Which social program supports sustainable grass-root finance? Machine-learning evidence
Journal article, Peer reviewed
Published version
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http://hdl.handle.net/11250/2635421Utgivelsesdato
2019Metadata
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Originalversjon
Gonzales Martinez, R. (2019). Which social program supports sustainable grass-root finance? Machine-learning evidence. International Journal of Sustainable Development and World Ecology, 27(5), 389-395. doi: 10.1080/13504509.2019.1706059Sammendrag
Resources for development are used efficiently when social programs help to promote at the same time the sustainability of grass-root financial associations at the bottom of the pyramid. This study applies machine-learning to a worldwide database of grass-root associations in order to identify which social programs are good predictors of financial returns in the groups. The results indicate that education, income-generating activities and health programs are the most frequent programs provided by development agencies. Business training is not the most frequent intervention applied to grass-root associations, but it is in fact the most important social program to encourage financial sustainability, particularly after a development agency stops working with a group and leaves the community. Theoretical and practical implications of the findings are discussed.