Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| VAR cu Praguri Paneliene× | VAR cu Factori Augmentați și Parametri Variabili în Timp× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1996 | 2005 |
| Autorul original≠ | Bruce Hansen and colleagues | Bernanke, Boivin, and Eliasz |
| Tip≠ | Nonlinear panel model | Time-varying system |
| Sursa seminală≠ | Hansen, B. E. (1996). Inference when a nuisance parameter is not identified under the null hypothesis. Econometric Theory, 12(3), 386-414. DOI ↗ | Bernanke, B. S., Boivin, J., & Eliasz, P. S. (2005). Measuring monetary policy. Journal of Political Economy, 113(1), 161-208. link ↗ |
| Denumiri alternative | Panel-VAR with regime switching | Dynamic factor model with time-varying parameters |
| Înrudite | 3 | 3 |
| Rezumat≠ | The Threshold Panel VAR extends the standard vector autoregression framework to accommodate regime-switching behavior where relationships change when a threshold variable crosses a critical level. Introduced by Hansen (1996) and applied to panels by Caner and Hansen (2001), it allows different dynamic relationships across regimes (e.g., expansions versus recessions) while exploiting the cross-sectional dimension of panel data. This nonlinear framework captures state-dependent policy effects and economic mechanisms. | 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. |
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