Comparer des méthodes

	Test bayésien de racine unitaire de Phillips-Perron	Modèle VAR bayésien (BVAR)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1988 / early 1990s	1984
Auteur d'origine	Phillips & Perron (classical test, 1988); Bayesian framework: Sims & Uhlig (1991)	Doan, Litterman & Sims
Type	Unit root test (Bayesian)	Multivariate time-series model
Source fondatrice	Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346.	Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100.
Alias	Bayesian PP test, Bayesian Phillips-Perron test, Bayesian nonparametric unit root test, Bayes PP unit root	BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model
Apparentées	5	5
Résumé	The Bayesian Phillips-Perron unit root test combines the nonparametric long-run variance correction of the classical Phillips-Perron test with a Bayesian inferential framework. Instead of a p-value, it yields a posterior probability or Bayes factor quantifying evidence for or against a unit root, allowing researchers to incorporate prior economic knowledge and obtain probability statements directly about the persistence of a time series.	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.