Comparer des méthodes

	Modèle de données de panel dynamique robuste	Analyse de données de panel robustes
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1991–2005	1987
Auteur d'origine	Arellano & Bond (1991); robust extension via Windmeijer (2005)	Arellano (1987); White (1980) heteroscedasticity-consistent framework
Type	Dynamic panel estimator with robust inference	Robust estimation / inference correction
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.	Arellano, M. (1987). Computing robust standard errors for within-groups estimators. Oxford Bulletin of Economics and Statistics, 49(4), 431–434.
Alias	robust dynamic panel, heteroscedasticity-robust dynamic panel, robust GMM dynamic panel, dynamic panel with robust standard errors	robust panel regression, cluster-robust panel estimation, panel regression with robust standard errors, HC/CR panel estimator
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.	Robust panel data analysis applies standard panel estimators — fixed effects, random effects, or pooled OLS — while replacing conventional standard errors with cluster-robust or heteroscedasticity-consistent (HC) variants. The point estimates remain unchanged; what changes is the variance-covariance matrix used for inference, making t-tests and F-tests valid even when errors are heteroscedastic or correlated within cross-sectional units over time.