Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Байесовская регрессия «квантиль по квантилю»× | Модель нелинейной авторегрессии с распределенным лагом (NARDL)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2015–2019 | 2014 |
| Автор метода≠ | Bayesian QQ framework combines Sim & Zhou (2015) QQ regression with Bayesian quantile regression (Yu & Moyeed, 2001) | Shin, Yu & Greenwood-Nimmo |
| Тип≠ | Nonparametric quantile regression with Bayesian estimation | Nonlinear cointegration model |
| Основополагающий источник≠ | 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 ↗ | Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281–314). Springer. link ↗ |
| Другие названия | Bayesian QQR, Bayesian QQ regression, Bayes quantile-on-quantile, BQQ regression | NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Bayesian Quantile-on-Quantile (BQQ) Regression extends the Sim-Zhou quantile-on-quantile framework by replacing frequentist local linear estimation with Bayesian posterior inference. For each pair of quantiles (theta of the outcome, tau of the predictor), the method yields a full posterior distribution over the slope, enabling uncertainty quantification across the entire bivariate quantile surface — a key advantage when sample sizes are moderate and tail quantiles are sparse. | The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically. |
| ScholarGateНабор данных ↗ |
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