Comparer des méthodes

	Test de causalité de Granger	Autoregressive Vectoriel (VAR)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1969	1980
Auteur d'origine	Clive W. J. Granger	Christopher A. Sims
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.	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
Alias	Granger test, GC test, predictive causality test, Granger non-causality test	VAR, VAR model, vector autoregressive model, multivariate autoregression
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.	Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.