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Bayesowski dynamiczny model danych panelowych×Estymator GMM Arellano-Bonda×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania2002–20071991
TwórcaHsiao, Pesaran, Tahmiscioglu; Arellano & BonhommeManuel Arellano and Stephen Bond
TypBayesian panel modelGMM estimator for dynamic panel data
Źródło pierwotneHsiao, C., Pesaran, M. H., & Tahmiscioglu, A. K. (2002). Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods. Journal of Econometrics, 109(1), 107–150. 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 ↗
Inne nazwyBayesian DPD model, Bayesian lagged dependent variable panel model, Bayesian autoregressive panel model, B-DPDAB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator
Pokrewne65
PodsumowanieThe Bayesian dynamic panel data model extends standard dynamic panel models — which include a lagged dependent variable to capture state dependence — by estimating all parameters within a Bayesian framework. Prior distributions are combined with the likelihood to yield a full posterior distribution over model parameters, enabling probabilistic inference and coherent uncertainty quantification even in short panels.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.
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ScholarGatePorównaj metody: Bayesian Dynamic Panel Data Model · Arellano-Bond GMM estimator. Pobrano 2026-06-18 z https://scholargate.app/pl/compare