Applied Econometrics 1
| Module title | Applied Econometrics 1 |
|---|---|
| Module code | BEEM011 |
| Academic year | 2019/0 |
| Credits | 15 |
| Module staff | Dr Jack Rogers (Convenor) Dr Eva Poen (Lecturer) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 12 |
| Number students taking module (anticipated) | 140 |
|---|
Module description
This module includes the basic statistical foundation to study econometrics, the simple linear regression model, multi-regression model, empirical examples (CAPM, Demand function study), linear time series and nonlinear time series models.
Module aims - intentions of the module
The module aims to provide students with an applied econometric foundation necessary in order to conduct a high-standard empirical analysis of economic and finance data.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. Demonstrate aptitude in the econometric techniques to analyse economic and financial data
- 2. Exhibit technical expertise to analyse the data with a econometric software package
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 3. Formulate hypotheses of interest, derive the necessary tools to test these hypotheses and interpret the results
- 4. Demonstrate a specialised knowledge of linking the theory and empirical questions
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 5. Solve the analytical problems and provide appropriate interpretation of the outcomes for decision making
- 6. Demonstrate data analysis skills
Syllabus plan
The syllabus plan is as follows:
- Statistical fundamentals
- Linear regression models?
- Empirical examples of linear regression models
- Further issues on linear regression model
- Linear time series
- Nonlinear time series
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 36 | 114 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled Learning and Teaching activities | 33 | Lectures (10*2 hours+1h (week1 )) and Tutorials (11*1 hour) |
| Guided independent study | 40 | Writing up reports from empirical analysis of real data |
| Guided independent study | 40 | Reading and research |
| Guided independent study | 36 | Learning and practicing the econometric software package |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Weekly exercises | 5-10 questions | 1-6 | Verbal |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 40 | 60 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Two written Assignments | 40 | 1500 words maximum each | 1-6 | Written |
| Written Exam | 60 | 2 hours | 1, 3, 4 and 5 | Written |
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 |
|---|---|---|---|
| Two assignments | Two assignments (1500 words each) 40% | 1-6 | July |
| 2 hour exam | 2 hour exam 60% | 1, 3, 4 and 5 | August |
Indicative learning resources - Basic reading
Basic reading:
Basic Econometrics by Damodar N. Gujarati, 2009 (McGram Hill),
Introduction to Econometrics by Christopher Dougherty, 2016 (Oxford)?
The Econometric Modelling of Financial Time Series by Terence C. Mills 2008 (Cambridge)
?
Indicative learning resources - Other resources
Time Series Modelling (TSM): Econometrics Software Package
| 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 | 29/09/2016 |
| Last revision date | 24/09/2019 |