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unit and area level information, and which has been proposed as an alternative when the available census data is outdated.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

Highlights

  • IntroductionThe eradication of poverty was the first Millennium Development Goals (MDGs) established by the United Nations in 2000 and continues as Sustainable Development

  • The eradication of poverty was the first Millennium Development Goals (MDGs) established by the United Nations in 2000 and continues as Sustainable DevelopmentGoal (SDG) 1.1.1, but governments can only properly target poverty if they know where it is

  • The results suggest that the method could outperform direct estimates as well as misspecified models with random effects for the area level only, in terms of mean squared error (MSE), and may be an alternative under scenarios where census and survey data are not aligned

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Summary

Introduction

The eradication of poverty was the first Millennium Development Goals (MDGs) established by the United Nations in 2000 and continues as Sustainable Development. Goal (SDG) 1.1.1, but governments can only properly target poverty if they know where it is. For a given country, the best source for information on the living standards of its population are household surveys. These surveys are a powerful tool towards defining and addressing the needs of people. These surveys, usually offer reliable information only at highly aggregated levels of the population. Small areas can be any population subgroup and are not necessarily tied to geographical areas.

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