Nora Würz

Dr. Nora Würz serves as an Academic Councillor (Senior Lecturer) at the Chair of Statistics and Econometrics within the Faculty of Social Sciences, Economics and Business Administration at the University of Bamberg since 2022, where she leads teaching and research initiatives in advanced statistical methodologies.

Her academic journey includes a Bachelor's degree in Integrated Life Sciences from Friedrich-Alexander University Erlangen-Nuremberg (2015) and a Master's degree in Statistics through the Joint Masters Program of Berlin universities (2017). She completed her PhD at Freie Universität Berlin (2017-2022) under the German Academic Scholarship Foundation, with her dissertation winning the Federal Statistical Office's 2023 'Statistical Science for the Society' prize.

Dr. Würz specializes in small area estimation under data constraints, pioneering integrations of machine learning (particularly random forests) with traditional statistical models. Her research addresses critical gaps in poverty mapping, regional unemployment estimation using mobile network data, and construction of consumer price indices, with strong emphasis on real-world applications in official statistics and policy analysis.

Her publication trajectory reveals a strategic evolution toward leveraging non-traditional data sources (mobile networks, aggregated census data) and advanced computational techniques to solve persistent challenges in regional statistics, particularly where population microdata is inaccessible. This work has established new methodological standards for income indicator estimation and small area modeling transformations.

Her scientific recognition includes:

• Statistical Science for the Society prize (Federal Statistical Office, 2023)
• Young Scientist Award (German Statistical Society, 2023)
• Gerhard Fürst Prize (Federal Statistical Office, 2018)

Dr. Würz contributes significantly to statistical infrastructure through R package development (saeTrafo, povmap) and methodological guidelines for European statistical projects. Her research program receives ongoing support from official statistical agencies and focuses on translating methodological innovations into practical tools for national statistical offices.

As core faculty within the Chair of Statistics and Econometrics, she collaborates with Prof. Timo Schmid on European projects related to small area estimation, while maintaining active partnerships with the Federal Statistical Office and UK Office for National Statistics through EMOS (European Master in Official Statistics) initiatives.