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Fourier-kvantiili-kvantiiliregressio×Fourier ARDL -rajatesti×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi2015-2020s2001-2021
KehittäjäExtension combining Sim & Zhou (2015) QQ regression with Fourier flexible-form smoothingPesaran, Shin & Smith (ARDL foundation); Fourier extension by Nazlioglu and related authors
TyyppiNonparametric quantile regression with Fourier smoothingCointegration / bounds test
AlkuperäislähdeSim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗Nazlioglu, S., Gormus, A., & Soytas, U. (2021). Oil prices and monetary policy in emerging markets: structural breaks, asymmetries, and Fourier approximations. Energy Economics, 95, 105119. link ↗
RinnakkaisnimetFourier QQ regression, Fourier-QQR, Fourier quantile regression with quantile regressors, smooth structural-break QQ regressionFourier ARDL, Fourier bounds testing, ARDL with Fourier approximation, F-ARDL cointegration test
Liittyvät65
TiivistelmäFourier 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 ARDL bounds test augments the Pesaran-Shin-Smith cointegration framework with trigonometric (Fourier) terms that capture gradual, smooth structural breaks in the data-generating process. It tests for a long-run level relationship between variables without requiring the researcher to specify the number, timing, or form of structural breaks in advance.
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ScholarGateVertaile menetelmiä: Fourier Quantile-on-Quantile Regression · Fourier ARDL Bounds Test. Haettu 2026-06-19 osoitteesta https://scholargate.app/fi/compare