DRE 7043 Experimental Economics II

DRE 7043 Experimental Economics II

Course code: 
DRE 7043
Course coordinator: 
Tom-Reiel Heggedal
Course name in Norwegian: 
Experimental Economics II
Product category: 
PhD Economics courses
2022 Spring
Active status: 
Level of study: 
Teaching language: 
Course type: 
One semester

The aim of the course is to provide participants with a thorough understanding of selectec advanced topics in experimental economics. Selection of topics will depend on the instructor of the course.

Learning outcomes - Knowledge

In this course students obtain a deeper knowledge about the principles of design, programing, implementation, and analysis of data collected in economic experiments. Students also gain an understanding of the role of replication, committment and transparency in experimental economics. The relationship between field studies, field experiments and laboratory experiments is convered.  

Learning outcomes - Skills

After taking the course students should be able to design and more sophisticated economics experiment, program them, and run them in the laboratory for the relevant institutional settings covered in the course.

The course covers i) sophisticated design principles, ii) replication, transparency and committment in experimental economics, iii) selected topics in experimetrics, iv) programming of laboratory experiments, iv) the experimental study of stereotypes, honesty, social norms and selection, v) laboratory versus field experiments and field studies based on naturally occurring data.

General Competence

After taking the course students should be able to constructively reflect on the value of alternative assumptions in models of economics, and to be able to critically assess the value of collecting data in randomized and highly controlled settings such as an economics laboratory. Students should further have gained a thourough understanding of the pros et cons of laboratory experiments versus other study designs. Moreover students should obtain an understanding of how experiments are evaluated relative to each other according to principles of replication, transparency and committment.   

Course content

The course focuses on the methods of experimental economics, and some of the recent applications. Each lecture covers a different subject and illustrates how different experimental techniques are employed. Students will participate in experiments in order to acquire hands on experience.

The course builds on Experimental Economics I. In class we cover experiments on decision making under risk, bargaining, collective action problems, social norms, political economy, and market behavior. We also explore the strenght and weaknesses of laboratory versus field experiments and field studies based on naturally occurring data. As an important part of the course, students will learn how to program more sophisticated experiments in zTree, a software program particularly useful for running laboratory experiments that require interaction between subjects.


Teaching and learning activities

The course is taught in intensively in two days. Each day consists of 6-8 hours teaching.

Students are required to participate in class – both in discussions and by presenting experimental designs / computer programs for experiments / material from the reading lists.

Computer-based tools: zTree

Software tools
Software defined under the section "Teaching and learning activities".

Enrollment in a PhD Programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the courseleader. Sitting in on a course does not permit registration for the course, handing in exams or gaining credits for the course. Course certificates or confirmation letters will not be issued for sitting in on courses.


Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.


Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.

Exam category: 
Form of assessment: 
Written submission
1 Semester(s)
Exam code: 
DRE 70431
Grading scale: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
Student workload
Group work / Assignments
32 Hour(s)
Specified learning activities (including reading)
Student's own work with learning resources
32 Hour(s)
Autonomous student learning.
16 Hour(s)
Sum workload: 

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 3 ECTS credit corresponds to a workload of at least 80 hours.