37304 - Econometrics Models

Learning outcomes

This course introduces students to basic linear regression models, useful for the analysis of cross-sectional and time series data used by business decision makers as a tool supporting the decision making process. In particular, the student will acquire the ability to understand and critically evaluate the application of the various methods in the recent empirical literature and to apply the statistical and econometric tools discussed during the lectures to the analysis of business data using the econometric software Stata.

Course contents

1. Introduction to econometrics

2. Review of probability and statistics

3. The simple linear regression model

4. Statistical inference in the simple linear regression model

5. Linear regression with multiple regressors

6. Statistical inference in the linear regression model with multiple regressors

7. Nonlinear regression functions

8. Assessing studies based on multiple regression

9. Regression with panel data

10. Regression with a binary dependent variable

11. Instrumental variables regression

Readings/Bibliography

Stock, J. e M. Watson, Introduzione all'Econometria (5a edizione), Pearson, 2020.

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.

Assessment methods

The exam, partly theoretical and partly empirical, aims to assess the ability to apply the methodologies acquired in the classroom and through individual study to simulated or real data. It also evaluates the understanding of theoretical concepts and the skill to interpret estimation results by connecting them to underlying concepts.

There are no midterm exams during the course. The final exam at the end of the course will be based on the entire program and will consist solely of written tests. During the tests, only one handwritten A4 sheet (2 sides) prepared by the student may be consulted; photocopies, prints, or any electronic devices are not allowed.

It is possible to reject the grade only once. To do so, the request must be communicated via email to the instructor by the date of verbalization. The instructor confirms the receipt of the request by the same date.

The final exam lasts 1.5 hours, consisting of a theoretical part (3 true/false questions and two open-ended questions) and a practical part (5 interpretation and commentary questions based on a brief empirical analysis similar to those done in class or from STATAoutput provided at the beginning of the exam). The evaluation of individual questions will be communicated in the test text.

It is always possible to withdraw at any time during an exam by sending an email to the instructor before the conclusion of the exam, communicating the decision to withdraw.

Concerning the use of generative AI during the exam, this course adopts Option 1 among those foreseen by the University: the use of AI is forbidden; any use of AI will be considered a violation of academic integrity.

The maximum score achievable by providing all correct, complete, and appropriately formal answers is 30 cum laude. Grading scale:

<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
• STATA lab material

Software STATA: can be installed on students' personal computers (CAMPUS license) and is available at the Computer Lab of the School of Economics and Management.

Office hours

See the website of Andrea Carlo Michele Ichino