Using Stata to run Panel Data

LecturerDr. habil. Souhir Neifar
Date01.12./02.12.2022
(09:00 am – 03:00 pm each day)
Room/Adress TU Dresden (PC-Pool)
(organized by TU Chemnitz)
Seminar contentThis course aims to study how to use Stata software to run panel data. Within this course, students will be able to:
  • Prepare panel data and make panel data in Stata,
  • Verify the multicollinearity using Pearson correlation,
  • Run a fixed effect model.
  • Run random effect model.
  • Use the Hausman test
  • Use the normality test
  • Use Wald modified test to verify the heteroskedasticity problem
  • Use the Wooldridge test (2002) to test the autocorrelation problem
  • Correct the heteroskedasticity and autocorrelation problems
  • Interpret the different tests and the results of the Model.
At the end of this seminar, students will be able to recognize data and use Stata to run panel models. Students will be able also to interpret the different tests and results.
The students need to have data and statistic tables to interpret the results. All needed documents will be given by the lecturer. In addition, the lecturer will give the students a data and they will apply all the tests and steps using Stata on this data.
Toward the end of the seminar, participants will be asked to develop and present an initial design for a future study of their choosing. There will be two mandatory reading assignments. Participants are expected to read the assigned book and paper prior to attending the seminar.
CertificatePh.D. students from the Faculty of Economics, TU Dresden can earn a certificate according to § 9 of the Ph.D. doctoral regulations (PromO 2018):
Ph.D. students of Business Management: § 9 (1) Nr. 5 or 6
Ph.D. students of Business Informatics: § 9 (1) Nr. 6
Ph.D. students of Economics: § 9 (1) Nr. 6

Ph.D. students from other universities can earn a certificate as well.
Assignment1) Reading of/familiarization with preassigned articles and books
Mandatory Readings:
  • Arellano, M. (2003). Panel data econometrics. Oxford university press.
  • Neifar, S., & Utz, S. (2019). The effect of earnings management and tax aggressiveness on shareholder wealth and stock price crash risk of German companies. Journal of Applied Accounting Research.
Additional Readings:
  • Hsiao, C. (2014). Analysis of panel data (No. 54). Cambridge university press.
2) Upload all documents: the data (excel form) and statistic tables that will be sent by the lecturer to all participants before the course.
3) Each participant will be asked to do all tests in Stata with the PC
RegistrationParticipation is limited to 15. 
To register send an e-mail to Dr. Uta Schwarz: uta.schwarz@tu-dresden.de
Phone: +49 351 463-33141