ScholarGate
Assistent

Jämför metoder

Granska de valda metoderna sida vid sida; rader som skiljer sig är markerade.

Kvantil-VAR×Kvantil-ARDL×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår20062006
UpphovspersonKoenker and XiaoRoger Koenker and Zhijie Xiao
TypDistribution impulse responseConditional distribution model
UrsprungskällaKoenker, 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 ↗
AliasQuantile-based impulse responseQuantile ARDL
Närliggande33
SammanfattningQuantile 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.
ScholarGateDatamängd
  1. v1
  2. 2 Källor
  3. PUBLISHED
  1. v1
  2. 2 Källor
  3. PUBLISHED

Gå till sökningen Ladda ner bildspel

ScholarGateJämför metoder: Quantile VAR · QARDL. Hämtad 2026-06-18 från https://scholargate.app/sv/compare