Panel regression with multiplicative measurement errors

The paper explores the effect of multiplicative measurement errors on the estimation of a linear panel data model. Multiplicative errors are often used to minimize disclosure risk of micro data. We use unbiased estimating equations to construct consistent and asymptotically normal estimators.

Research Highlights► The paper focuses on multiplicative errors. ► Such errors are added to the data in order to minimize the disclosure risk. ► Multiplicative errors are often used to minimize disclosure risk of micro data. ► In the US Longitudinal Employer-Household Dynamics Program this approach is used. ► Our corrected estimator provides consistent estimates for such anonymized data sets.