Economics BSc (Hons): XJTLU 2+2 programme

Econometrics is a branch of economics aimed at providing rigorous statistical techniques to test, empirically, the validity of economic hypotheses and economic models using data from the real world. Therefore, this module provides students with opportunities to develop and further strengthen important, but crucially transferable, advanced academic skills in economics, mathematics, statistics and computing, which can be used in a variety of different contexts such as applied economics and finance research. These skills are very useful and in high demand by graduate employers. A key feature of this module is the combination of rigorous theoretical foundation of OLS with hands-on applications using a relevant analytical software package (for example, EViews or STATA) and economic data.

The module provides training in the principal methodologies, theories and techniques of modern macroeconomic analysis. It is designed to introduce classic macroeconomic issues such as growth, inflation, unemployment, interest rates, exchange rates, technological progress, and budget deficits. The course will provide a unified framework to address these issues and to study the impact of different policies, such as monetary and fiscal policies, on the aggregate behaviour of individuals. These analytical tools will be used to understand the recent experience of the United States and other countries and to address how current policy initiatives affect their macroeconomic performance.

Introduction to the functions of individual decision-makers, both consumers and producers. Students will learn the major principles of microeconomics including consumer theory, producer theory, and general equilibrium. Perhaps more importantly, students will also learn how to apply these principles to a wide variety of real world situations in both personal and professional lives.

The scale of data available to analysts and researchers has increased rapidly over the past two decades. There are more careers available where analysing data is central, and there is generally an increasing demand within economics related careers for familiarity with programming languages such as Python and SQL, in order to perform more sophisticated tasks with data or to work with large data sets.
This module aims to help students develop these relatively challenging higher-level data and computing skills, particularly skills for managing data sets and producing useful visualisations with data. The module will draw on earlier quantitative/mathematical modules in the BSc Economics and on the concurrent module ECON212.

The module is for students who would like to perform data management tasks, create visualisations of data (graphs, charts, etc), and learn to analyse data, using the Python programming language. Unlike ECON212, ECON213, ECON311 and ECON312, this is not a module on econometric or statistical methodology – the focus is on developing a specific set of computing skills that will be useful for those who wish to pursue data-intensive careers or postgraduate research degrees after graduation from the BSc Economics.

Though the lectures and lab sessions centre around one particular textbook, participants on the module are expected use the vast amount of internet resources freely available for learning Python and SQL, and to spend time modifying code examples in order to gain competency with the facilities for data management, data visualisation, and data analysis. The module is assessed with a 2-week Python coursework project at the end of the module, where students will need to use the competency that they have gradually acquired over the course of the semester, and also with a timed written exam (Python and SQL).

The aims of this module are to build on ECON212 by extending the treatment of regression to the multiple regression model and to develop practical research skills which would be expected from a graduate in Economics either as a foundation for postgraduate study or for work as a professional economist recruited at graduate level.

The aim of this module is to further extend the study of macroeconomics at intermediate level. The module follows a modern approach to macroeconomics by building macroeconomic models from microeconomic principles.
On completion of this module, students should be able to: 1) examine macroeconomic data and analyse macroeconomic events; 2) critically evaluate macroeconomic models, 3) build and solve micro-founded macroeconomic models; 4) explain the implications of shocks and evaluate the effects of fiscal and monetary policies using macroeconomic models.

This module aims to introduce students to three topics in microeconomic theory: game theory, asymmetric information and welfare economics.

The aim of this module is to introduce students to the use of mathematical models in the study of Economics. This module builds on the material of the first year Mathematics and Economics modules and will deepen students’ knowledge of mathematical techniques involved in Microeconomics and game theory. At the end of this course, students will have: A1. More advanced mathematical skills A2. Know how to use models to solve some economic problems using matrix and optimization.

Since the financial crash there seems to have been a growing interest in economic ideas that challenge orthodox views. This unit provides an introduction to alternative ideas in economics. It provides the students with a knowledge of the debates between the different schools of thought, and also leads to a deeper understanding of mainstream views, and of the discipline of economics as a whole.

The scale of data available to analysts and researchers has increased rapidly over the past two decades. There are more careers available where analysing data is central, and there is generally an increasing demand within economics related careers for familiarity with programming languages such as Python and SQL, in order to perform more sophisticated tasks with data or to work with large data sets.
This module aims to help students develop these relatively challenging higher-level data and computing skills, particularly skills for managing data sets and producing useful visualisations with data. The module will draw on earlier quantitative/mathematical modules in the BSc Economics and on the concurrent module ECON212.

The module is for students who would like to perform data management tasks, create visualisations of data (graphs, charts, etc), and learn to analyse data, using the Python programming language. Unlike ECON212, ECON213, ECON311 and ECON312, this is not a module on econometric or statistical methodology – the focus is on developing a specific set of computing skills that will be useful for those who wish to pursue data-intensive careers or postgraduate research degrees after graduation from the BSc Economics.

