Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Test de Hausman sur données de panel× | Modèle à effets aléatoires sur données de panel× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1978 | 1966 |
| Auteur d'origine≠ | Jerry A. Hausman | Balestra & Nerlove |
| Type≠ | Specification test | Panel data estimator |
| Source fondatrice≠ | Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271. DOI ↗ | 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. DOI ↗ |
| Alias | Hausman endogeneity test, Wu-Hausman test, fixed-vs-random effects test, Hausman chi-squared test | random effects estimator, RE model, GLS random effects, error components model |
| Apparentées | 5 | 5 |
| Résumé≠ | 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. | 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. |
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