Postgraduate Course: Econometrics Applications in Banking (CMSE11315)
Course Outline
| School | Business School |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 15 |
ECTS Credits | 7.5 |
| Summary | This course covers cross section and panel data techniques. Its main objective is to equip students with quantitative skills commonly needed at financial institutions and in empirical analyses used in MSc dissertations. The methods studied are illustrated with examples of their applications in banking. |
| Course description |
This course provides foundation knowledge that is required to:
1. give students a broad understanding of a variety of research questions and methodology used in empirical analyses in banking;
2. provide complementary information that is needed for students to benefit the most from other courses taken on the MSc Banking Innovation and Risk Analytics, and
3. equip students with practical skills to undertake dissertations, company sponsored projects, quantitative assignments and tasks at financial institutions.
In general, four types of models are taught: basic linear model, linear models accounting for endogeneity, panel data and models with limited dependent variables.
Outline Content
- OLS Review and Limitations
- Multicollinearity, Heteroscedasticity and Autocorrelation
- Instrumental Variables
- Panel Data (Fixed and Random Effects)
- Difference-in-Differences
- Generalised Methods of Moments
- Binary Response Models
- Multinomial Unordered Models
- Multinomial Ordered Models
- Tobit Model
Student Learning Experience
The approaches studied will be illustrated by means of practical examples in classes. The limitations of the methods taught and potential ways to overcome them will be discussed in lectures and tutorials. Students will be challenged to come up with their own ideas to solve the problems discussed.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | Students MUST also take:
Statistics for Analytics (CMSE11624)
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| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2023/24, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
150
(
Lecture Hours 16,
Seminar/Tutorial Hours 8,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
121 )
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| Assessment (Further Info) |
Written Exam
70 %,
Coursework
30 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
70% exam (individual) - assesses all course Learning Outcomes
30% coursework (individual) - assesses course Learning Outcomes 2, 3 and 4 |
| Feedback |
Formative: Feedback will be provided throughout the course.
Summative: Feedback will be provided on the assessments within agreed deadlines. |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | Econometrics Applications in Banking (CMSE11315) | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand the objectives and the main characteristics of each regression model studied on the course
- Understand and critically assess the results of econometric models
- Understand and critically discuss the implications of the results of econometric models
- Understand and critically evaluate the limitations of the models used
- Select the most suitable regression model vis-à-vis the characteristics of the data and the problem analysed
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Reading List
Wooldridge, Jeffrey (2010). Econometric Analysis of Cross Section and Panel Data. MIT Press, 2nd ed.
Verbeek, Marno (2012). A Guide to Modern Econometrics. John Willey and Sons, 4th ed.
Hill, Campbell (2012). Using SAS for Econometrics. John Wiley and Sons. |
Additional Information
| Graduate Attributes and Skills |
Communication, ICT, and Numeracy Skills
After completing this course, students should be able to:
Critically evaluate and present digital and other sources, research methods, data and information; discern their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of organisational contexts.
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| Keywords | Not entered |
Contacts
| Course organiser | Dr Fernando Moreira
Tel: (0131 6)51 5312
Email: Fernando.Moreira@ed.ac.uk |
Course secretary | Miss Aoife McDonald
Tel: (0131 6)50 8074
Email: Aoife.McDonald@ed.ac.uk |
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