Estimating Treatment Heterogeneity of International Monetary Fund Programs on Child Poverty with Generalized Random Forest
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DOI: 10.31219/osf.io/awfjt
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Cited by:
- Daoud, Adel & Kim, Rockli & Subramanian, S.V., 2019. "Predicting women's height from their socioeconomic status: A machine learning approach," Social Science & Medicine, Elsevier, vol. 238(C), pages 1-1.
- Adel Daoud & Anders Herlitz & SV Subramanian, 2020. "Combining distributive ethics and causal Inference to make trade-offs between austerity and population health," Papers 2007.15550, arXiv.org, revised Aug 2020.
- Sourabh Balgi & Jose M. Pe~na & Adel Daoud, 2022. "$\rho$-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows," Papers 2209.07111, arXiv.org, revised Aug 2024.
- Sourabh Balgi & Jose M. Pe~na & Adel Daoud, 2022. "Counterfactual Analysis of the Impact of the IMF Program on Child Poverty in the Global-South Region using Causal-Graphical Normalizing Flows," Papers 2202.09391, arXiv.org.
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