BSc (hons) mathematics with economics

3 Years On Campus Bachelors Program

London School of Economics and Political Science

Program Overview

The BSc (Hons) Mathematics with Economics at LSE combines rigorous mathematics and statistical training with core economics theory — ideal if you enjoy problem-solving, analytics, and economic thinking. This degree gives you a strong foundation in mathematical methods, probability/statistics, and economic modelling, preparing you for careers in finance, economics, data analysis, policy, or further academic study.

Curriculum Structure

Year 1

In the first year, you build your mathematical and statistical fundamentals through modules such as Mathematical Methods and Elementary Statistical Theory, which cover calculus, algebra, probability, and basic statistics. Concurrently, you take Microeconomics I, introducing economic principles and decision-making frameworks, and the course LSE100, designed to develop academic skills and interdisciplinary thinking. This early mix helps you become comfortable with both quantitative analysis and foundational economic concepts.

Year 2

During the second year, your mathematics and statistics training becomes more advanced: you take Further Mathematical Methods and more in-depth statistical/econometric courses like Probability, Distribution Theory & Inference and Applied Regression. These strengthen your ability to handle data, uncertainty, and modelling — skills essential for economics, finance, or data-driven roles. Alongside, you begin choosing elective modules (in economics, business, finance or further maths/statistics) to tailor your studies toward your interests and career goals.

Year 3 (Honours Year)

In your final year, you focus on advanced electives and specialisation: you select from higher-level mathematics, statistics or economics/finance modules depending on your intended pathway (for example, financial economics, econometrics, economic policy, quantitative analysis, etc.). This structure gives you flexibility to build a profile suited for finance, economic analysis, research, consulting or data-driven industries — consolidating quantitative skills with economic understanding.

Focus areas

"Mathematics, probability and statistics, economic theory, econometrics, quantitative modelling, data analysis, financial economics, economic policy and business applications."

Learning outcomes

"You will graduate with strong mathematical and statistical reasoning, the ability to model and analyze economic and financial problems quantitatively, data-analysis and econometric skills, and a deep understanding of both abstract mathematics and applied economic theory — ready for roles in finance, economics, data analysis, consulting or further academic study."

Professional alignment (accreditation)

While not tied to a single professional accreditation, this degree provides a robust quantitative and economics foundation aligned with careers in finance, banking, economic policy, consulting, data analysis, and research. It also serves as a strong basis for postgraduate studies in economics, finance, mathematics or data-related disciplines.

Reputation (employability rankings)

LSE’s Economics and Mathematics departments are internationally recognized and the university is widely regarded as a leading institution for social sciences and quantitative disciplines. Graduates of this programme are highly sought-after by top finance firms, economic consultancies, data–analytics companies, governmental and international organisations — reflecting excellent employability and career outcomes.

Experiential Learning (Research, Projects, Internships etc.)

The BSc Mathematics with Economics at LSE is designed for students who want strong mathematical depth combined with a solid grounding in economics. From your first term, you work with mathematical methods, probability, statistics, and introductory economic theory — giving you a robust analytical foundation. As you progress, the course blends advanced mathematics with intermediate and advanced economics, allowing you to understand economic behaviour, market structures, financial systems, and policy analysis through a quantitative lens.

Because the programme is jointly delivered by the Mathematics and Economics Departments, your learning is shaped by two academically renowned units. You’re exposed to research-informed teaching in areas like optimisation, discrete mathematics, financial mathematics, and economic modelling. This is exactly the kind of training valued in consulting, finance, economic research, tech, and policy roles.

