Working Paper

Predicting School Dropout with Administrative Data : New Evidence from Guatemala and Honduras

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collection.link.5
https://openknowledge.worldbank.org/handle/10986/9
collection.name.5
Policy Research Working Papers
dc.contributor.author
Adelman, Melissa
dc.contributor.author
Haimovich, Francisco
dc.contributor.author
Ham, Andres
dc.contributor.author
Vazquez, Emmanuel
dc.date.accessioned
2017-07-19T18:08:36Z
dc.date.available
2017-07-19T18:08:36Z
dc.date.issued
2017-07
dc.date.lastModified
2020-12-07T08:41:46Z
dc.description.abstract
Across Latin America, school dropout is a growing concern, because of its negative social and economic consequences. Although a wide range of interventions hold potential to reduce dropout rates, policy makers in many countries must first address the basic question of how to target limited resources effectively for such interventions. Identifying who is most likely to drop out and, therefore, who should be prioritized for targeting, is a prediction problem that has been addressed in a rich set of research in countries with strong education system data. This paper makes use of newly established administrative data systems in Guatemala and Honduras, to estimate some of the first dropout prediction models for lower-middle-income countries. These models can correctly identify 80 percent of sixth grade students who will drop out in the transition to lower secondary school, performing as well as models used in the United States and providing more accurate results than other commonly used targeting approaches.
en
dc.identifier
http://documents.worldbank.org/curated/en/273541499700395624/Predicting-school-dropout-with-administrative-data-new-evidence-from-Guatemala-and-Honduras
dc.identifier.uri
http://hdl.handle.net/10986/27645
dc.language
English
dc.language.iso
en_US
dc.publisher
World Bank, Washington, DC
dc.relation.ispartofseries
Policy Research Working Paper;No. 8142
dc.rights
CC BY 3.0 IGO
dc.rights.holder
World Bank
dc.rights.uri
http://creativecommons.org/licenses/by/3.0/igo
dc.subject
DROPOUT RATES
dc.subject
SCHOOL ENROLLMENT
dc.subject
SECONDARY EDUCATION
dc.subject
PREDICTIVE MODEL
dc.title
Predicting School Dropout with Administrative Data
en
dc.title.subtitle
New Evidence from Guatemala and Honduras
en
dc.type
Working Paper
en
okr.associatedcontent
https://openknowledge.worldbank.org/handle/10986/30146 Accepted journal manuscript
okr.crossref.title
Predicting School Dropout with Administrative Data: New Evidence from Guatemala and Honduras
okr.date.disclosure
2017-07-10
okr.doctype
Publications & Research
okr.doctype
Publications & Research :: Policy Research Working Paper
okr.docurl
http://documents.worldbank.org/curated/en/273541499700395624/Predicting-school-dropout-with-administrative-data-new-evidence-from-Guatemala-and-Honduras
okr.googlescholar.linkpresent
yes
okr.identifier.doi
10.1596/1813-9450-8142
okr.identifier.externaldocumentum
090224b084dafee0_1_0
okr.identifier.internaldocumentum
27714679
okr.identifier.report
WPS8142
okr.imported
true
okr.language.supported
en
okr.pdfurl
http://documents.worldbank.org/curated/en/273541499700395624/pdf/WPS8142.pdf
en
okr.region.administrative
Latin America & Caribbean
okr.region.country
Guatemala
okr.region.country
Honduras
okr.topic
Education :: Economics of Education
okr.topic
Education :: Education For All
okr.topic
Education :: Education Reform and Management
okr.topic
Education :: Educational Policy and Planning
okr.topic
Education :: Secondary Education
okr.unit
Education Global Practice Group

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