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Using data differently and using different data
Stockholm University, Faculty of Social Sciences, Institute for International Economic Studies.
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Number of Authors: 52018 (English)In: Journal of Development Effectiveness, ISSN 1943-9342, E-ISSN 1943-9407, Vol. 10, no 4, p. 462-481Article in journal (Refereed) Published
Abstract [en]

The lack of adequate measures is often an impediment to robust policy evaluation. We discuss three approaches to measurement and data usage that have the potential to improve the way we conduct impact evaluations. First, the creation of new measures, when no adequate ones are available. Second, the use of multiple measures when a single one is not appropriate. And third, the use of machine learning algorithms to evaluate and understand programme impacts. We motivate the relevance of each of the categories by providing examples where they have proved useful in the past. We discuss the challenges and risks involved in each strategy and conclude with an outline of promising directions for future work.

Place, publisher, year, edition, pages
2018. Vol. 10, no 4, p. 462-481
Keywords [en]
Data, measurement, impact evaluation, machine learning
National Category
Social and Economic Geography Media and Communications
Identifiers
URN: urn:nbn:se:su:diva-163748DOI: 10.1080/19439342.2018.1530279ISI: 000452000700005OAI: oai:DiVA.org:su-163748DiVA, id: diva2:1276611
Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-01-08Bibliographically approved

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Almås, Ingvild
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