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 |
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primo semestre triennali | Sep 19, 2016 | Jan 13, 2017 |
secondo semestre triennali | Feb 20, 2017 | Jun 1, 2017 |
Session | From | To |
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Prove intermedie primo semestre | Nov 7, 2016 | Nov 11, 2016 |
Appelli esami sessione invernale | Jan 16, 2017 | Feb 17, 2017 |
Prove intermedie secondo semestre | Apr 10, 2017 | Apr 13, 2017 |
Appelli esami sessione estiva | Jun 5, 2017 | Jul 7, 2017 |
Appelli esami sessione autunnale | Aug 28, 2017 | Sep 15, 2017 |
Session | From | To |
---|---|---|
Sessione autunnale | Nov 30, 2016 | Dec 1, 2016 |
Sessione invernale | Apr 5, 2017 | Apr 7, 2017 |
Sessione estiva | Sep 11, 2017 | Sep 13, 2017 |
Period | From | To |
---|---|---|
Vacanze natalizie | Dec 23, 2016 | Jan 5, 2017 |
Vacanze pasquali | Apr 14, 2017 | Apr 18, 2017 |
Vacanze estive | Aug 7, 2017 | Aug 25, 2017 |
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.
Academic staff
Baronchelli Adelaide
adelaide.baronchelli@univr.itCicogna Veronica
veronica.cicogna@univr.it 045 802 8246Study 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
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2° Year activated in the A.Y. 2017/2018
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3° Year activated in the A.Y. 2018/2019
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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.
Introductory econometrics (2018/2019)
Teaching code
4S02453
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-P/05 - ECONOMETRICS
Period
primo semestre lauree triennali dal Sep 17, 2018 al Jan 11, 2019.
Learning outcomes
The module aims to provide 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 module 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 module 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.
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
Author | Title | Publishing house | Year | ISBN | Notes |
---|---|---|---|---|---|
James H. Stock, Mark W. Watson | Introduzione all'econometria (Edizione 4) | Pearson Education Italia | 2016 | 978-8-891-90124-8 |
Examination Methods
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. In order to pass the exam, it is necessary to obtain a grade not below 16/30 in the written essay.
The written essay is taken in a teaching room, lasts two hours and covers the whole program of the module. It is possible to use a calculator, but neither notes nor other teaching material. It is possible to split the essay in two parts, with each covering about half program. The grade of the essay is given by the simple average of the grades in the two parts. The first-part essay (90 minutes long) is planned in the week devoted to intermediate exams, while the second-part essay (60 minutes long) will be held together with the "primo appello" in January. Students are admitted to the second-part essay provided that their grade in the first-part exam is not lower than 16/30.
The homework is developed individually outside the teaching rooms, and can be of two types (Homework I and Homework II). Each student can choose which type of homework to deliver, but must deliver one of them. Once the deadline for delivery of Homework II has expired, it is possible to deliver Homework I only. The homework grade remains valid throughout the academic year.
Homework I
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 alessandro.bucciol[at]univr.it within the day in which the latest exam of the academic year 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 II
The homework aims to develop analytical skills through personal data analysis in Gretl. Any student interested in this homework must write to the address alessandro.bucciol[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.
Type D and Type F activities
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: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and also via the Univr app.
Graduation
List of thesis proposals
theses proposals | Research area |
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Tesi di laurea - Il credit scoring | Statistics - Foundational and philosophical topics |
Student mentoring
Linguistic training CLA
Gestione carriere
Internships
The curriculum of the three-year degree courses (CdL) and master's degree courses (CdLM) in the economics area includes an internship as a compulsory training activity. Indeed, the internship is considered an appropriate tool for acquiring professional skills and abilities and for facilitating the choice of a future professional outlet that aligns with one's expectations, aptitudes, and aspirations. The student can acquire further competencies and interpersonal skills through practical experience in a work environment.