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
The Take-Off is the introduction programme for all new students at Erasmus School of Economics. During the Take-Off you will meet your fellow students, get acquainted with our study associations and learn all the ins and outs of your new study programme, supporting information systems and life on campus and in the city.
Traditionally, the firm is treated as a structure where inputs are transformed into output. Yet, 'the firm' is not a decision-making unit. Rather, production is shaped by the decisions of people within the organisation. People involved in an organisation (or, more generally, in any transaction) will have different objectives, which may hamper cooperation.
The issues we will discuss include the effects and limitations of various instruments that may improve efficiency, such as property rights, contracts, financial and non-financial incentives, and organisational structure. Throughout, we take a microeconomic perspective.
This course provides an overview of modern industrial organization that blends theory with real-world applications. It acquaints the students with the most important models for understanding strategies chosen by firms with market power and shows how such firms adapt to different market environments. These insights are then applied to study market outcomes and competition policy. Formal theory is complemented throughout by real-world cases that show how it applies to actual organizational settings.
The main analytical tools used are microeconomic theory and game theory.
- Sampling
- Regression and Prediction (OLS, Lasso, etc.)
- Causal Inference (Differences-in-Differences, Instrumental Variables, Regression Discontinuity)
- Panel Data (Random Effects, Fixed Effects, Dynamic Panels)
- Limited Dependent Variables (Probit, Logit, Poisson, etc.)
- Inequalities and Discrimination in Labour Markets
- other Economics and Business master's course
This course introduces students to the use of Machine Learning (ML) in economic analysis with a specific focus on its application to human resource problems within organizations. Students will learn basic techniques of machine learning and its integration with econometric techniques commonly used in current empirical research. The focus will be on practical applications to human resource problems (and not the methods themselves). Topics can vary from year to year depending on research frontier.
During the seminar, academic research papers are presented and discussed by students. Moreover, each student works on a research project (which can, but need not be an extension of one of the papers) and writes a short note on this. Papers are chosen from a list of recent academic research papers on current topics in the economics of markets and organisation. These include both theoretical and empirical papers.
In this course, students apply the knowledge and skills acquired throughout their studies to real-world contexts in organizations. During the seminar, we will apply methods and use findings from academic research papers to solve problems that are important to organizations. These problems can be related to organizational structure, corporate strategy, and human resources management, with the dual objective of improving firm performance and creating a positive impact at work. Throughout the seminar, students will perform in-depth analyses of cases, find and apply relevant knowledge from the most advanced research in economics (both theoretical and empirical), analyze relevant data, and develop innovative solutions for organizations.
The thesis is an individual assignment about a subject from your Master's specialisation. More information about thesis subjects, thesis supervisors and the writing process can be found on the Master thesis website.
Disclaimer
The overview above provides an impression of the curriculum for this programme for the academic year 2023-2024. It is not an up-to-date study schedule for current students. They can find their full study schedules on MyEUR. Please note that minor changes to this schedule are possible in future academic years.