Imbens G.W., Rubin D.B. (2015).
Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction.
Cambridge University Press
Teaching Methods
Theoretical lectures and practical labs
Type of Assessment
Final grades are based on the results obtained in three intermediate tests (a midterm test and two projects) and in the final oral exam.
Course program
1) Introduction to casual inference
2) Randomized experiments
- Methods based on randomization
- Regression models for randomized experiments
3) Observational studies
- Design: Unconfoundedness and Overlap; Propensity score; Subclassification, matching and trimming to assess and improve covariate balance
- Analysis: Methods based on Propensity Score; Sensitivity analysis to assess unconfoundedness
- Methods for non-binary treatments
Each method will be illustrated using empirical analyses from various fields: economics (labor, population and development economics), social policy and other social sciences.