Compara mètodes

	Model de Vector Autoregressiu Estructural Bayesiana (B-SVAR)	Model vectorial d'error de correcció bayesià (Bayesian VECM)
Camp	Econometria	Econometria
Família	Regression model	Regression model
Any d'origen	1998–2005	2002–2005
Autor original	Sims & Zha (1998); Uhlig (2005) for sign-restriction identification	Kleibergen & Paap; Villani
Tipus	Structural multivariate time-series model	Bayesian multivariate time series model
Font seminal	Sims, C. A., & Zha, T. (1998). Bayesian methods for dynamic multivariate models. International Economic Review, 39(4), 949–968.	Kleibergen, F., & Paap, R. (2002). Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration. Journal of Econometrics, 111(2), 223–249.
Àlies	Bayesian SVAR, B-SVAR, Bayesian structural VAR, Bayesian identified VAR	Bayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correction
Relacionats	6	5
Resum	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 Bayesian VECM combines the classical Vector Error Correction Model — which captures both short-run dynamics and long-run cointegrating relationships among non-stationary multivariate time series — with Bayesian prior distributions over the cointegrating rank and coefficient matrices. This allows principled uncertainty quantification, incorporation of economic theory as priors, and coherent inference even in small samples.