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
primo semestre (lauree) Sep 28, 2020 Dec 23, 2020
secondo semestre (lauree) Feb 15, 2021 Jun 1, 2021
Exam sessions
Session From To
sessione invernale Jan 11, 2021 Feb 12, 2021
sessione estiva Jun 7, 2021 Jul 23, 2021
sessione autunnale Aug 23, 2021 Sep 17, 2021
Degree sessions
Session From To
sessione autunnale (validità a.a. 2019/20) Dec 9, 2020 Dec 11, 2020
sessione invernale (validità a.a. 2019/20) Apr 7, 2021 Apr 9, 2021
sessione estiva (validità a.a. 2020/21) Sep 6, 2021 Sep 8, 2021
Holidays
Period From To
Vacanze di Natale Dec 24, 2020 Jan 6, 2021
Vacanze di Pasqua Apr 3, 2021 Apr 6, 2021
Vacanze estive Aug 9, 2021 Aug 15, 2021

Exam calendar

Exam dates and rounds are managed by the relevant Economics 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

B C D F G L M N P R S V Z

Bucciol Alessandro

alessandro.bucciol@univr.it 045 802 8278

Chiarini Andrea

andrea.chiarini@univr.it 045 802 8223

Cipriani Giam Pietro

giampietro.cipriani@univr.it 045 802 8271

Corbella Silvano

silvano.corbella@univr.it 045 802 8217

Corsi Corrado

corrado.corsi@univr.it 045 802 8452 (VR) 0444/393937 (VI)

De Crescenzo Veronica

veronica.decrescenzo@univr.it 045 802 8163

Di Caterina Claudia

claudia.dicaterina@univr.it 0458028247

Ferrari Maria Luisa

marialuisa.ferrari@univr.it 045 802 8532

Fiore Simona

simona.fiore@univr.it

Fioroni Tamara

tamara.fioroni@univr.it 0458028489

Giaretta Elena

elena.giaretta@univr.it 045 802 8051

Lubian Diego

diego.lubian@univr.it 045 802 8419

Malpede Maurizio

maurizio.malpede@univr.it

Menon Martina

martina.menon@univr.it

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Nicodemo Catia

catia.nicodemo@univr.it +39 045 8028340

Pasquariello Federica

federica.pasquariello@univr.it 045 802 8233

Perali Federico

federico.perali@univr.it 045 802 8486

Picarelli Athena

athena.picarelli@univr.it 045 8028242

Pilati Andrea

andrea.pilati@univr.it 045 802 8444 (VR) - 0444 393938 (VI)

Polin Veronica

veronica.polin@univr.it 045 802 8267

Renò Roberto

roberto.reno@univr.it 045 802 8526

Roveda Alberto

alberto.roveda@univr.it Dip. Sc. Ec. 045 802 8096 C.I.D.E. 045 8028084

Salomoni Alessandra

alessandra.salomoni@univr.it 045 802 8443

Sclip Alex

alex.sclip@univr.it

Sommacal Alessandro

alessandro.sommacal@univr.it 045 802 8716

Sproviero Alice Francesca

alicefrancesca.sproviero@univr.it 045 802 8216

Vernizzi Silvia

silvia.vernizzi@univr.it 045 802 8168 (VR) 0444 393937 (VI)

Zarri Luca

luca.zarri@univr.it 045 802 8101

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.

ModulesCreditsTAFSSD
9
A
IUS/01
9
A
SECS-P/01
9
A
SECS-S/06
9
C
SECS-P/12
English language B1 level
3
E
-
ModulesCreditsTAFSSD
9
B
SECS-P/01
9
B
SECS-P/03
9
B
SECS-S/01
ModulesCreditsTAFSSD
9
B
SECS-P/05
6
B
SECS-P/02
Training
6
F
-
Final exam
3
E
-

1° Year

ModulesCreditsTAFSSD
9
A
IUS/01
9
A
SECS-P/01
9
A
SECS-S/06
9
C
SECS-P/12
English language B1 level
3
E
-

2° Year

ModulesCreditsTAFSSD
9
B
SECS-P/01
9
B
SECS-P/03
9
B
SECS-S/01

3° Year

ModulesCreditsTAFSSD
9
B
SECS-P/05
6
B
SECS-P/02
Training
6
F
-
Final exam
3
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°

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

9

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-P/05 - ECONOMETRICS

Period

Primo semestre (lauree) dal Sep 19, 2022 al Jan 13, 2023.

Learning objectives

The course provides the main econometric tools to develop, based on the available data, an empirical analysis on the relationship between economic variables and to correctly interpret and use the results obtained. In fact, many economic decisions require quantitative answers to quantitative questions, and decisions based on empirical evidence are generally considered more helpful and effective.
The course uses a scientific language based on deductive reasoning. Technical aspects of econometrics, however, will be introduced only when necessary, whereas key attention will be given to the development of an intuitive comprehension of the material, in such a way to allow for an effective and creative use of the acquired knowledge.
At the end of the course the student is expected to (a) have critical skills with respect to empirical applications made by others and (b) be able to autonomously set up and run empirical analyses in the broad areas of economics and finance.

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.10-12)
3.1. Regression with instrumental variables
3.2. Regression with binary dependent variable
3.3 Regression with panel data

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 72 hours of frontal lectures. During the semester students will be given problem sets to attempt at home to encourage systematic studying and self-feedback. In addition, a designated tutor will present additional questions and empirical problems to equip students with knowledge of the software Gretl.

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 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

Bibliography

Type D and Type F activities

primo semestre (lauree) From 9/28/20 To 12/23/20
years Modules TAF Teacher
Future matters D Alessandro Bucciol (Coordinatore)
Future matters D Alessandro Bucciol (Coordinatore)
secondo semestre (lauree) From 2/15/21 To 6/1/21
years Modules TAF Teacher
Design and Evaluation of Economic and Social Policies D Federico Perali (Coordinatore)
Public debate and scientific writing - 2020/2021 D Martina Menon (Coordinatore)
Wake up Italia - 2020/2021 D Sergio Noto (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
Ciclo di video conferenze: "L’economia del Covid, Verona e l’Italia. Una pandemia che viene da lontano?" - 2020/21 D Sergio Noto (Coordinatore)
Ciclo tematico di conferenze (on-line): “Come saremo? Ripensare il mondo dopo il 2020” - 2020/21 D Federico Brunetti (Coordinatore)
Marketing plan - 2020/21 D Virginia Vannucci (Coordinatore)
1° 2° 3° Data Analysis Laboratory with R (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° Data Visualization Laboratory D Marco Minozzo (Coordinatore)
1° 2° 3° Python Laboratory D Marco Minozzo (Coordinatore)
1° 2° 3° Data Science Laboratory with SAP D Marco Minozzo (Coordinatore)
1° 2° 3° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° Programming in Matlab D Marco Minozzo (Coordinatore)
1° 2° 3° Programming in SAS D Marco Minozzo (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.

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