Publication:
SAE - A Stata Package for Unit Level Small Area Estimation

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dc.contributor.authorNguyen, Minh Cong
dc.contributor.authorCorral, Paul
dc.contributor.authorAzevedo, Joao Pedro
dc.contributor.authorZhao, Qinghua
dc.date.accessioned2018-11-01T18:44:01Z
dc.date.available2018-11-01T18:44:01Z
dc.date.issued2018-10
dc.description.abstractThis paper presents a new family of Stata functions devoted to small area estimation. Small area methods attempt to solve low representativeness of surveys within areas, or the lack of data for specific areas/sub-populations. This is accomplished by incorporating information from outside sources. Such target data sets are becoming increasingly available and can take the form of a traditional population census, but also large scale administrative records from tax administrations, or geospatial information produced using remote sensing. The strength of these target data sets is their granularity on the subpopulations of interest, however, in many cases they lack the ability to collect analytically relevant variables such as welfare or caloric intake. The family of functions introduced follow a modular design to have the flexibility with which these can be expanded in the future. This can be accomplished by the authors and/or other collaborators from the Stata community. Thus far, a major limitation of such analysis in Stata has been the large size of target data sets. The package introduces new mata functions and a plugin used to circumvent memory limitations that inevitably arise when working with big data. From an estimation perspective, the paper starts by implementing a methodology that has been widely used for the production of several poverty maps.en
dc.identifierhttp://documents.worldbank.org/curated/en/398721540906483895/sae-A-Stata-Package-for-Unit-Level-Small-Area-Estimation
dc.identifier.urihttps://hdl.handle.net/10986/30650
dc.languageEnglish
dc.publisherWorld Bank, Washington, DC
dc.relation.ispartofseriesPolicy Research Working Paper;No. 8630
dc.rightsCC BY 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/igo
dc.subjectSMALL AREA ESTIMATION
dc.subjectPOVERTY MAPPING
dc.subjectBIG DATA
dc.subjectGEOSPATIAL ECONOMICS
dc.subjectSTATA
dc.subjectREMOTE SENSING
dc.titleSAE - A Stata Package for Unit Level Small Area Estimationen
dc.typeWorking Paperen
dc.typeDocument de travailfr
dc.typeDocumento de trabajoes
dspace.entity.typePublication
okr.crossref.titleSae: A Stata Package For Unit Level Small Area Estimation
okr.date.disclosure2018-10-30
okr.doctypePublications & Research
okr.doctypePublications & Research::Policy Research Working Paper
okr.docurlhttp://documents.worldbank.org/curated/en/398721540906483895/sae-A-Stata-Package-for-Unit-Level-Small-Area-Estimation
okr.guid398721540906483895
okr.identifier.doi10.1596/1813-9450-8630
okr.identifier.externaldocumentum090224b08652e72f_1_0
okr.identifier.internaldocumentum30562503
okr.identifier.reportWPS8630
okr.importedtrueen
okr.language.supporteden
okr.pdfurlhttp://documents.worldbank.org/curated/en/398721540906483895/pdf/WPS8630.pdfen
okr.statistics.combined3182
okr.statistics.dr398721540906483895
okr.statistics.drstats1523
okr.topicPoverty Reduction::Small Area Estimation Poverty Mapping
okr.unitPoverty and Equity Global Practice
relation.isAuthorOfPublication562ed170-5271-5853-9c3c-a3ad9e16e176
relation.isAuthorOfPublication360f7a2e-0784-56e1-acf4-7f805fd50257
relation.isAuthorOfPublication.latestForDiscovery360f7a2e-0784-56e1-acf4-7f805fd50257
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