Econometrics (2019/2020)

Course code
Name of lecturer
Laura Magazzini
Laura Magazzini
Number of ECTS credits allocated
Academic sector
Language of instruction
I semestre dal Oct 1, 2019 al Jan 31, 2020.

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?
- Economic questions and data
- 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
- Nonlinear regression functions

3. Extensions to the regression model
- Models for binary dependent variable
- The instrumental variable estimator

Reference books
Author Title Publisher Year ISBN Note
R. Carter Hill, William E. Griffiths, Guay C. Lim Principi di econometria Zanichelli 2013 9788808175304

Assessment methods and criteria

The final exam consists of a written exam and a set of exercises to be developed individually. The final grade will be obtained as a weighted average of the two parts with weight 90% (written exam) and 10% (exercises).
The written exam aims at evaluating the understanding of theoretical concepts and the ability to interpret the econometric models. The exam will last two hours and will cover the whole program of the course. The student may use a calculator and statistical tables when solving the written exam; no other material will be allowed.
The exercises will be developed independently and aims at evaluating the capabilities of students in using software for econometric analysis. The exercises will be published on the moodle platform of the course and must be handed in before the day of the written exam.