Scottish Budget 2026 to 2027: distributional analysis

Annex: Methodology

Modelling Approach

This analysis uses two separate models, one for tax and benefit modelling, and one for public spending.

The tax and benefit analysis uses UKMOD, an open-access microsimulation model developed by the Institute for Social and Economic Research (ISER) at the University of Essex. The model applies tax and benefit rules to a set of individual and household-level data, allowing the user to simulate and compare alternative scenarios.

The input data in UKMOD is derived from the Department for Work and Pensions' Family Resources Survey (FRS). The analysis of tax and benefits in this paper uses three years of FRS data, 2021-22, 2022-23 and 2023-24. To pool the data, the grossing weights used to scale the FRS sample to the whole population are divided by the number of data years.

The public spending analysis uses a separate, purpose-built model. It links supplementary service-use information to the UKMOD output dataset. This linkage enables estimation of which households are likely to access public services, based on demographic and socioeconomic characteristics.

The income components and other monetary variables are scaled to the year being analysed (2024-25) based on the Office for Budget Responsibility (OBR) latest forecasts. No adjustments are made for demographic change.

All modelling includes adjustments to take-up rates of social security payments to reflect the latest take-up estimates. Overall amounts are reviewed against published outturn statistics. The model does not include any behavioural effects associated with tax policies.

Analysing the distribution of income

Parts one and two of the analysis examine the impact of policies on net household income before housing costs, showing how tax and benefit changes affect households across the income distribution. In contrast, part three shows a modelled allocation of government spending across the income distribution. All results are presented across the income distribution, which is arranged using equivalised net household income before housing costs. In this context, net means after the impact of direct taxes and social security payments.

Equivalised means income is adjusted based on household size and composition, to allow for the fact that larger households will require a higher income to maintain a similar standard of living as a smaller household. This analysis uses the modified OECD equivalence scale, following the same approach as used in UK and Scottish Government poverty analysis. Further detail on the equivalisation calculation is available here.

Household income means that all income is assumed to be shared across all members of the household. This analysis uses the Family Resources Survey definition of a household (i.e. one person living alone or a group of people - not necessarily related - living at the same address, who share cooking facilities and share a living room or sitting room or dining area).

Before housing costs means that no deductions are made for rent or mortgage payments from household incomes.

Part one and part two report results based on the average gain or loss of income within household income deciles. Part three reflects the average government resource spending per household within household income quintiles. There may still be considerable variation around the estimated averages.

As an indication of the income levels in each decile, table A1 below shows the median gross (i.e. pre-tax and pre-social security) unequivalised household income in each decile.

valised net income decile in the 2026-27 policy scenario,/

Table A1: median unequivalised gross annual household income, by equivalised net income decile in the 2026-27 policy scenario

Equivalised household income decile, before housing costs	Median unequivalised gross annual household income (£)
1	£900
2	£2,900
3	£10,600
4	£23,000
5	£26,800
6	£33,400
7	£46,200
8	£63,400
9	£80,000
10	£128,900

Tax and benefits: scope

The following policies are devolved taxes or social security payments which are explicitly modelled in this analysis: Scottish Income Tax, Council Tax (excluding Water and Sewerage charges), Scottish Child Payment, Discretionary Housing Payments (DHPs) used to mitigate the bedroom tax and benefit cap, Carers Allowance Supplement, Best Start Grant and Best Start Foods, Child Winter Heating Payment and Pension Age Winter Heating Payment.

In addition to the payments listed above, the Scottish Government also has responsibility for a range of disability benefits, which have been replaced by the Adult Disability Payment, Child Disability Payment and Pension Age Disability Payment.

These benefits are reflected in the underlying survey data, but the impact of the changes introduced by the Scottish Government are not modelled. Consequently, differences in policy on these aspects of the social security system do not account for any of the differences shown in figures 2 or 3 above. As more data becomes available on the effect Scottish Government policy changes have on take-up, we may revisit modelling of these aspects of the social security system.

Figure 1 presents analysis of a wider segment of the tax and social security system, including several reserved policy measures, and so additionally includes: Employee National Insurance Contributions, Income tax on savings and dividends income

Universal Credit, and the legacy benefits it replaces, Pension Credit, Child Benefit, State Pensions, Statutory sick pay and Statutory maternity pay.

