Economics MSc

  • Programme duration: Full-time: 12 months  
  • Programme start: Autumn 2021
  • Entry requirements: A 2:1 Honours degree (or overseas equivalent) in Economics or a related discipline with a quantitative focus. Students with a 2:1 degree from a quantitative Science discipline are also encouraged to apply.
Economics msc

Module details

Due to the impact of COVID-19 we're changing how the course is delivered

The 12-month programme consists of three compulsory modules and five optional modules, followed by a dissertation carried out over the summer period upon completion of Semester 2.

Students must select one optional module in Semester 1 followed by either or both of Applied Macroeconometrics (ECON920) and Applied Microeconometrics (ECON826) in Semester 2 and then two or three additional modules.

Students are required to complete 180 credits to achieve a full MSc.

Compulsory modules

Econometric and Statistical Methods (ECON814)
LevelM
Credit level15
SemesterFirst Semester
Exam:Coursework weighting100:0
Aims

The aim of this module is to give the student an understanding of basic econometric and statistical methods suitable for financial and economic data series. Extensive use will be made of econometrics software including EViews in tutorials to supplement the theory with applications and to provide hands-on experience. The aims are that the student will:

Understand the multiple regression model including the matrix and statistical background;

Be apply to apply statistical tests estimate regression models;

Understand the assumptions and limitations;

Understand the maximum likelihood principle and be able to perform the relevant specification tests;

Understand the principle underlying instrumental variables and GMM estimation;

Be confident in the use of econometric software such as EViews for a range of methods and applications.

Learning Outcomes

(LO1) Formulate and estimate regression models.

(LO2) Perform diagnostics on regression models.

(LO3) Perform all the calculations required via EVIEWS.

(LO4) Perform maximum likelihood estimation and be aware of the properties of the estimators.

(LO5) Perform GMM estimation.

(S1) Problem solving skills

(S2) Numeracy

(S3) IT skills

(S4) Communication skills

Macroeconomic Analysis (ECON905)
LevelM
Credit level15
SemesterFirst Semester
Exam:Coursework weighting100:0
Aims

This module aims to provide students with a well-rounded overview of modern macroeconomics. Topics covered are facts about growth, the Solow growth model (theory and empirics), the Neoclassical Growth model (growth with dynamic optimisation), and endogenous technical change. The second half of the course will focus on Real Business Cycle models and the New Keynesian framework. We will evaluate the successes and failures of the basic models in matching data.

Learning Outcomes

(LO1) Demonstrate in-depth knowledge and understanding of macroeconomic theory.

(LO2) Apply core advanced economic theory and quantitative methods to applied topics.

(LO3) Show theory and model based understanding of advanced analytical methods.

(S1) Problem solving skills

(S2) Numeracy

(S3) Commercial awareness

(S4) Communication skills

(S5) IT skills

(S6) International awareness

(S7) Lifelong learning skills

(S8) Ethical awareness

Microeconomic Analysis (ECON915)
LevelM
Credit level15
SemesterFirst Semester
Exam:Coursework weighting80:20
Aims

This module aims to provide an opportunity to understand and appreciate the fundamental aspects of decision making in an uncertain environment, allowing for the possible synchronic or diachronic incidence of risk. Individual risk linked behaviour will be linked to symmetric and asymmetric imperfect information scenarios. In this context individual or circumscribed group behaviour may be related to an aggregate and institutional context.

Learning Outcomes

(LO1) An appreciation of the basic aspects of consumer and producer decision making both under certainty and uncertainty;

(LO2) An understanding of the underlying assumptions needed to justify the existence of a general competitive equilibrium;

(LO3) An understanding of the relationship between a general equilibrium and welfare considerations.

(S1) Problem solving skills

(S2) Numeracy

(S3) Organisational skills

(S4) Communication skills

(S5) Lifelong learning skills

Dissertation (ECON912)
LevelM
Credit level60
SemesterWhole Session
Exam:Coursework weighting0:100
Aims

The aim of this module is to enable a student to undertake an independent piece of work that demonstrates a consolidated level of thorough understanding achieved by undertaking theoretical as well as empirical analysis on a particular aspect of interest. The work could be a fundamental ground for the research that is anticipated to be undertaken in due course to be continued by the student.

Learning Outcomes

(LO1) Development of skill of presenting theoretical and empirical analysis on a particular aspect of interest in the discipline. Further development of the work for further research may be considered.

(S1) Research skills

(S2) Written communication skills

(S3) Organisational skills

Optional modules

Portfolio Theory (ACFI923)
LevelM
Credit level15
SemesterFirst Semester
Exam:Coursework weighting80:20
Aims

To understand and appreciate the basic notions underlying the management and selection of efficient investments for portfolio construction. Special emphasis is given to notions of efficiency and the discussion of selection criteria.

Learning Outcomes

(LO1) Appreciate the pivotal elements of decision making under certainty and uncertainty, risk and risk management, portfolio choice, management and performance evaluation.

(LO2) Develop a systematic understanding, knowledge and critical awareness of the nature, concepts and construction of portfolios, having regard for the type of investor.

(LO3) Apply knowledge, understanding and techniques underlying portfolio management strategies including risk management strategies in uncertain contexts.

(LO4) Develop a conceptual and practical understanding of the understanding of performance evaluation of portfolios at the forefront of current practice.

(S1) Adaptability

(S2) Numeracy

(S3) Commercial awareness

(S4) Teamwork

(S5) Organisation skills

(S6) Communication skills

(S7) International awareness

(S8) Lifelong learning

(S9) Ethical awareness

(S10) Leadership

International Economics (ECON704)
LevelM
Credit level15
SemesterFirst Semester
Exam:Coursework weighting0:100
Aims

The module aims to introduce key facts and theories in international economics and discuss contemporaneous issues in the global economy. The topics covered in this module will introduce students to the up-to-date knowledge of the global economic environment, equip students with necessary tools analyse recent political and economic events and prepare them to work in economic consulting, data analytics, civil service, and industry. The focus on theory underpinning policy and then empirically testing the impact of policy exposes students to the way policy-oriented research is conducted.

Learning Outcomes

(LO1) Students will be able to describe the key economic aspects of the global economic and business environment in recent years.

(LO2) Students will be able to identify major economic issues experienced by nations and institutions and use appropriate economic analysis to examine such issues.

(LO3) Students will be able to read and discuss empirical analyses conducted by other researchers.

(LO4) Students will be able to develop the ability to conduct individual study by drawing on multiple data sources.

(LO5) Students will be able to program empirical analyses in STATA.

(LO6) Students will be able to analyse and quantify the economic impacts of recent regional and global issues (e.g., Brexit and COVID).

(S1) Problem solving
The module teaches students to define a research hypothesis and empirically test it through discussions in lectures and seminars and written assignments.

(S2) Verbal and written communication
The module teaches students to discuss research on international trade policies through discussions in lectures, seminars and written assignments. Especially, through the module students will develop the skills of essay-based argument. This is a specialist academic skill that requires students to demonstrate the synthesis of considerable research and analysis and develop a strong, coherent argument. These skills though specialist in the form of an essay can be adapted to wider forms of communication.

(S3) Numeracy
This module will develop two types of analytical skills, data analysis and the use of economic models. To develop these two skills, weekly tutorial questions are designed to introduce real world data analysis problems. By attempting these tutorial questions and participating in seminars, students can learn how to source data from various databases, produce good summary statistics and analyse real world economic and policy issues using economic models.

(S4) IT skills
Seminars will teach students how to program empirical analyses in STATA.

(S5) International awareness
This module introduces the key facts and concepts of global economic and business environment, covering issues such as the establishment of the world’s economic order after the second world war, the functions of key international institutions, the pros and cons of economic integration, and the impacts of Brexit and the US-China trade war.

(S6) Lifelong learning
A key objective of this module is to teach students on how to conduct their own research. Students will gradually learn how to approach and solve new problems by practicing the tutorial questions and completing their assessments.

Game Theory With Applications (ECON813)
LevelM
Credit level15
SemesterFirst Semester
Exam:Coursework weighting80:20
Aims

The objective of the module is to provide a graduate level and modern 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 those of others. In particular, students will be taught how to apply game theory to a range of economic, business, everyday and social contexts.

Learning Outcomes

(LO1) Conduct advanced strategic analysis by modelling a game and possible reasoning concepts and inferring behavioural predictions.

(LO2) Distinguish between types of games.

(LO3) Apply games in a range of economic, business and social contexts.

(S1) Analytical and problem solving skills.
Students will be taught analytical skills to solve problems using game theory.

(S2) Numeracy.
Students will be taught to mathematically analyse and solve problems.

(S3) Communication skills.
Students will be taught to describe strategic interactions in a precise manner.

Applied Macroeconometrics (ECON920)
LevelM
Credit level15
SemesterSecond Semester
Exam:Coursework weighting70:30
Aims

The aim of this module is to build on the first semester econometrics module and give the student an understanding of more advanced econometric and statistical methods suitable for analysing financial and macroeconomic data series. Extensive use will be made of the econometrics package EViews in lab-based tutorials to supplement the theory with applications and to provide hands-on experience. The aims are that the students will:

Understand the main tools of modern econometric techniques for analysing financial and macroeconomic data.

Understand the assumptions and limitations.

Be confident in the use of an econometric computer programme (EViews) for a range of methods and applications.

Learning Outcomes

(LO1) Formulate and estimate time series models;

(LO2) Use time series models for testing economic theories and making economic forecasts.

(LO3) Perform all the calculations required via EVIEWS.

(LO4) Understand and be able to interpret time series models estimated from EVIEWS.

(S1) Problem solving

(S2) Numeracy

(S3) Communication skills

(S4) Teamwork

Applied Microeconometrics (ECON826)
LevelM
Credit level15
SemesterSecond Semester
Exam:Coursework weighting75:25
Aims

This module seeks to teach students to become a critical consumer of the empirical work in existing literature. The goal is for students to learn to discuss, critique, and analyse applied economics research. The material in this course will provide students with the techniques needed to conduct their own original research in microeconomics.

Learning Outcomes

(LO1) Students will be able to discuss the methods economists use to obtain causal identification.

(LO2) Students will be able to code basic statistical analyses in STATA.

(LO3) Students will be able to critique various research methods.

(LO4) Students will be able to assess the validity and plausibility of assumptions needed for results to be causal.

(S1) Problem solving.
Lectures and coursework provide problem sets designed to teach problem solving.

(S2) IT skills.
Coursework requires students to learn to code in STATA.

(S3) Numeracy.
Lectures, coursework, and the exam teach students the mathematics of causal identification.

(S4) International awareness.
Lectures and coursework teach students to analyse research and assess the efficacy of policies.

Machine Learning and Big Data Econometrics (ECON701)
LevelM
Credit level15
SemesterSecond Semester
Exam:Coursework weighting50:50
Aims

The module aims to prepare students for careers where a good understanding of Machine Learning methods and Python programming is necessary or advantageous. Examples include: research careers in applied economics or finance, careers in data science, or careers in data analysis generally.

Learning Outcomes

(LO1) Students will be able to define, explain and motivate a number of Machine Learning methods.

(LO2) Students will be able to use libraries in Python for Machine Learning and scientific research.

(LO3) Students will be able to produce Jupyter Notebook documents, mixing formatted text in Markdown with Python code.

(LO4) Students will gain a good general ability with the Python programming language.

(S1) Flexibility and adaptability
Students will need to learn in various directions for this module, using a variety of different resources for learning the underlying Machine Learning methodology and the programming, and this will require a degree of adaptability.

(S2) Problem solving
The module involves programming exercises.

(S3) Numeracy
The module involves a substantial amount of data analysis.

(S4) Commercial awareness
Commercial uses of the Machine Learning methodologies will be described in class. The Python libraries used in the module are widely used in the commercial world.

Money and Banking (ECON916)
LevelM
Credit level15
SemesterSecond Semester
Exam:Coursework weighting80:20
Aims

To develop a microeconomic and a macroeconomic perspective of banking;

To acquire an understanding of the specific nature of a bank as a firm, the role of banks in an economy, and of the regulatory environment in which banks operate;

To develop an understanding of economic foundation of the banking sector and analyse its importance for the macro-economy.

Learning Outcomes

(LO1) Understand the role and characteristics of banks in an economy;   

(LO2) Understand the competitive environment banks operate in;

(LO3) Explain the main risks, eg credit, liquidity, interest rate, that banks face;

(LO4) Explain how banks measure and manage these risks;

(LO5) Describe the main systemic risks and explain why and how banks are regulated;

(LO6) Explain the macroeconomic role of the banking system.

(S1) Problem solving skills

(S2) Adaptability

(S3) Numeracy

(S4) Commercial awareness

(S5) Teamwork

(S6) Organisational skills

(S7) Communication Skills

(S8) IT Skills

(S9) International awareness

(S10) Lifelong learning skills

(S11) Ethical awareness

Security Analysis, Valuation and Investment (ACFI825)
LevelM
Credit level15
SemesterSecond Semester
Exam:Coursework weighting0:100
Aims

Understand the essential characteristics of different asset classes;

Understand the theories underpinning the techniques of security analysis and valuation;

Applying security analysis technique in constructed examples and real world data;

Critically appraise investment strategy in the context of theory and practice.

Learning Outcomes

(LO1) A systematic understanding, knowledge and critical awareness of the nature of equity securities and current professional practice related to equity markets.

(LO2) The application and critical appraisal of fundamental analysis to the valuation of equity securities, including residuals analysis in complex scenarios.

(LO3) A conceptual understanding of the principles underlying the equity markets and equity security valuation, including hybrids at the forefront of current practice.

(LO4) A systematic understanding, knowledge and critical appraisal of professional practice related to fixed income securities.

(LO5) The application of knowledge and understanding of applied techniques and methods to analyse yields, risks and valuation for fixed income securities in an uncertain context.

(LO6) A conceptual understanding of the principles underlying the yields, risks and valuation of fixed income securities and the application of current valuation techniques.

(S1) Problem solving. Students will be required to develop problem solving skills in lectures and practical lab sessions.

(S2) Numeracy. Numeracy skills will be developed through the application of techniques taught in lectures to various real and artificial data sets.

(S3) Commercial awareness. Within interactive lecture environment and supported self learning.

(S4) Communication skills. Communication skills will be developed through the careful interpretation and guided discussion of results in practical sessions.

Current Topics in Economics (ECON827)
LevelM
Credit level15
SemesterSecond Semester
Exam:Coursework weighting0:100
Aims

This module aims to provide students with knowledge of cutting-edge topics in economics, and develop their understanding of the contribution of economic science to tackling both new and existing challenges faced by consumers, firms, governments, and regulators in practice. The module aims to prepare students for the workplace, whether industrial or academic, by developing life-long learning skills and embodying an approach to learning that is rooted in fundamental economic research. The module also provides the opportunity to acquire, develop and apply a range of advanced research skills, independent critical thinking, and presentation and report writing skills.

Learning Outcomes

(LO1) Be able to actively engage with economic research.

(LO2) Be able to apply the theories and methodologies studied to current economic issues.

(LO3) Be able to deliver technical presentations, explain complex economic models and concepts.

(LO4) Be able to critically evaluate research outputs.

(LO5) Be an independent thinker, capable of original ideas and research questions.

(S1) Adaptability.
Practiced in lectures, roundtable discussions and self-directed learning.

(S2) Problem solving.
Taught explicitly in lectures, practiced in presentations and in written coursework.

(S3) Numeracy.
Taught explicitly in lectures, practiced in presentations and in written coursework.

(S4) Communication.
Practiced in presentations and in written coursework.

(S5) Lifelong learning.
Taught implicitly in lectures, practiced in roundtable discussions and self-directed learning.

Labour Economics (ECON702)
LevelM
Credit level15
SemesterSecond Semester
Exam:Coursework weighting50:50
Aims

The module aims to prepare students for careers where a good understanding of microeconometric analysis is key. The topics covered in this module will prepare students to work in economic consulting, data analytics, civil service, and industry. The focus on theory underpinning policy and then empirically testing the impact of policy exposes students to the way policy-oriented research is conducted. This systematic approach reinforces the skills they have learned in other modules but brings them all together in a way that teaches students to be well rounded economists.

Learning Outcomes

(LO1) Students will be able to model supply of labour by individuals and demand for labour by firms in competitive and uncompetitive environments.

(LO2) Students will be able to program empirical analyses in STATA.

(LO3) Students will be able to read and discuss empirical analyses conducted by other researchers.

(LO4) Students will be able to quantify the effects of labour market policies.

(LO5) Students will be able to discuss the distributional impact of policies on different groups.

(S1) Problem solving
The module teaches students to define a research hypothesis and empirically test it through discussions in lectures and seminars and written assignments.

(S2) Verbal and written communication
The module teaches student to discuss research on labour market policies through discussions in lecture and seminars and written assignments.

(S3) Numeracy
The module teaches students empirical skills to analyse public policy through lectures and seminars.

(S4) IT skills
Seminars will teach students how to program empirical analyses in STATA.

(S5) International awareness
Examples covered in this class will draw on labour markets from a number of countries.

Public Economics (ECON703)
LevelM
Credit level15
SemesterSecond Semester
Exam:Coursework weighting50:50
Aims

The aim of the module is to prepare students for a variety of careers, ranging from any type of government and civil service, to economic consulting, data analytics, and other data-related work in the private sector. The goal of the module is to synthetize theoretical and microeconometric skills, many of which students have learned in other modules, to produce well-rounded economists who are knowledgeable about the current state-of-the-art methods used in conducting policy-oriented research. A particular emphasis in the module will be placed on the role of government policies in addressing environmental pollution and climate change, which are arguably among the most important issues faced by the current and future generations.

Learning Outcomes

(LO1) Students will be able to model the responses of individuals and firms to various local and national government policies.

(LO2) Students will be able to read, comprehend, and evaluate empirical analyses conducted by other researchers.

(LO3) Students will be able to program empirical analyses in STATA statistical software.

(LO4) Students will be able to quantify the effects of various national and local government policies.

(LO5) Students will be able to discuss the distributional impact of policies on difference groups.

(S1) Problem solving
The module will teach students how to state a research hypothesis, and how to empirically test it. This will be accomplished via group discussions in lectures and seminars, as well as via written assignments.

(S2) Numeracy
The module will teach students various empirical skills to analyse government public policy via lectures and seminars.

(S3) IT skills
Seminars will teach students programming of empirical analyses using STATA statistical software.

(S4) Verbal and written communication
The module teaches students to evaluate, analyse, and discuss research on various national and local government policies through group discussions in lectures and seminar, as well as via written assignments.

(S5) International awareness
Examples discussed in class will cover government policies from a number of countries.