This module covers a variety of the mathematical methods and their application to economic theory. The module starts off with a review and extension of stage 1 calculus, including integration. We examine production functions, returns to scale and their relation to firm profits. The module then covers dynamic systems where students learn to solve second-order difference equations, and, in so doing, learn about complex numbers. We use this analysis to generate insights about monetary policy. Matrix algebra is explored and used to analyse multiple equation dynamic systems. We then cover more optimisation theory, using Lagrangians to solve problems with equality and inequality constraints. Building on matrix algebra, we use Hessians to examine when we have found a genuinely desired optimum. Some of the further economic ideas we analyse are efficiency wages and monopsony power in the labour market, the duality theory of cost minimisation, and consumer theory, including Roy's identity and Shephard's Lemma.
Private Study: 120
Contact Hours: 30
Total: 150
This is an optional module for all Single and Joint Honours Degree courses in Economics.
The module is NOT available to students across other degree courses in the University.
Moodle Quiz (10%)
In-Course Test (20%)
Examination, 2 hours (70%)
Reassessment Instrument: 100% exam
*Exams will be in-person*
The University is committed to ensuring that core reading materials are in accessible electronic format in line with the Kent Inclusive Practices.
The most up to date reading list for each module can be found on the university's reading list pages.
See the library reading list for this module (Canterbury)
On successfully completing the module students will be able to:
1 Demonstrate the ability to work with abstract mathematical concepts
2 Understand the mathematical aspects of economic modelling techniques
3 Formulate and solve problems in economics using a range of mathematical techniques
4 Identify the range of more advanced mathematical modelling used in economics
5 Use optimization methodologies and matrix algebra
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