Publication:
How Survey-to-Survey Imputation Can Fail

dc.contributor.authorNewhouse, D.
dc.contributor.authorShivakumaran, S.
dc.contributor.authorTakamatsu, S.
dc.contributor.authorYoshida, N.
dc.date.accessioned2014-08-15T16:54:27Z
dc.date.available2014-08-15T16:54:27Z
dc.date.issued2014-07
dc.description.abstractThis paper proposes diagnostics to assess the accuracy of survey-to-survey imputation methods and applies them to examine why imputing from the Household Income and Expenditure Survey into the Labor Force Survey fails to accurately project poverty trends in Sri Lanka between 2006 and 2009. Survey-to-survey imputation methods rely on two key assumptions: (i) that the questions in the two surveys are asked in a consistent way and (ii) that common variables of the two surveys explain a large share of the intertemporal change in household expenditure and poverty. In addition, differences in sampling design can lead validation tests to underestimate the accuracy of survey-to-survey predictions. In Sri Lanka, the causes of failure differ across sectors. In the urban sector, the primary culprit is differences between the two surveys in the design of the questionnaire. In the rural and estate sectors, the set of common variables in the prediction model does not adequately capture changes in poverty. The paper concludes that in Sri Lanka, survey-to-survey imputation between the Household Income and Expenditure Survey and the Labor Force Survey cannot produce accurate poverty estimates unless the Labor Force Survey adds additional questions on assets and is redesigned to use a questionnaire that is compatible with the Household Income and Expenditure Survey. Alternatively, a new welfare-tracking survey that satisfies these conditions could be established.en
dc.identifierhttp://documents.worldbank.org/curated/en/2014/07/19754254/survey-to-survey-imputation-can-fail
dc.identifier.doi10.1596/1813-9450-6961
dc.identifier.urihttps://hdl.handle.net/10986/19364
dc.languageEnglish
dc.language.isoen_US
dc.publisherWorld Bank Group, Washington, DC
dc.relation.ispartofseriesPolicy Research Working Paper;No. 6961
dc.rightsCC BY 3.0 IGO
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/igo/
dc.subjectAVERAGE WAGES
dc.subjectBIASES
dc.subjectCALCULATION
dc.subjectCHANGES IN POVERTY
dc.subjectCONFIDENCE INTERVALS
dc.subjectCONSUMPTION DATA
dc.subjectCONSUMPTION EXPENDITURE
dc.subjectCONSUMPTION EXPENDITURES
dc.subjectDECLINE IN POVERTY
dc.subjectDRINKING WATER
dc.subjectDUMMY VARIABLES
dc.subjectEMPLOYMENT INCOME
dc.subjectEMPLOYMENT STATUS
dc.subjectESTIMATES OF POVERTY
dc.subjectFOOD CONSUMPTION
dc.subjectHOUSEHOLD BUDGET
dc.subjectHOUSEHOLD CONSUMPTION
dc.subjectHOUSEHOLD DEMOGRAPHICS
dc.subjectHOUSEHOLD EXPENDITURE SURVEYS
dc.subjectHOUSEHOLD HEAD
dc.subjectHOUSEHOLD HEADS
dc.subjectHOUSEHOLD INCOME
dc.subjectHOUSEHOLD SIZE
dc.subjectHOUSEHOLD SURVEY
dc.subjectHOUSEHOLD SURVEYS
dc.subjectHOUSEHOLD WELFARE
dc.subjectHOUSING
dc.subjectINCOME GROWTH
dc.subjectINEQUALITY
dc.subjectLIVING STANDARDS
dc.subjectNATIONAL POVERTY
dc.subjectNATIONAL POVERTY RATE
dc.subjectPER CAPITA CONSUMPTION
dc.subjectPOOR
dc.subjectPOOR PROVINCES
dc.subjectPOVERTY ANALYSIS
dc.subjectPOVERTY ASSESSMENT
dc.subjectPOVERTY DATA
dc.subjectPOVERTY ESTIMATES
dc.subjectPOVERTY INDICATOR
dc.subjectPOVERTY LINES
dc.subjectPOVERTY MAPPING
dc.subjectPOVERTY MAPS
dc.subjectPOVERTY MEASUREMENT
dc.subjectPOVERTY MEASURES
dc.subjectPOVERTY RATE
dc.subjectPOVERTY RATES
dc.subjectPOVERTY REDUCTION
dc.subjectPRECISION
dc.subjectPREDICTION
dc.subjectPREDICTIONS
dc.subjectPROBABILITIES
dc.subjectPROBABILITY
dc.subjectREDUCTION IN POVERTY
dc.subjectREDUCTION OF POVERTY
dc.subjectREGIONAL DIFFERENCES
dc.subjectREGIONAL LEVEL
dc.subjectREGIONAL LEVELS
dc.subjectREGIONAL PERSPECTIVE
dc.subjectRELIABILITY
dc.subjectRURAL
dc.subjectRURAL AREAS
dc.subjectRURAL POPULATION
dc.subjectRURAL POVERTY
dc.subjectRURAL PUBLIC
dc.subjectRURAL SECTOR
dc.subjectRURAL SECTORS
dc.subjectSAMPLE DESIGN
dc.subjectSAMPLING ERRORS
dc.subjectSELF-EMPLOYMENT
dc.subjectSTANDARD DEVIATION
dc.subjectSTANDARD ERRORS
dc.subjectUNEMPLOYMENT
dc.subjectVILLAGE LEVEL
dc.subjectWAGE INCOME
dc.subjectWAGE RATES
dc.subjectWAR
dc.subjectWELFARE INDICATORS
dc.subjectWELFARE MONITORING
dc.titleHow Survey-to-Survey Imputation Can Failen
dspace.entity.typePublication
okr.crossref.titleHow Survey-to-Survey Imputation Can Fail
okr.date.disclosure2014-07-01
okr.date.doiregistration2025-04-10T09:17:38.150504Z
okr.doctypePublications & Research::Policy Research Working Paper
okr.doctypePublications & Research
okr.docurlhttp://documents.worldbank.org/curated/en/2014/07/19754254/survey-to-survey-imputation-can-fail
okr.globalpracticeMacroeconomics and Fiscal Management
okr.globalpracticeTransport and ICT
okr.globalpracticePoverty
okr.guid763111468164962978
okr.identifier.doi10.1596/1813-9450-6961
okr.identifier.externaldocumentum000158349_20140701155002
okr.identifier.internaldocumentum19754254
okr.identifier.reportWPS6961
okr.language.supporteden
okr.pdfurlhttp://www-wds.worldbank.org/external/default/WDSContentServer/WDSP/IB/2014/07/01/000158349_20140701155002/Rendered/PDF/WPS6961.pdfen
okr.region.administrativeSouth Asia
okr.region.countrySri Lanka
okr.topicPoverty Reduction::Rural Poverty Reduction
okr.topicMacroeconomics and Economic Growth::Regional Economic Development
okr.topicPoverty Monitoring and Analysis
okr.topicStatistical and Mathematical Sciences
okr.topicScience and Technology Development
okr.unitEconomic Policy and Poverty Unit, South Asia Region; and Poverty Reduction and Equity Unit, Poverty Reduction and Economic Management Network
okr.volume1 of 1
relation.isSeriesOfPublication26e071dc-b0bf-409c-b982-df2970295c87
relation.isSeriesOfPublication.latestForDiscovery26e071dc-b0bf-409c-b982-df2970295c87
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