All impacts on household incomes are shown excluding any behavioural responses. This is particularly important when considering impacts of tax policy on higher income deciles, where behavioural responses to policy changes are likely to be greatest. The analysis may not reflect impact on the very richest households.

Public Spending

The public spending model combines income variables and household characteristics from the FRS with modelled tax and benefit data, supplemented by service-use information. The aim is to estimate how much individuals use each public service, enabling spending to be allocated and averaged across the income distribution.

This publication covers five areas of public spending: Health, Funded Early Learning and Childcare (ELC), Further and Higher Education, Schools, and Transport. The methodology builds on the 2021 Scottish Government feasibility study^[13] on distributional analysis of taxes, social security, and public services.

Spending lines are taken from Level 4 budget tables where possible. For schools and funded ELC, expenditure is funded through Local Government and therefore is not separately identified in Budget allocations.

Resource spending is aggregated to the household level, and all charts present household-level allocations to ensure comparability with the tax and social security analysis in Parts One and Two.

Where detailed data on individual service use is not available, the analysis assumes that individuals with similar broad characteristics access services in a comparable way. These assumptions are necessary given data constraints and are consistent with established practice in distributional analysis. Further discussion of these methodological considerations can be found in the Institute for Fiscal Studies (IFS) report on modelling public service spending.^[14]

Health

The health modelling approach aims to follow the principles of the National Resource Allocation Formula (NRAC), which Public Health Scotland use to distribute NHS funds to health boards in Scotland.

Spending is allocated according to an individual's age and sex using the NRAC cost curves across six care packages: Acute, Care of the Elderly (COTE), Mental Health and Learning Difficulties (MHLD), Maternity, Community, and GP Prescribing.

An additional adjustment is applied according to the individual area of residence. This aims to account for relative need due to differences in morbidity and life circumstances. However, this adjustment is relatively minor because location data is only available at a high level and does not capture the variation across smaller geographies.

No adjustment is made for differences in the cost of delivering services in different geographic areas (e.g., additional travel costs for district nurses in remote regions). This is because the model assumes that the level of care, and therefore its value to the household, is consistent across locations.

The total allocation is then scaled to match the total health spending reported in the Level 4 tables.

Unlike other areas of public spending, which allocate resources based on actual or modelled usage patterns, this approach uses an insurance-based method. This is due to limited availability of reliable health service usage data and the need to reflect the greater costs associated with illness, rather than actual service consumption.^[15]

Funded Early Learning and Childcare (ELC)

The analysis models the entitlement to 1,140 hours of funded ELC for 3 and 4 year olds and eligible 2 year olds. It uses data from the FRS to identify users of funded and formal childcare. The FRS is based on self-reported data, and may not perfectly represent all households eligible for funded ELC, especially if some groups are underrepresented.

To increase sample sizes, data is pooled across three years: 2021, 2022 and 2023. While most of this period follows the introduction of the policy in August 2021, it also includes some data from before implementation.

Spending data is taken from Local Government 2024-25 Provisional Outturn and 2025-26 Budget Estimates and uprated by the overall growth in resource spend, excluding spend on health and social care, education and skills, and transport. The amount spent on funded ELC is allocated proportionately to households based on the modelled number of hours used. This household spending figure is then averaged across quintiles and household type.

Further and Higher Education

To model further and higher education, the FRS is used to identify people who are students or who might be students.

The caseload of further education students identified in survey responses is lower than reported figures. This is partly because some groups are underrepresented in the survey classification. For example, individuals under 16 who attend further education part-time alongside secondary school are recorded as attending secondary school only.

To address this, random sampling is applied to under-16s, and individuals aged 16 and over who report being economically inactive and not in higher education. These sampled cases are added to the further education caseload until the target caseload is met.

For higher education, the number of respondents reporting that they are in higher education is reasonably close to the reported caseload. This group is split into individuals who identify as Scottish in the FRS and those who don't.

Spending data for further education is taken from the Level 4 spending line for college resource. This expenditure covers both further and higher education delivered in colleges. However, as there is not sufficient detail in the data to distinguish higher education students attending college from those attending university, we assume that higher education students in colleges receive the same per-student allocation as higher education students in university. The remaining college expenditure is allocated solely to further education students. This is allocated evenly across all further education students.

