Comparer des méthodes

	Modèle VAR bayésien (BVAR)	Autoregressive Vectoriel (VAR)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1984	1980
Auteur d'origine	Doan, Litterman & Sims	Christopher A. Sims
Type	Multivariate time-series model	Multivariate time-series model
Source fondatrice	Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100.	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
Alias	BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model	VAR, VAR model, vector autoregressive model, multivariate autoregression
Apparentées	5	5
Résumé	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.	Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.