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.
The Study plan 2007/2008 will be available by May 2nd. While waiting for it to be published, consult the Study plan for the current academic year at the following link.
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.
Quantitative Models for Economic Analyses - ECONOMETRIA (2009/2010)
Teaching code
4S02761
Teacher
Credits
4
Also offered in courses:
- Mathematical Statistics of the course Bachelor's degree in Applied Mathematics
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-P/05 - ECONOMETRICS
Period
1st Semester dal Oct 1, 2009 al Jan 31, 2010.
Location
VERONA
To show the organization of the course that includes this module, follow this link: Course organization
Learning outcomes
Statistic tools and economic theory will be applied in order to provide students with competences and 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 and capabilities needed for the analysis of economic data.
Program
Review of statistical inference.
The linear regression model.
Estimation: ordinary least squares.
Inference and testing.
Model diagnostics.
Time series regression.
Examination Methods
Written exam.
