Bayesian Inference in the Time Varying Cointegration Model
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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- 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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