How Survey-to-Survey Imputation Can Fail

Show simple item record

collection.link.5
https://openknowledge.worldbank.org/handle/10986/9
collection.name.5
Policy Research Working Papers
dc.contributor.author
Newhouse, D.
dc.contributor.author
Shivakumaran, S.
dc.contributor.author
Takamatsu, S.
dc.contributor.author
Yoshida, N.
dc.date.accessioned
2014-08-15T16:54:27Z
dc.date.available
2014-08-15T16:54:27Z
dc.date.issued
2014-07
dc.description.abstract
This 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.identifier
http://documents.worldbank.org/curated/en/2014/07/19754254/survey-to-survey-imputation-can-fail
dc.identifier.uri
http://hdl.handle.net/10986/19364
dc.language
English
dc.language.iso
en_US
dc.publisher
World Bank Group, Washington, DC
dc.relation.ispartofseries
Policy Research Working Paper;No. 6961
dc.rights
CC BY 3.0 IGO
dc.rights.uri
http://creativecommons.org/licenses/by/3.0/igo/
dc.subject
AVERAGE WAGES
dc.subject
BIASES
dc.subject
CALCULATION
dc.subject
CHANGES IN POVERTY
dc.subject
CONFIDENCE INTERVALS
dc.subject
CONSUMPTION DATA
dc.subject
CONSUMPTION EXPENDITURE
dc.subject
CONSUMPTION EXPENDITURES
dc.subject
DECLINE IN POVERTY
dc.subject
DRINKING WATER
dc.subject
DUMMY VARIABLES
dc.subject
EMPLOYMENT INCOME
dc.subject
EMPLOYMENT STATUS
dc.subject
ESTIMATES OF POVERTY
dc.subject
FOOD CONSUMPTION
dc.subject
HOUSEHOLD BUDGET
dc.subject
HOUSEHOLD CONSUMPTION
dc.subject
HOUSEHOLD DEMOGRAPHICS
dc.subject
HOUSEHOLD EXPENDITURE SURVEYS
dc.subject
HOUSEHOLD HEAD
dc.subject
HOUSEHOLD HEADS
dc.subject
HOUSEHOLD INCOME
dc.subject
HOUSEHOLD SIZE
dc.subject
HOUSEHOLD SURVEY
dc.subject
HOUSEHOLD SURVEYS
dc.subject
HOUSEHOLD WELFARE
dc.subject
HOUSING
dc.subject
INCOME GROWTH
dc.subject
INEQUALITY
dc.subject
LIVING STANDARDS
dc.subject
NATIONAL POVERTY
dc.subject
NATIONAL POVERTY RATE
dc.subject
PER CAPITA CONSUMPTION
dc.subject
POOR
dc.subject
POOR PROVINCES
dc.subject
POVERTY ANALYSIS
dc.subject
POVERTY ASSESSMENT
dc.subject
POVERTY DATA
dc.subject
POVERTY ESTIMATES
dc.subject
POVERTY INDICATOR
dc.subject
POVERTY LINES
dc.subject
POVERTY MAPPING
dc.subject
POVERTY MAPS
dc.subject
POVERTY MEASUREMENT
dc.subject
POVERTY MEASURES
dc.subject
POVERTY RATE
dc.subject
POVERTY RATES
dc.subject
POVERTY REDUCTION
dc.subject
PRECISION
dc.subject
PREDICTION
dc.subject
PREDICTIONS
dc.subject
PROBABILITIES
dc.subject
PROBABILITY
dc.subject
REDUCTION IN POVERTY
dc.subject
REDUCTION OF POVERTY
dc.subject
REGIONAL DIFFERENCES
dc.subject
REGIONAL LEVEL
dc.subject
REGIONAL LEVELS
dc.subject
REGIONAL PERSPECTIVE
dc.subject
RELIABILITY
dc.subject
RURAL
dc.subject
RURAL AREAS
dc.subject
RURAL POPULATION
dc.subject
RURAL POVERTY
dc.subject
RURAL PUBLIC
dc.subject
RURAL SECTOR
dc.subject
RURAL SECTORS
dc.subject
SAMPLE DESIGN
dc.subject
SAMPLING ERRORS
dc.subject
SELF-EMPLOYMENT
dc.subject
STANDARD DEVIATION
dc.subject
STANDARD ERRORS
dc.subject
UNEMPLOYMENT
dc.subject
VILLAGE LEVEL
dc.subject
WAGE INCOME
dc.subject
WAGE RATES
dc.subject
WAR
dc.subject
WELFARE INDICATORS
dc.subject
WELFARE MONITORING
dc.title
How Survey-to-Survey Imputation Can Fail
en
okr.date.disclosure
2014-07-01
okr.doctype
Publications & Research :: Policy Research Working Paper
okr.doctype
Publications & Research
okr.docurl
http://documents.worldbank.org/curated/en/2014/07/19754254/survey-to-survey-imputation-can-fail
okr.globalpractice
Macroeconomics and Fiscal Management
okr.globalpractice
Transport and ICT
okr.globalpractice
Poverty
okr.googlescholar.linkpresent
yes
okr.identifier.doi
10.1596/1813-9450-6961
okr.identifier.externaldocumentum
000158349_20140701155002
okr.identifier.internaldocumentum
19754254
okr.identifier.report
WPS6961
okr.language.supported
en
okr.pdfurl
http://www-wds.worldbank.org/external/default/WDSContentServer/WDSP/IB/2014/07/01/000158349_20140701155002/Rendered/PDF/WPS6961.pdf
en
okr.region.administrative
South Asia
okr.region.country
Sri Lanka
okr.topic
Poverty Reduction :: Rural Poverty Reduction
okr.topic
Macroeconomics and Economic Growth :: Regional Economic Development
okr.topic
Poverty Monitoring and Analysis
okr.topic
Statistical and Mathematical Sciences
okr.topic
Science and Technology Development
okr.unit
Economic Policy and Poverty Unit, South Asia Region; and Poverty Reduction and Equity Unit, Poverty Reduction and Economic Management Network
okr.volume
1 of 1

Show simple item record



This item appears in the following Collection(s)