Last modified: 25 Mar 2016 11:39
This course develops a mathematical and statistical ‘toolbox’ for MSc Petroleum Energy Economics and Finance students. These tools will useful in understanding and implementing research in energy economics-related fields both during a student’s academic career as well as after graduation. The first part of the course covers basic mathematical models common across these fields. The second part of the course develops standard data analysis methods, including multivariate regression. Applications from various energy economic areas are used in order to illustrate the mathematical and statistical concepts.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Old Aberdeen | Sustained Study | No |
| Co-ordinators |
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Postgraduate work in energy economics and finance relies on a grounding in quantitative and empirical methodologies. This course surveys some of the basic methods used to understand the underlying theories and empirical examples and tests found in these fields. Thus students will be introduced to basic mathematical concepts such as discounting, calculus, unconstrained and constrained optimisation, and matrix algebra focusing on straightforward examples of how these concepts are applied. The course will also review basic statistical concepts and extend them to hypothesis testing and least squares regression methodologies which form the backbone of empirical testing of theories. Examples and applications from various areas of energy economics and finance will be used in order to illustrate the methods. The course will also discuss some potential problems in these methodologies as well as offer ways to overcome these problems.
Information on contact teaching time is available from the course guide.
1st attempt: 1 two-hour written examination (60%) plus continuous assessment (40%)
comprising 30% term time exam and 10% empirical group exercise.
Resit attempt: 1 two-hour written
examination (100%).
There are no assessments for this course.
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