The course gives an introduction to methods in Macroeconometrics with special emphasis on Bayesian techniques.

We will discuss the following topics:

- Vector Auto Regressions (VARs): estimation, identification, impulse response functions

- Dynamic Stochastic General Equilibrium (DSGE) models 

- Likelihood methods: Kalman filter, ML estimation of DSGE models

- Introduction to Bayesian estimation and simulation

- Bayesian VARs (BVARs): priors for VARs, Bayesian estimation, structural BVARs

- Bayesian time series: Factor models, time-varying parameter models, Bayesian DSGE estimation and evaluation

- Model uncertainty and model misspecification 

Form of evaluation:  

- practical exercises

- short research paper

Students are presumed to have knowledge of econometrics at the intermediate undergraduate level. No prior knowledge of Bayesian estimation is required. Some basic knowledge of programming using Matlab or R is expected for the practical exercises.