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Polynomial Cointegration between Stationary Processes with Long Memory

Author

Listed:
  • Marco Avarucci

    (SEFeMEQ, University of Rome “Tor Vergata”)

  • Domenico Marinucci

    (Department of Mathematics, University of Rome “Tor Vergata”)

Abstract
In this paper we consider polynomial cointegrating relationships between stationary processes with long range dependence. We express the regression functions in terms of Hermite polynomials and we 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," CEIS Research Paper 99, Tor Vergata University, CEIS.
    • Handle: RePEc:rtv:ceisrp:99
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    File URL: https://ceistorvergata.it/RePEc/rpaper/No-99.pdf
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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.

    More about this item

    Keywords

    Nonlinear cointegration; Long memory; Hermite polynomials; Spectral regression; Diagram formula.;
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