Course Unit Page


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

Quality education Decent work and economic growth

Academic Year 2021/2022

Learning outcomes

The aim of the course is to introduce econometric techniques to study the empirical behaviur of individual economic agents. At the end of the course, the student will be able to assess the empirical researchpublished in the literature on these subjects, apply a number of econometric techniques to their own data.

Course contents

1. Modelling cross sections, time series and panels of data
2. The econometric software
3. The theory ofmultiple regression (OLS, GLS, IV)
4. Limited dependent variable models


(1) Basics: 2 options, either

(1a) J. Stock e M. Watson, Introduction to Econometrics (5th edition), Addison Wesley
Chapters: (1-9), 11, (12), 18, 19 (note: in brackets the parts which should be have done during the bachelor that are integrant part of the course) 

(1b) Verbeek M., A Guide to Modern Econometrics (4th edition). Wiley

(2) Other material will be available during the course

Further readings:
Linton, O, Probability, Statistics and Econometrics, Academic Press


Teaching methods

Each lecture presents both theoretical and applied aspects of the econometric method, by using the PC screen in class in order to show main outcomes of the regression analysis. For this, attending the lectures is very important,

Assessment methods

Students attending the lectures: the final examination is made of two steps of different relevance:
30% applied work with Stata and Gretl using data and topics chosen by the teacher.
70% individual written exam (oral in caso of pandemic)

Students not attending the lectures are requested to make a written exam.

Scales of assessment: <18: insufficient; 18-23: sufficient; 24-27:good; 28-30:very good; 30 e lode: outstanding.

Teaching tools

PC and slides

Links to further information


Office hours

See the website of Roberto Golinelli