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Mittelineaarne autokorrelatsiooniga ja hajutatud viitajaga (NARDL) mudel×STAR-mudel (Smooth Transition Autoregressive Model)×
ValdkondÖkonomeetriaÖkonomeetria
PerekondRegression modelRegression model
Tekkeaasta20141994
LoojaShin, Yu & Greenwood-NimmoTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
TüüpAsymmetric cointegration / error-correction modelNonlinear time-series regime-switching model
AlgallikasShin, 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 ↗
Rööpnimetusednonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL)smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Seotud44
KokkuvõteThe 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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ScholarGateVõrdle meetodeid: NARDL Model · STAR Model. Loetud 2026-06-17 aadressilt https://scholargate.app/et/compare