Salīdzināt metodes

	Robusts dinamiskā paneļa datu modelis	Dinamiskais paneļa datu modelis
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1991–2005	1988–1991
Autors	Arellano & Bond (1991); robust extension via Windmeijer (2005)	Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988)
Tips	Dynamic panel estimator with robust inference	Dynamic regression / GMM estimation
Pirmavots	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., & 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.
Citi nosaukumi	robust dynamic panel, heteroscedasticity-robust dynamic panel, robust GMM dynamic panel, dynamic panel with robust standard errors	dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model
Saistītās	5	5
Kopsavilkums	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.	The dynamic panel data model extends standard panel regression by including a lagged value of the outcome variable as a regressor, capturing persistence and adjustment dynamics. Because the lagged dependent variable is correlated with the unit-specific fixed effect, ordinary OLS or within estimators are biased; GMM-based methods using internal instruments are the standard remedy.