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ECON42560

Academic Year 2024/2025

Behavioural Economics (ECON42560)

Subject:
Economics
College:
Social Sciences & Law
School:
Economics
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Dr Vessela Daskalova
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

The purpose of this course is to provide a graduate level introduction to key topics in behavioural economics, covering both theories and empirical evidence. Behavioural economics incorporates methods and insights from psychology, sociology, philosophy, and other fields into economic analysis in order to enrich our understanding of human behaviour. The lectures will be highly interactive and aim to equip students with the ability to critically evaluate and discuss cutting edge research in Behavioural Economics.

About this Module

Learning Outcomes:

The key learning outcomes of this module:
• A mastery of key concepts in behavioural economics.
• An understanding of how theory and empirics can be combined to better understand human behaviour.
• The ability to apply behavioural concepts more generally to economic areas of interest.
• The ability to critically evaluate, present, and write about research in Behavioural Economics.

Indicative Module Content:

The course will focus on the following topics:
• Methodology.
• Bounded Rationality in Individual Decisions. Heuristics and Biases.
• Framing. Reference Dependence.
• Bounded Rationality in Games. Level-k. Focal Points. Variable Frame Theory. Coordination and Cognition. Categorization.
• Identity Economics. Social Preferences, Beliefs, and Coordination.
• Diversity in Organizations.

Student Effort Hours:
Student Effort Type Hours
Lectures

22

Autonomous Student Learning

100

Total

122


Approaches to Teaching and Learning:
The module will be delivered through a series of lectures on cutting-edge topics in behavioural economics. The approach to teaching and learning is highly interactive and includes student presentations, class discussions, and individual as well as group work. Students will have the opportunity to participate in interactive classroom experiments using their smartphones. This technology-enhanced approach allows students to experience an economic decision making problem, work on a solution, and receive real-time feedback, promoting active and experiential learning.

The use of AI for any purpose is not allowed in this module.

Requirements, Exclusions and Recommendations
Learning Recommendations:

There are no formal pre-requisites for the course. However, prior knowledge of microeconomics, game theory, and statistical methods will be assumed.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Exam (In-person): Problem solving and answering questions. End of trimester
Duration:
2 hr(s)
Alternative linear conversion grade scale 40% No
70
No
Group Work Assignment: In-class presentation of a group project. Week 4, Week 5, Week 6, Week 7, Week 8, Week 9, Week 10, Week 11, Week 12 Alternative linear conversion grade scale 40% No
30
No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Spring Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

- Students will receive comments following their group presentation - Students will be given individual feedback in the form of grades for the presentation and exam paper

There is no single textbook for the course and much of the material is based on scientific articles and books. A detailed References List will be provided for each topic.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Lecture Offering 1 Week(s) - Autumn: All Weeks Fri 12:00 - 13:50