Сравнение методов

	Нелинейная модель VAR	Модель нелинейной авторегрессии с распределенным лагом (NARDL)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1990s–2000s	2014
Автор метода	Tsay (1998); Krolzig (1997); Tong (1990) for threshold framework	Shin, Yu & Greenwood-Nimmo
Тип	Multivariate nonlinear time series model	Nonlinear cointegration model
Основополагающий источник	Tsay, R. S. (1998). Testing and modeling multivariate threshold models. Journal of the American Statistical Association, 93(443), 1188–1202.	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.
Другие названия	NLVAR, nonlinear vector autoregression, threshold VAR, TVAR	NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model
Связанные	4	5
Сводка	The Nonlinear VAR (NLVAR) model extends the standard vector autoregression by allowing the dynamic relationships among multiple time series to switch or change smoothly depending on an observed threshold variable, a latent regime state, or a smooth transition function. It is used when economic systems exhibit asymmetric responses, regime shifts, or state-dependent dynamics that a linear VAR cannot capture.	The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically.