Sensitivity of GLS estimators in random effects models

Andrey Vasnev

Journal of Multivariate Analysis, 2010, vol. 101, issue 5, 1252-1262

Abstract: This paper studies the sensitivity of random effects estimators in the one-way error component regression model. Maddala and Mount (1973)Â [6] give simulation evidence that in random effects models the properties of the feasible GLS estimator are not affected by the choice of the first-step estimator used for the covariance matrix. Taylor (1980)Â [8] gives a theoretical example of this effect. This paper provides a reason for this in terms of sensitivity. The properties of are transferred via an uncorrelated (and independent under normality) link, called sensitivity. The sensitivity statistic counteracts the improvement in . A Monte Carlo experiment illustrates the theoretical findings.

Keywords: Panel; data; Sensitivity; analysis; Random; effects; model (search for similar items in EconPapers)
Date: 2010
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