The curriculum consists of foundation courses courses, core courses and seminars. The tool courses, Applied Econometrics and Game Theory, provide a foundation for empirical and theoretical analysis. Game Theory trains students to quickly reduce a situation to its essence, and provides insight into situations of strategic interaction. Applied Econometrics equips you with the tools to extract reliable information from available Big Data and assess the credibility of empirical results.
The curriculum consists of core courses, field courses, seminars, and the master thesis. We start with three core courses: Applied Econometrics, Industrial Organisation, and Economics of Organisations. Applied Econometrics equips you with the tools to extract reliable information from available data and to assess the credibility of empirical results. Industrial Organisation discusses how market structure affects the strategic interaction between firms, and studies innovation, advertisement, pricing, product differentiation and bundling, and cartel formation. It also discusses the role of competition policy. Economics of Organisations examines the role of organisations in the economy and studies what drives performance of organisations, drawing from a wide variety of cases.
In the field courses, you apply the skills and insights obtained in the core and tool courses. Data Science and HR Analytics introduces students to the use of machine learning, with a specific focus on its application to human resource management within organizations. Inequalities and Discrimination in Labor Markets studies when and how discrimination in labour markets and organizations arises, the consequences of discrimination, and the effects of both organisational and government policies aimed at reducing inequality and discrimination.
The seminars are the main courses in the programme. Here students conduct short analyses, write research notes, present their findings, and actively participate in classroom discussions. Lectures are based on recent research findings and on real-life case studies. In the last part of the programme you write your thesis under close supervision of one of our academic staff members.
Curriculum
The curriculum consists of:
- 20%: Theoretical and empirical skill formation
- 40%: Organisations
- 40%: Markets
In class
Class size is limited to facilitate interaction. A variety of approaches is used in class: traditional lectures, hands-on data science in computer rooms, and interactive discussion sessions. In the seminar Recent Advances in EMO, students present a recent research article as if they authored it and answer questions raised by other students. In the seminar Practical Applications, students apply their analytical skills to real-world cases.
Study schedule
Disclaimer
The overview above provides an impression of the curriculum for this programme for the academic year 2025-2026. It is not an up-to-date study schedule for current students. They can find their full study schedules on MyEUROpens external. Please note that minor changes to this schedule are possible in future academic years.