Universität Wien

040081 UE Empirical Methods II (MA) (2019W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

Attendance:

As part of the course grade, your class participation will be assessed every session. You will automatically fail the class if you miss more than 10% of sessions.

Pre-requisites:
For Major: completed Minor
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 30.10. 08:00 - 11:15 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 06.11. 08:00 - 11:15 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 13.11. 16:45 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 20.11. 13:20 - 16:30 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 27.11. 11:30 - 14:45 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 05.12. 09:45 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 11.12. 13:20 - 16:30 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 08.01. 09:45 - 11:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 15.01. 15:00 - 18:15 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock

Information

Aims, contents and method of the course

This course complements “Empirical Methods I” and builds on the knowledge acquired in that introductory class. The goal of this follow-up course is for students to learn how to work with data and analyse it against the backdrop of a given research question. After a brief recap of the contents of “Empirical Methods I”, we will delve into data analysis both in an applied and theoretical manner. Our theory sessions will mainly focus on descriptive and inference statistics for cross-sectional data. Our applied sessions will revisit the programming skills and theoretical know-how of students and introduce data analysis using statistical programming software. Students will participate by reading and presenting scientific articles in some of the highest ranked strategy journals. Knowledge gained in this course and its preceding class “Empirical Methods I” is also applied during a project where students actively conduct their own empirical research.

Assessment and permitted materials

Students will be assessed based on their class participation (class work, home assignments and a presentation of an empirical paper), a written exam and an empirical project (own paper and a presentation of own findings). The final project (including presentation) accounts for 40%, the exam for 30% and class participation accounts for 30% of the final grade.

Minimum requirements and assessment criteria

Please be aware that attendance during the first session of this course is absolutely mandatory. If students miss the first session without contacting the lecturer in writing (at the very latest until 24 hours before the first session), giving a relevant reason/proof (e.g. illness=doctor's certificate, exam=confirmation by the examiner) for their absence, they will be deregistered from the course and their place will automatically be awarded to the next in line on the waiting list. After that, students are allowed to miss 10% of the classes without any consequences (2.25 hours). Exceeding this threshold would result in failing the class. In order to pass the course, at least 50% of the total 100% are required. Please note that TURNITIN will be used in order to test all written coursework (e.g. the final project) for possible plagiarism.
Grading scheme: [0%;50%) [50%;62.5%) [62.5%;75%) [75%;87.5%) [87.5%;100%]

Examination topics

Students are required to know and have understood all topics discussed in class and presented on the lecture slides.

Reading list

Jeffrey M. Wooldridge (2013) Introduction to Econometrics: EMEA Edition
Additional literature will be discussed in class.

Association in the course directory

Last modified: Mo 07.09.2020 15:19