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Fourier Kvantil-på-Kvantil Regression×Fourier ARDL Bounds Test×
FagområdeØkonometriØkonometri
FamilieRegression modelRegression model
Oprindelsesår2015-2020s2001-2021
OphavspersonExtension combining Sim & Zhou (2015) QQ regression with Fourier flexible-form smoothingPesaran, Shin & Smith (ARDL foundation); Fourier extension by Nazlioglu and related authors
TypeNonparametric quantile regression with Fourier smoothingCointegration / bounds test
Oprindelig kildeSim, 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 ↗
AliasserFourier 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
Relaterede65
ResuméFourier 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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ScholarGateSammenlign metoder: Fourier Quantile-on-Quantile Regression · Fourier ARDL Bounds Test. Hentet 2026-06-19 fra https://scholargate.app/da/compare