Comparer des méthodes

	Modèle VAR non linéaire	Modèle ARDL non linéaire (NARDL)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1990s–2000s	2014
Auteur d'origine	Tsay (1998); Krolzig (1997); Tong (1990) for threshold framework	Shin, Yu & Greenwood-Nimmo
Type	Multivariate nonlinear time series model	Nonlinear cointegration model
Source fondatrice	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.
Alias	NLVAR, nonlinear vector autoregression, threshold VAR, TVAR	NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model
Apparentées	4	5
Résumé	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.