Universität Wien
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040120 SE Topics in data-driven decision making (MA) (2019W)

Track in Data Analysis und Track in Behavioral Economics and Experiments and Policy Evaluation

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
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. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 01.10. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 08.10. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 15.10. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 22.10. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 29.10. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 05.11. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 12.11. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 19.11. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 26.11. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 03.12. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 10.12. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 17.12. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 07.01. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 14.01. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 21.01. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 28.01. 11:30 - 13:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock

Information

Aims, contents and method of the course

Aims, content, and methods: Digital services permeate almost every aspect of life, reshaping business transactions and social interactions alike. In this course, we investigate recent advances in data-driven approaches to decision making relevant to economics. The aim of this course is to introduce students to recent research trends and to discuss critically how these tools can used for decision making in organizations.
The course consists of two parts. In part 1, we review theoretical concepts related to causal inference through randomized experiments and concepts of prediction. In part 2, we investigate how these concepts can be applied to a number of relevant questions in economics and management. The fields from which applications are selected include behavioral economics, game theory, organizational behavior and industrial organization.

Assessment and permitted materials

Assessment: The assessment is based on presentations (of exercises and research papers), written peer feedback and a research summary. Note that it is imperative to participate in the first session. Students who cannot (for a good reason) participate in the first session should send me an e-mail one week before the first session.

Minimum requirements and assessment criteria

Participants should have taken an introductory course to the field of experimental economics, for example the MA course “Behavioral and Experimental Economics” (UK040832). Students with comparable backgrounds can also be admitted but need to provide evidence that their knowledge is comparable. In addition, a sound knowledge of microeconomics, microeconometrics and R (for exercises) is required. Details on the assessment criteria are given in the first session. The course language is English.

Examination topics

Students are assigned exercises and choose a research paper on their own.

Reading list

handout/moodle

Association in the course directory

Last modified: Mo 07.09.2020 15:19