Undergraduate: Level 6
Thursday 05 October 2023
Friday 15 December 2023
07 November 2023
Requisites for this module
This course covers a range of methods used in the modern application of econometric techniques to economic and financial data. Following a review of linear regression methods, students are introduced to maximum likelihood estimation and instrumental variable methods, before proceeding to a more in-depth treatment of certain classes of models that arise in economics and finance to deal with particular types of data.
These include: limited dependent variables; univariate and multivariate time series (stationary and nonstationary); and panel data. Issues of model specification, estimation and hypothesis testing will be stressed throughout. The course is designed to enable students to practise the relevant methods, rather than to derive estimators or tests, or to prove the theorems upon which these are based.
The aims of this module are:
- To teach students advanced undergraduate level econometric methods. Those methods are highly sophisticated compared to prerequisite modules such as EC252.
- To provide necessary background to students who wish to write a final year dissertation by using quantitative methods.
- To benefit students with the motivation of pursuing graduate programs or consultation type job applications.
By the end of this module, students will be expected to be able to:
- Demonstrate their knowledge of modern econometric methods.
- Analyse economic data using the appropriate techniques.
- In completing the course test, demonstrate their problem-solving analytical and deductive skills.
Employability skills include:
- Academic skills: Literacy, numeracy, problem-solving and ICT skills.
- Professional working skills: adaptability; flexibility, decision-making.
- External awareness: economic and business environment and policy.
- Personal development planning: Time management, self management, reflection and evaluation.
No additional information available.
The module will be delivered via:
- Two 1-hour lectures per week, weeks 2-11.
- One (optional) lab per week, weeks 3-11.
The above list is indicative of the essential reading for the course.
The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students.
Further reading can be obtained from this module's reading list
Assessment items, weightings and deadlines
|Coursework / exam
||EC352 Mid-Term In Person test
||Main exam: In-Person, Open Book, 120 minutes during Summer (Main Period)
||Reassessment Main exam: In-Person, Open Book, 120 minutes during September (Reassessment Period)
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Module supervisor and teaching staff
Dr Neslihan Sakarya, email: firstname.lastname@example.org.
Lectures: Dr Neslihan Sakarya / Laboratories: Mr Mohsen Eshraghi
For further information, send an email message to email@example.com.
Mr Georgios Papadopoulos
Available via Moodle
Of 30 hours, 28 (93.3%) hours available to students:
0 hours not recorded due to service coverage or fault;
2 hours not recorded due to opt-out by lecturer(s), module, or event type.
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