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

Derek Bond, Michael J. Harrison () and Edward O'Brien
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Michael J. Harrison: Department of Economics, Trinity College

Economic Papers from Trinity College Dublin, Economics Department

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.

JEL-codes: C22 C52 E41 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2005-10
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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http://www.tcd.ie/Economics/TEP/2005_papers/TEP21.pdf

Related works:
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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