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EC343 - Behavioural Economics

EC343-Behavioural Economics

Module Provider: School of Politics, Economics and International Relations
Number of credits: 20 [10 ECTS credits]
Level:6
Terms in which taught: Autumn term module
Pre-requisites: EC201 Intermediate Microeconomics and EC206 Intermediate Mathematics for Economics or EC201 Intermediate Microeconomics and MA2DE Differential Equations
Non-modular pre-requisites: Restricted to BSc Economics, BSc Economics and Econometrics, BSc Economics and Finance, BSc Mathematics and Economics
Co-requisites:
Modules excluded:
Current from: 2020/1

Module Convenor: Dr Stephen Kastoryano

Email: s.p.kastoryano@reading.ac.uk

Type of module:

Summary module description:

This module offers students the opportunity to extend their understanding of how a broad range of economic decisions are made. Neoclassical economics is underpinned by numerous assumptions about how agents make decisions. Many decisions routinely observed are indeed at odds with classical economic theory. This module builds descriptively accurate models of decision making based on actually observed behaviour and aimed at including psychological intuitions about the drivers of such behaviour. While being descriptively more accurate, the models aspire at the same formal and mathematical rigour of classical models, thus constituting generalisations of the former. 


Aims:

The aims of this module are to:

• Explain the key assumptions that underlie neoclassical economics regarding the manner in which economic decisions are made;

• Illustrate and evaluate the empirical evidence that apparently contradicts neoclassical assumptions;

• Introduce formal, descriptively accurate models that capture the observed behaviour and overcome the violations of the classical models;

• Discuss and show policy implications of the modified theories


Assessable learning outcomes:

Students will be assessed on their ability to describe and critically evaluate with precision both the challenges to neoclassical economics and the contributions of behavioural economics highlighted in the module. This will include the ability to rigorously analyse: concepts of economic rationality; alternative formulations of economic preferences; and the manner in which economic choices are made both under uncertainty and across time. Data analysis is an integral part of the course, and ser ves to inform the development of alternative theories in a `learning by doing’ approach. Existing models will be checked based on such data, and used to develop an intuition about why the models may be violated. This intuition will then seve as the starting point for the introduction of more general models of behaviour.


Additional outcomes:

Students will be required to apply theoretical knowledge to real world situations. Students should be able to apply the key insights of the module to a broad range of economic decision-making, such as consumption, investment decisions, inter-temporal trade offs and strategic interactions. 


Outline content:

Basic topics include: expected utility theory; anomalies of decision making under risk and uncertainty and alternative models; violations of rationality; time-inconsistency and hyperbolic discounting; behavioural game theory and social preferences (broadly defined). 


Brief description of teaching and learning methods:
A combination of lectures, group discussions of assigned topics and problems, and assessed essays. Problem sets and data analysis are an integral part of the learning process as well as the assessment.

Contact hours:
  Autumn Spring Summer
Lectures 20
Guided independent study: 180
       
Total hours by term 0 0
       
Total hours for module 200

Summative Assessment Methods:
Method Percentage
Written assignment including essay 50
Class test administered by School 50

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

There is a final essay/classroom test that carries 50% of the weight. The remaining 50% is assigned based on coursework, including data analysis, solution of problem sets, and/or a classroom assessment. 


Formative assessment methods:

Penalties for late submission:

The Module Convenor will apply the following penalties for work submitted late:

  • where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day[1] (or part thereof) following the deadline up to a total of five working days;
  • where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
The University policy statement on penalties for late submission can be found at: http://www.reading.ac.uk/web/FILES/qualitysupport/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:
A minimum overall mark of 40%.

Reassessment arrangements:
Re-assessment is by resubmission of coursework which will be required by the end of the re-examination period in August/September.

Additional Costs (specified where applicable):

1) Required text books:



Dhami, Sanjit (2016). The Foundations of Behavioral Economic Analysis. Oxford University Pess (available from the libarary as an online resource)

2) Specialist equipment or materials:

3) Specialist clothing, footwear or headgear:

4) Printing and binding: There may be optional costs associated with photocopying or printing sources listed on the reading list relating to this module. Please note that the Library charges approximately 5p per photocopy.

5) Computers and devices with a particular specification:

6) Travel, accommodation and subsistence: 


Last updated: 4 September 2020

THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.

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