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The effect of microaggregation by individual ranking on the estimation of moments

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  • Schmid, Matthias
  • Schneeweiss, Hans
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    Abstract

    Microaggregation by individual ranking (IR) is an important technique for masking confidential econometric data. While being a successful method for controlling the disclosure risk of observations, IR also affects the results of statistical analyses. We conduct a theoretical analysis on the estimation of arbitrary moments from a data set that has been anonymized by means of the IR method. We show that classical moment estimators remain both consistent and asymptotically normal under weak assumptions. This theory provides the justification for applying standard statistical estimation techniques to the anonymized data without having to correct for a possible bias caused by anonymization.

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    File URL: http://www.sciencedirect.com/science/article/B6VC0-4WK43XM-1/2/79abb9409d785c0bfb4a8b6815821032
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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 153 (2009)
    Issue (Month): 2 (December)
    Pages: 174-182

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    Handle: RePEc:eee:econom:v:153:y:2009:i:2:p:174-182

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    Web page: http://www.elsevier.com/locate/jeconom

    Related research

    Keywords: Consistent estimation Disclosure control Individual ranking Microaggregation General moments;

    References

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    1. Matthias Schmid, 2006. "Estimation of a linear model under microaggregation by individual ranking," AStA Advances in Statistical Analysis, Springer, vol. 90(3), pages 419-438, September.
    2. Matthias Schmid & Hans Schneeweiss & Helmut Küchenhoff, 2007. "Estimation of a linear regression under microaggregation with the response variable as a sorting variable," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 61(4), pages 407-431.
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    Cited by:
    1. López, Alberto, 2011. "The effect of microaggregation on regression results: an application to Spanish innovation data," MPRA Paper 30403, University Library of Munich, Germany.
    2. Hans Schneeweiss & Daniel Rost & Matthias Schmid, 2012. "Probability and quantile estimation from individually micro-aggregated data," Metrika, Springer, vol. 75(6), pages 721-742, August.

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