Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Study Plan

A.A. 2024/2025 A.A. 2023/2024 A.A. 2022/2023 A.A. 2021/2022 A.A. 2020/2021 A.A. 2019/2020 A.A. 2018/2019 A.A. 2017/2018 A.A. 2016/2017 A.A. 2015/2016 A.A. 2014/2015 A.A. 2013/2014 A.A. 2012/2013 A.A. 2011/2012 A.A. 2010/2011 A.A. 2009/2010

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea in Matematica applicata - Enrollment from 2025/2026

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

CURRICULUM TIPO:

1° Year 

ModulesCreditsTAFSSD
12
A
MAT/02 ,MAT/03
12
A
MAT/05
6
B
MAT/08
12
A
FIS/01
6
B
MAT/01
12
A
INF/01

2° Year   activated in the A.Y. 2019/2020

ModulesCreditsTAFSSD
6
A
MAT/02
12
B
MAT/05
6
B
MAT/08
6
B
MAT/03
6
C
SECS-P/01
6
C
SECS-P/01
6
B
MAT/06
6
B
MAT/05
English B1
6
E
-

3° Year   activated in the A.Y. 2020/2021

ModulesCreditsTAFSSD
6
C
SECS-P/05
12
C
SECS-S/06
6
B
MAT/08
6
B
MAT/09
6
B
MAT/06
Final exam
6
E
-
activated in the A.Y. 2019/2020
ModulesCreditsTAFSSD
6
A
MAT/02
12
B
MAT/05
6
B
MAT/08
6
B
MAT/03
6
C
SECS-P/01
6
C
SECS-P/01
6
B
MAT/06
6
B
MAT/05
English B1
6
E
-
activated in the A.Y. 2020/2021
ModulesCreditsTAFSSD
6
C
SECS-P/05
12
C
SECS-S/06
6
B
MAT/08
6
B
MAT/09
6
B
MAT/06
Final exam
6
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°
12
D
-
Between the years: 1°- 2°- 3°
Other activities
6
F
-

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.

A Basic activities
B Characterizing activities
C Related or complementary activities
D Activities to be chosen by the student
E Final examination
F Other training activities
S Placements in companies, public or private institutions and professional associations

Econometrics  (2020/2021)

Teaching code

4S01951

Teacher

Coordinator

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-P/05 - ECONOMETRICS

Period

I semestre dal Oct 1, 2020 al Jan 29, 2021.

Lessons timetable MoodleMoodle Seminars 0

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.

Program

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
- Regression with serial correlated errors

Reference texts
Author Title Publishing house Year ISBN Notes
Stock, J. e M. Watson Introduzione all'econometria (Edizione 3) Pearson 2015

Examination Methods

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.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE