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

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.