Universität Wien
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040063 KU Digital Economics - Macro (MA) (2024S)

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

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. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 07.05. 15:00 - 16:30 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 08.05. 15:00 - 16:30 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 14.05. 15:00 - 16:30 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 15.05. 15:00 - 16:30 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 21.05. 15:00 - 16:30 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 22.05. 15:00 - 16:30 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 28.05. 15:00 - 16:30 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 04.06. 15:00 - 16:30 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 05.06. 15:00 - 16:30 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 11.06. 15:00 - 16:30 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 12.06. 15:00 - 16:30 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 18.06. 15:00 - 16:30 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 19.06. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock

Information

Aims, contents and method of the course

The objective of this course is to introduce students in the key challenges of digitalization in the modern economy. It will combine theoretical and empirical methods, with a special focus on policy.

Assessment and permitted materials

Open Books exam (40%), Class Participation (20%), Group Project (40%)

Minimum requirements and assessment criteria

85% +, 1
70-85%, 2
60-70%, 3
50-60%, 4
Less than 50%, 5

Examination topics

1. Automation: Theory
2. Automation: Empirics and Policy
3. The future of Work
4. Macroeconomics and the use of Data.

Reading list

Selected articles available in Moodle

Association in the course directory

Last modified: Tu 14.05.2024 10:45