Causal inference (SPS-METRI-CAU-24)
SPS-METRI-CAU-24
| Department |
SPS |
| Course category |
SPS Research Seminar |
| Course type |
Seminar |
| Academic year |
2024-2025 |
| Term |
2ND TERM |
| Credits |
20 (EUI SPS Department) |
| Professors |
|
| Contact |
Altesini, Sofia
|
| Course materials |
| Sessions |
|
Purpose
This course provides an introduction to causal inference in the social sciences, equipping students with the skills to critique methods used in contemporary academic work and apply these methods in their research. It begins with an overview of causality in the social sciences, covering the potential outcomes framework and randomized experiments. The second part of the course delves into the most widely used approaches for drawing causal inferences from observational data, such as "selection on observables" (regression, matching, and subclassification), difference-in-differences, instrumental variables, and the regression discontinuity design. Students are expected to have a basic understanding of probability, statistics, and the R programming language.
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Page last updated on 05 September 2023