Quarterly report on the euro area. Volume 17, No 3 (2018).
Date: 2019-01-04
Institutions: Directorate-General for Economic and Financial Affairs
Subjects: Economic and Monetary Union, activity report, euro, euro area

ISSN 2443-8014 (online) 

Quarterly 
Report 
on the Euro Area

Volume 17, No 3 (2018)

INSTITUTIONAL PAPER 093 | DECEMBER 2018

EUROPEAN ECONOMY

Economic and 
Financial Affairs

The  Quarterly  Report  on  the  Euro  Area  is  written  by  staff  of  the  Directorate-General  for  Economic  and 
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European Commission 
Directorate-General for Economic and Financial Affairs 

Quarterly Report on the Euro Area 
Volume 17, No 3 (2018) 

EUROPEAN ECONOMY                                                                                   Institutional Paper 093 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table of contents 

Editorial 

I. 

II. 

III. 

IV. 

Introduction 

Wage dynamics in the EMU 
I.1. 
I.2.  Wage developments in the euro area: Setting the scene 
I.3.  Wage responsiveness to labour market slack 
I.4.  Wage dynamics and rebalancing in the euro area 
I.5. 
I.6. 

Policy instruments that influence wage developments 
Conclusions 

Introduction 

Determinants of economic resilience in the euro area: An empirical assessment of 
policy levers 
II.1. 
II.2.  A framework for empirical analysis 
II.3.  Factors affecting the shock absorption capacity and persistence of shocks 
II.4.  An econometric analysis of the absorption and recovery capacity: Illustrative results 
II.5.  Conclusions and policy implications 

Assessing Prudent NIIP and Current Account Positions 
III.1.  Introduction 
III.2.  Prudential benchmarks for the NIIP 
III.3.  The required current account 
III.4.  Results for EU Member States 
III.5.  Conclusion 

Cyclical patterns of residential construction 
IV.1.  Introduction 
IV.2.  Past residential construction cycles and GDP growth 
IV.3.  Drivers of residential construction investment 
IV.4.  Model-based prospects for residential construction 
IV.5.  Conclusion 

Boxes 

I.1. 

Estimating wage growth using an augmented Phillips curve 

7 

9 
9 
10 
11 
17 
19 
25 

27 
27 
28 
29 
37 
41 

47 
47 
48 
51 
55 
57 

59 
59 
60 
61 
64 
66 

15 

 
 
 
 
 
 
 
II.1.  Estimating absorption and recovery capacity in case of common shock. 
II.2.  Data on structural factors. 
II.3.  Econometric results. 

30 
36 
43 

 
 
 
 
Marco Buti 
Director-General 

Over  the  past  two  years,  the  euro  area  has  benefitted 
from  a  broad-based  economic  expansion.  While 
relatively strong growth has helped re-absorb the large 
output  gap  accumulated  during  the  financial  crisis, 
potential  growth  remains  subdued  in  most  Member 
States  and  the  euro  area  as  a  whole.  Most  of  the 
reforms needed to lift growth potential also strengthen 
economic  resilience  by  reducing  vulnerability  and 
boosting the economy’s ability to adjust to shocks.  

This  issue  of  the  QREA  provides  policy-relevant 
empirical analysis related to wage  dynamics, the move 
towards 
external 
economic 
sustainability,  as  well  as  the  cyclical  patterns  of 
residential construction investment. 

structures, 

resilient 

slack  and  weak 
to 

The  first  section  discusses  wage  dynamics  and  the 
relevance  of  wage  behaviour  for  macroeconomic 
adjustment  in  a  monetary  union.  Whilst  in  the  past, 
economic research on wages typically focussed on their 
importance  as  a  signal  guiding  the  efficient  allocation 
of  resources  and  their  role  in  sustaining  demand, 
greater  attention  is  now  paid  to  the  role  of  wages  in  
delivering  inclusive  growth.  The  analysis  in  this  issue 
shows  that  nominal  wage  growth 
in  the  recent 
recovery has not been picking up in the way one would 
expect  based  on  the  historical  relationship  with 
standard  indicators  of  labour  market  slack.  While 
remaining  pockets  of 
labour 
productivity  growth  contribute 
the  subdued 
behaviour of wages, they do not fully explain the slow 
pace of  growth. Incorporating  low core inflation and 
“sticky” 
inflation  expectations,  however,  enables 
current  wage  developments  to  be  predicted  with 
reasonable  precision.  The  potential  contribution  of 
other factors is assessed in a qualitative way, including 
broader measures of labour under-utilisation, declining 
hours  worked  per  employee,  the  after-effects  of 
downward  nominal  wage  rigidities,  and  the  impact  of 
such  as  globalisation, 
other 
technological progress and the decline in unionisation. 
Looking  ahead,  the  section  reports  that  productivity-
increasing  structural  reforms,  such  as  reforms  that 
make  labour  markets  more  adaptable  and  responsive 
improve  allocative  efficiency,  and  adequate 
and 
and 
investment 

