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Smooth Transition Autoregressive (STAR) modell×Tröskelregression×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår19942000
UpphovspersonTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)Bruce E. Hansen
TypNonlinear time-series regime-switching modelNonlinear regime-switching regression
UrsprungskällaTeräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗Hansen, B. E. (2000). Sample Splitting and Threshold Estimation. Econometrica, 68(3), 575-603. DOI ↗
Aliassmooth transition autoregressive model, LSTAR, ESTAR, logistic STARthreshold model, regime-switching regression, sample splitting model, Eşik Değer Regresyonu (Threshold Regression)
Närliggande45
SammanfattningThe 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.Threshold regression is a nonlinear, regime-switching model in which the regression parameters take different values above and below an estimated threshold value of a threshold variable. The sample-splitting and threshold-estimation framework was developed by Bruce E. Hansen (2000) and is widely used for time-series and panel data with structural breaks and regime-dependent relationships.
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ScholarGateJämför metoder: STAR Model · Threshold Regression. Hämtad 2026-06-18 från https://scholargate.app/sv/compare