96499 - FUNDAMENTALS OF ECONOMETRICS

Learning outcomes

By the end of the course the student has adequate knowledge of the basic instrument used by economists for conducting their empirical investigations, understands the concept of causality and is aware of several available strategies to identify and estimate a causal relationship. At the end of the course he/she is capable to understand scientific articles using the linear regression model and to critically appreciate the identification strategy adopted.

Course contents

Regression models, binary models, causal inference methods

Readings/Bibliography

Main

Introductory Econometrics: A Modern Approach, 2019, 7th Edition, Jeffrey M. Wooldridge.

Impact evaluation in practice, 2nd edition. World Bank Publications, 2016. Gertler, P. J., Martinez, S., Premand,

P., Rawlings, L. B., & Vermeersch, C. M.

Additional readings

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

Teaching methods

In-person lectures, practical tutorials

Assessment methods

The final grade will depend on:

• Quizzes in class
• Group problem sets
• Final exam

More details will be provided in the Virtuale page of the course.

The maximum possible score is 30 cum laude, in case all answers/course works are correct, complete and formally rigorous.

The grade is graduated as follows:

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

Teaching tools

Dedicated page on the VIRTUALE platform containing:

• News and updated information
• Lectures slides
• STATA lab 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