Equality-minded treatment choice
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- Toru Kitagawa & Aleksey Tetenov, 2021. "Equality-Minded Treatment Choice," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 561-574, March.
- Toru Kitagawa & Aleksey Tetenov, 2018. "Equality-minded treatment choice," CeMMAP working papers CWP71/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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Citations
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Cited by:
- FUJISHIMA Shota & HOSHINO Tadao & SUGAWARA Shinya, 2020. "Heterogeneous Treatment Effects of Place-based Policies: Which Cities Should be Targeted?," Discussion papers 20036, Research Institute of Economy, Trade and Industry (RIETI).
- Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
- Susan Athey & Stefan Wager, 2021.
"Policy Learning With Observational Data,"
Econometrica, Econometric Society, vol. 89(1), pages 133-161, January.
- Susan Athey & Stefan Wager, 2017. "Policy Learning with Observational Data," Papers 1702.02896, arXiv.org, revised Sep 2020.
- Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev, 2022.
"Functional Sequential Treatment Allocation,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(539), pages 1311-1323, September.
- Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev, 2018. "Functional Sequential Treatment Allocation," Papers 1812.09408, arXiv.org, revised Aug 2020.
- Chunrong Ai & Yue Fang & Haitian Xie, 2024. "Data-driven Policy Learning for Continuous Treatments," Papers 2402.02535, arXiv.org, revised Nov 2024.
- Toru Kitagawa & Sokbae Lee & Chen Qiu, 2022. "Treatment Choice with Nonlinear Regret," Papers 2205.08586, arXiv.org, revised Oct 2024.
- Toru Kitagawa & Jeff Rowley, 2024. "Bandit algorithms for policy learning: methods, implementation, and welfare-performance," The Japanese Economic Review, Springer, vol. 75(3), pages 407-447, July.
- Riccardo Di Francesco, 2022. "Aggregation Trees," CEIS Research Paper 546, Tor Vergata University, CEIS, revised 20 Nov 2023.
- Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org.
- David Glynn & John Giardina & Julia Hatamyar & Ankur Pandya & Marta Soares & Noemi Kreif, 2024. "Integrating decision modeling and machine learning to inform treatment stratification," Health Economics, John Wiley & Sons, Ltd., vol. 33(8), pages 1772-1792, August.
- Anders Bredahl Kock & David Preinerstorfer, 2024. "Regularizing Discrimination in Optimal Policy Learning with Distributional Targets," Papers 2401.17909, arXiv.org.
- Hugo Bodory & Federica Mascolo & Michael Lechner, 2024. "Enabling Decision-Making with the Modified Causal Forest: Policy Trees for Treatment Assignment," Papers 2406.02241, arXiv.org.
- Daido Kido, 2022. "Distributionally Robust Policy Learning with Wasserstein Distance," Papers 2205.04637, arXiv.org, revised Aug 2022.
- Toru Kitagawa & Weining Wang & Mengshan Xu, 2022. "Policy Choice in Time Series by Empirical Welfare Maximization," Papers 2205.03970, arXiv.org, revised Jun 2023.
- Riccardo Di Francesco, 2024. "Aggregation Trees," Papers 2410.11408, arXiv.org.
- Ryo Okui, 2024. "The 2023 Japanese Economic Association Nakahara Prize: Recipient—Prof. Toru Kitagawa, Brown University and University College London," The Japanese Economic Review, Springer, vol. 75(3), pages 405-406, July.
- Kock, Anders Bredahl & Preinerstorfer, David & Veliyev, Bezirgen, 2023.
"Treatment recommendation with distributional targets,"
Journal of Econometrics, Elsevier, vol. 234(2), pages 624-646.
- Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev, 2020. "Treatment recommendation with distributional targets," Papers 2005.09717, arXiv.org, revised Apr 2022.
- Dalia Ghanem & D'esir'e K'edagni & Ismael Mourifi'e, 2023. "Evaluating the Impact of Regulatory Policies on Social Welfare in Difference-in-Difference Settings," Papers 2306.04494, arXiv.org, revised Jun 2023.
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Keywords
Program evaluation; Treatment choice; Social welfare; Inequality index; Gini coefficient;All these keywords.
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