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Bayesian Unit Root Testing: The Effect Of Choice Of Prior On Test Outcomes

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  • Charley Xia and William Griffiths

Abstract

A Monte Carlo experiment is used to examine the size and power properties of alternative Bayesian tests for unit roots. Four different prior distributions for the root that is potentially unity – a uniform prior and priors attributable to Jeffreys, Lubrano, and Berger and Yang – are used in conjunction with two testing procedures: a credible interval test and a Bayes factor test. Two extensions are also considered: a test based on model averaging with different priors and a test with a hierarchical prior for a hyperparameter. The tests are applied to both trending and non-trending series. Our results favor the use of a prior suggested by Lubrano. Outcomes from applying the tests to some Australian macroeconomic time series are presented.

Suggested Citation

  • Charley Xia and William Griffiths, 2012. "Bayesian Unit Root Testing: The Effect Of Choice Of Prior On Test Outcomes," Department of Economics - Working Papers Series 1152, The University of Melbourne.
    • Handle: RePEc:mlb:wpaper:1152
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    References listed on IDEAS

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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.
    2. Xuedong Wu & Jeffrey H. Dorfman & Berna Karali, 2018. "The impact of data frequency on market efficiency tests of commodity futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(6), pages 696-714, June.

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