Advanced Econometrics
| Module title | Advanced Econometrics |
|---|---|
| Module code | BEEM113 |
| Academic year | 2019/0 |
| Credits | 15 |
| Module staff | Dr Namhyun Kim (Convenor) Dr Namhyun Kim (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
| Number students taking module (anticipated) | 14 |
|---|
Module description
Summary:
The module introduces you to some important topics in advanced econometrics. The primary aim is to provide a deep and sound knowledge of modern econometric concepts and techniques. The first part of the module will give you an introduction to the probabilistic foundations, and discuss the advanced theory of estimation and inference. Subsequently, various special topics will be covered.
Additional Information:
Internationalisation
While this module is designed for those interested in theory and research, mathematics is an international language, making the course content relevant across the globe in theory and in practice.
Employability
This module is highly useful for those interested in conducting research in the field of econometrics. Also, students will have the opportunity to develop their numeracy skills, which are highly valued by many employers.
Sustainability
All of the resources for this module are available on the ELE (番茄视频 Learning Environment).
Module aims - intentions of the module
The module is intended to introduce students to some important topics in advanced econometrics. The primary aim is to provide a deep and sound knowledge of modern econometric concepts and techniques. The first part of the module will give an introduction to the probabilistic foundations, and discuss the advanced theory of estimation and inference. Subsequently, various special topics will be covered.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. a mastery of the underlying concepts in probability and their application in econometrics and the analysis of economic data.
- 2. knowledge of recent literature in this area.
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 3. Applied mathematical and statistical techniques
- 4. Computer programming skills.
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 5. Self-management/time-management
- 6. Locating / using learning resources (www, library)
- 7. Communication, oral and written
- 8. Problem solving
- 9. Data analysis
Syllabus plan
Weeks 1-2: Probabilistic fundamentals and stochastic process theory.
Weeks 3-4: Asymptotic theory, with applications to regression analysis.
Weeks 5-6: Advanced estimation theory – optimization estimators and maximum likelihood.
Week 7: Asymptotic theory for unit root and cointegration models.
Weeks 8-10: Special topics, including:
o Long memory processes; theory and applications.
o Nonlinear time series models, ARCH and Markov switching.
o Bootstrap methods for statistical inference.
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 30 | 120 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Contact hours | 20 | Lectures |
| 10 | Tutorials |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Weekly problem sets | 11 weeks | 1-9 | Answers on ELE discussion with module convenor if requested |
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 |
|---|---|---|---|---|
| Examination | 100 | 2.5 hours | 1-9 | Answers on ELE discussion with module convenor if requested |
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 |
|---|---|---|---|
| Examination | Examination | 1-9 | August Examination period |
Indicative learning resources - Basic reading
Basic reading:
James Davidson, Econometric Theory, Blackwell Publishers 2000.
James Davidson, Stochastic Limit Theory, OUP 1994.
James Hamilton, Time Series Analysis. Princeton UP 1994
Russell Davidson and James MacKinnon,Econometric Theory and Methods. OUP 2002
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | None |
| Module co-requisites | BEEM102 QRT |
| NQF level (module) | 7 |
| Available as distance learning? | No |
| Origin date | 03/09/2007 |
| Last revision date | 09/10/2017 |