Methoden vergelijken

	Fourier Random Effects Model	Fourier Panel Data Analysis
Vakgebied	Econometrie	Econometrie
Familie	Regression model	Regression model
Jaar van ontstaan	2006-2012	2006 (Fourier framework); panel extensions 2010s
Grondlegger	Becker, Enders & Lee; Enders & Lee	Becker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometricians
Type	Panel regression with Fourier approximation	Panel regression with Fourier terms
Oorspronkelijke bron	Becker, 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.	Becker, 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.
Aliassen	Fourier RE model, FFF random effects, flexible Fourier random effects, Fourier augmented random effects	Fourier panel regression, smooth structural break panel model, trigonometric panel data model, Fourier-flexible panel estimator
Verwant	5	6
Samenvatting	The Fourier Random Effects Model extends the standard random effects panel estimator by incorporating trigonometric (Fourier) terms to approximate smooth, gradual structural change in time trends or intercepts. It retains the GLS efficiency advantages of the random effects estimator while allowing parameters to shift continuously over time without requiring knowledge of exact break dates.	Fourier 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.