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| Байесов модел на структурен векторна авторегресия (B-SVAR)× | Векторна авторегресия (VAR)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1998–2005 | 1980 |
| Създател≠ | Sims & Zha (1998); Uhlig (2005) for sign-restriction identification | Christopher A. Sims |
| Тип≠ | Structural multivariate time-series model | Multivariate time-series model |
| Основополагащ източник≠ | Sims, C. A., & Zha, T. (1998). Bayesian methods for dynamic multivariate models. International Economic Review, 39(4), 949–968. DOI ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Други названия | Bayesian SVAR, B-SVAR, Bayesian structural VAR, Bayesian identified VAR | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Свързани≠ | 6 | 5 |
| Резюме≠ | 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. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
| ScholarGateНабор от данни ↗ |
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