Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Panel VARX× | Часові параметри з факторизаційним розширенням VAR× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2013 | 2005 |
| Автор методу≠ | Canova and Ciccarelli | Bernanke, Boivin, and Eliasz |
| Тип≠ | Multi-equation panel model | Time-varying system |
| Основоположне джерело≠ | Canova, F., & Ciccarelli, M. (2013). Panel vector autoregressive models: A survey. Advances in Econometrics, 32, 205-246. DOI ↗ | Bernanke, B. S., Boivin, J., & Eliasz, P. S. (2005). Measuring monetary policy. Journal of Political Economy, 113(1), 161-208. link ↗ |
| Інші назви | Panel VAR-X | Dynamic factor model with time-varying parameters |
| Пов'язані | 3 | 3 |
| Підсумок≠ | Panel VARX extends vector autoregression to heterogeneous panels with exogenous variables, enabling simultaneous modeling of multiple endogenous variables alongside observed external factors across many units. Introduced by Holtz-Eakin et al. (1988) and advanced by Canova and Ciccarelli (2013), it captures dynamic relationships within units while allowing parameters to vary across units. This framework is essential for macroeconomic panels and understanding cross-unit heterogeneity in responses to common shocks. | TVP-FAVAR is a hybrid framework combining factor-augmented VARs with time-varying parameter estimation via Kalman filtering. Introduced by Bernanke et al. (2005) and refined by Primiceri (2005), it extracts latent economic factors (e.g., a 'common monetary policy shock') from high-dimensional data while allowing VAR coefficients to evolve stochastically over time. This framework captures both reduced-dimensionality patterns and structural instability, making it ideal for studying evolving policy regimes and shock dynamics. |
| ScholarGateНабір даних ↗ |
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