Spending data for higher education is taken from the Level 4 tables. Higher education resource spending is allocated evenly across all higher education students. Student support and tuition fee payments are available to Scottish-domiciled students only. Spending is allocated to individuals who identify as Scottish and in higher education. This approach does not aim to model caseload by ethnicity but helps refine the estimate to bring it closer to the target caseload.

Schools

The schools methodology uses the FRS to identify children who attend state-run primary or secondary school, and distributes spending evenly among them.

Due to data issues, the special school education budget is shared proportionately across the primary and secondary education budgets based on pupil numbers. A location factor is applied to adjust for more spending on schools in deprived areas. The location factor is calculated using the amount spent in each local authority on primary and secondary.

Spending data is taken from Local Government 2024-25 Provisional Outturn and 2025-26 Budget Estimates and uprated by the overall growth in resource spend, excluding spend on health and social care, education and skills, and transport.

Transport

Transport modelling uses individual travel patterns from the Scottish Household Survey (SHS) to develop a logistic regression model. This model predicts the likelihood of using different methods of transport - car, bus, train, and concessionary bus passes - based on characteristics such as age, income, and sex.

The model is then applied to the FRS to estimate each individual’s probability of using each transport method. These probabilities are used to proportionally allocate transport expenditure among individuals as a proxy for usage. The allocated amounts are scaled so that the total matches the transport resource spend reported in the Level 4 spending lines.

As a validation step, results for specific demographic groups are compared against the Transport and Travel in Scotland (TATIS) survey to ensure consistency.

Scottish Spending Review

The distributional analysis of the Scottish Spending Review does not cover all resource spending, as only some areas of spending relate to the direct provision of goods and services to households. The distributional analysis model covers resource spending on Health, Schools, Further & Higher Education, Early Learning & Childcare (ELC) and Transport. Together these accounted for 70% of total spending in 2025-26, excluding spending on Social Security, which is covered in parts 1 and 2 of this publication.

Spending Review assumptions

• It is assumed that spending on Health will grow in line with the relevant Level 4 lines in 2026-27 and spending on the Health & Social Care portfolio in the SSR allocations for all future years (Health is the main component of that spending).
• Transport spending is assumed to follow relevant Level 4 lines in 2026-27 and the path set out for the Transport portfolio for all future years (although only a portion of that spending is covered in the model).
• Spending on Higher & Further Education is assumed to grow in line with proposed allocations for relevant Level 4 lines and the path set out for the Education & Skills portfolio for all future years.
• It is assumed that spending on Schools and ELC – in the absence of granular data – will grow in line with spending on all other portfolios combined, once Health & Social Care, Education & Skills and Transport are excluded.

Counterfactual Parameters

Table A2 below summarises the parameters used for each of the two counterfactuals reported on in this analysis.

Table A2: counterfactual parameters

Policy	Part 1 counterfactual: rUK policy counterfactual for 2026/27	Part 2 counterfactual: No policy change counterfactual for 2026/27
Income Tax	Income Tax rates and bands as in place in England & Northern Ireland for 2026/27, based on Autumn Statement announcements.	Personal allowance frozen, as per UK Government policy. All bands uprated by CPI (3.8%). All rates unchanged.
Council Tax	Excluded from comparisons made against this counterfactual.	Average Band D Council Tax uprated with CPI.
Scottish Child Payment	Policy not in place.	Awards uprated with CPI. Eligibility criteria remain unchanged.
Discretionary Housing Payments to mitigate bedroom tax benefit cap	Policy not in place.	Awards uprated with CPI. Eligibility criteria remain unchanged.
Carers Allowance Supplement	Policy not in place.	Awards uprated with CPI. Eligibility criteria remain unchanged.
Child Winter Heating Payment	Policy not in place.	Awards uprated with CPI. Eligibility criteria remain unchanged.
Best Start grant & Best Start Foods	Replaced with Sure Start and Healthy Start grants	Awards uprated with CPI. Eligibility criteria remain unchanged.
Pension Age Winter Heating Payment	Flat payments of £200 and £300.	Restricted eligibility for full payments to households receiving a qualifying benefit and a lower payment of £100 to all other pensioner households.