As a postgraduate researcher in Economics, you will be expected to attend a number of compulsory modules in your first year of the PhD programme, as well as have the option to attend elective modules.

This module provides training in research analysis and presentation skills for postgraduate students, with particular emphasis on identifying research questions, assessing research methods and results, judging the value added of published research and summarizing the key points of contributions to different fields.


Contact: Simone Valente

This course provides students with an introduction to select topics in mathematics that are likely to be used in other PhD level economic courses as well as in their research papers. Using select topics from discrete math, real analysis, topology, linear algebra and static optimisation, the course aims to introduce students to the formal “axiom-theorem-proof" style of mathematics used in economics.


Contact: Dr Farasat Bokhari

This is an advanced module in microeconomic theory. The first part of the course will cover fundamentals of game theory, from normal form games and games of complete information to dynamic games and games of incomplete information. The second part of the course will focus on applications to a variety of topics. This module involves more abstract and conceptual reasoning as well as more direct working with proofs.


Contacts: Dr Mark Le Quement and Dr Amrish Patel

This module is about the economy as a whole. The focus is consequently on the overall performance of the economy rather than on the functioning of particular parts of the economy. The issues relate to short term phenomena like business cycles and fluctuations as well as long term phenomena like growth. In addition the interaction between real markets, like the labour market and markets for different goods, and financial markets, like the markets for money and assets, is studied.

The module aims at improving your understanding of macroeconomic issues including how these issues are modelled and studied. In addition your skills in developing your own economic models as well as critically discussing research contributions will be developed.


Contact: Dr Simone Valente

This module provides postgraduate research students with an introduction to advanced methods in econometrics which they may encounter in their own research. By the end of the module, you will know how to use different econometric estimators and understand how to analyse the properties of estimator by Monte Carlo simulation. You will have a base of econometric and programming knowledge which will help you to understand and implement advanced econometric techniques they observe in current research in applied and theoretical econometrics.


Contact: Simone Valente

This module is intended for advanced graduate students with prior training in probability, statistics, matrix algebra, and linear regression. The focus of the module is on some advanced topics in variables selections models, non-linear econometrics, generalized method of moments, non-parametric and semi-parametric estimation, and panel data analysis. A key purpose of this class is to teach specific techniques, algorithms, and tools to ensure that students write robust, correct, and tested code.


Contact: Dr Simone Valente

The module is divided into two parts.  In the first part, various methods are introduced for the time-series modelling of asset prices, with particular attention paid to models of varying volatility.  In the second part, various methods for valuing options will be considered.  The second part follows naturally from the first, in the sense that the options considered in part 2 are assumed to be written on underlying assets of the type analysed in part 1.


Contact: Dr Peter Moffatt