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Model Bayesovská vektorová autoregrese (BVAR)×Bayesovský test mezí ARDL×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku19842001 (ARDL); Bayesian extension 2010s
TvůrceDoan, Litterman & SimsPesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literature
TypMultivariate time-series modelCointegration / bounds testing
Původní zdrojDoan, 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 ↗
Další názvyBVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR modelBayesian ARDL, Bayesian bounds testing approach, Bayes ARDL cointegration, Bayesian PSS bounds test
Příbuzné55
ShrnutíThe 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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ScholarGatePorovnat metody: Bayesian VAR model · Bayesian ARDL Bounds Test. Získáno 2026-06-17 z https://scholargate.app/cs/compare