The Second Quarter
Speech given by
Andrew G Haldane
Chief Economist
Bank of England
30 June 2020
The views expressed here are not necessarily those of the Bank of England or the Monetary Policy
Committee. I would like to thank Shiv Chowla and Andre Moreira for their help in preparing the text. I
would like to thank Andrew Bailey, Daniel Gray, Jonathan Haskel, Gregory Kidd, Sevim Kosem,
Clare Macallan, Becky Maule, Michael Saunders, Michal Stelmach, James Tasker, Silvana Tenreyro,
Ryland Thomas, Jan Vlieghe and Tugrul Vehbi for their comments and contributions.
I would like to discuss today the economic outlook in the UK in the light of the Covid crisis and the way
monetary policy is responding to this crisis. There is a debate about which letter of the alphabet will best
describe the path of the economy, with some scepticism about the V-shaped scenario path in the Bank's
May Monetary Policy Report (MPR). It is early days, but my reading of the evidence is so far, so V.
Covid-19 is, first and foremost, a global public health crisis. The measures put in place to contain the spread
of this terrible disease have been necessary, but have had severe economic and financial consequences.
As a result, most countries around the world are facing a twin crisis of public and economic health.
The economy in the period ahead will continue to be shaped by the virus and policy responses to it. The
economy will also, though, be shaped by the behavioural responses of households and businesses, and the
policy responses of Governments and central banks, to these shocks. Understanding those responses is the
purpose of my comments today.
or "quarters",
I will partition my assessment of the economic impact of the Covid crisis into four phases,
covering the past, present and near and distant future. The first "quarter" covers the initial impact of the
virus; the second, the immediate recovery following these shocks; the third, the second-round effects on
spending and employment; and the fourth, the longer-run impact on households and businesses.
already well into the "second quarter" -
Both the UK and the global economies are the recovery phase. The
UK's recovery is more than two months old, while the global economy is perhaps three months into its
recovery, in both cases from an exceptionally low starting point. Let me say a little about each of the phases,
before concluding on the role of policy in supporting the economy during the Covid crisis.
"The First Quarter"
The Covid-19 crisis has dramatically affected public health in every country in the world. There have been
over 9 million reported cases of Covid globally and over half a million reported deaths, around 0.01% of the
global population.1 As a point of comparison, the Spanish flu of 1918 recorded 33 million deaths or close to
2% of the global population back then.2
During the first few months of the year, and unlike in 1918, most countries put in place social distancing
measures to contain the spread of the virus, albeit at different times and with differing degrees of stringency
(Chart 1). Predictably - indeed, intentionally - these measures severely curtailed movement of goods,
services and peoples, constricting economic activity across a very wide range of sectors and countries.
1
Data from European Centre for Disease Prevention and Control.
2
Estimates of the death toll are uncertain. The number quoted here averages the mid-range of estimates in Patterson and Pyle (1991),
Johnson and Mueller (2002) and Spreeuwenberg et al (2018).
Chart 1: Stringency of lockdown measures for selected countries
China
Index
France
100
90
Germany
80
Italy
70
Japan
60
South Korea
50
Spain
40
United States 30
20
Sweden
10
United
Kingdom 0
Jan-20 Feb-20 Mar-20 Apr-20 May-20 Jun-20
Sources: University of Oxford, Blavatnik School of Government
As official data have come on stream, the speed and severity of that contraction during the early months of
the year has become clear. In fact this was apparent in close to real time, courtesy of a range of unofficial
"fast indicators" of activity and employment tracked by the Bank and others.
The Covid crisis has seen an
explosion of interest internationally in developing fast indicators to track the economy in a timely fashion.3
The fast indicators used by the Bank have included data on payments and credit card transactions; Google
searches of key economic and financial terms; measures of traffic flow, including around ports; measures of
footfall on the high street; mobility and transport use metrics; bespoke surveys of households and
businesses; and measures of energy demand. In some cases, such as payments data, these indicators can
be mapped into the different components of consumption.
"social consumption" -
For example, Table 1 shows the peak-to-trough fall in a proxy for spending in pubs,
-
restaurants, cinemas etc based on Google searches across a range of countries. This is one of the
categories of spending likely to have been hit hardest by social distancing measures. It suggests peak-to-
trough falls of 50-90% in social spending, across a wide range of countries, in the early months of the year.
Fast indicators for the UK point to a similarly precipitous fall over the same period. Table 2 looks at the
peak-to-trough falls in household spending using CHAPS payments data.4 These lie anywhere between
3
et al et al
For example, Hacioglu, Känzig and Surico (2020), Carvalho et al (2020), Chetty (2020) and Aaronson (2020).
4
CHAPS is a sterling same-day payment system that is used to settle high-value wholesale payments as well as time-critical,
lowervalue payments like buying or paying a deposit on a property. Further detail on how these data can be used to track the economy can
be found below in Chart 8.
50% and 80% for all spending other than on staples (such as food and rent). Social spending fell as much
as 80% while delayable spending, which includes clothing, household goods and cars, fell by around 50%.
UK "fast indicators"
Table 1: Google searches related to social Table 2: of consumption
consumption categories
Country Peak YoY change, % Category Peak change, %
Italy -67
Social -80
Spain -75
Work-related -65
France -73
Delayable -50
Germany -70
Staple -5
US -58
Total -30
Japan -82
China -73
UK -69
Sources: Google and Bank calculations. Source: Bank of England and Bank calculations.
GDP data so far broadly corroborates the message from these fast indicators. Compared with the fourth
quarter of 2019, UK GDP fell by around 25% during the first four months of this year. The fall in
UK-weighted world GDP is likely to have been similarly unprecedented. Unsurprisingly, these would be the
sharpest four-month falls in GDP on record, in both the UK and globally.
This contraction has affected almost every sector, if to differing degrees (Chart 2). The largest falls have
been in the accommodation and dining sectors (over 90%). But sectors such as arts and recreation,
construction and education have fallen by more than 40%. Utilities, food production and real estate have
Generally speaking, the greater a sector's reliance on personal contact, the
been among the least affected.
larger its fall.
Chart 2: Falls in output by sector
Industry output, hit to level, %
Accomm. & food
Other service
Arts & recreation
Construction
Education
Transp. & storage
Admin. & support
Distribution
Manufacturing
Extraction
Health
Professional, etc
Info. & comms
Electricity
Agriculture
Water
Financial
Real estate
Public admin. & def.
0 -20 -40 -60 -80 -100
Sources: ONS and Bank calculations.
Note: Data to April 2020.
This sharp contraction in economic activity has been accompanied, unsurprisingly, by a sharp fall in working
hours. Globally, it is estimated that hours worked in Q2 were almost 11% lower than prior to the crisis,
equivalent to over 300 million full-time workers.5 The IMF forecast that the advanced economy
unemployment rate will double this year to over 8%. And the ILO estimate that the crisis could increase
unemployment globally by anywhere between 5.3 and 24.7 million people.6
In the UK, employment data to April from the Labour Force Survey (LFS) does not point to a sharp
contraction so far. But other, more timely, labour market indicators suggest a sharp fall in employment.
Claims for Universal Credit have risen by 21⁄2 million since mid-March and administrative data from HMRC
point to a large rise in joblessness. Claimant count measures of unemployment have risen by around
11⁄2 million since the start of the year.
as part of the Government's Job
In addition, over 9 million jobs are estimated to have been furloughed
Retention Scheme.7 A further more than 2.5 million self-employed workers are claiming income support.
And perhaps as many as 8 million employees are working fewer hours for a variety of reasons.8 Taken
together, this means that perhaps as much as half the UK workforce is currently either unemployed or
underemployed. This, too, has no historical precedent.
5
ILO (2020a).
6
ILO (2020b).
7
The total number of jobs furloughed may not equate to the number of employees still under furlough. For example, some workers
may have more than one job. And some jobs may only have been furloughed temporarily.
8
MPR: "Those that remain in work may be working fewer hours than normal. This could be because of reduced demand for their
May
services, in which case they will have spare capacity. But they may also work fewer hours because they fall ill, are required to
children."
self-isolate, or have extra non-work responsibilities, such as caring for relatives or home-schooling The Ipsos Mori survey in
the May MPR suggested around 25% of employees are working fewer hours.
In its May Monetary Policy Report (MPR), the MPC produced an illustrative but plausible scenario for the UK
and global economies. In this scenario, UK-weighted global GDP was expected to contract by 26% between
the fourth quarter of 2019 and the second quarter of 2020 and by 13% over the course of 2020. For the UK,
the equivalent numbers were a peak-to-trough contraction of 27% and an annual contraction of 14%.
Charts 3 and 4 plot the distribution of quarterly (since 1955) and annual (since 1700) GDP growth rates in
the UK, with the Bank's
May MPR scenario highlighted. By any conceivable metric, the Covid crisis has
generated an extraordinary left-tail shock to the economy, with few if any historical precedents.
Chart 3: Distribution of quarterly GDP growth Chart 4: Distribution of annual GDP growth since
since 1955 1700
Number of observations
Number of observations
160 50
45
140
40
120
35
100
30
May
80
May
25
MPR
MPR
2020
60 20
2020 Q2
15
40
10
20
5
0
0
-24-22-20-18-16-14-12-10 -8 -6 -4 -2 0 2 4
1 3 5 7 9
-9 -7 -5 -3 -1
11 13 15 17 19
-15 -13 -11
Annual GDP growth (%)
Quarterly GDP growth (%)
Sources: ONS and Bank calculations. Sources: Bank of England Millennium of Data, ONS and
Bank calculations.
"The Second Quarter"
The same fast indicators used to track the collapse in activity in the first part of this year can also be used to
track its recovery. Generally speaking, these indicators suggest the recovery in both the UK and global
economies has come somewhat sooner, and has been materially faster, than in the MPC's May MPR
-
scenario indeed, sooner and faster than any other mainstream macroeconomic forecaster.
fast indicators point towards the trough in activity in the UK's main trading partners having come
Globally,
during, or just after the end of, the first three months of the year: in China in February and in the US and
euro area in early April. That means UK-weighted global GDP has perhaps been recovering for around three
months. Chart 5 plots PMIs for a range of the UK's major trading partners. Although the PMIs are a less
good guide than usual to GDP outturns, they have bounced back sharply, as have some other business
surveys.9
Chart 5: PMIs in selected countries
Index, 50 = no change
70
France
Germany
US
60
50
Euro
area
40
China
30
20
10
0
2006 2009 2012 2015 2018
Sources: Thomson Reuters Datastream.
Notes: Composite output PMIs. Solid red line shows ISM PMIs for US, dashed red line shows Markit PMIs.
Chart 6a plots the Google-based proxy for social spending in a range of countries since the start of the year,
most likely the slowest of the consumption categories to recover. This measure troughed in Q1 for most
countries and has since recovered across the board, albeit to different degrees. For some countries, it is
already close to pre-Covid levels. The country divergence is even larger in Chart 6b, showing restaurant
bookings across countries, but the extent of the recovery is nonetheless similar.
9
noted that "These surveys record net balances of respondents, so they provide an indication of how widespread falls in
The May MPR
output and expectations are, but are less informative about the magnitude of the falls. So, at a time when the contractions are likely to
be very large, it is difficult to use these data to predict the size of the change in output."
Chart 6a: Google searches for social spending Chart 6b: Restaurant bookings
Per cent
Global Australia Per cent change
50
change on
on a year ago
Canada Germany
50
a year ago
30
Ireland Mexico
United Kingdom United States
10 25
-10
0
-30
-25
-50
-50
-70
-75
-90
Jan Feb Mar Apr May Jun
-100
Italy Germany France Spain
18-Feb 18-Mar 18-Apr 18-May 18-Jun
UK US Japan China
Sources: Google and Bank calculations. Sources: Open Table and Bank calculations.
news, Bank staff's nowcasts for world GDP growth in
In the light of this Q2 have been revised up, by 13
percentage points to around -10%. Even relative to the scale of the fall, this is a large upward revision. One
reason is because social distancing measures have been loosened more rapidly than expected (Chart 1), as
we would expect the stringency of lockdown to affect GDP.
