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Tapping into existing household survey data for research or policy use: hands-on exercise on water access in Kinshasa
[Exploiter les données d’enquêtes ménages pour la recherche ou la décision publique : guide et étude de cas sur l’accès à l’eau à Kinshasa]

Author

Listed:
  • Florent Bedecarrats

    (AFD - Agence française de développement)

  • Oriane Lafuente-Sampietro

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, AFD - Agence française de développement)

  • Martin Lemenager

    (AFD - Agence française de développement)

  • Thimothée Makabu

    (INS - Institut National de la Statistique - Institut national de la statistique)

Abstract

In most countries, national statistical offices periodically run large surveys that provide outstanding insights on several subjects: social, economic, health, cultural, political. In many cases, this data is only used to produce nationally aggregated indicators that feed international statistical portals (WDGs, SDGs, World Bank, WHO, United Nations…). However, it is possible to do much more with the raw data collected during these surveys: calculate other indicators, cross different variables, run analysis for subnational areas, as well as more sophisticated analysis. This survey data is accessible to scholars, students, policy makers or practitioners and is most useful for the appraisal, monitoring and evaluation of development projects, programs and public policies. We first describe the typology of data generally available in developing countries, its possible uses and how to obtain it. Then we provide detailed guidelines on how to analyze it, using the survey package, available for R, a free and open source statistical software. We illustrate the step by step procedure for survey data processing using Democratic Republic of the Congo as an example: several surveys of different type and from different dates (MICS 2010, 1-2-3 2012 and DHS 2014) are analyzed to understand the levels and trends of access to drinking water, in particular in the Kinshasa megacity.

Suggested Citation

  • Florent Bedecarrats & Oriane Lafuente-Sampietro & Martin Lemenager & Thimothée Makabu, 2016. "Tapping into existing household survey data for research or policy use: hands-on exercise on water access in Kinshasa [Exploiter les données d’enquêtes ménages pour la recherche ou la décision publ," Working Papers hal-01396097, HAL.
    • Handle: RePEc:hal:wpaper:hal-01396097
    Note: View the original document on HAL open archive server: https://hal.science/hal-01396097
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    References listed on IDEAS

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    1. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    2. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    3. Kiel Katherine A. & McClain Katherine T., 1995. "House Prices during Siting Decision Stages: The Case of an Incinerator from Rumor through Operation," Journal of Environmental Economics and Management, Elsevier, vol. 28(2), pages 241-255, March.
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