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Robustný model vektorovej autoregresie (Robust VAR)×Kvantilový VAR×
OdborEkonometriaEkonometria
RodinaRegression modelRegression model
Rok vzniku1980s–2000s2006
TvorcaExtensions by Lutkepohl and others building on Sims (1980) VAR frameworkKoenker and Xiao
TypMultivariate time-series model with robust estimationDistribution impulse response
Pôvodný zdrojGoncalves, S., & Kilian, L. (2004). Bootstrapping autoregressions with conditional heteroskedasticity of unknown form. Journal of Econometrics, 123(1), 89-120. DOI ↗Koenker, R., & Xiao, Z. (2006). Quantile autoregression. Journal of the American Statistical Association, 101(475), 980-990. DOI ↗
Ďalšie názvyrobust VAR, outlier-robust VAR, heavy-tailed VAR, RVARQuantile-based impulse response
Príbuzné53
ZhrnutieThe 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.Quantile VAR estimates impulse responses of multivariate systems conditional on different quantiles of the distribution, revealing how shocks propagate heterogeneously across the conditional distribution. Introduced by Koenker and Xiao (2006) and applied to risk measurement by White et al. (2015), it reveals tail behavior and contagion effects invisible to mean-based VAR analysis. This is essential for risk management and understanding how crises propagate differently than normal times.
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ScholarGatePorovnať metódy: Robust VAR model · Quantile VAR. Získané 2026-06-17 z https://scholargate.app/sk/compare