विधियों की तुलना करें

	Robust Random Effects Model	पैनल सामान्यीकृत न्यूनतम वर्ग (पैनल GLS)
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1980s–2000s	1935 / developed for panels 1980s–1990s
प्रवर्तक	Wooldridge; White (sandwich covariance); Arellano	Aitken (1935); extended to panel data by Baltagi and others
प्रकार	Panel GLS estimator with robust inference	Generalized linear regression
मौलिक स्रोत	Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586	Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586
उपनाम	robust RE model, sandwich random effects estimator, cluster-robust random effects, GLS-robust RE	Panel GLS, Generalized Least Squares for panel data, FGLS panel, feasible GLS panel
संबंधित	5	3
सारांश	The Robust Random Effects model estimates panel data relationships using the GLS random effects estimator while replacing the conventional standard errors with sandwich (heteroscedasticity- and cluster-robust) variance estimates. This protects inference against arbitrary within-group correlation and heteroscedasticity without discarding the efficiency gains of random effects when unit-specific effects are genuinely uncorrelated with the regressors.	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.