Performance of a novel machine learning-based proxy means test in comparison to other methods for targeting pro-poor water subsidies in Ghana-Reference-Cited by-同舟云学术

Performance of a novel machine learning-based proxy means test in comparison to other methods for targeting pro-poor water subsidies in Ghana

Published:2022 Issue: Volume:7 Page:100098
ISSN:2352-7285
Container-title:Development Engineering
language:en
Short-container-title:Development Engineering

Author:

Poulin Chloé^ORCID,Trimmer John^ORCID,Press-Williams Jessica,Yachori Bashiru,Khush Ranjiv^ORCID,Peletz Rachel^ORCID,Delaire Caroline^ORCID

Publisher

Elsevier BV

Subject

Computer Science Applications,General Economics, Econometrics and Finance,General Engineering,Development

Reference64 articles.

1. Study of the Distributional Performance of Piped Water Consumption Subsidies in 10 Developing Countries;Abramovsky,2020

2. Predictive modelling for solar thermal energy systems: a comparison of support vector regression, random forest, extra trees and regression trees;Ahmad;J. Clean. Prod.,2018

3. Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance (Working Paper No. 29070), Working Paper Series;Aiken,2021

4. Targeting development aid with machine learning and mobile phone data: evidence from an anti-poverty intervention in Afghanistan;Aiken,2020

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