Course Unit Page


This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

No poverty Quality education Decent work and economic growth

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


S. Cunningham, Causal Inference: The Mixtape

Lecture notes and papers at the Virtuale online platform

Teaching 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