We use cookies in order to improve the quality and usability of the HSE website. More information about the use of cookies is available here, and the regulations on processing personal data can be found here. By continuing to use the site, you hereby confirm that you have been informed of the use of cookies by the HSE website and agree with our rules for processing personal data. You may disable cookies in your browser settings.

✖
  • A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
For visually-impairedFor visually-impairedUser profile (HSE staff only)SearchMenu
HSE University
User profile (HSE staff only)Search
Advanced search

Course Syllabus

Course Syllabus


 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Master 2024/2025

Panel Data

Type: Compulsory course (Data Analytics for Business and Economics)
Delivered by: Department of Economics
When: 2 year, 3 module
Open to: students of one campus
Instructors: Dmitry Kislitsyn
Language: English

Course Syllabus

Full SyllabusAsk Question

Abstract

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

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

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

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

Assessment Elements

  • non-blocking Project Work
  • non-blocking In-class Participation
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • 2024/2025 3rd module
    0.5 * Exam + 0.25 * In-class Participation + 0.25 * Project Work
Bibliography

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

Authors

  • POLYAKOVA EVGENIYA YUREVNA
  • BRODSKAYA NATALYA NIKOLAEVNA
  • Muravev Aleksandr Aleksandrovich