Universität Wien

040081 UE Empirical Methods II (MA) (2024W)

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

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

  • Thursday 03.10. 13:15 - 16:30 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 10.10. 13:15 - 16:30 Seminarraum 15 Oskar-Morgenstern-Platz 1 3.Stock
  • Thursday 17.10. 13:15 - 16:30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 24.10. 13:15 - 16:30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 31.10. 13:15 - 16:30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 14.11. 13:15 - 16:30 Digital
  • Thursday 21.11. 13:15 - 16:30 Digital
  • Thursday 12.12. 13:15 - 16:30 Digital
  • Thursday 16.01. 15:00 - 16:30 Hörsaal 15 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 27.01. 13:15 - 16:30 Digital

Information

Aims, contents and method of the course

This course complements “Empirical Methods I” and builds on the knowledge, datasets and STATA skills students acquired in that introductory class. Being an advanced course on writing empirical papers, the goal of this course is for students to learn how to work with data and analyze it against the backdrop of a given research question.

Therefore, after a brief recap of the contents of “Empirical Methods I”, we will re-activate knowledge acquired in undergraduate Statistics classes and 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 STATA skills and theoretical know-how of students and introduce data analysis using statistical programming software. Students will learn the basic idea behind the Least Squares method, several regression types and will become familiar with Gauss-Markov Conditions, as well as the concept of unbiased and efficient regression results. Students will participate by reading and presenting scientific articles in some of the highest ranked strategy journals and working with practice, as well as real-world datasets. Knowledge gained in this course will be applied during a project where students actively conduct their own empirical research, using the front-ends (introduction, theory and hypotheses) they wrote, as well as the data they obtained during Empirical Methods I. Having taken both classes, students shall be left with detailed knowledge and practical experience on how to put-up an empirical paper.

This course is interactive and built around the idea of a laboratory setup as is typical for social sciences. The setup necessitates certain software and IT equipment. To provide every student the same opportunity to successfully participate in the course, it is partly held in one of the PC-labs at the OMP 1. The class is hence held in-person with selected (non-theory, individual meetings) sessions held via Zoom. For those online meetings, students are required to ensure stable Internet connection and be able to join using their web cameras as well. Hence, not only an audio connection, also a video connection is required. The majority of all sessions, as well as the exam will be held in person. The exact format of individual sessions will be announced during Session 1.
Please refer to https://strategy.univie.ac.at/ for general information on our courses.

Assessment and permitted materials

30% - class participation (i.e., review, home assignments and presentation of an empirical paper)
35% - written exam
35% - empirical project (i.e., own paper including a presentation)

Minimum requirements and assessment criteria

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. 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:
5 – [0%; 50%)
4 – [50%; 62.5%)
3 – [62.5%; 75%)
2 – [75%; 87.5%)
1 – [87.5%; 100%]

Examination topics

Students are required to know and have understood all topics discussed in class and presented on the lecture slides. The written exam places focus not only on students' theoretical knowledge, but on applying theory to real-world examples.

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 04.11.2024 13:45