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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2016/2017

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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 Humanities and Social Science
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.

Broadly speaking, five types of models are taught: basic linear model, linear models accounting for endogeneity, panel data, models with limited dependent variables and duration models.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2016/17, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 150 ( Lecture Hours 20, Seminar/Tutorial Hours 9, Summative Assessment Hours 2, Revision Session Hours 1, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 115 )
Assessment (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Additional Information (Assessment) The overall mark for the course will be the weighted average of two problem sets (20%), one group presentation (30%) and a final exam (50%).
Feedback All students will be given at least one formative feedback or feedforward event for every assessment component in the course in time to be useful in the completion of summative work on the course. Feedback for the individual problem sets will be just thesummative mark on the individual assignments. Explanations and solutions will be provided during tutorial 2 and tutorial 3.

Feedback on formative assessed work will be provided within 15 working days of submission, or in time to be of use in subsequent assessments within the course, whichever is sooner. Summative marks will be returned on a published timetable, which has been made clear to students at the start of the academic year.

Feedback will comprise individual feedback on the group assignment student assignments and overall exam mark feedback in the form of a report.
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 in 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. Decide 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.
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 of empirical research
- analyse the association among values 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 Davide Mare
Tel: (0131 6)51 5077
Email: Davide.Mare@ed.ac.uk
Course secretaryMiss Ashley Harper
Tel: (0131 6)51 5671
Email: Ashley.Harper@ed.ac.uk
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