Consultation outcome

Homelessness Prevention Grant technical note: proposed changes to the funding formula, 2023/24 onwards

Updated 23 December 2022

This was published under the 2019 to 2022 Johnson Conservative government

Applies to England

This document provides a technical description of the two options proposed in the 2022 Homelessness Prevention Grant consultation for updates to the funding formula, which would apply for 2023/24 onwards.

Both proposed options consider the allocations in 2 elements. The first element considers the allocation of £200m using a similar method to the Flexible Homelessness Support Grant formula. The second element considers the allocation of £110m using a similar method to the new formula first introduced in 2021/22 for the uplift in funding following a review of the Homelessness Reduction Act new burdens (referred to as the Homelessness Reduction Act uplift formula).

To note: This technical note outlines the proposed formula options based on the 2021/22 overall HPG amount of £310m. This does not mean that the overall amount of the grant will be £310m in 2023-24 or any future years. Decisions on overall funding for those years will be taken in due course. Allocations are very likely to change prior to confirmation.

In addition, we are proposing introducing transitional arrangements to minimise the impact of changes in allocations following updates to the formula. Please see the full consultation document for a comprehensive overview of the proposals.

Option 1

1. £200m

Relative homelessness pressures would be calculated by adding the number of acceptances + prevention and relief cases achieved by securing a private rented sector tenancy, with the following adjustments:

• accounting for private sector rental costs in different areas^{[footnote 1]}
• ensuring a minimum allocation level of £40,000
• ensuring that no authority receives an annual allocation less than 90% of their 3-year average historic spend share on temporary accommodation costs^{[footnote 2]}

2. £110m

The first 80% of the funding (worth £88m) would be allocated using a relative estimate of pressures using the following elements:

• A: The number of housing benefit claimants. This is the sum of private and social rented sector housing benefit claimants and households on universal credit with a housing entitlement in the private and social rented sector. This information can be found on DWP stat Xplore.
• B: Lower quartile monthly private rented sector rents for 2-bedroom properties^{[footnote 3]}
• C: Area cost adjustment, as used in allocating COVID-19 related funding to lower-tier authorities^{[footnote 4]}

Calculated using the following formula:

Pressure = A * (B + C * 8 hours * £15 per hour)

The allocation for each local authority would be derived as the proportion of the total pressure across all local authorities.

The remaining 20% of the funding (worth £22m) would be allocated based on the share of total single adult households owed a prevention or a relief duty^{[footnote 5]}.

An additional area-cost adjustment (ACA)^{[footnote 6]} would be applied to the entire £110m (HRA uplift formula).

Missing data

Where H-CLIC data is not available, local authority-level estimates would be calculated by apportioning published regional figures. Using the total figures for London and the Rest of England, we would calculate the amount of data within a given dataset that is attributable to local authorities with missing data, by subtracting the sum of data provided by local authorities from the total figure.

To distribute the remaining data to local authorities with missing data, we would distribute the data to local authorities with missing data using their percentage share of a 3-year average of historic TA spend.

If historic TA spend is not available for a given local authority, we would calculate their share using a population-weighted ACA.

The data would then be distributed using either of these shares and adjusted using a missing data multiplier of 0.75 (ensuring local authorities cannot gain by not providing data). For example, if there were 4000 units of missing data to be allocated and a local authority had a share of 10%, they would be allocated 300 units (= 4000 * 0.1 * 0.75).

Option 2

1. £200m

Number of acceptances + prevention and relief cases achieved by securing a private rented sector tenancy, with the following adjustments:

• accounting for private sector rental costs in different areas^{[footnote 7]}
• ensuring a minimum allocation level of £40,000
• ensuring that no authority receives less than 75% of their relative Area Cost Adjustment-weighted population share^{[footnote 8]}

2. £110m

The first 80% of the funding (worth £88m) would be allocated using a relative estimate of pressures using the following elements:

• A: The number of housing benefit claimants. This is the sum of private and social rented sector housing benefit claimants and households on universal credit with a housing entitlement in the private and social rented sector. This information can be found on DWP stat Xplore.
• B: Lower quartile monthly private rented sector rents for 2-bedroom properties^{[footnote 9]}
• C: Area cost adjustment, as used in allocating COVID-19 related funding to lower-tier authorities^{[footnote 10]}

Calculated using the following formula:

Pressure = A * (B + C * 8 hours * £15 per hour)

The allocation for each local authority would be derived as the proportion of the total pressure across all local authorities.

The remaining 20% of the funding (worth £22m) would be allocated based on the share of total single adult households owed a prevention or a relief duty^{[footnote 11]}.

An additional area-cost adjustment (ACA)^{[footnote 12]} would be applied to the entire £110m (HRA uplift formula).

Missing data

Where H-CLIC data is not available, local authority-level estimates would be calculated by apportioning published regional figures. Using the total figures for London and the Rest of England, we would calculate the amount of data within a given dataset that is attributable to local authorities with missing data, by subtracting the sum of data provided by local authorities from the total figure.

To distribute the remaining data to local authorities with missing data, we would use their percentage share of population weighted area cost adjustment (ACA).

The data is then distributed using these shares and is adjusted using a multiplier of 0.75 (this ensures local authorities cannot gain by not providing data). For example, if there were 4000 units of missing data to be allocated and a local authority had a share of 10%, they would be allocated 300 units (= 4000 * 0.1 * 0.75).

1. Lower quartile monthly private rented sector rents for 2-bedroom properties: Table 2.4. ↩

2. DLUHC local authority revenue expenditure and financing data – revenue outturn housing services RO4. ↩

3. Private rental market summary statistics in England, table 2.4. ↩

4. More detail: Technical note on allocation of tranche 4 of COVID-19 local authority funding, Annex B (PDF, 307KB). Data is available at: Coronavirus (COVID-19): emergency funding for local government in 2020 to 2021 and additional support in 2021 to 2022.  ↩

5. Live tables on homelessness. ↩

6. Lower Tier Local Authority Area Cost Adjustment, as used in the COVID-19 Relative Needs Formula (PDF, 307KB). ↩

7. Lower quartile monthly private rented sector rents for 2-bedroom properties, table 2.4. ↩

8. DLUHC Area Cost Adjustment (ACA) data, and ONS estimates of the population for the UK, England and Wales, Scotland and Northern Ireland – MYE4; Population Estimates; Summary for the UK, mid-2003 to mid-2020. ↩

9. Private rental market summary statistics in England, table 2.4. ↩

10. More detail: Technical note on allocation of tranche 4 of COVID-19 local authority funding, Annex B (PDF, 307KB). Data is available at: Coronavirus (COVID-19): emergency funding for local government in 2020 to 2021 and additional support in 2021 to 2022.  ↩

11. Live tables on homelessness. ↩

12. Lower Tier Local Authority Area Cost Adjustment, as used in the COVID-19 Relative Needs Formula (PDF, 307KB). ↩