New research project combines social and mathematical sciences

Life events such as losing a loved one, being convicted of a crime or completing an education have major impacts on an individual’s life, but how life events combine to cause the development of a particular life trajectory is still poorly understood. By developing and applying state-of-the-art causal learning methods to data on the entire Danish population, the new research project will address the core question:

How can life trajectories of individuals be causally attributed to their life event histories?

The project seeks to combine methodological and computational expertise in Copenhagen Causality Lab (CoCaLa), Department of Mathematical Sciences, with the data expertise and deep substantial knowledge in Copenhagen Center for Social Data Science (SODAS) to attack the question above.

This new bridge between two strong research environments at UCPH allows us to address the technical “how” as well as the substantive justification, interpretation, and application: how can we use data for the attribution; why is this justified; what does it mean; and how does it help human beings?

The project bridges leading methodological research from statistics with applications to causal inference within the social sciences. By establishing a new collaboration and using a unique data resource on the Danish population, the project promises to cross-fertilize the research in both groups and lead to cutting edge insights on causal dynamics of life trajectories.

The project - Causal dynamics of individual life trajectories in the Danish population - is awarded a total of DKK 804.000 from the UCPH Data+ Pool, aimed at researchers in cross-disciplinary projects that integrate data science in new research areas.

The grant will co-finance a PhD student for three years. The PhD student will be affiliated with the research environments of both CoCaLa and SODAS. Niels Richard Hansen from MATH will be supervisor, Andreas Bjerre-Nielsen and Sune Lehmann from SODAS will act as co-supervisors.

The application to data of this magnitude and complexity will expose new research avenues and promises substantive results with high impact.

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Copenhagen Causality Lab (CoCaLa) is a research group under the Section for Statistics and Probability Theory, Department of Mathematical Sciences. Causality is a fundamental concept in science, and the lab’s research is centred on this concept and how it relates to statistical modelling and data analysis. Read more about CoCaLa.

Copenhagen Center for Social Data Science (SODAS) is an interdisciplinary social science centre located at the Faculty of Social Sciences. Combining classic social science theories and methods with state-of-the-art data science techniques, SODAS aspires to do cutting-edge and creative interdisciplinary research, teaching and impact in the crossroads between the social sciences and data science. Read more about SODAS.