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The Effect of Microaggregation Procedures on the Estimation of Linear Models: A Simulation Study

  • Schmid Matthias

    ()

    (University of Munich, Department of Statistics, Ludwigstrasse 33, D-80539 Munich, Germany)

  • Schneeweiss Hans

    ()

    (University of Munich, Department of Statistics, Akademiestrasse 1, D-80799 Munich, Germany)

Registered author(s):

    Microaggregation is a set of procedures that distort empirical data in order to guarantee their factual anonymity. At the same time the information content of data sets should not be reduced too much and should still be useful for scientific research. This paper investigates the effect of microaggregation on the estimation of a linear regression by ordinary least squares. It studies, by way of an extensive simulation experiment, the bias of the slope parameter estimator induced by various microaggregation techniques. Some microaggregation procedures lead to consistent estimates while others imply an asymptotic bias for the estimator.

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    Article provided by De Gruyter in its journal Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik).

    Volume (Year): 225 (2005)
    Issue (Month): 5 (October)
    Pages: 529-543

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    Handle: RePEc:jns:jbstat:v:225:y:2005:i:5:p:529-543
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    1. Feige, Edgar L & Watts, Harold W, 1972. "An Investigation of the Consequences of Partial Aggregation of Micro-Economic Data," Econometrica, Econometric Society, vol. 40(2), pages 343-60, March.
    2. Winfried Pohlmeier & Sandra Lechner, 2003. "Schätzung ökonometrischer Modelle auf der Grundlage anonymisierter Daten," CoFE Discussion Paper 03-04, Center of Finance and Econometrics, University of Konstanz.
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