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Bayesowski wektorowy model korygowania błędem (Bayesian VECM)×Wektorowa Autoregresja Strukturalna (SVAR)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania2002–20051980
TwórcaKleibergen & Paap; VillaniSims (1980); identification schemes by Blanchard & Quah (1989)
TypBayesian multivariate time series modelMultivariate time series model
Źródło pierwotneKleibergen, F., & Paap, R. (2002). Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration. Journal of Econometrics, 111(2), 223–249. DOI ↗Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673. link ↗
Inne nazwyBayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correctionSVAR, structural vector autoregression, identified VAR, structural VAR model
Pokrewne55
PodsumowanieThe 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.Structural VAR extends the reduced-form VAR by imposing economic theory-based restrictions that identify orthogonal structural shocks. This allows researchers to disentangle the causal effects of distinct economic disturbances — such as supply versus demand shocks — and trace their dynamic propagation through a system of variables via impulse response functions and forecast error variance decompositions.
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  1. v1
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  3. PUBLISHED

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ScholarGatePorównaj metody: Bayesian VECM · Structural VAR. Pobrano 2026-06-15 z https://scholargate.app/pl/compare