Concepts and Workflow
GeoSC separates design questions that are often blurred together.
| Stage | Question | Main artefact | Important limit |
|---|---|---|---|
| Power | Could the proposed design detect effects on the tested grid under the fitted simulation DGP? | power_analysis_results.csv | It does not forecast campaign lift or establish identification. |
| Donors | Which eligible geographies have useful pairwise pre-period similarity to each treated geography? | donor_eval_results.csv | Recommendations and selected_weight are screening outputs, not fitted SparseSC weights. |
| Inference | How did treated outcomes differ from the SparseSC counterfactual during the measurement period? | geolift_results.json | Causal interpretation remains conditional on design assumptions. |
In GeoSC, a control is a geography not assigned treatment in the input to a stage. A donor is a control geography eligible to contribute to a synthetic counterfactual. Operationally, analysts often use the words interchangeably, but eligibility should be determined before model fitting.
The pipeline executes power, donors, then infer. It does not use donor
recommendations to filter the later power or inference inputs. Power uses every
non-treatment unit in its input panel as a control. Inference uses the control
units present in its prepared panel. If a screening decision should constrain a
later stage, create a filtered canonical panel or config and record that hand-off.
Before running any stage, define:
- the outcome and its unit of measurement;
- the treated geography or geographies;
- the treatment launch, cooldown, and measurement window;
- donor eligibility and exclusions;
- the effect scale, alpha, target power, and reporting rule;
- plausible spillover, concurrent-media, and measurement-change mechanisms.
Reject or redesign the study if these decisions cannot be defended. GeoSC is a measurement engine, not a machine for laundering an infeasible design into a number.