Comparer des méthodes

	Modèle de VAR structurel bayésien (B-SVAR)	Modèle Bayésien de Correction d'Erreur Vectoriel (Bayesian VECM)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1998–2005	2002–2005
Auteur d'origine	Sims & Zha (1998); Uhlig (2005) for sign-restriction identification	Kleibergen & Paap; Villani
Type	Structural multivariate time-series model	Bayesian multivariate time series model
Source fondatrice	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.
Alias	Bayesian SVAR, B-SVAR, Bayesian structural VAR, Bayesian identified VAR	Bayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correction
Apparentées	6	5
Résumé	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.