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Bayesian analysis of long memory and persistence using ARFIMA models

Author

Listed:
  • KOOP, G.
  • LEY, E.
  • OSIEWALSKI, J.
  • STEEL, M. F. J.

Abstract

This paper provides a Bayesian analysis of Autoregressive Fractionally Integrated Moving Average (ARFIMA) models. We discuss in detail inference on impulse responses, and show how Bayesian methods can be used to (i) test ARFIMA models against ARIMA alternatives, and (ii) take model uncertainty into account when making inferences on quantities of interest. Our methods are then used to investigate the persistence properties of real U.S. GNP.
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Suggested Citation

  • Koop, G. & Ley, E. & Osiewalski, J. & Steel, M. F. J., 1997. "Bayesian analysis of long memory and persistence using ARFIMA models," LIDAM Reprints CORE 1246, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvrp:1246
    DOI: 10.1016/0304-4076(95)01787-9
    Note: In : Journal of Econometrics, 76, 149-169, 1997
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    References listed on IDEAS

    as
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    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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