Bayesian Inference in the Time Varying Cointegration Model

Gary Koop, Roberto Leon-Gonzalez and Rodney Strachan

No 2008-60, SIRE Discussion Papers from Scottish Institute for Research in Economics (SIRE)

Abstract: There are both theoretical and empirical reasons for believing that the parameters 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 cointegration. 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.

Keywords: Bayesian; time varying cointegration; error correctionmodel; reduced rank regression; Markov Chain Monte Carlo (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Bayesian inference in a time varying cointegration model (2011)
Working Paper: Bayesian Inference in a Time Varying Cointegration Model (2011)
Working Paper: Bayesian Inference in the Time Varying Cointegration Model* (2011)
Working Paper: Bayesian Inference in the Time Varying Cointegration Model (2008)
Working Paper: Bayesian Inference in the Time Varying Cointegration Model (2008)
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