Area Data Science and Applied Econometrics [previously: Empirical Economics and Econometrics]

In today's information society, more and more findings of economic research as well as corporate decisions are based on the evaluation and interpretation of data. The focus of the internationally oriented Masterarea is the teaching of competences in the fields of economics, statistics and econometrics. The Masterarea thus conveys the understanding of complex economic issues and modeling approaches. At the same time, the statistical-econometric equipment is taught to independently evaluate and interpret economic data responsibly and accurately. The Masterarea thus pursues a multidisciplinary approach and is located at the interface between economics and econometrics and thus offers the best conditions for a later success in professional life.

The Masterarea prepares well for a career in research, economic consulting and business. Students in the Masterarea are brought to the margins of current econometric and economic research. The taught concepts are used to solve practical problems. The participating institutes cooperate with numerous companies and the international research community, so that applied content can be included in the lectures and assistance in the organization of internships can be offered.

The Masterarea Data Science and Applied Econometrics addresses economics-interested students with a tendency towards data-based work. It is aimed at students who want to learn theoretical concepts and let them undergo an empirical examination.

Due to the high demand of data scientists , the job prospects with this Masterarea are outstanding. Empirically oriented economists and data scientists work in addition to research and consulting in almost all major companies. Due to the ever-increasing importance of data analysis in times of high data availability (big data), the competent evaluation of this data is becoming increasingly important in companies as well. The demand for persons with solid empirical-econometric knowledge currently exceeds the supply many times over.