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Bayesovský model vektorovej korekcie chýb (Bayesian VECM)×Vektorový model korekcie chýb (VECM)×
OdborEkonometriaEkonometria
RodinaRegression modelRegression model
Rok vzniku2002–20051987
TvorcaKleibergen & Paap; VillaniRobert F. Engle and Clive W. J. Granger
TypBayesian multivariate time series modelMultivariate time-series model
Pôvodný zdrojKleibergen, F., & Paap, R. (2002). Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration. Journal of Econometrics, 111(2), 223–249. DOI ↗Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗
Ďalšie názvyBayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correctionVECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
Príbuzné55
ZhrnutieThe Bayesian VECM combines the classical Vector Error Correction Model — which captures both short-run dynamics and long-run cointegrating relationships among non-stationary multivariate time series — with Bayesian prior distributions over the cointegrating rank and coefficient matrices. This allows principled uncertainty quantification, incorporation of economic theory as priors, and coherent inference even in small samples.The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series.
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ScholarGatePorovnať metódy: Bayesian VECM · Vector Error Correction Model. Získané 2026-06-15 z https://scholargate.app/sk/compare