The MSc Econometrics provides a balanced and rigorous training in the quantitative analysis of issues in economics and finance. You will become proficient in the application of advanced mathematical and statistical methods, supported by modern software such as R, Matlab and Python. You can choose from 4 tracks and specialise in the field that interests you most.
In the multi-disciplinary MSc Econometrics we train you in statistical modelling, estimation and testing of economic models and in using economic and financial time series data. With your expertise you can advise organisations on the effect of economic policies. Or help businesses use extensive data analysis to shape their strategies.
During your year with us, you will discuss and reflect on theories, examine case studies and learn to work with advanced software.
The Amsterdam School of Economics has an exceptionally strong tradition in econometrics. Internationally leading experts conduct world-class research here. This means you will have access to the latest techniques and practices.
Also, our strong links to and support from international insurance and financial institutions will help you gain up-to-date insights.
The curriculum for the Master’s in Econometrics is quite demanding, with classes taking up 12-15 hours a week on average. An additional 25 hours are required for class preparation, homework, debates, casework and computer time.
Our Master’s programme in Econometrics consists of a common part for all students and a specific part where you follow courses related to the specialisation track of your choice. After the joint 1st period, you can choose the track that suits you best:
If you want to pursue a Master’s degree in Econometrics as well as in Mathematics, you can follow one of our Double Degree MSc programmes. These programmes consist of courses (150 credits) balanced between 2 schools: the Amsterdam School of Economics and the Faculty of Science.
In this course you will gain a deep understanding of econometric theory, practice and inference. You will learn how to apply advanced econometric techniques in practice, extend available methods for particular applications and how to implement them in a matrix programming environment. Also you will learn to understand and derive their statistical properties.
In this course you will study the microeconomic theory of perfect and imperfect competition. Learn under what conditions markets perform well as a means to organise economic activity (and under what conditions they do not).
In this course you will cover the basic theory of multivariate data analysis and of statistical methods in data science. You will focus on the most relevant multivariate techniques, as well as their application to econometric data in computer lab sessions. We will introduce you to Python, NumPy and pandas, data scraping, cleaning and wrangling.
In this course you will build upon the general knowledge you acquired in Advanced Econometrics 1. You will gain a deep understanding of econometric theory, acquire the technical skills to conduct inference and be able to implement these techniques using software like MATLAB, R or Python.
The Master’s thesis is the final requirement for your graduation. It is your chance to dive deep into an econometrics or data science topic that you are enthusiastic about. You present your research and findings in your thesis. A professor in your econometrics field of choice (track) will supervise and support you in writing your thesis.
The courses have a good balance between theoretical framework and practical implementation.Read about Bas' experiences with this Master's
If you have completed your curriculum, you can do an internship or go on an exchange abroad. For international students it is an excellent opportunity to experience the Dutch labour market.
Are you interested in learning Dutch? There are different options to give you the opportunity to maximise your Dutch experience and prepare for your future job in the Netherlands.
Many of our students are members of a study association. It is fun and useful for your future career at the same time. Faculty student associations are a great way to meet fellow students and future employers. They organise study trips (abroad), career events, weekly debates, parties and receptions with drinks. Sometimes you can also purchase your textbooks and course syllabi at reduced rates.
Overview Study Associations
Amsterdam has a thriving student community with many activities organised outside of the university’s grounds. You will find student associations focusing on networking, specific interests and sports. It is only at sororities and fraternities that you can expect an initiation ritual (hazing).
At university, you are entitled to make your voice heard and assess the quality of your own education. Students can participate in the discussion on the university's education policy in various ways, such as by joining the Programme Committee, the Faculty Student Council or the first-year focus group. You can also stand for election and dedicate your efforts to the programme and your fellow students.
During your Master’s, you will experience an inspiring combination of both offline and online education. We work with a blended learning teaching method. By applying this method, you will be able to combine different types of learning into 1 approach and enjoy mastering knowledge at your own pace. During class there will be more time for in-depth analyses and interaction with your lecturer and peers.
Types of education
In this programme, you will find that in your education there’s a balance between innovative teaching methods and traditional forms. Writing an academic paper can be alternated by an online challenge. A peer-feedback assignments or a video recording with explanation can also be part of the teaching method.
Our Centre for Educational Innovation and our Teaching and Learning Centre are continuously working on improving our teaching methods. We take the interactions between students, teachers, and learning resources into account. In doing so, we hope to offer you the right combination of challenging, effective, and efficient education.