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滑らかな遷移自己回帰(STAR)モデル×パネルベクトル自己回帰(Panel VAR)×分位点回帰×
分野計量経済学計量経済学計量経済学
系統Regression modelRegression modelRegression model
提唱年199419881978
提唱者Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)Holtz-Eakin, Newey & RosenKoenker & Bassett
種類Nonlinear time-series regime-switching modelPanel vector autoregressionConditional quantile regression
原典Teräsvirta, 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 ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
別名smooth transition autoregressive model, LSTAR, ESTAR, logistic STARPVAR, panel vector autoregression, Panel VAR (PVAR)conditional quantile regression, regression quantiles, Kantil Regresyon
関連435
概要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.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.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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ScholarGate手法を比較: STAR Model · Panel VAR · Quantile Regression. 2026-06-18に以下より取得 https://scholargate.app/ja/compare