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Model wpływu losowego Fouriera×Model efektów losowych ze zmiennymi w czasie parametrami×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania2006-20121970–1975
TwórcaBecker, Enders & Lee; Enders & LeeSwamy (1970); Hsiao (1975)
TypPanel regression with Fourier approximationPanel regression with time-varying random coefficients
Źródło pierwotneBecker, 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 ↗Swamy, P. A. V. B. (1970). Efficient inference in a random coefficient regression model. Econometrica, 38(2), 311–323. DOI ↗
Inne nazwyFourier RE model, FFF random effects, flexible Fourier random effects, Fourier augmented random effectsTVP-RE model, random coefficient random effects model, time-varying random effects, TVP panel random effects
Pokrewne55
PodsumowanieThe 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.
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ScholarGatePorównaj metody: Fourier Random Effects Model · Time-varying parameter random effects model. Pobrano 2026-06-17 z https://scholargate.app/pl/compare