COMPUTATIONAL METHODS IN MACROECONOMICS - 2023/4
Module code: ECO3063
Module Overview
This module introduces students to computational methods for solving and simulating economic models. The student will learn basic results and techniques in numerical analysis, acquire a working knowledge of programming language, and learn how to apply these tools to analyse quantitative implications of macroeconomic dynamic models and macroeconometrics. Matlab will be the main language taught in the course, while learning other languages (e.g. Python, Julia, etc) will be optional.
Module provider
Economics
Module Leader
TSUJIYAMA Hitoshi (Economics)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 6
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 63
Lecture Hours: 22
Laboratory Hours: 5
Guided Learning: 38
Captured Content: 22
Module Availability
Semester 2
Prerequisites / Co-requisites
None
Module content
-Command the basics of programming language
-Numerical analysis
-Basic dynamic macroeconomic models
-Macroeconomic policy analysis with computational modeling and coding
Assessment pattern
| Assessment type | Unit of assessment | Weighting |
|---|---|---|
| Coursework | COURSEWORK 1 | 50 |
| Coursework | COURSEWORK 2 | 50 |
Alternative Assessment
Different individual coursework assignments will be given for students who are resitting.
Assessment Strategy
The assessment strategy is designed to provide students with the opportunity to demonstrate: Familiarity and understanding of the theoretical notions of numerical methods as well as being able to implement quantitative analysis through programming language of real world macroeconomic policy.
Thus, the summative assessment for this module consists of:
- a first coursework
- a final coursework
Formative assessment & feedback
Students receive verbal feedback during the in-person lectures and tutorial sessions. Students are provided with a set of exercises relating to the lecture material which they solve independently or in teams in preparation for the tutorials. In these seminar tutorials, they receive feedback on their answers, and guidance on how these answers could be improved. In addition to this, students receive guideline solutions online. Office hours provide students with further feedback and consultation opportunities.
Module aims
- Appreciation of the relevance of computational analysis in economics
- Understand basic techniques for macroeconomic modelling
- Be able to write intuitive algorithms and clear computer code
Learning outcomes
| Attributes Developed | ||
| 001 | Understanding numerical methods for economic analysis | CKP |
| 002 | Establish a computational strategy to solve an economic model | CKP |
| 003 | Investigate the impact of macroeconomics policy with quantitative analysis | CKP |
| 004 | Develop effective teamwork on a common project | CKPT |
Attributes Developed
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: Explore the theoretical concepts of numerical methods and familiarize with computation coding. Be able to apply the computational technique learned in the lectures to macroeconomic policy. Equip students with the necessary knowledge and skills to enable them to conduct independent research in the field of quantitative economics. The learning and teaching methods include:
- Lectures
- 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.
Reading list
https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: ECO3063
Other information
This module incorporates some of the University's five pillars of learning as follows:
Resourcefulness and resilience: Students in this module will develop their understanding and skills through assessment and feedback in tutorials.
Employability: This module will provide students with relevant soft skills to prepare them to successfully compete in the labour market and continuing education.
Digital Capabilities: This module will provide students with relevant programming skills to carry out quantitative work.
Programmes this module appears in
| Programme | Semester | Classification | Qualifying conditions |
|---|---|---|---|
| Economics and Mathematics BSc (Hons) | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |
| Economics and Finance BSc (Hons) | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |
| Business Economics BSc (Hons) | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |
| Economics BSc (Hons) | 2 | Optional | 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 2023/4 academic year.