Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study
Derek Bond (),
Michael J. Harrison () and
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Michael J. Harrison: Department of Economics, Trinity College
Economic Papers from Trinity College Dublin, Economics Department
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.
JEL-codes: C22 C52 E41 (search for similar items in EconPapers)
Pages: 34 pages
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mac
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Working Paper: Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:tcd:tcduee:tep20021
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