Module description
This module provides a hands-on introduction to quantitative, statistical approaches to causal inference in the social sciences. It combines classroom instruction with workshop-based seminars where students learn to use the statistical software Stata to implement various approaches. The module is aimed at students who have studied an introductory statistics or econometrics course. It begins from a critical discussion of randomised experiments and basic regression as tools for causal inference. It then moves on to more advanced methods for observational data including panel regression models, instrumental variables, regression discontinuity designs, propensity score and Mahalanobis matching.
Please note module information is indicative and may change from year to year.
Staff information
Sunil Mitra Kumar
Teaching pattern
10 weeks of 2 - hour lectures and workshops
Module assessment - more information
1 x 3,000 word essay plus data analysis appendices (100%)