A Map of the Poor or a Poor Map?

This paper evaluates the performance of different small area estimation methods using model and design-based simulation experiments. Design-based simulation experiments are carried out using the Mexican Intra Censal survey as a census of roughly 3.9 million households from which 500 samples are draw...

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Autores principales:	Paul Corral, Kristen Himelein, Kevin McGee, Isabel Molina
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	small area estimation ELL poverty mapping poverty map empirical best parametric bootstrap Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/cad2b4f99a534e809b7bb3e582ddbc18
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spelling	oai:doaj.org-article:cad2b4f99a534e809b7bb3e582ddbc182021-11-11T18:19:19ZA Map of the Poor or a Poor Map?10.3390/math92127802227-7390https://doaj.org/article/cad2b4f99a534e809b7bb3e582ddbc182021-11-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/21/2780https://doaj.org/toc/2227-7390This paper evaluates the performance of different small area estimation methods using model and design-based simulation experiments. Design-based simulation experiments are carried out using the Mexican Intra Censal survey as a census of roughly 3.9 million households from which 500 samples are drawn using a two-stage selection procedure similar to that of Living Standards Measurement Study (LSMS) surveys. The estimation methods considered are that of Elbers, Lanjouw and Lanjouw (2003), the empirical best predictor of Molina and Rao (2010), the twofold nested error extension presented by Marhuenda et al. (2017), and finally an adaptation, presented by Nguyen (2012), that combines unit and area level information, and which has been proposed as an alternative when the available census data is outdated. The findings show the importance of selecting a proper model and data transformation so that model assumptions hold. A proper data transformation can lead to a considerable improvement in mean squared error (MSE). Results from design-based validation show that all small area estimation methods represent an improvement, in terms of MSE, over direct estimates. However, methods that model unit level welfare using only area level information suffer from considerable bias. Because the magnitude and direction of the bias is unknown ex ante, methods relying only on aggregated covariates should be used with caution, but may be an alternative to traditional area level models when these are not applicable.Paul CorralKristen HimeleinKevin McGeeIsabel MolinaMDPI AGarticlesmall area estimationELLpoverty mappingpoverty mapempirical bestparametric bootstrapMathematicsQA1-939ENMathematics, Vol 9, Iss 2780, p 2780 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	small area estimation ELL poverty mapping poverty map empirical best parametric bootstrap Mathematics QA1-939
spellingShingle	small area estimation ELL poverty mapping poverty map empirical best parametric bootstrap Mathematics QA1-939 Paul Corral Kristen Himelein Kevin McGee Isabel Molina A Map of the Poor or a Poor Map?
description	This paper evaluates the performance of different small area estimation methods using model and design-based simulation experiments. Design-based simulation experiments are carried out using the Mexican Intra Censal survey as a census of roughly 3.9 million households from which 500 samples are drawn using a two-stage selection procedure similar to that of Living Standards Measurement Study (LSMS) surveys. The estimation methods considered are that of Elbers, Lanjouw and Lanjouw (2003), the empirical best predictor of Molina and Rao (2010), the twofold nested error extension presented by Marhuenda et al. (2017), and finally an adaptation, presented by Nguyen (2012), that combines unit and area level information, and which has been proposed as an alternative when the available census data is outdated. The findings show the importance of selecting a proper model and data transformation so that model assumptions hold. A proper data transformation can lead to a considerable improvement in mean squared error (MSE). Results from design-based validation show that all small area estimation methods represent an improvement, in terms of MSE, over direct estimates. However, methods that model unit level welfare using only area level information suffer from considerable bias. Because the magnitude and direction of the bias is unknown ex ante, methods relying only on aggregated covariates should be used with caution, but may be an alternative to traditional area level models when these are not applicable.
format	article
author	Paul Corral Kristen Himelein Kevin McGee Isabel Molina
author_facet	Paul Corral Kristen Himelein Kevin McGee Isabel Molina
author_sort	Paul Corral
title	A Map of the Poor or a Poor Map?
title_short	A Map of the Poor or a Poor Map?
title_full	A Map of the Poor or a Poor Map?
title_fullStr	A Map of the Poor or a Poor Map?
title_full_unstemmed	A Map of the Poor or a Poor Map?
title_sort	map of the poor or a poor map?
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/cad2b4f99a534e809b7bb3e582ddbc18
work_keys_str_mv	AT paulcorral amapofthepoororapoormap AT kristenhimelein amapofthepoororapoormap AT kevinmcgee amapofthepoororapoormap AT isabelmolina amapofthepoororapoormap AT paulcorral mapofthepoororapoormap AT kristenhimelein mapofthepoororapoormap AT kevinmcgee mapofthepoororapoormap AT isabelmolina mapofthepoororapoormap
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A Map of the Poor or a Poor Map?

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