Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Estimateur GMM de Arellano-Bond pour données de panel× | Modèle à effets aléatoires sur données de panel× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1991 | 1966 |
| Auteur d'origine≠ | Manuel Arellano and Stephen Bond | Balestra & Nerlove |
| Type≠ | Dynamic panel GMM estimator | Panel data estimator |
| Source fondatrice≠ | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297. 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 | Arellano-Bond GMM, AB-GMM, difference GMM estimator, dynamic panel GMM | random effects estimator, RE model, GLS random effects, error components model |
| Apparentées | 5 | 5 |
| Résumé≠ | The Arellano-Bond GMM estimator addresses the two core problems of dynamic panel models — individual fixed effects correlated with the regressors, and the endogeneity introduced by a lagged dependent variable — by first-differencing to remove fixed effects and then using lagged levels of the dependent variable as internal instruments. | 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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