Linear models with measurement errors arising from mixture distributions

Abstract

The paper considers the linear model with multiplicative measurement errors. In particular, errors arising from mixture distributions will be analyzed. Such a model has to be used if the micro data have been protected by multiplicative noise. If all (continuous) variables are anonymized jointly by this approach, measurement errors will be correlated which is of special concern if the dependent variable is measured with error, too. The paper presents results for the biased naive least-squares estimator both in case of cross-section data and panel data. Moreover, derivation of consistent estimators is shortly discussed.