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.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
I semestre Oct 1, 2020 Jan 29, 2021
II semestre Mar 1, 2021 Jun 11, 2021
Exam sessions
Session From To
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
Degree sessions
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
Holidays
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.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

A B C D E G L M N O P R S Z

Albi Giacomo

giacomo.albi@univr.it +39 045 802 7913

Angeleri Lidia

lidia.angeleri@univr.it 045 802 7911

Baldo Sisto

sisto.baldo@univr.it 045 802 7935

Bos Leonard Peter

leonardpeter.bos@univr.it +39 045 802 7987

Caliari Marco

marco.caliari@univr.it +39 045 802 7904

Canevari Giacomo

giacomo.canevari@univr.it +39 045 8027979

Chignola Roberto

roberto.chignola@univr.it 045 802 7953

Collet Francesca

francesca.collet@univr.it

Cubico Serena

serena.cubico@univr.it 045 802 8132

Daffara Claudia

claudia.daffara@univr.it +39 045 802 7942

Dai Pra Paolo

paolo.daipra@univr.it +39 0458027093

Daldosso Nicola

nicola.daldosso@univr.it +39 045 8027076 - 7828 (laboratorio)

Delledonne Massimo

massimo.delledonne@univr.it 045 802 7962; Lab: 045 802 7058

De Sinopoli Francesco

francesco.desinopoli@univr.it 045 842 5450

Enrichi Francesco

francesco.enrichi@univr.it +390458027051

Gnoatto Alessandro

alessandro.gnoatto@univr.it 045 802 8537

Lubian Diego

diego.lubian@univr.it 045 802 8419

Mantese Francesca

francesca.mantese@univr.it +39 045 802 7978

Mantovani Matteo

matteo.mantovani@univr.it 045-802(7814)

Mariutti Gianpaolo

gianpaolo.mariutti@univr.it 045 802 8241

Mazzuoccolo Giuseppe

giuseppe.mazzuoccolo@univr.it +39 0458027838

Nardon Chiara

chiara.nardon@univr.it

Orlandi Giandomenico

giandomenico.orlandi at univr.it 045 802 7986

Pianezzi Daniela

daniela.pianezzi@univr.it

Rizzi Romeo

romeo.rizzi@univr.it +39 045 8027088

Schuster Peter Michael

peter.schuster@univr.it +39 045 802 7029

Segala Roberto

roberto.segala@univr.it 045 802 7997

Solitro Ugo

ugo.solitro@univr.it +39 045 802 7977

Zuccher Simone

simone.zuccher@univr.it

Study 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 enrolment year.

CURRICULUM TIPO:
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°
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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S01951

Teacher

Diego Lubian

Coordinatore

Diego Lubian

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-P/05 - ECONOMETRICS

Period

Primo semestre 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

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

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.

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

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.

 

I semestre From 10/1/20 To 1/29/21
years Modules TAF Teacher
1° 2° History and Didactics of Geology D Guido Gonzato (Coordinatore)
1° 2° 3° Algorithms D Roberto Segala (Coordinatore)
1° 2° 3° Scientific knowledge and active learning strategies F Francesca Monti (Coordinatore)
1° 2° 3° Genetics D Massimo Delledonne (Coordinatore)
II semestre From 3/1/21 To 6/11/21
years Modules TAF Teacher
1° 2° 3° Algorithms D Roberto Segala (Coordinatore)
1° 2° 3° Python programming language D Vittoria Cozza (Coordinatore)
1° 2° 3° Organization Studies D Giuseppe Favretto (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
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 (Coordinatore)
1° 2° 3° LaTeX Language D Enrico Gregorio (Coordinatore)

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.

Graduation

Attachments

Title Info File
Doc_Univr_pdf 1. Come scrivere una tesi 31 KB, 29/07/21 
Doc_Univr_pdf 2. How to write a thesis 31 KB, 29/07/21 
Doc_Univr_pdf 5. Regolamento tesi (valido da luglio 2022) 171 KB, 17/02/22 

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
Stage Research area
Internship proposals for students in mathematics Various topics

Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, 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.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Career management


Area riservata studenti