Academic Year 2021/2022

Learning outcomes

At the end of the course the student has adequate knowledge of the basic instrument used by economists for their empirical investigations (the linear regression model for the analysis of cross-sectional data) and is able to understand under what conditions the estimated relationship has a causal interpretation. Drawing on critical discussion about some micro-economic applications from recent research, the student receives specific data to practice at the computer and learn the basic skills to perform empirical work using the software GRETL. At the end of the course he/she is capable to understand scientific articles using the linear regression model and is also able to perform its own analysis with this instrument.

Course contents

The course is articulated according to the points below.

  • What is econometrics? The research question and the different types of data
  • The linear regression model and the OLS estimator: the assumptions of the method
  • Validate and interpred the OLS: specification tests and estimated results in simple and multiple regression models
  • What to do when OLS assumptions are no longer valid? The generalised least squares and instrumental variables approaches.
  • A brief introduction to panel data methods

Readings/Bibliography

The material (articles, notes, programs and data-sets) will be distributed during the lectures and make available on the platform Virtuale.

The reference textbook is:
Wooldridge J.M. 2020 Introductory Econometrics. A Modern Approach, Cengage, 7th Edition.

Teaching methods

To provide a smooth transition from theory to practice in the
discipline of econometrics, theoretical lectures are associated with working sessions. During the hands-on empirical applications, students will use the laptop, an econometric software (Gretl is free, while Stata is available using the CAMPUS license and students' university credentials).
At the end of the course, participants will be able to critically evaluate articles that present empirical analyses, and to model and estimate their regression of interest, with the most appropriate methods based on the problem they face.

Assessment methods

Students will have a written examination on theoretical and applied issues, with open ended questions aimed at assessing their capacity in understanding models' specifications and estimated results, and in evaluating the strengths and weaknesses of alternative estimating methods. During the exam students will use the computer and the econometric software.

According to the pandemic situation, the exams could be either in presence or online, but this will not alter the assessment methods.
Students have to register in Almaesami so as to receive the link to the virtual class in Zoom. Also, students will have to access to EOL (Exams Online) by using their institutional credentials.

The possible grades are:
< 18 failed
18-23 sufficient
24-27 good
28-30 very good
30L (cum laude) excellent


Teaching tools

Theoretical lectures are associated with working sessions; during them students will receive the suggestions needed to run their own empirical analysis. The data-sets and the programming files to perfom applied analyses will be provided during the lectures. The distributed material (articles, notes, programs, and data-sets) will be make available on the Virtuale platform.

Software STATA: click here

Denis Malaj (denis.malaj@studio.unibo.it) is the tutor who will present some more applications to help students in understanding econometrics.

Links to further information

https://sites.google.com/site/mariaelenabontempi/home/teaching/econometrics

Office hours

See the website of Maria Elena Bontempi

See the website of Annalisa Stacchini