Cost pressures and funding gap modelling 2026 – Technical guidance

1.1 The LGA updates 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 yearly by the Ministry for Housing, Communities and Local Government (MHCLG).

1.2 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. The 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.

1.3 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.’

1.4 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.

2.1 To assess future cost pressures:

• we take outturn council spend by service in the most recent published RO data. 
• we apply cost and demand drivers to the spend data to forecast future spending pressures in each sub-service. Cost drivers include metrics such as forecast inflation and pay, while demand drivers include factors such as change in population or household numbers. 
• some of our cost and demand drivers are formal projections made by external bodies such as the Office for Budgetary Responsibility (OBR) and the Office for National Statistics (ONS). Where we do not have formal forecasts, we use the trend in the relevant metric over previous years. We adjust the data to remove the impact of COVID-19 pandemic on trend data where necessary. 
• our model produces net spend cost pressures. We calculate these by modelling change in total spend (employee and running costs), and then netting off income from modelled sales, fees and charges and other income. 
• the model is based on analysis at the individual council level. This means that where possible we apply local cost drivers to individual councils. We model income at the case level as well.
• the model only includes councils – London borough councils (including the City of London), metropolitan borough councils, shire county councils, shire district councils and unitary authorities. It does not include the Greater London Authority, combined authorities, standalone fire authorities, police and crime commissioners, waste authorities or national park authorities.

2.2 To estimate the funding gap:

• we select a base year for the calculation – 2025/26 in this instance. Given that RO data is only available for 2024/25, our 2025/26 base year is a modelled figure and is based on the application of our cost and demand pressures to the 2024/25 RO data.
• we compare change in cost pressures in future years relative to the base year, against change in modelled income from the base year. Where cost pressures are expected to increase more rapidly than modelled income this represents a funding gap.
• the headline England total funding gap is then calculated by aggregating the funding gaps for each council for a particular year or time period. A small number of councils where funding growth outstrips growth in cost pressures, creating a notional ‘surplus’, are excluded from this calculation. Surpluses cannot be transferred from one council to another. 
• this iteration of the model covers the period up to an including 2028/29. This provides funding gap figures in 2026/27 and the two subsequent financial years.

3.1 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.

3.2 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. 

3.3 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

3.4 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.

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

• Adult social care
• Children’s social care
• Public health
• Highways
• Public transport (including integrated transport levies)
• Housing services (excluding housing revenue account (HRA) and housing benefits)
• Cultural and related services
• Waste management
• Environmental and regulatory services (including waste levy)
• Planning and development services
• Central services (including ‘other services’)
• Other education and community services
• Fire services (in shire county councils with fire services only)

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

• Education services - council spending cannot be separated from school spending. However, we include ‘other education’ spend in the model.
• Police services – these services are in general not provided by councils.  
• Expenditure by non-council bodies who appear in the RO forms. These are the Greater London Authority, police and crime commissioners, national park authorities, standalone fire and rescue authorities, combined authorities, and waste authorities.

Calculating net spend

3.7 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:

• We model change in the two components of total spend in each service area in the RO: 
  • Employee costs - which relate to the cost of councils’ employees; and 
  • Running costs - which relate to other costs incurred by councils including the commissioning of services from external providers. 
• We also model change in sales, fees and charges income and other income. These income projections are then subtracted from our modelled total spend to arrive at net spend cost pressures. 

3.8 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

3.9 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 the time period of the model. These relate to:

• Employer national insurance contributions (NICs): For 2025/26 we add an estimate of the costs to councils of changes to employer NICs announced in the 2024 Autumn Budget. We include an estimate of the ‘direct’ cost to council wage bills which apply to employee costs in each sector. We also include an estimate of the ‘indirect’ costs that could potentially be passed to councils by third party service providers. Indirect costs are applied to running costs in each service. 
• Adult social care Fair Pay Agreement (FPA): We add a cost pressure of £500 million in 2028/29 to reflect the introduction of the FPA. The precise cost of the FPA is not clear. However, Government is providing £500 million in Core Spending Power to relevant councils in 2028/29 to support with the introduction of the FPA. As this is a new responsibility not currently in councils’ baseline spend, we add an additional £500 million cost pressure to offset the new funding.
• Simpler Recycling: Government has provided councils with an unspecified amount of funding in CSP to support the implementation of this scheme from 1 April 2026. As this is a new responsibility not currently in councils’ baseline spend, we add a modelled cost pressure for the delivery of this new service to offset the new funding.
• Emissions Trading Scheme (ETS): We have included an adjustment to reflect that the ETS)will apply to waste incineration from January 2028. This is based on analysis commissioned by the LGA, which estimated the cost to the sector based on low, medium and high carbon pricing scenarios.

3.10 As new RO data sets are published annually, 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

3.11 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. 

3.12 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. 

Cost and demand drivers

3.13 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). 

3.14 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. 

3.15 Where possible, the measures are based on published projected data such as the OBR inflation forecasts or ONS population projections

3.16 Where these formal projections are not available we use the average annual change over the previous five years to produce an estimate of future annual change in demand. We adjust the data to remove the impact of the COVID-19 pandemic on trend data where necessary. In a small number of cases, particularly where the trend for a metric at the council level is highly variable, we use a linear regression to generate estimated future demand.

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

General drivers

3.18 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

3.19 The change in pay for directly employed staff is based on the total annual pay bill impact of pay settlements agreed for 2025/26. We also include an estimate of pay drift (the cost of annual increments payable to staff at certain stages in their local government employment). 

3.20 For 2026/27, we use the Joint Negotiating Committee’s (JNC) offer of 3.3 per cent. From 2027/28 onwards, we use the median pay increase estimate from CFOs to our January 2026 budget setting survey. These figures are applied to the employee costs line in each service area. 

3.21 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

3.22 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. 

3.23 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 2024/25 through to 2026/27 we use the actual increase in the NLW. In the absence of NLW forecasts in 2027/28 and 2028/29 we use the median pay increase estimate from CFOs in social care councils to our January 2026 budget setting survey.

Population and household projections

3.24 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.

3.25 To create up-to-date sub-national projections, we apply the rate of growth in the national population projections from 2022 to the actual 2024 mid-year estimate (MYE). This uprated data set is then collated by age categories to create more accurate percentage changes. 

3.26 This approach was not needed for household number projections as the most recent update to Household Projections for England was released in October 2025. Table 406 within this data set is used to calculate yearly household percentage increases for all LA.

3.27 Different demographic drivers to population and households are used in specific service areas, notably adult social care and looked after children. These are set out in the following sections.

Inflation

3.28 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).

3.29 For CPI we have used the Scenario B forecast from the Bank of England’s April 2026 Monetary Policy Report from 2026/27. This is the middle option of the Bank’s three scenarios published to reflect the uncertainty created by the current Middle East conflict. 

3.30 In the absence of an updated RPI forecast we use the RPI forecast inflation figures from the OBR released in March 2026

Energy prices

3.31 Considering current fluctuations in energy prices, it is 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.

3.32 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.

3.33 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 energy inflation, which is taken from the Bank of England’s April 2026 Monetary Policy Report

Service specific drivers

3.34 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

3.35 For the majority of the adult social care sub-service lines we model service demand based on the most recent published data from the Care Policy Evaluation Centre (CPEC – formerly the Personal Social Services Research Unit (PSSRU)). CPEC publish both demand and net spend forecasts. In principle we could use the net spend forecasts, however, we prefer to have the flexibility to apply our own up-to-date costs drivers for factors such as inflation and the NLW. Consequently, we use CPEC’s demand forecasts, which we rebase to the 2022 Population Projection, alongside our forecasts for CPI, the NLW and Green Book pay to produce a cost pressure.

