Local Area Knowledge
Local knowledge has it's place in terms of establishing local
poverty. However, it carries considerable limitations and should be
used to enhance more robust data rather than as a main data source.
Adding qualitative information about peoples' personal experiences
can make a powerful case when dealing with anti
face value, this approach would appear to be less time-consuming
than research-based alternatives, as it draws upon
upon existing knowledge could appear to be more cost-effective than
research-based alternatives, as there is no need to cover
additional research costs.
Credibility. As this approach represents the
common understanding (perception) of local poverty, it is likely to
be viewed locally as an accurate description.
·Reliability of local
knowledge when places are constantly changing.
Local knowledge is most robust when local poverty is less
changeable. Changes in population, area regeneration or local
economy may impact on the distribution and nature of local poverty
and therefore local knowledge.
·Precision of Poverty
Knowledge. Local knowledge is qualitative
information. It does not provide detailed estimates or comparisons
to assist with policy decisions.
The accuracy of information based on personal experience or third
party knowledge is hard to examine or confirm.
Comparability. The knowledge of local community
members and practitioners may only cover a certain area or
population group in detail. Therefore knowledge may be 'patchy' and
lack robust comparison.
Using local knowledge to define poverty may create
practical challenges for a robust
Cost. There would be resource
requirements (time and cost) in collecting and presenting local
opinion in a form that could be used in local policy-making.
Local Area Modelling
Local area modelling is a useful contribution to local poverty
measurement and understanding for large organisations with the
capacity to undertake advanced statistical analysis. In particular,
a comprehensive poverty analysis may find value in comparing
projected local poverty rates (estimated through local area
modelling) with actual local poverty rates. This may provide
insight into the nature of the drivers of local poverty.
data on poverty 'risk rates'. UK data on the
risk of poverty by population groups is published on an annual
basis. More limited Scottish data on the risk of poverty by age
group is also published on an annual basis.
comparisons. Using risk rate data to estimate local
poverty allows local and national comparison. It may also allow
comparisons between local areas e.g. comparing local poverty in the
electoral wards of Dundee and Glasgow.
comparisons. Local modelling could be applied to all
localities within an area, allowing for systematic comparison e.g.
comparing local poverty in all datazones in
analysis. Annually updated figures allow for trends
to be established.
·Availability of technical
expertise. Not all local organisations will have the
technical expertise or resources to undertake local
·Availability of local
population data. The ability to undertake local area
modelling depends on the availability of accurate local population
data. The National Census can provide this information.
However, the accuracy will decrease over the ten year period
·Availability of information
on local drivers of poverty. The theory of modelling
assumes that certain factors will have the same impact where ever
they are. The local drivers of poverty may imply that the
population at risk of poverty in a locality does not reflect that
for Scotland or the UK as a whole.
Accuracy of model for smaller geographical
areas. Local area models may be less robust for
smaller geographical areas as less local population data are
available compared to large geographical areas.
Material deprivation is a non income based measure which
captures the wider impact of living in poverty. The key measure of
material deprivation is "would like, but cannot afford", as opposed
to "do not have". Material deprivation can be used in bespoke
local analyses of poverty. However, it can be fairly demanding in
terms of data collection and processing, In particular, it is
possible to replicate the indicators used to measure child poverty
in the UK to allow a direct comparison of local and national
poverty. The results of the UK Government's annual
material deprivation analysis is reported in Households Below
Average Income survey.There are specific measures for child
material deprivation and pensioner material deprivation
·Established Methodology. Considerable
body of research-based evidence exists to advise researchers of
appropriate indicators to use.
·National Comparability. Material
deprivation indicators are available at the
·Comparable within Scotland. Information
on some aspects of deprivation is readily available for Scottish
·Useful for Population Surveys. Can be
easily incorporated into local population surveys
·Common sense. Common-sense understanding
suggests that areas of local poverty are likely to comprise
populations who are materially deprived.
· Time and cost. In general, there is a
need to incorporate a suite of indicators to adequately measure
deprivation. This can be demanding in terms of time (and cost) if
incorporating into a local population survey.
· Limited usefulness of indicator sets across the
population. Different indicator sets are most appropriate
for different groups in the population.
· Material bias. Focus on material
deprivation may imply that what matters most to people is their
ability to consume. However, opinion surveys and qualitative
research consistently show that the deprivations that matter most
to people are the 'soft' deprivations surrounding quality
· Skill required in survey administration and
analysis. The most useful material deprivation data
demands careful data collection and analysis, in order to avoid
classifying people as deprived, when they have chosen not to buy
something (but not on the grounds of cost).
· Differing access to goods within the same
household. A household having a material good might
not reflect equal access of all people. For example, parents have
been known to forego material goods to ensure that their children
have greater access to them. Care needs to be taken in
interpreting material deprivation data for households
Profiling local income means finding out the amount of
disposable household income (adding up all of the income from all
household members, after deductions) and comparing this to a
threshold measure of typical income. If household income is
below 60% of typical household income, then that household is
judged to be living in poverty.
