Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Анализ на панелни данни с времево променящи се параметри× | Модел с произволни ефекти за панелни данни× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1960–2003 | 2021 |
| Създател≠ | Cheng Hsiao (panel treatment); Kalman (state-space foundation) | Baltagi (textbook treatment); classical random-effects panel estimator |
| Тип≠ | Dynamic panel model | Panel data regression |
| Основополагащ източник≠ | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. DOI ↗ |
| Други названия | TVP panel model, time-varying coefficient panel model, state-space panel regression, random coefficient panel model | random effects panel model, RE estimator, GLS random effects, Panel Veri — Rassal Etkiler Modeli |
| Свързани | 5 | 5 |
| Резюме≠ | Time-varying parameter (TVP) panel data analysis extends standard panel regression by allowing the slope coefficients to evolve over time for each unit. Instead of assuming a single fixed or random coefficient, the model lets each unit's relationship between predictors and outcome shift period by period, capturing structural change, learning effects, and heterogeneous dynamics across individuals and time. | The Random Effects model is a panel-data regression that treats unobserved individual heterogeneity as a random component drawn from a common distribution, rather than a separate parameter for each unit. It is a standard estimator in panel econometrics, developed in textbook treatments such as Baltagi's Econometric Analysis of Panel Data (2021). |
| ScholarGateНабор от данни ↗ |
|
|