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Schätzung ökonometrischer Modelle auf der Grundlage anonymisierter Daten

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  • Pohlmeier, Winfried
  • Lechner, Sandra

Abstract

Die Anonymisierung von sensiblen Individualdaten führt zu einem Konflikt zwischen dem Ziel der Minimierung des Reidentifikationsrisikos und der Qualität ökonometrischer Schätzungen. Der durch Anonymisierung bedingte Verlust an Effizienz und/oder der Konsistenz eines Schätzers wirft die grundsätzliche Frage auf, inwieweit anonymisierte Individualdaten überhaupt für die wissenschaftliche Nutzung geeignet sind. Deshalb gehen wir in dieser Arbeit der Frage nach, welchen Einfluss Anonymisierungsverfahren auf die Eigenschaften von ökonometrischen Schätzern haben. Zunächst untersuchen wir die Auswirkungen gängiger Anonymisierungsverfahren auf lineare ökonometrische Schätzer in endlichen Stichproben. Im zweiten Schritt untersuchen wir, inwieweit sich die Selektionseffekte durch Anonymisierung aufgrund von Data Blanking mit Hilfe von semiparametrischen Verfahren korrigieren lassen. Die quantitative Evidenz beruht auf Monte-Carlo Simulationen und einer illustrativen Anwendung für einen Querschnitt der Kostenstrukturerhebung.

Suggested Citation

  • 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).
    • Handle: RePEc:zbw:cofedp:0304
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    References listed on IDEAS

    as
    1. Newey, Whitney K & Powell, James L & Walker, James R, 1990. "Semiparametric Estimation of Selection Models: Some Empirical Results," American Economic Review, American Economic Association, vol. 80(2), pages 324-328, May.
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    3. 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.
    4. Lanot, Gauthier & Walker, Ian, 1998. "The union/non-union wage differential: An application of semi-parametric methods," Journal of Econometrics, Elsevier, vol. 84(2), pages 327-349, June.
    5. Donald W. K. Andrews & Marcia M. A. Schafgans, 1998. "Semiparametric Estimation of the Intercept of a Sample Selection Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 497-517.
    6. Klein, Roger W & Spady, Richard H, 1993. "An Efficient Semiparametric Estimator for Binary Response Models," Econometrica, Econometric Society, vol. 61(2), pages 387-421, March.
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    Citations

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    Cited by:

    1. Gerd Ronning, 2009. "Stochastische Überlagerung mit Hilfe der Mischungsverteilung," IAW Discussion Papers 48, Institut für Angewandte Wirtschaftsforschung (IAW).
    2. Lechner Sandra & Pohlmeier Winfried, 2005. "Data Masking by Noise Addition and the Estimation of Nonparametric Regression Models," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(5), pages 517-528, October.
    3. Gerd Ronning & Martin Rosemann, 2006. "Estimation of the Probit Model from Anonymized Micro Data," IAW Discussion Papers 25, Institut für Angewandte Wirtschaftsforschung (IAW).

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    More about this item

    Keywords

    Mikroaggregation; stochastische Überlagerung; Data Blanking; IV-Schätzung; semiparametrisches Selektionsmodell;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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