To show you the practical experience clearly, here’s how your real-world learning develops:

🎯 Experiential Learning — Tools, Methods & Hands-On Training

Integrated Maths–Economics Start in Year 1
You begin with Mathematical Methods, Introduction to Abstract Mathematics, Elementary Statistical Theory, plus Microeconomics and Macroeconomics. This gives you both computational fluency and an understanding of core economic frameworks.
Advanced Mathematical Training in Years 2 & 3
You continue into deeper areas such as real analysis, further mathematical methods, probability, discrete mathematics, optimisation, or differential equations — depending on your chosen electives.
Economics Applied Through Quantitative Methods
Alongside mathematics, you take intermediate and advanced microeconomics and macroeconomics. These courses emphasise formal modelling, allowing you to see how mathematics drives economic theory.
Small-Group Classes and Workshops
Many modules include seminar classes or problem-solving sessions, giving you hands-on practice, guided feedback, and experience working through mathematical and economic models in a workshop environment.
Research-Led Content
You learn in a department active in optimisation, operations research, discrete mathematics, financial mathematics, and algorithmic methods. This means your training reflects current industry and research trends.
Modelling and Analytical Problem-Solving
The programme emphasises practical modelling — how mathematical techniques help explain real economic systems, forecast outcomes, analyse data, or support financial and policy decisions.
Flexibility to Tailor Optional Modules
In later years, you can choose from optional mathematics, statistics, or economics units, allowing you to specialise in areas like financial mathematics, probabilistic modelling, econometrics, or optimisation.

💡 Why Students Choose This Degree

The programme is mathematically rigorous, making it perfect for students who want a quantitative edge in economics, finance, research, or analytics.
Around three-quarters of your degree is mathematics, making it far more technical than typical economics programmes.
It’s ideal preparation for careers in finance, consulting, research, policy, actuarial work, or data-driven roles.
The teaching combines mathematical precision with real economic relevance, giving you both theoretical insight and applied analytical skill.
Graduates are highly sought after because they can work confidently with models, equations, data, and economic reasoning — a powerful combination.

Progression & Future Opportunities

The BSc Mathematics with Economics develops a powerful combination of mathematical precision and economic insight. Students graduate with strong quantitative skills, analytical reasoning, and an understanding of economic behaviour — ideal for careers in finance, consulting, analytics, policy, and data-driven industries. This blend prepares graduates to interpret complex data, model economic systems, and solve high-level analytical problems across global sectors.

Typical career roles include:

Economist / Economic Analyst / Policy Analyst
Financial Analyst / Investment or Risk Analyst
Data Analyst / Business Analyst
Quantitative Analyst / Modelling Specialist

University support & employability features:

Careers & Employability Service: individual career planning, CV and application help, interview coaching, and employer networking tailored for quantitative and economics-based careers.
Economics and Maths support centres: workshops in quantitative modelling, econometrics, mathematical methods, and statistical computing to enhance career readiness.
Industry-engaged projects: opportunities to work on real economic or financial datasets and problem-solving tasks valued by employers in finance and consulting.
Optional placements or internships: hands-on experience in banking, finance, government, consulting, or economic research organisations.

Employment statistics & salary outcomes:

Graduates in maths-economics disciplines typically secure work or further study within 6–15 months of graduating.
Starting salaries are typically around £28,000–£35,000, depending on the industry, with rapid progression in finance, analytics, and consulting.
The degree prepares students for high-demand roles across economics, data science, finance, insurance, and policy sectors.

Industry relevance & long-term value:

Employers value graduates who can combine mathematical rigour with economic understanding, especially for analytical or modelling roles.
Skills gained include econometrics, statistical analysis, optimisation, economic modelling, and advanced problem-solving — all essential in modern data-led economies.
Graduates develop a flexible skill set suitable for both technical and policy-oriented pathways, giving long-term career versatility.

Graduation outcomes:
Students complete the programme with a strong mathematical foundation, applied economic reasoning, and quantitative modelling abilities, ready for analytical, financial, and research-oriented roles across global industries.

Further Academic Progression:

After completing this programme, students may pursue:

Master’s degrees in Economics, Applied Mathematics, Econometrics, Finance, Data Science, Public Policy, Business Analytics, or Quantitative Finance.
Research degrees (MSc/PhD) in Economics, Financial Mathematics, Econometrics, or Statistical Modelling for students aiming for academic or research-intensive careers.
Professional careers in finance, government, consulting, economic research, analytics, insurance, or policy organisations, supported by strong mathematical-economic training.