PolicyEngine / PolicyEngine/snap-qc-sim
Natural-experiment validation: mid-sample option adopters
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 0
- Forks
- 0
- Avg merge
- 18m
- Merged PRs (30d)
- 5
Description
For states that adopted SMD/SSED/heat-and-eat/BBCE mid-sample, predict post-adoption category error rates from the pre-adoption model + engine-recomputed intermediates; score against realized rates. The test that separates a validated counterfactual from a scenario dial. docs/v2-error-model.md §3.
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Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with docs/v2-error-model.md §3 to understand the intended distinction between validated counterfactuals and scenario dials. Then locate the model and engine-recomputed intermediate entry points for mid-sample SMD, SSED, heat-and-eat, and BBCE adopters. Done means predicted post-adoption category error rates are scored against realized rates for those states.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, testing
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100