MSc Economics and Data Science / Course details

Please note that this course is subject to approval.

Year of entry: 2024

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.


This course will:
  • 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.
Upon completion of the course, you will be able to:
  • 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.
You will also gain valuable skills in communicating economics and data science knowledge and research to specialist and non-specialist audiences in a variety of ways, identifying legal, ethical and security challenges in working with data, and working constructively and resiliently in a team and individually to solve challenging problems.

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.


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.

Quantitative methods preparation for the MSc:

  1. Please visit our Introduction to Quantitative Methods in Economics website for information about the minimum level of knowledge of mathematics and statistics that you should possess from your current or previous training.
  2. The website also provides details and content of our Introduction course on Quantitative Methods in Economics which builds on the knowledge gained in (1) and is designed to equip you with further technical skills that you will require before starting the MSc.
  3. You are strongly advised to attend this course which is offered free of charge. The course will run during induction week and we recommend that you spend some time between July and September studying and familiarising yourself with the course material on the website, especially if you might not be able to attend the 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.

Scholarships and bursaries

Both home and international students may benefit from scholarships, merit awards, bursaries and loans available at The University of Manchester. For further information on fees and funding, available scholarships and bursaries, as well as their full eligibility criteria, please visit our funding pages .

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: