Huw Dixon & Kemar Whyte
In this study, we use the Understanding Society survey (USoc) to measure the volume of volunteering across the UK. We were able to use 5 waves of the survey that included a module of three questions relating to volunteering, namely waves 2 (2010-11), 4 (2012-12), 6 (2014-15), 8 (2016-17), and 10 (2018-19). The USoc has better geographic coverage than its next best alternative, The Community Life Survey (CLS) which is restricted to England only and hence leaves out the three nations of Northen Ireland, Scotland and Wales. Our geographic analysis was done at the NUTS 1 level: namely the 9 regions of England and three nations outside England (making 12 in total). The most recent work on this by the ONS was its 2018 household satellite account which included data on volunteering (along with unpaid housework, childcare etc) using data up to 2016 (based on the predecessor of the CLS, the Citizenship Survey, also exclusively English in coverage).
So, what did we find? Firstly, there is considerable regional variation in volunteering activity. If we average over the 5 waves, we can look at the percentage who volunteer at least once per month (this is called “frequent volunteering”).
We can see that Wales has the lowest proportion volunteering at 16% with the highest in the South West at 23%. We also look at other demographics, including sex, age and ethnicity and find significant differences there as well (these are reported in Table 2 of the paper ).
We also look at the total hours volunteered per year: this is obtained by multiplying the frequencies by the relevant demographic head counts and turning the monthly into annual figures.
Since the 12 NUTS1 geographical units contain quite different populations, there is much more variation in the volume of hours across the UK. Large populations such as London, the South East and North West are much larger than the smaller populations in Northern Ireland, Wales and the North East.
Lastly, we look at the imputed value of the voluntary hours in terms of GVA. It is the essence of volunteering that it is not paid and hence in conventional National Accounts do not count it as part of the official GDP statistic. To impute an economic value for volunteering, we follow the methodology of the ONS Household Satellite accounts and value voluntary work at its replacement value: what it would cost to employ someone to do it. We use the relevant occupational wages from the ONS Annual Survey of Hours and Earnings (ASHE) and apply them to the hours. We can then measure this as a percentage of the official GVA for each geography (the vertical axis is £100m) and again we average over the 5 waves.
The picture looks very similar in shape to Figure 2, since we are multiplying those figures for total hours by wages. However, it gives a feel for how big the contribution of volunteering is: 10 represents £1bn and 30 £3bn.
We can look at the allocation of voluntary work across different sectors. To do this we need to use the English CLS, since there is no information on this in USoc. The three main sectors are (by percentage share of total hours):
Sports, amusement and recreational activities 31.8%
Membership Organisations (from Churches to political parties) 23.4%
Education 12.9%
Others, such as health, creative arts, residential care and social work all come in at around the 4-5% level.
Over time, volunteering seems to be in decline. Looking at the whole of the UK, the share of the imputed value of volunteering appears to be on the wane. In Figure 4 we report the value for each “wave”.
We can see that there is a considerable diversity of volunteering, both across the geography of the UK and also across different sectors and over time. It is an important part of the economy that deserves more detailed attention and we hope that over time more information about volunteering will become available.
ESCoE blogs are published to further debate. Any views expressed are solely those of the author(s) and so cannot be taken to represent those of the ESCoE, its partner institutions or the Office for National Statistics.
