Philip Rademacher

Doctoral Student in Economics | Data Analyst

About Me

I have studied economics and history (as a minor subject) at the universities of Düsseldorf, Wuppertal and Tartu. During my studies, I have mainly worked as a student assistant in research and teaching, but also did internships in the financial and cultural sector, e.g. at the Deutsche Bundesbank.

Since June 2023, I am enrolled as an external doctoral student in Economics at the University of Düsseldorf and work as a Data Analyst. If you are interested in my research, feel free to contact me (via the contact form or LinkedIn).

Research Interests

Applied Economics

My research interests are very diverse and range from educational economics to economic policy. However, all of them have a common denominator: they are tackled empirically and data-based. I like to apply standard econometric techniques, but also focus on the implementation of new methods (like machine learning) and the utilization of other datatypes (e.g. unstructured text data).

Economic History

The generation of scientific knowledge in the humanities is predominantly based on written sources. Quantitative research approaches are strongly underrepresented, although data on various potential research topics is available (in particular for economic questions). Such research gaps are exciting because quantitative approaches may yield different results than their qualitative counterparts.


Forecasting is actually not far from economic history. The idea is to use data from the past to make a reliable prediction for the future. In recent years machine learning (ML) models were able to improve predictions in many areas. I am not only interested in the hunt for the best forecasts, but I want to take a closer look: Why are some ML-models better than econometric models? Can economists improve their theoretical understanding with the help of those models?


  • Coding: Python, R, Stata, SQL
  • Languages: German, English, Dutch (and Latin of course!)
  • Office: Word, Excel, PowerPoint
  • Design: GIMP, HTML, CSS, LaTeX

Current Research

  • Forecasting Recessions in Germany with ML
  • Transformation to Climate Neutrality from a Regional Perspective
  • Data Quality and Bias in the Coin Hoards of the Roman Empire Database