This lecture consists of three main blocks. While the first block is dedicated to a theoretical discussion of Bayesian econometrics, the second block covers computational issues and there implementation in the software package \textbf{R}. The third block gives a dense treatment of the current research frontier of high-dimensional problems and forecasting challenges.
Students carry out a group (max. 5 students) research project by applying the discussed tools and models to a macroeconomic question of choice. The paper should be structured and written according to the guidelines of Economics Letters and should not exceed about 10 pages in length (including: a separate title page with an abstract summarizing the paper; a complete list of references; excluding: a list of data sources, R code). The paper should be explicit enough for a fellow student to be able to replicate all results (therefore, data sources must be documented and modelling choices should be defended). You should clearly explain what the research question is, why the question is interesting, and what you have learned. For the paper you need to conduct an estimation by yourself implemented in R. The final paper that is due at the end of the term (01. July 2019) has to be uploaded at the learn@wu assignment tool for a plagiarism check.
Please make sure that you read the assigned literature PRIOR to the lecture. Each lecturer will cover a more or less closed topic.