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This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by extension, forecasting depends on numerical methods for simulating from the posterior distribution of the parameters and special attention is given to the implementation of the...
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In this paper, we develop novel Markov chain Monte Carlo sampling methodology for Bayesian Cointegrated Vector Auto Regression (CVAR) models. Here we focus on two novel exten sions to the sampling methodology for the CVAR posterior distribution. The first extension we develop replaces the...
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cointegrations. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues …. In this paper we develop a new time varying parameter model which permits cointegration. We use a specification which …
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