Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Dekompozice rozptylu chyby predikce (FEVD)× | Impulse Response Function (IRF)× | |
|---|---|---|
| Obor | Ekonometrie | Ekonometrie |
| Rodina | Regression model | Regression model |
| Rok vzniku | 2005 | 2005 |
| Tvůrce | Helmut Lütkepohl | Helmut Lütkepohl |
| Typ≠ | Multivariate time series analysis tool | Post-estimation diagnostic |
| Původní zdroj | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. ISBN: 978-3-540-40172-8 | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. ISBN: 978-3-540-40172-8 |
| Další názvy | Variance Decomposition, Error Variance Decomposition, VD Analysis, Varyans Ayrıştırması | IRF, Dynamic Multiplier, Shock Response Function, Etki Tepki Fonksiyonu |
| Příbuzné | 3 | 3 |
| Shrnutí≠ | Forecast Error Variance Decomposition (FEVD) is a multivariate time series technique used within Vector Autoregression (VAR) frameworks to quantify what proportion of the forecast error variance of each variable is attributable to shocks from every other variable in the system. It is widely used by econometricians, macroeconomists, and financial researchers to assess the relative importance of different structural disturbances in driving short-run and long-run fluctuations across interconnected economic series. | The Impulse Response Function (IRF) traces the dynamic response of each variable in a Vector Autoregression (VAR) system to a one-unit shock in one of its error terms over a user-specified forecast horizon. It is the primary tool for structural analysis following VAR estimation and is widely used in macroeconomics, monetary economics, and finance to quantify how shocks propagate through interconnected time series systems. |
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