Communities and Local Government Committee Reforming Local ...€¦ · Needs Formula (RNF) in...

FINANCE WITH VISION

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Communities and Local Government Committee Reforming Local Authority Needs Assessment

Paper 3 – Review of Needs Assessment Data Sources

October 2017

Contents

Contents 2

1. Key Points ................................................................................................ 3

2. Scope of the Analysis ............................................................................... 5

Population projections and estimates 8 Road lengths and geographic data 9 Income- and employment-related benefits 9 Socio-economic and demographic data 10 Disability-related benefits 11 Additional population measurements 11 Past expenditure and debt 12 Area Cost Adjustment (ACA) 12

3. Possible Additional Indicators ................................................................. 21

4. Conclusions ............................................................................................ 23


FINANCE WITH VISION 3

1. Key Points

This paper examines the indicators used by DCLG in the calculation of the Relative

Needs Formula (RNF) in 2013/14. It focuses on the timeliness of the indicators, and

whether up-to-date data could be used in future needs assessment formulae.

DCLG uses criteria to determine the appropriateness of indicators for use in the

formula. This includes whether or not the data can be influenced by local authority

discretion, whether it is open to manipulation, whether it creates any perverse

incentives for local authorities, and whether any variations in the data could lead to

misleading conclusions.

A key issue for future needs assessment formulae is the timeliness of the data,

and whether existing data sources could be updated. LG Futures has provided a

summary of the broad indicator categories used in the current RNF (excluding Police

and Fire & Rescue), based on the ease with which they could be updated. This

summary draws on analysis carried out by DCLG as part of its Fair Funding Review.

Population projections and estimates are one of the most important determinants

of assessed needs in the current formula. Up-to-date projections would be available

as part of any new needs assessment formula, incorporating the results of the 2011

census and subsequent projections of births, deaths and migration.

Demographic and socio-economic data, taken from the 2001 census, are used

extensively throughout the current formula. It would be possible to update these

figures based on the 2011 census; however, these would be several years old

once the next needs assessment formula is calculated.

A major challenge will be updating income- and employment-related benefit data.

These are used as a proxy for deprivation for a number of services. Given the ongoing

roll-out of Universal Credit, it may not be possible to obtain benefit statistics that are

comparable between local authorities. As a result, DCLG may be limited to using benefit

data from 2013 or older.

Some disability-related benefits used in the current formula will also be affected by the

introduction of Universal Credit, and so the existing data sources could not be updated.

Measurements of additional population – including net in-commuters, day visitor

and overnight visitor numbers – are presently out of date. Data on commuter

numbers could be updated based on the results of the 2011 census. Data on overnight

visitor numbers are now very old, and new estimates would need to be produced.

Previous attempts to model updated day visitor numbers proved challenging, and

DCLG reports that the results were rejected by local government.

Existing sources of road length and other geographical data could be updated,

though in some cases this would require the purchase or commissioning of the

necessary data.



Indicators based on past expenditure and debt, and data used to calculate the Area

Cost Adjustment, could be updated using existing data sources.

DCLG has not yet proposed a final set of indicators be used in future needs assessment

formulae, but has published an initial ‘long list’ of cost drivers for further consideration.

This paper lists the additional cost drivers which are not included in the current Relative

Needs Formula. These are still at discussion stage and, given a lack of detail, it is not

yet possible to fully assess whether indicators that reflect these cost drivers would be

appropriate for use in a future formula.

Once the final group of indicators has been identified, DCLG will need to select those

indicators to be included in the final formula. In the current needs assessment formula,

indicators were selected and assigned weights using both judgement and statistical

techniques. The choice of indicators will be of significant interest to local authorities, as

it will create ‘winners’ and ‘losers’ in terms of the resulting distribution of assessed

needs. The method used to select indicators for the simplified needs assessment

formula is currently being considered as part of the Fair Funding Review process.



2. Scope of the Analysis

2.1. Over 120 indicators were used to measure local authorities’ relative needs as part of the

current Relative Needs Formula (RNF).1 The RNF was the main determinant of each

authority’s Formula Funding, which was worth £17.9 billion in 2013/14, the final year in

which funding shares were calculated.2

2.2. DCLG employ a set of criteria for assessing whether indicators are appropriate for inclusion

in its needs assessment formulae. The following questions are currently considered when

determining whether a data source or indicator is appropriate for use in the formula:3

Is the data influenced by local policy discretion?

