Comparer des méthodes

	Modèle de données de panel dynamique	Modèle dynamique de données de panel
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1991–1998	1988–1991
Auteur d'origine	Arellano & Bond (1991); Blundell & Bond (1998)	Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988)
Type	Dynamic panel regression	Dynamic regression / GMM estimation
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., & 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.
Alias	dynamic panel model, lagged dependent variable panel model, Arellano-Bond type dynamic panel, GMM dynamic panel	dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model
Apparentées	5	5
Résumé	The dynamic panel data model extends standard panel regression by including one or more lagged values of the outcome variable as regressors. Because past outcomes directly predict current outcomes, the model captures persistence and adjustment dynamics — but it also introduces a correlation between the lagged dependent variable and the individual fixed effect, rendering OLS and standard fixed-effects estimators inconsistent. GMM-based approaches developed by Arellano-Bond and Blundell-Bond resolve this problem.	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.