Introduction to Big Data for Economics
Module Code: ECP77413
- ECTS Credit: 5
- Mandatory/Optional: Mandatory
- Semester/Term Taught: Michaelmas Term
- Module Personnel Lecturer: Professor Nicola Fontanta
Aims of Module
This module introduces the field of Big Data, examining its main features, such as real-time availability, scale, types of variables and structure. It focuses on showing how different types of Big Data, including administrative datasets, high-frequency information, web-scraped datasets, can be used to answer questions in economics. This module will introduce students to the main topics that have been arising around the concept of “Big Data”. With increasing computing and storage capacity, new opportunities and challenges arise for researchers. The goal of this module is to provide an overview of different papers, datasets and techniques, with an emphasis on practical implementation.
Learning Outcomes
On completion of the module, students will be able to:- Explain the challenges and opportunities arising from the “Big Data”.
- Distinguish which type of data to collect based on the typology of empirical questions to tackle and how to efficiently collect them.
- Apply the latest technique to analyse and summarize large amount of data.
- Apply Big Data methodologies such as Data Mining and High-Dimensional Data Analysis in different research settings.
Module Content
Topics covered in this module will include:
- Understanding Big Data in Economic Contexts: Key characteristics of "big data"
- Challenges and opportunities specific to "big data" such as: Privacy & confidentiality; Data management practices; Scalable approach
- Data Collection: Strategies & Challenges
- Data Analysis: Techniques & Tools for Big Data
- Applying Big Data: Case Studies in Economics
Recommended Reading List
- Lecture, lecture slides, list of compulsory and optional readings
Assessment
- Continuous assessment (50%)
- Project (50%)
Module Website
Blackboard