Can the data be open to manipulation by authorities?

Does the data create any perverse incentives? For example, ‘roads where

maintenance should be considered’ might be a key cost driver for Highway

Maintenance, but it would be a poor indicator for the formula, as it could theoretically

incentivise authorities to delay repairs.

Are there regional variations that are misleading? For example, lack of access to a car

may be a suitable indicator for deprivation in rural areas, but less so in urban areas

where residents are likely to have better access to public transport.

Is the data used elsewhere for policy calculations, and if so are there lessons to be

learnt?

How extensively has the data been validated by the provider?

If the data comes from a sample survey, is the sample size large enough for all

authorities?

How regularly can the data be updated?

2.3. DCLG therefore has a framework in place for determining what constitutes an appropriate

indicator. This section focuses primarily on last of these criteria: the timeliness of the

indicators, and the ability to update them. The needs assessment formula was last updated

in 2013/14, and now includes data that is over 25 years old, as well as a large number of

indicators derived from the 2001 census. Whether these indicators would be appropriate

for use in a future needs assessment formula will largely depend on whether or not they

can be updated.

1 DCLG and Local Government Association, Discussion 1: The Progress of the Fair Funding Review, from the Business Rates Retention Regional Consultation Event, 2017.

2 Excluding police authorities, the Greater London Authority and Isles of Scilly.

3 This list of requirements is part of DCLG’s current guidance, but was applied at least since 2006. See for example DCLG, Methods of Determining Relative Needs Formulae, Paper Presented at the 11th GSS Methodology Conference, June 2006.



2.4. This analysis focuses on the indicators used to calculate the Relative Needs Formula

(excluding emergency services). This is a subset of indicators used to allocate Formula

Funding, as it excludes Tailored Grants which were allocated using their own bespoke

criteria, rather than the Relative Needs Formula. The Relative Needs Formula was used to

estimate needs for 16 services, each of was assigned a different weighting or control total,

as shown in the table below.

Table 1: Relative Needs Formula – Breakdown by service block 2013/14

Service Block Sub-block Control total

Children’s Services

Youth & Community 1.2%

Central Education Functions 4.9%

Children’s Social Care 9.7%

Adult Social Services Older People 19.1%

Younger Adults 12.9%

Police 11.7%

Fire & Rescue 4.3%

Highway Maintenance 2.9%

Environmental, Protective & Cultural Services (EPCS)

District-level EPCS 15.1%

County-level EPCS 9.0%

Concessionary Travel 1.7%

Flood Defence 0.1%

Continuing EA Levies 0.0%

Coast Protection 0.0%

Fixed Costs 0.2%

Capital Financing 7.3%

Total 100.0%

2.5. As part of the analysis, we considered the data that was used to construct each indicator in

the current needs assessment formula. This draws on two key sources of information:

The data definitions and guidance that accompanied the 2013/14 local government

finance settlement;4 and

Papers produced by DCLG for the Needs and Redistribution Technical Working

Group, which provide a full list of indicators, their sources, and the availability of data

for future updates.5

4 DCLG, Calculating the 2013-14 Formula Funding, December 2012 and DCLG, Data Definitions of Indicators for 2013-14 (Parts 1 and 2), December 2012. 5 DCLG, Indicators used in the 2013-14 allocation of the Start-up Funding Assessment, meeting held 4 July 2106, http://www.local.gov.uk/topics/finance-and-business-rates/business-rates/business-rates-retention-minutes-agendas-and-papers



2.6. Each indicator has been assigned to one of four categories, corresponding to how easily

the data can be updated.6 The categories used in this report are described in the table

below. It should be emphasised the categories used in this report are based on LG Futures’

own assessment based on the best available information and do not necessarily reflect the

views of DCLG, nor does the availability of data necessarily mean that DCLG will choose

to update the indicator.

Table 2: Ability to update indicators

Update

Status Description Example(s)

The data can be updated using the

existing source, and the data source

is updated frequently (every one to

two years).

Population projections, which are updated

by ONS every two years.

Pupil numbers from the annual School

Census.

