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Uchanganuzi wa Utengamano wa Makosa ya Utabiri (FEVD)×Muundo wa Uhusiano wa Kiotomatiki wa Vecta (VAR)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili20052005
MwanzilishiHelmut LütkepohlLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
AinaMultivariate time series analysis toolMultivariate time-series model
Chanzo asiliaLütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. ISBN: 978-3-540-40172-8Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
Majina mbadalaVariance Decomposition, Error Variance Decomposition, VD Analysis, Varyans Ayrıştırmasıvector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Zinazohusiana34
MuhtasariForecast 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.Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
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ScholarGateLinganisha mbinu: FEVD · VAR Model. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare