방법 비교

	비선형 자기회귀 분산 시차 모형 (NARDL)	Vector Autoregression (VAR) Model
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	2014	2005
창시자	Shin, Yu, and Greenwood-Nimmo	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
유형	Nonlinear cointegration model	Multivariate time-series model
원전	Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281-314). Springer.	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
별칭	NARDL, nonlinear ARDL, asymmetric ARDL, nonlinear bounds test	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
관련	4	4
요약	The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing an explanatory variable into its positive and negative partial sums, it tests whether increases and decreases in a regressor have different effects on the dependent variable — a feature that linear cointegration methods cannot capture.	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).