ECONOMIC ANALYSIS WITH MATRICES - 2024/5
Module code: ECO2048
The module is composed of three macro areas: 1) An introduction to linear algebra 2) An introduction to programming in Matlab and 3) Applications of 1) and 2) to finance and economics problems. In the first part of the course students develop an understanding of key concepts in linear algebra (vector, matrices, rank, determinants, system solutions, quadratic forms) while also learning the functioning of MATLAB and the associated syntax. In the second part of the course students learn how to apply the toolkit learnt in the first part of the course to real world finance and economics scenarios.
LLORENS-TERRAZAS Jordi (Economics)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 5
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 90
Lecture Hours: 22
Laboratory Hours: 10
Guided Learning: 10
Captured Content: 18
Prerequisites / Co-requisites
Indicative content includes:
- Matrix algebra: vectors and matrices; matrix operations: addition, subtraction, multiplication, inversion; notation, linear dependence, determinants, rank, solution to a set of linear equations and quadratic forms
- Representation of simple economic models in matrix form
- Introduction to programming and debugging in MATLAB
- Fetching economic data through MATLAB
- OLS model in matrix form
- IS-LM model solution in matrix form
- Mechanical Trading rules
|Unit of assessment
|Online Scheduled Summative Class Test
|Online Test within a 4hr window
|Oral exam or presentation
|FINAL GROUP PROJECT
For both the group presentation and final group project, alternative assessments will be an individual presentation and project assignment in the appropraite reassessment period.
The assessment strategy is designed to provide students with the opportunity to demonstrate their understanding of basic matrix algebra, its use in standard software packages (i.e. MATLAB) and some selected but varied applications to real-world socio-economic themes.
Thus, the summative assessment for this module consists of:
- Class test testing knowledge of basic matrix (and linear algebra) and MATLAB programming (worth 25% of the overall mark) - linked to learning outcome 1.
- Group presentation (worth 20% of the overall mark) aimed at evaluating the approaches and steps undertaken towards the completion of the final group project, testing both knowledge of MATLAB programming and presentation skills – linked to learning outcomes 2, 3 & 4.
- Final group project which allows students to analyse a topic in depth by using techniques and concepts assimilated during the module (worth 55% of the overall mark). Each project will consist of a Matlab code, a written report and an assessment of individual performances in the group. The assessment is designed to evaluate the skills in Matlab programming, the ability to gather, analyse and interpret information on a particular topic and to use this knowledge to produce a written report. It also assesses the ability to work in a group and evaluate individual performances in their team (Note: individual marks within a group are capped at the overall project mark, students with lower contributions weights will be adjusted accordingly) - linked to all learning outcomes (1, 2, 3 & 4).
Formative assessment and Feedback:
Students receive verbal feedback during lectures and computer labs. Videos may also be used to deliver solutions of assignments, explaining concepts and procedures involved when the proposed solution code requires further clarifications. Computer lab feedback sessions deliver extensive formative assessment and feedback, possibly in small groups.
- Provide students with an appreciation of the variety of applications of simple matrix algebra in economics, finance and other social sciences.
- Promote students' confidence in applying and creating data-driven models solving real word problems with the use of standard software packages (i.e. MATLAB).
- Help students to build a basic understanding of programming techniques.
- Help students develop an appreciation and relevance of programming techniques within the "professional economist toolkit".
- Provide students with the relevant software and independent research skills that will enable them to successfully undertake the writing of the economics project (ECO3050).
|Understand and be familiar with linear algebra concepts and associated economic and financial applications as well as develop key analytical skills.
|Develop proficiency in Matlab programming and debugging.
|Appreciate the usefulness of the Matlab software for the creation and evaluation of models that solve real world financial and economic problems.
|Master proficiency in communication skills (written, oral).
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
- develop skills in both data analysis and written/oral presentation
- develop appreciation of the variety of applications of matrices in economics and finance
- develop understanding of the use of standard software packages (i.e. MATLAB) in the analysis of economic, financial data and models
- develop understanding of basic programming techniques
The learning and teaching methods include:
- 2 hour lecture per week x 11 weeks aimed at introducing the relevant theory and topics as well as at applying the relevant theory to real-world examples and scenarios
- 1 hour computer lab sessions per week x 10 weeks aimed at supporting students' learning and application of key concepts
- Captured content video-tutorials with practical exercises (18 hours) aimed at introducing students to MATLAB programming
- Guided learning (10 hours) aimed at providing students with references in support to the material seen in class
Students are expected to actively engage throughout the course. More precisely, students are expected to contribute actively to the lectures and tutorials. Students are also expected to bring their laptop so as to practice their coding skills in lectures and tutorials.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: ECO2048
The School of Economics is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities particularly in the following areas:
Students will develop the capacity to manage information and databases pertaining to various types of data. The module also requires students to use a software (MATLAB) to showcase familiarity with a wide range of statistical and descriptive techniques. These activities have the ultimate effect of leveraging students’ digital skills.
Students are equipped with theoretical and practical problem-solving skills, and transferable mathematical and theoretical knowledge that will allow them to analyze in theory and in practice data driven financial and economic applications. All of this is highly valuable to employers for different roles: e.g. economists, financial traders and investment analysts.
Global and Cultural Capabilities
Students learn to work together in groups with other students from different backgrounds to solve assignments. This module allows students to develop skills that will allow them to effectively collaborate with individuals from around the world.
Resourcefulness and Resilience
Final group assessment features real-world problem-based tasks. This final group project also fosters the development of team working, confidence and professionalism.
Programmes this module appears in
|Economics BSc (Hons)
|A weighted aggregate mark of 40% is required to pass the module
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2024/5 academic year.