Comparer des méthodes

	GMM Systémique Bayésien	Modèle de données de panel dynamique
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1998–2010	1991–1998
Auteur d'origine	Blundell & Bond (System GMM, 1998); Bayesian integration via Chib and related MCMC literature	Arellano & Bond (1991); Blundell & Bond (1998)
Type	Bayesian dynamic panel estimator	Dynamic panel regression
Source fondatrice	Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143.	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	Bayesian Sys-GMM, Bayesian BB estimator, Bayesian Blundell-Bond GMM, B-SGMM	dynamic panel model, lagged dependent variable panel model, Arellano-Bond type dynamic panel, GMM dynamic panel
Apparentées	5	5
Résumé	Bayesian System GMM combines the Blundell-Bond System Generalized Method of Moments estimator for dynamic panel data with Bayesian prior distributions and posterior inference via MCMC. It handles endogeneity, individual fixed effects, and weak-instrument problems while incorporating prior knowledge and delivering full posterior uncertainty quantification — not just point estimates and asymptotic standard errors.	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.