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Bayesian analysis of periodic unit roots in the presence of a break

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  • Alexander Vosseler
  • Enzo Weber

Abstract

A Bayesian testing approach for a periodic unit root in quarterly and monthly data is presented. Further a Bayesian test is introduced to test for unit roots at (non)seasonal spectral frequencies. All procedures admit one structural break in the periodic trend function, where the occurrence of a break and the associated timing are treated as additional model parameters. A Bayesian model averaging (BMA) approach is proposed and power functions of the tests are computed. Overall the results indicate that the BMA periodic unit root test exhibits favourable test properties even in small samples. In an empirical application the presented testing procedures are used to test for (non)seasonal forms of unemployment persistence among OECD countries.

Suggested Citation

  • Alexander Vosseler & Enzo Weber, 2017. "Bayesian analysis of periodic unit roots in the presence of a break," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3841-3862, August.
  • Handle: RePEc:taf:applec:v:49:y:2017:i:38:p:3841-3862
    DOI: 10.1080/00036846.2016.1270415
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    References listed on IDEAS

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    Cited by:

    1. Alexander Vosseler & Enzo Weber, 2018. "Forecasting seasonal time series data: a Bayesian model averaging approach," Computational Statistics, Springer, vol. 33(4), pages 1733-1765, December.

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