This two-year, English-taught Master’s programme is offered jointly by TU Dortmund University, Ruhr University Bochum and the University of Duisburg-Essen. It is designed for quantitatively oriented students who already hold a Bachelor’s degree in economics, statistics, mathematics or a closely related discipline. The multi-university setup gives access to the combined expertise and resources of three institutions while culminating in a single joint degree awarded by all three partners.
The curriculum focuses on econometric theory and applied statistical methods, equipping you to build and use mathematical models to analyse real-world problems. Graduates leave with a strong grounding in statistical techniques and a deep understanding of core economic causal relationships, preparing them for analytical roles in research, industry, government, financial institutions and other organisations where data-driven decision-making is essential.
To support incoming international students, an International Master’s Preparation and Cultural Transition (IMPACT) Programme is available. IMPACT provides targeted academic and administrative assistance to help you meet programme requirements and to familiarise you with study expectations and campus life at TU Dortmund and its partner universities. For details about the preparatory courses and services, please visit the IMPACT Programme website.
Requirements (summary)
The programme is built from five core modules, four electives and a concluding six‑month Master's thesis. Most modules are organized as several smaller courses, allowing you to pick classes that match your interests and career goals. In addition to traditional lectures, you will encounter seminars and project work that support both theoretical understanding and practical application.
Core teaching focuses on statistical theory, econometric methods and time‑series analysis, while also developing competencies in project management, consulting and applied research. Electives and seminars form a large, flexible pool so you can specialise in areas of interest — for example, health economics or financial econometrics — and tailor your study path toward either advanced research or applied work in industry or policy.
Key modules and learning outcomes
Program requirements (concise)
This Master’s is designed for strongly quantitative students who want the theoretical foundations for a career in econometric research. The core modules are mathematically demanding, so demonstrated ability and interest in mathematics/statistics are required. Pre-course classes are offered before lectures begin and are strongly recommended for applicants with a weaker mathematical background.
Applications are reviewed by an examination board; they may request conditions or additional coursework if prerequisites are incomplete. You may apply before your final degree certificate is issued, provided you submit other university documents proving that all requirements will be met. Note there is no numerus fixus (no limit on places). Processing can take several weeks — international applicants from non-EU countries should apply as early as possible to allow time for visa and housing arrangements.
Required application documents (submit all of the following)
These requirements may change; always check the Faculty of Statistics/TU Dortmund website for the latest details.
Winter Semester (International)
15 May 2026
Summer Semester (International)
15 January 2027
Graduates are prepared for analytically demanding roles in research, business, government and finance where advanced econometric and statistical methods are required. Typical positions include econometrician, quantitative analyst, data scientist, policy analyst, research associate, and consultant in financial institutions, public agencies, research institutes and private firms.
The programme’s strong emphasis on mathematical rigour and applied econometric techniques also provides a solid foundation for further academic research (PhD) or specialised roles in areas such as financial econometrics, health economics, risk management and empirical economic research.