COMMISSION STAFF WORKING DOCUMENT Identifying Europe's recovery needs Accompanying the document COMMUNICATION FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT, THE EUROPEAN COUNCIL, THE COUNCIL, THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE REGIONS Europe's moment: Repair and Prepare for the Next Generation
Date: 2020-05-27
Institutions: European Commission, Secretariat-General
Subjects: EU aid, EU situation, economic and social cohesion, economic consequence, economic policy, economic recession, epidemic, infectious disease, investment, single market

EN 

  EN 

   EUROPEAN COMMISSION  Brussels, 27.5.2020  SWD(2020) 98 final/2  Version finale/2. Annule et remplace le document SWD(2020) 98 final. Ajout d'un disclaimer à la page 51. COMMISSION STAFF WORKING DOCUMENT Identifying Europe's recovery needs Accompanying the document COMMUNICATION FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT, THE EUROPEAN COUNCIL, THE COUNCIL, THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE REGIONS Europe's moment: Repair and Prepare for the Next Generation       {COM(2020) 456 final}  
 
 
Identifying Europe’s recovery needs 

1.  A BLEAK ECONOMIC OUTLOOK 

The scale of the recession facing Europe is immense, as is the policy challenge. What 
started as a localised outbreak of a previously unknown virus infection in late 2019 has 
rapidly spread across the globe, wreaking havoc on European and global health systems 
and economies in the process.  Stemming the tide of CoVid-19 infections has forced all 
EU  Member  States  to  impose  wide-ranging  restrictions  that  curtail  the  production  and 
trade of goods and services. These supply-side problems are compounded by a collapse 
in spending and investment by households and companies, driven by their confinement, 
concerns about income and job prospects, worsening financial conditions, and pervasive 
uncertainty about the future course of the crisis. In recognition of the potential difficulty 
for  Member  States  to  recover  from  this  unprecedented  shock,  the  European  Council 
agreed on 23 April 2020 to work towards the establishment of a Recovery Fund. To this 
end,  they  tasked  the  Commission  to  “analyse  the  exact  needs  and  to  come  up  with  a 
proposal that is commensurate to the challenges we are facing”, further stating that ”this 
fund  shall  be  of  a  sufficient  magnitude,  targeted  towards  the  sectors  and  geographical 
parts of Europe most affected”.1 

The EU economy is  expected to contract sharply  in 2020. At the start of the second 
quarter  of  2020  all  EU  Member  States  were  operating  at  only  a  fraction  of  their  usual 
economic capacity. The Commission Spring 2020 forecast suggests that in Q2 2020 real 
GDP  will  be  around  14 %  below  the  level  recorded  in  the  same  quarter  of  2019.  The 
second  quarter  marks  the  trough  of  a  deep  recession  that  will  see  GDP  fall  in  2020  by 
7.4 %  in  the  EU,  with  only  a  partial  recovery  in  GDP  expected  in  2021  of  6.1 %.  The 
large majority of Member States will have a lower level of output at the end of 2021 than 
when  the  CoVid-crisis  erupted.  Although  containment  measures  are  likely  to  be 
progressively lifted  from mid-year onwards, the  Spring  Forecast  shows that  the path  to 
recovery  will  not  be  swift  or  easy  to  tread.2  Risks  to  this  central  scenario  are  strongly 
tilted  to  the  downside,  which  is  illustrated  in  the  Spring  Forecast’s  two  alternative 
downside  scenarios  of  a  ‘second  wave’  of  infections  and  longer-lasting  containment 
measures, which entail GDP contractions of 11 % and 16 % respectively in 2020. While 
an unusually large degree of uncertainty surrounds any economic forecasts or assessment 

1 

https://www.consilium.europa.eu/en/press/press-releases/2020/04/23/conclusions-by-president-charles-
michel-following-the-video-conference-with-members-of-the-european-council-on-23-april-2020/  

2  See  Communication 

of 

15  April 

https://ec.europa.eu/info/sites/info/files/communication_-

_a_european_roadmap_to_lifting_coronavirus_containment_measures_0.pdf  

1 

 
 
 
 
 
                                                 
at the current juncture, the avoidance of downside risks will require policy responses that 
are timely, comprehensive and effective.  

The  crisis  will  cause  large  losses  in  income  for  households  and businesses.  Modern 
economies  are  circular  systems  in  which  companies  and  households  rely  on  continued 
income  generation  through  production  and  consumption  in  order  to  sustain  livelihoods, 
invest,  and  meet  financial  obligations.  Part  of  the  immediate  crisis  response  therefore 
focused  on  supporting  income  streams  for  employees  through  short-time  working 
arrangements, thereby easing labour costs for employers, safeguarding jobs while at the 
same time shoring up cash flows for businesses. However, the duration of such schemes 
is  typically  limited  and  does  not  always  cover  the  full  wage;  temporary  workers  and 
those on non-standard contracts may not be covered altogether. For companies, liquidity 
problems will increase the longer production is stalled, and the use of public or private 
bridge financing from loans is difficult to sustain over time. Over the course of 2020 a 
resumption  of  production  and/or  an  increase  in  equity  levels  will  be  needed  for  many 
companies  to  survive,  especially  highly  leveraged  ones  or  those  with  low  financial 
buffers. 

A fragile corporate sector means fewer jobs and a meek recovery. Company failures 
can cause lasting economic damage in a number of ways. First, the layoffs following a 
bankruptcy  will  lead  to  rising  unemployment,  leaving  many  jobseekers  struggling  to 
retain  their  skills  and  attachment  to  the  labour  market,  especially  in  the  context  of  a 
global downturn. The longer individual unemployment spells last, the greater the loss of 
human  capital  and  an  economy’s  productive  potential.  Second,  bankruptcies  can  waste 
capital,  as  company  assets  such  as  machinery  will  only  partially  be  put  to  other  uses 
while intangible capital such as intellectual property may lose its value if not developed. 
Third, a company’s failure destroys the equity of its owners and may cause defaults on 
corporate  loans.  Business  failures  also  disrupt  economic  networks  and  can  bring 
international  supply chains  to  a halt. Even for companies that survive, their capacity to 
invest  will  shrink.  This  will  hold  back  potential  growth  and  employment  and  slow  the 
transition to a greener, more innovative economy. All the above factors can cause large 
negative second-round effects on investment, employment, growth and prosperity.  

In spite of efforts to protect workers and jobs, the crisis may cause a large increase 
in  unemployment,  hardship  and  inequality.  Household  incomes  are  likely  to  suffer, 
both  due  to  temporary  cuts  in  earnings  and  permanent  job  losses  —  the  latter  are 
expected to drive up the unemployment rate to around 9½ % in the euro area and 9 % in 
the  EU  in  2020,  undoing  three  years’  worth  of  job  market  improvements.  This  will 
worsen already low levels of domestic demand and further aggravate the recession. Low-
skilled  and  temporary  workers  are  likely  to  be  hit  hardest,  as  these  typically  work  in 
client-facing  services,  manufacturing  and  agriculture,  which  cannot  be  performed 
remotely.  Labour  supply  is  set  to  decline,  particularly  due  to  the  young,  elderly  and 
therefore 
vulnerable 
predominantly hit poorer and vulnerable households, adding both immediate and longer-
lasting social problems to economic ones; to avoid this, both firms and workers need to 
be protected. 

labour  market.  The  crisis  may 

losing  attachment 

the 

to 

Government finances may be permanently weakened. Both the immediate healthcare 
costs  and  the  effects  of  the  recession  will  take  their  toll  on  Member  States’  public 
finances. Government spending is projected to rise markedly, including for discretionary 
crisis-related measures,  while revenues from  taxes and fees will decline  on the back of 

2 

 
shrinking output. The Commission Spring 2020 forecast expects the average government 
deficit in the EU to rise from near-balance in 2019 to around 8½ % of GDP in 2020.  

This implies significantly higher sovereign financing needs for Member States, much of 
which  will  need  to  be  funded  in  a  short  period  of  time  and  under  market  conditions 
characterised by large uncertainty. Beyond the short-term, countries will unavoidably be 
left  with  significantly  higher  debt  to  be  financed  in  the  future.  The  increase  in 
government debt is a particular challenge for countries that entered the CoVid-19 crisis 
with  elevated  debt  and  deficit  levels.  Differences  in  access  to  financing  and  its 
affordability may constrain a country’s ability to respond adequately to the current crisis 
on its own. 

2. 

 UNEVEN IMPACT, DIVERGENT DYNAMICS 

The  containment  measures  will  have  a  devastating  impact  on  companies’ 
production  and  income  levels  in  2020,  though  with  large  differences  between 
sectors.  Most industries and services have seen significant restrictions being placed on 
them as part of the effort to stem CoVid transmission. Physical and operational aspects of 
business  models  largely  determine  the  degree  of  production  and  trading  bans.  Non-
essential  client-facing  businesses  or  those  involving  a  high  density  of  workers  or 
customers  have  generally  seen  the  largest  losses  in  turnover  and  profit.  Especially  the 
entertainment,  hospitality  and  transport  sectors  are  estimated  to  experience  the  largest 
losses  in  real  gross  value  added  in  2020,  ranging  from  20%  to  40%  compared  to  2019 
levels.  Corporate  earnings  are  expected  to  drop  very  sharply  in  2020;  for  many 
companies, the resulting cash flow difficulties risks pushing them to the brink of failure 
within only a few months of quasi-lockdown (see also section 3.1).  

The differing impact across  industrial ecosystems and sectors are clearly  reflected 
in  confidence  indicators.  Confidence  in  services  sectors  seems  more  affected  than  in 
manufacturing. The least favourable outlook is  that of the tourism ecosystem,  followed 
by  the  automotive  and  textile  industries,  with  record-low  sentiment  readings  being 
fuelled by pervasive current and expected weaknesses in both demand and supply factors. 
By  contrast,  the  health  and  —  to  a  lesser  extent  —  retail  trade  ecosystems  show 
comparatively  high  levels  of  confidence  indicators,  partly  owing  to  continued  robust 
demand.  

The  economic  impact  of  the  crisis  will  differ  greatly  across  Member  States.  Some 
had  the  misfortune  of  being  hit  harder  by  CoVid-19  than  others.  But  the  impact  also 
depends on Member States’ economic structures and capacity to  absorb and respond to 
the  resulting  economic  shock,  including  through  financial  buffers  in  the  public  and 
private  sector.  The  relative  weight  of  the  aforementioned  hard-hit  sectors  in  a  Member 
State’s economy is an important determinant of the gravity of the economic shock. The 
CoVid-19  crisis  has  affected  economies  with  sizeable  tourism  sectors  particularly 
severely.  Equally,  economies  with  underdeveloped  capital  markets  and  those  whose 
structure  is  mainly  based  on  small  and  very  small  enterprises  will  also  face  more 
difficulties to their limited access to financing sources. As a result, GDP losses in 2020 
are expected to be particularly large in Greece, Spain, Italy and Croatia, at around 9½% 
each,  compared  to  recessions  of  between  6 %  and  7½ % in  most  other  Member  States. 
Furthermore,  the  economic  impact  of  the  crisis  also  differs  substantially  across  regions 
within countries, showing a pronounced impact of the crisis in all corners of the EU (see 
Chart 2 below). 

3 

 
Chart 1: Confidence Indicator of EU Industrial Ecosystems: Current and Expected Supply and 
Demand Factors, April 2020. 

Source: Joint Harmonised EU Programme of Business and Consumer Surveys data. 
Note:  The  indicators  show,  for  each  ecosystem,  the  confidence  indicator  (red  bar),  the  assessment  of 
current  supply  factors  (dark  blue  bar),  the  assessment  of  current  demand  factors  (light  green  bar),  the 
expectations about future supply factors (light blue marker), and the expectations about future demand 
factors (dark green marker). Depending on the sector, supply factors refer to the indicators on observed 
production  trend, business  situation  development  and  production  expectations;  demand  factors  refer  to 
the indicators on reported evolution of demand, order-book levels and expectation about demand. 

Some labour markets will register severe employment losses. The sharp drop in real 
GDP will cause large employment losses in countries suffering most under CoVid-19 and 
its economic fallout. For instance, four Member States are expected to witness job losses 
of more than 5 % in 2020 (France, Italy and Spain and Estonia). By contrast, the majority 
of EU Member States are likely to see their respective employment levels fall by no more 
than 3% in the same period. More worrying still, the degree of recovery in employment 
levels  in  2021  is  particularly  weak  in  countries  severely  hit  by  pandemic,  but  also  in 
many  converging  Member  States.  For  instance,  while  some  countries  will  have  fully 
recouped  earlier  job  losses  by  2021,  in  seven  Member  States  —  predominantly  ones 
located in  Central  and Eastern Europe  —  employment  levels  are likely to  remain more 
than  2%  below  2019  levels.  The  expected  rise  in  unemployment  across  the  EU  may 
prove particularly hard to overcome in Member States where unemployment was already 
at  high  before  the  crisis,  where  the  recovery  is  anticipated  to  be  sluggish,  or  labour 
markets and social safety nets lack efficiency and effectiveness. 

4 

-60-50-40-30-20-10010Confidence indicator, indexConfidence IndicatorCurrent Supply FactorsCurrent Demand FactorsExpected Supply FactorsExpected Demand Factors 
 
 
 
 
 
 
Chart 2: GDP impact at regional NUTS 2 level excluding the impact of policy measures 

Source: JRC 
Note:  The  analysis  is  carried  out  using  the  RHOMOLO  macroeconomic  framework,  a  numerical-spatial 
general equilibrium model based on regional account  data and a set  of fully observed bilateral final and 
intermediate shipments consistent with the national accounts. The economic disturbances implemented in 
RHOMOLO are consistent with the 2020 Spring Forecast. 

Some countries  are able to provide far more  generous support to their economies. 
Many  of  the  EU  countries  currently  hit  hardest  entered  the  CoVid-19  crisis  on  weaker 
budgetary footing and with low macroeconomic resilience due to a mix of legacy factors 
and  policy  choices.  Starting  positions  differ  according  to  the  extent  of  debt  overhangs 
from the preceding decade, fiscal deficits, private sector financial buffers and the strength 
of social safety nets. The Spring Forecast expects budget balances in 2020 to deteriorate 
across  the  board  as  weaker  output  shrinks  the  revenue  base  and  government  spending 
rises.  Overall,  the  primary  government  balance  (i.e.  the  difference  between  current 
revenues and expenditures) will worsen in 2020 by around 7½ percentage points of GDP 
on  average  for  the  EU27.  The  countries  most  affected  by  CoVid-19  have  tended  to 
extend comparatively low levels of discretionary support to their economies in the form 
of additional spending and tax relief. In these countries, the deterioration of the primary 
balance was largely accounted for by the economic impact of the recession. This supports 
the conclusion that more vulnerable EU countries have been hit harder by the crisis and 
— due to lower resilience, weaker fiscal positions and a larger economic shock — have 
been constrained in their ability to take adequate support measures. 

5 

 
 
 
 
 
The support through the temporary State Aid framework also varies widely. Based 
on data available on 1 May 2020, the approved aid measures in the Member States (and 
the  UK)  to  address  the  COVID-19  outbreak  totalled  about  €1.9trn.3  The  breakdown  of 
this  total  by  country  shows  a  stark  disparity  across  Member  States.  For  example, 
Germany accounts for €996bn, equivalent to around 29% of German GDP and 52% of all 
State Aid provided, followed by France (around €324bn, 13.4% of GDP), Italy (around 
€302bn, 17% of GDP) and Belgium (around €54bn, 11% of GDP). The  aid  granted by 
the vast  majority of the  other Member States ranges in  the lower-single digits  of GDP, 
including Spain  with  around €27bn (2.2% of GDP). Although partly reflecting national 
policy  preferences,  the  disparity  in  support  volumes  across  Member  States  is  also 
affected  by  the  available  fiscal  headroom.  Leaving  normative  considerations  on 
individual State aid levels aside, large differences between Member States can exacerbate 
the divergence of recovery speeds and skew competitive positions in the Single Market. 
Furthermore,  binding  financial  constraints  in  some  Member  States  may  prevent  them 
from delivering sufficient support relative to the needs of their economy.  

The crisis risks harming the least resilient and still-converging Member States most. 
This will increase divergence, tilt the economic playing field and undermine the Single 
Market.  The  different  starting  positions  in  relative  income  levels,  budget  balances  and 
debt  levels  are  bound  to  further  reinforce  existing  divergences.  Member  States  with 
stronger starting positions can afford to provide more generous and long-lasting support 
to  business  and  households  without  facing  significant  funding  problems  or  prohibitive 
rises  in  sovereign  yields.  Member  States  with  more  limited  resources  and  policy  space 
will find their ability  to  meet  the  economic  and  social  needs of their citizens impaired. 
These countries will likely also face a slower recovery — an expectation that the Spring 
Forecast confirms. By the end of 2021, real GDP levels will be more than one percentage 
point  below  pre-CoVid  levels  in  at  least  half  a  dozen  Member  States,  including  those 
affected most by the pandemic. In the longer term, economically weaker countries may 
also  face  lower  rates  of  investment  and  growth,  higher  and  more  persistent 
unemployment, and less favourable debt dynamics. Finally, weaker banking systems will 
struggle to cope with the rise in non-performing loans, potentially reducing credit to the 
real  economy  and  denting  the  recovery.  This  effect  would  be  magnified  for  countries 
where capital markets are underdeveloped and unable to supplement bank financing. In 
the absence of strong European policy response some Member States may get stuck in a 
situation  of  prolonged  sluggish  growth,  high  unemployment  and  a  permanently 
weakened corporate sector, resulting in growing cross-country divergences. 

For the Union as a whole the crisis entails large fundamental risks. It would lead to a 
permanent  distortion  of  the  level  playing  field  of  the  Single  Market  and  increased 
divergence  of  living  standards.  These  two  effects  would  be  economically  harmful, 
jeopardising  competition,  trade  and  investment  across  the  Single  Market  and  further 
aggravating  Europe’s  long-term  growth  challenges.  Virtually  all  European  industrial 
ecosystems  rely  on  complex  supply  chains  spread  across  several  Member  States.  The 

3  Includes  COVID-19  aid  measures  approved  by  the  Commission  based  on  the  State  aid  Temporary 
Framework and Articles 107(2)(b) and (3)(b)TFEU. 1)). This does not include support that countries 
may have granted support without needing Commission approval (e.g. general measures for the whole 
economy such as “Kurzarbeit” schemes and/or aid measures that are block-exempted from approval by 
the  Commission).  There  are  important  caveats  about  the  data,  which  e.g.  might  have  been  based  on 
different  assumptions,  do  not  reflect  economic  effect  of  measures,  are  based  on  the  budgets  of  the 
notified  measures,  not  the  aid  element  involved.  Irrespective  of  this,  they  can  still  serve  as  a  first 
indication of potential trends as regards support measures in the current crisis. 

6 

 
                                                 
reliance of value chains on the Single Market is much more pronounced than the reliance 
on  extra-EU  suppliers.  Disrupted  supply  chains  reverberate  across  European  countries, 
potentially causing a vicious cycle of reduced inputs and outputs. (See Box 1) 

BOX 1 - ZOOMING INTO THE MOBILITY ECOSYSTEM  

Within complex ecosystems, the health of the whole depends on the strength of each individual 
component,  and  on  the  ability  of  the  system  to  swiftly  support  any  weakened  elements.  The 
Single Market has provided the right environment for firms, citizens and institutions to create 
complex and resilient ecosystems able to do just that.  

A  coordinated  recovery  must  factor  in  these  large  interlinkages  across  sectors  and  firms, 
spreading across all Member States. While the Covid-19 crisis represents a symmetric shock, its 
impact on countries will be asymmetric. However, if parts of an ecosystem is held back due a 
difficult economic situation in one region or country, the whole ecosystem will suffer. If a firm in 
one Member State is ramping up again in a supportive economic environment, but its suppliers 
are  in  another  country  where  the  situation  remains  difficult,  the  expected  recovery  will  not 
materialise,  and  money  will  not  be  used  effectively.  The  ties  on  which  the  ecosystem  relies 
would be loosened by result weakening the single market. The lens of ecosystems allows us to 
identify bottlenecks across the single market, and identify the critical policy levers to revitalise 
them.  

The mobility and automotive ecosystem accounts for around 5% of total EU value added. While 
carmakers  are  generally  large  companies,  the  size  of  suppliers  varies  much  more,  with  a  few 
major companies and a large number of SMEs and midcaps spread all over Europe and beyond. 
The automotive segment alone is composed by 1.4 million companies, including motor vehicles 
(cars, vans, trucks, motorbikes), parts and accessories supplier, tractors, batteries, metalworks, 
dealerships, parts retail & repairers, logistics and mobility services. Yet, the ecosystem extends 
beyond these. A number of financial institutions, sometimes owned by manufacturers, provide 
credit and insurance to final clients and support the dealers’ network. Universities and research 
institutions  are  involved  in  R&D  activities  to  design  the  clean,  safe  and  smart  mobility  of  the 
future,  ranging  batteries  and  digital  services.  R&D  investments  in  automotive  reached  €57.4 
billion in 2018, i.e. 28% of EU spending (source ACEA). Major original equipment manufacturers 
have  developed  strong  ties  with  the  academic  world  either  through  education  partnerships 
(including  vocational  training)  or  through  research  programs.  Public  investments  in  satellite 
technologies  and  industry innovation  cross-fertilise  each  other  resulting  in  a  range  of  services 
for mobility, increasing security, avoiding congestions and offering new business opportunity for 
data analysts. A fast growing recycling industry cooperates with manufacturers to reduce waste, 
decrease production costs and reduce EU dependency on foreign materials.  

Mobility is the most integrated ecosystem in intra-EU value chains, as it relies for almost half of 
its  total  production  (45.3%)  on  cross-border  value  chains  within  the  Single  Market.  This  is 
particularly  relevant  for  the  most  innovative  products,  as  electric  cars.  While  most  of  the 
European  production  is  concentrated  in  relatively  few  Member  States,  the  exposure  to  other 
countries is very significant. 

In the case of Germany, for instance, although most of the value added of the average motor 
vehicle is produced domestically (76.6%), when it comes to the various components necessary 
for the production, manufacturers and service providers depends heavily on foreign sources of 
intermediate  goods.  Almost  70%  of  value  added  originates  abroad.  A  very  large  number  of 
SMEs,  highly  specialised  in  specific  segments  of  the  value  chain  (exhausts,  interior  fittings, 
precision  tooling,  etc),  are  located  in  Member  States  as  Hungary,  Czech  Republic,  but  also 
France, Spain and Italy, where they play  fundamental role for the ecosystem.  

7 

 
Growing  divergences  contradict  the  European  ideal  and  our  common  objectives, 
and  could  undermine  the  European  integration  process.  Furthermore,  a  failure  to 
uphold the social dimension of our market economy would jeopardise one of its proudest 
features  and  harm  the  common  objectives  of  the  European  Pillar  of  Social  Rights. 
Counteracting  the  divisive  economic  forces  unleashed  by  the  crisis  requires  additional 
resources  that  ease  the  burden  on  the  hardest-hit  members.  Suitably  equipped  with 
instruments to offset the centrifugal forces of divergence, the EU budget and support for 
structural reform measures can help crisis repair and recovery efforts, as well as longer-
term investment challenges for the twin transition to a green and digital economic future. 

Common action at EU level will be instrumental to address immediate crisis-related 
needs  as  well  as  to  sustain  long-term  potential  growth.  The  revised  EU  long  term 
budget – the Multiannual Financial Framework – with targeted policy priorities and more 
modern delivery tools, and reinforced by the Union Recovery Instrument can leverage a 
substantial amount of investments, foster cross-country convergence and innovation and 
ensure the well-functioning of the single market.    

3. 

INVESTMENT AND FINANCING NEEDS 

This  section  provides  an  analysis  of  the  needs,  identifying  three  types  of  needs:  equity 
repair  needs,  investment  needs  (public  and  private),  and  social  spending  needs.  It  also 
discusses the link to sovereign  financing needs.  The different types of needs  cannot  be 
simply added to obtain overall investment needs as they may (partly) overlap such that 
addressing  one  investment  gap  will  also  reduce  the  other.  The  analysis  of  investment 
needs  is  made  against  the  backdrop  of  the  EU’s  objective  to  strive  for  inclusive  and 
sustainable  growth.  The  financing  of  an  investment-led  recovery  should  be  in  full 
alignment  with  EU’s  policy  goals  in  terms  of  digitalisation,  decarbonisation  and 
sustainability. 

3.1.  EQUITY REPAIR NEEDS 

The ability of the European economies to return to growth depends on the resilience and 
adaptability of the private sector. The Covid-19 crisis has a major impact on the liquidity 
and  equity  position  of  non-financial  corporations  (NFCs).4  Solvency  concerns  impinge 
strongly  on  both  non-financial  corporations  and  unincorporated  businesses,  the  latter 
being the main income source of many households. In the most vulnerable sectors — and 
for viable firms that start from a weaker position — solvency support may be necessary 
to allow them to stay in business and resume investments and employment growth as the 
recovery takes hold.  

This  section  provides  estimates  of  the  impact  of  the  crisis  on  corporate  equity  and 
assesses  equity  repair  needs  in  2020  and  2021  using  a  multi-dimensional  approach.  To 

4 The containment measures lead to a very sharp drop in production and turnover. Firms are likely to react 
to  this  by  scaling  back  production,  postponing  capital  expenditure,  cutting  dividends  (and  share 
buyback programmes) and spending down cash reserves. The running down of cash reserves and the 
cuts in dividends have a direct impact on equity value of firms. Financial analysts have estimated that 
in 2020 EU listed corporates will spend down cash reserves to the tune of €550bn and cut dividends by 
€90bn in 2020 alone. See e.g.  https://www.bridgewater.com/research-library/daily-observations/greg-
jensen-20-trillion-hit-to-global-corporations/ 

8 

 
 
                                                 
assess  the  impact  of  the  Covid-19  crisis  on  corporate  equity  it  applies  firm-level  data 
analysis  from  the  ORBIS  database.  To  gauge  the  sectoral  distribution  of  losses  it 
combines  this  analysis  with  market-based  information  on  the  pricing  of  credit  default 
swaps to calculate implicit default probabilities and expected losses on corporate debt.  

To  the  greatest  extent  possible,  the  following  needs  assessment  is  consistent  with  the 
macroeconomic  projections  from  the  Spring  2020  Forecast  in  terms  of  GDP  trajectory 
and  impact  by  industry.  In  addition  to  the  central  scenario  presented  by  the  Spring 
Forecast (in which a progressive re-opening of economies during the second quarter 2020 
is  assumed),  the  following  needs  assessment  also  considers  a  stress  scenario,  which 
illustrates a longer containment phase with a correspondingly deeper and more drawn-out 
recession.  As  noted  in  the  Spring  Forecast,  fundamental  uncertainty  surround  the 
economic outlook and the downside risks are particularly large. 

3.1.1.  The impact on corporate equity based on firm-level data  

The crisis will impact firms’ balance sheets and capital structure through falls in revenues 
and accumulation of losses. The magnitude of this effect has been estimated with firm-
level  data  from  the  ORBIS  dataset.5  Using  balance  sheet,  income  and  cash  flow 
disclosure  statements,  the  analysis  estimates  the  impact  of  the  economic  downturn  on 
firms’  profits/losses,  taking  into  account  the  implicit  solvency  support  provided  by 
governments through short term work schemes.6   

Equity  recapitalisation  will  be  required  to  offset  the  actual  losses  (i.e.  negative  net 
profits)  incurred  during  the  downturn  and  (at  least  partially)  restore  balance  sheets  of 
companies.  

The results of this initial analysis show that in case the baseline economic scenario from 
the  Spring  Forecast  economic  materialises  total  losses  to  be  incurred  by  firms  could 
exceed €720bn by the end of the year and would increase to above €1.2trn in the stress 
scenario.7  These  losses  translate  directly  into  a  deterioration  of  the  leverage  ratio  of 
corporates because they erode companies’ liquid assets. In turn, this limits their capacity 
to borrow, invest and grow. Additional needs for equity may arise to the extent that firms 
have to increase their indebtedness to meet the need for additional liquidity, leading to an 
increase  in  their  leverage  ratios  (e.g.  debt/equity  ratios).  As  highlighted  in  the  Spring 
Forecast the risks to the baseline scenario are clearly tilted to the downside. 

The actual degree of equity recapitalisation that is likely to be required to avoid corporate 
defaults  in  the  short-term  need  not  be  identical  with  the  incurred  losses.  Firms  with 
strong balance sheets can partially weather the incurred losses by relying on liquid assets 
and working capital buffers. Additional simulations therefore estimate how firms can use 
these two first lines of defence to  absorb the losses and what the outstanding financing 

5  Annex  I  documents  this  analysis  in  a  greater  detail.  In  view  of  important  uncertainties  and  data 
limitations,  the  simulations  are  based  on  rather  conservative  technical  assumptions  and  the  results 
should be seen as providing lower bounds for the needed equity repair. 

6 The simulations reported in the Annex I also consider, in a stylised form, additional policy measures such 
as deferred tax and interest payments. Further measures that Member States have introduced to support 
companies, e.g. loans or guarantees, are not modelled. 

7 The stress scenario corresponds to the “longer lasting” adverse scenario as described in the Commission’s 

Spring Forecast. 

9 

 
                                                 
shortfall would be (referred to  in  Chart 3 as  the cash buffer and working capital  buffer 
scenarios).8 

Chart 3: The results of the micro-simulations  

Source: Commisison services 

The  estimates  show  that  between  25%  and  35%  of  companies  would  experience  a 
financing shortfall by the end of the year after exhausting working capital and liquidity 
buffers,  respectively.  In  the  adverse  scenario,  these  shares  could  increase  to  35%  and 
50%, respectively.  

This means that around 180,000-260,000 of European companies employing around 25-
35 million employees could experience a financing shortfall should the adverse scenario 
materialise.  The  corresponding  liquidity  shortfall  to  be  covered  could  range  between 
€350bn  and  €500bn  in  the  baseline  scenario,  and  between  €650bn  and  €900bn  in  the 
adverse  scenario.  The  sectors  showing  the  greatest  share  of  firms  facing  liquidity  and 
working  capital  shortfalls  are  wholesale  and  retail  trade,  accommodation  and  food 
services, and transport industries (see Chart 4 below for the case of liquidity; results for 
working capital are broadly similar). These firms will face an acute risk of bankruptcy.  

8  The  “liquidity  buffer”  simulations  assume  that  all  firms  can  deplete  their  cash  reserves  to  (at  least 
partially) cover the losses. As a result, the volume of financing shortfall is smaller than the volume of 
accumulated losses. The “working capital” simulations consider that firms can also deplete other liquid 
assets,  beyond  cash.  In  such  a  case,  the  firm  can  sell  off  all  liquid  assets  but  only  to  the  extent  that 
these assets are larger than its current liabilities. Eventually, the shortfall of working capital is a good 
approximation  of  needed  equity  replenishment,  under  the  assumption  that  firms  cannot  (quickly) 
deplete their fixed assets. 

10 

0200400600800100012001400No bufferCash bufferWorking capitalbufferFinancial Shortfall BaselineStressbn EUR0%10%20%30%40%50%60%70%80%No bufferCash bufferWorking capitalbufferShare of distressed firmsBaselineStress 
 
 
 
 
 
 
 
 
 
 
                                                 
Chart 4: Share of firms with at least 20 employees with a liquidity shortfall by December 2020, 
by sector.   

C – Manufacturing; F – Construction; G45 – Wholesale and retail of motor vehicles; 
G46 – Wholesale except motor vehicles; G47 – Retail except motor vehicles; H49 – Land transport; 
H50 – Water transport; H51 – Air transport; I – Accommodation and food services; 
J – Information and communication; M – Professional, scientific, technical activities; 
N – Administrative, support service activities 
Source: Commission services, analysis based on ORBIS.  

The cash and working capital shortfalls may translate into a higher risk of default for a 
substantial share of firms, which were in a vulnerable situation already before the start of 
the crisis. A large share of the affected companies already have a relatively high leverage 
or low profitability, which will severely constrain their ability to tap alternative sources 
of financing. Both baseline and stress scenarios show that, by the end of 2020, between 
60 and 75% of the total shortfall is attributable to firms that are financially vulnerable.9 It 
indicates that a substantial share of the liquidity needs is likely to fall within firms that 
may be unable to get access to additional sources of financing. 

3.1.2.  Credit market-based assessment  

Additional  information  about  the  extent  and  distribution  of  losses  across  corporate 
sectors can be obtained from financial market data. The uncertainty and increased risks 
of  corporate  defaults  translate  into  higher  risk  premia  and  possible  credit  rationing, 
particularly  for  more  risky  companies.  The  10-year  BBB  corporate  bond  spread  over 
German  Bunds  peaked  at  close  to  300bps  in  mid-March,  jumping  by  some  150bps 
compared  to  its  level  before  the  CoVid-19  outbreak.  Corporate  bond  yields  data  by 
country show that similar increases of over 100bps have been observed in the investment 
grade  segment  across  the  largest  euro  area  Member  States.  However,  available  indices 
for  credit  default  swaps  (CDS)  suggest  that  financing  conditions  have  tightened  much 
more significantly for high-yield non-financial corporates, with the CDS spread of high-
yield  non-financial  corporates  increasing  by  close  to  450bps  by  mid-March.  These 

9 A firm is considered to be financially vulnerable when it is situated in the top leverage quartile (defined 
as the ratio of total debt to total equity) or in the bottom profitability quartile (defined as the ratio of 
EBIT to turnover). 

11 

01020304050607080TotalCFG45G46G47H49H50H51IJMNShare of distressed firms,cash bufferBaselineStress% 
 
 
 
                                                 
developments suggest that investors have become more risk averse and also see increased 
risks  of  corporate  failure,  particularly  among  the  more  vulnerable  firms  and  sectors. 
Moreover,  cost  of  capital  may  increase  for  those  firms  as  a  significant  share  of 
investment grade bonds is expected to be downgraded to high-yield bonds.  

