Confronta i metodi

	Modello ARMA (Autoregressive Moving Average)	Granger Causality Test
Campo	Econometria	Econometria
Famiglia	Regression model	Regression model
Anno di origine	1970	1969
Ideatore	George E. P. Box and Gwilym M. Jenkins	Clive W. J. Granger
Tipo	Time series model	Causality test (F-test on VAR)
Fonte seminale	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.	Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438.
Alias	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)	Granger test, GC test, predictive causality test, Granger non-causality test
Correlati	5	5
Sintesi	The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting.	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.