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Fourier kvantil-på-kvantil-regression×Fourier Granger-kausalitetstest×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår2015-2020s2016
UpphovspersonExtension combining Sim & Zhou (2015) QQ regression with Fourier flexible-form smoothingEnders and Jones
TypNonparametric quantile regression with Fourier smoothingCausality test
UrsprungskällaSim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗Enders, W., & Jones, P. (2016). Grain prices, oil prices, and multiple smooth breaks in a VAR. Studies in Nonlinear Dynamics and Econometrics, 20(4), 399–419. DOI ↗
AliasFourier QQ regression, Fourier-QQR, Fourier quantile regression with quantile regressors, smooth structural-break QQ regressionFourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causality
Närliggande66
SammanfattningFourier 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 Fourier Granger causality test extends the classic Granger causality framework by embedding low-frequency Fourier terms in the VAR equation, allowing the causal relationship to shift gradually over time without requiring the researcher to pre-specify the number or location of structural breaks.
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  3. PUBLISHED

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ScholarGateJämför metoder: Fourier Quantile-on-Quantile Regression · Fourier Granger Causality. Hämtad 2026-06-18 från https://scholargate.app/sv/compare