Obtaining your Master's Econometrics degree is a great step in your career. Leading experts will challenge you to discuss and reflect on theories, examine case studies and work with advanced software. Most of your teachers execute world-class research and will share their latest techniques and practices with you. Future employers will reward your MSc degree with a Master’s degree worthy starting salary and a wide range of promotion opportunities.
You have a full academic year to successfully complete the 48 ECTS credits programme. Throughout this year you can expect excellent teaching and support from our professors, each highly respected in their field of expertise.
For your convenience we selected a fixed set of 8 courses for you. These form an excellent preparation for any of the 4 tracks you will later on choose within the Master's Econometrics.
Gain fundamental insights into classical mathematical statistics and learn to work with basic statistical models.
Get acquainted with supervised learning, with a focus on regression and classification methods. Practice and discuss topics such as bias-variance trade-off and cross-validation and model selection in high dimensional regression.
Learn how to approach the economy in a mathematical, model-based manner. Focus on microeconomic theory and evaluating and analysing microeconomic arguments and models.
Get to know about modern investment and portfolio theory. Learn about financial-economic theories and the mathematical and statistical techniques to analyse and implement them.
Learn how to use the research techniques and theories in economics and actuarial science, that were discussed during your Bachelor’s years. You will collect your own data sets and analyse them. You will also discuss scientific articles and critically evaluate their underlying theory, assumptions and techniques.
Learn how to develop the multiple regression model with applications, especially to cross-sectional data. Make extensive use of matrix algebra and multivariate statistical theory. Use software packages EViews and R or Python for the execution of applications and simulations.
Learn about econometric models that are important for interpreting quantitative results. Discuss how they can explain measurement errors, simultaneous equation bias, self-selection, censoring and truncation. Develop the initial skills and techniques for correct modelling of economic variables.
Learn about the parts of univariate and multivariate time series analysis that are most relevant for analysing (macro)economic and financial time series.
Language | English |
Duration | 1 academic year |
ECTS | 48 ECTS |
Start pre-Master's | September |
Start Master's Econometrics | Following academic year in September (choose 1 of 4 tracks) |
Cost | You pay tuition fee per ECTS. Calculate your tuition fee |
The entry requirements for this pre-Master’s programme depend on your previous academic education.
Your eligibility is based on the following criteria:
Your eligibility is based on the following criteria:
Other test versions or modules are not accepted. Examples of this include but are not limited to: IELTS Indicator, IELTS One Skill Retake, TOEFL Home Edition, TOEFL MyBest Scores, etc.
Test scores may not be older than 2 years, counting back from the start of the programme. For example, if you are applying for the September 2025 intake, we do not accept English proficiency tests taken before September 2023. Scores older than 2 years are only valid in combination with certain study programmes (check the exemptions). Sufficient test scores received after the application deadline are accepted, as long as your English proficiency test was taken before the application deadline.
We do not require a specific minimum GPA for this programme, but we will compare and assess the performance on all selection criteria to make an informed decision regarding placement into the programme.
If you are a student with a non-EU nationality, you may consider applying for a Master’s-qualifying programme at the Cambridge Education Group.
We do not have a pre-Master’s programme available for students with previous education from a Dutch University of Applied Science (HBO). You can apply for our BSc Econometrics and Data Science.
If you meet all the admission requirements, you can apply for the pre-Master's programme. Please complete these steps to apply. Only applicants who complete these steps will be considered.
The application deadline for the September 2025 intake:
For applicants with an EU degree: | 1 May 2025 |
For applicants with a Dutch degree: | 1 June 2025 |
Register in Studielink – Select the programme: BSc Econometrics and Data Science - pre-Master's programme. After that choose: Econometrics.
After registering in Studielink, you will receive your UvAnetID. This will give you access to check the status of your personal enrolment Checklist. There you find the subsequent steps that you need to take in order to complete your enrolment.
In order to check if you are eligible for the programme you need to upload and submit your documents in our online application system Embark. Make sure you keep an eye on the deadlines!
You will most likely receive your results within 4-6 weeks after we have received a complete application, but in peak moments (January till June) evaluating your application may take a few weeks longer.
The tuition fees for your pre-Master’s programme depend on the number of ECTS credits you need to obtain. Please take into account that it is not possible to arrange payment of your tuition fees until the programme has officially admitted you to the pre-Master’s programme. The tuition fees for pre-Master's programmes are usually not calculated until August.
If you have received the great news that you are (conditionally) admitted to the programme, it's time to focus on other essential matters like arranging a visa (if necessary), finding accommodation, and preparing for the start of your academic journey. Want to get an early idea of what you need to consider? Visit one of these helpful pages: practical information / praktische zaken (Dutch info).