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On relative efficiency of Quasi-MLE and GMM estimators of covariance structure models

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Artem Prokhorov (Concordia University)

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Abstract

Optimal GMM is known to dominate Gaussian QMLE in terms of asymptotic efficiency (Chamberlain, 1984). I derive a new condition under which QMLE is as efficient as GMM for a general class of covariance structure models. The condition trivially holds for normal data but also identifies non-normal cases for which Gaussian QMLE is efficient.

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Paper provided by Concordia University, Department of Economics in its series Working Papers with number 08004.

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Date of creation: May 2008
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Handle: RePEc:crd:wpaper:08004

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