Orthogonal policy learning under ambiguity
R d'Adamo - arXiv preprint arXiv:2111.10904, 2021 - arxiv.org
This paper studies the problem of estimating individualized treatment rules when treatment
effects are partially identified, as it is often the case with observational data. By drawing …
effects are partially identified, as it is often the case with observational data. By drawing …
Orthogonal Policy Learning Under Ambiguity
R D'Adamo - 2022 - ideas.repec.org
This paper studies the problem of estimating individualized treatment rules when treatment
effects are partially identified, as it is often the case with observational data. By drawing …
effects are partially identified, as it is often the case with observational data. By drawing …
[PDF][PDF] Orthogonal Policy Learning Under Ambiguity
R D'Adamo - 2023 - rdadamo.github.io
This paper studies the problem of estimating individualized treatment rules when treatment
effects are partially identified, as it is often the case with observational data. By drawing …
effects are partially identified, as it is often the case with observational data. By drawing …
Orthogonal Policy Learning Under Ambiguity
R D'Adamo - 2022 - econpapers.repec.org
This paper studies the problem of estimating individualized treatment rules when treatment
effects are partially identified, as it is often the case with observational data. By drawing …
effects are partially identified, as it is often the case with observational data. By drawing …
Orthogonal Policy Learning Under Ambiguity
R D'Adamo - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
This paper studies the problem of estimating individualized treatment rules when treatment
effects are partially identified, as it is often the case with observational data. By drawing …
effects are partially identified, as it is often the case with observational data. By drawing …
[引用][C] Orthogonal Policy Learning Under Ambiguity
R d'Adamo - 2022 - pure.au.dk
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[PDF][PDF] Orthogonal Policy Learning Under Ambiguity
R D'Adamo - 2022 - tse-fr.eu
This paper studies the problem of estimating individualized treatment rules when treatment
effects are partially identified, as it is often the case with observational data. By drawing …
effects are partially identified, as it is often the case with observational data. By drawing …