3.36 We apply the same method for services for Working Age adults and those aged 65+. However, it is apparent that our cost drivers are not reflecting the full cost pressures for this group. Our forecast is some way below CPEC’s net spend forecast. Also when applying our method retrospectively our model materially undershoots actual spending growth for commissioned services for this group in recent years. We anticipate that this gap reflects factors that are not included in our costs drivers such as increasing complexity of need for this group and/or tightening market conditions. To address this, we add the average annual percentage underspend when our model is compared to actual spend over the period 2019/20 to 2024/25 to our forecast running costs for this group. This adjustment brings our figures in line with CPEC’s own net spend forecasts.

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

• For “Social support: Substance misuse support” we model future demand based on trend data in rates of drugs misuse. We model drugs misuse by using the ONS Crime Survey for England and Wales to take the average proportion of 16-59 year olds reporting drug misuse in any given year. We use a linear regression to model future demand.
• For “Social support: Asylum seeker support” we model future demand based on the trend in the number of Asylum seekers over the age of eighteen. We use Home Office data on the number of Asylum Seekers in Receipt of Support by Local Authority. This data is not broken down by age group. To capture those 18 and over we have weighted the indicator by the age breakdown that is available in Table Asy_D01 in the Asylum Initial Decisions and Resettlement dataset. The trend-based projection for this metric is based on the annual change in the average number of asylum seekers across the four quarters in each calendar year from 2016/17 to 2024/25, excluding 2020/21 and 2021/22 to remove the impact of the pandemic.

Children’s services

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

• In children’s social care, projected future demand for looked after children placements is based on five-year trend data in the number of children in different placement types using the Department for Education’s 'Children looked after in England including adoptions' data. We apply the change in rate of public placements to employee costs in the RO data and that of private placements to running costs. These are applied to the disaggregated lines around “Children's social care - Children Looked After” in the RO.
• For spend on looked after unaccompanied asylum-seeking children (UASC) we model future demand pressures using the annual average of the five-year trend in under eighteen asylum seekers numbers, excluding the pandemic affected years of 2020/21 and 2021/22. 
• We model demand pressures in safeguarding children and young people’s services based on trend data in child protection plans (CPP) using DfE’s Children in Need data. We use a linear regression to model future demand.
• We apply data around young offenders to the RO line “Children's social care - Youth Justice”. We  collate the regional numbers of young people in custody as of the end of March in each year (2015-2025) from government data. We use a linear regression to model future demand. 
• We model demand pressures in children’s social care – asylum seekers based on trend data in the number of asylum seekers aged under eighteen. We use Home Office data on the number of Asylum Seekers in Receipt of Support by Local Authority. This data is not broken down by age group. To capture under 18-year-olds we have weighted the indicator by the age breakdown that is available in the Asylum Initial Decisions and Resettlement dataset. The trend-based projection for this metric is based on the annual change in the average number of asylum seekers across the four quarters in each year calendar year from 2016/17 to 2024/25, excluding 2020/21 and 2021/22 to remove the impact of the pandemic.

3.39 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, in recent years unit costs for residential placements for looked after children have been increasing markedly faster than our standard pay and inflation cost drivers. 

3.40 To adjust for this difference, we calculate the annual average increase in unit costs for residential provision for both council-run services in the ‘employee’ line, and for external providers in the ‘running costs’ line. We add this to our pay and CPI drivers based on the difference between annual average growth in unit costs from 2019/20 to 2024/25 and our existing drivers. 

3.41 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.

DSG deficit costs

3.42 We do not include the fully value of councils’ DSG high needs deficits in the model. Councils’ general funds are currently protected from the full impact of the deficits by the statutory override. However, despite the statutory override, there are two direct costs to councils’ general funds from the deficits that we include in our model:

