Comparer des méthodes

	Modèle ARMA (Autoregressive Moving Average)	Autorégression Vectorielle Structurelle (SVAR)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1970	1980
Auteur d'origine	George E. P. Box and Gwilym M. Jenkins	Sims (1980); identification schemes by Blanchard & Quah (1989)
Type	Time series model	Multivariate time series model
Source fondatrice	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.	Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673.
Alias	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)	SVAR, structural vector autoregression, identified VAR, structural VAR model
Apparentées	5	5
Résumé	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.	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.