Сравнение на методи

	Байесов модел на структурен векторна авторегресия (B-SVAR)	Структурна векторна авторегресия (SVAR)
Област	Иконометрия	Иконометрия
Семейство	Regression model	Regression model
Година на възникване	1998–2005	1980
Създател	Sims & Zha (1998); Uhlig (2005) for sign-restriction identification	Sims (1980); identification schemes by Blanchard & Quah (1989)
Тип	Structural multivariate time-series model	Multivariate time series model
Основополагащ източник	Sims, C. A., & Zha, T. (1998). Bayesian methods for dynamic multivariate models. International Economic Review, 39(4), 949–968.	Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673.
Други названия	Bayesian SVAR, B-SVAR, Bayesian structural VAR, Bayesian identified VAR	SVAR, structural vector autoregression, identified VAR, structural VAR model
Свързани	6	5
Резюме	The Bayesian Structural Vector Autoregression model combines the structural identification of SVAR with Bayesian prior distributions over parameters. It estimates causal impulse responses between multiple time series while incorporating prior economic knowledge and producing full posterior uncertainty bands rather than point estimates alone.	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.