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Disaggregating data in household surveys: Using small area estimation methodologies

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  • Molina, Isabel

Abstract

Household surveys are widely used as a tool for obtaining information on people's socio-economic status and well-being. However, the accuracy of household survey estimates decreases significantly when it comes to making inferences for population groups who represent disaggregations for which the survey was not designed. It is possible, in this context, to use estimation processes that combine information from household surveys with existing auxiliary information at population level, such as censuses or administrative records. This paper offers a methodological guide to the combination of survey statistical techniques with probabilistic models in order to produce disaggregations for interest groups, known as small area estimation (SAE) techniques.

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  • Molina, Isabel, 2022. "Disaggregating data in household surveys: Using small area estimation methodologies," Estudios Estadísticos 48107, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    • Handle: RePEc:ecr:col027:48107
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    1. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
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    5. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    6. Sen, Amartya K, 1976. "Poverty: An Ordinal Approach to Measurement," Econometrica, Econometric Society, vol. 44(2), pages 219-231, March.
    7. Gianni Betti & Bruno Cheli & Achille Lemmi & Vijay Verma, 2006. "Multidimensional and Longitudinal Poverty: an Integrated Fuzzy Approach," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Achille Lemmi & Gianni Betti (ed.), Fuzzy Set Approach to Multidimensional Poverty Measurement, chapter 6, pages 115-137, Springer.
    8. Isabel Molina & Nicola Salvati & Monica Pratesi, 2009. "Bootstrap for estimating the MSE of the Spatial EBLUP," Computational Statistics, Springer, vol. 24(3), pages 441-458, August.
    9. Molina, Isabel & Rao, J.N.K., 2009. "Small area estimation on poverty indicators," DES - Working Papers. Statistics and Econometrics. WS ws091505, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Malay Ghosh & Rebecca Steorts, 2013. "Two-stage benchmarking as applied to small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(4), pages 670-687, November.
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    Cited by:

    1. Yegnanew A. Shiferaw, 2023. "Mapping Disaggregate-Level Agricultural Households in South Africa Using a Hierarchical Bayes Small Area Estimation Approach," Agriculture, MDPI, vol. 13(3), pages 1-17, March.

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