Course details
- Full-time: 12 months
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MSc Data Science for Economics is an excellent opportunity for students who wish to pursue a career requiring a sophisticated understanding of the way data is used in businesses and utilising state-of-the-art analytical skills to solve problems.
Data is everywhere in the modern economy and businesses are seeking talented new recruits to leverage it. The ability to extract, handle, and analyse large amounts of data is a key skill at the modern company to unlock the potential of firms.
MSc Data Science for Economics offers you rigorous training in the big data methods and cutting-edge econometric tools needed to answer the most important questions facing businesses. You will be fully prepared to work as a data scientist, statistician, or economist, driving the analytical direction of their firms.
MSc Data Science for Economics will teach you how to model economic problems, collect and analyse data, conduct rigorous empirical analyses, and discuss their work with diverse audiences. The modules in this programme cover a wide range of fields within economics and data science.
You will be taught to use data for forecasting and evaluating different policy options through models built on an understanding of causal relationships. Technical skills and competencies are at the heart of each module in the programme, and at the end of their studies, you will have a familiarity with two or more software packages (such as Python, R, and STATA).
The Management School has ringfenced a number of ULMS Excellence Scholarships for our economics master’s programmes. Eligibility and more information can be found on the School’s scholarship pages. In addition, international students could be eligible to receive a discount of up to £7,500 off your tuition fees with the University of Liverpool Postgraduate Global Advancement Scholarship, find out more on the Postgraduate Global Advancement Scholarship webpages.
The University of Liverpool Management School is one of an elite group of institutions worldwide to hold the gold standard ‘triple-crown’ accreditation from AACSB, AMBA and EQUIS.
Discover what you'll learn, what you'll study, and how you'll be taught and assessed.
The 12 month programme consists of seven compulsory modules and one optional module, followed by a dissertation carried out over the summer period upon completion of Semester two.
In addition to the modules outlined below, a new required module: Data Management and Visualisation for Economics will be taught in Semester one.
Econometric and statistical methods are of vital importance for estimating relationships between economic and financial variables, and for making predictions about the future. Central banks maintain large scale forecasting models for macroeconomic variables, for instance, and policy institutes use a wide range of econometric tools for modeling macroeconomic or microeconomic data. Within the private sector, financial analysts routinely estimate volatility models, credit risk departments estimate probability of default models, and, as a final example, marketing departments in large e-businesses make use of website hit counts and treatment test methods to test for the effect of their promotions on demand. These are just a few examples of how relatively advanced econometric methods are used in practice. ECON814 Econometric and Statistical Methods lays the foundation for learning the more specialised methods taught in ECON920 Advanced Econometrics, and equips the participant with a good general understanding of the methods used for estimating and testing linear and nonlinear relationships between variables.
In this module students will get a well-rounded overview of modern macroeconomics. Topics covered are facts about growth, the Solow growth model (theory and empirics), the Neoclassical growth model (growth with dynamic optimisation), and endogenous technical change. The second half of the module will focus on real business cycle models and the new Keynesian framework. We will evaluate the successes and failures of the basic models in matching data.
This module aims to provide an understanding of the essentials of microeconomic theory. This includes understanding what is meant by rational choice and how it can be used to predict what choices agents will make in different contexts. Students will also understand how markets work and what causes markets to fail.
The 12 month programme consists of seven compulsory modules and one optional module, followed by a dissertation carried out over the summer period upon completion of Semester two.
This module will provide students with an understanding of modern econometric time series methodology suitable for applications to financial and macroeconomic data. Topics include model selection, estimation and forecasting for univariate models; nonstationary models and testing for nonstationarity; models with conditional heteroscedasticity; and model selection, estimation and forecasting for multivariate models and testing for cointegration.
The module covers empirical strategies for applied microeconometric research. The focus is on methodological issues related to the estimation of causal or treatment effects. In each case, the empirical methods will be illustrated by papers drawn from the recent literature. There will be a particular focus on examples drawn from public economics, health economics, development economics, and labour economics.
Machine Learning and Big Data Econometrics teaches students the fundamentals of data analysis for big data. Students will be taught the latest machine learning methods, as well as how to implement machine learning using the Python coding language. Students will be taught valuable technical skills which apply to a wide range of careers in research and data science. Example topics include LASSO, Random Forests, and Deep Learning. The module will discuss the application of machine learning methods to economics and business.
The main objective of this module is to develop a microeconomic and a macroeconomic perspective of banking. Students will acquire a comprehensive insight into the specific nature of a bank as a firm, the role of banks in an economy, and of the regulatory environment in which banks operate. The module establishes an economic foundation for the banking sector and examines its significance for the macro-economy, employing a quantitative approach to introduce students to various banking topics.
This module covers a variety of cutting-edge topics in economics. Based on articles published in peer reviewed academic journals, publications by international and government agencies, and working papers, this module is delivered by several research active staff specialising in each area. The module is a mix of lectures delivered by staff and roundtable discussions led by student presentations.
This module covers the core concepts of labour economics. There is a strong emphasis on empirical analysis and the usage of practical models of labour markets to analyse public policy. In this module, topics to be covered include labour supply and demand, wages and compensation, labour market policies, and inequality and discrimination in the labour market. Empirical examples will feature a range of countries, industries, and demographic groups to allow students to compare and contrast how labour markets function under different competitive environments and policy regimes.
This module covers the core concepts in public economics. There is a strong emphasis on empirical analysis and the usage of practical models that explain the government’s intervention in the economy, and the interaction between the government and various economic agents. In this module, topics to be covered include provision of public goods, externalities and environmental protection, taxation, tax policy and redistribution, social insurance programs, and voting and enfranchisement. Empirical examples will feature a range of countries, different levels of government within a country, and the role of government programs and policies in the economy.
The 12 month programme consists of seven compulsory modules and one optional module, followed by a dissertation carried out over the summer period upon completion of Semester two.
Comprising two elements: research methods introduces students to the principles and practices of researching and writing dissertations and results in an agreed outline plan of work for the dissertation and a completed literature review. The dissertation itself will be undertaken over the summer period and will involve the implementation of the research work plan and the completion of a 15,000-20,000 word dissertation.
Modules are taught using the latest active learning techniques including real-world case studies, social media, lecture capture and real-time financial and business data using our Bloomberg trading floor.
The principal forms of teaching are face-to-face lectures and seminars with lectures normally being supported by material such as hand-outs and presentations. Seminars give the opportunity for detailed discussion of a topic under the direction of a tutor. You are normally expected to prepare work in advance for seminars and may be expected to present work or give presentations.
In addition, this course offers an enhanced programme of events and activities such as coding bootcamps and guest speakers.
Following semester two you will complete a dissertation the support of an academic supervisor.
Teaching time will account for an average of 10 hours per week and you should anticipate an additional 30 hours of self-directed study and group work.
In semester one and two, you will take modules totalling 120 credits. The dissertation completed during the summer period is worth 60 credits and students will be supported by their academic supervisor.
Students are required to complete 180 credits to achieve a full MSc.
Subject to meeting specific criteria outlined by the University, students will graduate with a Pass, Merit or Distinction.
Assessment tasks are varied and some may be designed specifically to meet the learning outcomes of a particular programme of study, but students can expect to be assessed via coursework, essay, group work, presentations, case studies, negotiation exercises, reports and examinations. The weighting of individual components will vary from one module to another. All assessment information is included within the module specification.
We have a distinctive approach to education, the Liverpool Curriculum Framework, which focuses on research-connected teaching, active learning, and authentic assessment to ensure our students graduate as digitally fluent and confident global citizens.
This programme is delivered by the triple-accredited University of Liverpool Management School.
The School has a thriving international master’s community with a comprehensive, interdisciplinary programme of social and extra-curricular events and dedicated careers and employability support.
Start your postgraduate economics journey at the University of Liverpool Management School.
