ECON30270 Behavioural Economics and Public Policy

Academic Year 2022/2023

The purpose of this course is to provide an advanced undergraduate level introduction to the principles of Behavioural Economics. Behavioural economics incorporates insights from psychology, sociology, philosophy, and other fields into economic analysis to enrich our understanding of how humans make decisions. The course will survey key concepts in behavioural economics and examine how they have influenced thinking on public policy. The content is divided into three main parts: Behavioural Decision Making, Behavioural Game Theory, Behavioural Public Policy.

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Curricular information is subject to change

Learning Outcomes:

At the end of the course, students should have a broad understanding of the field and, in particular:
1. Understand key theoretical concepts in behavioural economics.
2. Understand how to evaluate empirical evidence from behavioural research.
3. Be able to critically evaluate the role of behavioural research in informing public policy.

Indicative Module Content:

The course will cover a selection of the following topics:
- Decision Making under Risk and Uncertainty
- Probability Theory, Heuristics, and Biases
- Prospect Theory, Reference Dependence, and Mental Accounting
- Intertemporal Choice
- Social Preferences
- Role of Social Identities in Decision Making
- Behavioural Game Theory
- Nudging

Student Effort Hours: 
Student Effort Type Hours
Autonomous Student Learning

100

Lectures

22

Total

122

Approaches to Teaching and Learning:
The module is driven by recent research in behavioural economics. The lectures provide a survey of key topics and methods used in the field. Students are encouraged to engage with a range of materials (published papers, books, videos) and to take a hands-on approach, learning through problem solving, critical discussion, and participation in mock experiments.

The lecture will be delivered in-person and 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.
 
Requirements, Exclusions and Recommendations
Learning Recommendations:

There are no formal pre-requisites for the course. However, having some basic knowledge of microeconomics and game theory can be helpful.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Examination: A final exam consisting of problem solving and answering questions. 2 hour End of Trimester Exam No Alternative linear conversion grade scale 40% No

70

Examination: An intermediate exam consisting of problem solving and answering questions. Week 6 No Alternative linear conversion grade scale 40% No

30


Carry forward of passed components
Yes
 
Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment
• Self-assessment activities

How will my Feedback be Delivered?

Students will be given individual feedback in the form of grades for the assessed assignments. There will be group/class feedback post-assessment.

There is no standard textbook for this module. Much of the material is based on scientific articles and books. The first part of the course will draw on the textbook "A Course in Behavioral Economics" by Erik Angner, 3rd edition, McMillan, a few copies of which are available in the UCD library. Specific reading recommendations will be provided in each lecture.
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) - 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Mon 12:00 - 12:50
Lecture Offering 1 Week(s) - 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Wed 11:00 - 11:50
Autumn