We can use a model to explain GDP across a range of countries using the stringency of their lockdowns in
that quarter, as well as a range of other country-specific factors (Chart 7).10 That model suggests world GDP
will be 15% lower in Q2 than at the turn of the year, compared to 26% in the May MPR scenario.
Chart 7: Lockdown stringency against GDP growth over 2020 H1
GDP change
10
from 19Q4 to
5
20Q2, %
0
-5
-10
-15
-20
-25
UK
-30
-35
0 20 40 60 80 100 120
Average Oxford stringency index over quarter
Sources: Apple, University of Oxford and various national data sources.
Notes: See Footnote 10.
10
For a panel of 55 countries, we employ a forecast combination analysis of around 20 different regression models, each of which uses
different sets of explanatory variables and the final forecast is a root mean square error weighted average of forecasts from all our
specifications. The variables we use are containment, economic and health policy response indices, which are calculated in-house
using the Oxford University Covid monitoring database, Apple mobility trends and country characteristics, e.g. share of exports in GDP,
dummies for income level and geographic region and average GDP growth between 2014 and 2018. We also include containment
policy characteristics such as the maximum containment policy response and the time spent at this maximum response in a quarter.
For the UK the picture is broadly similar. Fast indicators suggest the trough in activity was reached in the
middle of April, with a steady recovery thereafter. Chart 8 plots payments-based fast indicators for the UK
mapped into four convenient categories of consumer spending. By late-June, these spending components
had recovered at least a third, and in some cases all, of their prior fall. They have risen both sooner and
materially faster than in the May MPR scenario.
Chart 8: Fast indicators for the UK
% change from Jan-Feb level
60
40
Staples
20
0
-20
Aggregate
-40
Delayable
-60
Work-related
Social
-80
-100
Mar-20 Apr-20 May-20 Jun-20
Sources: Bank of England and Bank calculations.
Notes: Based on the CHAPS payments that a sample of around 90 UK companies receive from their merchant acquirers
on a daily basis. These payments reflect the sales that companies make through debit and credit card purchases, which
are summed to estimate rolling seven-day revenues. Definitions of the different consumption groups are discussed in
the May MPR.
- -
Among the negatively-affected components of spending social, work-related and delayable the fastest
recovery has been in delayable expenditure such as DIY and household goods.11 There has also been a
sharp up-tick in the car and housing markets, albeit from stagnant levels. Some elements of consumer
consumers' appetite for
confidence have bounced back too, in particular major purchases.
Official data on retail sales have confirmed this recovery in spending, rising 12% in May to leave spending
13% below its pre-Covid level. In part this may reflect the partial opening-up of a larger number of shops.
But a larger part appears to have reflected a shift towards online purchases. As a fraction of total retail
spending, online sales has risen from around a fifth prior to the Covid crisis to around a third now.
Reflecting these trends, many business surveys have also bounced back from their April lows. UK PMIs for
May and June rose back to levels only a little below the 50 (no change) mark (Chart 9), as in our major
trading partners, although the precise signal to take from these balances at present is unclear.
11
The May MPR discusses what these different categories of household spending represent.
Chart 9: UK PMIs
Diffusion Index
70
Services Business Activity
60
50
Manufacturing Output
40
Composite Output
30
20
10
0
2006 2008 2010 2012 2014 2016 2018 2020
Sources: IHS Markit.
Notes: Output balances.
UK's faster recovery might simply reflect an earlier relaxation of lockdown than
The was assumed in May, as
in other countries. But there is less evidence to support that hypothesis in the UK, with the pace of relaxation
broadly in line with the May MPR scenario (Chart 10a). On the face of it, this suggests some greater than
expected degree of underlying strength in consumer spending in the UK economy.
Chart 10a: Lockdown stringency (actual and May Chart 10b: Share of consumption basket that is
MPR-consistent) unavailable
Stringency of government measures
Restricted consumption share
0.5
80
70
0.4
60
50
0.3
40
30
0.2
20
10
0.1
0
Jan Mar May Jul Sep
0.0
May MPR-consistent Index
Mar Apr May Jun
Sources: University of Oxford, ONS and Bank calculations.
MPR
Note: Blue line simply in Chart 10a takes Stringency Index as of early-May, and extrapolates it based on May
assumption that
"The illustrative scenario is conditioned on social distancing measures and government support
schemes remaining as they are until early June, before being gradually unwound by the end of Q3."
Taking this evidence together, Bank staff now expect consumer spending to be around 20% lower in Q2,
relative to nearly 30% in the MPR scenario. By the end of Q2, spending is likely to be around 10% lower
than at the start of the year. Or, put differently, consumer spending in the UK is probably already above the
level projected to prevail in Q3 in the May MPR scenario.
Some of these data cover the opening-up of non-essential retail stores on 15 June. That opening-up was
quantitatively significant, representing around 13% of consumption spending and halving the share of goods
and services consumers which were previously unavailable (Chart 10b). Initial indications from payments
and footfall figures suggest this opening-up has accelerated, perhaps significantly, consumer spending. In
particular, CHAPS data suggests spending on delayable goods has now returned to pre-Covid levels (Chart
8), well ahead of the corresponding May scenario profile.
Looking ahead, the opening of pubs, restaurants, hotels, cinemas and other hospitality outlets on 4 July will
provide further impetus to spending. My own market intelligence suggests considerable pent-up demand.
Together, these categories represent around another 10% of consumer spending. Initial reports from
businesses in these sectors, including from the Bank's Agents, suggest advance bookings are brisk.
There is less evidence on which to base an updated judgement on the other components of GDP. For net
trade, the May MPR scenario suggested around a 40% peak-to-trough fall in gross export and import
volumes. Trade and port traffic data suggest a somewhat smaller contraction. With the world economy
recovering sooner than in the UK, this implies a slightly larger boost to UK GDP growth from net trade in Q2.
For housing and business investment, there are even less data on which to make an assessment. The May
MPR scenario suggested peak-to-trough falls of 60% and 40% respectively, based in part on results from the
Bank's Decision
Maker Panel (DMP). The latest results from the DMP appear broadly consistent with this.
Updating Staff's
nowcasts for these high-frequency data gives an estimated fall in Q2 GDP of around 20%
relative to its pre-Covid peak. While this is an exceptionally weak number, that is not in itself news. The
news is that it is 7 percentage points less than in the May MPR scenario. By comparison, an estimate based
on the stringency-based model implies a broadly similar contraction in UK GDP in Q2 of 19% (Chart 7).
It could be argued that, while these are large upward revisions in an absolute sense, they are still relatively
modest by comparison with the falls already seen. And of course, some of this rise in spending might simply
be the release of pent-up demand, which could dissipate subsequently.
Against that, the evidence so far suggests the recovery is not simply the bringing-forward of spending. Were
this higher level of spending maintained, it would put GDP on a different path than in the May MPR scenario.
The cumulative loss of annual GDP in the May scenario, relative to the January MPR forecast, was around
17%. If the higher starting level of GDP were maintained, the cumulative loss of GDP would more than halve
to around 8%.12
"The Third Quarter"
Looking to the second half of the year, what might we expect? In the May MPR, the MPC's scenario foresaw
a sharp pick-up in activity, with quarterly growth rates of 12-13% in each of Q3 and Q4. These increases
were driven, in large measure, by the assumption of a phased relaxation of lockdown measures, and
accompanying policy support, between July and September.
To my mind, two paths are possible in the second half of the year. One involves a negative feedback loop
from higher unemployment to lower spending, the other a positive feedback loop from higher spending to
lower unemployment. The first poses a downside risk to the outlook, the second an upside risk. As things
stand, it is unclear which of these scenarios, or feedback loops, will prove the more potent.
The negative loop has its roots in the labour market. So far, levels of employment appear to have fallen less
rapidly than output. Against that, the number of furloughed workers has exceeded expectations, perhaps by
in excess of a million people. This is good news for household incomes in the short run, as the income loss
from furlough is far lower than from unemployment. Indeed, this might help explain some of the greater than
expected strength in demand in Q2.
As the furlough scheme tapers from August, however, there is a risk this greater number of furloughed
workers are not hired back by employers, adding to the unemployment pool. The May MPR scenario had
unemployment rising to 9%, but assumed the risk of workers not being re-hired was small. Recent survey
evidence, from both households and companies, suggests this risk could be larger. For example, survey
evidence of companies by the DMP suggests private sector employment could be almost 10% lower by the
end of 2020, implying an unemployment path somewhat higher than in the May MPR scenario.
If unemployment was to rise more than expected, it increases the risk of a negative feedback loop.
Joblessness, or fears of it, have historically been a key driver of household savings. Higher unemployment,
as well as lowering incomes, could cause households to increase precautionary savings. That higher saving
would lower demand and negatively affect company revenues and employment, in a vicious cycle.
John Maynard Keynes described this dynamic in the 1930s as the "paradox of thrift".13 A paradox because
prudent decisions by households, given the risks they face, have the perverse collective consequence of
increasing risks to the economy and those same individuals. These dynamics might be particularly potent at
12
Cumulative loss calculated as the percentage difference in the four-quarter sum of quarterly GDP at the Year 1, 2 and 3 points of the
January MPR, summed together.
13
(1936) described this pattern and Samuelson (1948) used the term 'paradox of thrift'.
Keynes
-
present because households face double jeopardy risks to their lives and their livelihoods. Elsewhere, I
have called this dread risk.14 At present, dread is double-barrelled.
Yet this is not the only path possible for the economy. The willingness of companies to take back furloughed
workers will depend importantly on their expectations about future demand for their goods and services. The
stronger those expectations, the lower the likelihood of job losses. Firms will not make workers redundant if
they need to rehire them, at a cost, soon afterwards. This lowers unemployment risk, raises household
incomes, confidence and spending and thereby boosts firm revenues and employment, in a virtuous cycle.
Back in the 1950s John Hicks called this dynamic a "super-multiplier" - "super" because the cumulative
effects are amplified when emerging from recession.15 There is survey evidence to support this dynamic.
(BCC) firms'
The British Chambers of Commerce's weekly survey suggests demand and employment
intentions have moved upwards in lockstep since April (Chart 11). Indeed, employment was close to balance
by mid-May. Surveys of employment intentions and vacancies have also recently recovered from low levels.
Chart 11: BCC survey
Balance
60
Composite output
40
20
0
Reported employment -20
-40
-60
-80
-100
2007 2009 2011 2013 2015 2017 2019
Sources: BCC and Bank calculations.
Notes: Chart shows BCC Quarterly Survey and dashed lines show more recent weekly survey after Covid-19 crisis
began.
A further mitigating factor is that household savings rates appear to have risen, involuntarily and significantly,
due to social distancing policies. A Bank of England survey in conjunction with Ipsos Mori suggests the
aggregate saving ratio is broadly unchanged, although with considerable heterogeneity across income
cohorts (Chart 12). But it is possible these survey respondents did not capture the involuntary increase in
households'
cash balances when they answered questions about their savings behaviour.
14
Haldane (2020).
15
Hicks (1950).
For example, sterling deposits held by households and companies in banks have increased sharply over the
past few months, by around £120 billion (Chart 13). That is consistent with a significant rise in the saving
ratio. These higher involuntary savings could be drawn down to finance future spending, at least by some
households. In aggregate, they potentially dwarf any voluntary rise in savings for precautionary purposes.
Chart 12: Saving rates by income (net balance)
Net balance increased savings (%)
25
20
15
10
5
0
-5
-10
-15
Up to £19,999 £20,000-£34,999 £35,000 - £54,999 £55,000+
Sources: Ipsos Mori and Bank calculations.
Notes: Research was carried out by Ipsos MORI on behalf of The Bank of England. It surveyed a nationally
representative quota sample of 2,243 adults in the United Kingdom aged 16-75 using its online i:omnibus on 29 May to
3 June. Data has been weighted to the known offline population proportions for age, gender, government office region,
working status and social grade. Respondents were asked, "as a result of the coronavirus pandemic, would you say
that your household savings have increased, decreased, or stayed the same?"
