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Nonlinear Persistence and Copersistence

In: Nonlinear Financial Econometrics: Markov Switching Models, Persistence and Nonlinear Cointegration

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  • Christian Gourieroux
  • Joann Jasiak

Abstract

Theoretical research on long-term relationships between economic time series has a history that spans several decades during which various linear and nonlinear comovements were unveiled, such as the Phillips curve, and the purchasing power parity. In contrast, the econometric analysis of long-term relationships is much more recent, and has been conducted mainly in the linear framework. This is the case of the cointegration theory for nonstationary time series (see Granger, 1986; Engle and Granger, 1987; Johansen, 1998), and the codependence theory for stationary series (Gourieroux and Peaucelle, 1992; Engle and Kozicki, 1993; Kugler and Neusser, 1993). Under both approaches, the dynamics of the time series of interest (i.e. VAR model) as well as their long-term relationships are assumed to be linear.

Suggested Citation

  • Christian Gourieroux & Joann Jasiak, 2011. "Nonlinear Persistence and Copersistence," Palgrave Macmillan Books, in: Greg N. Gregoriou & Razvan Pascalau (ed.), Nonlinear Financial Econometrics: Markov Switching Models, Persistence and Nonlinear Cointegration, chapter 4, pages 77-103, Palgrave Macmillan.
    • Handle: RePEc:pal:palchp:978-0-230-29521-6_4
    DOI: 10.1057/9780230295216_4
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    References listed on IDEAS

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    2. Darolles, Serge & Florens, Jean-Pierre & Gourieroux, Christian, 2004. "Kernel-based nonlinear canonical analysis and time reversibility," Journal of Econometrics, Elsevier, vol. 119(2), pages 323-353, April.

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    More about this item

    Keywords

    Gaussian Process; Canonical Correlation; Hermite Polynomial; Nonlinear Transformation; Canonical Decomposition;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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