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Furjē nelineārā ARDL (Fourier NARDL)×Vektora kļūdu labojuma modelis (VECM)×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads2014–2020s1987
AutorsExtension of Shin, Yu & Greenwood-Nimmo (2014) NARDL, incorporating Fourier terms from Becker, Enders & Lee (2006)Robert F. Engle and Clive W. J. Granger
TipsNonlinear cointegrating model with smooth break approximationMultivariate time-series model
PirmavotsShin, 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 ↗Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗
Citi nosaukumiFourier NARDL, Fourier nonlinear ARDL, F-NARDL, Fourier asymmetric ARDLVECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
Saistītās65
KopsavilkumsFourier 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 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.
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ScholarGateSalīdzināt metodes: Fourier NARDL · Vector Error Correction Model. Izgūts 2026-06-15 no https://scholargate.app/lv/compare