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Fourier-Paneldatenanalyse×Panel-Random-Effects-Modell×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr2006 (Fourier framework); panel extensions 2010s1966
UrheberBecker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometriciansBalestra & Nerlove
TypPanel regression with Fourier termsPanel data estimator
Wegweisende QuelleBecker, 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 ↗Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612. DOI ↗
AliasnamenFourier panel regression, smooth structural break panel model, trigonometric panel data model, Fourier-flexible panel estimatorrandom effects estimator, RE model, GLS random effects, error components model
Verwandt65
ZusammenfassungFourier 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 panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation.
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ScholarGateMethoden vergleichen: Fourier Panel Data Analysis · Panel Random Effects Model. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare