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Regresión Cuantil-sobre-Cuantil de Fourier×Regresión Cuantil-sobre-Cuantil en Panel×
CampoEconometríaEconometría
FamiliaRegression modelRegression model
Año de origen2015-2020s2015 (QQ); panel applications from ~2018
Autor originalExtension combining Sim & Zhou (2015) QQ regression with Fourier flexible-form smoothingSim and Zhou (cross-section QQ); panel extension in applied energy/finance econometrics
TipoNonparametric quantile regression with Fourier smoothingNonparametric quantile regression
Fuente seminalSim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗
AliasFourier QQ regression, Fourier-QQR, Fourier quantile regression with quantile regressors, smooth structural-break QQ regressionPanel QQ regression, panel QQ approach, panel quantile-on-quantile approach, PQQ regression
Relacionados66
ResumenFourier quantile-on-quantile regression extends the quantile-on-quantile (QQ) framework of Sim and Zhou (2015) by embedding Fourier trigonometric terms into the local linear quantile model. This allows the estimated dependence between the quantiles of one variable and the quantiles of another to vary smoothly over time, capturing gradual structural change without imposing a known break date.Panel quantile-on-quantile (QQ) regression jointly maps any quantile of the outcome distribution onto any quantile of the predictor distribution across multiple cross-sectional units observed over time. It generalises Sim and Zhou's (2015) cross-sectional QQ framework to a panel setting, revealing a full dependence surface rather than a single average effect, while accounting for individual heterogeneity through fixed or random effects correction.
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ScholarGateComparar métodos: Fourier Quantile-on-Quantile Regression · Panel Quantile-on-Quantile Regression. Recuperado el 2026-06-18 de https://scholargate.app/es/compare