Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Байєсівська модель динамічних панельних даних× | Байєсівський аналіз панельних даних× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2002–2007 | 1971–1999 |
| Автор методу≠ | Hsiao, Pesaran, Tahmiscioglu; Arellano & Bonhomme | Zellner (1971); Hsiao, Pesaran, and Tahmiscioglu (1999) |
| Тип≠ | Bayesian panel model | Bayesian estimation for panel data |
| Основоположне джерело≠ | 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 ↗ | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 |
| Інші назви | Bayesian DPD model, Bayesian lagged dependent variable panel model, Bayesian autoregressive panel model, B-DPD | Bayesian panel model, Bayesian longitudinal model, hierarchical panel model, Bayesian multilevel panel |
| Пов'язані≠ | 6 | 5 |
| Підсумок≠ | 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. | Bayesian panel data analysis applies Bayesian inference to models with repeated observations on multiple units. By placing prior distributions on coefficients and variance components, it merges prior knowledge with the observed panel likelihood to produce full posterior distributions for fixed or random effects, slope heterogeneity, and variance parameters — rather than point estimates and asymptotic standard errors. |
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