Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Strukturālā pārtraukuma VAR modelis× | Strukturālā vektorautoregresija (SVAR)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1980–1998 | 1980 |
| Autors≠ | Bai & Perron (structural breaks); Sims (VAR framework) | Sims (1980); identification schemes by Blanchard & Quah (1989) |
| Tips≠ | Multivariate time series model with regime change | Multivariate time series model |
| Pirmavots≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ | Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673. link ↗ |
| Citi nosaukumi | VAR with structural breaks, break-point VAR, regime-switching VAR, SB-VAR | SVAR, structural vector autoregression, identified VAR, structural VAR model |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | The Structural Break VAR model extends the standard Vector Autoregression (VAR) framework by allowing coefficient matrices and error covariance to shift at one or more unknown break dates. It is designed for multivariate time series where economic relationships change abruptly due to policy shifts, financial crises, or major structural events. | Structural VAR extends the reduced-form VAR by imposing economic theory-based restrictions that identify orthogonal structural shocks. This allows researchers to disentangle the causal effects of distinct economic disturbances — such as supply versus demand shocks — and trace their dynamic propagation through a system of variables via impulse response functions and forecast error variance decompositions. |
| ScholarGateDatu kopa ↗ |
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