Bayesian analysis of a fractional cointegration model

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The concept of fractional cointegration, whereby deviations from an equilibrium relationship follow a fractionally integrated process, has attracted some attention of late. The extended concept allows cointegration to be associated with mean reversion in the error, rather than requiring the more stringent condition of stationarity. This paper presents a Bayesian method for conducting inference about fractional cointegration. The method is based on an approximation of the exact likelihood, with a Jeffreys prior being used to offset identification problems. Numerical results are produced via a combination of Markov chain Monte Carlo algorithms. The procedure is applied to several purchasing power parity relations, with substantial evidence found in favor of parity reversion.

Original languageEnglish
Pages (from-to)217-234
Number of pages18
JournalEconometric Reviews
Issue number2
Publication statusPublished - 2001


  • Bayesian inference
  • Fractional cointegration
  • Jeffreys prior
  • JEL Classification: C11; C32
  • Markov chain Monte Carlo

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