Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Панельна квантиль-на-квантиль регресія× | Регресія квантиль-на-квантиль (QQ)× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2015 (QQ); panel applications from ~2018 | 2015 |
| Автор методу≠ | Sim and Zhou (cross-section QQ); panel extension in applied energy/finance econometrics | Sim and Zhou |
| Тип | Nonparametric quantile regression | Nonparametric quantile regression |
| Основоположне джерело | 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 ↗ | 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 назви | Panel QQ regression, panel QQ approach, panel quantile-on-quantile approach, PQQ regression | QQ regression, QQ approach, quantile-on-quantile approach, nonparametric quantile regression |
| Пов'язані | 6 | 6 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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