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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2021/2022

Information in the Degree Programme Tables may still be subject to change in response to Covid-19

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DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Econometrics Applications in Banking (CMSE11315)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits15 ECTS Credits7.5
SummaryThis 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 courses taken on the MSc in Banking and Risk, 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.

Content:
OLS ¿ Review and Limitations
Multicollinearity, Heteroscedasticity and Autocorrelation
Instrumental Variables
Panel Data (Fixed and Random Effects)
Difference-in-Differences
Generalized 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 lectures and tutorials. 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.

Tutorial/seminar hours represent the minimum total live hours - online or in-person - a student can expect to receive on this course. These hours may be delivered in tutorial/seminar, lecture, workshop or other interactive whole class or small group format. These live hours may be supplemented by pre-recorded lecture material for students to engage with asynchronously.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2021/22, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 150 ( Seminar/Tutorial Hours 15, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 130 )
Additional Information (Learning and Teaching) Seminar/Tutorial hrs are the min total live hrs, online or in-person, students can expect to receive
Assessment (Further Info) Written Exam 70 %, Coursework 30 %, Practical Exam 0 %
Additional Information (Assessment) 70% exam (individual) - assesses all course Learning Outcomes
30% coursework (individual) - assesses course Learning Outcomes 2, 3 and 4
Feedback Not entered
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:
  1. Understand the objectives and the main characteristics of each regression model studied on the course
  2. Understand and critically assess the results of econometric models
  3. Understand and critically discuss the implications of the results of econometric models
  4. Understand and critically evaluate the limitations of the models used
  5. Select the most suitable regression model vis-à-vis the characteristics of the data and the problem analysed
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.

Resource List:
https://eu01.alma.exlibrisgroup.com/leganto/public/44UOE_INST/lists/26181398260002466?auth=SAML
Additional Information
Graduate Attributes and Skills Cognitive Skills

On completion of the course students will be able to:
- perform quantitative analyses in accordance with the type of the data used
- plan and execute projects involving empirical research
- analyse the association among variables in data sets
- assess the relevance of the results of quantitative analyses

Subject Specific Skills

After completing this course, students should be able to:
- run tests on the suitability of econometric models
- interpret the outputs of econometric models
- evaluate the performance of econometric models
- use the statistical package SAS to run several types of regressions
KeywordsNot entered
Contacts
Course organiserDr Fernando Moreira
Tel: (0131 6)51 5312
Email: Fernando.Moreira@ed.ac.uk
Course secretaryMiss Mary Anne Boeff
Tel: (0131 6)50 8072
Email: MaryAnne.Boeff@ed.ac.uk
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