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Model d'Autoregressió Distribuïda No Lineal (NARDL)×Model de Transició Suau Autorregressiu (STAR)×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen20141994
Autor originalShin, Yu & Greenwood-NimmoTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
TipusAsymmetric cointegration / error-correction modelNonlinear time-series regime-switching model
Font seminalShin, 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 ↗
Àliesnonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL)smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Relacionats44
ResumThe 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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ScholarGateCompara mètodes: NARDL Model · STAR Model. Recuperat el 2026-06-15 de https://scholargate.app/ca/compare