Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Vector Autoregresiv Structural (SVAR)× | Modelul Vectorial cu Corecție de Eroare (VECM)× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1980 | 1987 |
| Autorul original≠ | Sims (1980); identification schemes by Blanchard & Quah (1989) | Robert F. Engle and Clive W. J. Granger |
| Tip≠ | Multivariate time series model | Multivariate time-series model |
| Sursa seminală≠ | Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673. link ↗ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ |
| Denumiri alternative | SVAR, structural vector autoregression, identified VAR, structural VAR model | VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model |
| Înrudite | 5 | 5 |
| Rezumat≠ | 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. | The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series. |
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