Comparer des méthodes

	Autorégression Vectorielle Structurelle (SVAR)	Test de causalité de Granger
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1980	1969
Auteur d'origine	Sims (1980); identification schemes by Blanchard & Quah (1989)	Clive W. J. Granger
Type	Multivariate time series model	Causality test (F-test on VAR)
Source fondatrice	Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673.	Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438.
Alias	SVAR, structural vector autoregression, identified VAR, structural VAR model	Granger test, GC test, predictive causality test, Granger non-causality test
Apparentées	5	5
Résumé	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 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.