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Applied Economics and Data Science - Master's Programme
Orientation and Goals
The design and evaluation of government interventions in markets to ensure that they function properly or to achieve societal goals has always been a cornerstone of economics. A classic example, which is currently the subject of controversial public debate, is the use of market regulation to protect the environment, for example through the introduction of taxes or the expansion of certificate trading to reduce CO2 emissions. There are many more examples in areas such as development policy, foreign trade, the housing market and financial markets.
In all of these fields, the evaluation of interventions requires huge amounts of data and a combination of modern empirical methods, such as econometric estimates, simulation techniques and Big Data processing and analysis methods.
This degree programme, which is at the crossroads between economics and computer science, acknowledges the fact that empirical methods for analysing data in both disciplines are becoming increasingly similar. Due to the ever-growing data sets used to analyse economic issues, methods for analysing Big Data are increasingly finding their way into economics.
The Master’s degree programme in Applied Economics and Data Science combines the fields of economics and computer science. In this degree programme, students acquire in-depth knowledge of theoretical concepts and empirical findings on government regulation and in-depth methodological knowledge of modern analytical procedures for empirical data. They learn how to prepare, analyse and interpret large data sets.
The emphasis of this programme is on learning, applying and critically questioning methods and concepts used in current research to analyse and solve economic issues using empirical data.
This Master’s degree programme in Applied Economics and Data Science is a research-oriented programme in which students are systematically introduced to the current state of research and in which they conduct a self-designed research project. After graduation, students are in a strong position to make their own contribution to research.
In all of these fields, the evaluation of interventions requires huge amounts of data and a combination of modern empirical methods, such as econometric estimates, simulation techniques and Big Data processing and analysis methods.
This degree programme, which is at the crossroads between economics and computer science, acknowledges the fact that empirical methods for analysing data in both disciplines are becoming increasingly similar. Due to the ever-growing data sets used to analyse economic issues, methods for analysing Big Data are increasingly finding their way into economics.
The Master’s degree programme in Applied Economics and Data Science combines the fields of economics and computer science. In this degree programme, students acquire in-depth knowledge of theoretical concepts and empirical findings on government regulation and in-depth methodological knowledge of modern analytical procedures for empirical data. They learn how to prepare, analyse and interpret large data sets.
The emphasis of this programme is on learning, applying and critically questioning methods and concepts used in current research to analyse and solve economic issues using empirical data.
This Master’s degree programme in Applied Economics and Data Science is a research-oriented programme in which students are systematically introduced to the current state of research and in which they conduct a self-designed research project. After graduation, students are in a strong position to make their own contribution to research.
Study Design and Contents
The four-semester Master’s degree programme in Applied Economics and Data Science has a workload of 120 credit points and is split into four subject areas.
In the Economics component (36 credit points), students learn about market mechanisms, international trade, financial markets, development economics, climate, energy and resource economics in the two compulsory modules Advanced Microeconomics and Industrial Organisation as well as in the three elective modules.
In the Empirical Methods component (18 credit points), students learn advanced methods in the fields of econometrics, statistics and simulation. These constitute the basis of all empirical research in economics and meet contemporary methodological requirements.
In the Data Science modules (18 credit points), students are taught current methods of data management, machine learning and deep learning, and they learn how to apply these techniques for conducting analyses in the field of economics.
The Specialisation elective modules (18 credit points) give students the opportunity to develop their own individual specialisation profile. They can choose courses from the Economics, Empirical Methods and Data Science components. Students can also take other modules in Business Administration, Law and Computer Science to create a specialisation profile that matches their own interests and career aspirations.
In the Economics component (36 credit points), students learn about market mechanisms, international trade, financial markets, development economics, climate, energy and resource economics in the two compulsory modules Advanced Microeconomics and Industrial Organisation as well as in the three elective modules.
In the Empirical Methods component (18 credit points), students learn advanced methods in the fields of econometrics, statistics and simulation. These constitute the basis of all empirical research in economics and meet contemporary methodological requirements.
In the Data Science modules (18 credit points), students are taught current methods of data management, machine learning and deep learning, and they learn how to apply these techniques for conducting analyses in the field of economics.
The Specialisation elective modules (18 credit points) give students the opportunity to develop their own individual specialisation profile. They can choose courses from the Economics, Empirical Methods and Data Science components. Students can also take other modules in Business Administration, Law and Computer Science to create a specialisation profile that matches their own interests and career aspirations.
Teaching and Learning
The modules offered as part of the Master’s degree programme in Applied Economics and Data Science comprise a mix of lectures, seminars and practical exercises. Research-oriented learning modules are also offered.
Foreign Language Skills
German language skills are not required for admission.
In order to study this course at the University of Oldenburg, you need an adequate knowledge of English.
English language proficiency see admissions regulations
In order to study this course at the University of Oldenburg, you need an adequate knowledge of English.
English language proficiency see admissions regulations
- Common European Framework of Reference for Languages (CEFR) level B2
- if applicants have obtained a first university degree in English in a country with English or German as your official language
The proof of language proficiency must be presented for the enrolment and should not be older than two years. For other proof possibilities see: Language requirements
Careers and Areas of Employment
Graduates of this degree programme are particularly suited for the following careers:
Since this degree programme is research-oriented, graduates may also pursue a doctorate.
- Decision-makers in politics and administration who are responsible for designing and implementing policy measures. Examples of potential employers include:
- The Federal Ministry for the Environment, Nature Conservation and Nuclear Safety
- The Federal Ministry of Economics and Energy
- The Lower Saxony Ministry for the Environment, Energy, Construction and Climate Protection
- Corresponding state ministries in other federal states
- Corresponding institutions at EU level
- The German Environment Agency
- NGOs such as BUND, WWF
- Political parties
- Professionals in the private sector who are responsible for assessing the impact of government regulations and evaluating their consequences. Examples of potential employers include:
- Automotive companies
- Energy suppliers
- IT companies
- Employees at universities and research institutions who conduct research on the implementation and efficiency of regulations and government measures. Examples of potential employers include:
- Economic research institutes, such as the German Institute for Economic Research (DIW), the Centre for European Economic Research (ZEW), the Institute for the World Economy (IfW) or Institute for Economic Research (IfO Institute)
- Universities that specialise in relevant research areas. In the field of sustainability: University of Oldenburg, University of Hamburg, University of Lüneburg, etc.
Since this degree programme is research-oriented, graduates may also pursue a doctorate.
Target Group/Admission Requirements
- Bachelor's degree or equivalent qualification from prior studies in Sustainability Economics, Economics, Business Administration, Economics and Business Administration, Business Informatics or in a closely related field worth at least 180 credit points.
- Economics with at least 24 ECTS
- Mathematics with at least 12 ECTS
- Statistics with at least 12 ECTS
- Econometrics with at least 6 ECTS
English Language Proficiency see admissions regulations
- Level B2 of Common European Framework of Reference for Languages (CEFR)
Application/Admission Procedures
This course of studies accepts a limited number of applicants, and application is only possible in the winter semester.