Postdoctoral Researcher
Riccardo Di Francesco
University of Southern Denmark
I am an applied econometrician specialising in causal inference and causal machine learning, developing tools for heterogeneous treatment effects and ordered outcomes with applications to health and labour economics. My applied work examines how economic and social environments shape worker health, team production, and social preferences, drawing on data from administrative registers, corporate disclosures, professional sports leagues, and online platforms.
