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Bayesian Inference in the Time Varying Cointegration Model

  • Gary Koop

    (University of Strathclyde)

  • Roberto Leon Gonzalez

    (National Graduate Institute for Policy Studies)

  • Rodney W. Strachan


    (School of Economics, University of Queensland)

There are both theoretical and empirical reasons for believing that the pa- rameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit coin- tegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.

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Paper provided by National Graduate Institute for Policy Studies in its series GRIPS Discussion Papers with number 08-01.

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Length: 48 pages
Date of creation: May 2008
Date of revision:
Handle: RePEc:ngi:dpaper:08-01
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  1. Centoni, Marco & Cubadda, Gianluca, 2003. "Measuring the business cycle effects of permanent and transitory shocks in cointegrated time series," Economics Letters, Elsevier, vol. 80(1), pages 45-51, July.
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