34481 - Econometrics 2

Academic Year 2021/2022

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Economics (cod. 8408)

Learning outcomes

At the end of the course the student has acquired knowledge of the core microeconometric models and methods designed to study the behaviour of economic agents using cross-section and panel data, including static paneld data models, instrumental variable methods, and the most widely used limited dependent variable modes. In particular, he/she is able: - to critically understand the applications of these models in the recent empirical economic literature; - to apply the models and perform his/her own analysis of economic datasets using the software STATA.

Course contents

  • Pooling cross sections across time
  • Linear panel data methods
  • Instrumental variables and two stages least squares
  • Maximum likelihood methods
  • Limited dependent variable models
  • Sample selection corrections
  • Laboratory sessions devoted to the application to real data of different methods using the software STATA

Readings/Bibliography

References

  • Jeffrey M. Wooldridge (2020). Introductory Econometrics: a Modern Approach, Seventh edition, CENGAGE (the Sixth edition is also valid).
  • Jeffrey M. Wooldridge (2010). Econometric Analysis of Cross Section and Panel Data, 2nd edition, MIT Press.

Suggested additional reference:

  • Chris Baum, An Introduction to Modern Econometrics Using Stata, Stata Press

On the VIRTUALE platform students can access to:

  • Lectures slides
  • An Example of exam text
  • Files for the STATA lab sessions

Teaching methods

During the lectures, the presentation of theoretical issues will be complemented by critical discussion of some micro-economic applications from recent research using linear regression models.

Students will receive data to practice at the computer and learn how to apply the various models using the software STATA, which is available to them  through the CAMPUS license.

Students will receive take home problem sets, to be solved in small groups and handed in with specific deadlines. These homework require data analysis work and writing short essays.

 

Assessment methods

There are two components of the course assessment: take home assignments and written exam.

Take home exercises are computer based, and they test the ability to apply the methods learnt  to simulated or real data, using STATA.

The written exam aims at testing the acquired knowledge of the theoretical concepts and the ability to interpret estimation results in the light of the underlying theory.

The average mark of the homeworks will account for the 40% of the final mark.

The written exam is closed book. It is divided in three parts:

  • True or False (answer with concise motivation): 3 questions, 12 points
  • Open question (formal answer to theoretical question): 1 or 2 questions, 8 points
  • Interpretation question (answer on STATA log file with estimation output): 2 or 3 questions, 10 points

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 are 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

For students attending the Master in Economics LMEC the Econometrics 2 grades will contribute to the final grade of the integrated course Econometrics I.C. The latter is obtained as the average of the grades of Econometrics 2 and Econometrics 3 (see the LMEC booklet on the LMEC webpage for detailed information on the integrated courses' exams).

 

 

 

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.

Links to further information

http://sites.google.com/site/chiaramonfardiniwebpage/home/teaching

Office hours

See the website of Chiara Monfardini

SDGs

Quality education Gender equality Decent work and economic growth Reduced inequalities

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.