Comparer des méthodes

	Modèle à effets aléatoires de Fourier	Modèle à Effets Aléatoires et Paramètres Variables dans le Temps
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	2006-2012	1970–1975
Auteur d'origine	Becker, Enders & Lee; Enders & Lee	Swamy (1970); Hsiao (1975)
Type	Panel regression with Fourier approximation	Panel regression with time-varying random coefficients
Source fondatrice	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.	Swamy, P. A. V. B. (1970). Efficient inference in a random coefficient regression model. Econometrica, 38(2), 311–323.
Alias	Fourier RE model, FFF random effects, flexible Fourier random effects, Fourier augmented random effects	TVP-RE model, random coefficient random effects model, time-varying random effects, TVP panel random effects
Apparentées	5	5
Résumé	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.	The time-varying parameter random effects model extends the classic random effects panel framework by allowing regression coefficients to change over time and across units. Rather than imposing a single fixed slope for all individuals and periods, each coefficient is treated as a random draw that evolves, capturing genuine parameter instability while preserving the random effects assumption that unit-specific components are uncorrelated with the regressors.