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.

A.A. 2021/2022

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 magistrali) Oct 4, 2021 Dec 17, 2021
secondo semestre (lauree magistrali) Feb 21, 2022 May 13, 2022
Exam sessions
Session From To
sessione invernale Jan 10, 2022 Feb 18, 2022
sessione estiva May 23, 2022 Jul 1, 2022
sessione autunnale Aug 22, 2022 Sep 23, 2022
Degree sessions
Session From To
sessione autunnale (validità a.a. 2020/2021) Dec 6, 2021 Dec 10, 2021
sessione invernale (validità a.a. 2020/2021) Apr 6, 2022 Apr 8, 2022
sessione estiva (validità a.a. 2021/2022) Sep 5, 2022 Sep 6, 2022

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 M N P R S V Z

Bertoli Paola

paola.bertoli@univr.it 045 8028 502

Brunetti Federico

federico.brunetti@univr.it 045 802 8494

Buccheri Giuseppe

giuseppe.buccheri@univr.it 045 8028525

Bucciol Alessandro

alessandro.bucciol@univr.it 045 802 8278

Campolmi Alessia

alessia.campolmi@univr.it 045 802 8071

Chesini Giuseppina

giusy.chesini@univr.it 045 802 8495 (VR) -- 0444/393938 (VI)

Ciampi Annalisa

annalisa.ciampi@univr.it 045 802 8061

Cipriani Giam Pietro

giampietro.cipriani@univr.it 045 802 8271

De Sinopoli Francesco

francesco.desinopoli@univr.it 045 842 5450

Di Caterina Claudia

claudia.dicaterina@univr.it 0458028247

Fratea Caterina

caterina.fratea@univr.it 045 802 8858

Gaudenzi Barbara

barbara.gaudenzi@univr.it 045 802 8623

Matteazzi Eleonora

eleonora.matteazzi@univr.it 045 8028741

Menon Martina

martina.menon@univr.it 045 802 8420

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Nicodemo Catia

catia.nicodemo@univr.it

Pellegrini Letizia

letizia.pellegrini@univr.it 045 802 8345

Perali Federico

federico.perali@univr.it 045 802 8486

Pertile Paolo

paolo.pertile@univr.it 045 802 8438

Picarelli Athena

athena.picarelli@univr.it 045 8028242

Piovesan Marco

marco.piovesan@univr.it 045.80.28.104

Roffia Paolo

paolo.roffia@univr.it 045 802 8012

Scricciolo Catia

catia.scricciolo@univr.it 045 802 8341

Sommacal Alessandro

alessandro.sommacal@univr.it 045 802 8716

Stacchezzini Riccardo

riccardo.stacchezzini@univr.it 045 802 8186

Vannucci Virginia

virginia.vannucci@univr.it

Zago Angelo

angelo.zago@univr.it 045 802 8414

Zoli Claudio

claudio.zoli@univr.it 045 802 8479

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
B
(SECS-P/05)
One module between the following
3
F
(-)
ModulesCreditsTAFSSD
Two modules among the following
6
C
(SECS-P/03)
6
C
(SECS-P/02)
Two modules among the following
6
B
(SECS-P/11)
One module between the following

1° Year

ModulesCreditsTAFSSD
9
B
(SECS-P/05)
One module between the following
3
F
(-)

2° Year

ModulesCreditsTAFSSD
Two modules among the following
6
C
(SECS-P/03)
6
C
(SECS-P/02)
Two modules among the following
6
B
(SECS-P/11)
One module between the following
Modules Credits TAF SSD
Between the years: 1°- 2°
Between the years: 1°- 2°

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

4S02464

Credits

9

Scientific Disciplinary Sector (SSD)

SECS-P/05 - ECONOMETRICS

Language

English en

Period

secondo semestre (lauree magistrali) dal Feb 21, 2022 al May 13, 2022.

Learning outcomes

The course provides an overview of the main econometric tools, with particular emphasis on economic applications, developed interactively using professional packages. The program covers standard econometric models (OLS regression and its diagnostics) as well as more advanced models for the analysis of cross-sectional, time series and panel data (IV, probit, tobit, random and fixed effects). Particular attention will be given to the intuition behind each topic, in addition to more formal issues. Towards the end of the course a voluntary assignment will be proposed, with the aim of translating research questions into empirical analyses, applying on real data the tools learnt in class, and stimulating discussion among students. At the end of the course, students should be able to: i) read and critically interpret empirical works developed by other researchers, ii) manage small and large datasets in order to extract useful information, and iii) design and implement on their own empirical analyses based on real data.

Program

1) Introduction
1.1) What is Econometrics?
Definition; cross-section, time series and panel data.
1.2) R tutorial
Data management; basic statistics; graphics.

2) Ordinary Least Squares (OLS) Estimator
2.1) Introduction
Univariate and multivariate regression; marginal effects and elasticity; R-squared and adjusted R-squared; outliers.
2.2) Properties
Gauss-Markov assumptions; unbiasedness; efficiency; consistency; asymptotic normality.
2.3) Testing
t-test on one restriction; F test on several restrictions.

3) OLS Diagnostics
3.1) Specification
Collinearity; superfluous and omitted variables; RESET test of specification; Chow test of structural stability.
3.2) Heteroskedasticity
White test and Breusch-Pagan test; White robust standard errors.

4) Instrumental Variable (IV) Estimator
4.1) Estimator
Assumptions; Simple instrumental variable (SIV) and generalized instrumental variable (GIV); properties; two-stage derivation (2SLS).
4.2) Instrument selection
Relevance test; weak instruments; Sargan validity test; Hausman exogeneity test.

5) Limited Dependent Variable (LDV)
5.1) Binary dependent variable
Linear probability model (LPM); probit and logit models; marginal effects; maximum likelihood estimate; goodness of fit; hypothesis testing.
5.2) Truncated and censored data
Truncated regression; tobit-I model; tobit-II and heckman models; marginal effects; goodness of fit.

6) Further types of data
6.1) Time series
Stationarity; AR processes; Durbin-Watson and Breusch-Godfrey tests; Newey-West robust standard errors.
6.1) Panel data
Diff-in-diff; Pooled effects, fixed effects and random effects; goodness of fit; comparison tests; attrition.

Lecture method: frontal teaching

Bibliografia

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.

Examination Methods

The exam is written; no oral integration is planned.
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 80% and 20% weights respectively. In order to pass the exam, it is necessary to obtain a grade not below 16/30 in the written essay. Students can separately reject the essay grade and the homework grade. However, the homework grade can be rejected only once.
The written essay lasts one hour and thirty minutes and covers the whole program of the course. Use of handheld calculators is allowed, but use of personal notes or other teaching material is not allowed.
The homework is developed individually, and can be of two types (Homework I or Homework II). Homework I aims to develop analytical skills through personal data analysis. Homework II aims to develop critical skills with respect to empirical applications. Each student can choose which type of homework to deliver, but must deliver one of them. Once the deadline for delivery of Homework I has expired, it is possible to deliver Homework II only. The homework has to be delivered before taking part in the written essay; its grade remains valid throughout the academic year.

Type D and Type F activities

1° periodo lezioni (1A) From 9/16/21 To 10/30/21
years Modules TAF Teacher
1° 2° The fashion lab (1 ECTS) D Caterina Fratea (Coordinatore)
1° 2° The fashion lab (2 ECTS) D Caterina Fratea (Coordinatore)
1° 2° The fashion lab (3 ECTS) D Caterina Fratea (Coordinatore)
primo semestre (lauree) From 9/20/21 To 1/14/22
years Modules TAF Teacher
1° 2° Marketing plan D Virginia Vannucci (Coordinatore)
Periodo generico From 10/1/21 To 5/31/22
years Modules TAF Teacher
1° 2° Data Analysis Laboratory with R (Verona) D Marco Minozzo (Coordinatore)
1° 2° Data Visualization Laboratory D Marco Minozzo (Coordinatore)
1° 2° Python Laboratory D Marco Minozzo (Coordinatore)
1° 2° Data Science Laboratory with SAP D Marco Minozzo (Coordinatore)
1° 2° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° Programming in Matlab D Marco Minozzo (Coordinatore)
1° 2° Programming in SAS D Marco Minozzo (Coordinatore)
1° 2° Samsung Innovation Camp D Marco Minozzo (Coordinatore)
primo semestre (lauree magistrali) From 10/4/21 To 12/17/21
years Modules TAF Teacher
1° 2° Business & Predictive Analytics for International Firms (with Excel Applications) - 2021/2022 D Angelo Zago (Coordinatore)
1° 2° What paradigms beyond the pandemic? Individual vs. Society, Private vs. Public D Federico Brunetti (Coordinatore)
1° 2° Data Discovery for Business Decisions- 2021/2022 D Claudio Zoli (Coordinatore)
1° 2° Elements of Financial Risk Management - 2021/2022 D Claudio Zoli (Coordinatore)
1° 2° English for business and economics F Claudio Zoli
1° 2° Integrated Financial Planning D Riccardo Stacchezzini (Coordinatore)
1° 2° Introduction to Business Plan- 2021/2022 D Paolo Roffia (Coordinatore)
Modules borrowed from the Faculty of Scienze matematiche fisiche e naturali
1° periodo lezioni (1B) From 11/5/21 To 12/16/21
years Modules TAF Teacher
1° 2° The fashion lab (1 ECTS) D Caterina Fratea (Coordinatore)
1° 2° The fashion lab (2 ECTS) D Caterina Fratea (Coordinatore)
1° 2° The fashion lab (3 ECTS) D Caterina Fratea (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° How to Enter in a Foreign Market. Theory and Applications - 2021/2022 D Angelo Zago (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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Internships


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Doppio Titolo

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Graduation


Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.