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A Note on an Iterative Least Squares Estimation Method for ARMA and VARMA Models

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  • George Kapetanios

    () (Queen Mary, University of London)

Abstract

In this note we suggest a new iterative least squares method for estimating scalar and vector ARMA models. A Monte Carlo study shows that the method has better small sample properties than existing least squares methods and compares favourably with maximum likelihood estimation as well.

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File URL: http://www.econ.qmul.ac.uk/papers/doc/wp467.pdf
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Bibliographic Info

Paper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 467.

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Date of creation: Nov 2002
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Handle: RePEc:qmw:qmwecw:wp467

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Related research

Keywords: ARMA models;

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  1. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711.
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Cited by:
  1. Christian Kascha & Karel Mertens, 2008. "Business cycle analysis and VARMA models," Working Paper 2008/05, Norges Bank.
  2. Christian Kascha, 2007. "A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models," Economics Working Papers ECO2007/12, European University Institute.

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