השוואת שיטות

	מודל מרחב מצב (מסנן קלמן)	אוטורגרסיה וקטורית מבנית (SVAR)
תחום	אקונומטריקה	אקונומטריקה
משפחה	Regression model	Regression model
שנת המקור	1990	1980
הוגה השיטה	Harvey; Durbin & Koopman (state space treatment); Kalman filter	Sims (1980); identification schemes by Blanchard & Quah (1989)
סוג	State space time series model	Multivariate time series model
מקור מכונן	Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press.	Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673.
כינויים	state space, Kalman filter, unobserved components model, Durum Uzayı Modeli (State Space / Kalman Filter)	SVAR, structural vector autoregression, identified VAR, structural VAR model
קשורות	4	5
תקציר	A state space model is a general time series framework that describes a series through unobserved (latent) state variables linked by a measurement equation and a transition equation, with the states estimated in real time by the Kalman filter. Developed in the state space tradition of Harvey (1990) and Durbin & Koopman (2012), it nests ARIMA and exponential smoothing as special cases.	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.