The module is primarily designed to give you an improved understanding of how to carry out theoretical research in economics. It is also intended to develop skills in critical appraisal of other people’s research and in clear and concise oral and written presentation of research, and to help students as a group to learn about one another’s research topics, thus facilitating future cooperation.
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 optimization, the course aims to introduce students to the formal “axiom-theorem-proof" style of mathematics used in economics.
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.
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.
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, students will know how to use different econometric estimators and understand how to analyse the properties of estimator by Monte Carlo simulation. They will have a base of econometric and programming knowledge which will help them to understand and implement advanced econometric techniques they observe in current research in applied and theoretical econometrics.
This module provides postgraduate research students with an introduction to advanced empirical designs for identifying causal estimates and evaluating policy interventions. Students will get acquainted with the basic theory behind and application of Randomised Control Trials, Two-Stage Least Squares, Difference-in-Difference and Regression Discontinuity Design.
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.