Publication:
Learning Poverty: Measures and Simulations

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dc.contributor.authorAzevedo, Joao Pedro
dc.date.accessioned2020-10-22T17:57:37Z
dc.date.available2020-10-22T17:57:37Z
dc.date.issued2020-10
dc.description.abstractCOVID-19-related school closures are pushing countries off track from achieving their learning goals. This paper builds on the concept of learning poverty and draws on axiomatic properties from social choice literature to propose and motivate a distribution-sensitive measures of learning poverty. Numerical, empirical, and practical reasons for the relevance and usefulness of these complementary inequality sensitive aggregations for simulating the effects of COVID-19 are presented. In a post-COVID-19 scenario of no remediation and low mitigation effectiveness for the effects of school closures, the simulations show that learning poverty increases from 53 to 63 percent. Most of this increase seems to occur in lower-middle-income and upper-middle-income countries, especially in East Asia and the Pacific, Latin America, and South Asia. The countries that had the highest levels of learning poverty before COVID-19 (predominantly in Africa and the low-income country group) might have the smallest absolute and relative increases in learning poverty, reflecting how great the learning crisis was in those countries before the pandemic. Measures of learning poverty and learning deprivation sensitive to changes in distribution, such as gap and severity measures, show differences in learning loss regional rankings. Africa stands to lose the most. Countries with higher inequality among the learning poor, as captured by the proposed learning poverty severity measure, would need far greater adaptability to respond to broader differences in student needs.en
dc.identifierhttp://documents.worldbank.org/curated/en/232501603286799234/Learning-Poverty-Measures-and-Simulations
dc.identifier.doi10.1596/1813-9450-9446
dc.identifier.urihttps://hdl.handle.net/10986/34654
dc.languageEnglish
dc.publisherWorld Bank, Washington, DC
dc.relation.ispartofseriesPolicy Research Working Paper;No. 9446
dc.rightsCC BY 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/igo
dc.subjectLEARNING POVERTY
dc.subjectPRIMARY EDUCATION
dc.subjectSUSTAINABLE DEVELOPMENT GOALS
dc.subjectSDGs
dc.subjectCORONAVIRUS
dc.subjectCOVID-19
dc.subjectPANDEMIC IMPACT
dc.titleLearning Povertyen
dc.title.subtitleMeasures and Simulationsen
dc.typeWorking Paperen
dc.typeDocument de travailfr
dc.typeDocumento de trabajoes
dspace.entity.typePublication
okr.crossref.titleLearning Poverty: Measures and Simulations
okr.date.disclosure2020-10-21
okr.doctypePublications & Research
okr.doctypePublications & Research::Policy Research Working Paper
okr.docurlhttp://documents.worldbank.org/curated/en/232501603286799234/Learning-Poverty-Measures-and-Simulations
okr.guid232501603286799234
okr.identifier.doi10.1596/1813-9450-9446
okr.identifier.doihttp://dx.doi.org/10.1596/1813-9450-9446
okr.identifier.externaldocumentum090224b087eec0d1_2_0
okr.identifier.internaldocumentum32503844
okr.identifier.reportWPS9446
okr.importedtrueen
okr.language.supporteden
okr.pdfurlhttp://documents.worldbank.org/curated/en/232501603286799234/pdf/Learning-Poverty-Measures-and-Simulations.pdfen
okr.statistics.combined12086
okr.statistics.dr232501603286799234
okr.statistics.drstats3518
okr.topicEducation::Education For All
okr.topicEducation::Education Indicators and Statistics
okr.topicEducation::Education and Digital Divide
okr.topicEducation::Effective Schools and Teachers
okr.topicEducation::Primary Education
okr.unitEducation Global Practice
relation.isAuthorOfPublication360f7a2e-0784-56e1-acf4-7f805fd50257
relation.isAuthorOfPublication.latestForDiscovery360f7a2e-0784-56e1-acf4-7f805fd50257
relation.isSeriesOfPublication26e071dc-b0bf-409c-b982-df2970295c87
relation.isSeriesOfPublication.latestForDiscovery26e071dc-b0bf-409c-b982-df2970295c87
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