Though the lectures and lab sessions centre around one particular textbook, participants on the module are expected use the vast amount of internet resources freely available for learning Python and SQL, and to spend time modifying code examples in order to gain competency with the facilities for data management, data visualisation, and data analysis. The module is assessed with a 2-week Python coursework project at the end of the module, where students will need to use the competency that they have gradually acquired over the course of the semester, and also with a timed written exam (Python and SQL).

An optional module addressing the interaction of Economic Theory with Psychology and investigating the way in which psychological findings can inform economics. This module will be useful in preparation for third year modules in Behavioural Finance and in the Economics of Arts and Culture.

The aim of this module is to introduce students to the use of mathematical models in the study of Economics. This module builds on the material of the first year Mathematics and Economics modules and will deepen students’ knowledge of mathematical techniques involved in Microeconomics and game theory. At the end of this course, students will have: A1. More advanced mathematical skills A2. Know how to use models to solve some economic problems using matrix and optimization.

This module seeks to provide students with an understanding of the role of securities markets in the global economy. This will be achieved through a presentation of their basic mechanisms and technical features, an explanation of the valuation of certain financial assets and an assessment of the operational and allocative efficiency of the markets. The module will be delivered via weekly small group face to face sessions and through weekly online lectures delivered asynchronously. Students will be directed to various media resources relevant to their day to day following and awareness of the activities of the global financial markets.

This is a third year advanced module in microeconomic theory focussed on the study of asymmetric information environments. In the seminar/tutorial students will be expected to present and discuss additional material as well as solve exercises.

This module is designed for Economics students who wish to advance further their understanding of modern macroeconomic analysis. The module considers a number of macroeconomics topics at a more advanced level and in greater depth. Why do countries grow? What are the sources of recessions and booms? Why is there unemployment and what determines its extent? What are the sources of inflation? How do government policies affect output, unemployment, inflation and growth?

What is globalisation? How does it constrain or enable economic policy making? This module follows on from the intermediate coverage of macroeconomics in year 2 and develops the interpretation of economic theory in a global economic context.
In this course we consider different exchange rate régimes and how they relate to the balance of payments and the scope for policy design.
The euro zone and the euro crisis present uswith a multilateral exchange rate peg between differing economies. We will study the nature and history of such arrangements before discussing the nature of its current European incarnation.
Finally, we will relate abstract models to empirical applications and ask where to obtain real world data to inform theory driven debates. As an alternative to the Advanced Macroeconomics module on the BSc Economics programmes, this module puts less emphasis on the in-depth development of formal model representations, although an appropriate amount of formal modelling is still used. Instead, it widens the focus of the discussion and emphasises the applied dimension.​

Behavioural finance attempts to explain several widely cited market phenomena (including e.g. excess volatility, overreaction, bubbles and crises) by drawing on concepts and principles from psychology and their applications in investors’ behaviour. The module provides a thorough introduction to this area, with theoretical analyses being enhanced through the use of quantitative financial data.

The creative sector of the economy rivals the financial services sector in size in the UK. This module first provides context for the sector in both the UK and globally. It then explores the application and development of economic theory in a sector which is often characterised by ‘non-standard’ markets (i.e. markets where neoclassical microeconomic assumptions may not hold) such as: Insubstitutability of labour for capital; superstar labour markets; intangible property of copyrights; fundamental measures of economic ‘value’; demand under utility models influenced by taste formation and differing levels of public sector influence. It is applied by examining a variety of creative industries, including fine arts, music, broadcasting, movies and others.

This module aims to give students a broad understanding of the key contemporary issues faced by political institutions and policymakers in the United Kingdom and in an international context. The module will analyse key challenges faced by democratic institutions around the world as well as by policymakers in the areas of education, labour and health. The module will also briefly cover the present and future challenges presented by Brexit and the policy reactions to the COVID-19 pandemic. Finally, the module will assess the contribution that Economics as a discipline can offer to tackle the challenges presented by environmental changes and congestion. The module will allow students to apply theoretical concepts to real life challenges

The aim of this module is to address the following and related questions: 1) What distinguishes banks from other firms? 2) What determines their behaviour when they set interest rates and extend loans? 3) What is their role in the economy? 4) Why is banking subject to a long list of specific regulations? 5) How is monetary policy transmitted through the banking system? 6) Why do banking crises occur and what are their consequences for the macroeconomy? The module covers both microeconomic and macroeconomic issues. It has points of connection to modules on industrial organization, finance and monetary policy.

The module will introduce students both to the theoretical arguments and the empirical evidence related to financial crises and defaults. The module will discuss in detail the main aspects of the recent financial crisis that shook the world economy including (a) the economic and financial environment in the years just before the crisis, (b) the causes of the crisis and (c) the action taken by policy-makers to deal with the crisis. The module will proceed by discussing the main aspects of the recent Eurozone debt crisis, as well as GREXIT and BREXIT issues. Noting the increasing role of social media both in becoming a popular open forum for analysing economic issues and reflecting public sentiment minute by minute, the module will draw on recent academic work to explain the impact of #Grexit tweets on the Eurozone bond market over and above the impact of economic fundamentals.

Some of the module content will be applied. In particular, using the econometric software EVIEWS and a number of macroeconomic and financial datasets, case studies will be developed to (a) test the adverse impact of excessive debt on economic growth for the G7 economies and (b) provide an empirical assessment of whether financial assets become mispriced prior, during and after financial crises. Students taking this module will need to have basic knowledge of macroeconomic and statistical theory as well as very basic knowledge of simple regression analysis. Prior knowledge of EVIEWS is not essential. A short introduction to EVIEWS will be offered as part of the module.

The objective of this module is to provide an introduction to Game Theory. This is the study of strategic interactions i.e. situations where outcomes depend not only on our own actions but also on how others react to our actions. This module complements those in core macro and microeconomics and offers more insight into strategic business decisions and competitive behaviour in general. In particular, we will use game theory to study market competition, auctions, bargaining, signalling, etc.

The aim of this module is to introduce final year Economics students to the key principles and tools of health economics. The module aims to show how the health care system differs from the economic textbook model of perfectly competitive markets. It will offer an overview of the issues of demand and supply for health care, supplier-induced demand, equity and inequality, health care financing and health insurance. It will emphasize the use of economic evaluation for assessing health care interventions as a way of making informed decisions in terms of costs and benefits. In addition, a range of practical examples will be provided of how health economics is applied in practice in both resource rich and resource poor countries.

Industrial organisation is concerned with the economic analysis of firms and industries, with a particular focus on how well consumers (society) are being served by particular industry structures and firm actions. The module incorporates debate between alternative schools of thought. The coursework is based on an industry case study selected by each student, which they research and which develops skills of independent research, writing, analysis and critical appraisal. In particular students are asked to evaluate which school of thought provides the most plausible interpretation of firm strategies and market outcomes.

This module aims to develop a good understanding of the main trade theories, their assumptions, implications, applications and limitations, and provide essential skills to students to engage in an analytical discussion of the impact of trade patterns,trade policies of government,foreign direct investment and World Trade Organisation on the economies of both developing and developed countries.

This module will provide an advanced, albeit non-technical, critical understanding for students with a variety of academic backgrounds of a number of current issues faced by both academics and practitioners in the area of finance for development. These will include, for example, trying to answer the question of whether foreign aid works, the impact of multinational firms upon the economy of host countries, the evolving roles of the IMF and World Bank and whether microcredit really provides a “silver bullet” solution to poverty. The module will also cover the main principles of Islamic Finance. This a very strongly research-led module. Finally, the module will have a developmental form of assessment in the form of a research-based proposal for a new textbook that will allow students to revisit the knowledge they have acquired in the module from a perspective of their choice like, for instance, de-colonisation of the curriculum, sustainability, environment, fintech, financial inclusion, gender.

The module will introduce a series of key advanced techniques in microeconometrics, building on second year work in econometrics. It covers typical topics such as binary choice models including logit and probit models, count data models which is widely used to deal with integer variables as well as panel data models. The module will develop applied research skills, including the ability to analyse data using appropriate econometric techniques and bespoke software. Successful students at the end of the module will be expected to be equipped for study at leading graduate schools of Economics and for work as professional economists or business analysts.

This module aims to offer students the opportunity to learn basic econometric theories for time series analysis. The module will build upon the materials of ECON212 Basic Econometrics but make important extensions in order to model serial dependence in time series data. This module will introduce the classic ARIMA type of linear time series modelling framework and the classic ARCH/GARCH type conditional heteroskedasticity modelling framework as well as ARDL type multivariate time series model and cointegrated systems. Upon successful completion of this module, students should be able to apply these classic models to univariate and/or multivariate time series data for the purposes of, for example, producing economic/financial forecasts  and/or investigating causal relationships between multiple economic/financial variables.

This module provides a broad introduction to essential topics in modern financial economics, which crucially includes decision-making under uncertainty, portfolio selection, pricing financial assets and state contingent claims, and forecasting asset returns and volatility from historical data. In addition to offering students necessary exposure to essential knowledge in the aforementioned topics, this module also aims to develop two essential analytical abilities, namely the ability to formulate real world decision problems into mathematically solvable optimization questions and the ability to solve formulated questions either analytically or numerically. Students will gain exposure to such knowledge and develop such analytical abilities from properly selected examples and problem sets to be discussed in lectures and tutorials.

This module critically explores the economics of the sports sector, in particular the market for professional team sport. Over the past number of years, the sports sector has grown in social and economic significance, however, in some instances, there are peculiar aspects that merit economic inquiries. For example, collusion and collaboration between firms are generally prohibited, however, professional clubs organised in leagues are able to engage in collusive behaviour. At the same time, sports markets have many characteristics that make it particularly relevant to test general economic theories.

The aim of this module is to apply economic theories and principles to enhance knowledge and understanding of the sports sector and its constituent markets, and to use sports markets to understand general economic theories. The module will critically explore a range of issues and in doing so will make use of econometric modelling. Therefore, students will be able to develop an informed view of how an analytical view of sports can be used to guide decision making.