A relevant issue in panel data estimation is heteroskedasticity, which often occurs when the sample size 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. This paper considers the general least squares estimation of heteroskedastic stratified two-way error component model of both single equations and seemingly unrelated regressions (SUR) systems (with cross-equations restrictions) on unbalanced panel data. The derived heteroskedastic estimators improve the estimation efficiency, with the SUR procedures performing better than the singleequation procedures.

Platoni, S., Moro, D., Sckokai, P., Barbieri, L., Heteroskedastic Stratified Two-way Error Component Models of Single Equations and Seemingly Unrelated Regressions Systems, <<Università Cattolica del Sacro Cuore - DIPARTIMENTO DI SCIENZE ECONOMICHE E SOCIALI>>, 2016; 2016 (117/settembre): 3-44 [http://hdl.handle.net/10807/86460]

Heteroskedastic Stratified Two-way Error Component Models of Single Equations and Seemingly Unrelated Regressions Systems

Platoni
Primo
;
Silvia; Moro
Secondo
;
Daniele; Sckokai
Penultimo
;
Paolo; Barbieri
Ultimo
2016

Abstract

A relevant issue in panel data estimation is heteroskedasticity, which often occurs when the sample size 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. This paper considers the general least squares estimation of heteroskedastic stratified two-way error component model of both single equations and seemingly unrelated regressions (SUR) systems (with cross-equations restrictions) on unbalanced panel data. The derived heteroskedastic estimators improve the estimation efficiency, with the SUR procedures performing better than the singleequation procedures.
Inglese
Università Cattolica del Sacro Cuore - DIPARTIMENTO DI SCIENZE ECONOMICHE E SOCIALI
978-88-343-3273-3
Vita e Pensiero
Platoni, S., Moro, D., Sckokai, P., Barbieri, L., Heteroskedastic Stratified Two-way Error Component Models of Single Equations and Seemingly Unrelated Regressions Systems, <<Università Cattolica del Sacro Cuore - DIPARTIMENTO DI SCIENZE ECONOMICHE E SOCIALI>>, 2016; 2016 (117/settembre): 3-44 [http://hdl.handle.net/10807/86460]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/86460
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact