- Student Records
Programme & Unit Catalogues


ES10095: Mathematical economics

Follow this link for further information on academic years Academic Year: 2019/0
Further information on owning departmentsOwning Department/School: Department of Economics
Further information on credits Credits: 6      [equivalent to 12 CATS credits]
Further information on notional study hours Notional Study Hours: 120
Further information on unit levels Level: Certificate (FHEQ level 4)
Further information on teaching periods Period:
Semester 2
Further information on unit assessment Assessment Summary: CW 50%, EX 50%
Further information on unit assessment Assessment Detail:
  • Coursework (CW 50%)
  • Exam (EX 50%)
Further information on supplementary assessment Supplementary Assessment:
ES10095 Resit Exam (where allowed by programme regulations)
Further information on requisites Requisites:
Further information on descriptions Description: Aims:
To present methods of optimization commonly used in economics; to explain their theoretical basis and give a solid understanding of the wide variety of applications in economics and game theory that these optimization techniques are applicable to.

Learning Outcomes:
On completing this unit, students should be able to:
* Recognise economic and practical problems where static and dynamic optimization methods can be applied fruitfully.
* Solve optimization problems analytically and, where appropriate, numerically by means of appropriate software (such as Mathematica).
* Implement appropriate solution algorithms, and understand their procedures.
* Recognise economic and practical problems in which game theory tools can be used effectively.
* Understand and apply the main solutions concepts from game theory, such as equilibrium in dominant strategies, Nash Equilibrium, etc.

Skills:
Problem solving, abstraction, modelling of real-world optimisation problems, recognising different types of optimisation problems, using mathematical software.

Content:
I. The Mathematical Programming Problem: Unconstrained Optimization; The Method of Lagrange Multipliers; The Interpretation of Lagrange Multipliers.
II. Nonlinear Programming: The Case of No Inequality Constraints; The Kuhn-Tucker Conditions; The Kuhn-Tucker Theorem; The Interpretation of the Lagrange Multipliers; Solution Algorithms.
III. Dynamic Optimization: Formal Statement of the Problem; Costate Variables, Hamiltonians, and the Maximum Principle; Interpretation of the Costate Variables. Applications of Dynamic Optimization.
IV. Game Theory: Basic concepts of strategic games, two-person zero sum games, two-person non-zero sum games. Applications.
Further information on programme availabilityProgramme availability:

ES10095 is Compulsory on the following programmes:

Department of Economics
  • UHES-AFB04 : BSc(Hons) Economics and Mathematics (Year 1)
  • UHES-AAB04 : BSc(Hons) Economics and Mathematics with Study year abroad (Year 1)
  • UHES-AKB04 : BSc(Hons) Economics and Mathematics with Year long work placement (Year 1)
  • UHES-ACB04 : BSc(Hons) Economics and Mathematics with Combined Placement and Study Abroad (Year 1)

Notes: