@techreport{oai:grips.repo.nii.ac.jp:00000983,
 author = {KOOP, Gary and LEON-GONZALEZ, Roberto and STRACHAN, Rodney W.},
 note = {https://www.grips.ac.jp/list/jp/facultyinfo/leon_gonzalez_roberto/, 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 speci<br />cation 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., JEL Classification Codes: C11, C32, C33, 経済学 / Economics},
 title = {Bayesian Inference in the Time Varying Cointegration Model}
}