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| Байесов анализ на панелни данни× | Байесов модел с произволни ефекти× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1971–1999 | 1972–1995 |
| Създател≠ | Zellner (1971); Hsiao, Pesaran, and Tahmiscioglu (1999) | Lindley & Smith (1972); extended by Gelman, Rubin and colleagues |
| Тип≠ | Bayesian estimation for panel data | Bayesian hierarchical panel model |
| Основополагащ източник≠ | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 | Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955 |
| Други названия | Bayesian panel model, Bayesian longitudinal model, hierarchical panel model, Bayesian multilevel panel | Bayesian hierarchical model, Bayesian mixed effects model, Bayesian multilevel model, BREM |
| Свързани | 5 | 5 |
| Резюме≠ | 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. | The Bayesian random effects model combines panel-data random effects with a Bayesian prior framework, allowing unit-specific effects to be treated as draws from a population distribution whose hyperparameters are estimated from the data. This produces regularised, uncertainty-quantified estimates that borrow strength across units — particularly valuable for short panels, sparse groups, or settings where frequentist variance-component estimation is unstable. |
| ScholarGateНабор от данни ↗ |
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