Comparer des méthodes

	Régression Quantile-sur-Quantile sur Données de Panel	Régression quantile-quantile (QQ)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	2015 (QQ); panel applications from ~2018	2015
Auteur d'origine	Sim and Zhou (cross-section QQ); panel extension in applied energy/finance econometrics	Sim and Zhou
Type	Nonparametric quantile regression	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	Panel QQ regression, panel QQ approach, panel quantile-on-quantile approach, PQQ regression	QQ regression, QQ approach, quantile-on-quantile approach, nonparametric quantile regression
Apparentées	6	6
Résumé	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.	Quantile-on-quantile regression is a nonparametric technique that estimates how the quantiles of one variable depend on the quantiles of another. By combining standard quantile regression with local linear smoothing, it produces a full two-dimensional surface of slope coefficients indexed by both the quantile of the outcome and the quantile of the predictor, revealing heterogeneous and asymmetric dependency structures invisible to standard regression.