Σύγκριση μεθόδων

	Μοντέλο Bayesian VAR (BVAR)	Μοντέλο Bayesian Structural VAR (B-SVAR)
Πεδίο	Οικονομετρία	Οικονομετρία
Οικογένεια	Regression model	Regression model
Έτος προέλευσης	1984	1998–2005
Δημιουργός	Doan, Litterman & Sims	Sims & Zha (1998); Uhlig (2005) for sign-restriction identification
Τύπος	Multivariate time-series model	Structural multivariate time-series model
Θεμελιώδης πηγή	Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100.	Sims, C. A., & Zha, T. (1998). Bayesian methods for dynamic multivariate models. International Economic Review, 39(4), 949–968.
Εναλλακτικές ονομασίες	BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model	Bayesian SVAR, B-SVAR, Bayesian structural VAR, Bayesian identified VAR
Συναφείς	5	6
Σύνοψη	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.	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.