Bayesian Multivariate Time Series Methods for Empirical Macroeconomics provides a survey of the Bayesian methods used in modern empirical macroeconomics. These models have been developed to address the fact that most questions of interest to empirical macroeconomists involve several variables and must be addressed using multivariate time series methods. Many different multivariate time series models have been used in macroeconomics, but Vector Autoregressive (VAR) models have been among the most popular. Bayesian Multivariate Time Series Methods for Empirical Macroeconomics 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.

About the Author:

Gary Koop is Professor of Economics at the University of Strathclyde. He has published numerous articles in Bayesian econometrics and statistics in journals such as Journal of Econometrics, Journal of the American Statistical Association and the Journal of Business and Economic Statistics. He is an associate editor for several journals, including the Journal of Econometrics and the Journal of Applied Econometrics. He is the author of the books Bayesian Econometrics, Analysis of Economic Data and Analysis of Financial Data.

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