- Docente: Guglielmo Barone
- Credits: 6
- SSD: SECS-P/05
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Economics and Public Policy (cod. 5945)
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from Feb 19, 2025 to Mar 13, 2025
Learning outcomes
The course illustrates the most recent identification strategies for the quantitative assessment of causal effects using observational data by referring to micro-econometric applications. It will cover matching and difference-in-differences strategies, and quasi-experimental approaches to identification. At the end of the class, student will be able: - to critically understand the application of these tools in the recent empirical economic literature; - to apply these approaches to design his/her own program evaluation.
Course contents
The problem of causality
Causality in a regression framework
Instrumental variables
Panel data, difference-in-differences, synthetic control method
Regression discontinuity design
Prerequisites: very good knowledge of the standard (OLS) multiple regression model, basic knowledge of panel data, and knowledge of Stata
Readings/Bibliography
Lecture notes and papers at the Virtuale online platform
S. Cunningham, Causal Inference: The Mixtape
Teaching methods
Frontal lectures, paper presentations, Stata programming
Assessment methods
Teamwork: drafting an presenting an original small-scale paper, or replicating an existing paper plus a short oral exam. Alternatively: long oral exam. The maximum possible score is 30 cum laude. The grade is graduated as follows:
<18 failed
18-23 sufficient
24-27 good
28-30 very good
30 cum laude excellent
Teaching tools
Slides, textbook, Stata software
Office hours
See the website of Guglielmo Barone
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.