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GLS Bias Correction for Low Order ARMA models

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Author Info

  • Patrick Richard

    ()
    (GREDI, Département d'économique, Université de Sherbrooke)

Abstract

We study the problems of bias correction in the estimation of low order ARMA(p, q) time series models. We introduce a new method to estimate the bias of the parameters of ARMA(p, q) process based on the analytical form of the GLS transformation matrix of Galbraith and Zinde-Walsh (1992). We show that the resulting bias corrected estimator is consistent and asymptotically normal. We also argue that, in the case of an MA(q) model, our method may be considered as an iteration of the analytical indirect inference technique of Galbraith and Zinde-Walsh (1994). The potential of our method is illustrated through a series of Monte Carlo experiments.

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File URL: http://gredi.recherche.usherbrooke.ca/wpapers/GREDI-0719.pdf
File Function: First version, 2007
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Bibliographic Info

Paper provided by Departement d'Economique de la Faculte d'administration à l'Universite de Sherbrooke in its series Cahiers de recherche with number 07-19.

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Length: 34 pages
Date of creation: 2007
Date of revision:
Handle: RePEc:shr:wpaper:07-19

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Postal: Sherbrooke, Québec, J1K 2R1
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Web page: http://www.gredi.org/home/documents-de-travail
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Related research

Keywords: ARMA; bias correction; GLS;

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Cited by:
  1. Patrick Richard, 2009. "Improving the accuracy of the analytical indirect inference estimator for MA models," Economics Bulletin, AccessEcon, vol. 29(4), pages 2795-2802.

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