Course Unit Page


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

Good health and well-being Quality education Reduced inequalities Partnerships for the goals

Academic Year 2022/2023

Learning outcomes

  • Learn how to bring (econometric) models to data - start simple, build up

  • Learn how to develop an empirical hypothesis

  • Learn how to interpret regression outputs

  • Learn the difference between association and causation
  • Learn the different methods that are used to derive causal inference.

  • Critically assess the advantages and disadvantages of alternative policy evaluation methods in various contexts

Course contents

1 - Regression model 

2 - Randomized trials

3 - Instrumental variables

4 - Regression discontinuity designs

5 - Panel data and differences-in-differences


Essential reading

Jeffrey M. Wooldridge, Introductory Econometrics: A Modern Approach, Cengage Learning, Seventh Edition, 2019.

Gertler, P. J., Martinez, S., Premand, P., Rawlings, L. B., & Vermeersch, C. M.. Impact evaluation in practice, 2nd edition. World Bank Publications, 2016.

Additional readings

Joshua D. Angrist and Jörn-Steffen Pischke, Mastering 'Metrics: The Path from Cause to Effect, Princeton University Press, 2014.

More advanced readings

Joshua D. Angrist and Jörn-Steffen Pischke, Mostly Harmless Econometrics: An Empiricist's Companion, Princeton University Press, 2009

A. Colin Cameron and Pravin K. Trivedi, Microeconometrics using Stata, Stata Press, 2010

Teaching methods

During each lecture we will discuss a different method and its applications to real-life problems. We will discuss and interpret empirical findings coming from published research articles. Data analysis with Stata will allow deeper understanding of the methods presented in class. 

Assessment methods

The assessments include problem sets, in class participation and written exam.

The maximum possible score is 30 cum laude, in case all anwers and exercises are correct, complete and formally rigorous.

The grade is expressed as follows:

<18 failed
18-23 sufficient
24-27 good
28-30 very good
30 e lode excellent

Teaching tools

  • Lectures slides
  • References to published research articles
  • STATA material

Software STATA: can be installed on students' personal computers (CAMPUS license) and is available at the Computer Lab of the School of Economics and Management.

Office hours

See the website of Elisabetta De Cao