0. Causal Questions and Designs
Define the counterfactual target before selecting data, controls or estimators
0. Causal Questions and Designs
This module turns a policy topic into an estimand and an assignment argument. Its governing rule is simple: no estimator repairs an undefined treatment or an implausible counterfactual.
Learning outcomes
After this module, you should be able to:
- separate offer, receipt, behaviour and outcome;
- write ATE, ATT and ITT in potential-outcome notation;
- explain why randomisation identifies a mean effect in expectation;
- diagnose non-compliance, attrition, interference and treatment versions;
- use a causal diagram to distinguish confounders, mediators and colliders.
Chapter route
- Causal Questions and Estimands — define the quantity before the method.
- Potential Outcomes and Experiments — observe one world and construct the other.
- Causal Diagrams and Controls — decide what to adjust for and what not to adjust for.
Prepare, work, follow up
- Prepare (45 min): choose one intervention and write its unit, treatment, comparator, outcome and horizon.
- Workshop (120 min): convert three vague claims into estimands; randomise the Pathways offer; audit attrition and spillovers.
- Follow up (60 min): submit a directed graph and a control table with a one-sentence justification for every variable.
Postgraduate extension: state consistency, positivity and no-interference assumptions separately, then show how one treatment version or spillover breaks each target.