Estimation of the error-components model with incomplete panels

Abstract The error-components model (ECM) is probably the most frequently used approach to analyze panel data in econometrics. When the panel is incomplete, which is the rule rather than the exception when the data come from large-scale surveys, standard estimation methods cannot be applied. We first discuss estimation in the fixed-effects analogue of the ECM, and then present two estimators (quadratic unbiased and maximum likelihood) for the ECM. Some simulation results are given to assess finite-sample properties and computational burden of the various methods.

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