Using Census data to derive a new area-based measure of deprivation - Section 7: Discussion

Section 7: Discussion and concluding remarks

Our aim in this paper was to firstly outline the creation of a new area-based measure of deprivation using Census 2011. Having done so, we then assessed its correlation with income and the extent to which it differs to the Indices of Deprivation. Overall, the findings provide evidence in favour of our measure being related to low income and also offering added value to users of deprivation statistics through overcoming some of the known limitations of the Indices of Deprivation. Furthermore, given it is UK-wide, our measure can also enable comparable statistics to be developed across nations – a mark of quality as highlighted in the UK Code of Practice for Statistics.

In all nations, our measure captures a greater proportion of rural areas in the bottom quintile when compared with a multiple deprivation index. However, this is particularly the case in Scotland, where all council areas emerge in this quintile. As highlighted earlier, this is not the case for SIMD, where some known areas of deprivation are not found in the bottom quintile. For England, the lowest quintile of the variable we have created also has the advantage (over the same quintile of IMD) of picking up medium/large towns in northern and central England experiencing deprivation. As in Scotland, the bottom quintile of our measure covers all local authorities/LGDs in Wales and Northern Ireland, respectively. In Wales, one of the key differences between our measure and the bottom quintile of WIMD is the greater ability of our variable to catch deprivation across two local authorities in the south. Meanwhile, for Northern Ireland, the benefit of our measure relative to NIMDM (based on our assessment of the lowest quintile) appears to lie in picking up parts of the north and/or east of the country.

It is perhaps useful at this point to illustrate how this measure could be applied in practice and we shall do this by taking the example of the higher education sector. Across all nations of the UK, one of the objectives of education policy at all levels is to ensure equal opportunity for all. Providers of higher education are therefore expected to conduct ‘outreach’, which are activities that are designed to raise aspiration and attainment within disadvantaged communities. Programmes may be designed through collaboration with schools and colleges or may involve disadvantaged students applying directly to providers to take part in events such as summer schools. To ensure these opportunities reach those from low socioeconomic backgrounds, providers often set one of their eligibility criteria to be that the individual should be from an area that falls into the bottom quintile of the country’s multiple deprivation index. However, as noted earlier in this paper, not all those living in deprived circumstances are captured in the lowest quintile of the index, which may result in disadvantaged students missing out on participating in such activities. However, the inclusion of our measure as one of the conditions for admittance onto a programme could help resolve this, given it is able to capture deprived areas in the lowest quintile that a multiple deprivation index is not able to. Furthermore, in their review of statistics in the post-16 education and skill sector within England, the Office for Statistics Regulation (OSR, 2019) noted the lack of a UK-wide deprivation metric was inhibiting the potential to publish country-level analysis, as well as assessing the progress being made on improving social mobility within society. Our measure will also help to resolve this concern, given its UK-wide applicability.

Although taking part in the Census is obligatory, it should be acknowledged that the data is still self-reported and could therefore be subject to measurement error, as individuals may be unwilling or unable to give an accurate response to questions on their qualifications and occupation. Indeed, the ONS (2014) completed a Census Quality Survey between May and August 2011, in which volunteers were requested to participate in a face-to-face interview. Those who agreed were asked the same questions that they responded to approximately two to five months earlier, with the key difference being the mode of survey completion. Agreement rates were generally found to be lower (around two-thirds) for the questions on occupation and education, which tended to be for reasons such as respondents giving different job titles or struggling to recall the qualifications they had attained. Additionally, in this paper, our evaluation of the degree to which our measure is correlated with income relies upon estimates at a relatively aggregated level of geography. We recognise that within such areas, there is likely to be variation in the incomes of households. In the case of Northern Ireland, we had no relevant data that we could draw upon.

Our future lines of work will therefore be as follows. Firstly, the 2021 Census has now been administered across all nations of the UK. Once this data is released into the public domain, we will be able to produce an updated version of the measure we have presented here. Furthermore, we shall be exploring the feasibility to obtain access to income information held by government-owned organisations at the household level, which we can subsequently link to our Census 2021 data. This will enable us to carry out a further evaluation of how our measure relates to income and will bring the added benefit that we know that the validated income records will not be subject to the same level of concern around measurement error as is the case with self-reported data.

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