Cost pressures and funding gap modelling 2025 – Technical Guidance

The LGA tends to update its analysis on future cost pressures and funding gaps facing local councils on an annual basis. This analysis is based on financial data reported by councils in the Revenue Outturn (RO) forms published by the Ministry for Housing, Communities and Local Government (MHCLG).

The model applies cost drivers, such as inflation and pay, and demand drivers, such as demographic change, to councils’ spending in a base year to estimate service cost pressures faced by councils in future years. Our cost pressures analysis relates solely to the funding needed to maintain services at their levels in the base year. It does not include funding needed to address existing underfunding or to improve or expand council services.

Growth in modelled future cost pressures is then compared to known or modelled future changes in councils’ income to assess the sufficiency of future funding growth relative to cost pressures. Where modelled cost pressures are growing more rapidly than income this creates a ‘funding gap.’

This note sets out the design of the model, the data sources used, and the assumptions made relating to the cost and demand drivers. Further details on the data and assumptions are available in Appendix 1.

To assess future cost pressures:

To estimate the funding gap:

Our cost pressure figures are a measure of pressures faced by councils when setting their budgets rather than a spending forecast. We do not include any assessment of councils’ ability to find efficiencies or the impact of other spending decisions that councils may make to manage the full range of pressures they face in the context of their funding envelope.

Councils have faced significant demand and cost pressures in recent years in service areas such as children’s social care, homelessness services, and home to school transport for children. In the absence of formal cost and demand forecasts for these services we model future pressures based on recent trend data. We recognise that these demand trends may change over the period covered by the model, particularly if there are Government interventions to manage demand and/or shape provider markets. However, at the current time we are not aware of any concrete plans to manage cost and demand in these service areas.

Expenditure data overview

Service areas

Each year councils submit financial data to MHCLG on spending and income through their RO forms. The cost pressures model only considers General Fund revenue spending on services (and waste and transport levies). Councils’ capital programmes and Housing Revenue Account spending are not within the scope of this analysis.

Using this financial data, the cost pressures model projects the path of council spending in these areas:

The following General Fund revenue service spending is excluded from the model:

 Calculating net spend

Our funding gap analysis is based on modelled pressures in net service spending. However, to produce our net spend figures we model the components of net spend separately:

By disaggregating net spend into its component parts in this way we can apply different cost drivers to different elements of spend and income, rather than assuming they will all move in line with each other. 

One-off adjustments

In addition to the application of cost and demand drivers to spend and income data we make specific adjustments to the RO data to reflect one-off changes to spending or income in our 2024/25 base year. These relate to:

As new annual RO data sets are published, we will remove these adjustments from the model as the real-life impacts of these changes will be implicit within the new outturn data. 

Debt costs

Given the significant information gaps – such as the maturity profile of councils’ borrowing, their investment plans or the precise nature of their minimum repayment provision policy – we do not attempt to model future debt costs or treasury management and/or investment income. 

The one exception is that we include an estimate of the treasury management cost to councils of funding their Dedicated Schools Grant (DSG) deficits from cash. Using cash in this way means that it is not available to councils to invest and therefore accrue interest. We estimate the loss to councils based on the income they would have earned if cash used to fund DSG deficits had instead been placed in the Debt Management Office deposit facility. 

Our estimate of the DSG deficit is taken from a joint LGA / County Councils Network report published in summer 2024. 

We do not include DSG deficits themselves in the model.

Cost and demand drivers

Cost and demand drivers are variables which directly affect service spend. We apply them to different components of total spend (employee and running costs) and income (sales, fees and charges and other income).

Both types of drivers can be grouped into general measures, such as population change and inflation, which apply to all or most service areas, and specific measures which only apply to specific service areas, for example the change in vehicle miles for road maintenance.

Where possible, the measures are based on published projected data such as the OBR inflation forecasts or ONS population projections. Where these formal projections are not available projected change is based on an average annual change over the previous five years. We adjust the data to remove the impact of the COVID-19 pandemic on trend data where necessary.

The projected change for all variables is based on public data.

General drivers

There are several measures which affect all or most services and are considered to drive the demand for and cost of delivering services. These are: pay, population, inflation, and energy costs. 

Pay for staff directly employed by councils

The change in pay for directly employed staff is based on the total annual pay bill impact of pay settlements agreed for 2024/25. We also include an estimate of pay drift (the cost of annual increments payable to staff at certain stages in their local government employment). We use the OBR’s average earnings growth forecasts for 2025/26 onwards (excluding pay drift). These figures are applied to the employee costs line in each service area.

Employers’ pension and national insurance costs are included in the employee costs line in the RO data. Consequently, these costs are uprated in line with the annual pay uplift and any demographic drivers applied in a particular service area. 

Pay in commissioned adult social care services

We assume that 70 per cent of the cost of running expenses for adult social care commissioned services is related to provider staff costs and that these costs are heavily driven by changes in the National Living Wage (NLW). This is based on evidence from the UK Home Care Association’s fair price of care model which suggests around 70 per cent of the cost of an hour of home care is related directly to care worker salary and on-costs. 