Income based measures of poverty are widely accepted as the most
robust measures. However, their lack of availability of income data
at the local level has led to the search for alternative measures
of local poverty. Recent methodological developments are raising
the prospects for utilising local income-based measures
· Comparisons. It allows a direct
comparison of local poverty to national levels of poverty (Scotland
and the UK) using the key measures of poverty in
· Availability for larger Geographical Areas.
The Scottish Government is currently working to develop poverty
estimates for Scottish local authorities . The estimates currently
published on the website are a step toward an estimate that will be
quality assured. At present, these data should be understood to be
'data under development'. Information can be accessed from
commercial companies for smaller geographical areas
· Useful for Small Households.
Processing of household income data into a measure of poverty is
less problematic for smaller households and, in particular, for
households without children.
· Lack of availability for smaller areas.
There is a lack of income data available at local level.
· Cost. There may be an associate cost
of procuring income data estimates for local areas from
· Quality and uncertainty of using estimates.
Commercially provided income data are estimates and not measures
· Quality assurance of survey data. It is
difficult to be assured of the quality of income data collected
from local area surveys, particularly from larger households and
households with more complex earning patterns.
· Access to resources within the
household. As a household based measure of poverty
it assumes everyone has access to an equal share of household
resources and/or benefit equally from them.
· Debt and Disposable Income. Disposable
income is not necessarily an accurate measure of the income that is
actually at the disposal of the household. For example, households
that are servicing debt may find that they have less income to
spend than their disposable income suggests.
Two main approaches can be used to identify clusters of service
users. Service use can be taken as an indication of poverty (for
example, entitlement to free school meals) or lack of access can be
used as an indication of poverty (for example, lack of access to
Service user data may be a readily available source of poverty
information, particularly for the organisation that is providing
the service. However, it is likely to be less robust than
income-based indicators and care must be taken when assessing
whether data should be used as a poverty indicator.
Service use data tend to be used within measures of multiple
deprivation, although where the services that are being accessed
are those which largely service people experiencing poverty there
is the potential to use this information as an indicator of local
poverty in its own right.
· Useful for Population Surveys.
Service use indicators can be incorporated easily into local
population surveys (particularly when determining either the
presence or absence of service use).
·Administrative Data. These data may be
collected routinely as part of the
· Easy to compare locally. Where data
are administered across an area, data will be available to compare
across localities within that area.
· Availability. Robust measures of
geographical access to key services are readily available and have
been incorporated in the Scottish Index of
· Calculating travel or geographical
access. Critics of the measure feel that differences
between public and private transport are not adequately accounted
for e.g no account for the frequency of
· Easy to make assumptions. Service
access is not only determined on the basis of where you live. There
can be significant variations in access across populations (for
example, between car owners and non car owners)
· Service Uptake. Not all of those who
are entitled to services (and who would be defined as living in
poverty) would access the services.
· Limitations in target audience. If a
service is targeted at one section of the population e.g. the
unemployed, it may fail to capture poverty among the under-employed
or low paid.
· Broad Base of Service Users. Service
users may extend beyond the population who are living in poverty so
they may be hard to distinguish.
· Limitations to national
comparisons. If eligibility is determined locally, it
is impractical to use service use data to compare poverty more
widely as other areas may have different
As one of the Local Outcome Indicators, fuel poverty is widely
accepted as a particular measure of poverty. The
twin-definition of fuel poverty and extreme fuel poverty is also
helpful as a measure of poverty intensity. It has, however,
tended to be used just as a measure of fuel poverty and not as a
more general indicator of poverty in its own right.
The Scottish Government has set a target to tackle fuel poverty.
The term 'Fuel Poverty' refers to the situation where a household
must spend more than 10% of their disposable income on heating
their home to an adequate level. 'Extreme Fuel Poverty' is defined
as a household having to spend more than 20% of its disposable
income on fuel. Local Outcome Indicator 54 (version 5.1) concerns
fuel poverty. Measuring fuel poverty is demanding in that it
requires information on both income and expenditure. The strengths
and weaknesses below can also be relevant for other measures
· Established Measure. The
national status of fuel poverty means that this is a widely
understood measure of poverty.
· National Comparablity. Scottish
Household Condition Survey data are available for Scottish local
authorities, allowing comparative analysis.
· Useful for Population Surveys. A
simplified measure of fuel poverty could be easily used in local
population surveys, e.g. Do you spend more than 10% of your
disposable income on household fuel?
· Common sense. Common-sense
understanding suggests that areas of local poverty are likely to
comprise populations who are materially deprived.
· Demanding in terms of data
required. Data are required on both income
· Limited focus. Fuel poverty
only concerns one aspect of poverty.
· Local influences on fuel
costs. Local variations in the factors that determine
fuel costs (quality of local housing stock, cost of fuel) will
influence the proportion of income that is expended on fuel. Fuel
poverty data may not be directly equivalent to poverty defined on
the basis of the income that is available to
The ready availability, income-base and regularity of data
series mean that welfare statistics are a valuable means of
estimating local poverty. Particularly valuable is the availability
of such data for smaller geographical areas. Welfare benefits can
be a useful proxy indicator of poverty levels as welfare benefit
populations are known to receive a similar low level of income in
order to qualify. However, changes to welfare entitlement
over time and the transitions involved in the wider Welfare Reform
implies that long term analysis or comparison must be handled with
care and is not as reliable when used in isolation.
· Regular data. Data are updated
monthly, meaning that welfare data are not as dated as other
poverty indicators can be.
· Availability of data. Data are
readily available. A data tabulation tool enables local level
analysis and the production of a user-defined report. Welfare
statistics are also incorporated in wider indices of deprivation
and can be accessed through SIMD and Scottish Neighbourhood
· Easy to measure. The single
straightforward indicator approach to measuring poverty is
relatively easy to apply and comprehend.
· Easy to compare nationally and
regionally. The results would be directly comparable
to national data. It is also likely that the local results in one
area, could be compared to the local results in other areas, e.g.
comparing local poverty in the electoral wards of Fife and
· Easy to compare within a Local
Authority. The results could be applied to all
localities within an area, allowing for systematic comparison
across an area, e.g. comparing local poverty in all datazones
· Changing entitlement to
welfare. Changes to welfare entitlement over time
implies that long term analysis or comparison must be handled
· Welfare Reform. The scale of the
changes to the current Welfare reforms will present a series of
issues. In this transitional period, reliance on welfare data alone
may be inadequate as a means to estimate local levels of poverty.
For example, changes proposed to Housing Benefit may have an impact
on the threshold household income levels that are used to
· Expert knowledge of welfare
system. Although it is planned to simplify the system
in future years, at present there is a need for expert knowledge of
the system in order to understand how benefit entitlement can be
used as a measure of poverty. The DWP have published a user guide
to welfare statistics.
· Inaccurate assumptions. Some
people are missed from the claimant count as they may live below
the income threshold but don't quality or because they do not
claim. Alternatively there are concerns over welfare abuse (claims
made by those who are not entitled to support).
· Working poor. Unless tax
credits are considered, there is a risk that welfare statistics
will not capture the significant proportion of those living in
poverty who are working. Some welfare measures may
underestimate the extent of poverty in areas with a higher level of
in-work poverty, e.g. rural Scotland.
· Population dependent. The use
of individual benefits, or entitlement to all benefits for a
defined age group, means that welfare statistics are often only
relevant to a limited range of the population.
The Scottish Index of Multiple Deprivation (SIMD) ranks the 6505
datazones in Scotland from most to least deprived in terms of
concentration of poverty. The 15% Most Deprived datazones has
become a key threshold that is widely used by local government and
the Third Sector as an estimate of relative need.
SIMD is an excellent resource for Scotland as a means to
identify small pockets of multiple deprivation. Rural local
authorities or local authorities with a mix of urban and rural
areas may choose to analyse datazones outwith the 15% most
deprived, for example to identify the most deprived datazones in
their area or selecting a higher cut-off using
· Familarity. Users and
stakeholders are now familiar with the SIMD.
· Availability. SIMD data are
readily available from both the SIMD home pages and Scottish
· Cost. These data are made
available by the Scottish Government to all users
· Disaggregation and data on Income
Deprivation. The SIMD can be disaggregated into
'domains' e.g. Housing Deprivation, Health Deprivation, etc. In
particular, the Income Deprivation domain has value as a close
proxy of income poverty.
· Time Series Analysis. Although
not all sections are updated annually, the stable methodology,
combined with the updates to the Index, means that time series
analysis is possible. (The Income and Employment domains are
· Comparisons. The national focus
means that the SIMD is very useful for comparison across datazones
(and local authorities).
· Flexible Geographies. The
building block of the datazone means that it would be possible to
use the SIMD to generate a range of area profiles at larger
· Urban / rural. The SIMD is
concerned with areas of concentrated multiple deprivation. Some
rural areas may also experience poverty and deprivation that isn't
as concentrated geographically so tend not to rank as highly within
the scale. However, there is clear guidance and advise on how SIMD
can be best used as a measure for rural areas.
· Not Measuring Poverty. Although
small area multiple deprivation and poverty are related, they are
not interchangeable. Sensitivity is required in using the
SIMD to inform understanding of poverty in Scotland.
· Area based. The SIMD is an area-based
measure; it is not designed to estimate multiple deprivation for
particular population groupings.
· Data Quality. Not all of the data
that is used in the SIMD is of an equivalent standard. In
particular, data for the Housing Domain relies on the National
Census and can therefore become dated a few years after the last
Census has elapsed.