방법 비교

	Quantile VAR	Vector Autoregression (VAR) Model
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	2006	2005
창시자	Koenker and Xiao	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
유형	Distribution impulse response	Multivariate time-series model
원전	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.
별칭	Quantile-based impulse response	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
관련	3	4
요약	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).