Comparar métodos

	Análisis de Datos de Panel con Transformada de Fourier	Prueba de Causalidad de Granger de Fourier
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	2006 (Fourier framework); panel extensions 2010s	2016
Autor original	Becker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometricians	Enders and Jones
Tipo	Panel regression with Fourier terms	Causality test
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.	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.
Alias	Fourier panel regression, smooth structural break panel model, trigonometric panel data model, Fourier-flexible panel estimator	Fourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causality
Relacionados	6	6
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 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.