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Panelowy model efektów losowych×Uogólniona metoda najmniejszych kwadratów dla danych panelowych (Panel GLS)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania19661935 / developed for panels 1980s–1990s
TwórcaBalestra & NerloveAitken (1935); extended to panel data by Baltagi and others
TypPanel data estimatorGeneralized linear regression
Źródło pierwotneBalestra, 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 ↗Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586
Inne nazwyrandom effects estimator, RE model, GLS random effects, error components modelPanel GLS, Generalized Least Squares for panel data, FGLS panel, feasible GLS panel
Pokrewne53
PodsumowanieThe 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.Panel GLS is a regression method for longitudinal data that explicitly models the non-spherical error structure — heteroscedasticity across units and serial correlation within units — to recover efficient coefficient estimates. Unlike OLS, it weights observations by the inverse of the error covariance matrix, yielding the Best Linear Unbiased Estimator when the error structure is correctly specified.
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ScholarGatePorównaj metody: Panel Random Effects Model · Panel GLS. Pobrano 2026-06-15 z https://scholargate.app/pl/compare