Сравнение методов

	Модель нелинейной авторегрессии с распределенным лагом (NARDL)	Модель коррекции ошибок вектора (VECM)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	2014	1987
Автор метода	Shin, Yu & Greenwood-Nimmo	Robert F. Engle and Clive W. J. Granger
Тип	Nonlinear cointegration model	Multivariate time-series model
Основополагающий источник	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.	Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276.
Другие названия	NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model	VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
Связанные	5	5
Сводка	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.	The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series.