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Impulsresponsfunksjon (IRF)×Prognosefeilvariansdekomponering (FEVD)×
FagfeltØkonometriØkonometri
FamilieRegression modelRegression model
Opprinnelsesår20052005
OpphavspersonHelmut LütkepohlHelmut Lütkepohl
TypePost-estimation diagnosticMultivariate time series analysis tool
Opprinnelig 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
AliasIRF, Dynamic Multiplier, Shock Response Function, Etki Tepki FonksiyonuVariance Decomposition, Error Variance Decomposition, VD Analysis, Varyans Ayrıştırması
Relaterte33
SammendragThe 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.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.
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ScholarGateSammenlign metoder: Impulse Response Function · FEVD. Hentet 2026-06-15 fra https://scholargate.app/no/compare