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Fourier-paneeliaineiston analyysi×Fourier Granger -kausaatiotesti×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi2006 (Fourier framework); panel extensions 2010s2016
KehittäjäBecker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometriciansEnders and Jones
TyyppiPanel regression with Fourier termsCausality test
AlkuperäislähdeBecker, 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 ↗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 ↗
RinnakkaisnimetFourier panel regression, smooth structural break panel model, trigonometric panel data model, Fourier-flexible panel estimatorFourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causality
Liittyvät66
TiivistelmäFourier 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 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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ScholarGateVertaile menetelmiä: Fourier Panel Data Analysis · Fourier Granger Causality. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare