Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Regresia Cuantile-pe-Cuantile Fourier× | Regresia Panel Quantilă-pe-Quantilă× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 2015-2020s | 2015 (QQ); panel applications from ~2018 |
| Autorul original≠ | 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 |
| Tip≠ | Nonparametric quantile regression with Fourier smoothing | Nonparametric quantile regression |
| Sursa seminală | 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 ↗ |
| Denumiri alternative | 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 |
| Înrudite | 6 | 6 |
| Rezumat≠ | 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. |
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