A relevant issue in panel data estimation is heteroscedasticity, which often occurs 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 to panel data are frequently multi-equation models. The general least squares estimation of the heteroscedastic stratified two-way error component (EC) models of both single equations and seemingly unrelated regressions (SUR) systems (with cross-equation restrictions) on unbalanced panel data is considered. The derived heteroscedastic estimators of both single equations and SUR systems improve the estimation efficiency.

Platoni, S., Barbieri, L., Moro, D., Sckokai, P., Heteroscedastic stratified two-way EC models of single equations and SUR systems, <<ECONOMETRICS AND STATISTICS>>, 2020; 15 (N/A): 46-66. [doi:10.1016/j.ecosta.2019.03.004] [http://hdl.handle.net/10807/133249]

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

Platoni;Silvia; Barbieri;Laura; Moro;Daniele; Sckokai
2020

Abstract

A relevant issue in panel data estimation is heteroscedasticity, which often occurs 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 to panel data are frequently multi-equation models. The general least squares estimation of the heteroscedastic stratified two-way error component (EC) models of both single equations and seemingly unrelated regressions (SUR) systems (with cross-equation restrictions) on unbalanced panel data is considered. The derived heteroscedastic estimators of both single equations and SUR systems improve the estimation efficiency.
Inglese
Platoni, S., Barbieri, L., Moro, D., Sckokai, P., Heteroscedastic stratified two-way EC models of single equations and SUR systems, <<ECONOMETRICS AND STATISTICS>>, 2020; 15 (N/A): 46-66. [doi:10.1016/j.ecosta.2019.03.004] [http://hdl.handle.net/10807/133249]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/133249
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