方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 预测误差方差分解 (FEVD)× | 脉冲响应函数 (IRF)× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份 | 2005 | 2005 |
| 提出者 | Helmut Lütkepohl | Helmut Lütkepohl |
| 类型≠ | Multivariate time series analysis tool | Post-estimation diagnostic |
| 开创性文献 | 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 |
| 别名 | Variance Decomposition, Error Variance Decomposition, VD Analysis, Varyans Ayrıştırması | IRF, Dynamic Multiplier, Shock Response Function, Etki Tepki Fonksiyonu |
| 相关 | 3 | 3 |
| 摘要≠ | 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. |
| ScholarGate数据集 ↗ |
|
|