Understanding Universal Credit Recipients

We recently began analysing Universal Credit claimant levels to support the Skills and Employability team to better understand why, despite record low unemployment, Universal Credit (UC) claimant numbers had barely decreased from their March 2021 peak[1]. [2].

Once we started exploring the data, it became clear that something more than a simple analysis of the raw claimant data was needed[3]. More useful, we thought, in helping us to understand why was to create a calculator that would simulate benefit eligibility for different household personas under different scenarios.

But first, we explored subgroups in the claimant data to give us a sense of who was using the system. We found that the largest group of claimants are single adults with no children (45%). This is followed closely by single parents with children (37%). Couples with/out children represent a minor proportion of claimants, at just under 18% combined (as at Nov 2021). When looking at the gender of claimants, the gender split is approximately 50/50, with a slightly higher number of female claimants. When factoring in employment, females in employment (64% in Feb 2022) are more likely to be claiming UC than males in employment (36% in Feb 2022).

We also looked at children in households claiming UC. First, we found that over recent years, the number of households in receipt of the Child Entitlement of UC has been consistently growing (47% at Feb 2022) while those without Child Entitlement is declining. Second, when looking at the proportion of households with children on UC by age, we found that no less than 50% of these households had children aged 0-4; 30% had children aged 5-10; and the remaining 20% had children aged 11-19. Importantly, when looking at claimants by their duration on UC it becomes clear that there is not much turnover of claimants and that once claiming, people tend to stay on UC.

To dig a bit deeper, we next simulated the income (earnings + benefits) of three distinct personas or “types” of claimants and under varying monthly work-hour scenarios. We looked at a single parent in employment with two children of school-age, a couple with a child where one parent was in employment, and a single adult in employment with no children. For each of these types we found the same outcome - the more work hours worked, the better off they were financially. As work hours increased, UC benefits gradually tapered off (eventually to zero) but net monthly income (after income tax and NI) continued to grow.

Importantly, there are a few things that our analysis has not yet taken into account, and which might be important for the findings reported above. First, our simulations did not account for Housing Cost Support, Free School Meals (FSM), and Council Tax Support. Second, the analysis also did not account for household debt, which can create additional challenges for households on benefits. Finally, we also only looked at core UC awards. It is therefore possible that once we account for these additional factors, the findings could change. However, based on the current analysis we do find that in its current form, UC does not create disincentives to work more.

Given this finding, we then wanted to explore some of the other reasons (besides payments) that people may not want to work more hours. Recent qualitative research from our Research and Citizen Insight team on working families who are “just about managing” highlights a number of possible explanations. They combine focus groups and longitudinal research and examine the financial experiences of working families with low income, but who do not qualify for UC. Their analysis shows that the high cost of childcare demotivates parents from increasing the number of work hours. Respondents indicate that their work and childcare arrangements are finely balanced, and that part time work and flexible hours are strategies used to avoid paying for childcare. Similarly, respondents say that they use annual leave to cover school holidays.

A compounding factor is that work for respondent families is often insecure, with many on zero-hour and temporary contracts. Although some respondents plan to refocus their careers at some point in the future, many are pessimistic about the cost and opportunity to upskill or retrain later in life. And finally, for many, the cost of travel is a barrier to seeking better work (commuting to London in particular), while the costs of running a car are high and inhibiting. Many prioritise time with their children and work closer to home to reduce petrol costs, the risk for mechanical faults, and to leave more time for family.

In summary, our findings thus far suggest that factors such as the cost of childcare, precarious work, and the costs associated with transport and travel to better jobs may affect people’s work choices and therefore we need to explore these and other factors.


[1] At the peak in 2021, this was about 80,000 households

[2] At the peak in 2021, this was about 80,000 households

[3] This data is accessible through DWP’s open data platform, Stat-Xplore.

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