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| Estimateur GMM systémique (Estimateur de Blundell-Bond)× | Modèle à effets aléatoires sur données de panel× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1998 | 1966 |
| Auteur d'origine≠ | Blundell & Bond (1998); Arellano & Bover (1995) | Balestra & Nerlove |
| Type≠ | GMM estimator for dynamic panel data | Panel data estimator |
| Source fondatrice≠ | Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143. 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 | System GMM, Blundell-Bond estimator, SYS-GMM, two-step System GMM | random effects estimator, RE model, GLS random effects, error components model |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | Panel System GMM is a two-equation GMM estimator for dynamic panel data that stacks the differenced equation (using lagged levels as instruments) with the levels equation (using lagged differences as instruments). Developed by Blundell and Bond (1998) on the foundation of Arellano and Bover (1995), it is the preferred tool when the lagged dependent variable is highly persistent or individual effects are large. | 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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