Module
Research Methods II
Module description
This module will introduce the students to a broad set of computational methods used by economists to solve economic models. The first part of the course covers the basic computational methods while the second part focuses on heterogeneous agent models and machine learning.
Full module specification
Module title: | Research Methods II |
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Module code: | BEEM143 |
Module level: | M |
Academic year: | 2020/1 |
Module lecturers: |
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Module credit: | 15 |
ECTS value: | 7.5 |
Pre-requisites: | BEEM136 |
Co-requisites: | None |
Duration of module: |
Duration (weeks) - term 2: 11 |
Module aims
The module goal is to equip students with a set of tools that allows them to solve economic models in an appropriate way.
ILO: Module-specific skills
- 1. identify and explain the main approaches to solving economic models;
- 2. use different approaches to solve economic models;
- 3. use visualisation techniques for presenting computational findings.
ILO: Discipline-specific skills
- 4. use different software to analyse economic data;
- 5. master numerical methods for economic analysis.
ILO: Personal and key skills
- 6. command the basics of scientific computing;
- 7. identify the relevant method to solve a problem;
- 8. work independently.
Learning activities and teaching methods (given in hours of study time)
Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
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33 | 117 | 0 |
Details of learning activities and teaching methods
Category | Hours of study time | Description |
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Scheduled Learning and Teaching Activity | 33 | Lectures (3hr per week) |
Guided Independent Study | 117 | Background reading, preparation for classes and assessments |
Formative assessment
Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
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Practice Problems | Varies | 1-8 | Oral/Written |
Summative assessment (% of credit)
Coursework | Written exams | Practical exams |
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45 | 55 | 0 |
Details of summative assessment
Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
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Practical Exam | 55 | An extended examination to be taken over a week to solve a practical problem | 1-8 | Oral/Written |
4 Problem Sets | 45 | 1-4 Problems each | 1-8 | Oral/Written |
Details of re-assessment (where required by referral or deferral)
Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
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Practical Exam (55%) | Examination 55% (3 hours) | 1-8 | August Examination Period |
Problem Sets (45%) | Problem set 45% (1-4 problems) | 1-8 | August Examination Period |
Syllabus plan
- Numerical methods: solving nonlinear equations, optimisation, approximation methods, numerical differentiation and integration, projection methods, numerical dynamic programming
- Heterogeneous Agent models
- Machine learning
Indicative learning resources - Basic reading
Judd, K.L. (1998). Numerical methods in economics. Cambridge, MA: MIT Press.
Miao, J. (2014). Economic dynamics in discrete time. Cambridge, MA: MIT Press.
Module has an active ELE page?
Yes
Origin date
24/06/2019
Last revision date
26/08/2020