Economics (Econometrics and Big Data) MSc - 2026/7
Awarding body
University of Surrey
Teaching institute
University of Surrey
Framework
FHEQ Levels 6 and 7
Final award and programme/pathway title
MSc Economics (Econometrics and Big Data)
Subsidiary award(s)
| Award | Title |
|---|---|
| PGDip | Economics (Econometrics and Big Data) |
| PGCert | Economics (Econometrics and Big Data) |
Professional recognition
Chartered Institute of Management Accountants (CIMA)
Accredited by the Chartered Institute of Management Accountants (CIMA) for the purpose of exemption from some professional examinations through the Accredited degree accelerated route.
Modes of study
| Route code | Credits and ECTS Credits | |
| Full-time | PLC61017 | 180 credits and 90 ECTS credits |
QAA Subject benchmark statement (if applicable)
Other internal and / or external reference points
N/A
Faculty and Department / School
Faculty of Arts, Business and Social Sciences - Economics
Programme Leader
GARFAGNINI Umberto (Economics)
Date of production/revision of spec
15/11/2024
Educational aims of the programme
- Engage the whole learner with a transformative curriculum that promotes advanced knowledge and offers ample opportunity to do, create, develop, and self-reflect
- Enhance student employability, resilience and resourcefulness, global and cultural capabilities, sustainability awareness, and digital capabilities (the five pillars of the University of Surrey's Curriculum Framework) through a range of appropriate, contemporary, and engaging pedagogical methods
- Develop an appreciation of economics, both as an intellectual discipline and as an important contributor to an understanding of the world in ways which are of practical significance, with a focus on the use of econometric techniques applied to big data
- Facilitate effective learning and communication within an open, scholarly environment by fostering knowledge discovery and the creation of personal meaning
- Promote the capacity for independent study through the completion of an MSc dissertation in econometrics and big data
- Prepare students for a range of careers in which advanced quantitative analysis and independent thought, as well as the qualities developed through the application of the curriculum framework, can contribute to self-fulfilment and/or an improvement in social and economic welfare
- Enable better performing students completing the programme to progress to postgraduate research in economics and econometrics
Programme learning outcomes
| Attributes Developed | Awards | Ref. | |
| Demonstrate an advanced understanding of the core principles in microeconomics, macroeconomics, and econometrics with a focus on the use of econometric techniques applied to big data | K | PGCert, PGDip, MSc | |
| Show a systematic understanding of the techniques used in contemporary economic research | K | PGDip, MSc | |
| Establish a critical awareness of current and advanced problems and the methodologies that are most common in economics and econometrics | K | PGCert, PGDip, MSc | |
| Evidence understanding of different methodologies and an ability to choose amongst these as required in different settings, with a special reference to big data | C | PGDip, MSc | |
| Combine relevant theory and analytical techniques with insightful data analysis to produce convincing explanations of economic phenomena | C | MSc | |
| Comprehend published economic research papers and integrate the implications of published research in own studies | C | PGDip, MSc | |
| Demonstrate high-level problem-solving skills | P | PGDip, MSc | |
| Select appropriate techniques to evaluate policy interventions | P | PGDip, MSc | |
| Communicate the results of independent research in the form of a dissertation | P | MSc | |
| Display programming skills to be used in estimations of models with big data | P | PGDip, MSc | |
| Exhibit Interpersonal and generic skills, such as communication, literacy, numeracy, IT | T | PGCert, PGDip, MSc |
Attributes Developed
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Programme structure
Full-time
This Master's Degree programme is studied full-time over one academic year, consisting of 180 credits at FHEQ level 7*. All modules are semester based and worth 15 credits with the exception of project, practice based and dissertation modules.
Possible exit awards include:
- Postgraduate Diploma (120 credits)
- Postgraduate Certificate (60 credits)
*some programmes may contain up to 30 credits at FHEQ level 6.
Programme Adjustments (if applicable)
N/A
Modules
Year 1 (full-time) - FHEQ Levels 6 and 7
Module Selection for Year 1 (full-time) - FHEQ Levels 6 and 7
Two from the list of optional modules
Opportunities for placements / work related learning / collaborative activity
| Associate Tutor(s) / Guest Speakers / Visiting Academics | N | |
| Professional Training Year (PTY) | N | |
| Placement(s) (study or work that are not part of PTY) | N | |
| Clinical Placement(s) (that are not part of the PTY scheme) | N | |
| Study exchange (Level 5) | N | |
| Dual degree | N |
Other information
The School of Economics is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This programme is designed to allow students to develop knowledge, skills, and capabilities, particularly in the following areas.
Employability: Students are equipped with theoretical and practical problem-solving skills, and transferable mathematical, statistical, and theoretical knowledge that will allow them to analyse in theory and in practice (big) data-driven financial and economic applications. All of this highly valuable to employers for different roles.
Digital capabilities: Students will develop the capacity to manage information and databases pertaining to various types of data, i.e., cross-section and time series. The programme also requires students to use software to showcase familiarity of with a wide range of statistical, descriptive and machine learning techniques.
Global and cultural capabilities: Students learn more about real-world examples, working with data from different and heterogeneous sources and countries.
Sustainability: This programme uses real life examples and builds students' views towards a sustainable society, including topics which blend together theoretical ideas and practical examples of the difficulties in achieving a sustainable world.
Resourcefulness and Resilience: This programme relies on key event sessions and class dialogue and discussion to face feelings of anxiety and stress. The programme features 'service learning'-based assessment, small group tutoring and student-led, solution-focused, independent learning approach.
Quality assurance
The Regulations and Codes of Practice for taught programmes can be found at:
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2026/7 academic year.