The data can be updated using the

existing source; however the data

source is only updated periodically

(e.g. decennial census).

Replacing data from the 2001 census with

data from the 2011 census.

The data could be updated, but this

would involve a cost, in terms of

financial expenditure and/or the time

required to produce new estimates.

Updating local authority estimates of

foreign and domestic visitor nights requires

the purchase of data.

The data source is no longer

available, or previous attempts to

update the indicator were rejected

by local government.

The partial roll-out of Universal Credit

means benefit numbers are no longer

directly comparable across local

authorities.

Previous attempts to update estimates of

day visitors to each local authority were

rejected by local authorities.

2.7. Given the large number of indicators used in the Relative Needs Formula, it would not be

possible to provide a detailed assessment every data source. LG Futures has therefore

sought to simplify and summarise the analysis by creating eight major categories as follows:

Population projections and estimates

Road lengths and geographic data

Income- and employment-related benefits

Socio-economic and demographic data

Disability-related benefits

Additional population measurements

Past expenditure and debt

6 The categories used in this report are different to those used in DCLG’s original paper.



The Area Cost Adjustment

2.8. The remainder of this section provides commentary on each of these categories, and the

ability to update their constituent indicators as part of any future needs assessment formula.

The table below provides a general summary of each category.

Table 3: Categories used in the current Relative Needs Formula (exc. emergency services)

Broad indicator category General ability to update indicators Status of

indicators

Population projections and

estimates

Can generally be updated using existing data

sources.


Some data can be updated but must be

purchased and/or new estimates must be

produced.

Income- and employment-related

benefits

Cannot be updated using the existing data

source, due to the roll out of Universal Credit.

Socio-economic and demographic

data

Can be updated using data from the 2011

census.

Disability-related benefits Two indicators can be updated using existing

data sources, but one indicator cannot.

Additional population

measurements

Some existing indicators can be updated

using data from the 2011 census; some data

can be updated but must be purchased

and/or new estimates must be produced;

some indicators cannot be updated using the

existing data source.

Past expenditure and debt Can generally be updated using existing data

sources.

Area Cost Adjustment Can generally be updated using existing data

sources.

Population projections and estimates

2.9. Population projections are one of the most important determinants of local authorities’

assessed needs. For each service, assessed needs are typically calculated using a basic

‘client group’, and then a top-up for each client. In most cases, the ‘client group’ is the

projected population for each authority, or the specific age band relevant to the service in

question (for example, residents aged 0 to 17 for Children’s Social Care).

2.10. For most services, this is based on the 2011-based Sub-national Population Projections,

which are produced by the Office for National Statistics (ONS). This is the case for Youth &

Community, Children’s Social Care, Adult Social Services, and district- and county-level

Environmental, Protective and Cultural Services (EPCS). These population projections take

the 2011 Census as their starting point, ‘age on’ the population each year, and then adjust

for estimated births, deaths and net migration (internal and international), based on recent



trends for each local authority. These projections are updated every two years by ONS, with

the latest projections being released in May 2016.

2.11. ONS’ population estimates are similarly based on the most recent census, aged-on by one

year and adjusted for births, deaths and migration, but these are not projected into the

future. Timely population projections and estimates would therefore be available for any

revised needs assessment formula.

2.12. For Local Authority Central Education Functions, the ‘client group’ is the number of pupils

aged 3 to 18 who are resident or attending school in each local authority. This is based on

the School Census, produced by the Department for Education (DfE). This is produced

annually and so is not likely to present challenges for future updates.


2.13. For Highway Maintenance, the ‘client group’ is actually the length of roads in each local

authorities (kilometres), weighted by road type. DCLG reports that this data now needs to

be updated. This is likely to include updates to the way in which road length is measured;

for example, potentially using geographic information systems (GIS) data to define roads

as either rural or urban, rather than using speed limits to distinguish between ‘built-up’ and

‘non built-up’ roads as is currently the case.

2.14. Geographic data includes the days with snow laying and predicted gritting days. These are

also used in the Highway Maintenance formula. This is generally based on averages

between 1978 and 1990 (for snow) and between 1992 and 2002 (for gritting), where this

data was available. DCLG is of the view that this data now needs updating as weather

patterns have changed. This data would need to be purchased from the Met Office.

