Сравнение методов

	Робастная модель динамической панельной регрессии	Системный GMM для панельных данных (оценщик Бланделла-Бонда)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1991–2005	1998
Автор метода	Arellano & Bond (1991); robust extension via Windmeijer (2005)	Blundell & Bond (1998); Arellano & Bover (1995)
Тип	Dynamic panel estimator with robust inference	GMM estimator for dynamic panel data
Основополагающий источник	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.
Другие названия	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
Связанные	5	6
Сводка	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.