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Prognoosivea dekompositsioon (FEVD)×Impulssvastuse funktsioon (IRF)×
ValdkondÖkonomeetriaÖkonomeetria
PerekondRegression modelRegression model
Tekkeaasta20052005
LoojaHelmut LütkepohlHelmut Lütkepohl
TüüpMultivariate time series analysis toolPost-estimation diagnostic
AlgallikasLütkepohl, 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
RööpnimetusedVariance Decomposition, Error Variance Decomposition, VD Analysis, Varyans AyrıştırmasıIRF, Dynamic Multiplier, Shock Response Function, Etki Tepki Fonksiyonu
Seotud33
KokkuvõteForecast 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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ScholarGateVõrdle meetodeid: FEVD · Impulse Response Function. Loetud 2026-06-15 aadressilt https://scholargate.app/et/compare