Comparar métodos

	Análisis de Datos de Panel con Transformada de Fourier	Modelo de efectos aleatorios para datos de panel
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	2006 (Fourier framework); panel extensions 2010s	1966
Autor original	Becker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometricians	Balestra & Nerlove
Tipo	Panel regression with Fourier terms	Panel data estimator
Fuente seminal	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.	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.
Alias	Fourier panel regression, smooth structural break panel model, trigonometric panel data model, Fourier-flexible panel estimator	random effects estimator, RE model, GLS random effects, error components model
Relacionados	6	5
Resumen	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.	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.