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Nelineārais Johansena kointegrācijas tests×Nelineārais ARDL (NARDL) modelis×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads20012014
AutorsBreitung (2001), building on Johansen (1988, 1991)Shin, Yu & Greenwood-Nimmo
TipsNonparametric rank-based cointegration testNonlinear cointegration model
PirmavotsBreitung, J. (2001). Rank tests for nonlinear cointegration. Journal of Business and Economic Statistics, 19(3), 331-340. DOI ↗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. link ↗
Citi nosaukuminonlinear cointegration test, threshold Johansen cointegration, rank test for nonlinear cointegration, nonlinear VECM cointegrationNARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model
Saistītās35
KopsavilkumsNonlinear Johansen cointegration extends the classical Johansen framework to detect long-run equilibrium relationships among integrated time series when the adjustment process is nonlinear. Using rank-based transformations, the approach tests for cointegration without assuming a linear error-correction mechanism, making it suitable for economic relationships characterized by asymmetric or threshold dynamics.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.
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ScholarGateSalīdzināt metodes: Nonlinear Johansen Cointegration · Nonlinear ARDL. Izgūts 2026-06-18 no https://scholargate.app/lv/compare