The module aims to develop the skills and knowledge of industrial organisation necessary for a career as an academic economist and in all areas where advanced research skills in economics are required. Specifically, it aims to teach the students to understand, appreciate, and ultimately contribute to, frontier research. It is intended to be comparable to modules taught in the best research universities in the USA and elsewhere in Europe.
Principal Learning Outcomes
Have a good overview and a thorough understanding of topics in industrial organisation and Data Science methods. Develop a critical knowledge of recent research in some key areas of industrial organisation and Data Science Methods. Enable students to pursue their own research agenda in the field.
Illustrative topics might include:
Industrial Organisation: Introduction to Structural Models, Models of Demand, Supply and Firms’ Conduct, Market Structure.
Data Science: Model Selection, Supervised Learning, Unsupervised Learning, Case studies of papers in economics, statistics and natural language research that use data science methods.
- Pre or Co-requisites
- Satisfactory completion of MRes year 1
- Assessment Method
- Coursework (100%)
- Coursework Details
- 2 assessments (worth 50% each)
- Exam Timing