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Predicting school dropout with administrative data: new evidence from Guatemala and Honduras

Acceso Abierto
ID Minciencias: ART-0000127789-13
Ranking: ART-ART_A2

Abstract:

School dropout is a growing concern across Latin America because of its negative social and economic consequences. Identifying who is likely to drop out, and therefore could be targeted for interventions, is a well-studied prediction problem in countries with strong administrative data. In this paper, we use new data in Guatemala and Honduras to estimate some of the first dropout prediction models for lower-middle income countries. These models correctly identify 80% of sixth grade students who will drop out within the next year, performing better than other commonly used targeting approaches and as well as models used in the U.S.

Tópico:

Poverty, Education, and Child Welfare

Citaciones:

Citations: 34
34

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Paperbuzz Score: 0
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Información de la Fuente:

SCImago Journal & Country Rank
FuenteEducation Economics
Cuartil año de publicaciónNo disponible
Volumen26
Issue4
Páginas356 - 372
pISSNNo disponible
ISSN1469-5782

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Artículo de revista