Find out more about studying MSc Economics with Data Science at University of Essex? We've gathered all the key details, entry requirements, modules, fees, and more. Take the next step by booking an open day to explore it for yourself.
MSc - Master of Science
University of Essex
Full Time
Oct 2026
1 Year
The MSc Economics with Data Science is for you. The Department of Economics and the School of Computer Science and Electronic Engineering have created a joint course that allows you to develop the economic and computational tools to not just isolate problems but also develop sophisticated evidence-based answers.You'll have the opportunity to learn the essentials of economics, so you can build a grounding to analyse economic problems, you will then build on this knowledge with programming skills. We combine these two approaches in a series of applications that allow you to access and process big data using advanced econometrics and also apply computational techniques to questions of financial economics and macroeconomics.Our MSc Economics with Data Science allows you to build a theoretical understanding of how to approach economic problems, together with computational skills, with the opportunity of applying these research skills in applications by studying topics such as:Computational Models for Microeconomics and FinanceComputational Macroeconomics and Policy DesignMicroeconometricsApplications of Data Analysis
What interests you? Undertake a research project of your choosing, studying a specific economic issue or set of problems in depth, with supervision from our world-leading academic staff. Gain experience of original and independent work, making use of and building on skills that you have acquired during your Masters.
What are the concepts and methods of modern microeconomics? And how can you apply economic reasoning to this? Understand the main principles and theories of modern microeconomics, looking at topics like contract theory, equilibrium concepts in game theory, and market signalling. Learn to apply economic reasoning to these arguments.
Wish to conduct your own research using econometric methods? Understand econometric methods and learn to apply them to a wide variety of situations. Examine methods of linear regression and hypothesis testing. Study time series concepts of unit roots and co-integration. Explore ideas around model selection and panel data models.
This postgraduate module equips you with the key tools in modern data science, with a focus on machine learning (ML) and its application to Economics and Finance. The main goal of this module is to enable you to understand how machine learning tools can complement the tools of traditional econometrics and how to apply these techniques to real-world economics and finance problems. By the end of this module you will have: 1. Developed a comprehensive understanding of key concepts in modern machine learning (ML): classification, prediction, supervised and unsupervised learning 2. Demonstrated a critical understanding of the advantages and disadvantages of ML as compared to traditional econometric approaches 3. Applied ML to real-world economics and finance problems, with examples based on: i. Prediction ii. Causal Inference and Policy Evaluation
