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Fractional Integration and Business Cycles Features

Author

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  • Luis A. Gil-Alana

    (School of Economics and Business Administration, University of Navarra)

  • Bertrand Candelon

Abstract

We show in this article that fractionally integrated univariate models for GDP may lead to a better replication of business cycle characteristics. We firstly show that the business cycle features are clearly affected by the degree of integration as well as by the other short run components of the series. Then, we model the real GDP in France, the UK and the US by means of fractionally ARIMA (ARFIMA) models, and show that the three time series can be specified in terms of this type of models with orders of integration higher than one but smaller than two. Comparing the ARFIMA specifications with those based on ARIMA models, we show via simulations that the former better describes the business cycles features of the data at least for the cases of the UK and the US.

Suggested Citation

  • Luis A. Gil-Alana & Bertrand Candelon, 2004. "Fractional Integration and Business Cycles Features," Faculty Working Papers 09/04, School of Economics and Business Administration, University of Navarra.
    • Handle: RePEc:una:unccee:wp0904
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    References listed on IDEAS

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    Cited by:

    1. Guglielmo Maria Caporale & Juncal Cuñado & Luis A. Gil-Alana, 2013. "Modelling long-run trends and cycles in financial time series data," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 405-421, May.
    2. L.A. Gil-Alanaa, 2007. "Testing The Existence of Multiple Cycles in Financial and Economic Time Series," Annals of Economics and Finance, Society for AEF, vol. 8(1), pages 1-20, May.
    3. Guglielmo Maria Caporale & Luis Gil‐Alana, 2014. "Long‐Run and Cyclical Dynamics in the US Stock Market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(2), pages 147-161, March.
    4. Roger Bowden & Jennifer Zhu, 2010. "Multi-scale variation, path risk and long-term portfolio management," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 783-796.
    5. Guglielmo Caporale & Luis Gil-Alana, 2006. "Long memory at the long run and at the cyclical frequencies: modelling real wages in England, 1260–1994," Empirical Economics, Springer, vol. 31(1), pages 83-93, March.
    6. Ekaterini Panopoulou & Nikitas Pittis & Sarantis Kalyvitis, 2010. "Looking far in the past: revisiting the growth-returns nexus with non-parametric tests," Empirical Economics, Springer, vol. 38(3), pages 743-766, June.
    7. L.A. Gil-Alana, 2005. "Fractional Cyclical Structures & Business Cycles in the Specification of the US Real Output," European Research Studies Journal, European Research Studies Journal, vol. 0(1-2), pages 99-126.
    8. Artiach, Miguel, 2012. "Leverage, skewness and amplitude asymmetric cycles," MPRA Paper 41267, University Library of Munich, Germany.

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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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