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Analiza danych panelowych Fouriera×Test przyczynowości Granger w wersji Fouriera×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania2006 (Fourier framework); panel extensions 2010s2016
TwórcaBecker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometriciansEnders and Jones
TypPanel regression with Fourier termsCausality test
Źródło pierwotneBecker, 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 ↗
Inne nazwyFourier 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
Pokrewne66
PodsumowanieFourier 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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ScholarGatePorównaj metody: Fourier Panel Data Analysis · Fourier Granger Causality. Pobrano 2026-06-17 z https://scholargate.app/pl/compare