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Pension Credit spending rises to 2030-31 while DWP forecasts a fall

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Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
25/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
python
Área
data

Línea de trabajo

Rerun the aggregate-impact Pension Credit spending and caseload paths for 2025-26 to 2030-31 on both the Enhanced FRS file enhanced_frs_2024_25.h5 (uk-data 1.58.1) and Microcosm build microcosm-uk-2024-25-national-20261025T091414Z-a6299504 (policyengine.py 6.11.1, pe-uk 2.151.0). Record commands and hashes, then test the three candidates—State Pension age rise, cohort private pension income, take-up—by age and caseload. Done means both paths are reported, each candidate’s share is quantified, and any remaining gap is documented or split into fix issues/PRs.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

Raised by @vahid-ahmadi in his review of #2092 (comment, 27 October). #2092 does not change this gap: its aggregate impact shows no household change against main. The gap exists on main.

The gap

Model figures are #2092's aggregate-impact head levels on the Enhanced FRS (enhanced_frs_2024_25.h5, uk-data 1.58.1). DWP figures are from the Spring Forecast 2026 benefit expenditure and caseload tables (Pension Credit tab, nominal, GB).

2025-26 2026-27 2027-28 2028-29 2029-30 2030-31
Model spending (UK) £6.66bn £7.04bn £7.32bn £7.46bn £7.60bn £7.77bn
DWP spending (GB) £6.14bn £6.06bn £5.91bn £5.78bn £5.83bn £5.82bn
DWP caseload 1,382k 1,312k 1,253k 1,188k 1,142k 1,133k
  • The model is 8% above DWP in 2025-26 and 33% above in 2030-31.
  • Over those years DWP's spending falls 5% and its caseload falls 18%. The model's spending rises 17%.
  • The model covers the UK and DWP covers Great Britain. Northern Ireland explains only a small part of the level gap, and none of the change in the gap.

Where to look

#2092 makes the uprating rules match the law, so the divergence must come from the caseload side. These are candidates; none has been tested:

  1. The State Pension age rise from 66 to 67 between 2026 and 2028.
  2. Newer cohorts' private pension income.
  3. Take-up (compare #1813 for pension-age Housing Benefit).

Before diagnosing

Measure the path again on the Budget dataset, Microcosm build microcosm-uk-2024-25-national-20261025T091414Z-a6299504 (certified by policyengine.py 6.11.1 with pe-uk 2.151.0). The figures above are from the Enhanced FRS, and the gap may differ on Microcosm. Report spending and caseload for 2025-26 to 2030-31 on both datasets.

Done when

  • The spending and caseload paths are measured on Microcosm and the Enhanced FRS, with commands and dataset hashes.
  • Each candidate above is tested (for example, caseload by single year of age across the State Pension age rise) and its part of the gap is reported.
  • Each cause found has its own fix PR or issue. If a gap remains, the issue records how big it is and why.

Pension-age Housing Benefit was not compared: DWP has it at £7.1bn in 2025-26, but the aggregate report gives only total Housing Benefit (£8.55bn).

🤖 Generated with Claude Code

Lenguaje dominante
Python
Estrellas
53
Forks
34
Merge medio
4 d 54 min
PR fusionados (30 d)
381

Preparar el entorno

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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