Comparar métodos

	Regresión Cuantílica	Modelo Autorregresivo de Transición Suave (STAR)
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	1978	1994
Autor original	Koenker & Bassett	Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
Tipo	Conditional quantile regression	Nonlinear time-series regime-switching model
Fuente seminal	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.	Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218.
Alias	conditional quantile regression, regression quantiles, Kantil Regresyon	smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Relacionados	5	4
Resumen	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.	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.