Linganisha mbinu

	Mfumo wa ARDL Usiohusisha Mstari (NARDL)	Kielelezo cha Usahihishaji wa Hitilafu wa Kielekezi (VECM)
Nyanja	Ekonometriki	Ekonometriki
Familia	Regression model	Regression model
Mwaka wa asili	2014	1987
Mwanzilishi	Shin, Yu & Greenwood-Nimmo	Robert F. Engle and Clive W. J. Granger
Aina	Nonlinear cointegration model	Multivariate time-series model
Chanzo asilia	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.
Majina mbadala	NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model	VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
Zinazohusiana	5	5
Muhtasari	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.