The Theory for Econometric Modelling specialization area offers you the opportunity to engage academically with current issues in politics and economics. The program not only analyzes problems from a theoretical perspective but also focuses on teaching the empirical methods needed to analyze these problems empirically using real-world data.
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What is this about? In this specialization, you’ll learn the core concepts of empirical economic research. You’ll acquire practical data analysis methods and deepen your knowledge of evidence-based economic analysis. This will prepare you, in particular, for a research-oriented or quantitative master’s program.
What is being researched? In the Theory for Econometric Modelling specialization, real-world data is used to investigate current issues in politics and the economy. Among other topics, research focuses on the causes of inequality, the effects of international trade, and the returns on education.
Why should you choose this specialization? The results of empirical analyses are increasingly serving as the basis for decision-making in business and politics. Due to the digital transformation of the economy and society, ever-larger volumes of data are becoming available, meaning that research-based activities involving the processing and analysis of large datasets are playing an increasingly important role. In the Theory for Econometric Modelling specialization, you will therefore gain knowledge in the areas of empirical research, quantitative methods, and computer-aided data analysis - core competencies in the modern workplace.
| Module | Recommended Semester | Required |
|---|---|---|
| Introduction to Econometrics | 4th Semester | Compulsory |
| Introduction to Quantitative Economic History | 4th Semester | Elective |
| Public Finance: Taxation | 4th Semester | Elective |
| International Trade | 4th Semester | Elective |
| Introduction to Data Science with R and R-Studio | 4th Semester | Elective |
| Introduction to Financial Data Science | 4th Semester | Elective |
| Tools for AI & Data Science | 4th/5th Semester | Elective |
| Basics of Innovation Economics | 5th Semester | Elective |
| Empirical Strategies in Economics | 5th Semester | Elective |
| The Industrial Revolution and the Roots of Modern Growth | 5th Semester | Elective |
| Introduction to Statistical Learning | 5th Semester | Elective |
| My First Data Science Project | 5th Semester | Elective |
| Module | Recommended Semester | Required |
|---|---|---|
| Project Seminar Humboldt Reloaded | 4th/3rd Semester | Semi-Elective |
| Profile Seminar Topics in International Economics | 5th Semester | Semi-Elective |
| Profile Seminar Historical Economics | 6th Semester | Semi-Elective |
| Profile Seminar Public Finance | 6th Semester | Semi-Elective |
| Profile Seminar Econometrics | 6th Semester | Semi-Elective |
Note: At least one seminar must be selected.
When selecting your modules, there are two strategies to consider: focusing on a specific area or developing broader skills. In general, many other module combinations are possible, allowing you to tailor your personal profile to your own interests.
Today’s workplace requires the proper handling of ever-increasing amounts of data. Companies and public organizations base their decisions on analyses of internal and external data. As a graduate of this program, you are therefore in high demand.
Some typical career paths:
Employers include, for example:
Helpful skills:
The CareerCenter offers support with career orientation and starting your career. You can also receive personalized advice here on choosing a major and discuss your potential career paths. The F.I.T. program also offers courses to help you make these decisions.
After completing your bachelor’s degree in Business Administration and Economics with a specialization in Theory for Econometric Modelling, the following Hohenheim degree programs are particularly recommended:
You are also very well prepared for the following degree programs:
A master’s degree qualifies you, among other things, for academic work at universities and research institutes.