Chart  5  shows  the  implied  risk-neutral  probability  of  default  (within  5  years)  based  on 
Credit Default Swaps (CDS) for selected sectors. The implied probability of default has 
risen particularly sharply in the following sectors: leisure, metals and mining, transport, 
media and auto manufacturing. In most sectors, market-based default risks have declined 
since early April, while remaining elevated in the leisure and transport sectors. Based on 
the  increase  in  implicit  probability  of  default,  the  expected  default  losses  using  an 
industry standard loss-given-default (LGD) would be around €200bn. As bond investors 
internalise in their analysis the ability of the firms to restore equity via lower dividends to 
existing  shareholders,  raising  equity  on  the  market  and  the  policy  support  in  place  and 
expected from  Member  States and EU institutions,  this number cannot  be equated with 
equity repair needs. The analysis however, provides some indication about the sectorial 
distribution of recapitalisation needs.     

Chart 5: EU CDS based Probability of Default by sector 

Source: JRC based on sector data from Refinitv Thomson Reuters Datastream CDS indices 
Note: The probabilities of default are calculated using the ISDA standard model for CDS. The probabilities 
are bootstrapped using as an input the EUR term structure from 6 months to 5 years and the quoted CDS 
spread by sector.  

3.1.3.  Conclusions on equity repair needs 

While is  a difficult  to  precisely quantify  equity  repair needs  given the many modelling 
assumptions involved, simulations using firm-level data suggest that these needs could be 
around €720bn in 2020 in case the baseline scenario underlying the Spring Forecast 
were  to  materialise.  These  needs  would  be  significantly  higher  in  case  the  lockdown 
measures  stay  in  place  longer  than  assumed  in  the  baseline  scenario  of  the  Spring 
Forecast. In the longer-lasting confinement scenario presented in chapter 3 of the Spring 
Forecast, the damage to corporate equity in the EU could be as big as €1.2trn.  

12 

010203040EU CDS based PoDs, by sector and by week, risk neutral probabilitiesWeek1 JanWeek1 FebWeek4 FebWeek1 Apr% 
 
 
 
The  equity  repair  needs  are  heavily  concentrated 
the  following  sectors: 
accommodation  and  food  service  activities;  arts,  entertainment  and  recreation;  and  to 
some lesser extent wholesale and retail trade; transportation; and manufacturing. 

in 

Chart 6: Real gross value added by industry, % change over 2019 

Source: Commission services 

If  left  unaddressed  the  capital  shortfalls  may  lead  to  a  prolonged  period  of  lower 
investment  and  higher  unemployment.  Whilst  solvency  and  sustained  credit  insurance 
support  can  prevent  companies  from  bankruptcy,  this  alone  will  probably  not  be 
sufficient to restore the investment capacity of the corporate sector (see section 3.2). The 
impact  of  the  capital  shortfall  will  be  uneven  across  sectors  and  Member  States,  with 
negative  consequences  for  integrated  supply  chains  in  internal  market.  This  is 
compounded by the fact that the capacity of Member States  to  provide state aid  differs 
greatly, affecting the level playing field.  

3.2. 

INVESTMENT NEEDS 

Investment  is  forecast  to  be  significantly  affected  by  the  crisis  due  to  lower  levels  of 
demand, higher uncertainty, supply side constraints on investment (lacking availability of 
raw materials, capital equipment, labour) and worsening financial conditions (mainly due 
to losses in equity of firms and impacts on the banking sector’s lending capacity). 

The short-term impact of the crisis on aggregate EU27 investment is almost exclusively 
registered in the private sector. However, both public and private sector investment were 
clearly insufficient already on pre-crisis trends as described below. The analysis at hand 
distinguishes between three different investment needs.  

  Basic macroeconomic investment gaps due to  the crisis  impact,  relative to  the 

baseline (see section 3.2.1)  

  Additional  investment  needs  revealed  by  the  crisis,  such  as  the  excessive 
reliance  on  third  countries  for  strategic  supply  chains,  including  for  essential 
medical equipment (see section 3.2.2). 

  Investment  needs  irrespective  of  the  crisis,  including  additional  needs  to 
achieve the Green transition and Digital transformation (see sections 3.2.3) and to 

13 

-45-40-35-30-25-20-15-10-50Arts,entertainment &recreationAccommodationand foodservicesTransportationand storageWholesale andretail tradeManufacturingConstructionProfessional,technical andbusinesssupport services% change in GVA, 2020Impact on real gross value added by industry, EU27  
 
 
avoid  a  decline  in  the  ratio  of  the  public  sector  capital  stock  to  GDP  (section 
3.2.4). 

These actual needs should be contrasted with further potential needs that may materialise 
in  case  the  central  forecast  scenario  of  the  Spring  Forecast  proves  too  optimistic.  In 
particular,  an  additional  public  investment  gap  will  open  up  if  EU  governments  scale 
down  public  investment  in  response  to  the  impact  of  the  crisis  on  budget  deficits,  debt 
and sovereign financing  needs.  In view of the experience following the 2008/09  global 
financial crisis, this risk is considerable. 

3.2.1.  Closing the basic private sector investment gap 

This  analysis  constructs  a  baseline  scenario  using  the  Autumn  2019  Forecast  trajectory 
for economy-wide investment. Setting this against the Spring 2020 Forecast projections 
reveals a cumulative drop in investment that is estimated at €846bn in 2020 and 2021 
taken  together,  of  which  €831bn  is  accounted  for  by  lower  private  investment.10  This 
sharp reduction in private sector investment can be viewed as an attempt by companies to 
shore up cash positions in the face of collapsing turnover and profits. The investment gap 
concerns  all  types  of  investment  assets  and  differs  substantially  across  Member  States 
(Chart  8).  Addressing  the  profit-related  equity  gap  of  the  corporate  sector  (section  3.1) 
would be an important, but not sufficient step in restoring the investment capacity of EU 
non-financial  corporations.  In  view  of  the  weakened  corporate  balance  sheets  and 
elevated uncertainty, instruments  providing  additional sources of risk finance are likely 
to be necessary to stimulate investments.  

Chart 7: Basic investment gap of non-financial corporations by type of investment asset (2020-
2021 cumulative) 

Note:  The  basic  investment  gap  is  defined  as  the  total  of  2020  and  2021  (equipment/construction) 
investments  as  projected  in  the  2019  Autumn  Forecasts  minus  the  same  total  as  projected  in  the  2020 
Spring Forecast. Here as a share of 2021 GDP. 

Source: Commission services 

10   Note that due to the large slack in the economy due to the CoVid crisis, additional investment is likely 
to  have  limited  crowding  out  effects.  Model  simulations  of  investment  increases  to  meet  the  EU’s 
current 2030 climate and energy policy goals (see below) assumed that the economy operates at full 
capacity. In such context any increase in investment across the economy must be met by a decrease in 
private consumption through a reallocation of resources. 

14 

-7-6-5-4-3-2-10CYSIESHUMTIEROELBGLVBEFRDKEELUCZEUEA19PLATNLSKITFISEDEPTLTShortfall in Construction investment spending, 2020-21 cumulative% GDP -7-6-5-4-3-2-10ROIEELHUSESISKBGCZPTESEEBEEUITLTATEA19LVPLDKFIDENLLUFRCYShortfall in Equipment investment spending, 2020-21 cumulative% GDP 
 
 
                                                 
3.2.2.  Additional  investment  to  correct  vulnerabilities  exposed  by 

the CoVid-19 crisis 

The  crisis  has  exposed  certain  vulnerabilities  of  the  EU,  such  as  excessive 
dependence  on  imports  of  critical  goods  and  services,  whose  supplies  were 
disrupted.  Europe  should  therefore  strive  to  strengthen  its  strategic  autonomy  by 
reducing  excessive  import  dependence  for  the  most-needed  goods  and  services  such  as 
medical products and pharmaceuticals,11 critical materials and key enabling technologies, 
food,  strategic  digital  infrastructure  (e.g.  5G,  quantum  communication  infrastructure), 
security  and  other  strategic  areas  (e.g.  space  and  defence).  Reducing  dependency  does 
not  require  producing  everything  at  home  or  closer  to  home.  For  some  sectors  and 
industrial ecosystems, autonomy can be achieved through diversifying and strengthening 
global  supply  chains  (e.g.  provision  of  some  medical  products).  For  ecosystems 
considered more strategic, it may require increasing supply capacity within the EU Single 
Market (e.g. Aerospace). The size and diversity of the EU Single Market allows for such 
a commitment and allows for striking a good balance between allocative efficiency and 
strategic autonomy. Additional investments in both infrastructure and innovation will be 
needed  (as  done  via  the  European  Batteries  Alliance  to  ensure  strategic  autonomy  for 
electric cars). Avoiding undue third-country control of strategic EU assets (e.g. via FDI 
screening) will also contribute to maintaining a sufficient level of strategic independence. 

Relevant  sectors/economic  activities  for  strategic  autonomy  mentioned  in  the  New 
Industrial Strategy Communication are:12   

  Strategic  digital  infrastructures  (5G,  cybersecurity,  quantum  communication 

infrastructure) 
  Key  enabling 

technologies: 

robotics,  microelectronics,  high-performance 
computing  &  data  cloud  infrastructure,  blockchain,  quantum  technologies, 
photonics, 
nanotechnologies, 
industrial 
pharmaceuticals, advanced materials.  

biotechnology, 

biomedicine, 

  Defence & Space  
  Critical  raw  materials  crucial  for  e-mobility,  batteries,  renewable  energies, 

pharmaceuticals, aerospace, defence and digital applications 

  Medical products & pharmaceuticals. 

The resilience of these industries and their capacity to continue to meet the needs of 
EU  citizens  calls  for  some  additional  investments  in  the  short  term.  A  tentative 
estimate in view of high uncertainty is €20bn per year in the short run. In the medium- to 
long  term,  such  investments  would  have  to  focus  on  strategic  supply  chains  and  large-

11  APIs  (active  pharmaceutical 

ingredients)  constitute 

the 
pharmaceuticals supply chain. EU accounts for 27.9 % of the world’s API production (60.5 % being 
produced  in  China  and  India,  4.6  %  in  North  America  and  7%  in  the  rest  of  the  world).    Europe 
imports 80% of chemical raw materials and APIs from China and India, mainly for generics (67% of 
all  medicine  supplies  on  the  EU  market).  The  dependency  on  chemical  raw  materials,  necessary  for 
production  of  APIs,  is  considered  critical  worldwide  and  the  outbreak  and  the  spread  of  virus  has 
illustrated the vulnerability of the EU supply chains. 

important  component  of 

the  most 

12 COM(2020) 102 

15 

 
 
                                                 
scale  development  of  innovative  technologies,  such  as  5G,  and  production  capacity  in 
order to strengthen the resilience of the European economy.  

In  addition  to  these  investment-led  improvements  to  the  resilience  of  European  value 
chains,  businesses  throughout  Europe  are  likely  to  explore  options  to  enhance  their 
supply chains management in light of the CoVid-19 crisis, thereby improving Europe’s 
industrial resilience from the ground up.  

3.2.3. 

Investments  needs  to  deliver  the  green  transition  and  digital 

transformation 

The investment needs for delivering the green transition and digital transformation 
are  estimated  to  amount  to  at  least  €595bn  per  year  (€1.190bn  over  the  next  two 
years).  This  amount  includes  the  additional  investments  needed  to  reach  the  EU’s 
current  2030  climate  and  environmental  policy  goals,  which  are  around  €470bn  per 
year, and the EU’s needs to pursue digital transformation, which amount to €125bn per 
year.  

The total green investment needs cover not only the  current 2030 climate and energy 
targets (€240bn additional annual investment) but also investment needs to deliver 
on  Europe’s  wider  transport  infrastructure  (€100bn  per  year)  and  environmental 
objectives (€130bn per year). Member States in their draft National Energy and Climate 
Plans  already  plan  for  the  implementation  of  the  majority  of  additional  investments 
related  to  climate,  energy  and  transport  for  the  coming  years.13  Moreover,  these  
investment  needs,  shown  in  Table  1,  take  into  account  environmental  protection  more 
broadly, resource management (with the exception of energy), and additional investments 
into the circular economy.14 They notably include the 8th Environmental Action Plan, the 
Biodiversity Strategy, the Farm to Fork Strategy, the Circular Economy Action Plan, and 
the Zero Pollution Action Plan.  

It is not possible to quantify all green investment needs at the current stage, making 
the above estimate a conservative benchmark for adequate green investment levels. 
The above needs estimates do not yet include the foreseen increases in policy ambition, 
nor  the  strategies  for  various  environmental  objectives,  some  of  which  are  currently 
under  adoption  or  preparation.  In  this  context,  the  estimates  relating  to  the  broader 
environmental objectives do not account for investments into climate change adaptation 
— an important need in view of the EU economy susceptibility to future climate shocks 
and the natural catastrophes arising from them. Investments related to marine issues and 
areas covered under the Water Framework and Floods Directives are not included. They 
also only partially include investment needs for the agri-food sector.  

13 Communication assessing the 28 draft NECPs,  COM(2019) 285 final 
14  Investments  into  the  circular  economy  are  partially  addressed.  In  order  to  account  for  the  increased 
policy ambition of these initiatives, estimates will need to be adjusted and may need to be increased. 

16 

 
 
 
 
                                                 
 
Table 1: Sectoral breakdown of green transition investment gaps 

Given the rising importance of digital value chains and technologies with the potential to 
boost productivity and innovation, there are considerable needs for additional investment 
into the digital transformation. As Table 2 below shows, these amount to  €125bn per 
year  (€250bn  over  the  next  two  years).  The  EU  suffers  from  low  and  fragmented 
investments in digital capacities and infrastructures  and from a slow adoption of digital 
innovations  in  private  and  public  sectors,  which  weakens  the  entire  EU  digital 
ecosystem.15  

15 The main investment needs for the digital transformation are in telecommunications infrastructure. There 
is  consensus  among  experts  that  market  forces  will  not  guarantee  the  achievement  of  the  Digital 
Agenda  for  Europe  and  European  Gigabyte  Societies  targets.  According  to  a  recent  study 
commissioned by the EIB (forthcoming), the estimated investment needs to meet such targets as from 

17 

Climate mitigation and energy 2030 targetsWider environ- mental objectives, beyond climateTotal green transformationPower grids10-10Power plants20-20Total Renewable Energy30-30Residential energy efficiency115-115Business energy efficiency70-70Total Construction185-185Industrial/other energy efficiency Industrial energy efficiency, new efficient boilers5-5Vehicles, rolling stock, vessels and airplanes20-20Infrastructure - Core TEN-T network 30-30Infrastructure - Other interurban infrastructures35-35Infrastructure - Urban transport35-35Total Transport120-120Protection of ambient air and climate-4040Wastewater management-1515Waste management-1010Protection of soil, ground-/surface water-11Noise and vibration abatement-11Biodiversity landscapes / Agri-food-44Protection against radiation-55Environmental R&D-22Total Environmental protection-7777Management of waters-2020Management of forest resources-22Management of wild flora and fauna-11Management of materials and efficiencies-1010Resource management R&D-55Total Resource management (excl. energy)-3838Circular economy (beyond needs already included)Additional potential (based on EMF papers) in 3 sectors (food, mobility and built environment), informal expert view-1515340                      130                       470                         Sectoral breakdown of green transformation investment gaps (EUR bn, per year)Source: Commission services; Estimate for additional investments needs in the power, construction, industrial and transport (vehicles and rolling stock, excluding infrastructure) sector based on EUCO32-32.5 scenario, https://ec.europa.eu/energy/en/data-analysis/energy-modelling/euco-scenarios. Estimates of additional investment per year over the period 2021-2030 are relative to 2016 Reference, estimates per sector rounded to the nearest € 5 bn. Estimates not yet updated to include raising the ambition of GHG emission reductions to 50-55%. Climate change adaptation is not yet assessed and incorporated in climate figures. The European Green Deal initiatives, being rolled out currently, are only partly addressed yet. Environmental figures do not comprehensively cover marine issues. For the water domain, the Water Framework Directive and the Floods Directive still to be added to the assessment, as well as the most recent OECD-ENV water study results (not fully captured yet). SectorsResource management (excluding energy)Environmental protectionTransportConstructionRenewable energy 
 
 
 
                                                 
 
Table 2: Breakdown of Digital Transformation investment gaps 

3.2.4.  Additional investments to avoid the decline of the public capital 

stock  

Already before the crisis, the level of public investment in the EU27 was insufficient to 
keep the public capital stock constant as a share of GDP. Net public investment, i.e. gross 
fixed capital formation less consumption of fixed capital, amounted to only 0.3% in the 
EU27  in  2019,  a  level  which  would  —  if  maintained  —  result  in  a  declining  public 
capital stock as a share of GDP. Stabilising the capital stock in relation  to output so as 
not to erode the EU economy’s capacity to support future growth and prosperity would 
require  an  increase  in  public  investment  (compared  to  Spring  2020  Forecast  plans)  of 
about  €100bn  per  year16.  Public  investment  tends  to  be  lowest  in  Member  States  with 
high debt (Chart 8).  

To  maximise  complementarity  between  EU  policy  objectives,  the  annual  public 
investment increase required to stabilise the public sector capital stock should consist of 
investments that correspond to the investment needs of the green and digital transition as 
described  in  section  3.2.3.  To  the  extent  that  this  is  achievable,  the  two  needs  can  be 
netted out against each other so as to avoid double-counting of investment needs. 

2018 amount to €345-360bn for the EU27 (€380-395bn for the EU28). Expected private funding will 
cover  about  one  third  of  this  amount,  leaving  an  estimated  investment  gap  on  an  annual  basis  of 
around 42bn€ until 2025. As the private funding baseline was projected before he COVID crisis, the 
gap  may  have  increased  due  to  investment  cut  backs  in  the  private  sector  (that  are  covered  in  the 
cumulative investment drop estimated in section 3.2.1) In addition, there  are investment gaps for e.g. 
digital skills, high performance computing, AI, digitalisation of businesses, digitalisation of the public 
administration. 

16 Note that the €100bn investment gap to stabilise the capital stock as share of GDP is based on the current 
depreciation  rate  for  public  capital.  During  the  green  and  digital  transition  phase,  part  of  the  capital 
stock  will  have  to  be  replaced  before  it  has  reached  the  end  of  what  would  have  otherwise  been  its 
normal economic life. If the transition would lead to a depreciation rate of 7% instead of the current 
5,5%, the annual investment gap to stabilise the capital stock to GDP share would be around 190 bn.   

18 

Communication networks42HPC, Graphene and Quantu6Cloud11AI and Blockchain23Digital green technologies6Cybersecurity3Digital Innovations/ Data and Next Generation Internet5Semiconductor/Photonics17Digital skills9Common European data spaces3Total125                Source: DG CNECT estimates, 2 May 2020; The investment gap estimated as a difference between what EU competitors (US/China) and the EU invest (including both private & public)Investment gaps for digital transformation (EUR bn, per year) 
 
 
 
                                                                                                                                                 
Chart 8: Public sector net fixed capital formation versus gross government debt (average 2010-
2019, %GDP)  

Source: Commission services 

In addition to addressing these investment gaps, sustaining public investment levels 
at the levels projected in the Spring Forecast may prove challenging. It should be re-
emphasised that the estimates for the basic investment gap in the public sector are small 
(€15bn) as public investment levels are forecast to remain broadly unchanged compared 
to pre-crisis plans.  

However, the 2008-2009 global financial crisis illustrated that cutting public investment 
has  been  a  common  way  for  governments  to  limit  high  deficits  and  corresponding 
financing needs. This strategy came at the expense of economic growth in the medium to 
long run; investment levels a number of Member States with high debts (e.g. ES, IT, PT, 
and  EL)  have  never  recovered.  Therefore,  it  is  important  to  support  the  recovery  and 
foster potential growth through structural reforms and investments. This is to prevent the 
crisis from causing lasting damage to economic convergence between Member States. In 
addition,  emergency  EU  cohesion  policies  can  help  to  contain  economic  divergences 
across countries providing additional funding for the most important sectors investment 
to  repair  labour  markets,  including  through  employment  subsidies,  short  time  work 
schemes  and  youth  employment  measures,  support  to  health  care  systems  and  the 
provision  of  essential  liquidity  and  solvency  support  for  small-  and  medium-sized 
enterprises.  

19 

BEBGCZDKDEESFRITPTNLEEELCYLVLTLUHUMTHRATPLIEROSISKFISEUKEAy = -0.0145x + 1.7442R² = 0.4543-1-0.500.511.522.5020406080100120140160180Average NFCF2010_2019(%GDP) average GG debt in 2010-2019Net public investment and government debt%GDP%GDP 
 
 
 
 
 
3.2.5.  Conclusions on investment needs 

Table 3 provides an overview of the basic investment need due to the crisis impact, the 
additional investment needs to stabilise the public sector capital stock to GDP ratio, the 
investment  needs  for  the  green  transition  and  digital  transformation  and  the  needs  for 
strategic  investment.  While  these  needs  can  be  quantified  individually  with  a  broad 
degree of precision, they cannot be simply summed to calculate an overall economy-wide 
investment  gap.  In  particular,  addressing  the  basic  investment  and  public  sector 
investment gap may well lead to increased energy efficiency-enhancing investment or of 
a digital nature. Given the potential overlap of basic investment needs and those to ensure 
the  green  transition  and  digital  transformation  and  in  view  of  inherent  uncertainty  on 
additionality17, an aggregate conservative minimum investment need can be obtained by 
allowing  for  a  certain  degree  of  overlap  when  summing  the  basic  and  additional 
investment needs in the following table. 

Table 3: Overview table of investment gaps 

In total, the overall EU27 investment needs described in this section (public and private) 
amount to  at least €1.5trn in 2020 and 2021 in addition to the baseline assumed in 
the Spring Forecast. Realising these investments now would serve a double purpose: a 

17 Even if the sector-based assessments take full account of the extent to which new investment is  net of 
substitution and replacement investments (e.g. old vehicles are replaced by energy efficient low emission 
vehicles at the end of their economic life), it does not consider the scope for reallocation of investments 
and  the  extent  to  which  existing  policies  at  EU  or  national  level  address  the  investment  gaps  in  the 
baseline.  For  instance  the  European  Green  Deal's  Investment  Plan  should  lead  to  at  least  €1trn  of 
investments  over  the  coming  decade,  and  the  Sustainable  Finance  agenda  aims  to  use  market  forces  to 
redirect investments towards support of the green objectives.  

20 

  EU27 Investment Gaps following the crisis (current €bn, 2020-2021 cumulative)PublicPrivateTotalBasic investment gap (relative to pre-crisis trend)15831846Avoid declining public capital stock 200n/a2001,046                   Investment needs to meet targets of strategic twin transitions (current €bn, 2020-2021 cumulative)PublicPrivateTotalGreen transition940Climate mitigation and energy 2030 targets* 680Wider environmental objectives, beyond climate 260Digital transformation250Strategic investment (for EU autonomy on critical value chains)401,230                 Total twin transition needs* includes 100bn per year for greening transport infrastructure; excludes the higher costs of raising the ambition of emission reduction to 50-55%, as well as adaptation investmentsn/an/an/aTotal investment gaps unrelated to policyn/an/a 
 
 
                                                 
 
rapid recovery from the Covid-19 crisis and a transition to a cleaner and more productive 
economy.  

It should be noted that the baseline in the Spring Forecast assumes that the Multiannual 
Financial Framework with a strong emphasis on modern policies and new delivery tools 
will be in place. In fact, an unprecedented share of the long-term EU budget, reinforced 
with  the  Union  Recovery  Instrument,  will  be  allocated  to  policies  supporting  research 
and  development,  connectivity,  internal  market  policies  and  support  for  the  green  and 
digital transitions. Private investments will add up to the public support for more impact. 
For investments to be effective, they need to be accompanied by appropriate economic, 
fiscal,  financial  and  social  policies  and  reforms.  Together,  these  policies  will  sustain 
productivity and growth over long term.  

3.3.  ADDRESSING SOCIAL NEEDS AND SUPPORTING EMPLOYMENT 

Europe rightly prides itself on universal healthcare and a social safety net to cater 
for  those  in  need.  The  CoVid  crisis  is  putting  a  strain  on  the  EU’s  health  and  social 
systems,  and  highlights  scope  for  enhancing  its  resilience  and  treatment  capacity.  The 
budgetary  impacts  of  social  support  and  unemployment  schemes,  as  well  as  healthcare 
measures that have been adopted, are incorporated in the forecasts and the corresponding 
financing  needs  estimates.  However,  some  social  investments  and  future  costs  deserve 
particular attention.  

To  prevent  large-scale  social  hardship  caused  by  surging  unemployment,  EU  Member 
States have taken swift and decisive support measures by introducing or extending short-
term  work schemes.  This  type of crisis  response is  included in the Commission Spring 
Forecast’s budgetary projections and financing needs. The budgetary impact of the crisis 
on expenditures on short-time work schemes in 2020 is estimated at €135bn and can be 
covered by SURE for countries with high funding costs.  

Beyond  the  short-term,  the  budgetary  pressures  of  unemployment  schemes  will  remain 
elevated  in  the  medium  term  as  unemployment  is  projected  to  remain  above  the  pre-
CoVid  level  also  after  2021.  This  contributes  to  higher  government  deficits  and  debt 
levels and may put pressure on public investment expenditure. Cumulated over the period 
to  2027,  the  higher  unemployment  benefit  expenditure  (excluding  short-term  work 
support) due to the CoVid-impact is estimated at €150bn euros by 2027. In this context, 
policies  financed  through  the  Multiannual  Financial  Framework,  such  as  the  European 
Social  Fund  Plus,  can  provide  a  much  necessary  support  for  labour  mobility  and  re-
skilling. 

The  CoVid-19  pandemic  has  accentuated  the  need  for  re-orienting  EU  health  systems 
towards  increased  use  of  hospitals  for  infectious  diseases  treatment,  prevention  and 
diagnostics, where care is falling short, as well as the need for a more substantive health 
programme to finance cross border issues related to health security and the resilience of 
health  systems.  Analysing  variations  in  public  expenditure  on  these  components  across 
the  health  systems  of  Member  States  allows  for  an  estimation  of  the  additional 
expenditure  requirements.  These  spending  needs  are  likely  to  exceed  €70bn,  or  around 
0.6 %  of  EU  GDP,  though  with  large  variations  across  countries.  Key  elements  in  the 
implementation of such investments will be good governance practices and achieving a 
sustained  improvement  of  accessibility,  quality  and  efficiency  of  health  systems, 
including  through  an  emphasis  on  smart  digitalisation  and  strengthened  health 
prevention.  

21 

 
Taking  account  of  the  additional  health  care  needs,  estimates  of  additional  investment 
needs in the area of social infrastructure have been increased to €192bn per year. These 
estimates  cover  investment  needs  for  affordable  housing,  health  and  long-term  care, 
education  and  life-long  training,  with  health  and  long-term  care  accounting  for  62%  of 
the investments needed.  

Table 4: Social infrastructure investment needs 

Social spending not only prevents individual hardship and underpins social cohesion, but 
it also supports aggregate demand in the recession. As budgetary pressures rise, it will be 
important that increasing provision of essential social support does not crowd out public 
investment  or  liquidity  and  solvency  support  to  the  corporate  sector  in  countries  with 
weaker fiscal positions. A healthy economic recovery requires that both  are maintained 
through the trough of the crisis. The strength of Europe’s recovery also relies on pursuing 
reforms  to  generate sustainable and fair  growth,  including through  fair tax policies and 
broad  and  equitable  tax  bases.  The  alternative  of  a  contractionary  path  marked  by  jobs 
destruction rising poverty, defaults and increasing divergence within societies and across 
the  EU  must  be  avoided  by  addressing  sovereign  financing  needs  and  addressing 
common EU challenges through EU funds.  

3.4.  ADDRESSING THE NEEDS OF OUR NEIGHBOURHOOD COUNTRIES 

The  economic  outlook  for  Eastern  and  Southern  neighbourhood  countries  has  radically 
changed following the global spread of the corona virus in early 2020. Forecasts were for 
a  continued  good  or  improving  performance  relative  to  2019,  with  growth  generally 
expected  to  strengthen  in  2020.  The  spread  of  the  corona  virus  has  brought  an  abrupt 
deterioration  of  the  outlook:  all  neighbours  appear  to  be  set  for  a  recession  this  year, 
while  its  duration  and  severity  are  still  difficult  to  estimate.  In  order  to  alleviate  the 
burden of the crisis on the economy and population, most authorities have announced a 
number of health-related, fiscal and monetary policy measures. However, more funding 
is  likely  to  be  needed.  Therefore,  several  countries  in  the  region  will  be  in  need  of 
additional  financial  support  from  external  partners  to  provide  liquidity,  sustain  macro-
economic stability and avoid adverse fiscal dynamics.  

3.5. 

SOVEREIGN FINANCING NEEDS 

Additional government financing needs due to the impact of the CoVid-19 crisis are 
estimated at almost €1.7trn for EU Member States over 2020 and 2021. This estimate 
captures the impact of higher spending and lower tax revenues compared to a pre-crisis 
baseline scenario; that pre-crisis baseline scenario already foresaw gross financing needs 
of  €3.7trn.  Adding  the  additional  financing  needs  resulting  from  the  crisis  brings  total 
financing needs to close to €5.4trn. This estimate includes also financing needs to cover 
governments’  current  and  public  investment  spending  in  2020  and  2021,  as  forecast  in 
the Spring Forecast. It also includes funding needed to roll over maturing sovereign debt. 
It does not, however, include the public sector investment gaps identified in section 3.2 

22 

15705057192                                 Social infrastructure investment needs (EURbn, per year)* The original estimate of 20bn before the crisis has been inceased to 70bn due to the crisis. Source: European Green Deal Investment Plan Communication (January 2020) and the Report of the High-level taskforce on investing in social infrastructure (2018)  TotalLong term careEducation and long-life learningHealth*Affordable housing 
 
of this paper.18 Furthermore, risks surround this gross financing needs estimate of €5trn, 
as EU governments’ finances are also exposed to unbudgeted losses from guarantees and 
potential banking sector losses.  

Gross  financing  needs  will  reach  exceptional  levels  as  of  May  2020,  and  will  involve 
very high volumes of debt issuance at short-term maturities, which may create crowding-
out effects for lower-rated debt. Liquidity remains a challenge despite the ECB’s PEPP, 
market tensions are emerging, creating challenges for all EU Member States, particularly 
for  higher-debt  countries  with  large  rollover  requirements.  The  beneficial  financing 
conditions  of  EU  borrowing  can  help  alleviating  the  short-term  pressure  on  Member 
States public finances and allow to put in place the necessary growth enhancing measures 
and avoiding widening divergence. 

4.  ECONOMIC IMPACT OF A RECOVERY INSTRUMENT 

The  revised  Multiannual  Financial  Framework  (MFF)  for  2021-2027  is  reinforced 
through  a  Recovery  Instrument  that  can  fill  sectoral  and  regional  financing  gaps, 
irrespective of the country they stem from. The creation of a Recovery Instrument linked 
to the EU budget could add €750bn, equivalent to around 5¼ % of annual EU GDP, to 
the EU’s  capacity to  finance the  recovery. The  majority of this funding  would take the 
form  of concessional  loans and grants  to  Member States, channelled to  them  through  a 
market-based  funding  capacity  linked  to  the  EU  budget.  A  smaller  share  of  the  total 
financing  package  consists  of  guarantees  for  EFSI  and  InvestEU  loans  and  equity-type 
funding for private sector investments. 

Simulations  using  the  Commission’s  QUEST  model  can  show  the  macroeconomic 
impact on the EU27 economy of the Recovery Instrument in operation. This exercise 
inevitably takes a stylised form and relies on a number of modelling assumptions. For the 
purpose of the analysis, 93.5 % of the Instrument’s total size is assumed to be used for 
public investment purposes, predominantly delivered through grants but with a sizeable 
component  of  loan  to  Member  States.  The  remaining  6.5%  share  of  the  Instrument  is 
used  as  loss  provisioning  for  financing  of  private  investment  by  EFSI  and  InvestEU. 
These  guarantees  allow  the  mobilisation  of  a  significantly  larger  financing  volume.  A 
range of scenarios are considered in this exercise using different assumptions about the 
additionality  of  investment  loans  and  grants  compared  to  a  counterfactual  scenario 
without  the  Recovery  Instrument.  The  different  scenarios  also  capture  uncertainty 
concerning  the  pricing  and  risk  structure  of  the  supported  investments  and  final  loan 
demand  from  borrowers.  The  total  supported  investment  is  assumed  to  take  place  in 
equal  portions  between  2021  and  2024,  i.e.  25%  in  each  year.  In  all  scenarios,  the 
economic additionality of this lending is based on the notion of loan supply restrictions 
by private banks in the current recession. 

The Recovery Instrument is likely to have a permanent positive effect on EU27 real 
GDP.  The  mobilised  investment  is  estimated  to  raise  real  EU  GDP  levels  by  around 
1¾ % in 2021 and 2022, rising to 2¼% by 2024. This assumes a total Instrument volume 
of €750bn, applying prudent assumptions regarding the additionality of loan-based public 

18 Below-average income economies with high debt have particularly high total financing needs, not only 
because  of  higher  budget  deficits  but  also  due  to  larger  refinancing  needs  for  maturing  government 
debt. EU instruments contribute to ensuring market access, avoiding undue tightening of fiscal policy 
and squeezing public investment. 

23 

 
                                                 
and private investment.19 Due also to the productivity-enhancing nature of the supported 
investments, economic output remains persistently above baseline levels in the medium 
to long run. Even ten years later, real GDP levels are estimated to be at least 1 % higher 
compared to the baseline scenario.  

