This course helps PhD students to write a research paper by applying methods used in Bayesian times series econometrics to their field of research. Students will employ and extend the toolkit acquired in ``363-1161-00L Time Series Econometrics and Macroeconomic Forecasting''.

This course examines the behaviour of macroeconomic variables, such as gross domestic product, unemployment and inflation rates. It tries to answer questions like: How can we explain fluctuations of national economic activity? What can economic policy do against unemployment and inflation?

This block course introduces students to the multivariate time series toolkit — vector autoregressions, large scale simultaneous equation systems, state space models, and machine learning nowcasts — used by central banks and research institutes to forecast and analyze macroeconomic activity. Intensive computer labs let students build real time forecasts and policy scenarios.