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Kvantilni VAR (Quantile VAR)×QARDL (Quantile Autoregressive Distributed Lag)×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka20062006
TvoracKoenker and XiaoRoger Koenker and Zhijie Xiao
TipDistribution impulse responseConditional distribution model
Temeljni izvorKoenker, R., & Xiao, Z. (2006). Quantile autoregression. Journal of the American Statistical Association, 101(475), 980-990. DOI ↗Koenker, R., & Xiao, Z. (2006). Quantile autoregression. Journal of the American Statistical Association, 101(475), 980-990. DOI ↗
Drugi naziviQuantile-based impulse responseQuantile ARDL
Srodne33
SažetakQuantile 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.QARDL (Quantile Autoregressive Distributed Lag) combines quantile regression with ARDL modeling to estimate conditional relationships at different points of the distribution, revealing heterogeneous short-run and long-run effects. Introduced by Koenker and Xiao (2006) and refined by Cho et al. (2015), it captures how the effect of explanatory variables on outcomes varies across quantiles, essential for understanding tail behavior and distributional impacts rather than just mean effects.
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ScholarGateUporedite metode: Quantile VAR · QARDL. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare