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Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Robust Generalized Least Squares (Robust GLS)×Mínimos Quadrados Generalizados em Painel (Panel GLS)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem1936 / 19801935 / developed for panels 1980s–1990s
Autor originalAitken (GLS theory, 1936); White (robust covariance, 1980)Aitken (1935); extended to panel data by Baltagi and others
TipoRobust linear regressionGeneralized linear regression
Fonte seminalGreene, W. H. (2012). Econometric Analysis (7th ed.). Pearson. Chapter 9: The Generalized Regression Model and Heteroscedasticity. ISBN: 978-0131395381Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586
Outros nomesrobust generalized least squares, GLS with robust standard errors, heteroscedasticity-consistent GLS, HC-GLSPanel GLS, Generalized Least Squares for panel data, FGLS panel, feasible GLS panel
Relacionados53
ResumoRobust GLS extends classical Generalized Least Squares by pairing GLS coefficient estimation with heteroscedasticity- and autocorrelation-consistent (HAC) standard errors, or by using M-estimation within the GLS framework. It corrects for non-spherical errors — heteroscedasticity, autocorrelation, or both — while also guarding inference against misspecification of the error covariance structure.Panel GLS is a regression method for longitudinal data that explicitly models the non-spherical error structure — heteroscedasticity across units and serial correlation within units — to recover efficient coefficient estimates. Unlike OLS, it weights observations by the inverse of the error covariance matrix, yielding the Best Linear Unbiased Estimator when the error structure is correctly specified.
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ScholarGateComparar métodos: Robust GLS · Panel GLS. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare