Introduction to Econometrics for Finance
| Module title | Introduction to Econometrics for Finance |
|---|---|
| Module code | BEF1023 |
| Academic year | 2025/6 |
| Credits | 15 |
| Module staff |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
| Number students taking module (anticipated) | 200 |
|---|
Module description
BEF1023 introduces you to the theory and application of econometrics.
Additional Information:
This module is only available to first year students on the BSc Finance (and variants) degree programme. It cannot be taken with BEE1023. It cannot be taken by students on any other programme.
Employability
The module introduces methods of empirical analysis which are frequently employed in academia and businesses across many disciplines and industries.
Research in Teaching
Students will study and replicate examples from various empirical research projects in economics
Module aims - intentions of the module
BEF1023 aims to familiarise students with basic linear regression analysis and inference in the linear model.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. select, fit and interpret linear regression models in the context of economic theory;
- 2. recognise estimators, their properties and sampling distributions under standard assumptions;
- 3. perform and interpret hypothesis tests involving single and multiple coefficients;
- 4. explain how software is used in econometric analysis;
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 5. identify the role and contribution that econometrics methods make in the understanding of economic models;
- 6. discuss the limitations of econometric methods;
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 7. analyse data and communicate effectively about numerical evidence
Syllabus plan
- Review of summation notation, expected values and calculus
- The Nature of Econometrics
- The Simple Regression Model
- Multiple Regression Analysis: Estimation
- Multiple Regression Analysis: Hypothesis Testing and Confidence Intervals
- Multiple Regression Analysis: Categorical variables and further issues
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 32 | 118 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled Learning and Teaching activities | 22 | Lectures |
| Scheduled Learning and Teaching activities | 10 | Tutorials or problem classes |
| Guided Independent Study | 118 | Reading and preparation for lectures, tutorials and assessments. |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Weekly exercises | 50 minutes | 1-7 | In-class |
| Online homework quizzes | Approx. 30 minutes each | 1-7 | On ELE |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 0 | 100 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Mid-term exam | 20 | 1 hour | 1-3, 5-7 | Final grade & feedback on ELE |
| Final exam | 80 | 1.5 hours | 1-7 | Final grade & feedback on ELE |
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 |
|---|---|---|---|
| Mid-term exam | Examination (1 hour, 20%) | 1-3, 5-7 | Referral/deferral period |
| Final exam | Examination (1.5 hours, 80%) | 1-7 | Referral/deferral period |
Re-assessment notes
If you pass the module overall, you will not be referred in any component – even if you have not passed one or more individual components.
Indicative learning resources - Basic reading
- Most reading will be provided by way of lecture notes
- Selected textbook chapters may be assigned as additional reading, e.g. from Wooldridge, J.M. (2020), Introductory Econometrics: A Modern Approach, 7th edition, CENGAGE Learning.
Indicative learning resources - Web based and electronic resources
- ELE
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | BEA1014 Statistical Methods for Accounting and Finance. This module is only available to first year students on the BSc Finance (and variants) degree programme. Non-requisites (cannot be taken with): MTH1004 Probability, Statistics and Data, BEE1023 Introduction to Econometrics |
| Module co-requisites | None |
| NQF level (module) | 4 |
| Available as distance learning? | No |
| Origin date | 08/05/2025 |
| Last revision date | 08/05/2025 |
