معرفی
Riccardo Di Francesco is a Postdoctoral Researcher in the Department of Economics at the University of Southern Denmark, Faculty of Social Sciences. His work bridges econometrics, causal inference, and statistical learning, with a focus on innovative methods for applied microeconomic analysis.
His research interests include:
- Econometrics
- Causal Inference
- Statistical Learning
- Applied Microeconomics
- Machine Learning in Economics
- Covariate Modeling
- Distributional Analysis
His recent publication introduces the Ordered Correlation Forest, a novel machine learning technique enhancing variable importance and conditional probability estimation in econometric modeling. This reflects a broader trend in his work of integrating advanced statistical learning tools into traditional econometric frameworks to improve robustness and interpretability.
He is currently involved in the research project Beyond the Paycheck: Insights into the effect of Unemployment, Organisational Change, and Job Security on Mental Health, funded by private foundations and running from 2024 to 2027. This project explores the socio-economic determinants of mental health, aligning with his expertise in causal inference and applied microeconomics.
Riccardo Di Francesco contributes to impactful interdisciplinary research at the intersection of data science and economics, with a strong methodological foundation and real-world policy relevance.
