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Bayesiansk VAR-modell (BVAR)×Bayesiansk ARDL-gränstest×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår19842001 (ARDL); Bayesian extension 2010s
UpphovspersonDoan, Litterman & SimsPesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literature
TypMultivariate time-series modelCointegration / bounds testing
UrsprungskällaDoan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100. DOI ↗Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326. DOI ↗
AliasBVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR modelBayesian ARDL, Bayesian bounds testing approach, Bayes ARDL cointegration, Bayesian PSS bounds test
Närliggande55
SammanfattningThe 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.The Bayesian ARDL Bounds Test extends the classical Pesaran-Shin-Smith (2001) bounds testing approach to cointegration by embedding it within a Bayesian inferential framework. Instead of relying on frequentist F- and t-statistics with tabulated critical values, the researcher specifies prior distributions on the model parameters and derives posterior evidence of a long-run level relationship between variables that may be integrated of order zero or one.
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ScholarGateJämför metoder: Bayesian VAR model · Bayesian ARDL Bounds Test. Hämtad 2026-06-17 från https://scholargate.app/sv/compare