Income- and employment-related benefits

2.15. Benefit data is used extensively throughout the current needs assessment formula as a

proxy for deprivation. This is based on means-tested benefits, for which eligibility is based

on individuals’ (or households’) income or employment status.

2.16. A major challenge when updating the needs assessment formula will be to find a

replacement for benefit data. This is complicated by the ongoing roll-out of Universal Credit,

which replaces a number of means-tested benefits. This includes income-based

Jobseekers Allowance and Income Support, based on data from the Department of Work

and Pensions (DWP), and Child Tax Credit, based on data from HM Revenue & Customs

(HMRC), which are used in the current Relative Needs Formula.

2.17. These benefits are used in the needs assessment formulae for the following services:

Children’s Services – Youth and Community

Children’s Services – LA Central Education Functions

Children’s Services – Children’s Social Care



Social Services for Older Adults

Social Services for Younger Adults

District-level EPCS

County-level EPCS

2.18. Universal Credit was introduced to pilot areas in October 2013 for single claimants, and,

since 2016, has been expanded to Job Centres in all areas of the country and begun to

include all claimant types. However, existing claimants remain on the old benefits and tax

credits, and the migration of these ‘legacy’ claims to Universal Credit is not expected to start

until July 2019.7 DCLG has stated that ‘until all of the country is receiving universal credit it

will not be possible to use this data to calculate needs’, but also noted that ‘ONS and DWP

are working to provide statistics on claimant count that are comparable across areas.’8

2.19. ONS have now developed a new ‘claimant count’ which measures the proportion of the

population (ages 16 to 64) claiming benefits principally for the reason of being unemployed,

whether through Universal Credit or the older Jobseeker’s Allowance.9 However, this

claimant count will still be affected by the roll-out status of Universal Credit in each local

area, meaning the proportion of residents counted as unemployed is not measured on an

entirely like-for-like basis.

2.20. In the absence of an alternative comparable data source, benefit data would need to be

taken from 2013 or earlier to avoid the issues associated with Universal Credit. This could

lead to local authorities challenging the timeliness of the data.

Socio-economic and demographic data

2.21. A wide range of socio-economic and demographic data are used in the needs assessment

formula. The main source of this data is the 2001 census. This includes data used to

calculate population density and sparsity, as well as demographic and socio-economic

variables, such as ethnicity; country of birth; qualifications; occupation; employment history;

household composition; living arrangements; housing tenure; and commuter numbers.

2.22. The current Relative Needs Formula was calculated after the 2011 census was conducted.

This enabled DCLG to use population projections which took this most recent census as

7 Written Parliamentary Statement on Welfare Reform, 20 July 2016

(http://www.parliament.uk/business/publications/written-questions-answers-statements/written-

statement/Lords/2016-07-20/HLWS98/)

8 Technical Working Group on Needs & Redistribution, Meeting 4 July 2016 http://www.local.gov.uk/business-

rates

9 See for example the following ONS methodology document: https://www.ons.gov.uk/employmentandlabourmarket/peoplenotinwork/outofworkbenefits/methodologies/revisionstotheclaimantcountfromtheinclusionoffulluniversalcreditserviceclaimants



their starting point. However, there was insufficient time to update the other indicators which

continued to be taken from the 2001 census.

2.23. In future needs assessment formulae, DCLG would be able to use data from the 2011

census. ONS reports that the questions included in the 2011 census are either ‘fully

comparable’ or ‘broadly comparable’ with the 2001 census,10 meaning that it should be

possible to update each indicator. The census data could be further updated in 2021, which

the government intends to be the last census; after that, administrative and survey data

sources will be used to generate the statistics.

2.24. A drawback of the census is that it is only carried out every decade, and so the data in any

future needs assessment formulae would be several years old. Nevertheless, given that the

census collects information on a wide range of variables which are not otherwise captured

by administrative data sources, and enables a statistically-robust comparison between local

authorities, it is likely to remain an indispensable source of data for the next needs

assessment formula.

Disability-related benefits

2.25. Disability-related benefits included in the current needs assessment formula include

Incapacity Benefit and Severe Disablement Allowance (the EPCS formula), Attendance

Allowance (Social Services for Older People formula), and Disability Living Allowance

(Social Services for Younger Adults formula).

2.26. The first of these indicators (Incapacity Benefit and Severe Disablement Allowance) will be

affected by the roll-out of Universal Credit, and so it would not be possible to update this

data in future needs assessment formulae. This remaining two indicators will not be affected

by Universal Credit, and could be updated using existing data sources.

Additional population measurements

2.27. Additional population measurements reflect the additional demand for local services by

people other than usual residents. These include:

Net in-commuters (for the EPCS and Highway Maintenance formulae);

Domestic and foreign visitors staying the night in a local authority (Highway

Maintenance formula); and

Day visitors (EPCS formulae).

10 Office for National Statistics, 2011-2001 Census in England and Wales Questionnaire Comparability, December 2012.



2.28. Net in-commuters are based on census data, and so could be updated to reflect the results

of the 2011 census.

2.29. The number of domestic and foreign overnight visitors are based on fairly recent survey

data (2008-2010 and 2009-11 respectively), but are not available at the shire district level.

Numbers were apportioned to the shire districts using older data, from as far back as 2002

and 1991 (for domestic and foreign visitors, respectively). Given the age of this data, this

will need to be updated, presumably requiring DCLG to produce modelled estimates for

some local authorities. DCLG report that some of this data was previously purchased from

the UK Tourism Board.

2.30. DCLG report that there is no consistent reliable source of data on the number of day visitors

to and from each local authority. As a result, the figures had to be estimated using a model,

which now includes data that is over 25 years old. Given the age of this data, it is highly

likely that visitor patterns have changed over time and now differ significantly from those

estimated by the model. DCLG reports that proposals for updating the indicator were set

out in 2005 and 2007, but the results were not widely accepted as reliable or were otherwise

rejected by local government.

Past expenditure and debt

2.31. Past expenditure is used in the needs assessment formula for a number of minor services,

including Flood Defence, Continuing Environmental Agency Levies and Coast Protection.

2.32. These appear to be inconsistent with DCLG’s principles that the indicators should not be

subject to manipulation by local authorities or perverse incentives, as, in theory, additional

expenditure by local authorities could result in greater funding. However some of this past

expenditure is based on levies, which may be beyond the control of local authorities to

influence. The control totals for these needs assessment formulae account for a very small

share of England authorities’ overall needs, so any financial incentives to manipulate

expenditure could be regarded as trivial.

2.33. For the Capital Financing formula, assessed needs is based on an estimated amount of

outstanding debt, which is used to calculate (i) an assumed rate of interest payments and

(ii) assumed capital repayments. Because this is based on historical debt, and the assumed

interest rates and capital repayments are the same for each local authority, this is not

subject to manipulation or perverse incentives. Being based on historical data, this would

not necessarily need to be updated as part of any future needs assessment formula.

Area Cost Adjustment (ACA)

2.34. The ACA measures the different costs of providing local services in different geographical

areas to due to variations in wage and salary costs (and, to a lesser extent, differences in

business rates paid on local authority premises). The labour cost element of the ACA draws

on wage data from the Annual Survey of Hours and Earnings (ASHE), a 1% sample of all



employees in employment.11 Regression analysis was carried out to measure the average

difference in wages between geographic areas while controlling for age, gender, occupation

and industry.

2.35. The Area Cost Adjustment is not calculated for every local authority, but rather for 53 larger

geographical areas in England and Wales. Because wage data is drawn from a sample, the

results would not be statistically robust if they were calculated at the local authority level –

at this level, differences could be due to chance, rather than meaningful differences in

labour costs. To minimise the risk of these statistical errors, the ACA was therefore

calculated a broader geographical level.

2.36. Because the ACA is based largely on the annual ASHE data set, it is likely that this indicator

could be updated in future years should DCLG choose to do so.

2.37. The ACA has attracted significant debate in the past.12 Some of the issues debated include

the following:

The ACA geography in which each local authority is grouped (for example, with some

London boroughs in the Outer London geography arguing that they should be in the

Inner London grouping);

The level of spatial disaggregation at which the ACA is calculated;

Whether the ASHE is an appropriate data source, given that it does not have

information on workers’ qualifications; and

Whether the differences in wages measured by the ACA, based on both private and

public sector income data, overstates the difference in authorities’ labour costs given

the existence of national pay scales.

2.38. A full review of the ACA was carried out by DCLG between 2008 and 2010. Nevertheless,

the ACA is likely to continue to be highly contentious, given the major impact it has on

funding allocations across England. For example, for social services, the ACA increased

the assessed needs of some Inner London authorities by 19.7% relative to authorities in

parts of England with the lowest wage costs.

2.39. The following tables provide a list of the indicators used for each service’s Relative Needs

Formula (excluding Police and Fire & Rescue).

11 DCLG, Methodology Guide for the Area Cost Adjustment 2013/14. 12 See for example NERA Economic Consulting¸ Area Cost Adjustment: A Response to the DCLG’s recent consultations, January 2010 http://www.nera.com/content/dam/nera/publications/archive1/PUB_ACA_Jan2010.pdf



Table 4: Children’s Services – Youth & Community

Indicator Source(s) Date of data Update

Status

Projected population aged 13-19 in

2013

ONS: Sub-national Population

Projections 2011

Children in out-of-work families

receiving Child Tax Credit, above a

threshold

HMRC 2008 - 2011

ONS: Mid-Year Population

Estimates 2011

Secondary pupils in low-achieving

ethnic groups, above a threshold DfE: School Census 2012

Table 5: Children’s Services – Local Authority Central Education Functions


Status

Pupils aged 3-18 (including resident

pupils)

DfE: School Census 2012

DfE: Pupil Referral Unit Census 2012

DfE: Alternative Provision Census 2012

DfE: Early Years Census 2012


receiving Child Tax Credit, above a

threshold

HMRC 2008 - 2011

ONS: Mid-year Population Estimates 2011

Population sparsity, at the ward level ONS: 2001 Census 2001



Table 6: Children’s Services – Children’s Social Care


Status


2013


Projections 2011

People aged 18-64 receiving certain

income and employment related

benefits

DWP: Work and Pensions

Longitudinal Study (WPLS) 2009 - 2012

DWP: DWP Computer System 2009 - 2011

ONS: Mid-Year Population Estimates 2011


receiving Child Tax Credit

HMRC 2008 - 2011

ONS: Mid-year Population Estimates 2011

Children without good health ONS: 2001 Census 2001

Children in black ethnic groups ONS: 2001 Census 2001

People in mixed ethnic groups ONS: 2001 Census 2001

People in other ethnic groups ONS: 2001 Census 2001

People aged 16 to 74 whose highest

qualification attained was level 1 or 2 ONS: 2001 Census 2001

People aged 16 to 74 whose highest

qualification attained was level 4 or 5 ONS: 2001 Census 2001

Females aged 16-74 looking after

home and/or family ONS: 2001 Census 2001



Table 7: Social Services for Older People


Status

Projected household and supported

residents aged 65 and over in 2013


Projections 2011

ONS: Mid-Year Population Estimates 2011 ONS: 2001 Census 2001

NHS: Adult Social Care Combined

Activity Return (ASC-CAR) 2011

The ratio of older residents aged 90+


ONS: 2001 Census 2001

NHS: Adult Social Care Combined

Activity Return (ASC-CAR) 2011

Older adults receiving Attendance

Allowance



Older adults living in rented

accommodation ONS: 2001 Census 2001

Older adults living alone ONS: 2001 Census 2001

Population sparsity among older

residents ONS: 2001 Census 2001

Older adults receiving certain income

and employment related benefits





Table 8: Social Services for Younger Adults


Status


2013


Projections 2011

Adults aged 18-64 who work in

routine or semi-routine occupations ONS: 2001 Census 2001

Households with no family ONS: 2001 Census 2001

Adults aged 18-64 who are long-term

unemployed or have never worked ONS: 2001 Census 2001

Adults aged 18-64 receiving

Disability Living Allowance






Table 9: Highway Maintenance


Status

Weighted road length DfT: Road network database 2012

DfT: R199b form 2012

Traffic Flow, all motor vehicles DfT: Information provided by private

contractors and Highway Authorities

on behalf of DfT

2009 - 2011 Traffic Flow, heavy goods vehicles,

buses and coaches

Domestic visitor nights(a) VisitBritain: UK Tourism Survey 2002 - 2010

ONS: Index of place names 2002 - 2004

Foreign visitor nights(a)

ONS: International Passenger

Survey 2009 - 2011


Net in-commuters(a) ONS: 2001 Census 2001

Resident population(a) ONS: Mid-Year Population Estimates 2011

Days with snow lying Meteorological Office 1978 - 1990

Predicted gritting days Meteorological Office 1992 - 2002

(a) In the final formula, these four indicators are used to construct the indicator ‘daytime visitors per

kilometre’.



Table 10: Environmental, Protective and Cultural Services (district- and county-level)


Status

Projected population in 2013 ONS: Sub-national Population

Projections 2011

Population sparsity ONS: 2001 Census 2001

Population density



County of birth of residents ONS: 2001 Census 2001

Day visitors

Leisure Day Visits Survey 1988 - 1989


National Tourist Boards: 1991

Survey of Visits to Tourist Attractions 1991

ONS: 1991 Census of Employment 1991

Other information about urban areas,

National Parks, areas of outstanding

national beauty and official bathing

beaches

Not specified

Net in-commuters ONS: 2001 Census 2001

Older adults receiving certain income

and employment related benefits(a)




People receiving certain income and

employment related benefits




Incapacity Benefit and Severe

Disablement Allowance



Unemployment related benefit

claimants

ONS: National Online Manpower

Information System (NOMIS) 2012

(a) This indicator is included in the district-level EPCS formula but not the county-level EPCS formula.



Table 11: Other EPCS services


Status

Concessionary Travel

Modelled boardings

ONS: Mid-Year Population Estimates 2009 - 2010

ONS: Rural / urban status Not specified

ONS: Annual Population Survey 2010-2011

DfT: Public Service Vehicle Operator

Survey 2010-2011

DfT: Light rail operators survey

DfT: National Public Transport Data

Repository 2009-2010

DfT: Vehicle registration statistics

based on DVLA data 2010

Flood Defence

Internal drainage board (IDB) levies

expenditure

DEFRA: Annual Reports of Internal

Drainage Boards 2012-13

Ordinary watercourses not covered

by internal drainage board Environment Agency Not specified

Continuing EA Levies

Environment agency (England) levy DEFRA 2012-13

Coast Protection

Coast protection expenditure DCLG: General Fund Revenue

Accounts Returns 2008-2011

Capital Financing

Interest rate

PWLB

2012 Bank of England

CIPFA

Assumed outstanding debt

Outstanding debt as at 1 April 1990 1990

Credit approvals 1990 to 2004 1990-2004

Supported Capital Expenditure

(Revenue) 2004-2011

Assumed capital repayments N/A



Table 12: Area Cost Adjustment


Status

ACA for (i) Education, (ii) Children’s

Social Care and Younger Adults’

Personal Social Services, (iii) Older

People’s Personal Social Services,

(iv) Highway Maintenance, and (v)

Environmental, Protective and

Cultural Services.

ONS: Annual Survey of Hours and

Earnings 2009-2011

ONS: Annual Business Inquiry Part 2 2007

DBIS: Small and Medium Enterprise

(SME) statistics 2008

DCLG: Subjective Analysis Return 2005-2008

DCLG: Trading Services Revenue

accounts 2005-08

DCLG: Revenue Outturn forms 2007-08

Base Estimate Returns 1992-93

VOA: Business Floorspace 2012

VOA: Revaluation of Local Authority

Schools 2010

DCLG: National Non-Domestic

Rates Provisional Contributions

Return

2010-11

NHS: Council Personal Social

Services Gross Expenditures PSS

EX1

2008

Publicly available company accounts Not specified




3. Possible Additional Indicators

3.1. DCLG has published a long-list of ‘cost drivers’ for local services, which could potentially

be used as indicators in future needs assessment formulae.13 The long list is based on

papers discussed by the Needs and Redistribution Working Group and put forward by other

government departments. It is DCLG’s intention that the list should be significantly

shortened, first through an engagement process and then through statistical techniques (to

be determined) which would help identify those cost drivers that are ‘key’.

3.2. The following is a list of additional cost drivers mentioned by DCLG, which are not already

included as indicators in the existing Relative Needs Formula. We only list those cost drivers

that are presented as a measurable indicator, rather than general descriptions such as

‘deprivation’. A definition, rationale and data source was not provided for the cost drivers,

and so it is not possible to comment on their appropriateness for use in a formula. However,

some of the cost drivers appear to be at odds with DCLG’s criteria that indicators should

not be subject to manipulation or perverse incentives; for example, the proposal to use

actual client numbers for children’s social care.

3.3. For Adult Social Care, additional indicators included in the long list include:

Number of people aged 85 and over with a limiting (significantly) condition per person

aged 65 and over.

Number of couple households aged 65 and over per household aged 65 and over

Number of home owner households (outright ownership only) aged 65 and over per

household aged 65 and over

Number of properties in Council Tax bands A to E as a proportion of all Council Tax

banded properties

Number of properties in Council Tax bands F to H as a proportion of all Council Tax

banded properties

Number of people ages 16 to 64 whose day-to-day activities are limited a lot per

person aged 16 to 64

Portion of people aged 16 to 64 who are aged 16 to 24

3.4. For Children’s Social Care and Youth Services, additional indicators include:

Service demand measurements, including the number or rate of care applications,

children who are the subject of a child protection plan, care leavers eligible for care

leaver support, and specialist Special Education Needs (SEN) places.

13 DCLG, A long list of possible cost drivers by the Department for Communities and Local Government, Needs & Redistribution Working Group, January 2017.



Radicalisation: the number of children and families which require intensive

intervention and the number of children with complex needs (exact criteria not

specified).

Unaccompanied asylum seeking children.

Awareness: differing prevalence of awareness raising campaigns on child abuse and

neglect.

Number of young people not in education, employment or training.

Number of young people up to 25 with disabilities.

3.5. For Highway Maintenance, only one additional indicator is included in the long list, namely

the cost of oil.

3.6. Homelessness does not currently have its own Relative Needs Formula, but suggested

cost drivers are:

Number of local authority acceptances.

Cases of prevention / relief achieved by securing a private rented sector tenancy.

Differing rental costs across the country.

Additional cost of housing larger families in some areas.

High numbers of historic temporary accommodation in some areas.

3.7. Waste and Recycling also does not currently have its own Relative Needs Formula, but

long-listed cost drivers include:

Number of households.

Deprivation: Percent of population as social grade D and E; deprivation deciles from

the Indices of Multiple Deprivation.

Number of high rise blocks of flats.

Demand for municipal and civic amenity waste collection.

Varying capability for cost recovery.

Extent of service integration across local authorities.

3.8. For Cultural Services, an additional cost driver is the ‘local supply of cultural assets and

facilities’.

3.9. DCLG’s paper also mentions the fact that benefit data might not be sufficiently robust in

future formulae, given the introduction of Universal Credit. They state that another way to

reflect deprivation would be to use the Index of Multiple Deprivation. This measures seven

aspects of deprivation, namely: income; employment; health and disability; education, skills

and training; barriers to housing and services; crime; and living environment.



4. Conclusions

4.1. DCLG has established a clear set of criteria for assessing the appropriateness of indicators

that could be included in the needs assessment formula. This rules out data that can be

influenced or manipulated by local authorities or creates perverse incentives, and ensures

that the indicators are statistically robust, comparable across local authorities, and are

relevant measurements of authorities’ ‘need to spend’ on services.

4.2. The main challenge facing DCLG is likely to be the timeliness of data, most notably the

need to update measures of ‘deprivation’ which at present are largely based on benefit and

tax credit data. Assuming these indicators continue to be used in future needs assessment

formula, it is possible that this will need to be based on older benefit data that precedes the

roll-out of Universal Credit.

4.3. Potentially, a large number of indicators meet DCLG’s criteria and could serve as

candidates for the revised needs assessment formula. A more controversial issue is likely

to be selection of indicators for use in the final formula. At present, indicators are included

in the formula (and assigned relative importance) using either judgement or statistical

techniques.

4.4. Either approach is likely to be controversial, given that the choice of one indicator over

another creates ‘winners’ and ‘losers’ among local authorities, given their varying

characteristics (such as population density, deprivation levels, age profiles, and so on). The

method that will be used to select indicators for the final formula is currently being

considered as part of DCLG’s Fair Funding Review.

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