Is Predicted Data a Viable Alternative to Real Data?

doi:10.1093/wber/lhz007

Publication:
Is Predicted Data a Viable Alternative to Real Data?

creativeworkseries.issn	1564-698X
dc.contributor.author	Fujii, Tomoki
dc.contributor.author	van der Weide, Roy
dc.date.accessioned	2021-12-10T18:03:30Z
dc.date.available	2021-12-10T18:03:30Z
dc.date.issued	2020-06
dc.description.abstract	It is costly to collect the household- and individual-level data that underlie official estimates of poverty and health. For this reason, developing countries often do not have the budget to update estimates of poverty and health regularly, even though these estimates are most needed there. One way to reduce the financial burden is to substitute some of the real data with predicted data by means of double sampling, where the expensive outcome variable is collected for a subsample and its predictors for all. This study finds that double sampling yields only modest reductions in financial costs when imposing a statistical precision constraint in a wide range of realistic empirical settings. There are circumstances in which the gains can be more substantial, but these denote the exception rather than the rule. The recommendation is to rely on real data whenever there is a need for new data and to use prediction estimators to leverage existing data.	en
dc.identifier.citation	World Bank Economic Review
dc.identifier.doi	10.1596/36720
dc.identifier.issn	1564-698X
dc.identifier.uri	https://hdl.handle.net/10986/36720
dc.publisher	Published by Oxford University Press on behalf of the World Bank
dc.relation.ispartofseries	World Bank Economic Review
dc.rights	CC BY-NC-ND 3.0 IGO
dc.rights.holder	World Bank
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/igo
dc.subject	PREDICTION
dc.subject	DOUBLE SAMPLING
dc.subject	SURVEY COSTS
dc.subject	POVERTY
dc.title	Is Predicted Data a Viable Alternative to Real Data?	en
dc.type	Journal Article	en
dc.type	Article de journal	fr
dc.type	Artículo de revista	es
dspace.entity.type	Publication
okr.date.disclosure	2021-12-01
okr.date.doiregistration	2025-05-06T11:08:03.453844Z
okr.doctype	Publications & Research
okr.doctype	Publications & Research::Journal Article
okr.identifier.doi	10.1093/wber/lhz007
okr.language.supported	en
okr.peerreview	Academic Peer Review
okr.topic	Poverty Reduction::Living Standards
okr.topic	Poverty Reduction::Poverty Lines
okr.topic	Poverty Reduction::Poverty Monitoring & Analysis
okr.volume	34(2)
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