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EC301: Mathematical Economics 2: Dynamics, Uncertainty & Asymmetrical Information

  • Claudio Mezzetti

    Module Leader
  • James Massey

    Module Lecturer
15 CATS - Department of Economics
Summer Module

Principal Aims

EC301-15 Mathematical Economics 2: Dynamics, Uncertainty & Asymmetrical Information

Principal Learning Outcomes

Subject knowledge and understanding… demonstrate an appreciation of the use and limitations of formal mathematical approaches to economic theory and applicationsThe teaching and learning methods that enable students to achieve this learning outcome are: Lectures, background readingThe summative assessment methods that measure the achievement of this learning outcome are: Test, final exam

Subject knowledge and understanding… demonstrate a comprehensive understanding of the main results and open questions in the chosen areasThe teaching and learning methods that enable students to achieve this learning outcome are: Lectures, background readingThe summative assessment methods that measure the achievement of this learning outcome are: Test, final exam

Cognitive skillsCognitive skillsDemonstrate capacity of: Abstraction and Problem solving. The teaching and learning methods that enable students to achieve this learning outcome are: Lectures, background readingThe summative assessment methods that measure the achievement of this learning outcome are: Test, exam

Cognitive skillsCognitive skillsDemonstrate capacity of: Critical, creative and strategic thinking. The teaching and learning methods that enable students to achieve this learning outcome are: Lectures, background readingThe summative assessment methods that measure the achievement of this learning outcome are: Test, exam

Cognitive skills… convey and interpret material to a critical audienceThe teaching and learning methods that enable students to achieve this learning outcome are: Lectures. The summative assessment methods that measure the achievement of this learning outcome are: Test, exam

Cognitive skillsDemonstrate capacity of: Analytical thinking, reasoning and application.The teaching and learning methods that enable students to achieve this learning outcome are: Lectures, background readingThe summative assessment methods that measure the achievement of this learning outcome are: Test, exam

Subject-specific/professional skills… show the ability to absorb and analyse peer-reviewed literature The teaching and learning methods that enable students to achieve this learning outcome are: Lectures, background readingThe summative assessment methods that measure the achievement of this learning outcome are: Test, exam

Syllabus

The module will typically cover the following topics:

The role of asymmetric information in competitive markets. Topics on games of incomplete information: Bayesian and Perfect Bayesian equilibrium - especially in signalling and agency games. Screening and moral hazard.

Context

Optional Module
GL11 - Year 3, GL12 - Year 3, L100 - Year 3, L103 - Year 4, L116 - Year 3, L1P5 - Year 1, L1PA - Year 1, LM1D (LLD2) - Year 3, LM1H - Year 4, Y602 - Year 3, Y603 - Year 4, G300 - Year 3, G301 - Year 4, G300 - Year 4
Pre or Co-requisites
Modules: (EC220-12 or EC220-15)
Part-year Availability for Visiting Students
Available in the Autumn term only (1 x test and 1 x seminar presentation – 12 CATS)

Assessment

Assessment Method
Coursework (40%) + 1.5 hour examination (summer) (60%)
Coursework Details
In Class Test (40%), 1.5 hour examination (summer) (60%)
Exam Timing
N/A

Exam Rubric

Time Allowed: 1.5 Hours plus 15 minutes reading time, during which notes may be made (on the question paper) BUT NO ANSWERS MAY BE BEGUN.

Read all instructions carefully- and read through the entire paper at least once before you start entering your answers.

There is ONE section in this paper. Answer TWO questions (50 marks each).

Approved pocket calculators are allowed.

You should not submit answers to more than the required number of questions. If you do, we will mark the questions in the order that they appear, up to the required number of questions in each section.

Previous exam papers can be found in the University’s past papers archive. Please note that previous exam papers may not have operated under the same exam rubric or assessment weightings as those for the current academic year. The content of past papers may also be different.

Reading Lists