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Model slučajnih učinaka sa strukturnim promjenama×Model panel podataka s nasumičnim učincima×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka1998–2000s1966
TvoracBai & Perron (break detection); Baltagi (panel RE framework)Balestra & Nerlove
VrstaPanel regression with regime shiftsPanel data estimator
Temeljni izvorBai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗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. DOI ↗
Drugi naziviRE model with structural breaks, break-adjusted random effects, random effects break model, panel RE with regime shiftsrandom effects estimator, RE model, GLS random effects, error components model
Srodne55
SažetakThe 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.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.
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ScholarGateUsporedite metode: Structural Break Random Effects Model · Panel Random Effects Model. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare