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| Granger Causality Test× | Structural Vector Autoregression (SVAR)× | |
|---|---|---|
| Campo | Econometria | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 1969 | 1980 |
| Ideatore≠ | Clive W. J. Granger | Sims (1980); identification schemes by Blanchard & Quah (1989) |
| Tipo≠ | Causality test (F-test on VAR) | Multivariate time series model |
| Fonte seminale≠ | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. DOI ↗ | Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673. link ↗ |
| Alias | Granger test, GC test, predictive causality test, Granger non-causality test | SVAR, structural vector autoregression, identified VAR, structural VAR model |
| Correlati | 5 | 5 |
| Sintesi≠ | The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis. | 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. |
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