Comparer des méthodes

	Modèle à effets aléatoires robuste	Modèle à effets aléatoires sur données de panel
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1980s–2000s	1966
Auteur d'origine	Wooldridge; White (sandwich covariance); Arellano	Balestra & Nerlove
Type	Panel GLS estimator with robust inference	Panel data estimator
Source fondatrice	Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586	Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612.
Alias	robust RE model, sandwich random effects estimator, cluster-robust random effects, GLS-robust RE	random effects estimator, RE model, GLS random effects, error components model
Apparentées	5	5
Résumé	The Robust Random Effects model estimates panel data relationships using the GLS random effects estimator while replacing the conventional standard errors with sandwich (heteroscedasticity- and cluster-robust) variance estimates. This protects inference against arbitrary within-group correlation and heteroscedasticity without discarding the efficiency gains of random effects when unit-specific effects are genuinely uncorrelated with the regressors.	The panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation.