A curriculum that builds deep expertise in econometric modelling and analysis
The Econometrics specialisation within the MSc Econometrics and Management Science offers a rigorous and comprehensive curriculum that prepares you to model, analyse, and solve real-world problems using advanced quantitative methods. You will gain a strong foundation in econometric theory and develop the skills to apply and extend these methods in practice.
Programme structure
The programme is structured across five blocks of eight weeks.
- Core courses cover a wide range of topics essential to modern econometrics, including microeconometrics and time series econometrics.
- Electives allow you to tailor your learning, with options ranging from machine learning to advanced macroeconomics.
- Seminar (Case Studies in Applied Econometrics) is a team-based research project where you apply your skills to real-world data under faculty supervision.
- Master thesis is written individually in the final blocks and may be theoretical or practice-oriented, often in combination with an internship or traineeship.
Curriculum overview
- 70% Courses
- 30% Case Studies in Applied Econometrics
The exact composition depends on your course selection.
In class
You will work on applied problems that reflect the complexity of modern economic and financial systems. For example:
How can we estimate the effect of a policy intervention or predict economic turning points?
You will explore topics such as modelling rare events, forecasting business cycles, and dealing with outliers and missing data.
In the seminar and thesis, you may work on cases such as:
- Estimating the market value of NBA players
- Predicting investor behaviour in financial markets
- Filtering long-run economic trends from real-time data
You will develop models, analyse data, and present findings that are both academically sound and practically relevant.
Study schedule
| period | course name | EC |
|---|---|---|
| block1 | Take-Off Master | 0 ec |
| block1 | Panel Data Econometrics | 4 ec |
| block1 | Bayesian Econometrics | 4 ec |
| block1 | Machine Learning in Econometrics | 4 ec |
| block2 | Robust Methods | 4 ec |
| block2 | Time Series Econometrics for Macroeconomics | 4 ec |
| block2 | Probabilistic Modeling | 4 ec |
| block3 | Causal Inference | 4 ec |
| block3+4 | Seminar Case Studies in Applied Econometrics | 12 ec |
| block4+5 | Master's Thesis Proposal E&MS | 4 ec |
| block4+5 | Master's Thesis Econometrics | 16 ec |
Disclaimer
This overview provides a general impression of the 2027-2028 curriculum. It is not the current study schedule. Enrolled students can find the most up-to-date version on MyEUR. Please note that minor changes may occur in future academic years.