Course Unit Page
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Teacher Guglielmo Barone
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Credits 5
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SSD SECS-P/02
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Teaching Mode Traditional lectures
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Language Italian
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Campus of Bologna
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Degree Programme Second cycle degree programme (LM) in Economics and Economic Policy (cod. 8420)
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.
Academic Year 2021/2022
Learning outcomes
The course aims at presenting the most recent econometric techniques aimed at identifying causal links between economic variables, with a strong focus on economic policy issues. At the end of the course it is expected that students, when facing a microeconomic public policy, will be able to identify the problem of causal inference, to propose an appropriate counterfactual estimation strategy, to implement it through the use of software, and to critically discuss the relevant literature.
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: knowledge of the standard (OLS) multiple regression model and basic knowledge of Stata
Readings/Bibliography
S. Cunningham, Causal Inference: The Mixtape
Lecture notes and papers at the Virtuale online platformTeaching methods
Frontal lectures, paper presentations, Stata programming, seminars
Assessment methods
Drafting of an original paper and its presentation. 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
Alumni