Covid-19· Labour market· Cities and regions Local differences Responding to the local economic impact of coronavirus 14 June 2020 Charlie McCurdy Britain’s jobs crisis has hit every part of the country hard. At a headline regional level, job loss and furloughing has been fairly evenly spread. But increases in unemployment-related benefit claims have been larger in areas that started out with higher claimant rates, with this especially true when we focus at a more local level. The reliance on tourism in some local areas adds to the generalised impact of the shutdown that has hit sectors like hospitality and leisure – which are quite spread across the country – particularly hard. Coastal areas like Blackpool, Pembrokeshire, Devon and Cornwall face a double lockdown whammy: many local businesses have been shut, and travel restrictions mean that demand for a broader set of goods and services is particularly depressed in these areas because it tends to come from elsewhere. As restrictions ease, both these challenges will remain in place. These findings have implications for how we think about local differences in the policies that will support the recovery. The size and speed of the economic hit during this crisis necessitates a national and geographically spread policy response. But the particular uphill challenge faced by some areas means they will require more resources, and in some cases a more targeted set of policy measures. The coronavirus labour market shock is being felt across all regions and nations of the country, but with some difference between regions The scale and speed of the effects of the current pandemic on Britain’s jobs market have been unprecedented. Between March and April, the number of employees being paid through PAYE, which will include furloughed workers, fell by 450,000. The ‘claimant count’ (an administrative measure of the number of people claiming benefits principally for the reason of being unemployed[i]) rose by 850,000 between early March and early April, taking it to 2.1 million, about a third higher than the levels seen after the financial crisis. Recent memories of a jobs miracle are fading fast. Modelling and survey data tell us a lot about which groups were likely to be most affected, and have been so far. For example, previous Resolution Foundation research shows that the youngest and lowest-paid workers were expected to be most affected by the current crisis, and early survey evidence has borne this out. But these methods are far less helpful for understanding the local impacts of the crisis. Beginning with a high-level perspective on the geography of the current crisis, the chart below shows the proportion of employees who have experienced significant job changes since the coronavirus outbreak (based on our new coronavirus survey[ii]), and private sector employment, by region. Nationally, 23 per cent of workers have either been furloughed, lost their job or lost hours and pay due to coronavirus. But, as this chart shows, there is some regional variation, with between 17 and 26 per cent of workers experiencing these job changes across the Great Britain’s regions and nations. The pattern of furloughing shown here is mirrored in regional Coronavirus Job Retention Scheme (JRS) data published by HM Revenue and Customs (HMRC) this week (although levels are higher in the HMRC data, because it presents cumulative furloughing totals and is more up to date). This regional variation is largely explained by the sectoral nature of this crisis. 13.6 per cent of employees in the South West of England – the worst-affected region in the above chart – work in the tourism sector, compared to 11.3 per cent nationally. Only 15 per cent of workers in Wales and the North East England have experienced significant job changes. As the right-hand panel in the above chart shows, this could reflect the relatively low concentration of private sector jobs in these parts of the country – with public sector jobs much more likely to protect workers from the negative effects of this crisis. The fact that the hardest-hit sectors are largely evenly spread across the country (bar tourism) means that the sectoral nature of this crisis translates much less into regional differences than, for example, the 1980s recession – when manufacturing’s decline and service sector growth had a distinctive spatial pattern. Regional data also shows that unemployment-related benefit claims have risen across the country, with a rise of at least 50 per cent between early March and early April in all regions of the UK. The biggest increases were in the North East, North West and Northern Ireland, while the South East and East of England had the smallest increases. This is precisely the opposite of the pre-crisis trend of shrinking regional gaps in employment and household incomes. However, regional geographies often smooth over key local differences – it is these local differences we turn to next. Local differences look set to be exposed by the current jobs crisis Some of the UK’s most deprived towns and cities, many reliant on tourism or with workers concentrated in low-paid service jobs, look set to be hit hardest in this crisis. The chart below compares local claimant unemployment in March to the change in claimants between March and April. It shows that every single local authority in the country has experienced an increase in the proportion of working-age residents claiming benefits primarily for the reason of being unemployed. By this measure, the claimant count has risen by more than one-third in every local authority, and in one-in-five areas it has doubled. Not only have unemployment-related benefit claim increases been widespread, but local differences have been exacerbated (here we focus on absolute, i.e. percentage point, changes[iii]). For example, Blackpool, which already had the highest claimant count in the UK, has experienced the biggest percentage point increase – its claimant count jumped 3.9 percentage points to 11.1 per cent in April. On the flipside, Cambridge’s claimant count increased by just 0.9 percentage points, to 2.5 per cent, in April. What’s clear is that the claimant count rise is strongly correlated with the pre-coronavirus claimant level and the strength of local labour markets – with Liverpool, Hull and Manchester experiencing some of the largest increases, in contrast to places like Cambridge and Milton Keynes. In addition, the labelled areas in the chart above suggest that there have been particularly large claimant count increases in coastal, tourism-reliant areas. It is this outcome that we explore in more detail below. Tourist hotspots face the double whammy of hospitality business closures and reduced demand because of travel restrictions The closure of restaurants and cafes means that most hospitality businesses have been hit very hard in this crisis. Tourism businesses have also been hard hit – hotels and guesthouses have been shut; even British Airways has opted to use the furlough scheme; and VisitBritain has estimated that the tourism sector will lose £37 billion from the impact of coronavirus. But taking a place-based focus, we note an additional impact on not-strictly-tourism businesses in tourism-reliant areas (including hospitality but also stretching to retail, leisure, and other parts of the economy) because their demand has not been able to travel to them. In this sense, areas traditionally reliant on tourism have suffered a double whammy in lockdown – encompassing both supply restrictions and a significant reduction in demand. Both aspects of this will ease, but remain, as the economy slowly opens back up with many restrictions and social distancing measures still in place. The chart below gives us a sense of where these areas are, mapping the proportion of employees in tourism-related industries, by local authority district. It shows that places like Richmondshire in North Yorkshire, South Lakeland in Cumbria and West Devon have more than one-fifth of their workforce employed in the tourism sector. As the chart above shows, the local authorities most reliant on tourism tend to be coastal – the same areas experiencing the largest claimant count increases (and, as HMRC’s new data published this week shows, the areas with the highest proportion of employees furloughed, with the likes of South Lakeland, Scarborough and North Norfolk leading the pack). Overall, the chart below shows that the claimant count rise isn’t associated with high concentrations of tourism employment in non-coastal local areas. There is, however, a relationship when we focus just on the coastal parts of Britain. Moving beyond scatter chart explorations, linear regression analysis shows that a range of factors – including the density of tourism employees, whether a local authority is coastal, the pre-coronavirus claimant count and levels of weekly pay – all have a significant relationship with the percentage point change in the claimant count when combined in the same model (a negative relationship in the case of pay). This gives us a good sense of the factors we need to consider in order to understand how the effects of this crisis are likely to differ by locality as it unfolds further. Given these very unique spatial circumstances, what else do we know about rural and coastal Britain? Previous Resolution Foundation research highlighted these local authorities are also the parts of the country that have aged fastest since the turn of millennium, as a result of low birth and migration rates compared to the rest of the country. Not only are these local areas most exposed to jobs loss, but their older populations mean the pandemic’s health effects may be more acute here, too. We might also expect knock-on effects in terms of specific local economic consumption if these areas have significant proportions of their populations shielding. Besides age, the health effects of the coronavirus crisis are correlated with geographical deprivation. We make no attempt to unpick the drivers here, but note that the most deprived places will be many of the same places with the most severe jobs market effects. We turn, finally, to the policies needed to ameliorate any long-lasting impacts of the coronavirus crisis on local areas. Policy support needs to be spread across the UK with more resources targeted at specific areas The coronavirus crisis has had a very large affect across the country. But we have shown that its initial effects on claimant unemployment have been greatest in those areas that started out with the highest claimant counts, as well as being concentrated in coastal, tourist hotspots. So, what can policy do to prevent existing local differences becoming amplified as the recovery unfolds? First, we should note that policy has already played a massive role: were it not for the JRS and Universal Credit, the impact would be much larger in the worst-affected places. As the crisis moves from rescue to recovery, the response will need to evolve, including the phasing out of the JRS, the shift towards more generalised economic stimulus, and the introduction of back-to-work support. Other past and forthcoming Resolution Foundation reports set out the components of this response in detail. A clear conclusion given the large and broad-based (regional) geographic spread of this crisis, and its speed, is that a national, geographically distributed response will be essential. Beyond that fact, we conclude here by noting three local considerations, on the basis that some places are likely to face a bigger uphill challenge than others, and that the nature of the challenge will be different in different areas. First, we note that a national back-to-work strategy will require significant local capacity, particularly given reductions in Jobcentre Plus resources over the past decade. Local coordination and delivery were essential to the active labour market policies in the previous crisis, but local authorities’ capacity has been significantly depleted over the past decade. Supporting that local capacity to be mobilised quickly will be essential. Second, the nature of the back-to-work response will need to become more differentiated – both in terms of the level of resource and the nature of support – as the crisis unfolds, with weaker local labour markets likely to experience much slower recoveries. And finally, the fact that demand in tourism-reliant areas comes from people who live elsewhere means that general demand stimulus will be less effective in these areas if tourism activity remains supressed in the absence of a vaccine or effective treatment. As with the nature of the challenge on the employment support side, we expect that these worst-affected areas will require more resource and, in some cases, a much more targeted policy response. [i] The Office for National Statistics’ experimental claimant count data covers claims for Jobseeker’s Allowance and those Universal Credit claimants who are considered to be jobseekers; that is, claimants who are required to seek work in order to remain eligible for benefits. Claimant count data is a useful resource, particularly at a local level. Other sources, for example the Annual Population Survey, rely on survey data and at a local level tend to be much jumpier. [ii] The survey was designed and commissioned by the Resolution Foundation, in partnership with the Health Foundation (although the views in this note are not necessarily those of the Heath Foundation). It was conducted using an online interview administered to members of the YouGov Plc UK panel, which is made up of 800,000+ individuals who have agreed to take part in surveys. The total sample size was 6,005 adults, aged 18-65 and fieldwork was undertaken during 6-11 May 2020. The figures presented here have been analysed independently by the Resolution Foundation and are not the views of YouGov. [iii] We have chosen to focus on percentage point changes in the claimant count, as opposed to proportional changes. This is primarily due to the fact that the base claimant count was so low pre-coronavirus that proportional increases are dominated by the size of the pre-coronavirus claimant count. This explains why the places with the lowest base claimant count have experienced the biggest proportional increases between March and April 2020.