Up to two million additional jobs are estimated to be created in the EU through the 
operation of the instrument over the medium term. Employment levels in the 2021-
2024  period  can  be  expected  to  be  around  1 %  higher  on  average  than  in  a  baseline 
scenario,  which  is  equivalent  to  around  2  million  jobs.  The  positive  effect  on 
employment  mainly  results  from  stronger  demand  due  to  the  mobilised  investment 
between 2021 and 2024. From 2025 onwards, the positive employment effect gradually 
gives way to a rise in real wages as productivity increases due to the effect of additional 
investment.    

The overall package is ‘self-financing’. A large share of the financing supports public 
investment; this has a multiplier larger than one, meaning one additional euro in public 
investment leads to more than one euro additional of GDP share of resources. In turn, this 
leads to a reduction in the debt-to-GDP ratio in the first  year (denominator effect). The 
assumed  favourable  effects  from  additional  provision  of  finance  to  the  private  sector 
increase government revenues via automatic stabilisers. Overall, the average government 
debt-to-GDP ratio in the EU27 falls by around ¾ of a percentage point in the short run, 
and  falls  further  below  baseline  levels  over  the  medium  to  long  term.  By  2030,  the 
average debt-to-GDP ratio in the EU is estimated to be almost 3 percentage points lower 
than in the baseline scenario.  

The  impact  of  the  Recovery  Instrument  is  differentiated  by  Member  State, 
counteracting  forces  of  divergence  resulting  from  the  crisis.  Using  an  illustrative 
allocation key for apportioning the above €750bn in grant and loan support to individual 
Member States, QUEST-based analysis can show the impact on real economic variables 
and debt-to-GDP ratios  by country group. Member States with below-average GDP per 
capita levels — further sub-divided by government debt ratios into a ‘higher debt’ and a 
‘lower  debt’  cluster  for  the  purpose  of  this  analysis  —  are  estimated  to  experience  the 
largest  boost  to  economic  activity  in  the  medium  term,  with  GDP  levels  4½ %  above 
baseline  by  2024  for  the  lower  debt  cluster  and  4¼ %  for  the  higher  debt  cluster.  The 
group of above-average GDP per capita levels (‘higher-income’) is likely to experience 
smaller, but still positive GDP effects of around 1¼ % compared to baseline by 2024.20  

The Recovery Instrument is estimated to not increase the debt burden significantly 
for any of the three Member State groups. Debt-to-GDP ratios are estimated to decline 
in the higher-debt group (-5 pps) and lower-debt group (-3¼ pps) by 2024, compared to a 
baseline scenario. Viewed over the longer term, the respective debt ratios decline further 
in  both  the  higher-debt  group  (-8½ pps)  and  lower-debt  group  (-7 pps  by  2030).  In  the 
higher-income  group,  the  public  debt  ratio  increases  slightly  in  the  medium  term  but 

19 EU averages quoted in this section refer to GDP-weighted averages for the 27 EU Member States, using 

2019 GDP shares. 

20 Member States are grouped according to GDP per capita levels and by general government debt ratios as 
follows:  ‘higher-income’  (FR,  AT,  BE,  DE,  DK,  FI,  IE,  LU,  NL,  SE),  ‘Higher-debt’  below-average 
income  (CY,  EL,  ES,  IT, PT),  ‘lower-debt’  below-average  income  (BG,  RO,  HR,  LV,  PL,  HU,  LT, 
EE, SK, CZ, MT, SI). 

24 

 
                                                 
remains  no  more  than  1  pp  above  baseline  levels;  by  2030,  the  debt-to-GDP  ratio  is 
estimated  to  have  fallen  back  to  the  same  level  as  in  the  baseline  scenario.  Sovereign 
credit spreads in the higher-debt group are reduced compared a baseline scenario due to 
the  favourable  economic  impact  that  drives  down  their  debt-to-GDP  ratio.  Finally,  the 
simulations  show  that  the  higher-income  group  also  benefits  from  the  reallocation  of 
investment  resources  in  the  sense  that  its  GDP  levels  are  boosted  by  higher  exports 
resulting from increased demand in the lower income groups. 

Chart 9: QUEST simulation results of impact of Recovery instrument 

Source: Commission services 

Sensitivity  analysis  shows  that  even  if  only  half  of  the  investment  grants  were 
absorbed there would still be a significant positive economic impact for all groups. 
While the aforementioned results assume that grants made from the Recovery Instrument 
to Member States are 100% additional — meaning they translate ‘one-for-one’ to  extra 
public investment that would not occur in the baseline scenario  —  the simulations can 
also  be  repeated  using  unfavourable  assumptions  regarding  the  additionality  of  grants. 
Assuming  that  only  50%  of  the  received  grants  translate  into  additional  public 
investment,  the GDP effects  are somewhat  smaller but  otherwise show little qualitative 
difference  compared  to  the  central  scenario  described  above.  In  particular,  EU  GDP 
levels  would  still  be  significantly  raised  in  2021  and  2022  on  average,  by  around  1  pp 
compared to the baseline scenario.  Debt-to-GDP levels in the EU would fall slightly in 
2021 and 2022 on average (by around ½ pp), and would decline further below baseline 
levels  in  the  longer  term  due  to  favourable  denominator  effects  from  stronger  growth 
throughout Europe. 

25 

-6-4-20246EU27HigherIncomeHigherDebtLowerDebtEU27HigherIncomeHigherDebtLowerDebtGDPDebt-to-GDPImpact of Recovery Instrument on GDP and government debt ratios compared to baseline in 2024 (pps.)pps.of GDP 
 
 
 
 
 
 
 
 
 
5.  CONCLUSION 

The CoVid-19 crisis has severely affected every EU Member State, business and citizen. 
In  view  of  an  unprecedented  economic  crisis  Europe  faces  grave 
to 
macroeconomic  stability  and  internal  cohesion  alike.  The  large  income  losses  for 
households  and  companies  caused  by  the  crisis  are  partly  cushioned  by  the  decisive 
support  measures  already  taken  by  Member  States  and  the  EU  itself.  However,  the 
impact of the pandemic differs considerably between Member States, as does their ability 
to absorb the economic and fiscal shock and to respond adequately to it.  

threats 

Member States hit hardest by the crisis are, by and large, those that entered the crisis on 
weaker  budgetary  footing  and  with  a  lower  degree  of  economic  resilience.  Unless 
supplemented  by  a  Multiannual  Financial  Framework  that  can  cater  for  the  size  and 
national disparity of the challenge at hand, the crisis risks undermining convergence, the 
Single Market and European unity. 

Ensuring  a  swift  and  sustainable  recovery  requires  identifying  unmet  needs  of  our 
economies  and  helping  to  finance  these  appropriately.  The  need  for  EU  action  in  this 
respect  has been  assessed from  three  angles:  the crisis  impact  on European companies’ 
equity  shortfall,  new  and  pre-existing  gaps  in  private  and  public  investment,  and  the 
impact on social spending. All three are interrelated, and — if met — can form a virtuous 
cycle of economic repair, continued employment, social  cohesion,  reinforced aggregate 
demand, and long-term economic transformation.  

The estimates presented in this assessment are consistent with the Commission’s Spring 
2020 Forecast, which presents a comprehensive analysis of the economic and budgetary 
outlook  for  EU  Member  States  in  the  context  of  the  CoVid  crisis.  As  such,  the  needs 
assessment  is  conditional  upon  the  Spring  forecast  scenario  materialising.  Significantly 
worse  economic  outcomes  are  conceivable,  and  their  avoidance  in  part  depends  on 
continued  forceful  policy  action  at  all  levels.  Should  downside  risks  to  the  Spring 
Forecast materialise, this would almost certainly increase estimated financing needs of all 
kinds.  

Equity losses for European incorporated companies (listed and non-listed) resulting from 
lower profits in 2020 alone are likely to range between  €720bn and €1.2tn, depending 
on  whether  the  central  scenario  of  the  Spring  Forecast  or  the  adverse  scenarios 
materialises. As was highlighted in the Spring Forecast, the risks are clearly tilted to the 
downside.  The  sectors  with  greatest  equity  losses  are  wholesale  and  retail  trade, 
accommodation and food services, and transport industries.  

The  crisis  has  opened  up  new  investment  gaps  resulting  from  a  collapse  in  private 
investment  plans, which compound  structural  investment  needs in  support of long-term 
growth and transformation. Given that a degree of overlap between the two exists, total 
investment gaps in 2020 and 2021 amount to at least €1.5trn, the majority of which will 
fall onto the private sector. This estimate includes, in addition to the investment shortfall 
caused by the crisis, needs to deliver on the green transition and digital transformation. In 
addressing this gap, an increase in public investment of about €100bn per year would be 
needed to stop the trend decline in the public capital stock as a share of GDP, while any 
cuts in current public investment plans to limit high deficits and corresponding financing 
need to be prevented.  

CoVid-19  strains  EU  health  and  social  systems.  Social  spending  not  only  prevents 
individual hardship and underpins social cohesion, but it also supports aggregate demand 

26 

 
 
in  the  recession.  Taking  account  of  the  additional  health  care  needs,  estimates  of 
additional investment needs in the area of social infrastructure have increased to around 
€200bn per year. These estimates cover investment needs for affordable housing, health 
and long-term care, education and life-long training. As budgetary pressures rise, it will 
be important to provide essential social support without crowding out public investment, 
especially in countries with limited fiscal space. The strength of Europe’s recovery also 
relies  on  pursuing  social  reforms  to  generate  sustainable  and  fair  growth,  including 
through fair tax policies and broad and equitable tax bases. 

Meeting  all  the  above  needs  will  in  part  fall  on  the  public  sector,  which  already  faces 
ample  sovereign  gross  financing  needs  in  the  coming  period.  These  amount  to  around 
€5.4trn in 2020 and 2021 taken together, of which €1.7trn is due to the additional crisis 
impact.  Ensuring  that  this  funding  is  available  can  help  to  prevent  public  investment 
being cut further, as happened in previous crises. 

A  Recovery  Instrument  worth  around  5¼ %  of  EU27  GDP  and  attached  to  the  EU 
Budget  is  estimated  to  have  a  permanent  positive  effect  on  EU27  economic  activity.  
Real  GDP  levels  could  be  lifted  by  around  2¼ %  by  2024  compared  to  a  baseline 
scenario, assuming an instrument size of €750bn financing size and under conservative 
modelling  assumptions.  Up  to  2  million  additional  jobs  are  estimated  to  be  created  by 
2022 thanks to the operation of the Recovery Instrument; it is also estimated to be self-
financing,  leaving  EU  government  debt-to-GDP  levels  slightly  lower  even  in  the 
medium-  to  long  term.  While  a  well-targeted  Recovery  Investment  package  would  be 
particularly beneficial for lower-income Member States, it would also raise GDP growth 
in higher-income Member States by increasing demand for their exports.  

This needs assessment should be seen as a central element of the recovery strategy. The 
latter  also  depends  on  appropriate  reform  implementation,  which  can  and  will  also  be 
supported  through  financial  incentives.  For  a  genuine,  investment-led  and  sustainable 
recovery to be achievable, a concerted effort will be required by all actors and levels. 

27 

 
 
 
ANNEX I: ASSESSMENT OF CORPORATE FINANCING NEEDS WITH FIRM-LEVEL DATA 

The  unfolding  of  the  CoVid-19  pandemic  has  had  an  unprecedented  impact  on  firms’ 
financial situation in the EU. In such an environment, firm sales and profits have taken a 
hit.  Using  firm-level  balance  sheet,  income  and  cash  flow  disclosure  statements,  this 
Annex presents  initial  estimates of the  financing  needs of firms  in  the EU, and obtains 
the potential impact of the crisis on firms’ balance sheets. These impacts are gauged in 
terms of months of operations until net losses, illiquidity and working capital shortfalls 
occur and the share of firms that experience them.  

The calculations make use of a number of important assumption, including as regards the 
strength  and  duration  of  disturbances  to  sectoral  activity  as  well  as  the  impact  on 
different  elements  of  firms’  revenues  and  expenditures.  In  view  of  important 
uncertainties  and  data  limitations,  the  simulations  are  based  on  rather  conservative 
technical assumptions and the results should be seen as providing lower bounds for the 
needed equity repair. At the same time, it must be stressed that there is a large margin of 
error around the estimates. 

1. 

The approach 

The  firm-level  data  base  Orbis  has  been  used  to  assess  the  financing  needs  of  the 
corporate sector due to the impact of the impact of the CoVid-19 pandemics. 

The  crisis  will  impact  the  firms’  balance  sheets  and  capital  structure  through  drops  in 
revenues and accumulation of losses. A degree of recapitalisation will be required to (at 
least  partially)  restore  the  financial  position  prevailing  before  the  crisis,  and  offset  the 
actual  losses  (i.e.  negative  net  profits)  incurred  during  the  downturn.  The  amount  of 
corporate profits or losses is calculated from the following specification:  

𝑝𝑟𝑜𝑓𝑖𝑡/𝑙𝑜𝑠𝑠𝑖𝑡 =

(1−𝑑𝑠𝑡)𝑆𝑖
12

−

(1−𝜀𝑀𝑑𝑠𝑡)𝑀𝑖
12

−

(1−𝜀𝑊𝑑𝑠𝑡)𝑊𝑖
12

−

(1−𝜀𝐹𝑑𝑠𝑡)𝐹𝑖
12

−

𝐼𝑖
12

−

𝑇𝑖
12

where 
𝑆𝑖 is firm i's annual sales/revenue in the last reported year; 
𝑑𝑠𝑡 is the demand shock in sector s and month t, derived from the SF2020; 
𝑀𝑖 is firm i's annual expenses on material input in the last reported year; 
𝑊𝑖 is firm i's annual expenses on labour input in the last reported year; 
𝐹𝑖 is firm i's annual expenses on fixed inputs (e.g. rent) in the last reported year; 
𝐼𝑖 is firm i's annual interest payment in the last reported year; 
𝑇𝑖 is firm i's annual taxes in the last reported year; 
𝜀𝑀 is the elasticity (common across all dimensions) of material cost wrt sales, currently 
set at 0.5; 
𝜀𝑊 is the elasticity (common across all dimensions) of labour cost wrt sales, currently set 
at 0.8; 
𝜀𝐹 is the elasticity (common across all dimensions) of fixed cost wrt sales, currently set at 
0.1. 
The assumed elasticities are in line with existing papers.21  

21 Corporate sector vulnerabilities during the Covid-19 outbreak: assessment and policy responses, OECD, 

ECO/CPE/WP1(2020)12 and Schivardi and Romano (2020). 

28 

 
  
 
 
                                                 
The evaluation of the impact of the crisis in terms of total corporate losses is seen as the 
central  simulation.  To  better  gauge  the  extent  of  the  additional  financing  needs,  the 
calculations on corporate profits / losses is  complemented by  assessing to what extent 
firms  can  weather  the  incurred  losses  by  relying  on  liquid  assets  and/or  working 
capital (capital that can easily be converted to liquid assets). Additional simulations 
have  been  performed  in  order  to  estimate  how  the  profit  losses  dent  these  two  buffers 
respectively.  As  variables  of  interest,  the  calculations  use  cash  and  demand  deposits 
(for liquid assets) and current assets minus current liabilities (for working capital). 

The simulations take this form (example for the case of liquidity):  

𝑙𝑖𝑞𝑢𝑖𝑑𝑖𝑡𝑦𝑖𝑡 = 𝑙𝑖𝑞𝑢𝑖𝑑𝑖𝑡𝑦𝑖𝑡−1 +

(1−𝑑𝑠𝑡)𝑆𝑖
12

−

(1−𝜀𝑀𝑑𝑠𝑡)𝑀𝑖
12

−

(1−𝜀𝑊𝑑𝑠𝑡)𝑊𝑖
12

−

(1−𝜀𝐹𝑑𝑠𝑡)𝐹𝑖
12

−

𝐼𝑖
12

−

𝑇𝑖
12

Result Buffer    Initial Buffer  

 Revenue-Expense = Profit or Loss 

It  is  assumed  that  the  situation  of  firms  at  the  beginning  of  the  crisis  was  broadly  the 
same  as  in  2018,  the  latest  available  data  in  the  Orbis  data  set.  To  correct  for  possible 
data  issues  or  legacy  problems  (i.e.  firms  with  liquidity  problems  already  before  the 
crisis),  it  is  assumed  that  if  a  firm’s  starting  position  in  terms  of  liquidity  or  working 
capital is negative, it is set at zero. Additional cleaning has been done on the Orbis data 
base  to  keep  firms  with  reasonable  quality  of  data.  Representative  estimates  are  then 
derived  through  re-weighting  based  on  the  Eurostat  Structural  Business  Statistics  data 
set. Due to data quality issues for small-sized firms in Orbis, results are only reported for 
companies with 20 and more employees. 

Policy simulations 

The central simulation (and the variants with buffers) also reflects the impact of policy 
measures that have been put in place to alleviate the impact of the crisis on firms’ wage 
bill,  in  particular  short-time  work  schemes.  These  measures  are  modelled  in  a  stylised 
way by increasing the elasticity of the wage bill to 0.8 from 0.15, which is used when 
firms have to bear the brunt of the shock themselves and find it difficult to quickly adjust 
their labour costs. 

To better assess the potential impact of  policies, we ran a no policy simulation, which 
assumes  no  wage  bill  support,  i.e.  keeping  the  respective  elasticity  at  0.15,  and  an 
extended  policy  simulation,  which  on  top  of  the  employment  measures  also  includes 
deferral  of  tax  and  interest  payments.  The  latter  is  modelled  as  setting  interest  and  tax 
payments (Ii and Ti) to zero. This is clearly a gross simplification and it is likely that over 
a longer time horizon the deferrals will be phased out (although the tax payments will be 
considerably lower considering the hit to profits). 

Macroeconomic scenarios 

Two  macroeconomic  scenarios  are  used,  namely  the  ones  presented  in  the  Spring 
Forecast  2020:  a  baseline  scenario  for  country-sector  shocks  and  a  stress  scenario 
(also called adverse scenario) assuming longer lock down. 

29 

 
  
 
 
 
Overview of simulations 

The table below describes the individual simulations that have been made. These explore 
the  financing  needs  under  two  macroeconomic  scenarios  included  in  the  SF2020 
(baseline and stress), three variants on policy (no policy, short-time work schemes, short-
time  work  schemes  and  deferral  of  tax  and  interest  payments),  and  three  assumptions 
regarding the firms’ buffers (no buffer, liquidity buffer, working capital buffer). 

Table 1: Description of simulations  

No buffer 

Baseline scenario 
Liquidity 
buffer 

Accumulated 
losses 
STW (𝜀𝑊: 
0.15→0.8) 
SF: baseline 

Liquidity 
shortfall 
STW (𝜀𝑊: 
0.15→0.8) 
SF: baseline 

Policy 

Accumulated 
losses 
STW (𝜀𝑊: 
0.15→0.8) + 
deferred I &T 
(set at 0) 
SF: baseline 

Liquidity 
shortfall 
STW (𝜀𝑊: 
0.15→0.8) + 
deferred I &T 
(set at 0) 
SF: baseline 

“Extended” 
policy 

Working 
capital buffer 
Working 
capital 
shortfall 
STW (𝜀𝑊: 
0.15→0.8) 
SF: baseline 

Working 
capital 
shortfall 
STW (𝜀𝑊: 
0.15→0.8) + 
deferred I &T 
(set at 0) 
SF: baseline 

No policy 

Accum
ulated 
losses 
No policy 
SF: baseline 

Liquidity 
shortfall 
No policy 
SF: baseline 

Working 
capital 
shortfall  
No policy 
SF: baseline 

No buffer 

Accumulated 
losses 
STW (𝜀𝑊: 
0.15→0.8) 
SF: ‘longer 
lasting’ 
lockdown 

Accumulated 
losses 
STW (𝜀𝑊: 
0.15→0.8) + 
deferred I &T 
(set at 0) 
SF: ‘longer 
lasting’ 
lockdown 

Accumulated 
losses 
No policy 
SF: ‘longer 
lasting’ 
lockdown 

Stress scenario 
Liquidity 
buffer 

Liquidity 
shortfall 
STW (𝜀𝑊: 
0.15→0.8) 
SF: ‘longer 
lasting’ 
lockdown 

Liquidity 
shortfall 
STW (𝜀𝑊: 
0.15→0.8) + 
deferred I &T 
(set at 0) 
SF: ‘longer 
lasting’ 
lockdown 

Liquidity 
shortfall  
No policy 
SF: ‘longer 
lasting’ 
lockdown 

Working 
capital buffer 
Working 
capital 
shortfall 
STW (𝜀𝑊: 
0.15→0.8) 
SF: ‘longer 
lasting’ 
lockdown 
Working 
capital 
shortfall 
STW (𝜀𝑊: 
0.15→0.8) + 
deferred I &T 
(set at 0) 
SF: ‘longer 
lasting’ 
lockdown 
Working 
capital 
shortfall 
SF: ‘longer 
lasting’ 
lockdown 

The  simulations  provide  information  on  firms  incurring  losses,  and  to  what  extent  the 
available  buffers  can  cover  these  losses,  and  consequently  what  potential  equity 
injections they may need. The results span the period until end-2020. 

This approach provides  a range of possible needs, as a function of how firms can use 
such buffers. If there is no buffer, the overall financing gap is clearly bigger. However, 
this assumption is too strong in reality, and many firms will be able to cushion the shocks 
by  using  their  buffers.  So  the  main  question  is  how  the  firm  will  adjust  to  the  loss 
(replenish equity, take on more debt, sell some of its assets):  

 
The “liquidity buffer”  exercise assumes  that all firms  can deplete  cash reserves. 
As a result, the volume of financing shortfall is smaller. The results can also show how 
big  the  shortfall  is  in  fragile  firms  (those  with  initially  low  profitability  or  excessive 
leverage), as for these fragile firms going to the market to get credit may be difficult. 

 
The  “working  capital”  exercise  allows  the  firms  to  deplete  other  liquid  assets, 
beyond  cash.  In  such  a  case,  the  firm  can  sell  off  all  liquid  assets  (sell  inventories,  go 
after debtors, deplete its cash reserves) but only to the extent that these assets are larger 
than  its  current  liabilities  (short  term  debt,  people  to  whom  firm  owes  money). 

30 

 
 
 
Eventually,  the  shortfall  of  working  capital  is  one-for-one  to  need  for  the  equity 
replenishment if we want no firm to drive down its assets further, i.e. assuming the firm 
cannot deplete its fixed assets. 

It should be stressed that there is  a large margin of error around the estimates for a 
number  of  reasons:  because  of  uncertainty  regarding  sectoral  shocks  (depth,  duration), 
assumptions on cost elasticities, and flaws in the used micro-data (data 2 years old; not 
full  universe  of  firms  covered;  data  quality  heterogeneous  between  countries  and 
sectors).  

2. 

Results on financial need based on the simulations 

This section presents the results of the “Policy scenario” simulation described in the table 
above. This simulation captures some of the policy measures that have been put in place 
to alleviate the impact on firms' financial situation, namely short-time work schemes. The 
financing needs are reported for both the baseline shock scenario and the stress scenario 
that  assumes  an  extended  lockdown.  The  results  reflect  the  situation  by  the  end  of  Q4, 
accumulating the losses from the start of the lockdown in March until December 2020. 
All figures refer to firms with at least 20 employees, across all Member States of the EU, 
across all sectors of the total business economy. 

The charts below show that these firms would experience a total loss of 725 billion EUR 
in the baseline scenario and around 1.25 trillion EUR in the stress scenario.22 Allowing 
firms  to  absorb  the  incurred  losses  by  relying  on  their  liquid  assets  ("cash  buffer")  or 
working  capital  ("working  capital  buffer")  considerably  reduces  the  financing  shortfall. 
After  exhausting  their  liquidity  and  working  capital  buffer,  the  distressed  firms  would 
experience  a  financing  shortfall  of  450  and  350  billion  EUR  in  the  baseline  scenario, 
respectively. 

The estimates show that around 325 000 (375 000) firms would be distressed by the end 
of  the  year  in  the  baseline  (stress)  scenario,  assuming  no  buffer  to  cushion  the  shock. 
This  corresponds  to  60%  (70%)  of  all  companies.  Allowing  firms  to  deplete  their  cash 
reserves would reduce the share of distressed firms to around 35% (50%) in the baseline 
(stress) scenario. Allowing firms to absorb the shock with their working capital results in 
a  share  of  distressed  firms  of  around  25%  (35%)  in  the  baseline  (stress)  scenario.  The 
number of people employed in distressed companies amounts to ca 45 million assuming 
no  buffer,  30  million  with  cash  buffer  and  roughly  20  million  when  working  capital 
buffers can be depleted. 

Graph  A.1:  Impact  of  CoVid-19  on  financial  shortfalls  in  the  corporate  sector  (for 
different buffer assumptions and baseline and stress scenario) 

22 Note that these figures represent the total loss across the firms making losses. It does not account for the 

drop in profit due to the CoVid-19 crisis among firms that remain profitable. 

31 

 
 
                                                 
The above presented results correspond to a situation where some policy measures have 
been put in place to alleviate the impact on firms' financial situation, namely short-time 
work  schemes.  These  figures  can  be  confronted  with  those  from  a  simulation  that 
assumes  an  additional  set  of  policy  measures,  namely  deferral  of  interest  and  tax 
payments,  or  a  simulation  without  any  policy  put  in  place.  The  chart  below  shows  the 
financing  needs  for  both  the  baseline  and  stress  scenario  under  the  different  set  of 
policies, assuming no buffer to absorb the losses ("STW scheme" refers to the simulation 
for which results have been presented so far). The baseline shortfall of 725 billion EUR 
would increase to ca 825 billion EUR in the absence of STW schemes. Financing needs 
would  be  reduced  to  less  than  600  billion  EUR  if  interest  and  tax  payments  would  be 
deferred at least to 2021. 

Graph  A.2:  Comparison  of  total  shortfall  (under  different  policy  variants,  for  baseline 
and stress scenario) 

32 

 
 
 
 
 
 
Shortfall (billion EUR), no buffer 

Baseline

Stress

1600

1400

1200

1000

800

600

400

200

0

No policy

STW scheme

STW & tax/int
deferral

The  charts  in  Graph  A.3  present  the  share  of  distressed  firms  across  the  different  EU 
sectors, under both the baseline and stress scenario, for the case of no buffer as well  as 
cash  buffer.  Not  surprisingly,  the  sectors  showing  the  greatest  share  of  firms  facing 
liquidity shortfalls are wholesale and retail trade (G), accommodation and food services 
(I), and transport industries (H). 

Graph A.3: Share of distressed firms by sector (for no buffer and cash buffer variant and 
baseline and stress scenario) 

C – Manufacturing; F – Construction; G45 – Wholesale and retail of motor vehicles; G46 – Wholesale except motor 
vehicles; G47 – Retail except motor vehicles; H49 – Land transport; H50 – Water transport; H51 – Air transport; I – 
Accommodation  and  food  services;  J  –  Information  and  communication;  M  –  Professional,  scientific,  technical 
activities; N – Administrative, support service activities 

33 

 
 
 
 
 
 
 
The liquidity shortfall may translate into  a higher risk of default especially for firms 
who  already  find  themselves  in  a  vulnerable  position.  A  firm  is  considered  as 
financially vulnerable when it is situated in the top leverage quartile (defined as the ratio 
of debt to equity) or in the bottom profitability quartile (defined as the ratio of EBIT to 
turnover). Such vulnerable firms  may face difficulties in  obtaining access to  credit that 
may  be  required  to  cover  the  shortfall.  Indeed,  in  all  scenarios  with  policy  (short-term 
work schemes and deferral of interest and tax payments), between 58% and 75% of the 
total liquidity shortfall is attributable to financially vulnerable firms.  

In  the  baseline  scenario  with  policy,  the  total  shortfall  attributable  to  such  firms  after 
activation  of  the  liquidity  buffer  amounts  to  250  bn  EUR  by  the  end  of  2020.  The 
corresponding  amount  after  activation  of  the  working  capital  buffer  is  only  slightly 
lower, i.e. about 200 bn EUR. In the adverse scenario with policy, the share of the total 
shortfall  in  vulnerable  firms  is  somewhat  smaller  because  many  more  firms  become 
illiquid, but the total amount of the shortfall in vulnerable firms nearly doubles because 
the shocks are more severe. The shortfall in financially vulnerable firms amounts to 450 
bn  EUR  after  activation  of  the  liquidity  buffer  and  400  bn  EUR  after  activation  of  the 
working capital buffer (see Graph A.4).   

Graph A.4: Total shortfall in financially vulnerable firms (with policy) 

From  a  sectoral  perspective,  manufacturing  (C)  and  retail  (G)  are  the  two  sectors  in 
which a relatively large share of the total shortfall after activation of the liquidity buffer 
falls  within  the  vulnerable  firms.  For  example,  in  retail,  about  a  quarter  of  the  total 
shortfall is attributable to the vulnerable firms in the group with 250+ employees while a 
third  of  the  total  shortfall  is  attributable  to  such  firms  in  the  group  with  20-249 
employees.  In  the  other  sectors,  the  share  of  vulnerable  firms  in  the  total  liquidity 
shortfall is below 5%. Results are qualitatively similar in the adverse scenario as well as 
in the case of the working capital buffer.23 

23 In manufacturing, 13-15% in 20-249 group and 23-25% in 250+ group. In retail, 28-29% in the 20-249 
employee  group  and  20-22%  in  the  250+  employee  group.  So  the  shares  are  smaller  but  the  total 
amounts to which these shares correspond are significantly bigger. 

34 

 
 
 
 
                                                 
Graph  A.5:  Share  of  total  liquidity  shortfall  in  high  leverage  –  low  profitability  firms 
(baseline with policy) 

35 

 
 
 
 
ANNEX  II:  INDICATIVE  EQUITY  AND  INVESTMENT  LOSSES  FOR  14  INDUSTRIAL 
ECOSYSTEMS 

The breakdown is indicative, based on available survey data. 

ESTIMATED  DISTRIBUTION  OF  EQUITY  AND  INVESTMENT  NEEDS  ACROSS  ECOSYSTEMS 
USING SURVEY DATA 

Given the unique nature of this crisis the uncertainty surrounding any estimate is bigger 
than usual. . Survey data and information from stakeholders, if properly validated, reflect 
real time information and can be a valuable asset to complement other estimates.  

The notion of Ecosystems  captures  the complex set  of interlinkages among sectors and 
firms spreading across countries in the Single Market, and is therefore useful to support 
this analysis. The Ecosystems  encompass all players operating along a value chain: the 
smallest  start-ups  and  the  largest  companies,  the  research  activities,  the  services 
providers  and  suppliers.  They  allow  for  a  bottom-up  approach  that  takes  into  account 
specificities of business models, high percentage of vulnerable players (SMEs and micro) 
and  interdependencies.  So  far,  14  industrial  ecosystems  spreading  across  the  EU  have 
been identified. 

It suggests how the overall financing needs could be distributed across ecosystems, using 
stakeholder and survey information  on their expected drops in  turnover  (compared to  a 
year  earlier).  This  information  complements  other  sources  on  the  actual  extent  of  the 
impacts as is in line with the approach followed by other institutions.24  

EQUITY LOSSES 

The note has shown that the estimation of equity losses is a difficult endeavour, leading 
to a range of estimates, between 720 billion in the baseline scenario and 1.200 billion in 
the stress scenario. Understanding in which ecosystems these equity needs lie is crucial 
to prioritise spending and support with limited means. To assess the toll the current crisis 
has taken we have used survey methods to identify expected revenue losses in the most 
important  industrial  ecosystems  in  Europe  which  then  we  use  as  a  key  –together  with 
size- proxy to allocate the equity losses.  

24 

in 

its 

the 

ECB 

instance, 

For 
https://www.ecb.europa.eu/pub/economic-
bulletin/focus/2020/html/ecb.ebbox202003_01~767f86ae95.en.html)  presents  a  sectoral  analysis  that 
is  “indicative  and  based  on  anecdotal  evidence  and  available  survey  evidence.  It  helped  derive 
economy-wide  estimates  for  the  likely  economic  losses,  which  are  broadly  in  line  with  available 
estimates from other institutions”. 

Economic  Bulletin 

(1  May 

2020: 

box 

36 

 
 
 
 
                                                 
Current and expected drops in turnover reported by industry (share of turnover) 

Source: DG GROW survey, March and April 2020. Data aggregated by ecosystem. For the scope of this exercise, 
each  ecosystem  has  been  defined  in  a  relatively  narrow  way  to  avoid  double  counting  of  losses.  The  retail 
ecosystem does not include sales and repair of vehicles, which are included in the mobility ecosystem.  

These  figures  should  be  interpreted  with  caution  because  of  sample  limitations. 
Nevertheless  these  expected  drops  in  revenue  might  provide  a  rough  proxy  for  how 
different  ecosystems  are  impacted.  The  table  and  figures  below  shows  the  resulting 
equity  loss  distribution  starting  from  the  aggregate  equity  needs  developed  in  the  note, 
across two scenarios: 

37 

 
 
 
 
Scenario 
€720bn 

Scenario 
€1200bn 

Tourism 

Mobility-Transport-Automotive 

Aerospace & Defence 

Construction 

Agri-food 

Energy Intensive Industries 

Textile 

Creative & Cultural Industries 

Digital 

Renewable Energy 

Electronics 

Retail 

171 

91 

13 

113 

22 

61 

12 

33 

16 

3 

3 

57 

Proximity & Social Economy 
Health25 

Total 

   52 

N/A 

€648bn 

285 

152 

22 

188 

37 

101 

20 

55 

27 

5 

5 

   94 

87 

N/A 

€1080bn 

The  ecosystems  listed  in  the  table  represent  roughly  70%  of  the  EU  economy,  but 
roughly 90% of the business economy (as a share of value added). We can attribute the 
estimated  equity  losses  to  each  ecosystem  based  on  this  share  and  on  the  information 
collected from stakeholders.  

