The main goal of this course is to study the quantitative methods and techniques for statistical inference and policy evaluation. We will study the nature of these methods and apply them to data. The aim is that the students are able to perform data analysis through the methods taught in class and interpret the results. This course will provide a solid base for more advance courses in policy evaluation in this master.

The course is organized with traditional frontal lectures and applied seminars. For the seminars, we will use the STATA software.

Course objectives

• Learn the difference between association and causality
• Understand the importance of Randomised Control Trials and alternative methods (Quasi-experimental).
• Familiarised with the main econometric models: Ordinary Least Square, Binary models, Panel data, Matching techniques and Instrumental variables.
• Understand how to bring (econometric) models to data - start simple, build up
• Learn how to develop an empirical hypothesis and how to analyse data
• Learn how to evaluate a policy.
• Prepare students for advance courses in policy evaluation.

Final achievements

At the end of this course, you should be able to:

• Develop your own hypothesis
• Carry out empirical exercises yourself
• Critically assess empirical work
• Appreciate the beauty and usefulness of econometrics