From arrival to alumni, we’re with you all the way:
The rigorous training offered as part of the MSc Economics course has been essential for building my skills as a practising economist. The programme has a wonderful blend of modules and can really be tailored depending on different students’ career or research aspirations.
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The Management School’s master’s programmes have been designed from the ground up to prepare you for success in your chosen career. We have close ties with local, national and international organisations and constantly review the content of our programmes to meet the demands of top graduate employers.
You will have access to a specialist, in-house postgraduate careers team and have access to one-to-one careers guidance, workshops, seminars, and employability initiatives.
This new programme has been designed with employability at its heart and will appeal to students looking to work in data science and tech roles.
During the year, you can take part in dedicated skills and employability days including coding bootcamps in R and python to allow you to reach software fluency and allow you to excel at any task in the workplace.
The School will also host an event for data scientists from industry and the civil service to talk to you and give an insight into the career possibilities open to you.
Your tuition fees, funding your studies, and other costs to consider.
UK fees (applies to Channel Islands, Isle of Man and Republic of Ireland) | |
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Full-time place, per year | £13,500 |
International fees | |
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Full-time place, per year | £28,500 |
Tuition fees cover the cost of your teaching and assessment, operating facilities such as libraries, IT equipment, and access to academic and personal support.
If you're a UK national, or have settled status in the UK, you may be eligible to apply for a Postgraduate Loan worth up to £12,167 to help with course fees and living costs. Learn more about paying for your studies..
We understand that budgeting for your time at university is important, and we want to make sure you understand any course-related costs that are not covered by your tuition fee. This could include buying a laptop, books, or stationery.
Find out more about the additional study costs that may apply to this course.
We offer a range of scholarships and bursaries that could help pay your tuition and living expenses.
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The qualifications and exam results you'll need to apply for this course.
We've set the country or region your qualifications are from as United Kingdom. Change it here
Your qualification | Requirements |
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Postgraduate entry requirements |
A 2:1 Honours degree (or overseas equivalent) in Economics or a related discipline with a quantitative focus. Students with a 2:1 degree from a quantitative science discipline (e.g. Maths, Physics, Statistics, Operations Research) are also encouraged to apply. Applicants should have competency in A Level Mathematics/ Statistics or equivalent. We are able to offer a level of flexibility for applicants. Those with a 2:2 honours degree will be considered on an individual basis. |
International qualifications |
If you hold a bachelor’s degree or equivalent, but don’t meet our entry requirements, a Pre-Master’s can help you gain a place. This specialist preparation course for postgraduate study is offered on campus at the University of Liverpool International College, in partnership with Kaplan International Pathways. Although there’s no direct Pre-Master’s route to this MSc, completing a Pre-Master’s pathway can guarantee you a place on many other postgraduate courses at The University of Liverpool. |
You'll need to demonstrate competence in the use of English language, unless you’re from a majority English speaking country.
We accept a variety of international language tests and country-specific qualifications.
International applicants who do not meet the minimum required standard of English language can complete one of our Pre-Sessional English courses to achieve the required level.
English language qualification | Requirements |
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IELTS | 6.5 overall, with no component below 6.0 |
TOEFL iBT | 88 overall, with minimum scores of listening 19, writing 19, reading 19 and speaking 20 |
Duolingo English Test | 120 overall, with no component below 105 |
Pearson PTE Academic | 61 overall, with no component below 59 |
LanguageCert Academic | 70 overall, with no skill below 65 |
PSI Skills for English | B2 Pass with Merit in all bands |
INDIA Standard XII | National Curriculum (CBSE/ISC) - 75% and above in English. Accepted State Boards - 80% and above in English. |
WAEC | C6 or above |
Do you need to complete a Pre-Sessional English course to meet the English language requirements for this course?
The length of Pre-Sessional English course you’ll need to take depends on your current level of English language ability.
Find out the length of Pre-Sessional English course you may require for this degree.
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Last updated 8 October 2024 / / Programme terms and conditions