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Modelul Autoregresiv cu Tranziție Lină (STAR)×Regresia cuantilică×
DomeniuEconometrieEconometrie
FamilieRegression modelRegression model
Anul apariției19941978
Autorul originalTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)Koenker & Bassett
TipNonlinear time-series regime-switching modelConditional quantile regression
Sursa seminalăTeräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Denumiri alternativesmooth transition autoregressive model, LSTAR, ESTAR, logistic STARconditional quantile regression, regression quantiles, Kantil Regresyon
Înrudite45
RezumatThe 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.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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ScholarGateCompară metode: STAR Model · Quantile Regression. Preluat la 2026-06-15 de pe https://scholargate.app/ro/compare