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Cross-validating administrative and survey datasets through microsimulation


  • Philippe Liégeois

    () (CEPS/INSTEAD, 44 rue Emile Mark, 4620 Differdange, Grand-Duchy of Luxembourg and Department of Applied Economics (DULBEA), University of Brussels)

  • Frédéric Berger


  • Nizamul Islam


  • Raymond Wagener

    () (Inspection Générale de la Sécurité Sociale (IGSS), 26 rue Zithe, 2763 Luxembourg, Grand-Duchy of Luxembourg)


In this paper we cross-validate two sources of data, administrative and sample survey, addressing an issue commonly faced by analysts regarding the relative reliability and comparability of these two data sources. By way of case study, the paper uses data presently available in the Grand-Duchy of Luxembourg. While administrative data extracted from the recently implemented Social Security Data Warehouse contains information about the whole population of Luxembourg (449,000 observations) in 2003, survey data, extracted from the Luxembourg household panel PSELL3/EU-SILC for 2004 (incomes from 2003), provides a representative sample of only around 3,600 private households (9,800 individuals) living in Luxembourg. The attraction of the survey is the more detailed information it provides on incomes, family relationships and other socio-economic dimensions. Our paper first analyzes the advantages and limitations of each dataset, before outlining and addressing methodological difficulties relating to their cross-validation. Through the cross-validation that follows we conclude that the survey database performs reasonably well in capturing the relevant characteristics of the resident population and allows analyses with respect to characteristics not found in the administrative database, and vice versa. Importantly we find that even if, on average, some monetary variables are different in the two datasets, the shapes of the equivalised income distributions broadly coincide. Even so, we observe a few important discrepancies at the extremes of the curves. Finally, through use of the EUROMOD microsimulation platform, we are able to show that the discrepancies observed between these income data sources are insufficient to significantly affect the conclusions drawn from analysis of policy alternatives.

Suggested Citation

  • Philippe Liégeois & Frédéric Berger & Nizamul Islam & Raymond Wagener, 2011. "Cross-validating administrative and survey datasets through microsimulation," International Journal of Microsimulation, International Microsimulation Association, vol. 4(1), pages 54-71.
  • Handle: RePEc:ijm:journl:v:4:y:2011:i:1:p:54-71

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    References listed on IDEAS

    1. Atkinson, Tony & Cantillon, Bea & Marlier, Eric & Nolan, Brian, 2002. "Social Indicators: The EU and Social Inclusion," OUP Catalogue, Oxford University Press, number 9780199253494.
    2. Callan, Tim & Walsh, John, 2006. "Assessing the impact of tax/transfer policy changes on poverty: methodological issues and some European evidence," EUROMOD Working Papers EM1/06, EUROMOD at the Institute for Social and Economic Research.
    3. Paul Williamson, 2007. "Book Review - Micro-simulation in action: policy analysis in Europe using EUROMOD," International Journal of Microsimulation, International Microsimulation Association, vol. 1(1), pages 57-58.
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    Cited by:

    1. Whitaker, Stephan D., 2018. "Big Data versus a survey," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 285-296.
    2. repec:ijm:journl:v10:y:2017:i:2:p:144-176 is not listed on IDEAS
    3. Alessio Fusco & Philippe Kerm & A. Alieva & L. Bellani & F. Etienne-Robert & A.-C. Guio & I. Kyzyma & K. Leduc & P. Liégeois & M.N.P. Alperin & A. Reinstadler & E. Sierminska & D. Sologon & P. Thill &, 2013. "GINI Country Report: Growing Inequalities and their Impacts in Luxembourg," GINI Country Reports luxembourg, AIAS, Amsterdam Institute for Advanced Labour Studies.


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