structural  changes 

research 

capital, 

human 

in 

Editorial 

development  are  key  to  supporting  overall  wage 
growth. 

level, 

factors 

structural 

The second section is an econometric investigation of 
the  determinants  of  economic  resilience,  in  particular 
influencing  a  euro  area 
the 
economy’s  ability  to  absorb  and  recover  from  a 
common  shock.  The  potential  determinants  include 
diverse  factors  that  affect  the  working  of  markets  at 
such  as  product  market 
Member  State 
regulations, as well as other structural characteristics of 
economies,  including  openness  to  international  trade. 
The  analysis  suggests  that  euro  area  Member  States 
differ considerably in terms of their capacity to absorb 
from  common  shocks.  The  main 
and  recover 
determinants of resilience are related to how efficiently 
markets  function,  particularly  financial  and  product 
markets,  and 
the  business  environment.  More 
specifically, the findings suggest that a higher share of 
non-performing  loans  in  total  gross  loans  and  a 
weakening  of  competition  in  the  banking  sector,  as 
well  as  product  market  regulations,  such  as  state 
control  over  price  setting  and  network  industries,  has 
an  unambiguous  negative 
the 
absorption and recovery capacity. Trade openness also 
contributes to stronger resilience, although more open 
countries  are  also  more  affected  by  external  shocks. 
The 
interplay  between  the  various  determinants, 
together  with  the  ambiguous  impact  of  some  factors 
also call for further analysis.  

impact  on  both 

the  sustainability  of  euro  area 
To  help  assess 
third  chapter 
the 
economies’  external  positions, 
presents  a  methodology 
to  estimate  prudential 
benchmarks  or  reference  values  for  a  country’s  net 
international  investment  position  (NIIP).  The  results 
suggest that while stock imbalances persist in some EU 
countries,  external  sustainability  risks  continue  to 
abate.  Several  net  debtor  countries  still  have  legacy 
NIIPs  that  exceed  such  prudential  benchmarks.  But 
the  balanced  or  positive  current  accounts  in  most  of 
these Member States put them on track to return their 
NIIPs to safe levels by the mid-2020s at the latest. By 
contrast, while EU creditor countries by definition do 
not  face  external  sustainability  risks,  they  continue  to 
run current account surpluses that will further increase 

Volume 17 No 3 | 7 

 
 
 
 
The analysis provided in this issue of the QREA 
underscores  the  importance  of  implementing 
reforms – taking advantage of the still favourable 
economic conditions – that will help the euro area 
to  withstand  future  economic  and  financial 
shocks  and  deliver  sustainable  growth.  At  the 
same time, it points out that policy makers should 
guard  against  imbalances  that  could  develop  into 
self-fulfilling  crises  that  could  endanger  the 
functioning and cohesion of EMU. This must go 
hand-in-hand with reforms to the architecture of 
the  EMU–  starting  with  the  completion  of  the 
Banking  Union,  strengthening  the  institutional 
framework, and making progress on developing a 
viable central fiscal capacity. We have made great 
strides in deepening the EMU since the crisis but 
our  union  will  remain  vulnerable  until  we 
complete the extra mile. 

their NIIPs from already high levels. The combination 
of  policies  leading  to  a  gradual  reduction  of  both 
NIIPs  and  current  account  surpluses  would  make  the 
euro area more resilient as well as facilitate internal and 
external rebalancing.  

