It is widely accepted that Britain has a workers problem: over half a million more working-age people are economically inactive (neither in work nor looking for work) compared to before the pandemic. Jeremy Hunt is expected to focus on this problem in his Budget speech on Wednesday. Yet such is the complexity of the ‘participation puzzle’ that designing properly targeted policy solutions is far from easy – not least because three disorienting myths seem to have taken hold in the discourse.
The Chancellor can’t afford – literally can’t afford – to ignore the problem, however. The total number of job vacancies across the UK economy stood at 1.15m in Q4 2022, still 42% higher than before the pandemic and 76% higher than the average for the decade after the financial crisis. Again and again, employers are reporting difficulties in filling positions. This is obviously a constraint on short-run economic growth (and therefore tax revenues), and is probably having an inflationary effect too. Hence inactivity has become one of Britain’s most pressing economic problems.
True, other factors are also contributing to labour market imbalances: pent-up consumer demand from the pandemic, changing patterns of immigration and structural changes in the economy. But if we could get inactivity back to the pre-pandemic level, the number of vacancies in would be up to around 20% lower than in Q4 2019. So inactivity appears to be the decisive factor.
February ONS data shows that there are 516,000 more inactive people aged 16-64 than was the case pre-pandemic. That means 8.89 million people – 21.4% of the total workforce – are not participating in the labour market. And while participation rates are still higher in the UK than in most other OECD countries, we have seen a larger increase in economic inactivity since the pandemic than all but three of these nations. Indeed, in 80% of OECD countries, inactivity is now actually lower than it was before the pandemic. The UK is an international outlier.
Conventional wisdom has settled on a mix of three main explanations for why this should be so. First, strains on a health service battered by the pandemic and Government mismanagement resulting in more people out of work for untreated medical conditions. Second, that this is overwhelmingly a problem of the elderly – to the point where the House of Lords Economic Affairs Committee explicitly excluded younger cohorts in its otherwise excellent recent study. And third, that outside of the 50-64 cohort, increased inactivity is being driven by high and rising childcare costs, which is preventing young mothers from rejoining the workforce.
None of these explanations are entirely wrong – but they are overly simplistic. That is why, in a new report for the Centre for Policy Studies, ‘Where are the workers?’, I have attempted to shine a light on the overlooked and hidden aspects of Britain’s economic inactivity problem, for if we can’t even properly identify the problem, we have little hope of fixing it.
For instance, the headline figures do show an additional 352,000 individuals now inactive for reasons of long-term sickness – a startling 17% rise. But in fact, 69% of those moving into long-term sickness were already out of the labour market for another reason. Similarly, of those whose who moved out of the long-term sickness category in 2021 and 2022, 63% remained inactive for another reason, rather than re-entering the labour market.
The key reasons for inactivity seem for many people to be financial rather than health related. For instance, logistic regression modelling by the ONS found that men aged over 50 who owned their own home were 1.8 times more likely to be inactive then men in the same cohort who rented, while the equivalent figure for women was 1.6 times more likely. Levels of debt and perceived financial security also correlate strongly with inactivity. These finding are consistent across a number of studies, by both the ONS and other organisations such as polling company Public First. Basically, a number of people who experienced furlough or working from home have opted out of work where they have the (perceived) financial security to do so.
At the same time, many older people face strong financial incentives not to work anymore, given how tax benefits from pension contributions max out under the lifetime allowance (LTA). The lifetime allowance now stands at £1.07m – whereas that 2010/11 figure would have a real-terms value of £2.4 million. In other words, the pension cap has more than halved in real terms in a decade. Too many people aged 50-64 are now bumping up against this limit earlier (this is especially true of public sector workers). That is why rumours that Hunt will LTA in the Budget are welcome – though better to abolish it altogether.
In any case, among the elderly it is clear that affluence and lifestyle choices are at least as much a driver of increased inactivity as long-term sickness, and as I argue in the report, could be twice as important. It is also true that the elderly are a key group for understanding inactivity, accounting for 62% of the increase since the pandemic.
However, it is the 18-24 group that has actually seen the largest increase in its inactivity rate, rising from 28.8% to 31.3%. This represents an extra 105,000 inactive young people (20% of the total increase). Contrary to the prevailing narrative, an increase in student numbers account for at best around half this. It’s also not clear that people who chose to stay in education for longer during Covid are emerging better equipped to compete in the jobs market. In Q4 2022, as a cohort of Covid students left education, the number of unemployed NEETs shot up by 28% (65,000) – the largest quarterly rise since current records began in 2001. While not yet officially inactive, these unemployed NEETs are clearly at risk of drifting into inactivity.
Meanwhile, among younger people currently counted as inactive, there are worrying trends in long-term sickness that need investigating, not least a surge in inactivity for reasons of mental health that seems to have begun a year before Covid hit. There could be a range of reasons for this, not least how incentives are structured within the benefits system – but we can’t yet be confident of what is going on, and so are hamstrung in designing policy solutions. A bespoke investigation into economic inactivity among the young is urgently needed.
Where it has featured in the debate, increased economic inactivity as a problem among younger people has mainly been seen through the lens of childcare and female labour market participation. Of course, the childcare sector is in dire need of supply-side reform. But if the theory that childcare was driving the increase in inactivity were true, we would expect to see rising economic inactivity among women aged 25-34, as the mean age at which women become mothers is now 30.7 years.
In fact, the flow is in the other direction. There are now 60,000 fewer economically inactive women aged 25-34. In contrast, there are around 400,000 more working-age men economically inactive now than pre-pandemic, and around more 116,000 women – a stark 77:23 split.
No one has yet got to the bottom of why this is so, although I outline a few hypotheses in ‘Where are the workers?’, and Richard Reeves might have a few ideas. But one thing is for certain: if the Government wants to get enough people back into work to move the dial on economic growth, it needs to work out whether there are particular factors behind surging male inactivity.
There is a broader point here too, as encapsulated by Colvile’s dictum: ‘database management is both the most important part of modern government, and its most intractable limitation’. The conversation around inactivity has been complicated by poor data. Analysts are confronted with overlapping but incomplete datasets, making it hard to slice data across categories at requisite levels of granularity, and forcing a reliance on inference and comparing the not-quite-like-for-like.
The data problem is also related to the fact that, while the tax system works on an individual basis, the benefits system works on a household basis; this is reflected in how data is structured and managed in the respective departments. If instead the tax and welfare (and health and education) databases could talk to each other, rather than operating in departmental siloes, it would be much easier to pull out a high-resolution picture of what is going on in the labour market.
Ultimately though, what we do know for now is that there is no silver bullet – no simple incentive or reform – that is going to get people back into work and stop rising inactivity from becoming a persistent or structural rather than a transient or cyclical problem. Rather, we need a whole range of solutions to address the very different drivers of inactivity in different parts of the economy – not overlooking elderly high-earners, the young in general and men right across the board.
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