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Robust Vektor Autoregression (Robust VAR) Modell×Vektorautoregressionsmodell (VAR)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår1980s–2000s2005
UpphovspersonExtensions by Lutkepohl and others building on Sims (1980) VAR frameworkLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TypMultivariate time-series model with robust estimationMultivariate time-series model
UrsprungskällaGoncalves, S., & Kilian, L. (2004). Bootstrapping autoregressions with conditional heteroskedasticity of unknown form. Journal of Econometrics, 123(1), 89-120. DOI ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
Aliasrobust VAR, outlier-robust VAR, heavy-tailed VAR, RVARvector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Närliggande54
SammanfattningThe Robust VAR model extends the classical Vector Autoregression framework by replacing ordinary least squares estimation with robust estimators — such as M-estimators or median-based methods — to reduce the influence of outliers, structural breaks, and heavy-tailed shocks common in financial and macroeconomic time series.Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
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ScholarGateJämför metoder: Robust VAR model · VAR Model. Hämtad 2026-06-17 från https://scholargate.app/sv/compare