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.
Academic calendar
The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period | From | To |
---|---|---|
I semestre | Oct 1, 2020 | Jan 29, 2021 |
II semestre | Mar 1, 2021 | Jun 11, 2021 |
Session | From | To |
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Sessione invernale d'esame | Feb 1, 2021 | Feb 26, 2021 |
Sessione estiva d'esame | Jun 14, 2021 | Jul 30, 2021 |
Sessione autunnale d'esame | Sep 1, 2021 | Sep 30, 2021 |
Session | From | To |
---|---|---|
Sessione di laurea estiva | Jul 22, 2021 | Jul 22, 2021 |
Sessione di laurea autunnale | Oct 14, 2021 | Oct 14, 2021 |
Sessione di laurea autunnale - Dicembre | Dec 9, 2021 | Dec 9, 2021 |
Sessione invernale di laurea | Mar 16, 2022 | Mar 16, 2022 |
Period | From | To |
---|---|---|
Festa dell'Immacolata | Dec 8, 2020 | Dec 8, 2020 |
Vacanze Natalizie | Dec 24, 2020 | Jan 3, 2021 |
Vacanze di Pasqua | Apr 2, 2021 | Apr 6, 2021 |
Festa del Santo Patrono | May 21, 2021 | May 21, 2021 |
Festa della Repubblica | Jun 2, 2021 | Jun 2, 2021 |
Vacanze Estive | Aug 9, 2021 | Aug 15, 2021 |
Exam calendar
Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.
Should you have any doubts or questions, please check the Enrollment FAQs
Academic staff
Mazzuoccolo Giuseppe
giuseppe.mazzuoccolo@univr.it +39 0458027838Study Plan
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.
1° Year
Modules | Credits | TAF | SSD |
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2° Year activated in the A.Y. 2021/2022
Modules | Credits | TAF | SSD |
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3° Year activated in the A.Y. 2022/2023
Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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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.
Type D and Type F activities
Le attività formative in ambito D o F comprendono gli insegnamenti impartiti presso l'Università di Verona o periodi di stage/tirocinio professionale.
Nella scelta delle attività di tipo D, gli studenti dovranno tener presente che in sede di approvazione si terrà conto della coerenza delle loro scelte con il progetto formativo del loro piano di studio e dell'adeguatezza delle motivazioni eventualmente fornite.
years | Modules | TAF | Teacher | |
---|---|---|---|---|
1° 2° | History and Didactics of Geology | D |
Guido Gonzato
(Coordinator)
|
|
1° 2° 3° | Algorithms | D |
Roberto Segala
(Coordinator)
|
|
1° 2° 3° | Scientific knowledge and active learning strategies | F |
Francesca Monti
(Coordinator)
|
|
1° 2° 3° | Genetics | D |
Massimo Delledonne
(Coordinator)
|
years | Modules | TAF | Teacher |
---|---|---|---|
1° 2° 3° | Algorithms | D |
Roberto Segala
(Coordinator)
|
1° 2° 3° | Python programming language | D |
Vittoria Cozza
(Coordinator)
|
1° 2° 3° | Organization Studies | D |
Giuseppe Favretto
(Coordinator)
|
years | Modules | TAF | Teacher | |
---|---|---|---|---|
1° | Subject requirements: mathematics | D |
Rossana Capuani
|
|
1° 2° 3° | ECMI modelling week | F | Not yet assigned | |
1° 2° 3° | ESA Summer of code in space (SOCIS) | F | Not yet assigned | |
1° 2° 3° | Google summer of code (GSOC) | F | Not yet assigned | |
1° 2° 3° | Introduzione all'analisi non standard | F |
Sisto Baldo
|
|
1° 2° 3° | C Programming Language | D |
Pietro Sala
(Coordinator)
|
|
1° 2° 3° | LaTeX Language | D |
Enrico Gregorio
(Coordinator)
|
Econometrics (2022/2023)
Teaching code
4S01951
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-P/05 - ECONOMETRICS
Period
Semester 1 dal Oct 3, 2022 al Jan 27, 2023.
Learning objectives
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.
Prerequisites and basic notions
We require basic knowledge of calculus. The course material relies on prior knowledge of basic statistics and probability theory.
