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Reģresijas kvantiļu uz kvantiļu panelī×Kvantiļu-uz-kvantiļu (QQ) regresija×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads2015 (QQ); panel applications from ~20182015
AutorsSim and Zhou (cross-section QQ); panel extension in applied energy/finance econometricsSim and Zhou
TipsNonparametric quantile regressionNonparametric quantile regression
PirmavotsSim, 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 ↗
Citi nosaukumiPanel QQ regression, panel QQ approach, panel quantile-on-quantile approach, PQQ regressionQQ regression, QQ approach, quantile-on-quantile approach, nonparametric quantile regression
Saistītās66
KopsavilkumsPanel 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.
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ScholarGateSalīdzināt metodes: Panel Quantile-on-Quantile Regression · Quantile-on-Quantile Regression. Izgūts 2026-06-18 no https://scholargate.app/lv/compare