3.0

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This course is composed of two parts. In the first half, we will cover an introduction to Bayesian methods and standard methods as Metropolis, Metropolis-Hasting, Gibbs sampling, etc. We will then review the relation between Bayesian methods and machine learning. In the second part, we will study how Bayesian methods and machine learning have been used in the macro and macro-finance literatures to handle DSGE's, VAR's, Markov-switching-VAR's, Time-Varying VAR's, textual analysis, forecasting, etc.