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Kvantil-VAR×Vektorautoregressionsmodell (VAR)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår20062005
UpphovspersonKoenker and XiaoLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TypDistribution impulse responseMultivariate time-series model
UrsprungskällaKoenker, R., & Xiao, Z. (2006). Quantile autoregression. Journal of the American Statistical Association, 101(475), 980-990. DOI ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
AliasQuantile-based impulse responsevector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Närliggande34
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.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: Quantile VAR · VAR Model. Hämtad 2026-06-18 från https://scholargate.app/sv/compare