Rethinking the Benefits of Youth Employment Programs: The Heterogeneous Effects of Summer Jobs," NBER Working Papers 23443, National Bureau of Economic Research, Inc.
  48. 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.
  49. Jonathan M.V. Davis & Sara B. Heller, 2020. "Rethinking the Benefits of Youth Employment Programs: The Heterogeneous Effects of Summer Jobs," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 664-677, October.
  50. Pons Rotger, Gabriel & Rosholm, Michael, 2020. "The Role of Beliefs in Long Sickness Absence: Experimental Evidence from a Psychological Intervention," IZA Discussion Papers 13582, Institute of Labor Economics (IZA).
  51. Axenbeck, Janna & Berner, Anne & Kneib, Thomas, 2022. "What drives the relationship between digitalization and industrial energy demand? Exploring firm-level heterogeneity," ZEW Discussion Papers 22-059, ZEW - Leibniz Centre for European Economic Research.
  52. O'Neill, E. & Weeks, M., 2018. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Cambridge Working Papers in Economics 1865, Faculty of Economics, University of Cambridge.
  53. Nora Bearth & Michael Lechner, 2024. "Causal Machine Learning for Moderation Effects," Papers 2401.08290, arXiv.org, revised Jan 2025.
  54. Ruyi Ge & Zhiqiang (Eric) Zheng & Xuan Tian & Li Liao, 2021. "Human–Robot Interaction: When Investors Adjust the Usage of Robo-Advisors in Peer-to-Peer Lending," Information Systems Research, INFORMS, vol. 32(3), pages 774-785, September.
  55. Pedro Forquesato, 2022. "Who Benefits from Political Connections in Brazilian Municipalities," Papers 2204.09450, arXiv.org.
  56. Evan D. Peet & Dana Schultz & Susan Lovejoy & Fuchiang (Rich) Tsui, 2023. "Variation in the infant health effects of the women, infants, and children program by predicted risk using novel machine learning methods," Health Economics, John Wiley & Sons, Ltd., vol. 32(1), pages 194-217, January.
  57. Le Barbanchon, Thomas & Ubfal, Diego & Araya, Federico, 2020. "The Effects of Working While in School: Evidence from Uruguayan Lotteries," IZA Discussion Papers 13929, Institute of Labor Economics (IZA).
  58. Madhura Dasgupta & Samarth Gupta, 2024. "What Determines Enterprise Borrowing from Self Help Groups? An Interpretable Supervised Machine Learning Approach," Journal of Financial Services Research, Springer;Western Finance Association, vol. 66(1), pages 77-99, August.
  59. Arthur Charpentier & Emmanuel Flachaire & Ewen Gallic, 2023. "Optimal Transport for Counterfactual Estimation: A Method for Causal Inference," Papers 2301.07755, arXiv.org.
  60. Ajit Desai, 2023. "Machine Learning for Economics Research: When What and How?," Papers 2304.00086, arXiv.org, revised Apr 2023.
  61. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  62. Dinarte, Lelys & Egaña del Sol, Pablo & Martínez, Claudia & Rojas Alvarado, Cindy Jacqueline, 2024. "When Emotion Regulation Matters: The Efficacy of Socio-Emotional Learning to Address School-Based Violence in Central America," IDB Publications (Working Papers) 13448, Inter-American Development Bank.
  63. Dutt, Satyajit & Radermacher, Jan W., 2023. "Age, wealth, and the MPC in Europe: A supervised machine learning approach," SAFE Working Paper Series 383, Leibniz Institute for Financial Research SAFE.
  64. Anna Baiardi & Andrea A Naghi, 2024. "The value added of machine learning to causal inference: evidence from revisited studies," The Econometrics Journal, Royal Economic Society, vol. 27(2), pages 213-234.
  65. Michela Carlana & Eliana La Ferrara & Paolo Pinotti, 2022. "Goals and Gaps: Educational Careers of Immigrant Children," Econometrica, Econometric Society, vol. 90(1), pages 1-29, January.
  66. Evan D. Peet & Dana Schultz & Susan Lovejoy & Fuchiang (Rich) Tsui, 2024. "The infant health effects of doulas: Leveraging big data and machine learning to inform cost‐effective targeting," Health Economics, John Wiley & Sons, Ltd., vol. 33(6), pages 1387-1411, June.
  67. M. Kate Bundorf & Maria Polyakova & Ming Tai-Seale, 2019. "How do Humans Interact with Algorithms? Experimental Evidence from Health Insurance," NBER Working Papers 25976, National Bureau of Economic Research, Inc.
  68. Kelvin Mulungu & Zewdu Ayalew Abro & Wambui Beatrice Muriithi & Menale Kassie & Miachael Kidoido & Subramanian Sevgan & Samira Mohamed & Chrysantus Tanga & Fathiya Khamis, 2024. "One size does not fit all: Heterogeneous economic impact of integrated pest management practices for mango fruit flies in Kenya—a machine learning approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 75(1), pages 261-279, February.
  69. 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.
  70. Macours, Karen & Behaghel, Luc & Gignoux, Jérémie, 2020. "Social learning in agriculture: does smallholder heterogeneity impede technology diffusion in Sub-Saharan Africa?," CEPR Discussion Papers 15220, C.E.P.R. Discussion Papers.
  71. Anya Shchetkina & Ron Berman, 2024. "When Is Heterogeneity Actionable for Personalization?," Papers 2411.16552, arXiv.org.
  72. Doleac, Jennifer & Eckhouse, Laurel & Foster-Moore, Eric & Harris, Allison & Walker, Hannah & White, Ariel, 2022. "Registering Returning Citizens to Vote," IZA Discussion Papers 15121, Institute of Labor Economics (IZA).
  73. Strittmatter, Anthony, 2023. "What is the value added by using causal machine learning methods in a welfare experiment evaluation?," Labour Economics, Elsevier, vol. 84(C).
  74. Dinarte Diaz, Lelys & Egana-delSol, Pablo & Martínez A., Claudia & Rojas A., Cindy, 2024. "When Emotion Regulation Matters: The Efficacy of Socio-Emotional Learning to Address School-Based Violence in Central America," IZA Discussion Papers 16831, Institute of Labor Economics (IZA).
  75. Eoghan O'Neill & Melvyn Weeks, 2018. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Papers 1810.09179, arXiv.org, revised Oct 2019.
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