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| Faktorelosztott Vektorautoregresszió (FAVAR)× | Küszöbértékű és sima átmenetű Vektor Autoregresszió (TVAR / STVAR)× | |
|---|---|---|
| Tudományterület | Ökonometria | Ökonometria |
| Módszercsalád | Regression model | Regression model |
| Keletkezés éve≠ | 2005 | 1998 |
| Megalkotó≠ | Bernanke, Boivin & Eliasz (2005); building on Stock & Watson diffusion indexes | Tsay (multivariate threshold modelling) |
| Típus≠ | Multivariate time-series model | Nonlinear multivariate time-series model |
| Alapmű≠ | Bernanke, B. S., Boivin, J. & Eliasz, P. (2005). Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach. The Quarterly Journal of Economics, 120(1), 387-422. DOI ↗ | Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202. DOI ↗ |
| Alternatív nevek≠ | factor-augmented VAR, FAVAR model, Faktör Artırımlı VAR (FAVAR) | TVAR, STVAR, regime-switching VAR, threshold VAR |
| Kapcsolódó≠ | 4 | 5 |
| Összefoglaló≠ | FAVAR is a multivariate time-series model that first compresses information from a very large set of variables into a few common factors, then includes those factors alongside the observed variables in a vector autoregression. It was introduced by Bernanke, Boivin and Eliasz in 2005 to study monetary policy using hundreds of macroeconomic indicators at once. | Threshold VAR and Smooth-Transition VAR are nonlinear multivariate time-series models in which the coefficients of a vector autoregression switch between regimes according to a threshold variable. Building on Tsay's 1998 treatment of multivariate threshold models, they capture different dynamic structures across phases such as the business cycle, financial crises, or policy differences. |
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