BSc(Econ) (Hons) Economics and Data Science Bachelor's degree at Royal Holloway, University of London

Learn how to think like an economist, by learning to write essays, how to present data, how to collect economic data and how to do economic research. Four sections each lasting half a term: economic institutions, economic history, applied economics and policy & experimental & behavioural economics. Students get an overview/introduction to the topic based on economic theory which is followed by some applications/data.

Introduction to Employability, library resources, team building, and CV making. Career services session on self-awareness and decision making and library services present their relevant resources. Economics department organises team building exercises.

Cover the basic mathematical and quantitative tools used by economists every day. First half devoted to linear algebra, specific functions of one and more variables used in economics, manipulating those functions and finding their minima and maxima. Rules of integration and differentiation, constrained and unconstrained optimisation techniques. Second half devoted to optimisation theory, concave functions, matrices for solving systems of linear equations used in microeconomic and macroeconomic p

First-year undergraduate module in how the economy works, suitable for students with or without A-Level economics or equivalent. Cover the basic theories of macroeconomics and microeconomics. Adopts the CORE approach (Curriculum Open-access Resources in Economics) with three pillars: Formulate a problem that society is facing now or has faced in the past; Build a theory to explain and solve the problem; Evaluate the usefulness of the theory by using data observations and more novel theories.

Describe the key principles of academic integrity, focusing on university assignments. Plagiarism, collusion and commissioning as activities that undermine academic integrity. Possible consequences of engaging in such activities. Activities with feedback to reflect and develop understanding of academic integrity principles.

About understanding the data encountered constantly in everyday life and the data that social science researchers create. Understanding where data comes from and how to harvest it, what useful information the data contains, and how to create new data to generate useful insights. Learn to analyse and display data using the R statistical software package. Develop an ethos of clear communication of numerical information supported by understanding of statistical concepts and proficiency with compute

Understand how to use data in order to draw relevant conclusions, and how to present those conclusions. Both how to abstractly think about data and data analysis, and how to concretely implement techniques using the Python programming language. General programming tools that become more focused on data science applications. Applications in the form of economic and financial investigations. Lab class with significant hands on experience and investigating problems under guidance. Final project: pr

Career services session on how to be ready to apply for an internship at the end of the second year. Prepare for a psychometric test and undertake a series of mock interviews to improve interview technique. Attend at least one Econ@Work talk to be aware of professional life and challenges.

Develop an understanding of macroeconomics and macroeconomic policy-making. Look at a variety of contemporary and historical macroeconomic events, and the differences between the short, medium and long run. Consider why some countries are rich and some are poor, why different economies grow at different rates, and what determines economic growth and prosperity. Examine the role of monetary and fiscal policy, its impact on the economy and its limitations. Analyse how taxation, budget deficits, an

Develop an understanding of the models of individual optimisation and their applications. Look at the key determinants of an individual's behaviour in a variety of circumstances and the behaviour of firms in different market environments, such as perfect competition, monopoly and oligopoly. Consider how changing circumstances and new information influences the actions of the economic agents concerned. Examine the properties of competitive markets and the need for government intervention to corre

Advance the quantitative skills of the students and familiarize them with the use of Python and R in empirical work in economics. Includes collection, manipulation and presentation of data on economic phenomena, as well as the use of regression-based econometric techniques to draw causal inference and perform prediction and forecasting.

Provide a solid understanding of the essentials of empirical research techniques (i.e. econometrics) used by applied economists. Cover core econometric topics needed by all wishing to undertake econometric analysis, with a particular focus on topics in both time series and cross section econometrics that can be used by students of industrial, business and finance.

Extend your knowledge of the essentials of empirical research techniques (i.e. econometrics) used by applied economists. Build on the topics covered in Econometrics 1.

Third-year course that deepens the elements covered previously in Employability 1 and 2. Career services provides a session on how to be ready for employment at the end of the year. Prepare for a psychometric test and undertake a series of mock interviews to improve interview technique. Attend at least one Econ@Work talk to be aware of professional life and challenges.

Develop an understanding of the theoretical properties of different econometric estimation and testing procedures under various modelling assumptions. Learn to formulate, estimate, test and interpret suitable models for the empirical study of economic phenomena. Consider how to apply regression techniques and evaluate the appropriateness of each econometric estimation method under different data limitations.

Develop an understanding of the mathematics of optimisation and of equilibrium models. Look at the linkage between markets and Pareto optimality and consider the social outcomes that can be implemented in game-theoretic equilibrium. Examine the basic types of auctions and when and why they implement identical outcomes.

Develop an understanding of the mathematical models used to study and analyse strategic interactions between agents. Look at the fundamental concepts in game theory as applied to economics in general and microeconomics in particular. Become familiar with basic equilibrium concepts such as Nash equilibrium and subgame perfect equilibrium, and be able to find equilibrium outcomes of simple games including the use of backward induction.

Introduce the student to what factors affect corporate financial decisions. Particular emphasis given to the concepts of Net Present Value and Risk. Learning outcomes include: Understand what the goals of a firm are; Understand how investments are valued (Internal rate of returns) in order to help with good financial planning; Understand the concepts of risk, agency costs and how they feed into financial decision making; Understand the process of price formation in financial markets; Understand

Develop an understanding of economic inequality. Look at the factors that determine wage differentials among workers from a theoretical and empirical point of view. Consider why similar workers are paid differently and examine how labour mobility can improve the allocation of workers to firms, enhance aggregate productivity, and reduce inequality.

Develop an understanding of the different approaches to national economic policy. Consider the economic advantages and disadvantages of globalisation and look at the effects of tax-cutting, deregulation, privatisation, mixed economy, efficiency and income distribution.

Develop an understanding of the use of experiments to test economic theories. Look at how individuals make decisions in markets, how individuals decide to spend money today or save it for future spending, the assumption of self-regarding preferences commonly made in standard economic models, and the ability to act rationally in a strategic environment. Consider the issues raised by experimental design and critically evaluate the advantages and disadvantages of experimental methods.

Familiarise students with the principal techniques used in Financial Econometrics. In depth discussion of the key technical concepts needed to understand the Financial Econometrics literature. Make a real effort to facilitate awareness in students of how these techniques can be used and applied on real data, and provides the necessary background to understand and critically assess empirical findings reported in the financial literature, as well as to carry out th