86530 - Econometrics

Academic Year 2023/2024

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: First cycle degree programme (L) in Economics and Finance (cod. 8835)

Learning outcomes

In this course the student learns the basic econometric tools useful for a proper empirical analysis of economic phenomena. At the end of the course the student is able to: - Critically evaluate the application and empirical economic literature; - Apply the basic econometric methods to conduct empirical analysis (forecasts and estimates) in the economic field with the use of an appropriate econometric software.

Course contents

Topics discussed during the first part of the course (first subcycle):

1. Introduction to econometrics

2. Review of probability and statistics

3. The simple linear regression model

3.1 Least squares estimation: definition and properties

3.2 Interval estimation and hypothesis testing

3.3 Forecasting, goodness of fit and specification issues

4. The multiple linear regression model

4.1 Nonlinear in variables models and the use of interaction variables

4.2 Joint test of linear constraints on the parameters

4.3 Specification analysis

4.4 Use of nonsample information and collinearity

Topics discussed during the second part of the course (second subcycle):

5. Heteroskedasticity

6. Dynamic models and autocorrelation

7. Endogeneity and instrumental variables

8. Panel data models

8.1 Fixed effects

8.2 Random effects

8.3 Hausman-Taylor estimator


R. C. Hill, W. E. Griffiths, G. C. Lim, "Principles of Econometrics" (5th edition), Wiley 2018.

The slides used during classes, sketches of training sessions, exercises solutions and mock exams will be made available for download from Virtuale.

Teaching methods

Lecture and individual practice in the class.

For each topic we will first introduce the relevant theory, and then move as soon as possible to its empirical application. Special emphasis will be placed on the economic interpretation of the results. Attending classes is important especially to learn the empirical topics of the course. At the end of each lecture an exercise will be assigned to students and its solution will be discussed at the start of the following lecture. These "at home" exercises do not concur to the final grade.

Assessment methods

The exam, which is partly theoretical and partly empirical, tests the ability to apply the methods learnt to simulated or real data, using the R software, the acquired knowledge of the theoretical concepts and the ability to interpret estimation results in the light of the underlying theory.

Both the midterms and the total are written. It lasts one hour and it is composed of two distinct sections.

The first one is mainly theoretical, and it contains 5 multiple choice questions. The second one is mainly empirical, and it contains 11 questions whose answers shoud be computed using R and knowledge of the empirical analysis discussed during classes. Whatever the section, each correct answer yields two points; no penalty is applied to wrong answers. The final mark is the total number of point obtained in the two sections.
During the exam it is forbidden to consult notes, slides, books, pocket calculators and any other electronic devices. The purpose of the exam is to ascertain that students acquired the knowledge required to correctly specify, estimate and test the econometric models discussed during the lectures and possess the ability to properly interpret the results provided by these procedures.

Students can reject the grade obtained at the exam once. To this end, he/she must email a request to the instructor within the date set for registration. The instructor will confirm reception of the request within the same date.

Rejection is intended with respect to the whole exam, whose grade is the average of the grades obtained in the two mid-terms. If the grade is rejected, the student must retake the full exam (consisting of both parts). The only grade that can be rejected without any communication from the student is the one of the first mid-term: in this case the student can either take the second mid-term or sit the full exam (thus losing the grade obtained in the first mid-term).

Students sitting the first mid-term can take the second mid-term on the first examination date set for the full exam, right at the end of the course, or on the following call. A student can sit the second mid-term only once; if he/she fails or rejects the grade obtained, he/she will have to resit the full exam and will lose the grade obtained in the first mid-term.

In case online exams will be envisaged by the University of Bologna, the structure of the written exam is the same. The exam will be run through Zoom and Exams Online (EOL). Detailed instructions on how to manage and hand in the online exam will be available on the course page on the VIRTUALE platform.

The maximum possible score is 30 cum laude, in case all anwers are correct, complete and formally rigorous.

The grade is graduated as follows:

<18 failed
18-23 sufficient
24-27 good
28-30 very good
30 e lode excellent

Teaching tools

Dedicated page on the VIRTUALE platform containing:

  • News and updated information
  • Lectures slides
  • R lab material

Office hours

See the website of Sergio Pastorello