Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Modèle à effets aléatoires robuste× | Modèle à effets fixes robustes× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1980s–2000s | 1987 |
| Auteur d'origine≠ | Wooldridge; White (sandwich covariance); Arellano | Manuel Arellano |
| Type≠ | Panel GLS estimator with robust inference | Panel regression with robust inference |
| Source fondatrice≠ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 | Arellano, M. (1987). Computing robust standard errors for within-groups estimators. Oxford Bulletin of Economics and Statistics, 49(4), 431–434. link ↗ |
| Alias | robust RE model, sandwich random effects estimator, cluster-robust random effects, GLS-robust RE | FE with robust standard errors, cluster-robust fixed effects, fixed effects with heteroscedasticity-robust SE, within estimator with robust inference |
| 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 robust fixed effects model combines the within-group estimator for panel data with variance-covariance matrices that remain valid under heteroscedasticity and within-unit error correlation. Introduced by Arellano (1987), cluster-robust standard errors paired with the fixed effects estimator are now the default approach for credible panel data inference in economics and social science. |
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