2025 Fall School in Causal Inference and Optimal Policy Learning
Venue: Hotel Birger Jarl Conference
Stockholm, Sweden
Date: November 17—18, 2025
We’re excited to announce that registration is now open for the 2025 Fall School on Causal Inference and Optimal Policy Learning!
The 2025 Fall School is an intensive 1.5-day course in the closely intertwined fields of Causal Inference and Optimal Policy Learning. It is designed for researchers, practitioners, and professionals who want to deepen their understanding of Causal Inference while also gaining insight into Optimal Policy Learning, a nascent field that integrates causal insights into data-driven policy making.
This year's 2025 Fall School represents a return to Metrika's long tradition hosting seasonal, intensive schools. These seasonal schools represent a unique opportunity for students, academics, and professionals to expand their skills in data science, and to learn how these skills can be applied to their own fields. The course combine teaching and problem solving, and there are ample opportunities for participants to ask questions and to receive individualized guidance.
Instructor
Dr. Giovanni Cerulli is a researcher at the IRCrES-CNR, Research Institute on Sustainable Economic Growth, National Research Council of Italy, Unit of Rome.
He is a leading researcher in data science, widely published in top journals and author of the book Econometric Evaluation of Socio-Economic Programs: Theory and Applications.
Dr. Giovanni will be holding both the lectures and lead participants to apply the theoretical framework in several hands-on computer exercises.
Course Description
This intensive course introduces participants to advanced methods in causal inference, with a special focus on non-binary treatments and data-driven policy learning. Moving beyond the classical binary treatment framework, the course equips students with both theoretical foundations and practical tools to estimate causal effects when treatments are multivalued or continuous, and to learn optimal policy rules from data.
Structured in four modules, the course begins with the basics of causal inference, including the potential outcomes framework and the estimation of average and individual treatment effects. It then expands to multivalued and continuous treatment settings, covering the use of generalized propensity scores and multinomial models. The final module introduces the emerging field of Optimal Policy Learning (OPL), offering participants a modern framework for deriving ex-ante policy recommendations from observational data.
Throughout the course, an emphasis is placed on hands-on implementation using Stata, allowing participants to bridge the gap between theory and practice. Click here to show the full module outline and reading list.
Venue and logistics
The Fall School is held at the beautiful and inviting Hotel Birger Jarl, centrally located in Stockholm. Lunch and fika are included on both Monday and Tuesday, please specify any dietary restrictions when you sign up. The hotel also offer discounted accommodation for all course participants (please contact us for further details).
Attendance is limited and places are allocated on a first come, first serve basis. Please register long in advance to guarantee your place.
Stata 19 software is provided free of charge to all participants during the courses but participants are assumed to bring their own laptops.
Prerequisites
A general familiarity with Stata and a course in regression analysis or comparable experience.
Price
Academic and student 435 USD (excl. VAT)
Non-academic 600 USD (excl. VAT)
Please click here to sign up.
Terms and conditions apply. Click here for details.