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Nelinearni model autororegresivnih distribuiranih odmakâ (NARDL)×Model glatke prijelazne autoregresije (STAR)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka20141994
TvoracShin, Yu & Greenwood-NimmoTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
VrstaAsymmetric cointegration / error-correction modelNonlinear time-series regime-switching model
Temeljni izvorShin, Y., Yu, B. & Greenwood-Nimmo, M. (2014). Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework. In: Sickles, R. & Horrace, W. (Eds.), Festschrift in Honor of Peter Schmidt. Springer. DOI ↗Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗
Drugi nazivinonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL)smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Srodne44
SažetakThe NARDL model, introduced by Shin, Yu and Greenwood-Nimmo in 2014, extends the ARDL framework to capture asymmetric long-run and short-run relationships, testing whether positive and negative changes in a regressor affect the dependent variable differently.The Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations.
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ScholarGateUsporedite metode: NARDL Model · STAR Model. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare