A Map of the Poor or a Poor Map?

Paul Corral, Kristen Himelein, Kevin McGee and Isabel Molina
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Paul Corral: Poverty and Equity Global Practice, The World Bank Group, Washington, DC 98104, USA
Kristen Himelein: Poverty and Equity Global Practice, The World Bank Group, Washington, DC 98104, USA
Kevin McGee: Development Economics Data Group, The World Bank Group, Washington, DC 98104, USA
Isabel Molina: Department of Statistics, Universidad Carlos III de Madrid, 28903 Madrid, Spain

Mathematics, 2021, vol. 9, issue 21, 1-40

Abstract: 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unit and area level information, and which has been proposed as an alternative when the available census data is outdated.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.

Keywords: small area estimation; ELL; poverty mapping; poverty map; empirical best; parametric bootstrap; nested error model; twofold nested error model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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