Chart 13: Sterling deposits held by households and PNFCs (monthly flows into M4ex)
£ billion
Households PNFCs
60
50
40
30
20
10
0
-10
Jan - 19 Apr - 19 Jul - 19 Oct - 19 Jan - 20 Apr - 20
Sources: Bank of England and Bank calculations.
OFCs' M4.
Note: Chart does not include flows into non-intermediate
Which of these two paths will play out in practice? Back in May, the MPC observed that the balance of risks
to the outlook was skewed to the downside. Subsequent positive news on demand has, in my opinion, more
than counterbalanced the rise in downside risks to employment. To my mind, this leaves risks to the outlook
slightly more evenly balanced than in May, if still with a downside skew.
"The Fourth Quarter"
Looking beyond 2020, there is plainly a high degree of uncertainty about the economy. That in part reflects
uncertainty about the virus and the policy responses to it. But it also reflects uncertainties about the path of
the economy itself. Given the depth of the recession, there is likely to be a greater than usual degree of
history-dependence, or hysteresis, in this path. The deeper and longer the recession, the greater the
the economy's productive potential.
scarring effects on physical and human capital and hence
The May MPR scenario captured some of these scarring effects. In particular, it assumed that lower
investment as a result of the Covid crisis was not recovered, leaving the capital stock 4% lower. Combined
with some drag on total factor productivity (TFP) growth, the level of output ended 11⁄2% lower. That scenario
assumed no scarring effect on human capital, however, with unemployment returning to pre-Covid levels and
the long-run rate of unemployment unchanged at around 41⁄4%.
At the same time, it was recognised that this was just one of many possible paths for the economy. Other
paths would give rise to differing degrees of scarring to physical and human capital and losses to the
long-run productive potential of the economy. On 14 July, the Office of Budget Responsibility (OBR) will
publish three possible scenarios for the economy involving different degrees of depth and length of the
downturn.
Perhaps the key uncertainty, from a scarring perspective, concerns the labour market. As Chart 2 illustrates,
the Covid crisis has had markedly different effects on different sectors and, most likely, will continue to do so.
Chart 14 compares different sectors' contribution to the pre-Covid employment boom and its subsequent
output contraction. There is a negative correlation, suggesting it might be difficult for the sectors which
absorbed most workers pre-Covid to repeat this feat post-Covid.
Chart 14: Falls in output by sector against post-GFC employment growth
Covid-19 sectoral output hits, %
40
20
Contribution to post-GFC
employment growth, pp
0
-20
-40
-60
Accommodation & food
-80
-100
-1 0 1 2 3
Sources: ONS and Bank calculations.
Notes: Sectoral output hits on y-axis are from Chart 2. Numbers on x-axis are the percentage point contribution of each
sector to total growth in UK employment from its post-global financial crisis trough to end-2019.
Other, structural, factors may further complicate the labour market picture. The Covid crisis has shifted
relative prices in ways which could encourage companies to invest in machines rather than people during the
recovery. The price of capital goods has fallen while the price of labour has increased because of the need
for Covid-secure premises and practices. This shift in the relative price of capital versus labour will provide a
headwind to the re-absorption of workers.
A second structural headwind concerns the skills mix of those losing their jobs. Research suggests this is
likely to be skewed towards those with fewest skills and least experience, especially the young. The
Resolution Foundation estimates that high unemployment will result in a 13% lower probability of a new
graduate being in employment three years after completing education. For those without a university
qualification, the probability of being in work three years from now might be 27-37% lower.16
During jobs recessions, many workers choose to move down the skills spectrum to regain a foothold on the
jobs ladder.17 But if many displaced workers have low levels of skill and experience, the option of moving
down the skills spectrum may not be available or may at least have lower value. Skilling or re-skilling will
then be needed. This adds to the time it takes workers to re-enter the jobs market, prolonging high
unemployment.
16
Henahan (2020).
17
Haldane (2019), Moscarini and Postel-Vinay (2016) and Moscarini and Postel-Vinay (2018).
The possibility