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Instructors: Niklas Wallmeier
Event type:
Interactive class
Displayed in timetable as:
Hours per week:
3
Credits:
6,0
Language of instruction:
English
Min. | Max. participants:
- | 45
Comments/contents:
This course is designed to introduce students to the practice of experimental economics. It combines insights into seminal contributions to the field of experimental economics with an introduction to implementing experiments with state-of-the-art software. Students will acquire software skills during this course and from groups to apply these to replicate a prominent experimental study.
Learning objectives:
The course has three main objectives to prepare the students to pursue their own research ideas using experiments as a method. Firstly, students will gain insight in the challenges of designing an economic experiment. Moreover, they will acquire programming skills to set up their own experiment. The third objective is to for the students to gain experience how to handle the logistical challenges when an experiment is conducted with real participants.
Didactic concept:
Experimental Economics will be an interactive in-person course. There are four main course elements.
- An introduction to the experimental software.
- Development of the replication project.
- A code workshop for the replication project.
- In-class presentation of the results.
Further information on the course will follow in October. All course materials will be made available via the OpenOlat platform.
Literature:
The papers will be selected from:
Charness, G. and M. Pingle (2021). The Art of Experimental Economics: Twenty Top Papers Reviewed. Routledge. (see for paper list).
The course will be partly guided by:
Stojmenovska, D., T. Bol, and T. Leopold (2019). Teaching replication to graduate students. Teaching Sociology 47 (4), 303–313.
The software used in this course is oTree:
Chen, D. L., M. Schonger, and C. Wickens (2016). otree—an open-source platform for laboratory, online, and field experiments. Journal of Behavioral and Experimental Finance 9, 88–97.
An overview can be found at https://www.otree.org/
For installing the software on a personal computer it is recommended to follow: https://otree.readthedocs.io/en/latest/install.html
An introduction to python is provided at: https://otree.readthedocs.io/en/latest/python.html
Additional examination information:
The students will be graded based on a presentation in class (50%) and a written paper (50%). Further information (e.g. with respect to the pandemic status) will follow in the course of the semester.
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