The bias of some estimators for panel data models with measurement errors

Abstract

The paper deals with the (asymptotic) bias in the estimation of regression slope coefficients from panel data observed with error. Unobserved individual and time specific heterogeneity is also assumed. The estimators considered include: the standard ‘within’ and ‘between’ estimators, and estimators based on differences over time. It is shown that in terms of bias, there may be a trade-off between the effect of heterogeneity and of measurement errors. The paper also shows that in situations where the number of observations of each individual is finite (and in practice often small), changes in the correlograms of the measurement error and of the latent exogenous variable may substantially affect the relative bias of the different estimators of the slope coefficient.