Bayesian Multivariate Time Series Methods for Empirical Macroecomics provides a survey of the Bayesian methods used in modern empirical macroecomics. These models have been developed to address the fact that most questions of interest to empirical macroecomists involve several variables and must be addressed using multivariate time series methods. Many different multivariate time series models have been used in macroecomics, but Vector Autoregressive (VAR) models have been among the most popular. Bayesian Multivariate Time Series Methods for Empirical Macroecomics reviews and extends the Bayesian literature on VARs, TVP-VARs and TVP-FAVARs with a focus on the practitioner. The authors go beyond simply defining each model, but specify how to use them in practice, discuss the advantages and disadvantages of each and offer tips on when and why each model can be used.