Using Economic Data for Causal Inference

Over the last 30 years, economics has undergone a credibility revolution. This moment has sought to move economics from theory to empirics. This work is grounded on the need for economic theory to be evidence based and consequently economists have sought to use causal inference fuelled by experiments and quasi-experimental methods to analyse policies. This module will arm you with the toolkit of the modern economist.  

This module is in two halves. In the first, you’ll be given a grounding on linear regression with a strong emphasis on practical interpretation and use of ordinary least squares, the workhorse model of this module. In the second half of the module we focus on causality, and how this may be inferred using observational data.   

The methods covered include:  

• directed acyclic graphs;  
• instrumental variables;  
• regression discontinuity design; 
• differences-in-differences.   

The module also develops your skills by teaching statistical software. Many economics graduates and employers report that skills in data analysis are among the most important and regularly used of those needed by economists working in industry, or government.