Session 2 Causal Inference

2.1 Core content

  • What is a good causal question?

  • What are the stages of research design? Special focus on the stages of designing an RCT.

  • What do we mean when we say “cause”? (And why does it matter to be clear about the meaning of causal claims?)

  • A broad overview of how we might use observation (like interviews, surveys, administrative data, experiments, archival research, etc.) to learn about causal claims.

  • An introduction to the idea that randomization helps us learn about counterfactual causal claims in a particularly useful way.

  • Three key assumptions for causal inference: random assignment of subjects to treatment, non-interference, excludability.

2.3 Resources

EGAP Methods Guide 10 Things You Need to Know about Causal Inference

EGAP Methods Guide 10 Strategies for Figuring Out If X Caused Y

EGAP Methods Guide 10 Things You Need to Know about Mechanisms

“Causation and Explanation in Social Science” (Brady 2008)

2.4 Quizzes and Exercises

2.5 Examples

References

Brady, Henry E. 2008. “Causation and Explanation in Social Science.” In The Oxford Handbook of Political Science. https://www.oxfordhandbooks.com/view/10.1093/oxfordhb/9780199286546.001.0001/oxfordhb-9780199286546-e-10.