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Regresión Cuantil-sobre-Cuantil con Parámetros Variables en el Tiempo (TVP-QQ)×Regresión Cuantílica×
CampoEconometríaEconometría
FamiliaRegression modelRegression model
Año de origen2015–20191978
Autor originalExtension of Sim & Zhou (2015) QQ framework; TVP adaptation by subsequent applied econometriciansKoenker & Bassett
TipoNonparametric time-varying quantile regressionConditional quantile regression
Fuente seminalSim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking & Finance, 55, 1–8. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
AliasTVP-QQ regression, time-varying QQ regression, dynamic quantile-on-quantile regression, TVP quantile-on-quantileconditional quantile regression, regression quantiles, Kantil Regresyon
Relacionados25
ResumenTVP-QQ regression extends the quantile-on-quantile (QQ) framework by allowing the slope coefficients to evolve over time. It maps how the quantiles of a predictor variable affect the quantiles of an outcome differently across the joint distribution and across different time periods, uncovering dynamic, heterogeneous dependence structures that standard regression cannot detect.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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ScholarGateComparar métodos: Time-varying parameter quantile-on-quantile regression · Quantile Regression. Recuperado el 2026-06-17 de https://scholargate.app/es/compare