Assumptions form the foundation of statistical models and decision-making. Critically questioning these assumptions makes new methods and insights possible. Moreover, it deepens our understanding of societies and ourselves. This is what Professor of Econometric Methods and Applications Julia Schaumburg stated in her inaugural lecture.
My research focuses on developing methods at the intersection of time series econometrics, statistics, and machine learning. I have worked on making financial risk models more realistic by relaxing restrictive assumptions. My work includes modeling financial contagion, identifying bank business models, and forecasting interest rates.
During the coronavirus pandemic, I began to question my long-held assumptions about political responses to the climate crisis. Despite clear scientific evidence, action is lacking. This led me to analyze climate and weather data, where econometrics helps model extreme events like heat waves and floods. It also took me out on the streets with Scientist Rebellion.
For me, questioning assumptions is not merely a scientific pursuit, but a responsibility when the facts demand action," says Schaumburg.
