DRE XX34 Experimental Economics II

DRE XX34 Experimental Economics II

Course code: 
Program of study: 
Course coordinator: 
Leif Helland
Product category: 
PhD Economics courses
2022 Spring
Active status: 
Teaching language: 
Course type: 
One semester

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

Learning outcomes - Knowledge

In this course students obtain knowledge about how to design, program, implement, and analyze economic experiments

Learning outcomes - Skills

After taking the course students should be able to design and execute a simple economics experiment, program it, and run it in the laboratory for the relevant institutional settings covered in the course.

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.

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 II. 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. As an important part of the course, we will learn how to program 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 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 conformation letters will not be issued for sitting in on courses.

Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Form of assessment:
Written submission
Exam code:
Grading scale:
Grading rules:
Internal and external examiner
Examination when next scheduled course
100No1 Semester(s)Individual
Exam category:Submission
Form of assessment:Written submission
Grouping (size):Individual
Duration:1 Semester(s)
Exam code:DRE XXXX1
Grading scale:Pass/fail
Resit: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.
Teaching on Campus
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.