Alexander Dück, Zeb Consulting

Alexander Dück joined the IMFS in November 2019 as a Ph.D. student at GSEFM at Goethe University. Before joining the Macroeconomic Model Data Base (MMB) team, he worked as a research assistant in the Department of Money and Macroeconomics of Goethe University. During his studies at GSEFM he received a scholarship (Deutschlandstipendium) for two years. Alexander completed his Bachelor's degree at Goethe University where he was involved in teaching undergraduate students in Mathematics and Business Informatics for nearly three years. Apart from that, he was on the Dean’s List for excellent academic performance. His research interests lie in the fields of non-linear modelling, Bayesian estimation and machine learning. In September 2024, he graduated from GSFM and took his first position at a consulting agency.

How would you describe your job to other people?

I am a consultant in the Finance & Risk department. As part of the ESG and quant team, I combine quantitative skills with our specialists’ ESG knowledge to fulfill the needs of our clients. My work entails coding in Python, analyzing EU law, as well as performing the EU-Taxonomy reporting on large-scale balance sheets. In addition, I provide scenario analyses and I participate in topic workshops.

What do you like most about your job?

I enjoy working in a highly collaborative environment with very flat hierarchies. At zeb I can expand my ESG knowledge with practice-relevant content and code at the same time, which I particularly enjoyed during my Ph.D. studies. Coding has become my most used tool and strongest asset.

What was the main focus of your research at the IMFS?

My research focuses on answering policy questions using a variety of macroeconomic models. One part focuses on frequency-specific effects of monetary policy and how well macroeconomic models capture the volatilities across different frequency bands when compared to the data. Another part analyzes implications of carbon prices across different models and how the central bank should conduct its optimal monetary policy during the green transition. Lastly, I build an epidemiological macroeconomic model with endogenous behavioral rules to measure effectiveness of government COVID-19 interventions.

Besides my own research, I was primarily working on the development of the Epidemic-Macro Model Data Base (Epi-MMB), which provided me with a very detailed understanding of this class of models and its solution method.

How is your job at zeb related to your work at the IMFS?

Both jobs require a high level of precision, and elaborated results are presented internally and externally (whether at conferences or workshops). At the IMFS I was rather free when I decided what I want to do, while at zeb my work is mostly project related. Although both jobs are in the same broad area (climate change and interest rates), the main focus shifted from the macro to the micro level, especially for data work.

What did you enjoy most regarding your time at the IMFS?

There are three things I enjoyed at the IMFS. First, developing the Epi-MMB from scratch was an exciting task with friendly and collaborative co-workers, one becoming my co-author afterwards. Working on the Epi-MMB widened my knowledge about project management. Second, the IMFS supported my conference presentations in a great research community. Last, I was (nearly) completely free in my daily life enabling a good balance between work, life, and research.