Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Modèle à effets aléatoires robuste× | Test de Hausman sur données de panel× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1980s–2000s | 1978 |
| Auteur d'origine≠ | Wooldridge; White (sandwich covariance); Arellano | Jerry A. Hausman |
| Type≠ | Panel GLS estimator with robust inference | Specification test |
| Source fondatrice≠ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 | Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271. DOI ↗ |
| Alias | robust RE model, sandwich random effects estimator, cluster-robust random effects, GLS-robust RE | Hausman endogeneity test, Wu-Hausman test, fixed-vs-random effects test, Hausman chi-squared test |
| 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 Hausman specification test for panel data determines whether individual-specific effects are correlated with the regressors — a correlation that would make the random effects estimator inconsistent. A statistically significant result favours the fixed effects model; a non-significant result supports the more efficient random effects model. |
| ScholarGateJeu de données ↗ |
|
|