Findings: Accessibility and guidance
Poverty is most helpfully viewed as a basket of measures
Defining ‘poverty’, even solely in terms of income, is no easy feat. By its very nature, poverty means different things to different people, and there is no universal consensus on how it should be defined. Users we spoke to often referred to a so-called ‘basket of measures’ on income-based poverty. The most widely used measures in this ‘basket’ are drawn from the Department for Work and Pensions’ (DWP) Households Below Average Income (HBAI) statistics and include relative and absolute measures of poverty, calculated both before and after housing costs. Users told us that it is helpful to have different metrics which highlight different aspects of poverty, and which serve different purposes.
We found that user needs in the poverty space are multi-faceted. These range from policymaking and service provision to lobbying and campaigning, and encompass a broad range of specialist interests and priorities. In order to meet these needs, we consider having a variety of measures is most beneficial to users.
The Social Metrics Commission (SMC) advocates for a singular ‘headline’ measure of poverty, to prevent the perceived ‘cherry-picking’ of statistics in public debate and to create consensus across parties as to how progress on poverty should be measured. Whilst a single measure would prevent the selective use of statistics, focusing on one measure risks masking the many nuances about the nature of poverty in the UK. Users told us that it would not be feasible to try to attach income-based poverty to one headline measure and could also create barriers to holding government to account on poverty. Given this, we consider that one measure could not adequately meet all the multi-faceted and differing needs that users have for poverty statistics.
Signposting between existing statistics on income-based poverty could be improved
Whilst users prefer having a ‘basket’ of the main measures on income-based poverty over one headline indicator, we found that the current landscape of poverty statistics is difficult for many to navigate. Some users we spoke to were unaware of statistics that they would find useful for the purposes of their work, for example, that the Office for National Statistics (ONS) publishes its own household income statistics which are sourced from different data to the Family Resources Survey (FRS).
Some signposting between the different statistics on income-based poverty does already exist to an extent, and we are pleased that DWP has introduced clearer links to other publications in the latest FRS publication. We consider, however, that there is still scope for this signposting to be improved, as even experienced users we spoke to were unaware of some relevant statistics.
To meet this need, a central landing page or guide to sources which outlines the various income-based statistics on poverty and the different purposes they serve, would be helpful. This guide should set out the main measures of poverty, represented by the HBAI statistics, whilst also acknowledging other publications that serve more specific purposes – such as those on persistent poverty or in-work poverty. We are aware that this could create a significant additional resource burden for producers and recommend that, in the short-term, producers should look to provide clearer and more detailed signposting to other income-based poverty statistics in their bulletins. The GSS Coherence team in ONS could look to build on the guide to sources of data on income and earnings that was developed in response to our 2015 systemic review of the Coherence and Accessibility of Official Statistics on Income and Earnings.
The current guidance accompanying income-based poverty statistics is largely tailored to a more expert audience. Whilst experienced users and researchers told us that the guidance is thorough, we consider that a reasonable member of the public could not easily find what the statistics cover, the underlying assumptions and limitations and appropriate uses.
As an example, there is confusion among users as to how ONS’s Household Income Inequality statistics differ from those published by DWP. These are two different sources of information on household income within a similar timeframe and now a similar sample size. Whilst guidance covering the differences is available, it is difficult for users to access and understand what statistics should be used and when.
Producers should ensure supporting guidance is accessible to lay users and clear on the appropriate uses and quality of the statistics. Producers could look to the Welsh Index of Multiple Deprivation as an example of best practice – where a simplified guidance note is supplied for the more general user, alongside detailed methodology notes for analytical users.
If guidance accompanying the statistics gives clear judgements on the fitness for purpose of different poverty measures in different contexts, this could help mitigate the risk of selective use of poverty statistics in public debate.
The language and terminology of the statistics could be clearer
The accessibility of language used in statistical bulletins and supporting guidance for income statistics could also be enhanced to support users’ understanding. The HBAI statistics produced by DWP are widely regarded as the leading indicators on income-based poverty, despite there being no explicit reference to the word ‘poverty’ anywhere in the statistics bulletin or supporting guidance. We recognise that HBAI reports on low-income which is a quantifiable measure, rather than a subjective concept such as poverty. As one of the primary uses of the statistics is to describe poverty, it would be helpful if the guidance accompanying the HBAI bulletin made the uses of the data clearer. This would help users to reconcile public statements on poverty with the HBAI data.
The HBAI statistics report on both absolute and relative low-income, with relative low-income referring to household income below 60% of the median and absolute low-income meaning income below 60% of the 2010/11 median, adjusted for inflation. We found that the word-choice of ‘absolute’ can be easily misinterpreted as referring to people in the most abject or extreme levels of poverty, rather than ‘absolute’ in the quantitative sense. Users suggested that alternative terminology such as ‘anchored’ low-income might be more helpful and avoid issues of misinterpretation.
Many of the income-based poverty statistics cover households. However, there are a number which refer to families instead. This can result in statistics and terms being used interchangeably when they actually describe different concepts. A family (or benefit unit) is a single adult or a couple living as married and any dependent children, whereas a household can consist of one of more families who may not necessarily be related. Some users we spoke to also shared concerns around the impact of the changing state pension age on the way pensioners are counted and reported, and how this then creates confusion when comparing with statistics which report the number of retired individuals rather than pensioners.
There can also be confusion around the distinction between poverty and deprivation. Although the differences between the two are nuanced, they ultimately refer to different things. Poverty statistics, as we have set out in the introduction to this report, are focused on a lack of income. Deprivation statistics aim to capture a broader lack of resources and access to services, in which a lack of income forms just one part of deprivation. This is not always made clear for users, which leads to the terms being used synonymously and incorrectly. This is a particular concern when it comes to regional breakdowns of data, as the lack of sub-regional breakdowns of data on low-income can lead to users relying on the indices of multiple deprivation (which disaggregate to local area level) as an alternative.
We recommend that statistics producers consider the helpfulness of the language used in the poverty bulletins and accompanying guidance, to ensure that it does not risk confusing or misleading less-experienced users.
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