विधियों की तुलना करें

	पूर्वानुमान त्रुटि प्रसरण अपघटन (FEVD)	आवेग अनुक्रिया फलन (IRF)
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	2005	2005
प्रवर्तक	Helmut Lütkepohl	Helmut Lütkepohl
प्रकार	Multivariate time series analysis tool	Post-estimation diagnostic
मौलिक स्रोत	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. ISBN: 978-3-540-40172-8	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. ISBN: 978-3-540-40172-8
उपनाम	Variance Decomposition, Error Variance Decomposition, VD Analysis, Varyans Ayrıştırması	IRF, Dynamic Multiplier, Shock Response Function, Etki Tepki Fonksiyonu
संबंधित	3	3
सारांश	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.	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.