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..

Academic year:
Definition of lesson periods
Period From To
primo semestre Sep 23, 2013 Jan 10, 2014
secondo semestre Feb 17, 2014 May 30, 2014
Exam sessions
Session From To
Sessione Invernale Esami Jan 13, 2014 Feb 15, 2014
Sessione Estiva esami Jun 3, 2014 Jul 12, 2014
Sessione Autunnale Esami Aug 25, 2014 Sep 10, 2014
Degree sessions
Session From To
Sessione di Lauree - Novembre Nov 7, 2013 Nov 8, 2013
Sessione di Lauree - Aprile - Verona Apr 9, 2014 Apr 10, 2014
Sessione di Lauree - Settembre Sep 11, 2014 Sep 12, 2014
Holidays
Period From To
Vacanze Natalizie Dec 23, 2013 Jan 4, 2014
Vacanze Estive Aug 11, 2014 Aug 23, 2014

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 G L M N P R S V Z

Bucciol Alessandro

alessandro.bucciol@univr.it 045 802 8278

Chesini Giuseppina

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

Cipriani Giam Pietro

giampietro.cipriani@univr.it 045 802 8271

De Sinopoli Francesco

francesco.desinopoli@univr.it 045 842 5450

Gaudenzi Barbara

barbara.gaudenzi@univr.it 045 802 8623

Levati Maria Vittoria

vittoria.levati@univr.it 045 802 8640

Milano Enrico

enrico.milano@univr.it +39 045 8028836

Noto Sergio

elefante@univr.it 045 802 8008

Pellegrini Letizia

letizia.pellegrini@univr.it 045 802 8345

Perali Federico

federico.perali@univr.it 045 802 8486

Peretti Alberto

alberto.peretti@univr.it 0444 393936 (VI) 045 802 8238 (VR)

Pertile Paolo

paolo.pertile@univr.it 045 802 8438

Ricciuti Roberto

roberto.ricciuti@univr.it 0458028417

Roffia Paolo

paolo.roffia@univr.it 045 802 8012

Sartor Nicola

nicola.sartor@univr.it

Vaona Andrea

andrea.vaona@univr.it 045 8028537

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
A course to be chosen among the following
6
B
SECS-P/11
6
B
SECS-P/08
A course to be chosen among the following
Final examination
15
E
-

2° Year

ModulesCreditsTAFSSD
A course to be chosen among the following
6
B
SECS-P/11
6
B
SECS-P/08
A course to be chosen among the following
Final examination
15
E
-
Modules Credits TAF SSD
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

Language

English en

Scientific Disciplinary Sector (SSD)

SECS-P/05 - ECONOMETRICS

Period

primo semestre dal Sep 23, 2013 al Jan 10, 2014.

Learning outcomes

The course provides an overview of the main econometric tools, with particular emphasis on economic applications, developed interactively in class using the professional software Stata™.
After a short introduction on the purpose of Econometrics and the basic commands in Stata, the program is divided in five parts. The first part (OLS) introduces to the standard econometric method, ordinary least squares regression. The second part (OLS diagnostics) describes the main statistical tests on OLS estimates, as well as diagnostic tests on heteroscedasticity and wrong specification of the functional form. The third part (time series) presents tests on autocorrelation, and lists the models commonly used in the context of time series data. The fourth part (IV) discusses the problem of endogeneity and the instrumental variable estimators. The fifth part (extensions) introduces microeconometric models suited for binary dependent variables (probit, logit), and for panel data (random effects, fixed effects).

Program

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

2) Ordinary Least Squares (OLS) Estimator
2.1) Introduction
Univariate and multivariate regression; marginal effects and elasticity.
Example: House prices
2.2) Goodness of fit
R2, adjusted R2, AIC and BIC criteria; forecast; outliers.
Example: Forecasting stock returns
2.3) Properties
Gauss-Markov assumptions; unbiasedness; efficiency; consistency; asymptotic normality.

3) OLS Diagnostics
3.1) Testing
t-test on one restriction; F test on several restrictions.
Example: Capital asset pricing model
3.2) Specification
Collinearity; superfluous and omitted variables; RESET test of specification; Chow test of structural stability.
3.3) Heteroscedasticity
White test and Breusch-Pagan test; White robust standard errors.
Example: Risk profile

4) Time Series
4.1) Autocorrelation
Durbin-Watson test and Breusch-Godfrey test; Newey-West robust standard errors.
Example: Ice cream consumption
4.2) Modeling
Auto-Regressive (AR), Moving-Average (MA) and ARMA processes.
Example: GDP and consumption

5) Instrumental Variable (IV) Estimator
5.1) Motivation
Autocorrelation and lagged dependent variable; measurement error; omitted variables; simultaneity.
5.2) Estimator
Assumptions; Simple instrumental variable (SIV) and generalized instrumental variable (GIV); properties; two-stage derivation (2SLS).
Example: Women wage function
5.3) Instrument selection
Relevance test; weak instruments; Sargan validity test; Hausman exogeneity test.
Example: Returns to schooling

6) Extensions (Microeconometrics)
6.1) Binary dependent variable
Linear probability model (LPM); probit and logit models; marginal effects; maximum likelihood estimate; goodness of fit; hypothesis testing.
Example: Bus tickets
6.2) Panel data
Pooled effects, fixed effects and random effects; goodness of fit; comparison tests.
Example: Waste sorting

Suggested material:
- Course slides, available on eLearning.
- Verbeek, M., A Guide to Modern Econometrics, Wiley, 2000 or following editions.

Reference texts
Author Title Publishing house Year ISBN Notes
Marno Verbeek A Guide to Modern Econometrics (Edizione 4) John Wiley and Sons 2012 978-1-119-95167-4

Examination Methods

The exam is written. The final grade is based on one mandatory final exam and one voluntary homework (assigned in the middle of the semester). The final exam includes theoretical, numerical and applied exercises on all the topics covered in class; the homework includes theoretical and applied exercises on the topics covered in the first half of the class meetings. Applied exercises require the use of Stata.
During the final exam it will be allowed the use of handheld calculators, but not the use of textbooks or teaching notes.
The homework adds 1 bonus point to the final grade and accounts for 10% of the final grade.

Bibliography

Type D and Type F activities

Academic year:

Modules not yet included

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.

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.


Area riservata studenti


Internships


Graduation

List of theses and work experience proposals

theses proposals Research area
La (cattiva) gestione dei fondi comunitari in Italia ECONOMICS - ECONOMICS
Analisi dell'Impatto della Regolamentazione: potenziale e applicazioni concrete Various topics
Costs and benefits of the new Turin-Lyon railway line Various topics
Costs and benefits of new systems for speed control on italian motorways Various topics
Contingent valuation for the quality of hospital characteristics Various topics
Evaluating occupational impacts of large investment projects Various topics

Linguistic training CLA


Gestione carriere


Admission policy

ADMISSION POLICY

The admission procedure for international students is explained in details at:
www.magecverona.it/admission-benefits/
For further information please contact magec@dse.univr.it


Additional information

 

Additional information

For further information visit the program website, http://magec.dse.univr.it, or send an email at magec@dse.univr.it.