Course description
With the emergence of data science and its successful application in many fields, there is growing interest in both the public and private sectors to explore what new insights these methods can offer on issues in economics, econometrics and finance. For governments and central banks, there is particular interest in how data science techniques can inform the formulation and evaluation of economic policy.
This programme offers a comprehensive training in the use of data science methods to analyse economic issues, covering theories, methods and applications to real world problems. The programme is designed to prepare students for employment as economic data analysts in government, central banks or the private sector.
The University of Manchester is a leading centre for economics and research-led teaching. Many famous names from the world of economics have worked here, including three Nobel Prize winners. Graduate students from across the globe come here to study economics, attracted by our first-class postgraduate training and supervision in the core and specialist areas of economics.
All of our economic’s master’s courses require you to complete an essential course before starting your studies. Details of this essential course, as well as the differences between our four master’s courses, can be found on our preparation for master’s study in economics webpage .
Aims
- Examine key theories regarding the economic behaviour at aggregate, sectoral and individual level.
- Examine the mathematical theories behind the statistical models used in econometric and data science analysis.
- Explore the key issues in the processing of information for the creation of data sets for statistical analysis.
- Support you in the development of the computer-programming skills you need to implement data scientific analysis.
- Support you to develop the skills needed to implement data scientific methods in order to contribute to the formulation and evaluation of economic policy.
- Prepare you for post-graduation employment or PhD research, through the development of digital, group-work, data-handling, presentational and writing skills.
- Analyse economic and/or policy problems using in-depth knowledge of economic theory.
- Critically assess and engage with empirical economic research.
- Identify whether particular economic problems can be investigated empirically and if so, what strategy is to be used.
- Explain features, assumptions and estimation methods used by econometric and data science methods.
- Design, develop and conduct research on empirical economic issues using statistical and data science techniques and software.
- Analyse real life data to understand and describe empirical issues across a range of disciplines and real-world settings.
Special features
Lead the way
Master an emerging field which is seeing increasing demand from the world’s top employers. Get hands-on training to prepare for a career as an economic data analyst in government, central banks, the private sector or academia.
Specialise
Take advantage of two optional modules to specialise in a variety of areas of economics and econometrics.
Guest speakers
The course will feature special guest speakers from leading organisations in economics and data science, such as the Office for National Statistics, HM Treasury, the Bank of England and private sector companies.
Teaching and learning
The MSc will require a total of 180 credits. 135 credits are obtained from the successful completion of modules and 45 credits are obtained from a research component (individual project / dissertation). The course will be structured as follows:
- 4 x 15 credit modules in Semester 1
- 3 x 15 credit modules in Semester 2
- 1 x 30 credit module across both semesters
- 1 x 45 credit research component
Of the seven modules undertaken, five will be core modules (compulsory for all students) and two will be optional (compulsory, but students may choose from a list of available modules in which to specialise).
You must first check the schedule of the compulsory course units and then select your optional units to suit your requirements.
We combine traditional lecture-based teaching with tutorials, seminars and workshop sessions. Students will be expected to work both individually and on group projects.
Updated timetable information will be available from mid-August 2024 and you will have the opportunity to discuss your unit choices during induction week with your Course Director.
Part-time students
Part-time students complete the full-time course over two years. There are no evening or weekend course units available on the part-time course.
Coursework and assessment
The Master of Economics is awarded by the University on the recommendation of the Board of the School of Social Sciences, Graduate Office. The degree will be awarded with a pass, merit or distinction.
Students who fail a master's degree may be awarded a Postgraduate Diploma if they satisfy the appropriate conventions. Once a diploma has been awarded in these circumstances, a student cannot re-enrol on a master's degree.
Course unit details
Core modules
Subject to approval, core modules may include:
- Microeconomic Theory (15 credits)
- Macroeconomic Theory (15 credits)
- Econometric Methods (15 credits)
- Data Science & Machine Learning 1 (15 credits)
- Data Science & Machine Learning 2 (15 credits)
- Skills for Data Scientists (30 credits)
Optional modules
Subject to approval, optional 15-credit modules may include:
- Financial Econometrics
- Applied Macroeconometrics
- Microeconometrics
- Healthcare Economics
- Economics of Environmental Policy
- Labour Economics
Additional options outside of Economics may be explored as the programme progresses.
Course unit list
The course unit details given below are subject to change, and are the latest example of the curriculum available on this course of study.
Title | Code | Credit rating | Mandatory/optional |
---|---|---|---|
Microeconomic Theory | ECON60101 | 15 | Mandatory |
Macroeconomic Theory | ECON60111 | 15 | Mandatory |
Introduction to Quantitative Methods in Economics | ECON60901 | 0 | Mandatory |
Econometric Methods | ECON61001 | 15 | Mandatory |
Data Science and Machine Learning 1 | ECON61351 | 15 | Mandatory |
Data Science and Machine Learning 2 | ECON62012 | 15 | Mandatory |
Programming and other Skills for Data Scientists | ECON62020 | 30 | Mandatory |
Dissertation (for MSc Economics & Data Science) | ECON65000 | 45 | Mandatory |
Microeconometrics | ECON60052 | 15 | Optional |
Financial Econometrics | ECON60332 | 15 | Optional |
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Scholarships and bursaries
The School offers a number of awards for students applying for master's study.
To find our more, please visit our master's funding opportunity search page.