The final chapter examines the cyclical patterns of 
residential  construction  investment  in  the  euro 
area and selected EU Member States over the past 
several  decades.  The  behaviour  of  residential 
investment  is  important,  as  housing  and  GDP 
cycles are closely linked. Also, the boom and bust 
of  residential  construction  has  often  led  to  the 
accumulation  and  unwinding  of  large  imbalances 
within  the  euro  area  and  the  EU.  The  analysis 
residential 
the  main  drivers  of 
quantifies 
construction  in  the  short  and  medium  term.  It 
finds that, in the long run, residential construction 
activity  is  determined  by  real  disposable  income 
and  to  a  lesser  extent,  population  developments. 
In  the  short  run,  residential  construction  cycles 
are 
and 
unemployment.  The  positive  developments  now 
underway  in  the  labour  market  and  the  rise  in 
house  prices  should  thus  underpin  a  continued 
expansion  of  residential  construction  investment 
in the euro area in the near term. It may, however, 
weaken  in  Member  States  where  the  residential 
construction cycle is more advanced. 

to  house  prices 

related 

also 

8 | Quarterly Report on the Euro Area 

 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
I. Wage dynamics in the EMU 

This section takes stock of recent wage developments  in the euro area given their importance for the 
well-functioning  of  the  EMU.  In  the  euro  area,  wage  developments  not  only  affect  the  allocation  of 
resources and social cohesion, but also macro-economic adjustment. The latter is especially important 
in view of the remaining rebalancing challenges in the euro area. The section identifies several factors 
that may have caused sluggish wage growth in the euro area until recently, in spite of robust economic 
growth.  It  shows  that  remaining  slack  and  low  productivity  growth  can  account  for  some  of  this 
slowdown in wage growth, but leave a significant amount unexplained. Adding backward- and forward-
looking  inflation  measures  improves  the  fit  of  the  predicted  values  considerably.  Other  potential 
contributing factors to the observed wage dynamics are reviewed as well: broader measures of labour 
market  slack,  ongoing  structural  labour  market  changes,  the  downward  trend  in  hours  worked  per 
employee,  and  the  after-effects  of  downward  nominal  wage  rigidities.  The  section  shows  that  while 
wage  developments  mainly  result  from  the  interaction  between  market  forces,  policymakers  have  a 
number  of  instruments  at  hand  to  influence  wage  developments.  These  include  public  and  minimum 
wages,  the  tax  and  benefit  system,  and  the  steering  of  collective  bargaining  in  the  private  sector  via 
tripartite  agreements  or  by  reviewing  legal  frameworks  for  negotiation  in  consultation  with  social 
partners.  Structural  reforms  can  also  influence  wage  and  labour  cost  developments,  albeit  in  a  more 
indirect  way.  Of  particular  importance  are  reforms  that  support  productivity  growth,  e.g.  by  making 
labour markets more adaptable and improving allocative efficiency, and by investment in human capital 
and innovation. (1) 

I.1.  Introduction  

Wages play a key role in an economy. Sound wage 
behaviour  can  support  economic  resilience,  by 
being  a  possible  channel  for  macro-adjustment  in 
the  face  of  certain  types  of  shocks.  This  is 
especially relevant in a currency union, where other 
channels  for  adjustment  (such  as  exchange  rate 
adjustment)  can  no  longer  be  used.  Relative  wage 
differences  across  the  economy  can  also  signal 
where labour can be put to its most productive use, 
and  hence  where  labour  resources  should  be 
allocated.  At  the  same  time,  wages  are  crucial 
determinants of household incomes, and hence of 
aggregate demand and (inclusive) growth.   

is  entering 

The  euro  area 
its  sixth  year  of 
uninterrupted economic growth, and is expected to 
continue  growing,  albeit  at  slowing  pace  (from 
2.4% in 2017 to 1.9% in 2020). (2) The output gap 
is  estimated  to  have  fully  closed  in  2018.  These 
improvements  are  also  observed  in  the  labour 
market, which continues to recover at a rapid pace, 
with employment reaching pre-crisis levels in 2017 
and  unemployment  rates  gradually  approaching 

levels  prior  to  the  recession.  According  to  the 
Commission's 
forecasts,  unemployment  will 
decline from 9.1% in 2017 to 7.5% by 2020. 

