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Anonymisierung von Unternehmensdaten: Ein Überblick und beispielhafte Darstellung anhand des Mannheimer Innovationspanels

Author

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  • Gottschalk, Sandra

Abstract

Für Unternehmensdaten existieren im Gegensatz zu Personendaten keine einheitlichen Regeln zur Erstellung von Scientific-Use-Files, d.h. eines anonymisierten Datenfiles zur wissenschaftlichen Nutzung. Verschiedene Anonymisierungsmethoden werden hier vorgestellt. Um Mikrodaten einer breiten wissenschaftlichen Forschung zugänglich zu machen, soll deren Analysefähigkeit weitgehend erhalten bleiben. Es muss demnach ein Kompromiss zwischen den Anforderungen, der durch die den Merkmalsträgern - hier Unternehmen - gegebenen Zusage des Vertrauensschutzes entsteht, und dem Erhalt von wesentlichen Informationen für wissenschaftliche Untersuchungen gefunden werden. Ferner kann der Datennutzer selbst die Qualität seiner empirischen Analysen mit anonymisierten Mikrodaten verbessern. Zur Demonstration wird hier beispielhaft eine Korrekturmöglichkeit durch die Anononymisierung verzerrter Daten bei ökonometrischen Schätzungen vorgestellt.

Suggested Citation

  • Gottschalk, Sandra, 2002. "Anonymisierung von Unternehmensdaten: Ein Überblick und beispielhafte Darstellung anhand des Mannheimer Innovationspanels," ZEW Discussion Papers 02-23, ZEW - Leibniz Centre for European Economic Research.
    • Handle: RePEc:zbw:zewdip:874
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    References listed on IDEAS

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    1. Paass, Gerhard, 1988. "Disclosure Risk and Disclosure Avoidance for Microdata," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(4), pages 487-500, October.
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    Cited by:

    1. Ronning Gerd, 2008. "Measuring Research Intensity from Anonymized Data: Does Multiplicative Noise with Factor Structure Save Results Regarding Quotients?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(5-6), pages 644-653, October.
    2. Gottschalk, Sandra, 2003. "Microdata Disclosure by Resampling: Empirical Findings for Business Survey Data," ZEW Discussion Papers 03-55, ZEW - Leibniz Centre for European Economic Research.
    3. Martin Rosemann, 2003. "Erste Ergebnisse von vergleichenden Untersuchungen mit anonymisierten und nicht anonymisierten Einzeldaten am Beispiel der Kostenstrukturerhebung und der Umsatzsteuerstatistik," IAW Discussion Papers 09, Institut für Angewandte Wirtschaftsforschung (IAW).
    4. Pohlmeier, Winfried & Lechner, Sandra, 2003. "Schätzung ökonometrischer Modelle auf der Grundlage anonymisierter Daten," CoFE Discussion Papers 03/04, University of Konstanz, Center of Finance and Econometrics (CoFE).

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    More about this item

    Keywords

    Unternehmensdaten; Anonymisierungsmaßnahmen; Analysefähigkeit; Korrekturmöglichkeit verzerrter Daten;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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