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Estimating the long memory granger causality effect with a spectrum estimator

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  • Wen-Den Chen

    (Tung Hai University, Taiwan)

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    Abstract

    This paper discusses the Granger causality test by a spectrum estimator which allows the transfer function to have long memory properties. In traditional methodology the relationship among variables is usually assumed to be short memory or contemporaneous. Hence, we have to make sure they are of the same integrated order, else there might be a spurious regression problem. In practice, not all the variables are fractionally co-integrated in the economic model. They may have the same random resources, but under a different integrated order. This paper focuses on how to capture the long memory Granger causality effect in the transfer function. This does not necessarily assume the variables are of the same fractional integrated order. Moreover, by the transfer function we construct an estimator to test the long memory effect with the Granger causality sense. Copyright © 2006 John Wiley & Sons, Ltd.

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    File URL: http://hdl.handle.net/10.1002/for.981
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    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

    Volume (Year): 25 (2006)
    Issue (Month): 3 ()
    Pages: 193-200

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    Handle: RePEc:jof:jforec:v:25:y:2006:i:3:p:193-200

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    Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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    Cited by:
    1. Claudio Morana, 2007. "On the macroeconomic causes of exchange rates volatility," ICER Working Papers 8-2007, ICER - International Centre for Economic Research.
    2. Li, Yushu, 2012. "Estimating Long Memory Causality Relationships by a Wavelet Method," Working Papers 2012:15, Lund University, Department of Economics.

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