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Testing for Neglected Nonlinearity in Long Memory Models

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  • George Kapetanios

    ()
    (Queen Mary, University of London)

Abstract

Interest in the interface of nonstationarity and nonlinearity has been increasing in the econometric literature. The motivation for this development maybe be traced to the perceived possibility that processes following nonlinear models maybe mistakenly taken to be unit root or long-memory nonstationary. This paper considers the possibility that processes may exhibit both long memory and nonlinearity. We test against the possibility that the process u t in the model (1-L) dy t�=�u t is nonlinear. We do not assume a particular parametric form for the nonlinear process but construct a pure significance test. Clearly, such a test could be straightforwardly constructed if d were known. Unfortunately, if a linear model is assumed while estimating d the power of the test will be reduced. We propose new more powerful tests for this problem. We present Monte Carlo evidence on the performance of the new tests and apply them to Yen real exchange rates.

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Bibliographic Info

Paper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 473.

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Date of creation: Nov 2002
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Handle: RePEc:qmw:qmwecw:wp473

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Related research

Keywords: Long memory; Nonlinearity; Neural networks; Real exchange rates.;

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References

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  1. Andrew P. Blake & George Kapetanios, 2003. "A radial basis function artificial neural network test for neglected nonlinearity," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 357-373, December.
  2. Davidson, James & Sibbertsen, Philipp, 2005. "Generating schemes for long memory processes: regimes, aggregation and linearity," Journal of Econometrics, Elsevier, vol. 128(2), pages 253-282, October.
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Citations

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Cited by:
  1. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2012. "Quantile regression for long memory testing: A case of realized volatility," Working Papers w201207, Banco de Portugal, Economics and Research Department.
  2. Richard T. Baille & Claudio Morana, 2009. "Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach," ICER Working Papers - Applied Mathematics Series 06-2009, ICER - International Centre for Economic Research.
  3. Ulrike Busch & Dieter Nautz, 2009. "Controllability and Persistence of Money Market Rates along the Yield Curve: Evidence from the Euro Area," SFB 649 Discussion Papers SFB649DP2009-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  4. Kuswanto, Heri & Sibbertsen, Philipp, 2009. "Testing for Long Memory Against ESTAR Nonlinearities," Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Leibniz Universität Hannover dp-427, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  5. Smallwood, Aaron D., 2008. "Measuring the persistence of deviations from purchasing power parity with a fractionally integrated STAR model," Journal of International Money and Finance, Elsevier, vol. 27(7), pages 1161-1176, November.
  6. Aaron Smallwood, 2004. "Joint Tests for Long Memory and Non-linearity: The Case of Purchasing Power Parity," Computing in Economics and Finance 2004 23, Society for Computational Economics.
  7. S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.

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