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How Much Should We Trust Micro-data? A Comparison of the Socio-demographic Profile of Malawian Households Using Census, LSMS and DHS data

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  • Luca Tasciotti

    (International Institute of Social Studies of Erasmus University Rotterdam
    School of Oriental and African Studies (SOAS))

  • Natascha Wagner

    (International Institute of Social Studies of Erasmus University Rotterdam)

Abstract

This paper assesses the empirical representativeness of micro-data by comparing the Malawi 2008 census to two representative household surveys – ‘the Living Standard Measurement Survey’ and the ‘Demographic and Health Survey’ – both implemented in Malawi in 2010. The comparison of descriptive statistics – demographics, asset ownership, and living conditions – shows considerable similarities despite statistically identifiable differences due to the large samples. Differences mainly occur when wording, scope, and pre-defined answer categories diverge across surveys. Multivariate analyses are considerably less representative due to loss of observations with composite indicators yielding higher comparability as individual ones. Household-level fixed-effect specifications produce more similar results, yet are not suited for policy conclusions. Comparability of micro-data should not be assumed but checked on a case-by-case basis. Still, micro-data constitute reliable grounds for factually informed conclusions if design and context are appropriately considered.

Suggested Citation

  • Luca Tasciotti & Natascha Wagner, 2018. "How Much Should We Trust Micro-data? A Comparison of the Socio-demographic Profile of Malawian Households Using Census, LSMS and DHS data," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 30(4), pages 588-612, September.
    • Handle: RePEc:pal:eurjdr:v:30:y:2018:i:4:d:10.1057_s41287-017-0083-6
    DOI: 10.1057/s41287-017-0083-6
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    4. José G Dias & Isabel Tiago de Oliveira, 2018. "Exploring unobserved household living conditions in multilevel choice modeling: An application to contraceptive adoption by Indian women," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-17, January.
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