Comparer des méthodes

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