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| Regressió Quantil-sobre-Quantil amb Paràmetres que Varien en el Temps (TVP-QQ)× | Regressió quantílica× | |
|---|---|---|
| Camp | Econometria | Econometria |
| Família | Regression model | Regression model |
| Any d'origen≠ | 2015–2019 | 1978 |
| Autor original≠ | Extension of Sim & Zhou (2015) QQ framework; TVP adaptation by subsequent applied econometricians | Koenker & Bassett |
| Tipus≠ | Nonparametric time-varying quantile regression | Conditional quantile regression |
| Font seminal≠ | Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking & Finance, 55, 1–8. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| Àlies≠ | TVP-QQ regression, time-varying QQ regression, dynamic quantile-on-quantile regression, TVP quantile-on-quantile | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Relacionats≠ | 2 | 5 |
| Resum≠ | TVP-QQ regression extends the quantile-on-quantile (QQ) framework by allowing the slope coefficients to evolve over time. It maps how the quantiles of a predictor variable affect the quantiles of an outcome differently across the joint distribution and across different time periods, uncovering dynamic, heterogeneous dependence structures that standard regression cannot detect. | Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails. |
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