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A relevant issue in panel data estimation is heteroscedasticity, which oftenoccurs when the sample is large and individual units are of varying size.Furthermore, many of the available panel data sets are unbalanced in nature,because of attrition or accretion, and micro-econometric models applied topanel data are frequently multi-equation models. This paper considers thegeneral least squares estimation of the heteroscedastic stratified two-wayerror component (EC) models of both single equations and seemingly unrelatedregressions (SUR) systems (with cross-equations restrictions) on unbalancedpanel data. The derived heteroscedastic estimators of both single equations andSUR systems improve the estimation efficiency.

Heteroscedastic stratified two-way EC models of single equations and SUR systems