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IV-Schätzung eines linearen Panelmodells mit stochastisch überlagerten Betriebs- und Unternehmensdaten

Author

Listed:
  • Elena Biewen
  • Gerd Ronning
  • Martin Rosemann

Abstract

Eines der wichtigsten Verfahren zur Anonymisierung von Betriebs- und Unternehmensdaten ist die stochastische Überlagerung. Ihr Einsatz zur Sicherstellung der faktischen Anonymität der Einheiten eines Datensatzes führt jedoch zu inkonsistenten Schätzungen von linearen Panelmodellen und macht die Verwendung von Korrekturverfahren erforderlich. Dieser Beitrag befasst sich mit der Instrumentvariablen-Schätzung (IV-Schätzung) eines linearen Panelmodells mit Individualeffekten und überprüft die Eignung der IV-Methode zur Korrektur der Verzerrung. Als Instrumente werden (a) eine verzögerte Variable, (b) die Differenz von verzögerten Variablen und (c) eine zusätzlich anonymisierte Variable getestet. Wir kommen zum Ergebnis, dass lediglich das letzte Instrument in konsistenten IV-Schätzern resultiert.

Suggested Citation

  • Elena Biewen & Gerd Ronning & Martin Rosemann, 2009. "IV-Schätzung eines linearen Panelmodells mit stochastisch überlagerten Betriebs- und Unternehmensdaten," IAW Discussion Papers 53, Institut für Angewandte Wirtschaftsforschung (IAW).
    • Handle: RePEc:iaw:iawdip:53
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    File URL: http://www.iaw.edu/RePEc/iaw/pdf/iaw_dp_53.pdf
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    References listed on IDEAS

    as
    1. Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 104(2), pages 259-268, September.
    2. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February.
    3. Biorn, Erik & Klette, Tor Jakob, 1998. "Panel data with errors-in-variables: essential and redundant orthogonality conditions in GMM-estimation," Economics Letters, Elsevier, vol. 59(3), pages 275-282, June.
    4. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    5. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Instrumentvariablen-Schätzung; additive und multiplikative stochastische Überlagerungen; Anonymisierung von Paneldaten;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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