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Fourierovská panelová analýza dat×Graniční test Fourier ARDL×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku2006 (Fourier framework); panel extensions 2010s2001-2021
TvůrceBecker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometriciansPesaran, Shin & Smith (ARDL foundation); Fourier extension by Nazlioglu and related authors
TypPanel regression with Fourier termsCointegration / bounds test
Původní zdrojBecker, R., Enders, W., & Lee, J. (2006). A stationary test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409. 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 ↗
Další názvyFourier panel regression, smooth structural break panel model, trigonometric panel data model, Fourier-flexible panel estimatorFourier ARDL, Fourier bounds testing, ARDL with Fourier approximation, F-ARDL cointegration test
Příbuzné65
ShrnutíFourier panel data analysis embeds trigonometric sine and cosine terms into a standard panel regression to approximate smooth, gradual structural shifts in the data-generating process. Rather than assuming a sharp break at a known date, the Fourier approach lets the data reveal the timing and shape of any structural change through a flexible trigonometric approximation, while retaining the cross-sectional and time-series structure of panel data.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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ScholarGatePorovnat metody: Fourier Panel Data Analysis · Fourier ARDL Bounds Test. Získáno 2026-06-18 z https://scholargate.app/cs/compare