Policy Learning with New Treatments
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References listed on IDEAS
- Toru Kitagawa & Aleksey Tetenov, 2018.
"Who Should Be Treated? Empirical Welfare Maximization Methods for Treatment Choice,"
Econometrica, Econometric Society, vol. 86(2), pages 591-616, March.
- Toru Kitagawa & Aleksey Tetenov, 2015. "Who should be treated? Empirical welfare maximization methods for treatment choice," CeMMAP working papers CWP10/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Toru Kitagawa & Aleksey Tetenov, 2017. "Who should be treated? Empirical welfare maximization methods for treatment choice," CeMMAP working papers CWP24/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Toru Kitagawa & Aleksey Tetenov, 2015. "Who should be Treated? Empirical Welfare Maximization Methods for Treatment Choice," Carlo Alberto Notebooks 402, Collegio Carlo Alberto.
- Manski, Charles F., 2007. "Minimax-regret treatment choice with missing outcome data," Journal of Econometrics, Elsevier, vol. 139(1), pages 105-115, July.
- Hongming Pu & Bo Zhang, 2021. "Estimating optimal treatment rules with an instrumental variable: A partial identification learning approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(2), pages 318-345, April.
Citations
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Cited by:
- Lihua Lei & Roshni Sahoo & Stefan Wager, 2023. "Policy Learning under Biased Sample Selection," Papers 2304.11735, arXiv.org.
- 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.
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More about this item
NEP fields
This paper has been announced in the following NEP Reports:- NEP-DCM-2022-11-14 (Discrete Choice Models)
- NEP-ECM-2022-11-14 (Econometrics)
- NEP-EXP-2022-11-14 (Experimental Economics)
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