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Microdata Disclosure Control by Resampling - Effects on Regression Results

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  • Gottschalk Sandra

    (Centre for European Economic Research (ZEW), L 7, 1, D-68161 Mannheim, Germany)

Abstract

Nonparametric resampling is a method for generating synthetic microdata and is introduced as a procedure for microdata disclosure limitation. Theoretically, re-identification of individuals or firms is not possible with synthetic data. The resampling procedure creates datasets - the resample - which nearly have the same empirical cumulative distribution functions as the original survey data and thus permit econometricians to calculate meaningful regression results. The idea of nonparametric resampling, especially, is to draw from univariate or multivariate empirical distribution functions without having to estimate these explicitly. Until now, the resampling procedure shown here has only been applicable to variables with continuous distribution functions. Monte Carlo simulations and applications with data from the Mannheim Innovation Panel show that results of linear and nonlinear regression analyses can be reproduced quite precisely by nonparametric resamples. A univariate and a multivariate resampling version are examined. The univariate version as well as the multivariate version which is using the correlation structure of the original data as a scaling instrument turn out to be able to retain the coefficients of model estimations. Furthermore, multivariate resampling best reproduces regression results if all variables are anonymised.

Suggested Citation

  • Gottschalk Sandra, 2005. "Microdata Disclosure Control by Resampling - Effects on Regression Results," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(5), pages 567-583, October.
    • Handle: RePEc:jns:jbstat:v:225:y:2005:i:5:p:567-583
    DOI: 10.1515/jbnst-2005-0506
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    References listed on IDEAS

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    1. Almus, Matthias & Engel, Dirk & Prantl, Susanne, 2000. "The Mannheim Foundation Panels of the Centre for European Economic Research (ZEW)," ZEW Dokumentationen 00-02, ZEW - Leibniz Centre for European Economic Research.
    2. Hardle, Wolfgang & Linton, Oliver, 1986. "Applied nonparametric methods," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 38, pages 2295-2339, Elsevier.
    3. Hardle, Wolfgang & Linton, Oliver, 1986. "Applied nonparametric methods," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 38, pages 2295-2339, Elsevier.
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    1. Gottschalk, Sandra, 2013. "The Research Data Centre of the Centre for European Economic Research (ZEW-FDZ)," ZEW Discussion Papers 13-051, ZEW - Leibniz Centre for European Economic Research.

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