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Model nelineární autoregresní distribuované zpoždění (NARDL)×Model hladkého přechodu autoregresní (STAR)×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku20141994
TvůrceShin, Yu & Greenwood-NimmoTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
TypAsymmetric cointegration / error-correction modelNonlinear time-series regime-switching model
Původní zdrojShin, 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 ↗
Další názvynonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL)smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Příbuzné44
ShrnutíThe 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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ScholarGatePorovnat metody: NARDL Model · STAR Model. Získáno 2026-06-15 z https://scholargate.app/cs/compare