Undergraduate Course: Behavioural Economics (ECNM10066)
Course Outline
School | School of Economics |
College | College of Arts, Humanities and Social Sciences |
Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
SCQF Credits | 20 |
ECTS Credits | 10 |
Summary | Behavioural Economics looks at developing models that are motivated by empirical evidence of individual behaviour rather than assumptions about rationality. This course will cover a number of topics in behavioural economics. We will look at leading academic papers in the area to assess the empirical evidence (field and experimental) and the implications for standard assumptions on rationality and to look at how the theory has been developed in the light of this evidence. |
Course description |
Topics covered include decision making under certainty, decision making under uncertainty including prospect theory, experimental economics and/or neuroeconomics, intertemporal choice, self-control, behavioural game theory, case studies on saving and obesity, and the economics of happiness.
The course is taught through a programme of lectures and tutorials. Learning-by-doing, through problem solving and discussion of exercise sets, is an important ingredient of the course.
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Information for Visiting Students
Pre-requisites | Visiting students must have an equivalent of at least 4 semester-long Economics courses at grade B or above for entry to this course. This MUST INCLUDE courses in Intermediate Macroeconomics (with calculus); Intermediate Microeconomics (with calculus); Probability and Statistics; and Introductory Econometrics. If macroeconomics and microeconomics courses are not calculus-based, then, in addition, Calculus (or Mathematics for Economics) is required. |
High Demand Course? |
Yes |
Course Delivery Information
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Academic year 2020/21, Available to all students (SV1)
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Quota: None |
Course Start |
Semester 2 |
Timetable |
Timetable |
Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Seminar/Tutorial Hours 6,
Summative Assessment Hours 3,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
167 )
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Assessment (Further Info) |
Written Exam
90 %,
Coursework
10 %,
Practical Exam
0 %
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Additional Information (Assessment) |
Group Project: 10%
Degree Exam: 90%
Final mark for visiting students as above.
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Feedback |
Not entered |
Exam Information |
Exam Diet |
Paper Name |
Hours & Minutes |
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Main Exam Diet S2 (April/May) | | 2:00 | | Resit Exam Diet (August) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- A knowledge and understanding of strengths and weaknesses of the "rational actor" framework used elsewhere in economics, as well as a deeper understanding of the heuristics and biases that affect people¿s thinking. A knowledge and understanding of behavioural models and associated mathematical and statistical techniques, along with applications and policy implications of those models and a deeper understanding of recent research activity in some more specialised areas.
- Research and investigative skills such as problem framing and solving and the ability to assemble and evaluate complex evidence and arguments.
- Communication skills in order to critique, create and communicate understanding.
- Personal effectiveness through task-management, time-management, dealing with uncertainty and adapting to new situations, personal and intellectual autonomy through independent learning.
- Practical/technical skills such as, modelling skills (abstraction, logic, succinctness), qualitative and quantitative analysis and general IT literacy.
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Reading List
There is no single resource for this course. We will make use of readings from economic journals. |
Additional Information
Graduate Attributes and Skills |
See Learning Outcomes |
Keywords | BehEcon |
Contacts
Course organiser | Dr Tatiana Kornienko
Tel: 0131 650 8338
Email: Tatiana.Kornienko@ed.ac.uk |
Course secretary | Mr Robert Brown
Tel:
Email: rbrown13@exseed.ed.ac.uk |
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