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Modèle à effets aléatoires pour données de panel×Test de spécification de Hausman (FE vs RE)×
DomaineÉconométrieÉconométrie
FamilleRegression modelRegression model
Année d'origine19781978
Auteur d'origineBaltagi (textbook treatment); Hausman specification testJerry A. Hausman
TypePanel data regressionSpecification test for panel data models
Source fondatriceHausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251-1271. DOI ↗Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251–1271. DOI ↗
Aliasrandom effects panel regression, RE estimator, GLS panel estimator, Panel Rassal Etkiler ModeliHausman specification test, FE vs RE test, Durbin-Wu-Hausman test, Hausman Spesifikasyon Testi (FE vs RE)
Apparentées55
RésuméThe random effects model is a panel data estimator that explains an outcome using both within-unit and between-unit variation, treating the unobserved unit-specific heterogeneity as a random, normally distributed term rather than a fixed parameter. Its validity is judged with the Hausman (1978) specification test, and it is developed in standard treatments such as Baltagi's Econometric Analysis of Panel Data.The Hausman test is a specification test, introduced by Jerry A. Hausman in 1978, that decides between the fixed-effects (FE) and random-effects (RE) estimators in panel data models. The null hypothesis is that the random-effects estimator is consistent and efficient and should be preferred; the alternative is that random effects is inconsistent and fixed effects is required because the unit-specific effects are correlated with the explanatory variables.
ScholarGateJeu de données
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ScholarGateComparer des méthodes: Random Effects Panel Model · Hausman Test. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare