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Bayesian Unit Root Test in Nonnormal AR(1) Model

Author

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  • Hikaru Hasegawa
  • Anoop Chaturvedi
  • Tran Van Hoa

Abstract

In this paper, we approximate the distribution of disturbances by the Edgeworth series distribution and propose a Bayesian analysis in a nonnormal AR(1) model. We derive the posterior distribution of the autocorrelation and the posterior odds ratio for unit roots hypothesis in the AR(1) model when the first four cumulants of the Edgeworth series distribution are finite and the higher order cumulants are negligible. We also apply the posterior analysis to eight real exchange rates and investigate whether these exchange rates behave like a random walk or not.

Suggested Citation

  • Hikaru Hasegawa & Anoop Chaturvedi & Tran Van Hoa, 2000. "Bayesian Unit Root Test in Nonnormal AR(1) Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 21(3), pages 261-280, May.
    • Handle: RePEc:bla:jtsera:v:21:y:2000:i:3:p:261-280
    DOI: 10.1111/1467-9892.00185
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    Cited by:

    1. Magris Martin & Iosifidis Alexandros, 2021. "Approximate Bayes factors for unit root testing," Papers 2102.10048, arXiv.org, revised Feb 2021.

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