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Polynomial Cointegration Between Stationary Processes With Long Memory

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  • Marco Avarucci
  • Domenico Marinucci

Abstract

. In this article we consider polynomial cointegrating relationships between stationary processes with long range dependence. We express the regression functions in terms of Hermite polynomials and consider a form of spectral regression around frequency zero. For these estimates, we establish consistency by means of a more general result on continuously averaged estimates of the spectral density matrix at frequency zero.

Suggested Citation

  • Marco Avarucci & Domenico Marinucci, 2007. "Polynomial Cointegration Between Stationary Processes With Long Memory," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(6), pages 923-942, November.
    • Handle: RePEc:bla:jtsera:v:28:y:2007:i:6:p:923-942
    DOI: 10.1111/j.1467-9892.2007.00540.x
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    Cited by:

    1. Luis A. Gil-Alana & Christophe André & Rangan Gupta & Tsangyao Chang & Omid Ranjbar, 2016. "The Feldstein--Horioka puzzle in South Africa: A fractional cointegration approach," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 25(7), pages 978-991, October.
    2. Niels Haldrup & Robinson Kruse, 2014. "Discriminating between fractional integration and spurious long memory," CREATES Research Papers 2014-19, Department of Economics and Business Economics, Aarhus University.

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