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Regresia Cuantile-pe-Cuantile Fourier×Testul de cointegrare ARDL cu termeni Fourier×
DomeniuEconometrieEconometrie
FamilieRegression modelRegression model
Anul apariției2015-2020s2001-2021
Autorul originalExtension combining Sim & Zhou (2015) QQ regression with Fourier flexible-form smoothingPesaran, Shin & Smith (ARDL foundation); Fourier extension by Nazlioglu and related authors
TipNonparametric quantile regression with Fourier smoothingCointegration / bounds test
Sursa seminalăSim, 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 ↗
Denumiri alternativeFourier 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
Înrudite65
RezumatFourier 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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  3. PUBLISHED

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ScholarGateCompară metode: Fourier Quantile-on-Quantile Regression · Fourier ARDL Bounds Test. Preluat la 2026-06-19 de pe https://scholargate.app/ro/compare