Research Methods II
| Module title | Research Methods II |
|---|---|
| Module code | BEEM143 |
| Academic year | 2021/2 |
| Credits | 15 |
| Module staff | Dr Szabolcs Deak (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
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.
Module aims - intentions of the module
The module goal is to equip students with a set of tools that allows them to solve economic models in an appropriate way.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 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
On successfully completing the module you will be able to...
- 4. use different software to analyse economic data;
- 5. master numerical methods for economic analysis.
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 6. command the basics of scientific computing;
- 7. identify the relevant method to solve a problem;
- 8. work independently.
Syllabus plan
- Numerical methods: solving nonlinear equations, optimisation, approximation methods, numerical differentiation and integration, projection methods, numerical dynamic programming
- Heterogeneous Agent models
- Machine learning
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 33 | 117 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| 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 |
|---|---|---|---|
| Practice Problems | Varies | 1-8 | Oral/Written |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 45 | 55 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Practical Project | 55 | An extended project taken over a specific period of time to solve a practical problem | 1-8 | Oral/Written |
| 4 Problem Sets | 45 | 1-4 Problems each | 1-8 | Oral/Written |
| 0 | ||||
| 0 | ||||
| 0 | ||||
| 0 | ||||
| 0 |
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 |
|---|---|---|---|
| Practical Project (55%) | Practical project 55% (an extended project taken over a specific period of time to solve a practical problem) | 1-8 | August Examination Period |
| Problem Sets (45%) | Problem set 45% (1-4 problems) | 1-8 | August Examination Period |
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.
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | BEEM136 |
| Module co-requisites | None |
| NQF level (module) | 7 |
| Available as distance learning? | No |
| Origin date | 24/06/2019 |
| Last revision date | 10/11/2021 |
