Duration
30h Th, 15h Pr
Number of credits
Lecturer
Language(s) of instruction
English language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
This course introduces causal analysis in public policy.
Students learn how economists explore the causal effects of a policy and how to critically evaluate the findings. Starting from the fundamental problem of causal inference, the course covers:
- Randomized controlled trials
- Instrumental variables
- Regression discontinuity designs
- Difference-in-differences
- Event studies
The course ends with a discussion of how much we can trust causal evidence.
Throughout the course, we apply the different tools to policy-relevant topics and simulate the type of discussions about causality that take place in public policy decision-making bodies.
Learning outcomes of the learning unit
At the end of the course, the student will be able to:
- distinguish correlation from causation and state the conditions under which a policy can be said to have caused a change in an outcome;
- explain the loogic, the identifying assumtions and the limits of the main methods used to obtain causal evidence (randomized controlled trials, instrumental variables, regression discontinuity designs, difference-in-differences);
- critically evaluate a causal claim: identify the exogenous variation and assess threats to validity, robustness, alternative explanations, mechanisms and external validity;
- build and communicate the strongest possible case for a policy position using causal evidence, while being explicit about what is kown, what remains uncertain and what we still need to know;
- use causal evidence to justify their own judgement on a policy question.
Prerequisite knowledge and skills
Prior knowledge of econometrics (OLS) is strongly recommended.
Planned learning activities and teaching methods
The course combines weekly lectures and tutorials.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Further information:
Face-to-face course.
Course materials and recommended or required readings
Further information:
Further information:
Lecture slides.
Causal Inference:
Cunningham, S. (2026). Causal Inference: The Remix. Yale University Press.
Public Policy Applications:
Besley, T., Bucelli, I., & Velasco, A. (Eds.). (2025). The London consensus: Economic principles for the 21st century. LSE Press.
Continuous assessment
Further information:
Continuous assessment
- Weekly quizzes (20%, individual)
- RCT assessment report (25%, individual)
- Causal evidence policy debate and policy brief (40%, group)
- Vote justification (15%, individual)
Additional information:
There is no final exam.
Work placement(s)
Organisational remarks and main changes to the course
Lectures: Thursdays, 1-3 pm, Room 088 (N1d building).
Tutorials: Mondays, 10 am-12 pm, Room 235 (N1a building).
Contacts
Alejandra Ramos, e-mail: Alejandra.Ramos@uliege.be
Association of one or more MOOCs
There is no MOOC associated with this course.