Several  studies  have  however  observed  that  until 
recently,  nominal  wage  growth (3)  was  not  picking 
up  as  one  would  expect  based  on  its  historical 
relationship  with  standard  indicators  of  economic 
activity and labour market slack. (4)  

Different  reasons  have  been  advanced  by  now  to 
explain  this,  including  low  core  inflation,  "sticky" 
inflation expectations, a reduction in hours worked 
per  employee,  weak  productivity  developments, 
and  structural  labour  market  developments.  In 
countries  where  un(der)employment  remains  high 
compared  to  pre-crisis  levels,  labour  market  slack 
continues  to  exert  downward  pressure  on  wage 
growth.  

Subdued wage growth risks being a drag on private 
consumption, currently the main driver of growth. 
If  wage  growth  is  below  consumer  price  inflation, 
real  disposable  incomes  are  eroded.  Low  wage 
growth in itself puts a break on inflation. Low price 

(1)  This  section  was  prepared  by  Anneleen  Vandeplas,  Alfonso 
Arpaia, Eric Ruscher, Alessandro Turrini, and Werner Röger. The 
authors  wish  to  thank  Erik  Canton,  Pedro  Cardoso,  Barbara 
Kauffmann, Aron Kiss, Erik Meyermans, Karl Pichelmann, Mary 
Veronica  Tovsak  Pleterski  and  Václav  Žďárek  for  useful 
comments. 

(2)  European  Commission  (2018a)  European  Economic  Forecast, 
Autumn  2018.  DG  Economic  and Financial  Affairs  Institutional 
Paper 0789, November 2018. 

(3)  Measured in terms of nominal compensation per employee. In the 
remainder of this note, the term "wages" will be used to refer to 
nominal wages, unless otherwise (explicitly) stated. 

(4)  e.g.  Buti,  M.,  Turrini,  A.  (2017)  Overcoming  Eurozone  wage 
inertia.  Voxeu.org,  6  October  2017;  Bulligan,  G.,  Guglielminetti, 
E., Viviano, E. (2017) Wage growth in the euro area: where do we 
stand?,  Questioni  di  Economia  e  Finanza  (Occasional  Papers) 
413,  Bank  of  Italy;  ECB  (2017)  Assessing  labour  market  slack. 
ECB Economic Bulletin, Issue 3/2017 – Boxes. 

Volume 17 No 3 | 9 

 
                                                      
                                                      
the  European  Semester, 

inflation  can  also  hamper  rebalancing  within  the 
euro  area  by  complicating  real  wage  adjustment. 
These  considerations  have  brought  the  issue  of 
wage growth to the forefront of policy attention. In 
the  context  of 
the 
European Commission and the European Council 
have  encouraged  surplus  countries 
to  create 
conditions  to  promote  higher  real  wage  growth, 
while  respecting  the  role  of  social  partners.  Faster 
real  wage  growth  in  the  euro  area  as  a  whole  is 
expected to help sustain domestic demand, reduce 
inequalities  and  ensure  higher  standards  of  living, 
thereby  contributing  to  the  realisation  of  the  fair 
wage  principle  of  the  European  Pillar  of  Social 
Rights.(5)  Some observers have called for stronger 
coordination of (nominal) wage dynamics between 
euro area Member States. (6)   

In  this  context,  this  section  provides  an  overview 
of recent wage dynamics in the euro area, their link 
with  economic  slack  and  their  implications  for 
intra-euro area rebalancing. The section also looks 
into  the  set  of  instruments  governments  have  at 
hand to influence wage setting. 

I.2.  Wage developments in the euro area: 

Setting the scene 

Nominal  wage  growth  is  picking  up  in  the  euro 
area. Wages are estimated to have grown at 1.6% in 
2017,  up  from  1.1%  in  2016  (Graph  I.1).  Going 
further, wage growth is expected to reach 2.3% in 
2018 (including as a result of a pick-up in inflation) 
and then slow down again to 2.0% in 2019. (7) 

At  the  individual  country  level,  nominal  wage 
growth has been positive but still moderate in most 
cases in recent years (Graph I.1). (8) Nominal wage 
developments  remained  particularly  flat  in  those 
countries  still  characterised  by  high  levels  of 
unemployment,  notably  Greece,  Spain,  Italy,  and 
Cyprus. Wage growth was even slightly negative in 

(5)  see e.g. Annual Growth Survey 2018 (COM(2017) 690 final); 2018 
Council  recommendation  on  the  economic  policy  of  the  euro 
area. Faster real wage growth in the euro area can also contribute 
to the realisation of the fair wage principle of the European Pillar 
of Social Rights (C(2017) 2600 final); and Annual Growth Survey 
2019 (COM(2018) 770 final). 

