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.
Study Plan
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea in Matematica applicata - Enrollment from 2025/2026The 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. 2016/2017
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One course to be chosen among the following3° Year activated in the A.Y. 2017/2018
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One/two courses to be chosen among the following| Modules | Credits | TAF | SSD |
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One course to be chosen among the following| Modules | Credits | TAF | SSD |
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One/two courses to be chosen among the following| Modules | Credits | TAF | SSD |
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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.
Econometrics (2017/2018)
Teaching code
4S01951
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-P/05 - ECONOMETRICS
Period
I sem. dal Oct 2, 2017 al Jan 31, 2018.
Learning outcomes
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.
Program
1. Introduction
- Economic questions and data
- Review of probability
- Review of statistics
2. The regression analysis
- Linear regression model: single regressor and multiple regressors
- Ordinary least squares estimation of model coefficients
- Least squares assumptions
- Properties of OLS estimators
- Hypothesis testing and confidence intervals
- Goodness of fit
- Heteroschedasticity and homoschedasticity
- Omitted variable bias
- Generalized least squares
- Nonlinear regression functions
- Assessment of studies based on multiple regression
3. Regression analysis of time series data
- Forecasting
- Autoregression
- Non-stationarity: trend and structural break
- Stationarity in the AR(1) model
- Estimation of dynamic casual effects
| 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
During the exam the students will sit in the computer lab. It will last two hours and will cover the full program of the course. The exam aims at assessing the capabilities of the student for the econometric analysis of cross sectional and time series data. Students will be asked to perform an econometric analysis on a dataset with the software Gretl. Questions on econometric theory will also be assigned.
