Salīdzināt metodes

	Bayesiskais strukturālais VAR (B-SVAR) modelis	Vektora kļūdu labojuma modelis (VECM)
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1998–2005	1987
Autors	Sims & Zha (1998); Uhlig (2005) for sign-restriction identification	Robert F. Engle and Clive W. J. Granger
Tips	Structural multivariate time-series model	Multivariate time-series model
Pirmavots	Sims, C. A., & Zha, T. (1998). Bayesian methods for dynamic multivariate models. International Economic Review, 39(4), 949–968.	Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276.
Citi nosaukumi	Bayesian SVAR, B-SVAR, Bayesian structural VAR, Bayesian identified VAR	VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
Saistītās	6	5
Kopsavilkums	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.	The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series.