32626 - Econometrics

Learning outcomes

At the end of the course the student has adequate knowledge of the basic instrument used by economists for their empirical investigations (the linear regression model for the analysis of cross-sectional and panel data) and is able to understand under what conditions the estimated relationship has a causal interpretation. Drawing on critical discussion about some micro-economic applications from recent research, the student receives specific data to practice at the computer and learn the basic skills to perform empirical work using the software STATA. At the end of the course he/she is capable to understand scientific articles using the linear regression model and is also able to perform its own analysis with this instrument.

Course contents

Simple linear regression model, multiple regression model, statistical inference, OLS asymptotic, practical data issues, dummy variables, heteroskedasticity.

Readings/Bibliography

Introductory Econometrics: A Modern Approach, 2019, 7th Edition, Jeffrey M. Wooldridge, chapters 2 to 8.

Teaching methods

Face-to-face teaching, practical tutorials

Assessment methods

- Quizzes

- 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