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Within-Schätzung bei anonymisierten Paneldaten

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  • Elena Biewen

Abstract

Dieser Beitrag befasst sich mit der Untersuchung der Auswirkungen der datenverändernden Anonymisierungsverfahren ’variablenspezifische abstandsorientierte Mikroaggregation’ (vaabMA, im Englischen auch als Individual Ranking bezeichnet) und ’multiplikative stochastische Überlagerung’ auf die ’Within’-Schätzung eines linearen Panelmodells mit Individualeffekten. Es wird gezeigt, dass der ’Within’-Schätzer auf der Grundlage der mittels vaabMA anonymisierten Daten konsistent bleibt. Bei der multiplikativen stochastischen Überlagerung wird neben der allgemeinen Form der Überlagerung eine spezielle Variante analysiert, bei der die Variablen zuerst mit einem konstantem Grundüberlagerungsfaktor und danach zusätzlich additiv überlagert werden. Es wird weiterhin gezeigt, dass beide Varianten der Überlagerung zu Inkonsistenz der ’Within’-Schätzer führen. Anschließend werden korrigierte Schätzer hergeleitet.

Suggested Citation

  • Elena Biewen, 2007. "Within-Schätzung bei anonymisierten Paneldaten," IAW Discussion Papers 34, Institut für Angewandte Wirtschaftsforschung (IAW).
    • Handle: RePEc:iaw:iawdip:34
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