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Fourier Panel Data Analysis×Fourier Granger-kausalitetstest×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår2006 (Fourier framework); panel extensions 2010s2016
UpphovspersonBecker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometriciansEnders and Jones
TypPanel regression with Fourier termsCausality test
UrsprungskällaBecker, 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 ↗
AliasFourier 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
Närliggande66
SammanfattningFourier 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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ScholarGateJämför metoder: Fourier Panel Data Analysis · Fourier Granger Causality. Hämtad 2026-06-17 från https://scholargate.app/sv/compare