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

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 t...

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Main Authors:	Adelman, Melissa, Haimovich, Francisco, Ham, Andres, Vazquez, Emmanuel
Format:	Working Paper
Language:	English en_US
Published:	World Bank, Washington, DC 2017
Subjects:	DROPOUT RATES SCHOOL ENROLLMENT SECONDARY EDUCATION PREDICTIVE MODEL
Online Access:	http://documents.worldbank.org/curated/en/273541499700395624/Predicting-school-dropout-with-administrative-data-new-evidence-from-Guatemala-and-Honduras http://hdl.handle.net/10986/27645

id	okr-10986-27645
recordtype	oai_dc
spelling	okr-10986-276452021-06-08T14:42:47Z Predicting School Dropout with Administrative Data : New Evidence from Guatemala and Honduras Adelman, Melissa Haimovich, Francisco Ham, Andres Vazquez, Emmanuel DROPOUT RATES SCHOOL ENROLLMENT SECONDARY EDUCATION PREDICTIVE MODEL 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. 2017-07-19T18:08:36Z 2017-07-19T18:08:36Z 2017-07 Working Paper http://documents.worldbank.org/curated/en/273541499700395624/Predicting-school-dropout-with-administrative-data-new-evidence-from-Guatemala-and-Honduras http://hdl.handle.net/10986/27645 English en_US Policy Research Working Paper;No. 8142 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper Latin America & Caribbean Guatemala Honduras
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	English en_US
topic	DROPOUT RATES SCHOOL ENROLLMENT SECONDARY EDUCATION PREDICTIVE MODEL
spellingShingle	DROPOUT RATES SCHOOL ENROLLMENT SECONDARY EDUCATION PREDICTIVE MODEL Adelman, Melissa Haimovich, Francisco Ham, Andres Vazquez, Emmanuel Predicting School Dropout with Administrative Data : New Evidence from Guatemala and Honduras
geographic_facet	Latin America & Caribbean Guatemala Honduras
relation	Policy Research Working Paper;No. 8142
description	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.
format	Working Paper
author	Adelman, Melissa Haimovich, Francisco Ham, Andres Vazquez, Emmanuel
author_facet	Adelman, Melissa Haimovich, Francisco Ham, Andres Vazquez, Emmanuel
author_sort	Adelman, Melissa
title	Predicting School Dropout with Administrative Data : New Evidence from Guatemala and Honduras
title_short	Predicting School Dropout with Administrative Data : New Evidence from Guatemala and Honduras
title_full	Predicting School Dropout with Administrative Data : New Evidence from Guatemala and Honduras
title_fullStr	Predicting School Dropout with Administrative Data : New Evidence from Guatemala and Honduras
title_full_unstemmed	Predicting School Dropout with Administrative Data : New Evidence from Guatemala and Honduras
title_sort	predicting school dropout with administrative data : new evidence from guatemala and honduras
publisher	World Bank, Washington, DC
publishDate	2017
url	http://documents.worldbank.org/curated/en/273541499700395624/Predicting-school-dropout-with-administrative-data-new-evidence-from-Guatemala-and-Honduras http://hdl.handle.net/10986/27645
_version_	1764465632524369920

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

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