GMM estimation of linear panel data models with time-varying individual effects

This paper considers models For panel data in which the individual effects vary over time. The temporal pattern of variation is arbitrary, but it is t he same for all individuals. The model thus allows one to control for time- varying unobservables that are faced by all individuals (e.g., macro-econom ic events) and to which individuals may respond differently. A generalized within estimator is consistent under strong assumptions on the errors. but it is dominated by a generalized method of moments estimator. This is perha ps surprising, because the generalized within estimator is the MLE under no rmality. The efficiency gains from imposing second-moment error assumptions are evaluated: they are substantial when the regressors and effects are we akly correlated. (C). 2001 Elsevier Science S.A. All rights reserved.