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Paneļa vispārinātā mazāko kvadrātu metode (Panel GLS)×Robustā OLS (OLS ar robustām standarta kļūdām)×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads1935 / developed for panels 1980s–1990s1980
AutorsAitken (1935); extended to panel data by Baltagi and othersHalbert White
TipsGeneralized linear regressionLinear regression with robust inference
PirmavotsWooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. DOI ↗
Citi nosaukumiPanel GLS, Generalized Least Squares for panel data, FGLS panel, feasible GLS panelHC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errors
Saistītās36
KopsavilkumsPanel 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.Robust OLS applies ordinary least squares to estimate coefficients and then replaces the classical standard errors with heteroscedasticity-consistent (HC) standard errors — commonly called White standard errors. This leaves the point estimates unchanged while yielding valid t-statistics and confidence intervals even when the error variance is not constant across observations.
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ScholarGateSalīdzināt metodes: Panel GLS · Robust OLS. Izgūts 2026-06-19 no https://scholargate.app/lv/compare