PolicyEngine / PolicyEngine/policyengine-uk
Update 2026-27 Universal Credit Regulation 36 amounts
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- Dominant language
- Python
- Stars
- 50
- Forks
- 33
- Avg merge
- 20h 58m
- Merged PRs (30d)
- 14
Description
The new UK EFRS RuleSpec comparator in TheAxiomFoundation/axiom-encode#457 shows PolicyEngine UK 4.11.0 / policyengine-uk 2.88.20 is using forecast-indexed 2026 Universal Credit Regulation 36 amounts rather than the published 2026-27 table amounts encoded in rulespec-uk.
Observed on the full local Enhanced FRS 2023-24 dataset for policy year 2026:
- UC standard allowance PE monthly values are about 335.30 / 423.26 / 526.30 / 664.39, but RuleSpec Regulation 36 has 338.58 / 424.90 / 528.34 / 666.97.
- UC child element PE monthly values are about 350.53 and 302.77, but RuleSpec has 351.88 and 303.94.
- UC disabled child additions PE monthly values are about 164.16 and 512.73, but RuleSpec has 164.79 and 514.71.
- UC LCWRA/carer/childcare component values show the same pattern for 2026-27 published rates versus forecast/uprated PE values.
This is analogous to the Child Benefit and Pension Credit 2026-27 rate issues found by the same harness: #1739 and #1740.
Repro command from the axiom-encode PR branch:
uv run --with 'policyengine[uk]==4.11.0' axiom-encode uk-efrs-compare \
--root /Users/maxghenis/TheAxiomFoundation \
--sample-size 0 \
--dataset /Users/maxghenis/PolicyEngine/policyengine-uk-data/policyengine_uk_data/storage/enhanced_frs_2023_24.h5 \
--fail-on-mismatch
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 the uk-efrs-compare comparator and run the supplied uv command against the Enhanced FRS dataset to reproduce the 2026 mismatches. Trace how Universal Credit Regulation 36 amounts are sourced for 2026-27, then verify that standard allowances, child elements, disabled-child additions, LCWRA, carer, and childcare values match the published table rather than forecasts.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100