Comparer des méthodes

	VAR quantiles	Modèle de Vector Autoregression (VAR)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	2006	2005
Auteur d'origine	Koenker and Xiao	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
Type	Distribution impulse response	Multivariate time-series model
Source fondatrice	Koenker, R., & Xiao, Z. (2006). Quantile autoregression. Journal of the American Statistical Association, 101(475), 980-990.	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
Alias	Quantile-based impulse response	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Apparentées	3	4
Résumé	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.	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).