Comparer des méthodes

	Moindres Carrés Généralisés Robustes (MCG Robustes)	Moindres Carrés Généralisés sur Panneaux (MCG Panneau)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1936 / 1980	1935 / developed for panels 1980s–1990s
Auteur d'origine	Aitken (GLS theory, 1936); White (robust covariance, 1980)	Aitken (1935); extended to panel data by Baltagi and others
Type	Robust linear regression	Generalized linear regression
Source fondatrice	Greene, W. H. (2012). Econometric Analysis (7th ed.). Pearson. Chapter 9: The Generalized Regression Model and Heteroscedasticity. ISBN: 978-0131395381	Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586
Alias	robust generalized least squares, GLS with robust standard errors, heteroscedasticity-consistent GLS, HC-GLS	Panel GLS, Generalized Least Squares for panel data, FGLS panel, feasible GLS panel
Apparentées	5	3
Résumé	Robust 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.