Daniel has extensive experience in analyzing large datasets, visualizing results, and providing intelligible insights. Among other antitrust cases, he has conducted in-depth investigations in several arbitration and cartel litigation cases, developing and implementing robust econometric models to quantify the impact of anticompetitive behavior on prices. His expertise in econometric modeling includes techniques such as difference-in-differences, fixed effects, probit models, instrumental variables, and Monte Carlo simulations.
Beyond his antitrust and arbitration experience, he has gained extensive knowledge in predicting product sales globally, modeling different gas supply & demand scenarios and assessing economic & political country risk for internal financing purposes at a large international chemical company. He also acquired experience in automated business reporting for money market products and in asset management at a large asset management company, where he also handled minor client requests and prepared sales presentations.
Daniel holds a Master's and Bachelor's Degree in Economics from Heidelberg University, specializing in econometric methods, game theory, and behavioral science. He studied a year abroad at the Warsaw School of Economics in Poland as an Erasmus student. For his Master Thesis, he coded and ran an incentivized online experiment testing different instructional and survey designs to improve comprehension and survey quality. A native German speaker, he is also fluent in English and has basic knowledge of French.