The course offers a comprehensive introduction to various topics in monetary macroeconomics, from both a theoretical and empirical perspective. The first part of the course will be lecture based, introducing the relevant models and providing the tools needed to later on conduct small research projects.

The lectures on the theory part (taught by Katrin Rabitsch) will focus on the baseline New Keynesian model and simple extension, as well as a short introduction into solving and analyzing DSGE models. The lectures on the empirical part (taught by Florian Huber) focuses macroeconometric methods needed to analyze the conduct of monetary policy.

In the second part of the course, students gain hands-on-experience through an independent research project that comprises writing a seminar thesis and giving a presentation of the research outcome.

 The aim of the course is to introduce students to four important topics:
1.Conventional monetary policy
2.Unconventional monetary policy
3.The monetary transmission mechanism, International spillover analysis
4.Forecasting

Introduce students to key topics in monetary economics, international macroeconomics and monetary policy analysis from a theoretical and practical perspective. Students are encouraged to pursue their own research agenda which should provide valuable help in writing a MSc. thesis. Moreover, students gain hands-on experience using modern tools in solving dynamic stochastic general equilibrium (DSGE) models as well as in modern econometric tools that are commonly used in central banks and other policy institutions.

The first half of the course is based on lectures on theoretical monetary macroeconomic models (New Keynesian models) and on the econometric models.  The second half (approximately from May onwards) will be a seminar where students present their research outline (labeled mid-term presentation) and findings / research results (final presentation in June). 

Grading is based on active participation (10%), Final Exam (30%), Mid-term and End-term presentation (30%) and Term paper (approximately 15 pages, 30%).

Strong term-papers can be extended to a MSc. thesis 

• Knowledge in time series econometrics at the undergraduate level:
  • Especially univariate time series models (AR(p), MA(q), random walks)
  • Knowledge of maximum likelihood estimation is a plus, but not needed
• Some refreshment of the math course, especially optimization (Lagrangians, First Order Conditions) is advantageous

katrin.rabitsch@wu.ac.at

fhuber@wu.ac.at