University of Warwick

What you'll study

This programme blends advanced economics, econometrics and data-science methods. You will study core subjects such as microeconomic and macroeconomic analysis, advanced econometrics and causal inference alongside practical modules in machine learning, statistical computing and data engineering. Typical taught material covers:

• Advanced econometrics and time-series analysis – estimation, inference and forecasting for economic data
• Causal inference and programme evaluation – identification strategies, instrumental variables, difference-in-differences and synthetic controls
• Machine learning for economists – supervised and unsupervised methods, regularisation, ensemble models and model validation
• Computational methods and programming – Python or R for data manipulation, reproducible workflows, databases and cloud-based tools
• Applied topics – panel data, high-dimensional models, natural language processing, network analysis and big-data architectures
• Research design and ethics – data governance, privacy and interpretation of empirical results

The programme typically combines lectures, computer-based practical classes and seminars. Assessment is by a mix of coursework, project work and unseen or take-home exams. All students complete a substantial independent dissertation or applied data-science project, working on an empirical question or bespoke data challenge under academic supervision.

Entry requirements

Applicants are expected to have a strong quantitative undergraduate degree such as economics, mathematics, statistics, computer science, engineering or a related discipline, normally with an upper-second-class (2:1) honours or its international equivalent. Successful candidates demonstrate proficiency in calculus, linear algebra, probability and statistics, and prior programming experience in languages such as Python, R, MATLAB or similar is strongly preferred.

Where applicants have less directly relevant backgrounds, preparation through prior postgraduate study or professional experience involving quantitative analysis may be considered. All applicants whose first language is not English must satisfy the university's English language requirements.

Career prospects

Graduates from this programme move into analytical and technical roles across the public and private sectors. Typical career paths include:

• Data scientist, machine-learning engineer or quantitative analyst in finance, fintech and technology firms
• Economic or policy analyst in central banks, government departments and international organisations
• Consultant specialising in data-driven strategy, econometrics and impact evaluation
• Researcher in academic or industry research groups focusing on applied economics, causal inference or computational social science

The programme’s combination of economic reasoning and practical data skills is valued by employers that need staff who can frame economic problems, apply appropriate empirical methods and communicate evidence clearly to decision-makers.

Why study at University of Warwick

The University of Warwick is home to a large, research-active economics department and strong interdisciplinary data-science activity, providing access to leading academics working on applied econometrics, macroeconomics and computational methods. Students benefit from hands-on practical teaching, dedicated computer labs and access to large-scale computing resources and software used in industry.

Warwick’s campus offers a focused learning environment with an active careers service that connects students to internships and employers across finance, consulting, government and technology. The programme’s links with research centres and external partners give students opportunities for applied projects and networking that support transition into analytical careers or further research.