(6)  See e.g. Ragot, X. (2017) How to further strengthen the European 
Semester?  In-depth  analysis  provided  at  the  request  of  the 
Economic  and  Monetary  Affairs  Committee  of  the  European 
Parliament. 

(7)  European Commission (2018a), as above 
(8)  See  also  European  Commission  (2018b),  Labour  Market  and 
in  Europe.  Annual  Review  2018, 
for  Employment,  Social  Affairs  and 

Wage  Developments 
Directorate-General 
Inclusion. 

10 | Quarterly Report on the Euro Area 

Greece,  Spain  and  Cyprus  in  2016,  but  turned 
positive in 2017. In 2016, low wage growth (1% or 
below) was also observed in Belgium, France, and 
a 
Luxembourg,  which 
deterioration of their external position and a loss of 
cost  competitiveness  during  the  crisis.  In  2018, 
most  euro  area  countries  saw  an  acceleration  of 
wage  growth.  Only  in  Greece,  Spain,  Finland, 
Cyprus,  Portugal  and  Italy, nominal  compensation 
growth is estimated to remain below 2% in 2018.  

experienced 

had 

Graph I.1: Nominal compensation per 
employee, 2016-18,  annual % change 

the 

indicator  "Nominal 
(1)  Wages  are  measured  by 
compensation  per  employee",  which  is  calculated  as  a  total 
compensation  of  employees  divided  by  total  number  of 
employees.  The  total  compensation  is  defined  as  the  total 
remuneration,  in cash  or  in  kind,  payable by an employer to 
an employee in return for work done by the latter during the 
accounting  period  and  it  has  two  components:  i)  Wages  and 
salaries payable in cash or in kind; and ii) Social contributions 
payable  by  employers.  All  data  used  are  national  accounts 
data.  The  indicators  are  based  on  national  currency  values. 
2018  values  are  based  on  ECFIN’s  2018  Autumn  Forecast 
Aggregates  are  weighted  averages.  Countries  are  ranked  in 
ascending order of the unemployment rate in 20167. 
Source: European Commission, AMECO database. 

In 

Wages  grew  relatively  slowly  in  Germany  and  the 
Netherlands,  the  two  countries  with  the  strongest 
current account surpluses in the euro area. In spite 
of declining unemployment, wage growth declined 
from  2.8%  to  2.2%  over  the  period  2014-2016  in 
nominal 
Germany. 
compensation  grew  at  a  relatively  modest  rate  in 
2016  and  2017  (at  1.2%),  after  negative  observed 
growth in 2015. By 2018, wage growth is estimated 
the 
to  have  accelerated 
Netherlands (to 2.9 and 2.4% respectively), but not 
to the extent that it compensates for the period of 
slow wage growth in previous years.  

in  Germany  and 

the  Netherlands, 

Wages grew faster in euro area Member States with 
the lowest wage levels, partially as a result of rapid 

-20246810DEMTNLATLUEESIIEBELTSKFILVPTEA19FRCYITESEL201620172018  
 
                                                      
 
catching-up  of  GDP  per  capita  to  the  average. 
Annual growth of nominal wages lingered between 
6-9% in Estonia, Latvia and Lithuania in 2016 and 
2017.  In  Slovakia  wage  growth  saw  a  temporary 
drop  in  2016,  but  recovered  to  a  steady  5.2%  in 
2017.  Also  in  2018,  these  countries  continue  to 
observe steady wage growth. 

