Grow the pie, or have it? Using machine learning to impact heterogeneity in the Ultra-poor graduation model
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Title |
Grow the pie, or have it? Using machine learning to impact heterogeneity in the Ultra-poor graduation model
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Creator |
Chowdhury, Reajul Alam
Ceballos-Sierra, Federico Sulaiman, Munshi |
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Subject |
evaluation
machine learning modelling poverty impact poverty alleviation household expenditure |
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Date |
2023-11-22
2023-12-04T08:47:06Z 2023-12-04T08:47:06Z |
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Type |
Journal Article
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Identifier |
Chowdhury, R.A.; Ceballos-Sierra, F.; Sulaiman, M. (2023) Grow the pie, or have it? Using machine learning to impact heterogeneity in the Ultra-poor graduation model. Journal of Development Effectiveness, Online first paper (2023-11-22). ISSN: 1943-9407
1943-9407 https://hdl.handle.net/10568/134938 https://doi.org/10.1080/19439342.2023.2276928 |
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Language |
en
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Rights |
Copyrighted; all rights reserved
Limited Access |
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Publisher |
Taylor & Francis
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Source |
Journal of Development Effectiveness
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