Quantitative Research Techniques 1
| Module title | Quantitative Research Techniques 1 |
|---|---|
| Module code | BEEM102 |
| Academic year | 2021/2 |
| Credits | 15 |
| Module staff | Dr Sebastian Kripfganz (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
| Number students taking module (anticipated) | 40 |
|---|
Module description
Econometrics is the branch of economics devoted to the development and application of statistical methods to the study and clarification of the economic phenomena. This module provides an advanced introduction to econometric theory at the level of an MRes Economics programme. Econometric theory is a collection of mathematical and statistical ideas and principles that motivates much of the empirical analysis by economists.
Module aims - intentions of the module
This module aims at providing the students with an introduction to the theory of econometrics covering important topics in econometric estimation and inference. The module will provide students with the necessary knowledge for understanding recent developments in econometrics.
The module will help students carry out future applied econometric analysis since understanding the underlying econometric theory is important in order to make reasonable judgments about the methods to implement.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. demonstrate an in-depth understanding of theoretical aspects of important topics in econometrics
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 2. demonstrate an ability to apply important general principles and tools used in econometrics
- 3. demonstrate a specialised knowledge of theoretical aspects of econometrics to enable him/her to carry out applied research or direct them towards an academic career
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 4. demonstrate a logical attitude towards the solution of problems
- 5. demonstrate confidence in identifying, tackling and solving research problems
Syllabus plan
The following non-exclusive list gives an indication about possible topics covered by this module:
1. Review of matrix algebra and statistical theory
2. The linear regression model
- Ordinary least squares estimation
- Unbiasedness and efficiency
3. Model specification and hypothesis testing
- The partitioned regression model
- Omitted variables and irrelevant regressors
- Goodness of fit
- Testing linear restrictions
4. Asymptotic theory
- Modes of convergence
- • Consistency and asymptotic normality
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 27 | 123 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Contact hours | 22 | Lectures |
| Contact hours | 5 | Tutorials |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Bi-weekly exercises | 1-6 questions | 1-5 | Oral / written |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 30 | 70 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Problem Set | 15 | 2-4 problems | 1-5 | Oral / written |
| Problem Set | 15 | 2-4 problems | 1-5 | Oral / written |
| Examination | 70 | 2 hours | 1-5 | Oral / written |
| 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 |
|---|---|---|---|
| Problem Sets and Examination | Examination (100%) 2 hours | 1-5 | August Examination Period |
Indicative learning resources - Basic reading
Main textbook:
Greene, W. H. (2012). Econometric Analysis, 7th Edition (Int. Edition), Essex: Pearson.
Additional reading:
Davidson, R. and MacKinnon, J. (2009). Econometric Theory and Methods, Int. Edition, New York: Oxford University Press.
Hayashi, F. (2000). Econometrics, New Jersey; Woodstock: Princeton University Press.
Johnston, J. and DiNardo, J. (1997), Econometric Methods, 4th Edition, New York: McGraw-Hill.
Verbeek, M. (2012). A Guide to Modern Econometrics, 4th Edition, Chichester: Wiley.
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | None |
| Module co-requisites | None |
| NQF level (module) | 7 |
| Available as distance learning? | No |
| Origin date | 17/07/2014 |
| Last revision date | 06/02/2019 |
