Technische Universität Ilmenau

Empirical Research 2 - Modultafeln of TU Ilmenau

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module properties Empirical Research 2 in degree program Master Wirtschaftsingenieurwesen 2021
module number200775
examination number250012
departmentDepartment of Economic Sciences and Media
ID of group 2542 (Economic Policy)
module leaderProf. Dr. Thomas Grebel
term summer term only
languageEnglisch
credit points5
on-campus program (h)34
self-study (h)116
obligationelective module
examexamination performance with multiple performances
details of the certificateDas Modul Empirical Research 2 mit der Prüfungsnummer 250012 schließt mit folgenden Leistungen ab:
  • alternative semesterbegleitende Prüfungsleistung mit einer Wichtung von 50% (Prüfungsnummer: 2500529)
  • alternative semesterbegleitende Prüfungsleistung mit einer Wichtung von 0% (Prüfungsnummer: 2500530)

Details zum Abschluss Teilleistung 1:

50 % takehomes, 25 % mid term paper

Students need to register for the course during the first few weeks of the respective semester at the examination office. The examination office sets the actual deadline for registration. At the beginning of the course, the lecturor informs students about the registration procedure.


Details zum Abschluss Teilleistung 2:

final paper

alternative examination performance due to COVID-19 regulations incl. technical requirements
signup details for alternative examinationsDie Anmeldung zur alternativen semesterbegleitenden Abschlussleistung erfolgt über das Prüfungsverwaltungssystem (thoska) außerhalb des zentralen Prüfungsanmeldezeitraumes. Die früheste Anmeldung ist generell ca. 2-3 Wochen nach Semesterbeginn möglich. Der späteste Zeitpunkt für die An- oder Abmeldung von dieser konkreten Abschlussleistung ist festgelegt auf den (falls keine Angabe, erscheint dies in Kürze):
maximum number of participants
previous knowledge and experience

Mathematics, Statistics, Empirical Research 1

learning outcome

After attending the lectures, students know how to work with simulated as well as real economic data. They are familiar with advanced data analysis topics, such as cross-section, time-series as well as panel-data analyses and understand how to interpret different econometric results.
They understand the idea of linear regression, indicator variables, instrument variables, panel-data and other modern econometric concepts.
By attending the interactive exercises, students know to  conceptualize and perform empirical analyses using Stata and have the necessary skills to carry out their own empirical research.
In the interactive tutorials, students have learned to work on tasks independently, present them to the group, receive immediate feedback from the tutor and fellow students, and how to formulate constructive feedback themselves.
Based on intensive discussions during the lectures and tutorials, students can correctly assess and appreciate the achievements of their fellow students. They consider criticism and accept advice.

content

Generate, interpret, and present descriptive statistics, hypothesis testing, univariate and multivariate linear regression, maximum-likelihood estimation, logistic regression, panel data regession.

media of instruction and technical requirements for education and examination in case of online participation

Slides, Hands-on Stata programming, takehomes

literature / references

Baum, Christopher F. (2006): An introduction to modern econometrics using Stata, Stata Press.
Murray, Michael (2006): Econometrics: A Modern Introduction, Pearson Addison_Wesley.
 Greene, W. H. (2008): Econometric Analysis, 6th Ed. Pearson International.
Wooldridge, Jeffrey M. (2012): Introductory Econometrics: A Modern Approach, 5th Ed. South-Western.

evaluation of teaching