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Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study

Listed author(s):
  • Bond, Derek

    (University of Ulster)

  • Harrison, Michael J

    (Trinity College Dublin)

  • O’Brien, Edward J.

    (Central Bank and Financial Services Authority of Ireland)

This paper draws attention to the limitations of the standard unit root/cointegration approach to economic and financial modelling, and to some of the alternatives based on the idea of fractional integration, long memory models, and the random field regression approach to nonlinearity. Following brief explanations of fractional integration and random field regression, and the methods of applying them, selected techniques are applied to a demand for money dataset. Comparisons of the results from this illustrative case study are presented, and conclusions are drawn that should aid practitioners in applied time-series econometrics.

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File URL: http://www.centralbank.ie/publications/documents/2RT06.pdf
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Paper provided by Central Bank of Ireland in its series Research Technical Papers with number 2/RT/06.

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Length: 35 pages
Date of creation: Apr 2006
Handle: RePEc:cbi:wpaper:2/rt/06
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