قارن الطرق

	نموذج الانحدار الذاتي المتجه البايزي (BVAR)	الانحدار الذاتي الهيكلي المتجه (SVAR)
المجال	الاقتصاد القياسي	الاقتصاد القياسي
العائلة	Regression model	Regression model
سنة النشأة	1984	1980
صاحب الطريقة	Doan, Litterman & Sims	Sims (1980); identification schemes by Blanchard & Quah (1989)
النوع	Multivariate time-series model	Multivariate time series model
المصدر التأسيسي	Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100.	Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673.
الأسماء البديلة	BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model	SVAR, structural vector autoregression, identified VAR, structural VAR model
ذات صلة	5	5
الملخص	The Bayesian Vector Autoregression (BVAR) model extends the classical VAR framework by incorporating prior beliefs about the model coefficients. Priors — most commonly the Minnesota prior — shrink VAR coefficients toward economically sensible values, dramatically reducing overfitting and improving out-of-sample forecast accuracy even when the number of variables is large.	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.