37534 - Panel Data Analysis

Learning outcomes

The lectures have the aim of providing an overview of microeconometric models, both static and dynamic, for panel data (data on individuals over many periods of time). At the end of the lectures students are expected to be able to: - critically evaluate the applications on panel data presented in the empirical literature; - to apply quantitative methods and use one or more econometric softwares.

Course contents

1. Introduction to panel data; advantages and drawbacks.
2. The problem of heterogeneity and how to deal with it.
3. Static panel data models: one-way and two-ways error components; fixed and random effects; general instrumental variables estimation and Hausman test; Hausman-Taylor estimator.
4. Models with random slopes. Introduction to dynamic panel.

The teaching material is available at the following link:
https://sites.google.com/site/mariaelenabontempi/teaching/analisi-dei-dati-di-panel

Readings/Bibliography

The material (notes and data-sets) will be distributed during the lectures.
Students are invited to have a look at (the order respects the level of difficulty):
Wooldridge  J.M. 2003 Introductory Econometrics. A Modern Approach, Thomson South-Western, Ch. 13-14;
Verbeek M. 2008 A guide to Modern Econometrics, Wiley, 3rd edition, Ch. 10.
For some students may be better to read 1, 2, 3 and  4 chapters of Verbeek.

Teaching methods

Theoretical lectures and applied lectures during which students will work in the InfoLab using the econometric software under the guide of the teacher.

Assessment methods

Attending students will discuss an empirical application with the teacher.

Not attending strudents will have a written examination on theoretical and applied issues.

Teaching tools

Theoretical lectures will be followed by applied lectures; during applied lectures, held in the PC-lab, students are involved in empirical applications and will use the econometric software as well as data-sets. We will discuss together some special topics, including methods for estimating production functions, investment models and corporate capital structure models on companies' account data. Active partecipation to the lectures is highly recommended.

Links to further information

https://sites.google.com/site/mariaelenabontempi/teaching/analisi-dei-dati-di-panel

Office hours

See the website of Maria Elena Bontempi