Undergraduate Course: Essentials of Econometrics (ECNM10052)

Course Outline
School	School of Economics	College	College of Humanities and Social Science
Course type	Standard	Availability	Available to all students
Credit level (Normal year taken)	SCQF Level 10 (Year 3 Undergraduate)	Credits	20
Home subject area	Economics	Other subject area	None
Course website	None	Taught in Gaelic?	No
Course description	Essentials of Econometrics (EE) provides an opportunity to learn skills that are important for later stages of the Economics programme, and many future career and life contexts. EE aims to ensure that all economics honours students have a sound grasp of the basic techniques of modern empirical economics. The topics covered are likely to include: statistics (review of probability distributions, statistical inference, estimation and hypothesis testing); the linear regression model (two-variable model, multiple regression, functional forms, dummy variables); regression analysis in practice (model selection criteria and tests, multicollinearity, heteroskedasticity, autocorrelation). EE includes weekly lab sessions to reinforce lectures, with exercises which foster 'learning-by-doing'. The course provides an opportunity to develop and practice key practical skills in computing, data gathering, processing, analysis and presentation.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites	Students MUST have passed: Economics 2 (ECNM08006)	Co-requisites
Prohibited Combinations		Other requirements	Pre-requisite: Economics Honours entry or the permission of the course leader.
Additional Costs	None

Information for Visiting Students
Pre-requisites	Visiting students should usually have at least 3 Economics courses at grade B or above (or be predicted to obtain this) for entry to this course. This MUST INCLUDE courses in both Macroeconomics and Microeconomics. We will only consider University/College level courses.
Displayed in Visiting Students Prospectus?	Yes

Course Delivery Information

Delivery period: 2014/15 Semester 1, Available to all students (SV1)			Learn enabled: Yes	Quota: None
Web Timetable	Web Timetable
Class Delivery Information	Students are ALSO expected to attend weekly tutorials (start in week 2) and computer lab sessions (start in week 3).
Course Start Date	15/09/2014
Breakdown of Learning and Teaching activities (Further Info)	Total Hours: 200 ( Lecture Hours 20, Seminar/Tutorial Hours 14, Supervised Practical/Workshop/Studio Hours 15, Summative Assessment Hours 4, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 143 )
Additional Notes
Breakdown of Assessment Methods (Further Info)	Written Exam 70 %, Coursework 30 %, Practical Exam 0 %
Exam Information
Exam Diet	Paper Name	Hours & Minutes
Main Exam Diet S1 (December)	Essentials of Econometrics	1:30
Main Exam Diet S2 (April/May)		2:00

Delivery period: 2014/15 Semester 1, Part-year visiting students only (VV1)			Learn enabled: Yes	Quota: None
Web Timetable	Web Timetable
Class Delivery Information	Students are ALSO expected to attend weekly tutorials (start in week 2) and computer lab sessions (start in week 3).
Course Start Date	15/09/2014
Breakdown of Learning and Teaching activities (Further Info)	Total Hours: 200 ( Lecture Hours 20, Seminar/Tutorial Hours 15, Supervised Practical/Workshop/Studio Hours 14, Summative Assessment Hours 3, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 144 )
Additional Notes
Breakdown of Assessment Methods (Further Info)	Written Exam 20 %, Coursework 80 %, Practical Exam 0 %
Exam Information
Exam Diet	Paper Name	Hours & Minutes
Main Exam Diet S1 (December)		1:30

Summary of Intended Learning Outcomes
After successful completion of this course students will have developed an understanding of the essential techniques of econometrics and an ability to apply these techniques in a variety of contexts. The course emphasises general skills such as: critical analysis and assessment; reasoning adaptably and systematically, problem-framing and problem-solving; and practical skills in data analysis and interpretation.

Assessment Information
Mini project (20%) Mid-term MCQ test (10%) 1.5 hour MCQ class exam in December (10%) 2 hour degree exam in April/May (60%) The degree examination must be passed in order to pass the course, where the degree exam is failed the final mark recorded for the course will be the degree exam mark. Visiting Student Variant Assessment Mini project (20%) Mid-term MCQ test (10%) 1.5 hour MCQ exam in December (10%) Extended problem set (60%)

Special Arrangements
None

Additional Information
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