The concentration of charities focused on local need in UK cities is limited both by the level and distribution of local incomes.
The geography of charitable activity in the UK reflects local ability to give, not local need. This was a key finding of Donation nation: The geography of charitable giving in the UK. In the very areas that need charity the most, low incomes mean not only fewer donations but also fewer charitable organisations focused on local need.
But it is not just low income levels that reduce the number of these charities in UK cities. This blog looks at how the nature of local inequality – the local distribution of income – may also be a limiting factor.
There are two ways in which inequality might impact the number of local charities for local causes. The first is the size of the gap between the most and least deprived neighbourhoods: a large gap may support the existence of more local charities as differences in deprivation levels would be more apparent to local residents, encouraging donations.
The second is how local deprivation is clustered across space. For instance, if the richest and poorest tend to cluster in different parts of the city, charitable activity directed locally may be reduced as richer neighbourhoods (i.e., those most able to donate) would be less aware of local deprivation and so less inclined to support local causes. The theory is physical distance equates to ‘social distance’, reducing interactions between residents of different incomes, limiting richer residents’ pro-social behaviour.
Running a regression (technical details at the end) estimates the role of an urban area’s income deprivation in terms of i) level; ii) gap; and iii) clustering on local needs-focused charity density, helping to disentangle the effect of each. This is what is finds.
First, an increase in the level of local income deprivation is associated with a decrease in the density of local needs-focused charities even when accounting for how it is distributed. As an example, if Middlesbrough saw its income deprivation rate (currently 16 per cent) fall by five percentage points (with inequality remaining the same), the model predicts there would be seven more charities focused on local economic need in the city.
Second, the effect of the income deprivation gap is inconclusive. There is no evidence to suggest that the size of the gulf between the poorest and richest neighbourhoods within UK cities impacts the presence of local charities tackling local need.
Third, an increase in the clustering of income deprivation is associated with a decrease in the charity density measure. The following charts set this out more clearly, using Leeds as an example.
These are not causal relationships. But it illustrates that there are fewer local needs-focused charities in more deprived areas even when accounting for the size and spatial distribution of local inequality. And it is cities with the highest deprivation clustering that have lowest charity density, supporting the ‘social distance’ theory – how unequal places are does not seem to factor in to the concentration of these charities.
This is important context when thinking about how charity could play a larger role in levelling up the country.
Slow economic growth impacts incomes which are the greatest restriction on broad-based giving. And local charities are the other side of the coin – they are only able to operate through being supported by a steady flow of donations.
So to sustain voluntary organisations dedicated to meeting local economic need in the long term, national government must get the economies of left-behind cities firing again – Cities Outlook 2024 sets out the national steps to achieve local economic growth over the next decade.
But the number of charities dedicated to local causes would still be limited by the spatial clustering of income levels. Even with rising incomes, this social distance would remain a barrier.
For local authorities in high need areas, local charitable funds could be a way forward. These would divert donations to local charities under the umbrella of a wider cause, channelling local giving toward local need. And crucially, a fund would operate at a city-wide level (e.g., across a Combined Authority), overcoming the impact of neighbourhood-level income clustering that may prevent the formation of individual local charities. The broad fund would then help build capacity for local charities on the ground, helping donations to target need in the cities that need them most.
Results from estimation of relationship between the level and distribution of income deprivation, and the number of local needs-focused charities per head in urban local authorities
Outcome: Local needs-focused charity density | (1) | (2) | (3) |
---|---|---|---|
Income deprivation rate | -0.49*** | -0.46*** | -0.46*** |
(0.06) | (0.10) | (0.12) | |
Income deprivation gap | 0.21 | 0.31 | |
(0.21) | (0.24) | ||
Income deprivation clustering | -0.93 | -0.76* | |
(0.74) | (0.38) | ||
Additional LA characteristic controls | No | No | Yes |
Observations | 140 | 140 | 140 |
R-squared | 0.19 | 0.23 | 0.42 |
Source: ONS 2019; NCVO 2023. Notes: Unit of observation are local authorities (LAs) within Primary Urban Areas (PUAs) in England and Wales. Northampton omitted due to boundary changes. Model estimated by Ordinary Least Squares (OLS) regression. Income deprivation gap is measured as the percentage point difference in the income deprivation rate between the most and least deprived Lower Super Output Areas (LSOAs) within each LA. Income deprivation clustering is measured by Moran’s I, a measure of spatial correlation between the income deprivation rates of LSOAs within each LA. Column 3 takes Column 2 and additionally controls for LA population, whether the LA contains the city centre, and whether the LA is in the Greater South East. All headline results are based on Column 3. Natural logarithms are used for all variables (apart from binary variables). Standard errors reported in parentheses and are clustered at the PUA level to account for spatial correlation in deprivation between local authorities within the same PUA. *** p<0.01, ** p<0.05, * p<0.1.
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