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Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

Dekompozimi i Variancës së Gabimit të Parashikimit (FEVD)×Funksioni i Përgjigjes ndaj Shokut (IRF)×Autorregresioni Vektor Struktural (SVAR)×
FushaEkonometriEkonometriEkonometri
FamiljaRegression modelRegression modelRegression model
Viti i origjinës200520051980
KrijuesiHelmut LütkepohlHelmut LütkepohlChristopher Sims
LlojiMultivariate time series analysis toolPost-estimation diagnosticStructural multivariate time-series model
Burimi themeluesLütkepohl, 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: 978-3-540-40172-8Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1–48. DOI ↗
Emërtime të tjeraVariance Decomposition, Error Variance Decomposition, VD Analysis, Varyans AyrıştırmasıIRF, Dynamic Multiplier, Shock Response Function, Etki Tepki FonksiyonuStructural VAR, Identified VAR, SVAR Model, Yapısal Vektör Otoregresyon
Të lidhura332
PërmbledhjaForecast 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.Structural Vector Autoregression (SVAR) is a multivariate time-series model, developed by Christopher Sims (1980), that extends the reduced-form VAR by imposing economically motivated identifying restrictions on contemporaneous relationships among variables. SVAR enables researchers to isolate orthogonal structural shocks and trace their causal dynamic effects through impulse response functions and forecast error variance decompositions, making it a cornerstone of modern empirical macroeconomics.
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ScholarGateKrahasoni metodat: FEVD · Impulse Response Function · SVAR. Marrë më 2026-06-17 nga https://scholargate.app/sq/compare