Mathematical Methods for Economics 2

Module code: ECN119

This is the core mathematics module for students with A Level mathematics or equivalent. It introduces the basic mathematical skills required by economists.

Aims of the module

The module aims to provide an insight into the importance of mathematical methods in economics and to study the key mathematical concepts widely applied in modern economics

Learning objectives

By the end of this module students will be able to:

  • describe the mathematical methods used in economic analysis
  • employ the appropriate mathematical tools to formulate any analyse problems in economics
  • solve a range of mathematically-formulated economics problems

Syllabus

Topics covered in the course include: revision of algebra; functions; differential calculus; integration; constrained optimisation; matrix algebra. All topics are demonstrated with economic applications

Teaching methods

The module is taught over the full academic year. In Semesters 1 and 2, there will be two one-hour lectures per week in weeks 1-10. In selected weeks, there will be surgery sessions (workshops) held in one of the lecture slots. The surgery sessions/workshops will present economic applications of the mathematical concepts covered in lectures.

In addition, there will be ten tutorial classes (four in Semester 1 and six in Semester 2).

Assessment

An unseen end-of-module examination (50%), plus two class tests (25% each)

Basic reading

We advise you not to buy books before the module begins, as the reading list may change. If you wish to read in advance, look for these texts in the University library

The key text for this module, to which frequent reference will be made, is Renshaw, G (2016) Maths for Economics, 4th edition, Oxford University Press

For further reading: Jacques, I (2015) Mathematics for Economics and Business, 8th edition, Pearson

Prerequisites Restricted to students on a degree course for which this is a core unit. Cannot be taken with MAS110 or MAS152

Module leader Panos Nanos

Please note that the leader may change before the module begins

Semester Academic year

Credits 20