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

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  • Derek Bond

    ()
    (University of Ulster)

  • Michael J. Harrison

    ()
    (Department of Economics, Trinity College)

  • Edward J. O'Brien

    ()
    (Department of Economics, Trinity College and Central Bank of Ireland)

Abstract

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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Bibliographic Info

Paper provided by Trinity College Dublin, Department of Economics in its series Trinity Economics Papers with number tep20021.

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Length: 34 pages
Date of creation: Oct 2005
Date of revision:
Handle: RePEc:tcd:tcduee:tep20021

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