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Model slučajnih efekata sa Furijeovim transformacijama×Model slučajnih efekata sa strukturnim prekidima×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka2006-20121998–2000s
TvoracBecker, Enders & Lee; Enders & LeeBai & Perron (break detection); Baltagi (panel RE framework)
TipPanel regression with Fourier approximationPanel regression with regime shifts
Temeljni izvorBecker, 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 ↗Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗
Drugi naziviFourier RE model, FFF random effects, flexible Fourier random effects, Fourier augmented random effectsRE model with structural breaks, break-adjusted random effects, random effects break model, panel RE with regime shifts
Srodne55
SažetakThe 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 structural break random effects model extends standard panel RE estimation by allowing one or more breakpoints at which slope coefficients or error variances shift across time. It combines structural change detection (e.g., Bai-Perron) with the GLS-based random effects estimator, producing regime-specific parameter estimates while retaining the efficiency gains of pooling individual-level variation as random draws from a common distribution.
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ScholarGateUporedite metode: Fourier Random Effects Model · Structural Break Random Effects Model. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare