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Bayesian System GMM×Dinamikus panel regressziós modell×
TudományterületÖkonometriaÖkonometria
MódszercsaládRegression modelRegression model
Keletkezés éve1998–20101991–1998
MegalkotóBlundell & Bond (System GMM, 1998); Bayesian integration via Chib and related MCMC literatureArellano & Bond (1991); Blundell & Bond (1998)
TípusBayesian dynamic panel estimatorDynamic panel regression
AlapműBlundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143. DOI ↗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. DOI ↗
Alternatív nevekBayesian Sys-GMM, Bayesian BB estimator, Bayesian Blundell-Bond GMM, B-SGMMdynamic panel model, lagged dependent variable panel model, Arellano-Bond type dynamic panel, GMM dynamic panel
Kapcsolódó55
ÖsszefoglalóBayesian 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.
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ScholarGateMódszerek összehasonlítása: Bayesian System GMM · Panel Dynamic Panel Data Model. Letöltve 2026-06-15, forrás: https://scholargate.app/hu/compare