Module
Quantitative Research Techniques 2
Module description
Summary:
This module builds on Quantitative Research Techniques I and further develops your knowledge and understanding of econometric and methodological research tools and the application of various econometric methods and techniques to real life problems.
Additional Information:
Internationalisation
This methods covered in this module, such as those used to forecast inflation and GDP, are applicable across countries.
Sustainability
All of the resources for this module are available on the ELE (Exeter Learning Environment).
Employability
Students gain an understanding of the statistical techniques used to study topics such unemployment and forecasting inflation and economic growth which are all necessary skill for working in central banks. They also develop their numerical and problem-solving skills in learning these mathematical techniques.
Full module specification
| Module title: | Quantitative Research Techniques 2 |
|---|---|
| Module code: | BEEM112 |
| Module level: | M |
| Academic year: | 2022/3 |
| Module lecturers: |
|
| Module credit: | 15 |
| ECTS value: | 7.5 |
| Pre-requisites: | None |
| Co-requisites: | BEEM102 |
| Duration of module: |
Duration (weeks) - term 2: 11 |
Module aims
This module aims at providing the students with the necessary econometric and methodological research tools to equip them for carrying out empirical research projects as well as understand the contents of other Masters level modules.
The module is dedicated to the application of various econometric methods and techniques to real life problems.
ILO: Module-specific skills
- 1. apply modern econometric techniques in the analysis of economic data
ILO: Discipline-specific skills
- 2. formulate hypotheses of interest, derive the necessary tools to test this hypothesis and interpret the results
- 3. show a specialised knowledge of applied aspects of econometrics that will enable him/her to carry out applied research or direct them towards an academic career
ILO: Personal and key skills
- 4. have technical expertise in computing software, particularly econometric software, to tackle empirical problems
- 5. demonstrate confidence in identifying, tackling and solving research problems
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 |
|---|---|---|
| Contact hours | 22 | Lectures |
| 11 | Tutorials |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Weekly exercises | 5-15 questions per week | 1-5 | Written or verbal feedback |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 20 | 80 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Assignment | 20 | The assignment will be approximately of 5xA4 pages. | 1-5 | Written or verbal feedback |
| Written examination in May/June | 80 | Two hours | 1-5 | Written or verbal feedback |
| 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 |
|---|---|---|---|
| Assignment (20%) | Assignment (20%) (approx. 5 x A4 pages) | 1-5 | Standard re-assessment period |
| Written examination in May/June (80%) | Written exam (80%) (2 hours) | 1-5 | Standard re-assessment period |
Syllabus plan
Topics:
• Topics in estimation techniques:
1. Maximum Likelihood Estimation
2. Generalized Method of Moments
• Topics in Microeconometrics:
1. Binary choice Models and Limited Dependent Variables
2. Panel Data Models
• Topics in Time Series:
1. Univariate Time Series Models
2. Multivariate Time Series Models
3. Unit Roots and Cointegration
Indicative learning resources - Basic reading
Basic reading:
Indicative basic reading list:
Greene, W. (2008), Econometric Analysis, New Jersey: Prentice Hall, 6th Edition. (main textbook.)
Cameron, C. and P. Trivedi, (2005 ) Microeconometrics: Methods and Applications, Cambridge University Press
Hamilton, J. D. (1994), Time Series Analysis, Princeton University Press.
Module has an active ELE page?
Yes
Origin date
16/07/2014
Last revision date
23/09/2021