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Linganisha mbinu

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Mchoro wa Marekebisho ya Hitilafu ya Vekta wa Bayesian (Bayesian VECM)×Urejeshaji wa Vekta wa Kimuundo (SVAR)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili2002–20051980
MwanzilishiKleibergen & Paap; VillaniSims (1980); identification schemes by Blanchard & Quah (1989)
AinaBayesian multivariate time series modelMultivariate time series model
Chanzo asiliaKleibergen, 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 ↗
Majina mbadalaBayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correctionSVAR, structural vector autoregression, identified VAR, structural VAR model
Zinazohusiana55
MuhtasariThe 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.
ScholarGateSeti ya data
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  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Bayesian VECM · Structural VAR. Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/compare