25 The Health Ecosystem is assumed not to have incurred any equity losses. So far the immediate support 
provided  has  helped  to  cope  with  the  increasing  demand  and  needs.  However,  the  CoVid  crisis  is 
putting  a  strain  on  the  EU’s  health  and  social  systems,  highlighting  the  scope  for  enhancing  its 
resilience and treatment capacity, and the most recent surveys point to relevant negative expectations 
for the sector, mainly about the capacity of supply to match increasing demand. As a consequence, this 
is likely to lead to an underestimation of total needs. 

38 

 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                                 
INVESTMENT NEEDS 

Investment  needs  are  allocated  across  ecosystems  next.  At  this  stage,  only  the  basic 
investment  needs  are  distributed  while  further  work  will  be  carried  out  for  green, 
digital and resilient investment. As we move on, the challenge will be to allocate to each 
ecosystem the amount of investment needed not just to bounce back to pre-crisis levels, 
but to bounce forward and meet the pressing challenges of strengthening resilience and 
digital and green transitions. 

The  note  suggests  a  cumulative  drop  in  investment  of  €846bn  in  2020  and  2021  taken 
together,  of  which  €831bn  is  accounted  for  by  lower  private  investment.  This  figure 
represent the fall compared with pre-crisis levels, which were, nevertheless, worryingly 
low.  In  order  to  attribute  such  investment  needs  across  ecosystems,  we  apply  a 
combination  of  the  share  of  the  ecosystem  in  the  economy  together  with  the  pre-crisis 
level  of  investment.  The  resulting  figures,  then,  can  be  used  to  attribute  the  share  of 
investment  corresponding  a  90%  share  of  the  total  envelope,  which  probably  better 
reflects the actual investment needs of the ecosystems. 

39 

 
 
 
 
 
Basic investment needs  

Tourism 

Mobility-Transport-Automotive 

Aerospace & Defence 

Construction 

Agri-food 

Energy Intensive Industries 

Textile 

Creative & Cultural Industries 

Digital 

Renewable Energy 

Electronics 

Retail 

Proximity & Social Economy 

Health 

Total 

161 

64 

4 

54 

32 

88 

6 

6 

66 

100 

18 

115 

N/A 

32 

€748bn 

40 

 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ANNEX  III:  QUEST  SIMULATIONS  OF  THE  ECONOMIC  IMPACT  OF  A  RECOVERY 
INSTRUMENT  

1.  OVERVIEW: 

This  note  reports  QUEST  model  simulations  on  macroeconomics  effects  of  the 
Recovery  Instrument  included  in  the  multiannual  financial  framework  2021-2027 
(MFF).26  

A particular focus of this note is the distributional dimension across stylized blocks 
in  the  EU.  This  note  thereby  complements  previous  work  by  ECFIN  B3  on  different 
assumptions regarding the additionality of public and private investment. 

2.  SCENARIO SETUP 

2.1.  Modeling framework 

The  analysis  builds  on a  multi-region  QUEST  model  featuring  three  blocks  of  the 
EU-27  and  the  rest-of-the-world.  A  rich  empirical  trade  matrix  links  all  regions  of  the 
model.  

For  the  modelling  exercise,  Member  States  are  grouped  according  to  GDP  per 
capita and debt-to-GDP ratios. The high-income group consists of all Member States 
with  a  GDP  per  capita  above  the  average.27  The  other  two  groups  include  the  Member 
States  with  a  below-average  income  per  capita.  Here,  the  “EU  below  average  (high 
debt)”  includes  the  Member  States  characterized  by  high  public  indebtedness.  All 
remaining  Member  States  are  grouped  as  “EU  below  average  (low  debt)”.  Assuming 
either  pegged  currencies  or  common  monetary  policy,  the  Member  States  in  the  high-
income  group  and  high-debt  group  form  a  currency  union,  where  monetary  policy  is 
constrained by the effective lower bound.28 

The  model  accounts  for  region-specific  features  such  as  a  nonlinear  exposure  to 
sovereign debt risk and vulnerable financial markets in the high-debt group, as well as 
region-specific  trade  openness  and  trade  linkages.  These  features  matter  for  the 
macroeconomic  effects  of  the  Recovery  Instrument  and  motivate  the  stylized  grouping 
for this modelling exercise. 

To summarize, the blocks includes the following Member States: 

  EU above average GDP per capita: AT, BE, DE, DK, FR, FI, IE, LU, NL, SE 

26 The note is part of a sequence of confidential notes shared in April and May 2020. QUEST is the global 
macroeconomic model that the DG ECFIN uses for macroeconomic policy analysis and research. It is 
a  structural  macro-model  in  the  New-Keynesian  tradition  with  rigorous  microeconomic  foundations 
and frictions in goods, labour and financial  markets. Additional information and bibliography can be 
https://ec.europa.eu/info/business-economy-euro/economic-and-fiscal-policy-
found 
coordination/economic-research/macroeconomic-models_en  

here: 

27 Unweighted average using 2019 data, based on chain linked volumes (2010). See Annex A for additional 

details. 

28 This builds on the assumption that the ECB does not raise nominal rates in response to the investment 

stimulus for two years. 

41 

 
                                                 
  EU below average GDP per capita (high debt): CY, EL, ES, IT, PT 

  EU below average GDP per capita (low debt): All EU-27 members not included 

in the previous groups. 

2.2.  Size and time profile of the Recovery Instrument 

Table  1  presents  an  overview  of  the  configuration  of  the  Recovery  Instrument 
considered  in  this  note.  The  overall  package  of  EUR  750  bn,  in  total,  evenly  allocated 
across  four  years  (25%  in  each  year  from  2021  to  2024).  This  corresponds  to  around 
5.4% of annual EU-27 GDP or 1.35% of 2019 GDP in each year. 

Table 1: Simulation inputs (Scenario 2) 

Note: All components of the package are allocated between 2021 and 2024 (25% in each of the four years). 
GDP shares refer to shares of annual GDP in 2019. 

42 

Above average (High income)Below average (low debt)Below average (high debt)EU27/TotalGDP and allocationShare of EU GDP/contr64.5%10.7%24.8%1.0Share allocation24.5%25.0%50.6%1.0Total package Total contr (in bn)483.5                   80.4                      186.1                   750Total contr (in perc. of own GDP)5.39%5.39%5.39%Total received (in bn)183.8                   187.5                   379.5                   A Loansgiven (in bn)161.226.862.0250received (in bn)61.362.5126.5net (in bn)99.9-35.7-64.5total contr. (% of GDP)1.80%1.80%1.80%received (% of GDP)0.68%4.19%3.66%adj. for additionaltity (50%) 0.34%2.09%1.83%net contr. (% of GDP)1.11%-2.39%-1.87%B Grantsgiven (in bn)290.748.4111.9451received (in bn)110.5112.8228.2net (in bn)180.2-64.4-116.3total contr. (% of GDP)3.24%3.24%3.24%received (% of GDP)1.23%7.55%6.61%net contr. (% of GDP)2.01%-4.31%-3.37%C InvestEU/ESFI received 12.012.324.849incl. financial multiplier (1.5)18.018.437.274in % of GDP (incl. multiplier) 0.20%1.23%1.08% 
 
2.3.  The allocation key 

The  Recovery  Instrument  implies  important  redistribution  across  Member  States. 
The analysis aggregates a detailed allocation key. Table 1 presents the respective shares 
for each of the three clusters. Annex A provides further details at the Member State level.  

The simulations assume that the same allocation key applies for all components of 
package (grants, loans, additional provisioning to InvestEU, see below). The group with 
a GDP per capital above average receives 24.5% of the package, the “EU below average 
(low  debt)”  receives  25.0%,  and  the  “EU  below  average  (high  debt)”  receives  around 
50.6%. It is assumed that all Member States contribute according to their GDP shares.29 

2.4.  Components of the package 

2.4.1.  Grants and loans 

The largest share of the overall packages goes to boost public investment in forms of 
grants  and  loans.  EUR  451  bn.  (out  of  EU  750  bn)  will  be  provided  in  the  form  of 
grants  to  finance  public  investment.  EUR  250  bn.  resources  will  be  lending  to  the 
Member  States  to  finance  public  investment.  These  back-to-back  loans  will  be  repaid 
gradually over 20 years by the beneficiary Member States.  

Grants and loans have different implications for net foreign assets and government 
debt: 

  Providing a grant increases government debt and reduces net foreign assets (vice 

versa in case of receiving a grant). 

  Providing  a  loan  increases  net  foreign  assets  (vice  versa  in  case  of  obtaining  a 

loan). 

2.4.2.  Additional provisioning to InvestEU and ESFI 

ESFI and InvestEU use the remaining share of the package as loss provisioning for 
the  financing  of  private  investment.  In  times  of  inefficient  loan  provision  by  private 
banks, these guarantees allow the mobilisation of significantly larger financing volumes 
for  private  investment.  Assuming  a  provisioning  rate  of  40%,  the  guarantees  can  be 
larger  than  additional  provisioning  by  a  factor  of  1/0.4=2.5.  However,  there  are 
opportunity costs. The government must set aside the guarantees in case of loan defaults, 
which could have been invested directly in the economy. Therefore, the factor needs to 
be adjusted to 1/0.4-1 =1.5.30  

29  Very  small  rounding  error  are  possible.  The  GDP  shares  are  64.5%,  10.7%,  24.8%  for  high  income, 

below average (low debt), below average (high debt), respectively. 

30  The  amount  of  funding  that  the  EIB  can  provide  against  1  euro  of  capital  can  be  larger  for  special 
operation loans to the private sector. Still, for equity, the “multiplier” is one. We will consider only the 
case  of  full  equity  here.  A  previous  note  performed  additional  sensitivity  analysis  (circulated 
28/04/2020). 

43 

 
                                                 
2.5.  Assumptions on additionality 

2.5.1.  Loans and grants 

The simulations assume that Member States use 50% of the EU loans and 100% of 
EU grants for additional public investment. Only 50% of EU loans are used for public 
investment.  Since  the  other  half  finances  general  government  spending,  which  would 
take  place  anyway  (and  thereby  frees  resources),  the  impact  on  debt  is  also  50%.  This 
assumption  relates,  for  example,  to  borrowing  costs.  With  loans,  the  receiving 
government still faces the problem of rising interest rates. It has an incentive to use the 
loan to finance existing investment, which reduces additionality. 

The note also considers the case of 50% additionality of grants (labelled below as “L 
scenario”).  This  sensitivity  check  reflects  a  potential  lower  absorption  of  EU  grants 
given the large package size.  

2.5.2.  Additional provisioning and private lending 

The economic additionality of private lending is based on the notion of loan supply 
restrictions  by  private  banks  in  the  current  downturn.  The  additionality  is  likely 
much lower outside of a credit crunch.31  

The  analysis  here  assumes  that  all  additional  funding  is  provided  as  equity:  One 
additional  euro  in  provisioning  for  EFSI  and  Invest  EU  leads  to  1.5  euro  of  additional 
private investment. 

How  these  assumptions  can  be  achieved  is  not  addressed  here:  The  additional 
investment in the private sector based on the provisioning for EFSI and Invest EU is an 
assumption and not an outcome of the model-based analysis.32 

2.6.  Sovereign debt risks 

The Recovery Instrument addresses concerns about intertwined financial-sovereign 
debt risks following the unprecedented adverse effects of the COVID19 pandemic. The 
analysis of sovereign debt risks in the context builds on earlier work by B3 and is based 
on the debt projections of ECFINs Spring Forecast 2020.33 

The analysis assumes a nonlinear relationship between the default risk premia and 
the  level  of  government  debt  in  the  high-debt  cluster.  Higher  debt-to-GDP  ratio 
associated  with  sovereign  debt  risks  implies  higher  financing  costs  for  the  government 
and the private sector. Annex B provides additional information. 

31 For example, an evaluation of the literature for SME credit guarantees (probably the group most affected 
by market failure) shows that while CGSs increase the availability of credit and/or reduce its costs, the 
evidence as regards economic additionality are mixed. 

32 The simulations are based on the following additional assumptions: (i) There are no budgetary costs 
of  this  provisioning  for  EFSI  and  InvestEU  for  the  government  and  the  reduction  in  private  sector 
borrowing costs is exogenous. (ii) The pricing of loans is such that the remuneration covers the losses. 
(iii) The simulations account for improved credit access via an exogenous decrease in risk premia. 
33  A  confidential  note  shared  on  17/04/2020  (by  Philipp  Pfeiffer,  ECFIN  B.3)  and  a  recent  ECFIN 
discussion paper examine the sovereign-bank nexus in the euro area in more detail (Bellia et al., 2019). 

44 

 
                                                 
The calibration builds on a high risk-scenario of 2011 - admittedly an extreme case 
of distress. Current spreads are much lower.  Yet, it provides useful insights into the 
potential macroeconomic fallout from sovereign debt risks.34   

Reallocation, grants, and reduced indebtedness help avoid increases in risk premia 
and  adverse  sovereign-corporate  feedback  loops.  This  mechanism  will  be  an  important 
driver in the results for the high debt group.  

3.  SUMMARY OF MAIN RESULTS 

3.1.  Transmission 

For the public investment share of resources, the fiscal multiplier slightly above one 
contributes  to  a  reduction  in  the  debt-to-GDP  ratio  in  the  first  year  (denominator 
effect).  In the following years, there is an increase in debt ratios (see below). However, it 
remains modest as higher revenues from VAT, labour taxes, and profits as well as lower 
unemployment benefits relative to a no-policy change baseline partly offset the budgetary 
cost  of  higher  public  investment.  The  growth  effect  depends  crucially  on  the  assumed 
productivity of public capital.35  

All regions benefit from positive spillover due to the coordinated fiscal effort. 

The “multiplier” of private investment is large in case of loan supply restrictions by 
private banks. By assumption, one additional euro in provisioning for EFSI and Invest 
EU  leads  to  one  and  a  half  euros  of  additional  GDP.  Correspondingly,  the  assumed 
increase in private investment is sizable (see Table 2).  

The  absence  of  budgetary  costs  for  the  additional  provisioning  to  ESFI  and 
InvestEU  is  critical.  It  has  strong  implications  for  the  evolution  of  public  debt  and 
implies favourable debt dynamics. 

3.2.  Quantitative results 

3.2.1.  Dynamics of real GDP and debt 

Because of the mobilized investment, the level of GDP in the EU-27 is estimated to 
be  around  [2.3%]  higher  in  2024  than  foreseen  in  our  baseline.36  The  GDP  level 
increases in the first years (2021-2024) relative to a no-policy change baseline. Figure 1 
shows this result graphically by reporting the level deviation of key variables compared 
to our baseline. Further below we also discuss the positive labour market developments 
and stronger private investment in more detail. 

34 Corsetti et al. (2013) find such a relationship between credit default swaps (CDS) for governments bonds 
(5-year maturity) and the level of government debt (as a share of GDP) for OECD countries. Corsetti, 
G.,  Kuester,  K.,  Meier,  A.  and  Müller,  G.J.  (2013),  “Sovereign  Risk,  Fiscal  Policy,  and 
Macroeconomic Stability”. Economic Journal, 123: F99-F132.  

35  The  simulations  assume  an  output  elasticity  of  public  capital  is  0.12  (roughly  median  estimate  in  the 

empirical literature). 

36 The EU-27 variables are weighted averages based on 2019 GDP shares. 

45 

 
                                                 
Figure 1 also shows that the Recovery Instrument is estimated to lower the debt-to-
GDP ratio by up to [0.9 pp.] on average (2021-2024) for the EU27 aggregate. While 
debt  increases  in  nominal  terms,  the  budget  deficit  increases  by  less  than  the  ex-ante 
stimulus due to automatic stabilisers. The average debt-to-GDP ratio is lower on impact 
(denominator effect) but - given the persistent GDP effect – remains below the baseline.  

Turning  to  the  distributional  effects,  Figure  2  shows  that  GDP  effects  are  positive 
but quantitatively different across  blocks. Given the allocation key, the clusters with 
below-average  GDP  per  capita  levels  are  estimated  to  experience  the  largest  boost  to 
GDP  levels.  The  increase  in  output  reaches  almost  [4.6  %]  for  the  low  debt  group  and 
[4.2 %] for the high debt group in 2024, under full additionality of grants. The group of 
above-average GDP per capita levels is likely to experience smaller, but still sizable GDP 
effects of [1.2%] compared to baseline over the same period.  

The  debt-to-GDP  ratio  falls  for  the  groups  with  a  below-average  per  capita  GDP 
(low and high debt), but increase slightly in the high-income group (Figure 3). Loans 
increase the debt ratio only slightly since the public investment also leads to sizable GDP 
growth. By construction, receiving grants and additional provisioning lowers the debt-to-
GDP ratio compared to baseline, respectively.  

Real GDP in the low-debt (below average) cluster increases strongly in 2021. Most of 
the  growth  effects  come  from  grants  (orange).  By  contrast,  the  low  debt  levels  imply 
negligible effects from reduced sovereign debt risks compared to the high-debt cluster.  

Figure 1: Results for the EU-27 as a whole 

Note: This figure reports the debt-to-GDP ratio (all other variables) in percentage point (percent) deviation 
from a no-policy change baseline. All variables are reported in levels. H (orange) and L  (blue) scenarios 
refers  to  high  and  low  additionality  of  grants  (loans  are  always  50%  additional).  EU  refers  to  EU-27 
(weighted) averages. 

46 

 
 
The high debt group benefits from reallocation and reduced sovereign debt risks  – 
given the assumption of high spreads (see Figure 3, yellow bars). Relatively lower risk 
premia and spreads improve private investment and consumption of durable goods. The 
lower  pass-through  of  sovereign  risk  avoids  distress  in  the  private-sector  borrowing 
costs,  which  was  a  key  transmission  channel  in  the  sovereign  debt  crisis.  Turning  to 
public  sector  borrowing  costs,  note  that  the  sovereign  risk  increase  only  affects  new 
issuance. The maturity structure thus implies a gradual increase in debt service in light of 
average maturity of around seven years.37 This delayed effect also explains the persistent 
beneficial  effects  on  the  debt-to-GDP  ratio.  Note,  however,  that  current  spreads  would 
imply  smaller  gains.  As  pointed  out  above,  the  calibration  of  debt  risks  is  based  on 
extreme assumptions, namely adverse sovereign-corporate loops of the severity observed 
in 2011-2013.  

Interestingly,  reallocation  increases  GDP  in  the  high-income  group  due  to  higher 
exports  following  improved  demand  from  the  groups  with  a  GDP  per  capita  below 
average.38  Nonetheless,  the  provision  of  (net)  grants  increases  the  debt-to-GDP  ratio in 
the high-income group. In sum, the debt ratio increases slightly in the high-income group 
in the first years but decreases in the other blocks. 

High additionality of grants (H scenario) 

Figure 2: GDP (%) across clusters  

Low additionality of grants (L scenario) 

Note: The figure reports GDP in percent deviation from a no-policy change baseline (in levels). H and L 
scenarios refers to high and low additionality of grants (loans are always 50% additional). 

37  Household  and  firm  expectations  of  higher  future  taxes  to  cover  the  budgetary  costs  generate  some 

feedback. 

38  This  result  was  obtained  by  simulating  the  investment  programmes  only  in  the  groups  with  below-

average GDP per capita. 

47 

 
 
 
                                                 
The  GDP  effects  are  smaller  under  lower  additionality  of  grants  since  not  all 
resources  are  used  for  additional  public  investment  (L  scenario  in  the  Figure  1-3  and 
Table 2). Nonetheless,  the EU grants  free budgetary resources. Consequently, the debt-
to-GDP ratio falls more in the clusters with below-average GDP per capita compared to a 
scenario  with  full  additionality.  Exports  in  the  above-average  group,  however,  benefit 
less from sizable positive spillover (GDP effects in the other regions are small) and the 
debt-to-GDP  ratio  is  slightly  higher  than  in  the  full  additionality  case  due  to  a  smaller 
output expansion. 

Figure 3: Debt-to-GDP ratio (pps) across clusters 

High additionality of grants (H scenario) 

Low additionality of grants (L scenario) 

Note: The figure reports  the debt-to-GDP ratio deviation from a no-policy change baseline (in levels). H 
and L scenarios refers to high and low additionality of grants (loans are always 50% additional). 

3.2.2.  Labour markets 

The model simulations suggest a short-run increase in employment of in the range 
of two million jobs for the EU as a whole. Figure 4 shows as employment increases by 
up to [1.1 pp.] in 2022, the year with the highest impact resulting from stronger demand. 
The  strength  depends  on  the  assumed  additionality  of  EU  grants.  There  is  also  marked 
heterogeneity across regions. Similar to the GDP effects, employment growth is highest 
in  the  below-average  groups  –  in  particular  in  the  low  debt  cluster,  which  receives  the 
largest share (in terms of own GDP). 

In  the  medium  run,  real  wage  increases  relative  to  the  baseline  reflect  higher 
productivity  and  the  improved  labour  market  conditions.  In  the  model,  real  wages 
adjust  sluggishly  due  to  wage  adjustment  frictions  (e.g.  bargaining  processes).  Real 
wages  increase  following  higher  private  capital  and  productivity  gains  from  public 

48 

 
 
 
investment.  The  rise  in  real  wages  persists  after  the  governments  discontinue  direct 
stimulus packages.   

3.2.3.  Private investment 

The  level  of  private  investment  in  the  EU-27  is  estimated  to  be  more  than  [1%] 
higher  than  in  the  baseline  (on  average)  following  assumed  improvements  in  loan 
supply from InvestEU and ESFI, which effectively lower the cost of capital. Monetary 
policy  is  constrained  by  the  zero  lower  bound,  and  nominal  rates  are  not  raised  in 
response  to  the  investment  boom  for  two  years.  This  monetary  accommodation 
contributes  to  the  ex-post  impact  on  investment.  The  dynamics  of  the  real  interest  rate 
give rise to second-round effects on investment and the consumption of durable goods.39 
The effects on private investment are persistent. 

3.2.4.  The medium run 

Table  2  shows  that  the  levels  of  real  GDP,  real  wages,  and  private  investment 
remain persistently above a no-policy change baseline  (here shown until  2030). The 
table  also  includes  the  time  series  of  public  and  private  investment,  GDP  and  debt,  as 
well  as  employment  and  real  wages  for  all  regions  and  both  scenarios.  It  shows  the 
increases in GDP, real investment, and real wages are persistent.  

Figure 4: Labour markets and investment 

Note:  This  figure  reports  the  all  variables  in  percent  deviation  from  a  no-policy  change  baseline.  All 
variables are reported in levels. H and L scenarios refers to high and low additionality of  grants (loans are 
always 50% additional). EU-27 values are (weighted) averages. 

39 In addition, the expansionary effects of the other components of the package stimulate private investment 
further,  leading  to  a  sizable  increase  in  private  investment.  Investment  adjustment  frictions  explain 
why private investment increases more in 2022 than in 2021. 

49 

 
 
 
 
 
 
                                                 
Table 2: Detailed simulation results  

Note: All variables are reported in levels. The debt-to-GDP ratio is reported in percentage point deviation 
from a no-policy change baseline. Other variables are reported in real terms and in percent deviation from a 
no-policy change baseline. H and L refer to the assumed additionality of grants. 

50 

Region Scenario 2021202220232024202520262027202820292030L2.12.72.82.81.71.71.61.61.51.5H3.03.84.14.22.62.52.52.42.32.2L0.40.60.70.80.50.50.40.40.40.3H0.71.01.11.20.80.70.70.60.60.5L1.82.42.72.92.01.91.81.71.71.6H2.83.64.24.63.02.92.82.72.62.5L1.01.31.41.51.00.90.90.80.80.8H1.51.92.22.31.51.41.31.31.21.22021202220232024202520262027202820292030L1.31.51.10.70.0-0.1-0.1-0.10.00.0H1.82.01.61.1-0.1-0.2-0.1-0.1-0.10.0L0.30.40.40.40.20.10.10.00.00.0H0.50.60.60.60.20.10.10.00.00.0L1.11.21.00.80.10.00.00.00.00.0H1.61.81.51.20.10.00.00.00.00.0L0.60.70.70.50.10.00.00.00.00.0H0.91.11.00.80.10.00.00.00.00.02021202220232024202520262027202820292030L0.20.71.01.21.31.31.21.21.11.1H0.31.01.51.82.01.91.91.81.71.6L0.00.20.20.30.30.30.30.30.30.3H0.10.30.40.50.50.50.50.40.40.4L0.30.71.01.31.41.31.31.21.21.1H0.41.11.61.92.12.02.01.91.81.7L0.10.40.50.60.70.70.60.60.60.6H0.20.50.81.01.01.01.00.90.90.92021202220232024202520262027202820292030L2.02.92.61.91.41.21.11.11.11.1H2.13.02.72.21.71.61.61.51.51.5L0.20.40.40.40.40.40.40.40.40.4H0.30.50.60.60.60.60.60.60.60.6L1.72.62.31.71.31.11.01.01.01.0H1.82.82.62.11.71.51.51.51.51.4L0.81.31.20.90.80.70.70.60.60.6H0.91.41.31.21.01.01.00.90.90.92021202220232024202520262027202820292030L42.842.842.842.80.00.00.00.00.00.0H70.370.370.370.30.00.00.00.00.00.0L8.08.08.08.00.00.00.00.00.00.0H13.113.113.113.10.00.00.00.00.00.0L48.948.948.948.90.00.00.00.00.00.0H80.480.480.480.40.00.00.00.00.00.0L21.021.021.021.00.00.00.00.00.00.0H34.534.534.534.50.00.00.00.00.00.02021202220232024202520262027202820292030L-1.9-3.4-4.5-5.4-5.5-6.1-6.6-7.1-7.6-8.1H-2.1-3.3-4.2-4.9-4.7-5.5-6.3-7.1-7.8-8.6L0.10.40.81.21.41.21.10.90.80.7H-0.10.20.50.81.00.80.50.30.1-0.1L-1.4-2.2-3.1-3.9-4.0-4.5-5.0-5.5-6.0-6.5H-1.6-2.2-2.7-3.3-3.0-3.9-4.7-5.5-6.2-7.0L-0.6-0.8-0.9-1.0-0.9-1.2-1.5-1.8-2.0-2.3H-0.8-0.9-1.0-1.0-0.8-1.3-1.7-2.2-2.6-2.9GDP (%)Below average (high debt)Above average(high income)Below average (low debt) Employment (%)EU (weighted average)Below average (low debt)EU (weighted average)Private Investment (%)Below average (high debt)Above average(high income)Below average (low debt)Public investment (%)Below average (high debt)Below average (low debt)Above average(high income)Below average (low debt)Debt-to-GDP ratio (pps)Below average (high debt)Above average(high income)Below average (high debt)EU (weighted average)EU (weighted average)EU (weighted average)EU (weighted average)Above average(high income)Below average (low debt)Real wages (%)Below average (high debt)Above average(high income) 
 
Allocation keys 

Table A.1: Allocation key  

Note: E, S, and H groups refer to EU below average  GDP per capita (low debt), EU below average GDP per 
capita (high debt), and EU above average per capita income (high income), respectively. 

Explanatory note: illustrative key for the sole purpose of the preliminary estimation of the potential impact of 
the recovery package using the Commission’s QUEST model presented on p. 43  

51 

CountryAllocation KeyGroupGDP bnShare in EU 27 GDPRecip in bnContr (bn)Net (bn)Net (% GDP)GDP per capBE1.6                             H4743.4%12.0                   25.5                 -13.5-2.9%35900BG2.0                             E610.4%15.0                   3.3                   11.719.3%6800CZ1.5                             E2201.6%11.3                   11.9                 -0.6-0.3%18000DK0.6                             H3112.2%4.5                     16.7                 -12.2-3.9%49190DE6.9                             H343624.7%51.8                   185.1               -133.3-3.9%35980EE0.3                             E280.2%2.3                     1.5                   0.72.6%15670IE0.4                             H3472.5%3.0                     18.7                 -15.7-4.5%60350EL5.8                             S1871.3%43.5                   10.1                 33.417.8%18150ES19.9                           S12458.9%149.3                 67.1                 82.26.6%25170FR10.4                           H241917.4%78.0                   130.3               -52.3-2.2%33360HR2.0                             E540.4%15.0                   2.9                   12.122.4%11990IT20.4                           S178812.8%153.0                 96.3                 56.73.2%26860CY0.3                             S220.2%2.3                     1.2                   1.14.9%24250LV0.7                             E300.2%5.3                     1.6                   3.611.8%12490LT0.9                             E480.3%6.8                     2.6                   4.18.6%13880LU0.0                             H640.5%0.0                     3.4                   -3.4-5.4%83640HU2.0                             E1441.0%15.0                   7.7                   7.35.0%13180MT0.1                             E130.1%0.8                     0.7                   0.00.3%21890NL1.7                             H8125.8%12.8                   43.7                 -31.0-3.8%42020AT1.0                             H3992.9%7.5                     21.5                 -14.0-3.5%38240PL8.6                             E5293.8%64.5                   28.5                 36.06.8%12980PT4.2                             S2121.5%31.5                   11.4                 20.19.5%18550RO4.4                             E2231.6%33.0                   12.0                 21.09.4%9130SI0.5                             E480.3%3.8                     2.6                   1.22.4%20490SK2.0                             E940.7%15.0                   5.1                   9.910.5%15890FI0.7                             H2401.7%5.3                     12.9                 -7.7-3.2%37170SE1.2                             H4753.4%9.0                     25.6                 -16.6-3.5%43900 
 
Sovereign debt risk 

Figure  B.1  shows  the  historical  and  current  evolution  of  spreads  in  IT  and  ES 
(expressed in basis point difference to 10-year government bond yields in DE).  

Figure B.1: Dynamics of Spreads 

Note: This figure shows the historical (left panel) and current (right panel) evolution of spreads of 10-year 
government  bonds  yields  in  IT  (blue)  and  ES  (orange).  The  vertical  axis  reports  spreads  in  bps.  and  in 
difference to DE government bond yields. 

Current spreads are relatively low but rising. Current levels (as of 16/04/2020) are at 
230  basis  points  (bps)  and  127  bps  for  IT  and  ES,  respectively.  Yet,  they  remain 
significantly below the spreads observed in 2011-2013. 

The sovereign debt crisis in the euro area provides historical evidence on sovereign 
default risk and government debt in times of distress. Models of sovereign debt and 
empirical evidence often point to a nonlinear relationship between the default risk premia 
and the level of government debt: Corsetti et al. (2013) find such a relationship between 
credit  default  swaps  (CDS)  for  governments  bonds  (5-year  maturity)  and  the  level  of 
government  debt  (as  a  share  of  GDP)  for  OECD  countries.40  Figure  B.2,  taken  from 
Roeger  and  In ‘t  Veld  (2013, p.7), shows the highly  convex relationship between CDS 
spreads for governments bonds (5-year maturity).41 

Figure B.2 shows the nonlinear relation of debt levels and spreads during the peak 
of the sovereign debt crisis. Later on, the announcement of OMT in the second half of 
2012  has  reduced  spreads,  and  the  convexity  of  the  relationship  is  lower  in  February 
2013.  As  emphasized  in  Roeger  and  In  ‘t  Veld  (2013),  non-linearities  become  more 
severe for debt levels beyond 90%. There is also significant time variation and dispersion 
across countries. 

As  shown  in  Table  B.1,  the  Spring  forecast  projects  as  strong  rise  in  the  debt-to-
GDP  ratios  in  the  EU high-debt  group.    The average  debt  ratio  is  projected  to  reach 

40  Corsetti,  G.,  Kuester,  K.,  Meier,  A.  and  Müller,  G.J.  (2013),  “Sovereign  Risk,  Fiscal  Policy,  and 

Macroeconomic Stability”. Economic Journal, 123: F99-F132. doi: 10.1111/ecoj.12013   

41 Roeger W., and In ‘t Veld, J. (2013): “Expected sovereign defaults and fiscal consolidations”, European 

Economy. Economic Papers 479. April 2013.  

52 

 
 
                                                 
132%.  According  to  the  evidence  on  Figure  B.2,  the  fall  in  debt  based  the  Recovery 
Instrument would imply a reduction in risk premia by around 20 to 25 bps. 

The  simulations  assume  that  50%  of  the  sovereign  risk  premia  spill  over  to  the 
private  sector  borrowing  costs.  This  value  is  high  but  in  line  with  the  evidence  on 
sovereign-to-corporate  risk  spillover  in  Durbin  and  Ng  (2005),  implying  a  substantial 
increase  financing  costs  for  private  investment.  The  quantification  of  sovereign-to-
private  spillover  in  financing  costs  is  also  comparable  to  simulation  results  from  the 
QUEST  version  with  a  banking  sector  (Breuss  et  al.  2015).  In  this  model  version,  the 
spillover  of  sovereign  risk  to  loans  supply  and  equity  investment  is  endogenous  and 
occurs through the balance sheet, notably the capital requirements, of banks.  See also the 
discussion and evidence in In ‘t Veld (2013) and Zoli (2013). 42    

Figure B.2: 5-year sovereign CDS spreads vs debt-to-GDP ratios (July 2011) 

Table  B.1:  Debt  levels  (%  of  GDP)  in  the  high  debt  group  (ECFIN  Spring  forecast 
projection for 2021) 

42  Jan  in  ’t  Veld  (2013)  “Fiscal  consolidations  and  spillovers  in  the  Euro  area  periphery  and  core”. 

European Economy. Economic Paper no.506.  

Zoli,  E.  (2013),  Italian  Sovereign  Spreads:  Their  Determinants  and  Pass-through  to  Bank  Funding  Costs 

and Lending Conditions, IMF Working Paper 13/8. 

53 

CountryGDP bnShare in high debt clusterDebt-to-GDP ratioforecast 2021ES124536%113.7IT178852%153.6EL1875%182.6PT2126%124.4CY221%105