Program
1. INTRODUCTION (Stock-Watson, ch.2-3)
1.1. What is econometrics?
1.2. Probability
1.3. Statistics
2. REGRESSION ANALYSIS (Stock-Watson, ch.4-9)
2.1. Linear regressione with a single regressor and hypothesis testing
2.2. Linear regression with multiple regressions and hypothesis testing
2.3. Diagnostics of the regression model: specification, heteroskedasticity, autocorrelation
3. EXTENSIONS (Stock-Watson, ch.11-12)
3.1. Regression with instrumental variables
3.2. Regression with binary dependent variable
Bibliography
Didactic methods
This module is composed of 52 hours of frontal lectures and exercises. During the semester students will be given problem sets to attempt at home to encourage systematic studying and self-feedback.
The rights of students will be preserved in situations of travel limitation or confinement due to national provisions to combat COVID or in particular situations of fragile health. In these cases, you are invited to contact the teacher directly to organize the most appropriate remedial strategies.
Learning assessment procedures
The exam is made of one written essay and one individual homework. In order to pass the exam, it is necessary to obtain a grade not below 18/30 in the written essay.
The homework can be of two types (Homework 1 and Homework 2). Each student is free to choose either Homework 1 or Homework 2 but must deliver one of them. Once the deadline for delivery of Homework 2 has expired, it is possible to deliver Homework 1 only. The homework grade remains valid throughout the academic year.
Homework 1
The homework aims to develop critical skills with respect to empirical applications. Each student is free to choose one article from www.lavoce.info, www.voxeu.org/, www.ilsole24ore.com or other webiste, provided that it discusses an economic topic and makes use of data.
The homework consists in an essay of max. 2000 words, to be delivered to the address diego.lubian[at]univr.it within the day in which the exam is scheduled. The homework will pass through an antiplagiarism analysis by means of the Compilation software; it is advisable to make a personal preliminary analysis before submitting the homework.
The essay must be divided in sections in such a way to contain a) a reference to the chosen article (title, authors, link), b) a summary of the article, briefly describing its motivation, goal, methodology and results, and c) a critical comment on the methodology, also proposing alternative analyses and possible future developments. The essay must also report the word count.
Homework 2
The homework aims to develop analytical skills through personal data analysis in Gretl. Any student interested in this homework must write to the address diego.lubian[at]univr.it communicating name, surname and ID number. He or she will then receive a number, corresponding to the dataset to be used. The text of the homework will be made available at the end of the lectures; the solution must be delivered by email within the following three days.
Evaluation criteria
To obtain full marks, students should show knowledge of the various econometric methodologies to understand and solve the diverse issues posed by regression models.
Criteria for the composition of the final grade
The exam is made of one written essay and one individual homework; the final grade is given by the average of the grades in the essay and the homework, with 75% and 25% weights respectively.
Exam language
Italiano
Career prospects
Module/Programme news
News for students
There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and soon also via the Univr app.
Graduation
Documents
Title | Info File |
---|---|
1. Come scrivere una tesi | pdf, it, 31 KB, 29/07/21 |
2. How to write a thesis | pdf, it, 31 KB, 29/07/21 |
5. Regolamento tesi | pdf, it, 171 KB, 20/03/24 |
List of theses and work experience proposals
theses proposals | Research area |
---|---|
Formule di rappresentazione per gradienti generalizzati | Mathematics - Analysis |
Formule di rappresentazione per gradienti generalizzati | Mathematics - Mathematics |
Proposte Tesi A. Gnoatto | Various topics |
Mathematics Bachelor and Master thesis titles | Various topics |
THESIS_1: Sensors and Actuators for Applications in Micro-Robotics and Robotic Surgery | Various topics |
THESIS_2: Force Feedback and Haptics in the Da Vinci Robot: study, analysis, and future perspectives | Various topics |
THESIS_3: Cable-Driven Systems in the Da Vinci Robotic Tools: study, analysis and optimization | Various topics |
Stage | Research area |
---|---|
Internship proposals for students in mathematics | Various topics |
Attendance
As stated in the Teaching Regulations for the A.Y. 2022/2023, except for specific practical or lab activities, attendance is not mandatory. Regarding these activities, please see the web page of each module for information on the number of hours that must be attended on-site.
Career management
Student login and resources
Erasmus+ and other experiences abroad
Commissione tutor
La commissione ha il compito di guidare le studentesse e gli studenti durante l'intero percorso di studi, di orientarli nella scelta dei percorsi formativi, di renderli attivamente partecipi del processo formativo e di contribuire al superamento di eventuali difficoltà individuali.
E' composta dai proff. Sisto Baldo, Marco Caliari, Francesca Mantese, Giandomenico Orlandi e Nicola Sansonetto