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Model VAR Bayesian (BVAR)×Ujian Had Bayesian ARDL×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19842001 (ARDL); Bayesian extension 2010s
PengasasDoan, Litterman & SimsPesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literature
JenisMultivariate time-series modelCointegration / bounds testing
Sumber perintisDoan, 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
Berkaitan55
RingkasanThe 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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ScholarGateBandingkan kaedah: Bayesian VAR model · Bayesian ARDL Bounds Test. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare