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EC9C3: Topics in Industrial Organisation and Data Science

  • Camilla Roncoroni

    Module Leader
  • Mirko Draca

    Module Lecturer
12 CATS - Department of Economics
Autumn Module

Principal Aims

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.

Syllabus

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.

Context

Optional Module
L1PJ - Year 2
Pre or Co-requisites
Satisfactory completion of MRes year 1

Assessment

Assessment Method
Coursework (100%)
Coursework Details
2 assessments (worth 50% each)
Exam Timing
N/A