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预测误差方差分解 (FEVD)

预测误差方差分解 (FEVD) 是一种多变量时间序列技术,用于向量自回归 (VAR) 框架内,以量化系统中每个变量的预测误差方差中有多少比例可归因于来自其他变量的冲击。它被计量经济学家、宏观经济学家和金融研究人员广泛用于评估不同结构性扰动在驱动相互关联的经济系列短期和长期波动中的相对重要性。

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来源

  1. Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. ISBN: 978-3-540-40172-8

如何引用本页

ScholarGate. (2026, June 2). Forecast Error Variance Decomposition (FEVD). ScholarGate. https://scholargate.app/zh/econometrics/forecast-error-variance-decomposition

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被引用于

ScholarGateFEVD (Forecast Error Variance Decomposition (FEVD)). 于 2026-06-15 检索自 https://scholargate.app/zh/econometrics/forecast-error-variance-decomposition · 数据集: https://doi.org/10.5281/zenodo.20539026