Estimation of conditional average treatment effects with high-dimensional data
Given the unconfoundedness assumption, we propose new nonparametric estimators for the reduced dimensional conditional average treatment effect (CATE) function. In the first stage, the nuisance functions necessary for identifying CATE are estimated by machine learning methods, allowing the number of...
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| Main Authors: | , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2020
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/soe_research/2455 https://ink.library.smu.edu.sg/context/soe_research/article/3454/viewcontent/Unconditional_Quantile_Regression_High_D_sv.pdf |
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| Institution: | Singapore Management University |
| Language: | English |