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Forecast Error Variance Decomposition (FEVD)×Impulsresponsfunktion (IRF)×
FagområdeØkonometriØkonometri
FamilieRegression modelRegression model
Oprindelsesår20052005
OphavspersonHelmut LütkepohlHelmut Lütkepohl
TypeMultivariate time series analysis toolPost-estimation diagnostic
Oprindelig kildeLütkepohl, 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. ISBN: 978-3-540-40172-8
AliasserVariance Decomposition, Error Variance Decomposition, VD Analysis, Varyans AyrıştırmasıIRF, Dynamic Multiplier, Shock Response Function, Etki Tepki Fonksiyonu
Relaterede33
ResuméForecast 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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ScholarGateSammenlign metoder: FEVD · Impulse Response Function. Hentet 2026-06-15 fra https://scholargate.app/da/compare