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Decomposição da Variância do Erro de Previsão (FEVD)×Função de Resposta a Impulso (IRF)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem20052005
Autor originalHelmut LütkepohlHelmut Lütkepohl
TipoMultivariate time series analysis toolPost-estimation diagnostic
Fonte seminalLütkepohl, 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
Outros nomesVariance Decomposition, Error Variance Decomposition, VD Analysis, Varyans AyrıştırmasıIRF, Dynamic Multiplier, Shock Response Function, Etki Tepki Fonksiyonu
Relacionados33
ResumoForecast 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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ScholarGateComparar métodos: FEVD · Impulse Response Function. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare