Compară metode

	Modelul Bayesian Dinamic pentru Date de Panel	Modelul de date de panel dinamic
Domeniu	Econometrie	Econometrie
Familie	Regression model	Regression model
Anul apariției	2002–2007	1988–1991
Autorul original	Hsiao, Pesaran, Tahmiscioglu; Arellano & Bonhomme	Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988)
Tip	Bayesian panel model	Dynamic regression / GMM estimation
Sursa seminală	Hsiao, 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.	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.
Denumiri alternative	Bayesian DPD model, Bayesian lagged dependent variable panel model, Bayesian autoregressive panel model, B-DPD	dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model
Înrudite	6	5
Rezumat	The 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 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.