EC352-6-AU-CO:
Econometric Methods
2025/26
Economics
Colchester Campus
Autumn
Undergraduate: Level 6
Current
Thursday 02 October 2025
Friday 12 December 2025
15
20 August 2024
Requisites for this module
EC252
(none)
(none)
(none)
(none)
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 in Economics, Finance and/or Data Science 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
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 |
Description |
Deadline |
Coursework weighting |
| Coursework |
EC352 Midterm test |
|
|
| Exam |
Main exam: In-Person, Open Book (Restricted), 120 minutes during Summer (Main Period)
|
| Exam |
Reassessment Main exam: In-Person, Open Book (Restricted), 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.
Overall assessment
Reassessment
Module supervisor and teaching staff
Dr Neslihan Sakarya, email: neslihan.sakarya@essex.ac.uk.
Lectures: Dr Neslihan Sakarya / Laboratories: Mr Kai Zhang
For further information, send an email message to fineco@essex.ac.uk.
Yes
Yes
No
Dr Sanna Piritta Nurmikko-Metsola
University of Surrey
Senior Lecturer in Economics
Available via Moodle
Of 2 hours, 2 (100%) hours available to students:
0 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.
Economics
* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.
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