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Modelo de Defasagem Autorregressiva Não Linear Distribuída (NARDL)×Modelo Autorregressivo de Transição Suave (STAR)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem20141994
Autor originalShin, Yu & Greenwood-NimmoTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
TipoAsymmetric cointegration / error-correction modelNonlinear time-series regime-switching model
Fonte 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 ↗
Outros nomesnonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL)smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Relacionados44
ResumoThe 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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ScholarGateComparar métodos: NARDL Model · STAR Model. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare