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GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project

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dc.contributor.authorvan der Weide, Roy
dc.date.accessioned2014-10-02T19:40:15Z
dc.date.available2014-10-02T19:40:15Z
dc.date.issued2014-09
dc.description.abstractThis note adapts results by Huang and Hidiroglou (2003) on Generalized Least Squares estimation and Empirical Bayes prediction for linear mixed models with sampling weights. The objective is to incorporate these results into the poverty mapping approach put forward by Elbers et al. (2003). The estimators presented here have been implemented in version 2.5 of POVMAP, the custom-made poverty mapping software developed by the World Bank.en
dc.identifierhttp://documents.worldbank.org/curated/en/2014/09/20197348/gls-estimation-empirical-bayes-prediction-linear-mixed-models-heteroskedasticity-sampling-weights-background-study-povmap-project
dc.identifier.doi10.1596/1813-9450-7028
dc.identifier.urihttps://hdl.handle.net/10986/20332
dc.languageEnglish
dc.language.isoen_US
dc.publisherWorld Bank Group, Washington, DC
dc.relation.ispartofseriesPolicy Research Working Paper;No. 7028
dc.rightsCC BY 3.0 IGO
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/igo/
dc.subjectCAPITA CONSUMPTION
dc.subjectDEVELOPMENT RESEARCH
dc.subjectESTIMATORS
dc.subjectGEOGRAPHIC TARGETING
dc.subjectHOUSEHOLD INCOME
dc.subjectINCOME
dc.subjectINDEPENDENT VARIABLES
dc.subjectMATRICES
dc.subjectMATRIX
dc.subjectPOVERTY ALLEVIATION
dc.subjectPOVERTY INDICATORS
dc.subjectPREDICTION
dc.subjectPROBABILITIES
dc.subjectPROBABILITY
dc.subjectRA
dc.subjectRESEARCH METHODS
dc.subjectRESEARCH WORKING PAPERS
dc.subjectSAMPLE SIZE
dc.subjectSTANDARD ERRORS
dc.subjectSTATA
dc.subjectSURVEY DATA
dc.subjectTARGETING
dc.subjectYIELDS
dc.titleGLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Projecten
dspace.entity.typePublication
okr.crossref.titleGLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights: A Background Study for the POVMAP Project
okr.date.disclosure2014-09-01
okr.date.doiregistration2025-04-10T10:18:55.853160Z
okr.doctypePublications & Research::Policy Research Working Paper
okr.doctypePublications & Research
okr.docurlhttp://documents.worldbank.org/curated/en/2014/09/20197348/gls-estimation-empirical-bayes-prediction-linear-mixed-models-heteroskedasticity-sampling-weights-background-study-povmap-project
okr.globalpracticeAgriculture
okr.globalpracticeEducation
okr.globalpracticeTransport and ICT
okr.globalpracticePoverty
okr.guid397631468332346764
okr.identifier.doi10.1596/1813-9450-7028
okr.identifier.externaldocumentum000158349_20140911113652
okr.identifier.internaldocumentum20197348
okr.identifier.reportWPS7028
okr.language.supporteden
okr.pdfurlhttp://www-wds.worldbank.org/external/default/WDSContentServer/WDSP/IB/2014/09/11/000158349_20140911113652/Rendered/PDF/WPS7028.pdfen
okr.topicCrops and Crop Management Systems
okr.topicStatistical and Mathematical Sciences
okr.topicScientific Research and Science Parks
okr.topicScience Education
okr.topicPoverty Monitoring and Analysis
okr.topicEducation
okr.topicScience and Technology Development
okr.topicPoverty Reduction
okr.topicAgriculture
okr.unitPoverty and Inequality Team, Development Research Group
okr.volume1 of 1
relation.isAuthorOfPublicationc405b12a-6ae7-5b6a-a708-1f9aa2435c0d
relation.isAuthorOfPublication.latestForDiscoveryc405b12a-6ae7-5b6a-a708-1f9aa2435c0d
relation.isSeriesOfPublication26e071dc-b0bf-409c-b982-df2970295c87
relation.isSeriesOfPublication.latestForDiscovery26e071dc-b0bf-409c-b982-df2970295c87
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