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Simple GMM Estimation of the Semi-Strong GARCH(1,1) Model

  • Todd, Prono

Efficient GMM estimation of the semi-strong GARCH(1,1) model requires simultaneous estimation of the conditional third and fourth moments. This paper proposes a simple alternative to efficient GMM based upon the unconditional skewness of residuals and the autocovariances of squared residuals. An advantage of this simple alternative is that neither the third nor the fourth conditional moment needs to be estimated. A second advantage is that linear estimators apply to all of the parameters in the model, making estimation straightforward in practice. The proposed estimators are IV-like with potentially many instruments. Sequential estimation involves TSLS in a first step followed by linear GMM. Simultaneous estimation involves either two-step GMM or CUE. A Monte Carlo study of the proposed estimators is included.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 20034.

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Date of creation: Jan 2010
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Handle: RePEc:pra:mprapa:20034
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