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A unified framework for testing in the linear regression model under unknown order of fractional integration

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  • Bent Jesper Christensen

    ()
    (Aarhus University and CREATES)

  • Robinson Kruse

    ()
    (Leibniz University Hannover and CREATES)

  • Philipp Sibbertsen

    ()
    (Leibniz University Hannover)

Abstract

We consider hypothesis testing in a general linear time series regression framework when the possibly fractional order of integration of the error term is unknown. We show that the approach suggested by Vogelsang (1998a) for the case of integer integration does not apply to the case of fractional integration. We propose a Lagrange Multiplier-type test whose limiting distribution is independent of the order of integration of the errors. Different testing scenarios for the case of deterministic and stochastic regressors are considered. Simulations demonstrate that the proposed test works well for a variety of different cases, thereby emphasizing its generality.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2013-35.

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Length: 33
Date of creation: 05 2013
Date of revision:
Handle: RePEc:aah:create:2013-35

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Web page: http://www.econ.au.dk/afn/

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Keywords: Long memory; linear time series regression; Lagrange Multiplier test;

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  2. James Davidson & Nigar Hashimzade, 2007. "Representation and Weak Convergence of Stochastic Integrals with Fractional Integrator Processes," CREATES Research Papers 2007-45, School of Economics and Management, University of Aarhus.
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  18. Juan J. Dolado & Francesc Marmol, 2004. "Asymptotic inference results for multivariate long-memory processes," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 168-190, 06.
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