Teaching and Supervision

Courses

Economic Policy for Sustainable Energy (TPM0637SET): The course – an introduction to environmental and ecological economics focused on energy – runs annually in the third quarter. It is designed for students in the Sustainable Energy Technology MSc program, but it is open to students from other programs as well.

Statistical Methods for Causal Inference and Prediction (TPM039A): The course introduces modern methods for causal inference based on observational data. MSc students from all programs interested in evidence-based policy making are welcome to enroll. MSc students who take the course in the first quarter of the second year can fruitfully apply the methods learned in their master thesis projects.

Systems Science for Health and Care (SEN181A): The course is part of the Health Track in the Complex Systems Engineering and Management MSc program. I teach a module on causal inference in public health.

To access course materials, please enroll for the courses on Brightspace.

I used to co-teach Macroeconomics for Policy Analysis, together with Servaas Storm, and also Preparation for the Master Thesis.

Master Thesis Supervision

I supervise MSc students in various programs (EPA, MOT, COSEM, IE, SET, etc.) who are interested in doing quantitative empirical research on economic problems. The thematic domain is broad and includes research problems related to the energy transition, housing, and labor markets.

In the academic year 2026/27, I am particularly interested in projects related to the “housing affordability crisis” and the “European renovation wave”. The Woononderzoek Nederland (WoON) is one dataset that could be used to investigate questions in either of these areas, but there are many other possibilities.

The exact research question is open. You develop the research question and define the project together with me. One of the quickest ways to develop a good research question is to browse the scientific literature and identify a “role model”: a published scientific article that i) you find interesting and ii) more or less does what you want to do. You then learn to do research by emulating the role model in your own thesis.

I am particularly interested in projects that apply quantitative empirical methods. Depending on the research question, this could involve input-output modeling or statistical methods for causal inference, such as regression, difference-in-differences, or synthetic control.

Your thesis should make constructive use of economic theory and have implications for economic policymaking. You should have passed at least one master-level course in economics; even better, you are doing the elective package “Economics and Finance”; ideally, you are taking the course “Statistical Methods for Causal Inference and Prediction”. Experience with empirical research and scientific programming (e.g., Stata, R, Julia, Python) is helpful but not essential.

Contact me if you are interested.