Comparer des méthodes

	Régression Quantile-sur-Quantile de Fourier	Régression Quantile-sur-Quantile sur Données de Panel
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	2015-2020s	2015 (QQ); panel applications from ~2018
Auteur d'origine	Extension combining Sim & Zhou (2015) QQ regression with Fourier flexible-form smoothing	Sim and Zhou (cross-section QQ); panel extension in applied energy/finance econometrics
Type	Nonparametric quantile regression with Fourier smoothing	Nonparametric quantile regression
Source fondatrice	Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8.	Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8.
Alias	Fourier QQ regression, Fourier-QQR, Fourier quantile regression with quantile regressors, smooth structural-break QQ regression	Panel QQ regression, panel QQ approach, panel quantile-on-quantile approach, PQQ regression
Apparentées	6	6
Résumé	Fourier 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.