Project Title: Measuring Historical Institutions with Large Language Models: Craft Guilds, Patents, and Business Activity during Germany's Industrial Revolution.
Niclas received the Advanced Quantitative Methods Award to advance economic history using artificial intelligence.
In his doctoral work, Niclas leverages multimodal large language models to build large-scale datasets from archival image scans. With this new abundance of microlevel data, he analyses how innovation and institutions shaped labour markets and economic growth during the Industrial Revolution.
Niclas graduated top of his class in the MSc Economic and Social History at the University of Oxford and completed the MSc Computational Statistics and Machine Learning with Distinction at University College London (UCL). He also holds two bachelor’s degrees from the University of Tübingen, where he ranked third in his cohort in the BSc International Economics and graduated among the top 10% in the BSc Cognitive Science. As part of his undergraduate studies, he spent an exchange semester at the National University of Singapore.
