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Two-stage non Gaussian QML estimation of GARCH models and testing the efficiency of the Gaussian QMLE

  • Francq, Christian
  • Lepage, Guillaume
  • Zakoïan, Jean-Michel

In generalized autoregressive conditional heteroskedastic (GARCH) models, the standard identifiability assumption that the variance of the iid process is equal to 1 can be replaced by an alternative moment assumption. We show that, for estimating the original specification based on the standard identifiability assumption, efficiency gains can be expected from using a quasi-maximum likelihood (QML) estimator based on a non Gaussian density and a reparameterization based on an alternative identifiability assumption. A test allowing to determine whether a reparameterization is needed, that is, whether the more efficient QMLE is obtained with a non Gaussian density, is proposed.

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File URL: http://www.sciencedirect.com/science/article/pii/S030440761100159X
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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 165 (2011)
Issue (Month): 2 ()
Pages: 246-257

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Handle: RePEc:eee:econom:v:165:y:2011:i:2:p:246-257
DOI: 10.1016/j.jeconom.2011.08.001
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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