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Regresi Kuantil-atas-Kuantil Fourier×Model ARDL Taklinear (NARDL)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal2015-2020s2014
PengasasExtension combining Sim & Zhou (2015) QQ regression with Fourier flexible-form smoothingShin, Yu & Greenwood-Nimmo
JenisNonparametric quantile regression with Fourier smoothingNonlinear cointegration model
Sumber perintisSim, 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 ↗
AliasFourier QQ regression, Fourier-QQR, Fourier quantile regression with quantile regressors, smooth structural-break QQ regressionNARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model
Berkaitan65
RingkasanFourier 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.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.
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ScholarGateBandingkan kaedah: Fourier Quantile-on-Quantile Regression · Nonlinear ARDL. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare