INTRODUCTION TO ECONOMETRICS-1

This course falls under the fundamental teaching activities of the bachelor's course "Economia e Commercio". In line with the course's educational objectives, this activity aims to present the main mathematical and statistical tools necessary for analyzing economic phenomena; particular attention will be devoted to the use of formal language and methodological rigor. More specifically, the course aims to provide an introduction to econometric techniques that are essential for the correct interpretation of estimates and tests in dynamic equations. The students will approach the model specification strategies through simulations of economic and financial series. By the end of the course, students will be able to understand and manage univariate linear models estimated by standard econometric software (like Excel, EViews, and Gretl).

Knowledge and understanding skills.
Attendance and active participation in lectures, online activities, exercise sessions, tutoring activities, together with the individual study will allow the student to acquire the following knowledge and understanding skills:
- know and use the main mathematical tools necessary to represent complex economic phenomena;
- know the mathematical techniques useful to solve and analyze the proposed models.

Ability to apply knowledge and understanding.
Through the interaction with the instructors, the tutors, and peers and through the individual study the student acquires the following abilities:
- know how to use quantitative instruments to cope with complex problems related to an economic / business environment;
- know how to choose the most appropriate technique in order to solve the concrete problem under analysis.

Judgment skills, communication skills, learning skills.
Regarding the autonomy of judgment, communication skills and learning abilities, through the personal and group study of the concepts seen in class, the student will be able to:
- formulate rational justifications to the approach used to solve economic / business problems, understanding their relative strengths and weaknesses, by means of hypotheses, data and models;
- know how to formulate and communicate an adequate analysis and interpretation of economic-financial data through the use of mathematical models.

Mandatory priority exam: see https://www.unive.it/web/en/4624/exams

Problems faced by the econometrician. Types of data and of econometric models.
Recalls from sample estimation and testing theory. Recall of linear algebra.
Linear regression model and ordinary least squares. Goodness of fit and test of significance.
Univariate time series models. ARMA processes. Stationarity and unit roots tests.
Selecting regressors. Specification tests.
Heteroskedasticity and Autocorrelation. Generalised least squares.
Static and dynamic forecasts.

Johnston J., Econometrica, 3a ristampa 2010, 5a edizione 2001, Franco Angeli, Milano

Other references:
Cappuccio N. e R. Orsi, Econometria, Il Mulino, 2005
Marcellino M., Econometria Applicata, Egea, Milano 2006
Vogelvang B., Econometrics - Theory and Applications with EViews, FT Prentice Hall, 2005
Guala F. (2006), Filosofia dell'economia - Modelli, causalita, previsione, Il Mulino

Assessment of learning is conducted through a written exam, which may be supplemented by an optional practical assignment (subject to evaluation). The written exam covers basic concepts of econometrics. The practical assignment involves applying the learned concepts to data. The individual practical assignment is optional. Examples of practical assignments and past exam papers are available among the course materials.

Written exam
The written exam consists of exercises on basic theoretical concepts in econometrics and on examples of hypothesis testing. It includes up to four exercises to be completed within one and a half hours. The use of the textbook is allowed during the exam (open book).

Practical assignment (optional)
The practical assignment is optional and involves developing a linear regression model using a real dataset, with the econometric software GRETL. The assignment must be submitted via the Moodle platform by the end of the course, within the specified deadlines, and discussed with the instructor after passing the written exam with a grade equal to or above 18. The outcome of the discussion may result in a decrease or an increase of up to 2 points in the score obtained on the written exam.

written and oral

The instructor is responsible for ensuring the authenticity and originality of all examinations and coursework. In cases of suspected academic misconduct, an additional on-site assessment may be required during the exams, which may differ from the standard format.

As regards the gradation of the grade (how the grades will be assigned), regardless of the attending or non-attending mode:

A. scores in the 18-22 range will be awarded in the presence of:
- sufficient knowledge and ability to understand and apply in relation to the programme;
- limited ability to interpret the exercise and provide arguments regarding its resolution;

B. scores in the 23-26 range will be awarded in the presence of:
- reasonable knowledge and ability to understand and apply in relation to the programme;
- reasonable ability to interpret the exercise and provide arguments regarding its resolution;

C. scores in the 27-30 range will be awarded in the presence of:
- good or excellent knowledge and ability to understand and apply in relation to the programme;
- good or excellent ability to interpret the exercise and provide arguments regarding its resolution;

D. honours will be awarded in the presence of excellent knowledge and applied understanding of the course content, as well as outstanding judgment and communication skills.

Traditioanl lectures, practice sessions, and tutorials.

Assessment
Written exam on the estimation results of an univariate linear model and solutions of elementary econometric problems. Part of the final note may also depend on a practical exercise, which is not compulsory.

This subject deals with topics related to the macro-area "Climate change and energy" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development