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.

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:

2° Year   activated in the A.Y. 2017/2018

ModulesCreditsTAFSSD
6
A
MAT/02
6
B
MAT/03
6
C
SECS-P/01
6
C
SECS-P/01
6
B
MAT/06

3° Year   activated in the A.Y. 2018/2019

ModulesCreditsTAFSSD
6
C
SECS-P/05
activated in the A.Y. 2017/2018
ModulesCreditsTAFSSD
6
A
MAT/02
6
B
MAT/03
6
C
SECS-P/01
6
C
SECS-P/01
6
B
MAT/06
activated in the A.Y. 2018/2019
ModulesCreditsTAFSSD
6
C
SECS-P/05
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°
Between the years: 1°- 2°- 3°
Altre attività formative
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.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S01951

Teacher

Coordinator

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-P/05 - ECONOMETRICS

Period

I semestre dal Oct 1, 2018 al Jan 31, 2019.

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
- 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
- Generalized least squares
- Nonlinear regression functions
- Assessment of studies based on multiple regression

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

Reference texts
Author Title Publishing house Year ISBN Notes
R. Carter Hill, William E. Griffiths, Guay C. Lim Principi di econometria Zanichelli 2013 9788808175304

Examination Methods

The final exam consists of a written exam and a homework. The final grade will be obtained as a weighted average of the two parts with weight 90% (written exam) and 10% (homework).
The written exam will last two hours and will cover all the program of the course. The homework will be developed independently and it will be one of two typologies (Homework I e Homework II). Every student is free to choose one of the two typology, but at least one has to be chosen. After the deadline for Homework II, student would only be able to choose Homework I

Homework I
The student has to choose one article about economic issues and using data. As an example, the student can choose one article from www.lavoce.info, www.voxeu.org ... The student will have to write a critical assessment of the article (max 2000 words, discussing methodology with proposals for alternative analysis and further research) that will be handed in (by mail or in person) before the date of the written exam.

Homework II
Analysis of data using GRETL. Before 31st December 2018, the student interested in Homework II should write an email with name, surname and univr-id. On 3rd January the text of the homework and data will be delivered. The solution should be handed in before 31st January 2019.

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