Comparer des méthodes

	Estimateur GMM d'Arellano-Bond	Modèle dynamique de données de panel
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1991	1988–1991
Auteur d'origine	Manuel Arellano and Stephen Bond	Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988)
Type	GMM estimator for dynamic panel data	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	AB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator	dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model
Apparentées	5	5
Résumé	The Arellano-Bond GMM estimator is the standard approach for dynamic panel data models in which the lagged dependent variable appears as a regressor. By first-differencing to remove fixed effects and using deeper lags as instruments, it yields consistent estimates even when the error is serially correlated and regressors are endogenous.	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.