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Modèle autorégressif à transition lisse (STAR)×Autorégression Vectorielle sur Données de Panel (Panel VAR)×
DomaineÉconométrieÉconométrie
FamilleRegression modelRegression model
Année d'origine19941988
Auteur d'origineTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)Holtz-Eakin, Newey & Rosen
TypeNonlinear time-series regime-switching modelPanel vector autoregression
Source fondatriceTeräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗Holtz-Eakin, D., Newey, W. & Rosen, H. S. (1988). Estimating Vector Autoregressions with Panel Data. Econometrica, 56(6), 1371-1395. DOI ↗
Aliassmooth transition autoregressive model, LSTAR, ESTAR, logistic STARPVAR, panel vector autoregression, Panel VAR (PVAR)
Apparentées43
RésuméThe 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.Panel VAR extends the vector autoregression model to panel data, modelling the dynamic interactions among several variables while controlling for cross-unit heterogeneity through fixed effects. It was introduced by Holtz-Eakin, Newey and Rosen in 1988 and produces impulse-response functions and variance decompositions at the panel level.
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  1. v1
  2. 2 Sources
  3. PUBLISHED

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ScholarGateComparer des méthodes: STAR Model · Panel VAR. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare