Universität Wien

040294 UK Applied Causal Inference: how to answer interesting questions using data (BA) (2020W)

Track in Data Analysis

8.00 ECTS (4.00 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. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 20.10. 15:00 - 16:30 Digital
  • Wednesday 21.10. 15:00 - 16:30 Digital
  • Thursday 22.10. 15:00 - 16:30 Digital
  • Friday 23.10. 15:00 - 16:30 Digital
  • Wednesday 28.10. 15:00 - 16:30 Digital
  • Thursday 29.10. 15:00 - 16:30 Digital
  • Wednesday 04.11. 15:00 - 16:30 Digital
  • Thursday 05.11. 15:00 - 16:30 Digital
  • Wednesday 11.11. 15:00 - 16:30 Digital
  • Thursday 12.11. 15:00 - 16:30 Digital
  • Wednesday 18.11. 15:00 - 16:30 Digital
  • Thursday 19.11. 15:00 - 16:30 Digital
  • Wednesday 25.11. 15:00 - 16:30 Digital
  • Thursday 26.11. 15:00 - 16:30 Digital
  • Wednesday 02.12. 15:00 - 16:30 Digital
  • Thursday 03.12. 15:00 - 16:30 Digital
  • Wednesday 09.12. 15:00 - 16:30 Digital
  • Thursday 10.12. 15:00 - 16:30 Digital
  • Wednesday 16.12. 15:00 - 16:30 Digital
  • Thursday 17.12. 15:00 - 16:30 Digital
  • Thursday 07.01. 15:00 - 16:30 Digital
  • Wednesday 13.01. 15:00 - 16:30 Digital
  • Thursday 14.01. 15:00 - 16:30 Digital
  • Wednesday 20.01. 15:00 - 16:30 Digital
  • Thursday 21.01. 15:00 - 16:30 Digital
  • Wednesday 27.01. 15:00 - 16:30 Digital
  • Thursday 28.01. 15:00 - 16:30 Digital

Information

Aims, contents and method of the course

The aim of this course is to help you to understand modern applied econometric methods and to foster the skills needed to plan and execute your own empirical projects. Topics include randomized trials, regression, differences-in-differences, instrumental variables and regression-discontinuity designs. This is an “applied-empirical” course, meaning that priority will be given to concrete applications rather than to formal derivation of the econometrics methods used in the applications.

Assessment and permitted materials

Exam: 34%. Homework 33%. Class participation 33%.

By class participation I do not mean showing up in class, instead I mean engaging actively in the lecture.

Minimum requirements and assessment criteria

Assessment is based on one open-book exam, homework and participation in class.

Examination topics

All the material covered in class will be relevant for the exams.

Reading list

J. Angrist and J.S. Pischke, Mastering ‘Metrics: The Path from Cause to Effect, Princeton
University Press, 2014. http://masteringmetrics.com/

Association in the course directory

Last modified: Fr 12.05.2023 00:12