Econometrics (2020/2021)

Course code
Name of lecturer
Gian Piero Aielli
Gian Piero Aielli
Number of ECTS credits allocated
Academic sector
Language of instruction
I semestre dal Oct 1, 2020 al Jan 29, 2021.

Lesson timetable

Go to lesson schedule

Learning outcomes

Statistic tools and economic theory will be applied in order to provide students with capabilities to understand and perform empirical analysis of economic phenomena. Empirical problems and applications will be discussed during the course to provide students with the tools needed for the analysis of economic data.


1. Introduction
- What is econometrics?
- Review of probability
- Review of statistics

2. The regression analysis
- Linear regression model: single regressor and multiple regressors
- Ordinary least squares estimation of model coefficients
- Least squares assumptions
- Properties of OLS estimators
- Hypothesis testing and confidence intervals
- Goodness of fit
- Heteroschedasticity and homoschedasticity
- Omitted variable bias
- Models for binary dependent variable

Reference books
Author Title Publisher Year ISBN Note
Stock, J. e M. Watson Introduzione all'econometria (Edizione 3) Pearson 2015

Assessment methods and criteria

The exam is divided in two parts: a written test to be carried out in the classroom and a homework to be carried out individually. The exam mark consists of the weighted average of the marks in the written test and in the homework, weighed respectively by 75% and 25%.
The written test is conducted in online mode, lasts two hours and will contain both practical exercises and theoretical questions. During the test it is possible to use the calculator and the statistical tables, but not notes or other didactic material.
The homework consists in a MATLAB application of the linear regression model to be delivered in pdf format.