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Fourier Nonlinear ARDL (Fourier NARDL)×Model NARDL (Nonlinear Autoregressive Distributed Lag)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania2014–2020s2014
TwórcaExtension of Shin, Yu & Greenwood-Nimmo (2014) NARDL, incorporating Fourier terms from Becker, Enders & Lee (2006)Shin, Yu & Greenwood-Nimmo
TypNonlinear cointegrating model with smooth break approximationNonlinear cointegration model
Źródło pierwotneShin, 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 (pp. 281–314). Springer. link ↗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 ↗
Inne nazwyFourier NARDL, Fourier nonlinear ARDL, F-NARDL, Fourier asymmetric ARDLNARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model
Pokrewne65
PodsumowanieFourier NARDL extends the Nonlinear ARDL (NARDL) bounds-testing framework by adding Fourier trigonometric terms to the error-correction equation, allowing the model to capture smooth, gradual structural breaks in the long-run relationship without requiring the researcher to know or specify the break date in advance.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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  1. v1
  2. 2 Źródła
  3. PUBLISHED

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ScholarGatePorównaj metody: Fourier NARDL · Nonlinear ARDL. Pobrano 2026-06-18 z https://scholargate.app/pl/compare