Comparar métodos

	Vector Autoregression (VAR)	Prueba de Causalidad de Granger
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	1980	1969
Autor original	Christopher A. Sims	Clive W. J. Granger
Tipo	Multivariate time-series model	Causality test (F-test on VAR)
Fuente seminal	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.	Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438.
Alias	VAR, VAR model, vector autoregressive model, multivariate autoregression	Granger test, GC test, predictive causality test, Granger non-causality test
Relacionados	5	5
Resumen	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.	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.