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Bayesov vektorski model korekcije pogreške (Bayesian VECM)×Vektorski model korekcije pogreške (VECM)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka2002–20051987
TvoracKleibergen & Paap; VillaniRobert F. Engle and Clive W. J. Granger
VrstaBayesian multivariate time series modelMultivariate time-series model
Temeljni izvorKleibergen, 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 ↗
Drugi naziviBayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correctionVECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
Srodne55
SažetakThe 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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ScholarGateUsporedite metode: Bayesian VECM · Vector Error Correction Model. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare