Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Байесов модел с произволни ефекти× | Модел с фиксирани ефекти за панелни данни× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1972–1995 | 2014 |
| Създател≠ | Lindley & Smith (1972); extended by Gelman, Rubin and colleagues | Hsiao (textbook treatment); within transformation of panel data |
| Тип≠ | Bayesian hierarchical panel model | Panel data regression |
| Основополагащ източник≠ | 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 | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Други названия | Bayesian hierarchical model, Bayesian mixed effects model, Bayesian multilevel model, BREM | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Свързани | 5 | 5 |
| Резюме≠ | 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. | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). |
| ScholarGateНабор от данни ↗ |
|
|