EC9C3: Topics in Industrial Organisation and Data Science

Introduction

This module presents an overview of selected topics in industrial organisation and data science methods. It aims to teach students to understand, appreciate, and, ultimately, contribute to frontier research.

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 strategic overview and a detailed understanding of developments in industrial organisation and data science methods. The teaching and learning methods that enable students to achieve this learning outcome are: Lectures and background reading. The summative assessment methods that measure the achievement of this learning outcome are: 2 x Submitted assignments.

Develop a critical knowledge of recent research in some key developments in industrial organisation and data science methods. The teaching and learning methods that enable students to achieve this learning outcome are: Lectures and background reading. The summative assessment methods that measure the achievement of this learning outcome are: 2 x Submitted assignments.

Autonomously pursue their own original research agenda in the forefront of the field of industrial organisation and data science methods. The teaching and learning methods that enable students to achieve this learning outcome are: Lectures and background reading. The summative assessment methods that measure the achievement of this learning outcome are: 2 x Submitted assignments.

Syllabus

Context

Optional Module

L1PL - Year 2

Pre or Co-requisites

Satisfactory completion of MRes year 1

Assessment

Assessment Method

Coursework (100%)

Coursework Details

Assessment 1 (50%) , Assessment 2 (50%)

Exam Timing

N/A

Reading Lists