10 credits

This module aims to provide students with clear frameworks they can use to understand macroeconomic events. The skills developed will enable graduates to understand how policy makers and businesses can react to, cope with, and anticipate changes in the macroeconomic environment including business cycles, inflation, commodity price shocks, changes in interest rates, taxation, government spending and government debt.

The modules aims to provide you with the ability to:

• understand macroeconomic events in an integrated world;
• communicate the implications of changes in the macroeconomic environment for business managers;
• present macroeconomic analysis in clear and concise yet informative reports

You'll learn about:

• macroeconomic policies in an open economy
• the factors guiding the choice of a given exchange rate regime
• the economics of a monetary union
• the pros and cons of globalisation, and its interactions with economic development, inequality, and political economy
• the nature and impacts of financial crises
• the interactions between exchange rate crises, banking crises and sovereign debt crises
• the long-run determinants of economic growth in an open economy

10 credits

The main aim of this module is to introduce students to theoretical microeconomics. A further aim is to provide an understanding of how micreconomics knowledge can be applied to practical problems faced by businesses that compete in both competitive and regulated markets.

You'll meet some key concepts and principles of economics, focusing particularly on consumer theory and the theory of the firm. You’ll be shown how these concepts and theories are applied to the analysis of a range of contemporary real-world issues.

You'll be learn to:

• understand the economic way of thinking
• appreciate the relevance of economics to business
• understand the operation of markets and the interaction of supply and demand
• appreciate the relationship between revenue, costs and profits
• acquire an analytical understanding of profit maximisation
• understand the economic role of marketing and advertising
• develop the ability to describe market outcomes and how these change when the market environment changes
• understand alternative theories of the firm and different pricing strategies
• understand the impact that governments and demand/supply side policies have on business decisions

10 credits

The aim of this module is to provide you with the foundations of mathematics that are required to understand modern artificial intelligence techniques. The module will focus on three topics: probability, statistics and linear algebra.

On completion of the module you'll be able to:

• understand and apply probability theory as used in modern AI
• understand and apply statistical techniques as used in modern AI
• understand and use linear algebra techniques as used in modern AI

20 credits

This module primarily focuses on analysing and modelling macroeconomic and financial time series.

It's intended to provide students with a comprehensive introduction to time series and the application of basic time series econometrics in macroeconomics and finance. This is achieved through consideration of such topics as the introduction to univariate and multivariate time series modelling, local projections, vector autoregression, and factor models.

The module will provide the necessary basic knowledge and fundamental tools for modelling time series, which can be used to conduct individual structural policy as well as scenario analysis in macroeconomics and finance.

20 credits

You'll learn about the skills in data analysis that make up an essential part of the work of an applied economist. This will include carefully chosen applications of methods and techniques that permit insightful analysis of data, the specification and testing of hypotheses, and estimation techniques.

The module is taught via lectures and hands-on lab sessions, ensuring you gain experience in both undertaking the analysis of economic data and in interpreting results.

10 credits

This class provides students with a comprehensive and analytical overview of the energy finance system. This is done through consideration of such topics as:

• Corporate Finance
• Cost of Capital
• Energy Investment Appraisal
• Portfolio construction
• Energy Forecasting
• Energy Modelling

The class will provide the necessary foundational knowledge for studying other core classes in the course, and MSc EPECC students will get the opportunity to learn how the Finance function operates and how energy firms forecast and model energy prices.

20 credits

The abundance of time series data in economics and finance has sparked a growing interest in flexible data analytical techniques that efficiently handle data and identify meaningful patterns in time series. This module primarily focuses on statistical and machine learning tools that are increasingly used by practitioners, econometricians, data analysts and forecasters in central banks, government statistical agencies, policy institutions, or the private sector.

It's designed to provide you with an in-depth understanding and application of advanced time series econometrics by covering topics such as linear and non-linear time series regressions, textual inference, as well as popular machine and statistical learning techniques in macroeconomics and finance.

The module establishes a strong and closer link between students and the advanced and modern time series econometric tools used by data scientists and analysts for inference in macroeconomics and finance.

10 credits

You'll learn to make data-driven decisions relevant to government, business, economic consultancy, financial markets, and the third sector.

This module provides opportunities to develop practical skills, demystify core AI concepts, and apply them to economic contexts.

You'll work with accessible statistical and analytical software (such as Python) commonly used by practitioners in industry and government. The module also introduces selected generative AI tools and methods from modern machine, deep, and statistical learning, illustrating how these techniques support modern text analysis and economic research.

Moreover, it considers how AI can be applied responsibly in economic analysis and policymaking.

40 credits

Your summer project makes up 40 of the 180 credits required to receive your MSc award. While we expect that all learning throughout the degree will be helpful for the Summer Project, you can choose your topic from any area/issue in the field of economics, data science and AI.

You'll be supervised by an appropriate member of staff with expertise in the research area. This is your opportunity to develop a substantive piece of applied work on a topic that is of particular interest to you under the guidance of a supervisor.

In addition to providing a key opportunity to put into practice what you have learned during your MSc studies, this project will provide useful experience for your future careers. We're also able to supervise students who are sponsored by their employer and wish to work on a topic of interest to both them and their employer.

