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The BSc Economics and Mathematics at the University of Leeds is an interdisciplinary program that combines rigorous training in both economics and mathematics. Students gain a solid foundation in economic theory and quantitative methods, preparing them for careers that require analytical and problem-solving skills. The program offers flexibility, allowing students to tailor their studies through a range of optional modules in advanced topics such as statistics, financial mathematics, and micro/macro-economics.
Key Focus Areas
Economic Theory: Microeconomics and macroeconomics fundamentals.
Mathematical Foundations: Calculus, linear algebra, and mathematical analysis.
Statistical Methods: Probability, statistics, and econometrics.
Computational Skills: Programming and numerical analysis using tools like Python.
Applied Mathematics: Financial mathematics, differential equations, and stochastic modeling.
Year-wise Breakdown
Year 1: Foundations
Mathematics:
Core Mathematics (40 credits): Functions, calculus, linear algebra.
Probability and Statistics (20 credits): Introduction to probabilistic and statistical concepts.
Computational Mathematics and Modelling (20 credits): Basic programming in Python and computational techniques.
Economics:
Economic Theory and Applications (30 credits): Introduction to micro and macroeconomic principles.
Economics and Global History (10 credits): Historical context of economic development.
Year 2: Intermediate Studies
Economics:
Intermediate Microeconomics and Macroeconomics.
Application of economic models to real-world problems.
Mathematics:
Optional modules in statistics, financial mathematics, differential equations, and numerical analysis.
Year 3: Advanced Studies and Specialization
Final Year Project:
Undertake a project in either mathematics or economics.
Optional Modules:
Economics: Environmental and development economics, international trade, business strategy.
Mathematics: Actuarial mathematics, stochastic modeling in finance, pure and applied mathematics topics.
Learning and Assessment Methods
Teaching Methods:
Lectures, tutorials, workshops, and practical classes.
Extensive tutorial support and access to facilities like the Mathematics Active Learning Lab.
Assessment Methods:
Formal examinations.
In-course assessments, including assignments and projects
Rankings
Complete University Guide 2025:
University of Leeds ranked 23rd in the UK.
Economics ranked 10th.
The Guardian University Guide 2025:
University of Leeds ranked 37th overall.
Economics ranked 31st.
Times Higher Education World University Rankings 2025:
University of Leeds ranked 123rd globally.
Business and Economics subject area ranked in the top 125 worldwide
Study Abroad: Opportunity to study at partner universities worldwide.
Work Placement: Optional industrial placement year to gain practical experience.
Research Projects: Engage n independent research in the final year.
Discovery Modules: Choose from a range of modules to broaden academic horizons
Graduates of the BSc Economics and Mathematics program are well-equipped for careers in various sectors:
Finance and Banking: Roles in investment analysis, risk management, and financial consultancy.
Data Analysis and Statistics: Positions in data science, statistical modeling, and econometrics.
Public Sector and Policy: Opportunities in government departments and policy research organizations.
Further Study: Postgraduate programs in economics, mathematics, finance, or related fields.
A-Level offer is: AAA/A*AB.Minimum percentage required (12 standard or HSC) 85%.IELTS 6.5 overall, with no less than 6.0 in any component.International Baccalaureate: 17 points.Quantitative Analyst – Build financial and economic modelsEconomic Modeller – Simulate real world economic behaviorStatistical Analyst – Interpret large datasets with economic goalsRisk Analyst – Apply probability to economic risk scenariosActuarial Analyst – Use math and economics in insuranceOperations Researcher – Optimize systems using mathematical toolsEconometrician – Conduct advanced regression and forecastingFinancial Engineer – Design investment solutions using mathAcademic – Research theoretical economics using math foundationsData Scientist – Combine algorithms with economic understanding
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