Abstract
For micro-datasets considered for release as scientific or public use files, statistical agencies have to face the dilemma of guaranteeing the confidentiality of survey respondents on the one hand and offering sufficiently detailed data on the other hand. For that reason, a variety of methods to guarantee disclosure control is discussed in the literature. In this paper, we present an application of Rubin’s (J. Off. Stat. 9, 462–468, 1993) idea to generate synthetic datasets from existing confidential survey data for public release.
We use a set of variables from the 1997 wave of the German IAB Establishment Panel and evaluate the quality of the approach by comparing results from an analysis by Zwick (Ger. Econ. Rev. 6(2), 155–184, 2005) with the original data with the results we achieve for the same analysis run on the dataset after the imputation procedure. The comparison shows that valid inferences can be obtained using the synthetic datasets in this context, while confidentiality is guaranteed for the survey participants.
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The research provided in this paper is part of the project “Wirtschaftsstatistische Paneldaten und faktische Anonymisierung” financed by the Federal Ministry for Education and Research (BMBF) and conducted by the following institutes: Federal Statistical Office Germany, Statistical Offices of the Länder, Institute for Applied Economic Research (IAW), Centre for European Economic Research (ZEW), Institute for Employment Research (IAB). For more information about this project, see for instance Ronning and Rosemann (2006) or Ronning et al. (2005). We thank our project partners and the participants of the “UNECE Conference on Data Editing and Imputation,” 25.09.2006–27.09.2006 in Bonn and “The Conference on Privacy in Statistical Databases ’06,” 13.12.2006–15.12.2006 in Rome, and especially J.M. Abowd, T.E. Raghunathan, D.B. Rubin, J.P. Reiter, and two anonymous referees for their helpful comments on the paper.
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Drechsler, J., Dundler, A., Bender, S. et al. A new approach for disclosure control in the IAB establishment panel—multiple imputation for a better data access. AStA Adv Stat Anal 92, 439–458 (2008). https://doi.org/10.1007/s10182-008-0090-1
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DOI: https://doi.org/10.1007/s10182-008-0090-1