Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Modèle à effets aléatoires avec rupture structurelle× | Test de Hausman sur données de panel× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1998–2000s | 1978 |
| Auteur d'origine≠ | Bai & Perron (break detection); Baltagi (panel RE framework) | Jerry A. Hausman |
| Type≠ | Panel regression with regime shifts | Specification test |
| Source fondatrice≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ | Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271. DOI ↗ |
| Alias | RE model with structural breaks, break-adjusted random effects, random effects break model, panel RE with regime shifts | Hausman endogeneity test, Wu-Hausman test, fixed-vs-random effects test, Hausman chi-squared test |
| Apparentées | 5 | 5 |
| Résumé≠ | The structural break random effects model extends standard panel RE estimation by allowing one or more breakpoints at which slope coefficients or error variances shift across time. It combines structural change detection (e.g., Bai-Perron) with the GLS-based random effects estimator, producing regime-specific parameter estimates while retaining the efficiency gains of pooling individual-level variation as random draws from a common distribution. | 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. |
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