Mathematics for Economists
This module aims to make you familiar with those mathematical tools and methods which are used frequently in most economics courses and to show you how they are applied.
Mathematics is a global language, so the technical skills students acquire in this module can be used internationally.
By solving statistical mathematical problems and exercises, students are equipped with practical problem-solving skills, theoretical skills, and an understanding of mathematical relationships. All of these are highly valuable to employers.
All of the resources for this module are available on the ELE (Exeter Learning Environment).
[PLEASE NOTE THIS MODULE IS NOT AVAILABLE TO MATHS STUDENTS]
Full module specification
|Module title:||Mathematics for Economists|
BEE1020 OR BEE1035 or A-level Mathematics (or equivalent)
This module is not available to 2nd year AF students or Maths students.
Cannot be taken with BEA1010
|Duration of module:||
Duration (weeks) - term 1: |
Economic problems are often expressed using mathematical models. Therefore we introduce models which are to be formulated, analysed and then confronted with real-world data. This module aims to make students familiar with those mathematical tools and methods which are used frequently in most economic modules and to demonstrate how they are applied.
ILO: Module-specific skills
- 1. students will develop the skills to differentiate functions in several variables, the ability to solve economic optimisation problems and basic the skills of matrix manipulation
ILO: Discipline-specific skills
- 2. will understand the important role of mathematical tools in economics and related disciplines;
- 3. will have developed basic skills to analyse models from microeconomics and macroeconomics;
- 4. will be familiar with some concepts of linear algebra that are essential for econometrics;
ILO: Personal and key skills
- 5. students will have improved their numeracy and also their ability for logical and structured problem analysis
Learning activities and teaching methods (given in hours of study time)
|Scheduled Learning and Teaching Activities||Guided independent study||Placement / study abroad|
Details of learning activities and teaching methods
|Category||Hours of study time||Description|
|Form of assessment||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
Summative assessment (% of credit)
|Coursework||Written exams||Practical exams|
Details of summative assessment
|Form of assessment||% of credit||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|Examination||100||2 hours||1-5||Exam result|
Details of re-assessment (where required by referral or deferral)
|Original form of assessment||Form of re-assessment||ILOs re-assessed||Timescale for re-assessment|
|Examination||Examination (100%)||1-5||Exam result|
This is an indicative outline (further details will be available in lecture 1)
• Partial derivatives for multivariate functions (week 1)
• Unconstrained optimization and applications (week 2-3)
• Constrained optimization and applications (week 4-5)
• Second order conditions (week 6)
• Logarithms and exponential functions (week 7)
• Vectors and matrices (week 8-9)
• Determinants (week 10)
• Revision (week 11)
Indicative learning resources - Basic reading
Knut Sydsaeter and Peter J. Hammond, (2008) Essential Mathematics for Economic Analysis 3rd Edit, Prentice Hall. Geoff Renshaw, (2009) Maths for Economics 2nd Edit, Oxford.
Ian Jacques, Mathematics for Economics and Business, Addison-Wesley (2002)_ Preferred by students without A level math, but less comprehensive. Occasionally another book may have to be used
Module has an active ELE page?
Last revision date