Statusmelding

Kursbeskrivelsen finnes ikke for perioden du ba om. Viser deg aller siste versjon.

DRE 7042 Experimental Economics I

DRE 7042 Experimental Economics I

Course code: 
DRE 7042
Department: 
Economics
Credits: 
3
Course coordinator: 
Tom-Reiel Heggedal
Course name in Norwegian: 
Experimental Economics I
Product category: 
PhD
Portfolio: 
PhD Economics courses
Semester: 
2024 Spring
Active status: 
Hold - temporarily
Level of study: 
PhD
Deactivate term: 
2024 Spring
Teaching language: 
English
Course type: 
One semester
Introduction

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 basic 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. Students should also gain an understanding of the main types of behavioral biases in beliefs and preferences typically studied in economics expeiments. 

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 class will cover experiments on decision making under risk, bargaining, collective action problems, social norms, political economy, and market behavior. 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.

The course covers i) core design principles of laboratory experiments, ii) principles of control in the laboratory, iii) basic programming of laboratory experiments, and iv) experimental study of non-standard beliefs, and moral and social preferences.

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.

Software tools
No specified computer-based tools are required.
Additional information

Computer-based tools: zTree

Qualifications

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 course leader. 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.

Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Written submission
Weight: 
100
Grouping: 
Individual
Duration: 
1 Semester(s)
Exam code: 
DRE 70421
Grading scale: 
Pass/fail
Resit: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Group work / Assignments
32 Hour(s)
Specified learning activities (including reading)
Student's own work with learning resources
32 Hour(s)
Teaching
16 Hour(s)
Sum workload: 
80

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.