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Imputing Poverty Indicators without Consumption Data: An Exploratory Analysis

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dc.contributor.authorDang, Hai-Anh H.
dc.contributor.authorKilic, Talip
dc.contributor.authorAbanokova, Kseniya
dc.contributor.authorCarletto, Calogero
dc.contributor.authorAbanokova, Ksenia
dc.date.accessioned2024-08-19T13:48:23Z
dc.date.available2024-08-19T13:48:23Z
dc.date.issued2024-08-19
dc.description.abstractAccurate poverty measurement relies on household consumption data, but such data are often inadequate, outdated, or display inconsistencies over time in poorer countries. To address these data challenges, this paper employs survey-to-survey imputation to produce estimates for several poverty indicators, including headcount poverty, extreme poverty, poverty gap, near-poverty rates, as well as mean consumption levels and the entire consumption distribution. Analysis of 22 multi-topic household surveys conducted over the past decade in Bangladesh, Ethiopia, Malawi, Nigeria, Tanzania, and Viet Nam yields encouraging results. Adding household utility expenditures or food expenditures to basic imputation models with household-level demographic, employment, and asset variables could improve the probability of imputation accuracy by 0.1 to 0.4. Adding predictors from geospatial data could further increase imputation accuracy. The analysis also shows that a larger time interval between surveys is associated with a lower probability of predicting some poverty indicators, and that a better imputation model goodness-of-fit (R2) does not necessarily help. The results offer cost-saving inputs for future survey design.en
dc.identifierhttp://documents.worldbank.org/curated/en/099228108142416030/IDU1c7119da61fdaa14c4f18085152e810a6a8da
dc.identifier.doi10.1596/1813-9450-10867
dc.identifier.urihttps://hdl.handle.net/10986/42055
dc.languageEnglish
dc.language.isoen_US
dc.publisherWashington, DC: World Bank
dc.relation.ispartofseriesPolicy Research Working Paper; 10867
dc.rightsCC BY 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/igo/
dc.subjectCONSUMPTION
dc.subjectPOVERTY
dc.subjectSURVEY-TO-SURVEY IMPUTATIONS
dc.subjectHOUSEHOLD SURVEYS
dc.subjectVIET NAM
dc.subjectETHIOPIA
dc.subjectMALAWI
dc.subjectNIGERIA
dc.subjectTANZANIA
dc.subjectSUB-SAHARAN AFRICA
dc.subjectNO POVERTY
dc.subjectSDG 1
dc.subjectRESPONSIBLE CONSUMPTION AND PRODUCTION
dc.subjectSDG 12
dc.titleImputing Poverty Indicators without Consumption Dataen
dc.title.subtitleAn Exploratory Analysisen
dc.typeWorking Paper
dspace.entity.typePublication
okr.crossref.titleImputing Poverty Indicators without Consumption Data: An Exploratory Analysis
okr.date.disclosure2024-08-19
okr.date.doiregistration2025-04-30T04:31:42.642751Z
okr.date.lastmodified2024-08-14T00:00:00Zen
okr.doctypePolicy Research Working Paper
okr.doctypePublications & Research
okr.docurlhttp://documents.worldbank.org/curated/en/099228108142416030/IDU1c7119da61fdaa14c4f18085152e810a6a8da
okr.guid099228108142416030
okr.identifier.docmidIDU-c7119da6-fdaa-4c4f-8085-52e810a6a8da
okr.identifier.doi10.1596/1813-9450-10867
okr.identifier.doihttps://doi.org/10.1596/1813-9450-10867
okr.identifier.externaldocumentum34377257
okr.identifier.internaldocumentum34377257
okr.identifier.reportWPS10867
okr.import.id5081
okr.importedtrueen
okr.language.supporteden
okr.pdfurlhttp://documents.worldbank.org/curated/en/099228108142416030/pdf/IDU1c7119da61fdaa14c4f18085152e810a6a8da.pdfen
okr.region.geographicalWorld
okr.topicPoverty Reduction::Moving Out Of Poverty
okr.topicPoverty Reduction::Poverty Monitoring & Analysis
okr.topicMacroeconomics and Economic Growth::Consumption
okr.unitLiving Standards Measurement (DECLS)
okr.unitDevelopment Data Group (DECDG)
relation.isAuthorOfPublication6294aeeb-2ae1-5d24-908b-ad69a09277e4
relation.isAuthorOfPublicationd40874d9-de2a-4bac-8cfa-3ddcb7b30070
relation.isAuthorOfPublication.latestForDiscovery6294aeeb-2ae1-5d24-908b-ad69a09277e4
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