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Smooth Transition Autoregressive (STAR) Model×Drempelregressie×
VakgebiedEconometrieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan19942000
GrondleggerTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)Bruce E. Hansen
TypeNonlinear time-series regime-switching modelNonlinear regime-switching regression
Oorspronkelijke bronTeräsvirta, 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 ↗
Aliassensmooth transition autoregressive model, LSTAR, ESTAR, logistic STARthreshold model, regime-switching regression, sample splitting model, Eşik Değer Regresyonu (Threshold Regression)
Verwant45
SamenvattingThe 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.
ScholarGateGegevensset
  1. v1
  2. 2 Bronnen
  3. PUBLISHED
  1. v1
  2. 1 Bronnen
  3. PUBLISHED

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ScholarGateMethoden vergelijken: STAR Model · Threshold Regression. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare