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| Bayes'i dünaamiline paneelmudelis× | Dünaamiline paneelmudel× | |
|---|---|---|
| Valdkond | Ökonomeetria | Ökonomeetria |
| Perekond | Regression model | Regression model |
| Tekkeaasta≠ | 2002–2007 | 1988–1991 |
| Looja≠ | Hsiao, Pesaran, Tahmiscioglu; Arellano & Bonhomme | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) |
| Tüüp≠ | Bayesian panel model | Dynamic regression / GMM estimation |
| Algallikas≠ | 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. 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 ↗ |
| Rööpnimetused | 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 |
| Seotud≠ | 6 | 5 |
| Kokkuvõte≠ | 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. |
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