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To enable a smooth and safe start into the semester for all members of the University of Vienna, you can get vaccinated without prior appointment on the Campus of the University of Vienna from Saturday, 18 September, until Monday, 20 September. More information: https://www.univie.ac.at/en/about-us/further-information/coronavirus/.

Warning! The directory is not yet complete and will be amended until the beginning of the term.

040120 SE Topics in data-driven decision making (MA) (2020W)

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

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

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

For our meetings we use BB Collaborate (login through Moodle).

Tuesday 06.10. 13:15 - 14:45 Digital
Tuesday 13.10. 13:15 - 14:45 Digital
Tuesday 20.10. 13:15 - 14:45 Digital
Tuesday 27.10. 13:15 - 14:45 Digital
Tuesday 03.11. 13:15 - 14:45 Digital
Tuesday 10.11. 13:15 - 14:45 Digital
Tuesday 17.11. 13:15 - 14:45 Digital
Tuesday 24.11. 13:15 - 14:45 Digital
Tuesday 01.12. 13:15 - 14:45 Digital
Tuesday 15.12. 13:15 - 14:45 Digital
Tuesday 12.01. 13:15 - 14:45 Digital
Tuesday 19.01. 13:15 - 14:45 Digital
Tuesday 26.01. 13:15 - 14:45 Digital

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 and management. The aim of this course is to introduce students to recent research trends and to learn and 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 as well as concepts of prediction. In part 2, we study 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 R exercises and research papers), and a paper ('Seminararbeit').
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. The course language is English.

Examination topics

Students solve R exercises and write a seminar paper; they also present their R exercises and and their seminar paper topic.

Exercises count 20%, the presentation counts 30% and the written work counts 50% of the grade. At total of >50% is required for a passing grade.

Reading list

handout/moodle

Association in the course directory

Last modified: Mo 05.10.2020 10:48