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Schmid, Matthias and Schneeweiß, Hans (2005): The Effect of Microaggregation Procedures on the Estimation of Linear Models: A Simulation Study. Collaborative Research Center 386, Discussion Paper 443 [PDF, 369kB]


Microaggregation is a set of procedures that distort empirical data in order to guarantee the factual anonymity of the data. 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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