Is Predicted Data a Viable Alternative to Real Data?

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...

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Bibliographic Details
Main Authors:	Fujii, Tomoki, van der Weide, Roy
Format:	Journal Article
Published:	Published by Oxford University Press on behalf of the World Bank 2021
Subjects:	PREDICTION DOUBLE SAMPLING SURVEY COSTS POVERTY
Online Access:	http://hdl.handle.net/10986/36720

id	okr-10986-36720
recordtype	oai_dc
spelling	okr-10986-367202021-12-11T05:10:39Z Is Predicted Data a Viable Alternative to Real Data? Fujii, Tomoki van der Weide, Roy PREDICTION DOUBLE SAMPLING SURVEY COSTS POVERTY 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. 2021-12-10T18:03:30Z 2021-12-10T18:03:30Z 2020-06 Journal Article World Bank Economic Review 1564-698X http://hdl.handle.net/10986/36720 CC BY-NC-ND 3.0 IGO http://creativecommons.org/licenses/by-nc-nd/3.0/igo World Bank Published by Oxford University Press on behalf of the World Bank Publications & Research Publications & Research :: Journal Article
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
topic	PREDICTION DOUBLE SAMPLING SURVEY COSTS POVERTY
spellingShingle	PREDICTION DOUBLE SAMPLING SURVEY COSTS POVERTY Fujii, Tomoki van der Weide, Roy Is Predicted Data a Viable Alternative to Real Data?
description	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.
format	Journal Article
author	Fujii, Tomoki van der Weide, Roy
author_facet	Fujii, Tomoki van der Weide, Roy
author_sort	Fujii, Tomoki
title	Is Predicted Data a Viable Alternative to Real Data?
title_short	Is Predicted Data a Viable Alternative to Real Data?
title_full	Is Predicted Data a Viable Alternative to Real Data?
title_fullStr	Is Predicted Data a Viable Alternative to Real Data?
title_full_unstemmed	Is Predicted Data a Viable Alternative to Real Data?
title_sort	is predicted data a viable alternative to real data?
publisher	Published by Oxford University Press on behalf of the World Bank
publishDate	2021
url	http://hdl.handle.net/10986/36720
_version_	1764485767822835712

Is Predicted Data a Viable Alternative to Real Data?

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