• Government has announced a plan to write-off 90 per cent of councils’ historic deficits (accrued by 31 March 2026). We assume that all councils with a deficit will receive this funding, and that they will use their general funds to address the 10 per cent residual – spreading the costs evenly over 2026/27 and 2027/28. We include the estimated costs of the residual in these two years in the model. Government has not announced plans on how it intends to address deficits accruing in 2026/27 and 2027/28. However, for the purpose of modelling we have assumed that Government will apply a similar 90 per cent write-off – and that councils will address the 10 per cent residual evenly over 2028/29 and 2029/30. We recognise that Government would have to introduce a new statutory override or a similar arrangement for this to happen. We use the OBR’s analysis and methodology published at the 2025 Autumn Budget to estimate the size of both historic and accruing deficits.
• As set out above, we include an estimate of the treasury management costs to councils of maintaining the deficits. We use the OBR’s projected deficits and methodology published in the 2025 Autumn Budget to estimate the size of deficits. We adjust the deficits to reflect the timings of Government’s proposed write-off. We note that Government’s plan to pay the 90 per cent write-off of historic deficits in autumn 2026 means that councils will bear the treasury management costs of their full historic deficits for at least six months of 2026/27. We calculate the treasury management costs of the deficits as the income foregone compared to placing this cash in the Debt Management Office deposit facility (which applies the SONIA rates).

Highways

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

• The change in vehicle miles – principal local authority roads is applied to the RO line “Structural maintenance - principal roads, Environmental, safety and routine maintenance – principal roads” and is based on the average change in vehicle miles of principal LA roads from 2016/17 to 2023/24, which excludes any pandemic related impact in later years. The data source is the Department for Transport; Table TRA 0203
• The change in vehicle miles – other local authority roads is applied to the RO line “Structural maintenance – principal roads, Environmental, safety and routine maintenance – other LA roads” and is based on the average change in vehicle miles of principal local authority roads from 2016/17 to 2023/24, which excludes any pandemic related impact in later years. The data source is the Department for Transport; Table TRA 0203
• The change in vehicle miles – all roads is applied to the RO line “Structural maintenance - bridges, Winter service, Congestion charging” and is based on the average change in vehicle miles of principle local authority roads over the past five years from 2016/17 to 2023/24 , which excludes any pandemic related impact in later years. The data source is the Department for Transport; Table TRA 0203
• The change in the number of households is applied as the case level to the RO line “Street lighting (including energy costs)” and is based on our adjusted measure of household growth as described above. The raw data comes from  ONS Household projections
• The change in the number of vehicles registered is applied to the RO lines “On-street parking”, and “Off-street parking” and is based on the average change in the number of vehicles licensed from Q4 2018 to Q4 2025, as unlike the mileage data there is no clear pandemic impact here. 
• The data source is from the Department for Transport; VEH0101a. SORN vehicles (those declared off-road) are removed from the data set. 

Housing

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

• The change in the number of households at the case level is applied to the RO lines “Housing strategy, advice and enabling”, “Housing advances”, “Administration of financial support for repairs and improvements”, “Other private sector housing renewal”, “Rent allowances - discretionary payments”, “Non-HRA rent rebates - discretionary payments”, “Rent rebates to HRA tenants - discretionary payments”, “Other council property (Non-HRA)”, “Supporting People”, and “Other welfare services” and is based on our adjusted measure of household growth as described above. The raw data comes from ONS Household projections
• We model future demand pressures for homelessness services using the average growth in temporary accommodation from 2014/15 to 2024/25 and duty owed (source: Ministry for Housing, Communities and Local Government; Statutory homelessness England level time series "live tables", table TA1) and the change in population (source: ONS).

Waste management services

3.45 We use the following demographic drivers to model future demand and cost pressures in relation to waste management services:

• The adjusted measure of household growth is applied to the RO lines “Waste collection,” “Waste disposal,” “Trade waste,” and “Recycling” and is based on our adjusted measure of household growth as described above. The raw data comes from ONS Household projections
• We have included an adjustment to reflect that the Emissions Trading Scheme (ETS) will apply to waste incineration from January 2028. This is based on analysis commissioned by the LGA, which estimated the cost to the sector based on low, medium and high carbon pricing scenarios. This presents a cost pressure in 2027/28 and 2028/29, which we distribute according to existing levels of Waste Disposal spending by Waste Disposal Authorities (WDAs). 
• In 2026/27 we include an adjustment to the ‘Waste Collection’, ‘Waste Disposal’ and ‘Recycling’ RO lines to reflect the estimated cost of implementing separate collections for food waste and fibre-based materials from 1 April 2026 – Simpler Recycling. We have calculated the additional cost for each council by taking the net cost for these three service lines from the RO5 data from 2024/25. We then apply cost factors from WRAP’s Local Authority portal which estimates changes in costs per household, to disposal and collection spending lines. These factors reflect increases and decreases in costs from moving to the ‘simpler recycling’ model.  We have assumed there will not be a 100 per cent uptake of the scheme, therefore we apply an adjustment based on the variation in recycling rates between authorities with similar levels of rurality and deprivation. For Waste Disposal Authorities, we have calculated an aggregate cost factor on ‘Waste Disposal’ based on the cost factors provided for each constituent council. Where an authority is subject to transitional measures beyond 2028/29, reflecting where long-term disposal contracts prevent ‘simpler recycling’ collections from being introduced, their costs are excluded from this modelling.  

Other environmental services

3.46 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

3.47 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

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

• Rates of drugs misuse are applied to the RO line “Substance misuse - Treatment for drug misuse in adults.” We model drugs misuse by using the ONS Crime Survey for England and Wales to take the average proportion of 16-59 year olds reporting drug misuse in any given year. We use a linear regression to model future demand.
• The change in the number of new sexually transmitted infections (STI) diagnoses is applied to the RO lines “Sexual health services - STI testing and treatment (prescribed functions)”, “Sexual health services - Contraception (prescribed functions)”, and “Sexual health services - Advice, prevention and promotion (non-prescribed functions)”. We use fingertips data from the United Kingdom Health Security Agency (UKHSA), and sum the total incidences of Syphilis, Gonorrhoea, and Chlamydia at a local authority level by year. We use a linear regression to model future demand.
• Increase in obesity rates for adults and children is applied to the RO line “Obesity - adults” and “Obesity - children” respectively. We use fingertips data from the UKHSA for obesity prevalence in adults and year six prevalence of obesity (10-11 years) for children. We use a linear regression to model future demand.

Other education

3.49 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.

3.50 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). We use a linear regression to model future demand.

3.51 For the non-SEND element of this spend, we model future demand in line with projected demographic growth in 0–17-year-olds.

Levies

3.52 We include annual levies paid to waste and transport authorities. 

• Waste levies - There are significant changes expected in spending on the ‘Waste Disposal’ line over the next three years, driven by the introduction of Simpler Recycling and the Emissions Trading Scheme. These changes were not previously brought into the funding gap analysis, as we previously adjusted levies in line with total population growth. Therefore, we now assume that constituent councils’ levy payments will fluctuate in line with projected net spending by standalone WDAs. 
• Transport levies - We model future levy costs in line with total population growth.

4.1 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:

• The cost pressures element of the model estimates future total service spending costs. To convert this into net spend we estimate future changes in sales, fees, and charges, and ‘other income.’ We subtract these estimates from the total spend cost pressure to provide a net spend cost pressures figure.
• The funding gap element of the model then uses Core Spending Power and Public Health Grant. To calculate the funding gap, we compare change in net spending pressures against forecast change in Core Spending Power and Public Health Grant.

Sales, fees and charges and other income

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

Sales, fees, and charges income

4.3 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.

