- familiarize the students with contemporary methods of panel data analysis, starting with the pooled OLS model and ending with dynamic panel data models
- Students should have a firm grasp of the key methods of panel data analysis
- 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).
- 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
- homework assignmentThe home assignment includes problems and/or computer exercises in Stata. The assignment will be distributed in class and will be due in approximately two weeks. The homework (only paper versions, files sent by email will not be accepted!) is to be handed in before class on the day it is due. No late homework is accepted
- midterm examThe midterm exam is a closed book, closed notes test scheduled in the middle of the course
- final examAt the end of the course there is a final exam, which is a closed book, closed notes test to be held in the classroom. The duration of the final exam is two academic hours.
- Interim assessment (4 module)0.5 * final exam + 0.25 * homework assignment + 0.25 * midterm exam
- 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
- 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