This CPD teaches students how to apply quantitative methods to conduct causal impact analysis using data. In particular, students will learn how econometric methods can be used to answer questions related to human behaviour and strategic decision-making with the help of regression based econometric methods.

 

With the help of this course, participants will engage with advanced techniques to analyse data and to distinguish a causality link from a simple correlation. We will do it by looking both at the theoretical side and at the most recent application. Being able to identify causality links represents a crucial skill for a person interested in understanding the data that today's world produces.

 

On successful completion of this module students will be able to:

• Determine which methods can be used to analyse different datasets for addressing questions relevant to the social sciences.
• Critically assess findings of studies that apply these methods.
• Design their own randomised experiments.
• Conduct their own causal regression analysis using the statistical software package R.

 

What Topics will you Cover?

The CPD focuses on applied causal regression analysis providing an understanding of econometric methods for use with big data. In particular, the course covers regression-based evaluation methods to assess the casual relationships between different factors at play.

 

These include the use of panel data, difference-in-differences estimation, matching and regression discontinuity designs, randomised experiments, and natural or quasi-experiments.

 

The CPD has an applied focus, demonstrating the use of these methods with practical applications using the statistical software package R and referring to examples from recent studies that apply those methods to answer key questions in the social sciences.