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| Model bayesowskiej strukturalnej autoregresji wektorowej (B-SVAR)× | Bayesowski wektorowy model korygowania błędem (Bayesian VECM)× | |
|---|---|---|
| Dziedzina | Ekonometria | Ekonometria |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 1998–2005 | 2002–2005 |
| Twórca≠ | Sims & Zha (1998); Uhlig (2005) for sign-restriction identification | Kleibergen & Paap; Villani |
| Typ≠ | Structural multivariate time-series model | Bayesian multivariate time series model |
| Źródło pierwotne≠ | Sims, C. A., & Zha, T. (1998). Bayesian methods for dynamic multivariate models. International Economic Review, 39(4), 949–968. DOI ↗ | Kleibergen, F., & Paap, R. (2002). Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration. Journal of Econometrics, 111(2), 223–249. DOI ↗ |
| Inne nazwy | Bayesian SVAR, B-SVAR, Bayesian structural VAR, Bayesian identified VAR | Bayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correction |
| Pokrewne≠ | 6 | 5 |
| Podsumowanie≠ | The Bayesian Structural Vector Autoregression model combines the structural identification of SVAR with Bayesian prior distributions over parameters. It estimates causal impulse responses between multiple time series while incorporating prior economic knowledge and producing full posterior uncertainty bands rather than point estimates alone. | The 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. |
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