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Панельна квантиль-на-квантиль регресія×Регресія квантиль-на-квантиль (QQ)×
ГалузьЕконометрикаЕконометрика
РодинаRegression modelRegression model
Рік появи2015 (QQ); panel applications from ~20182015
Автор методуSim and Zhou (cross-section QQ); panel extension in applied energy/finance econometricsSim and Zhou
ТипNonparametric quantile regressionNonparametric quantile regression
Основоположне джерелоSim, 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 ↗
Інші назвиPanel QQ regression, panel QQ approach, panel quantile-on-quantile approach, PQQ regressionQQ regression, QQ approach, quantile-on-quantile approach, nonparametric quantile regression
Пов'язані66
ПідсумокPanel 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.
ScholarGateНабір даних
  1. v1
  2. 2 Джерела
  3. PUBLISHED
  1. v1
  2. 2 Джерела
  3. PUBLISHED

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ScholarGateПорівняння методів: Panel Quantile-on-Quantile Regression · Quantile-on-Quantile Regression. Отримано 2026-06-18 з https://scholargate.app/uk/compare