We create a cost driver that is weighted 70 per cent in line with change in the NLW and 30 per cent with CPI inflation. For 2023/24 through to 2025/26 we use the actual increase in the NLW. In the absence of NLW forecasts in 2026/27 and beyond we use the OBR’s average earnings forecast.

Population and household numbers

Population projections apply to the cost and income lines in each service. Data for population projections is taken from the Office for National Statistics (ONS). The relevant population age is used for each service. The change in population affects most service spending and income lines.

In the absence of up-to-date sub-national population projections, we create our own council level forecasts based on the national projections. We start by taking the ONS 2023 Mid-Year Estimates by year of age for each local authority. We then apply a growth rate to 2023 and beyond based on forecast annual growth by year of age in the 2024 National Population Projection. 

We adjust ONS forecasts of household numbers in a similar manner. Comparing household projections to the ONS’ population projections shows that the number of households grows at 67 per cent of the rate of the growth of population. We therefore multiply the forecast population growth figure in any given year by 0.67 and apply this rate of growth to the 2023 forecast number of households.

We apply different demographic drivers in several service areas, notably adult social care and looked after children. These are set out in the following sections.

Inflation

Consumer Price Index (CPI) inflation is applied to running costs for all services (except waste management where the Retail Price Index (RPI) was considered more appropriate because many contracts are linked to this measure rather than the lower CPI).

In the previous iteration of the model, we use an average of the Bank of England (February 2024) and OBR (March 2024) inflation forecasts. We used an average of the two owing to material differences in the two forecasts for 2025/26. At the current time there is no longer a material difference between the two forecasts, so we exclusively apply the OBR (October 2024) inflation forecasts

Energy prices

Considering the recent fluctuations in energy prices, it was appropriate to account for this impact separately from inflation. This has been modelled separately based on various sources to give an estimate of total energy expenditure in the years covered by the model.

Firstly, a total energy expenditure figure for 2022/23 is taken from the subjective analysis return (SAR). The SAR is also used to establish the proportion of running expenses attributable to energy costs, which is 0.1 per cent for Adult Social Care, 0.3 per cent for Children’s Social Care, and 2.9 per cent for all other services, excluding balancing items. Therefore, these proportions of all running expenses are affected by the change in energy assumption, with the remainder affected by CPI inflation.

A briefing from the Department for Energy Security and Net Zero (DESNZ) is used to establish the split of energy expenditure between gas and electricity. The 2022/23 expenditure figure from the SAR is then split into estimates of gas and electric costs and divided by DESNZ’s average unit costs to estimate overall energy usage. This usage is then multiplied by forecast cost, which is taken from the utilities index of the disaggregated CPI in the supplementary economy tables of the OBR’s October 2024 economic and fiscal outlook.

Service specific drivers

This section provides information on all other measures used in each service area (excluding those described above). A full list of drivers applied to each sub-services is shown in Appendix 1. The geographical level at which they are applied – national, regional, or local (case level) – is summarised in Appendix 2.

Adult social care

For the majority of the adult social care sub-service lines we model service demand based on the most recent published modelling on future user numbers from, the Care Policy Evaluation Centre (CPEC – formerly the Personal Social Services Research Unit (PSSRU)). We apply the forecasts by age to the relevant sub-service lines in the RO data. Given that the forecasts were published in 2020 and drew on now out of date population data we uprate the population base in line with the 2024 National Population Projection. 

We use different demographic demand drivers in some adult social care sub-services:

Children’s services

We use a range of different demographic drivers to model future demand pressures in children’s social care:

In general, for each service area in the model, in addition to a relevant demand (demographic) we apply Green Book pay as the cost driver to employee costs, and CPI as the cost driver to running costs. However, residential placements for looked after children unit costs have been increasing faster than our standard pay and inflation cost drivers. To adjust for this difference, we add a unit cost adjustment derived by CPEC (published under the former name of the PSSRU) to our pay and CPI drivers based on the difference between annual average growth in unit costs from 2015/16 to 2020/21 and our existing drivers. 

The RO includes a category for ‘other’ spending on looked after children. This includes a range of different areas of spend, none of which are broken down individually within the RO data. Given the range of activities in this spending line and the absence of granular data it is exceedingly hard to model future cost and demand pressures in this spending line. However, the DfE’s S251 data contains related categories on looked after children spending over a longer period than the RO. The DfE data shows that over the last five years net spend in “other spending on looked after children” has moved in line with spend in the aggregate of the other “looked after children” categories– residential placements, foster care and UASC that are looked after. On this basis we assume that net spend pressures in this ‘other’ line in our model will increase with our aggregate modelled net spend for these three other categories for looked after children spending.

Highways

We use the following trend-based metrics to model future demand pressures in highways spending:

Housing

We use the following demographic drivers to model future demand pressures in relation to housing and homelessness spend:

Waste management services

Other environmental services

The change in the number of households is applied to the RO line “Climate change costs” and is based on our adjusted measure of household growth as described above. The raw data comes from ONS Household projections.

Planning and development services

The change in the number of households is applied to the RO lines “Building control”, “Development control”, “Conservation and listed buildings planning policy”, “Other planning policy”, “Environmental initiatives”, “Economic development”, “Economic research”, and “Community development” and is based on our adjusted measure of household growth as described above. The raw data comes from ONS Household projections.

Public health

We use the following demographic drivers to model future demand pressures in relation to public health spend:

Other education

While we exclude schools spending from the model, we include costs related to the RO subcategory “Other Education” as much of this spend falls on councils’ general funds. We split this sub-category in two by separating spend on providing services for children with special educational needs and disabilities (SEND), which is primarily the cost of home to school transport for SEND children, from other activities in this spending line. We use the Department for Education’s (DfE) DfE S251 data, which includes a similar category for ‘other education’, to estimate the share of RO spend on services for children with SEND that falls in this spending line.

We apply different demographic drivers to these two new sub-categories. For the element focused on delivering SEND services we model future demand based on the annual average change in the number of education, health and care plans (EHCPs) over the five years up to and including 2022/23. For the non-SEND element of this spend, we model future demand in line with projected demographic growth in 0–17-year-olds.

Levies

We include annual levies paid to waste and transport authorities. We model future levy costs in line with total population growth.

We model income of different types in different elements of the model. We include sales, fees and charges and other income in our calculation of net cost pressures. Separately we include Core Spending Power and Public Health Grant in our calculation of the funding gap. Specifically:

Sales, fees and charges and other income

The model includes an estimate of future change in sales, fees and charges and other income. 

Sales, fees, and charges income

To estimate future change in sales, fees, and charges income we apply CPI inflation and demographic drivers relevant to the service area in question. However, in contrast to employee and running costs, where we use forecast measure of CPI inflation, we use the average of forecast CPI and a backward-looking measure of CPI inflation (over the 12 months to September before the financial year in question). This reflects the fact that different councils take different approaches when setting their sales, fees, and charges rates. Some set their rates in the autumn ahead of the relevant budget year using CPI over the previous 12 months, while others use a forecast of CPI for the coming year. We use both forecast and backward-looking measures available at this point. We do not update previous years to reflect actual inflation as the rates themselves for that particular year cannot be changed retrospectively.

We make two service-specific adjustments to sales, fees, and charges income:

Other income

Other income includes:

In our view these income streams do not necessarily move in line with inflationary, pay or demographic pressures. However, in many cases we have no real basis to model cost or demand drivers for these income streams. Consequently, for most service areas we assume that ‘other income’ will move in line with our modelled figure for total spend in the relevant service area. This approach effectively removes other income from our calculations and has no impact on change in net spend pressures. 

There are a small number of cases where we take a different approach:

Netting off ‘surpluses’

Where councils generate sales, fees and charges income, this income cannot be used to support service provision elsewhere in the authority. In some service areas income can exceed the cost-of-service provision, generating a net surplus. This surplus must remain, and be spent, in that service area. 

In our model we generate total service cost pressures by summing the net pressures across the services. If net surpluses were included in these calculations this would effectively transfer the service-specific surplus into a council’s overall spending. To prevent this from happening in our calculations, this is capped at zero in any year in which our model generates a net surplus.

In principle this can occur across several service areas. However, in general these surpluses are not material. The one exception is parking – both on street and off-street. Consequently, our capping adjustment is only made in relation to surpluses generated from parking income, which cap at zero if this exceeds the total cost pressure in the highways and transport service area as a whole. 

Calculation of estimated core income for future years

Core Spending Power and Public Health Grant

To calculate the funding gap, we compare change in modelled net cost pressures since 2024/25 against change in forecast Core Spending Power and Public Health Grant. In the absence of published data on these income sources for 2026/27 and beyond we make the following assumptions about different components of these funding streams:

The outcome of future Local Government Finance Settlements will have implications for the funding gap. For example, decisions over future council tax referendum thresholds and revenue grant funding for councils could be different to the assumptions in our model. Different decisions will act to increase or reduce the gap.

Extended Producer Responsibility for Packaging (pEPR)

Government has announced that £1.1 billion will be available to local authorities, of which £975 million is for councils, in England in 2025/26 through this scheme. This income is designed to cover the existing costs local authorities incur for managing household packaging waste, provide additional funding for new legal duties, and support investment in the waste and recycling industry.

While this income is not within CSP we include it in our income modelling in 2025/26 as it is a potentially significant new funding stream. While the scheme is designed to improve waste services, it is also designed to cover existing costs of managing household packaging waste. Given that these existing services are already covered by councils’ existing resources this creates the possibility that councils can release resources from their existing waste budgets to support pressures in other service areas.

While we include pEPR funding in our income figure for 2025/26, we make an adjustment to reflect the fact that councils will spend a proportion of the funding on improving services and meeting new legal duties. As this funding relates to service improvement and new responsibilities it falls outside the parameters of our model as it is not available to support councils in meeting pressures on existing services. The scale of this adjustment is based on an LGA survey of council chief financial officers in January 2025.

While we include an adjusted sum of pEPR income in 2025/26, we do not include any pEPR income in 2026/27 or beyond as the future of this funding stream is uncertain. It is not clear whether there will be an adjustment to the existing funding formula to account for the fact that councils are already paid for services that are now funded through pEPR.