Panel Data

2022/2023

Academic Year

ENG

Instruction in English

3

ECTS credits

Delivered at:

Department of Economics

Course type:

Compulsory course

When:

3 year, 4 module

Instructors

Zalyubovsky, Evgeny

Muravyev, Alexander

Course Syllabus

Abstract

The course is designed for third-year undergraduate students in Economics. The course is of applied nature: The material is presented, whenever possible, in a non-technical way, with examples of empirical studies published in leading international economics and finance journals discussed in class. Lectures are supplemented by computer labs, which ensures that the students get hands-on experience of analyzing real world panel data using Stata 14/15. The topics covered include: pooled OLS model, fixed- and random-effects models, dealing with unbalanced panels, measurement error in panel data, endogenous explanatory variables, the Hausman-Taylor model, and an overview of dynamic panel data models (the Nickel bias, Anderson-Hsiao estimator and Arellano-Bond estimator).

Learning Objectives

• familiarize the students with contemporary methods of panel data analysis, starting with the pooled OLS model and ending with dynamic panel data models

Expected Learning Outcomes

• Students should be able to effectively apply these methods in own empirical research.
• Students should be familiar with and be able to use key capabilities of the statistical package “Stata”, including its programming options (the so-called do-files).
• Students should have a firm grasp of the key methods of panel data analysis

Course Contents

• Panel data and pooled OLS model
• The fixed effects model
• The random-effects model
• Further topics in the analysis of linear panel data models
• Dynamic panel data

Assessment Elements

• In-class Participation
• Project Work
• Exam

Interim Assessment

• 2022/2023 4th module
  0.25 * Project Work + 0.25 * In-class Participation + 0.5 * Exam

Bibliography

Recommended Core Bibliography

• Patrick Sevestre, & Laszlo Matyas. (2008). The Econometrics of Panel Data. Post-Print. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.p.hal.journl.halshs.00279977

Recommended Additional Bibliography

• David Roodman. (2006). How to Do xtabond2: An Introduction to ‘Difference’ and ‘System. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.BDA319DD
• Mátyás, L. (2017). The Econometrics of Multi-dimensional Panels : Theory and Applications. [N.p.]: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1565303