Comparer des méthodes

	Modèle de données de panel dynamique robuste	Estimateur GMM systémique (Estimateur de Blundell-Bond)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1991–2005	1998
Auteur d'origine	Arellano & Bond (1991); robust extension via Windmeijer (2005)	Blundell & Bond (1998); Arellano & Bover (1995)
Type	Dynamic panel estimator with robust inference	GMM estimator for dynamic panel data
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.	Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143.
Alias	robust dynamic panel, heteroscedasticity-robust dynamic panel, robust GMM dynamic panel, dynamic panel with robust standard errors	System GMM, Blundell-Bond estimator, SYS-GMM, two-step System GMM
Apparentées	5	6
Résumé	The robust dynamic panel data model combines the dynamic panel GMM framework — which handles endogeneity from lagged dependent variables and unobserved heterogeneity — with robust covariance estimation that remains valid under heteroscedasticity and serial correlation. The Windmeijer finite-sample correction is the standard robust adjustment applied to two-step GMM estimators in this setting.	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.