In this class you'll explore key economic issues at the heart of topical energy questions – building on the University’s outstanding reputation as a centre of excellence in energy technology and policy. The class covers the objectives of energy policy; private and social perspectives on energy supply and demand; the special case of regulation of energy markets; the use of economic models in energy analysis; the economics of oil and gas activity and links between energy use and the energy sector and an economy.

10 credits

This class, run by the Department of Economics, provides students with a comprehensive overview of natural resources, sustainable consumption and the United Nations sustainable development goals (SDGs) through consideration of such topics as:

• where natural resources are located
• how they are used and what are the key challenges facing consumption
• what policies are in place to protect natural resources globally
• how environmental change and degradation may impact natural resources
• how conflicts can occur over natural resources and the steps we can take to remediate this

20 credits

Economic appraisal and modelling lie at the heart of what most economists in business, consulting and government do on a day-to-day basis. You'll examine the key principles and techniques of economic appraisal and learn – through your own applications - how these are used in private and/or social analysis.

Techniques covered will include cost-benefit analysis, cost-effectiveness analysis and multi-criteria analysis. The economic modelling component will provide you with insights into how models designed to describe the operation of any economy can be used to help inform decision making. You’ll drawing on the practical modelling expertise gained within the Fraser of Allander Institute which has – for over forty years – developed an international reputation in the development and use of economic modelling for analysing policy-relevant issues.

This course will enable you to understand global trends and to study the key drivers of international economics, including how exchange rates move; what determines flows of international investment; and why some countries grow more quickly than others. With the global economy becoming ever more integrated, understanding of these issues is important for the applied Economist working within business, consulting and policy.

10 credits

This class builds on the knowledge acquired in Foundations of Business Economics to explore the role of government and public policy in the economy. You'll learn about why governments often intervene in the economy when markets do not operate as planned, and gain an understanding of the trade-offs faced when intervening. You'll also learn about how public utilities operate and why and how they are regulated.

10 credits

10 credits

Understanding what drives inequalities in economic outcomes is a key aspect of modern economic thinking. Many of the drivers of such inequalities are cross-cutting, covering a range of economic issues from changes in economic policy through to the overall macroeconomic environment and the changing nature of our modern labour market. This class is designed to:

1. raise the awareness of the different roles for economic analysis in the formulation of effective policies aimed at tackling inequality and reducing poverty, and
2. develop policy-relevant understanding of current issues inclusive growth enabling students to effectively contribute as an applied economist

A growing, and increasingly important, part of the work of many applied Economists includes the economic analysis of environmental issues. Additionally, many professionals working in the fields of energy, the natural environment, or business more generally will find that their careers require some working knowledge of economic approaches to environmental problems. The main objective of this class is to provide a thorough grounding in the economics of the environment, with a particular focus on environmental protection in an international policy context, such as climate change the loss of biological diversity.

10 credits

Climate change is one the pre-eminent global political and economic issue of the 21st century. This class, run by the Department of Economics, is intended to provide students with an overview of the basic model underlying the economics of climate change and the economic approach to climate change policy. It then goes on to describe the complications that need to be considered beyond this basic model in order to think about climate change policy in the real world.

This class provides you with an introduction to health economic policy, a key area for their potential future careers. The purpose of this course is to develop your ability to use economic concepts and theories to analyse existing issues in the health care market and to inform decision making and policy development. The class will provide you with an overview of policy issues from both an academic and practitioner perspective. The class will also focus both on technical skills that are needed to do research in the area of health economics, as well as on policy implications and discussions. Due to its focus on policy evaluation, the course will provide a supporting function for you to proceed to the Summer Project study.

10 credits

10 credits

This module will introduce the challenges of analysing big data with specific focus on the algorithms and techniques which are embodied in data analytics solutions.

At the end of the module, you'll understand:

• the fundamentals of Python for use in big data technologies
• how classical statistical techniques are applied in modern data analysis
• the limitations of various data analysis tools in a variety of contexts

This module focuses on implementing AI algorithms and building autonomous systems. This involves gaining an understanding of what Artificial Intelligence means in the context of autonomous systems, such as the key algorithms and techniques that enable rational decisions.

On completion of the module you'll be able to:

• program in Python, with the goal being to implement key AI algorithms and build AI systems
• define and understand the problem of Artificial Intelligence as it relates to autonomous systems
• apply search techniques to enable autonomous systems to choose actions that are appropriate to their goals
• apply key techniques to adversarial problems, such as Mini-Max and Monte-Carlo Tree search

After completing this module you'll be able to:

• understand the aims and fundamental principles of machine learning
• understand a range of the essential core algorithms and approaches to machine learning
• apply the algorithms covered on substantial data sets using Python and Scikit-learn and interpret the outcomes
• understand the applicability of the algorithms to different types of data and problems along with their strengths and limitations

20 credits

This module provides an overview of the application of AI techniques - including those which mimic natural evolutionary processes (genetic algorithms and genetic programming in particular) - to a range of financial applications such as forecasting, portfolio optimisation and algorithmic trading.

After completing this module, you'll be able to:

• understand the benefits and opportunities for evolutionary computing in the context of financial applications
• understand the principles of evolutionary computation, in particular genetic programming and genetic algorithms, as well as neural networks (particularly those configurations most suited to time series data)
• understand how the computational approaches covered in the class may be applied to financial problem-solving and understand their limitations
• develop and evaluate practical solutions to finance-based problems