Salīdzināt metodes

	Strukturālā vektorautoregresija (SVAR)	ARMA modelis (Autoregresīvs vidējais aritmētiskais)
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1980	1970
Autors	Sims (1980); identification schemes by Blanchard & Quah (1989)	George E. P. Box and Gwilym M. Jenkins
Tips	Multivariate time series model	Time series model
Pirmavots	Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Citi nosaukumi	SVAR, structural vector autoregression, identified VAR, structural VAR model	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Saistītās	5	5
Kopsavilkums	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.	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.