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| Regressione Quantile-su-Quantile di Fourier× | Regressione Quantile-su-Quantile per Dati Panel× | |
|---|---|---|
| Campo | Econometria | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 2015-2020s | 2015 (QQ); panel applications from ~2018 |
| Ideatore≠ | 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 |
| Tipo≠ | Nonparametric quantile regression with Fourier smoothing | Nonparametric quantile regression |
| Fonte seminale | 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 ↗ |
| Alias | 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 |
| Correlati | 6 | 6 |
| Sintesi≠ | 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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