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

• Homelessness services. In recent years total spend in this service area has increased at roughly twice the rate of both sales, fees and charges and other income. We understand that this reflects a shortfall in the value of temporary accommodation subsidy relative to councils’ actual costs, and a growing inability of service users to meet the balance or pay other fees and costs.
• In the absence of any interventions with the potential to alter this pattern we assume that this trend will continue over the short-term. We reflect this in the model by assuming that sales, fees, and charges (and other income) in this service area will grow at approximately half (56.4 per cent) of our modelled increase in total expenditure on homelessness services. This reflects the five-year trend in this income stream, adjusted to remove any exponential growth.
• Adult Social Care. Higher costs for adult social care driven by increases in employer NICs may feed through into higher client contributions as these are often calculated on a pro-rata basis. To reflect this, we uprate adult social care sales, fees, and charges income in 2025/26 in line with our modelled percentage increase on total spend due to the indirect impact of the NICs changes on adult social care. This is in addition to our application of inflationary and demographic drivers to adult social care sales, fees, and charges income in that year.

Other income

4.5 Other income includes:

• revenue income received to finance a function/project jointly or severally undertaken with other bodies. 
• contributions from other local authorities. 
• value of costs recharged to outside bodies including other committees.
• recharges (to internal users).

4.6 In our view these income streams do not necessarily move in line with inflationary, pay or demographic pressures used throughout our model. 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. 

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

• In adult social care the bulk of other income is accounted for by transfers from NHS bodies including Better Care Fund spending. Trends in this income stream are not necessarily driven directly by CPI or demographic pressures. Consequently, we calculate the yearly percentage increase for the total Department Expenditure Limits (DEL) for Health and Social Care (table 5.1, 2025 Spending Review). ASC Other Income RO categories are therefore driven by this percentage increase.
• Other income is substantial in central services. Much of this income is accounted for by internal recharges. However, growth in other income in central services has not kept pace with total spend for central services over many years. Over the period 2019/20 to 2024/25 it has grown by 0.9 per cent annually less on average than total spend. We adjust our forecast for other income in central services to reflect this difference in growth rates.
• We model other income for homelessness services in the same way and for the same reasons as we do for sales, fees, and charges income for this service area.

Netting off ‘surpluses’

4.8 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.

4.9 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.

4.10 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

4.11 To calculate the funding gap, we compare change in modelled net cost pressures since 2024/25 against change in forecast Core Spending Power (CSP) and Public Health Grant. With the multi-year settlement announced in February, we have used the values provided for CSP and consolidated grants up to 2028/29. We have applied some caveats to this: 

• Council tax – we have used the Government’s projected increases in Council Tax over the multi-year settlement. This includes estimated council taxbase growth. As a result, this includes projected incomes for six authorities who will not be subject to referendum principles in 2027/28 and 2028/29. However, it also does not reflect where exceptional referendum principles were granted to councils in 2026/27. 
• ‘Consolidated Grants’ – We have included all the new consolidated grants in our model, except for the Crisis and Resilience Fund. This includes the Public Health Grant and components of the Children, Families and Youth Grant which sit outside CSP. . 
• New Burdens Funding – From 2026/27 a number of s.31 new burdens funding grants provided in 2025/26 have been rolled into Revenue Support Grant and some of the consolidated grants. As these activities started in 2025/26 at the earliest, the costs of delivering these responsibilities are not yet in the 2024/25 RO data that forms the basis of our model. Including the funding without adding in a cost would misrepresent the level of funding available relative to costs. Given the relatively small scale of these grants and the complexity of modelling their associated service costs we simply remove this funding from our income figures.

4.12 Any changes in funding over the multi-year settlement will have implications for the funding gap. Different decisions will act to increase or reduce the gap.

Extended Producer Responsibility for Packaging (pEPR)

4.13 Government has announced that £1.2 billion will be available to local authorities in England through this scheme, of which £1.1 billion is for councils, in 2025/26. 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.

4.14 While this income is not within CSP, we include it in our modelled income from 2025/26 onwards, 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.

4.15 While we include pEPR funding in our modelling, 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

4.16 The Government has confirmed EPR the final allocation for 2025/26 and indicative allocations for 2026/27. The Government indicated at the Autumn Statement 2025 that there will be reforms to the scheme over the next few years. Whilst we await detail on these reforms, we have assumed that funding will increase with CPI each year. 

Download Appendix 1 - cost pressures and funding gap modelling 2026 technical guidance