At the same time, purchasing power has increased, 
as real wages rose in most euro area countries over 
the  period  2015-17,  in  spite  of  the  uptick  in 
inflation.  The  increase  in  real  consumption  wages 
(i.e.  wages  adjusted  for  the  change  in  consumer 
prices)  helped  sustain  aggregate  demand.  Real 
consumption  wages 
in  Spain  and 
Greece—due  to  a  decline  in  nominal  wages–-and 
in  Italy,  Belgium,  and  Finland  where  it  was  the 
result  of  consumer  price 
inflation  exceeding 
nominal wage growth.  

fell  only 

Over  the  longer  term,  while  real  wage  growth  has 
been broad-based, it has not always kept pace with 
productivity  growth.  Cumulative  growth  in  real 
compensation  since  2000  amounts  to  10%  on 
average  in  the  euro  area  (around  0.6%  annually) 
(Graph I.2). The strongest growth was observed in 
countries  starting  from  the  lowest  wage  levels 
(Latvia,  Lithuania,  Estonia),  where  purchasing 
power roughly doubled over the considered period, 
partially  as  a  result  of  rapid  catching-up  of  GDP 
per capita to the EU average. Real wage growth in 
line  with  productivity  supports  sustained  firm 
profitability  and  sustainable  job  creation,  growth, 
and  underpins  increases  in  living  standards.(9)  On 
average  in  the  euro  area,  real  wage  growth  was 
slightly  weaker  than  productivity  growth  over  the 
period  2000-17  resulting  in  a  slight  decline  in  real 
unit labour costs of 1.7 ppt (Graph I.2). The largest 
gaps were observed in Ireland and Portugal. (10) A 
smaller  gap  is  noted  in  Spain,  Malta,  Cyprus  and 
Germany.    

Even  if  inflation  remained  weak,  the  inflation 
component  was  the  main  contributor  to  wage 
growth in the EA. Growth of real wages has been 
trailing marginally behind productivity growth since 
2012; and this is expected to remain the case over 

(9)  Note that real unit labour costs are also a (rough) measure of the 
labour  income  share  (labour  income  as  a  share  of  GDP),  which 
has  a  positive  relationship  with  aggregate  demand  to  the  extent 
that the marginal propensity to consume out of labour income is 
higher  than  the  marginal  propensity  to  consume  out  of  capital 
income. 

(10)  The  Irish  case  is  particular  as  its  real  GDP  grew  by  more  than 

25% in 2015 as a result of revisions in calculation methods. 

I. Wage dynamics in the EMU 

the  forecast  period  (with  the  exception  of  2018). 
Hence,  while  nominal  unit  labour  cost  growth  is 
estimated to have accelerated to 1.6% in 2018 (up 
from  0.7%  in  2017)  as  a  result  of  a  pick-up  in 
inflation;  real  unit  labour  costs  are  predicted  to 
continue on their gradual decline in the euro area. 

Graph I.2: Cumulative growth in real 
compensation and real unit labour costs, 
2000-17 

(1) Real compensation is measured as nominal compensation, 
deflated  with  private  consumption  prices.  Real  unit  labour 
costs  are  defined  as  the  ratio  of  real  compensation  per 
employee  over  GDP  per  worker  (in  this  case,  both  deflated 
with the GDP price deflator). 
Source: European Commission, AMECO database 

The  largest  real  unit  labour  cost  reductions  over 
2015-17  were  observed  in  Ireland,  Cyprus,  Malta 
and  Finland.  In  contrast,  real  wage  growth 
exceeded  productivity  growth  significantly  in  the 
Baltic  States,  Slovakia,  and  Luxembourg,  resulting 
in positive real unit labour cost growth. 

I.3.  Wage responsiveness to labour market 

slack  

I.3.1.  Stylised facts of subdued wage growth 

Wage  growth  tends  to  reflect 
labour  market 
conditions,  as  depicted  by  the  Phillips  curve.  The 
Phillips  curve  relation  predicts  that  wage  growth 
will be higher in tight labour markets, and lower in 
the presence of substantial labour market slack. (11) 
A  steeper  Phillips  curve  reflects  a  stronger 
relationship  between  wages  and  labour  market 
slack,  in  other  words,  that  wage  growth  is  more 
reactive  to  cyclical  fluctuations  in  unemployment; 
conversely,  a  flatter  curve 
implies  a  weaker 
response. 

In  2016  and  2017,  wage  growth  in  the  euro  area 
remained  almost  one  ppt  below  what  would  be 
expected  based  on  its  historical  relationship  with 

(11)  Phillips, A. W. (1958). The Relationship between Unemployment 
and  the  Rate  of  Change  of  Money  Wage  Rates  in  the  United 
Kingdom, 1861-1957. Economica, 25, 283-299. 

Volume 17 No 3 | 11 

-40-20020406080100120IEPTESMTCYDEATSIEA19NLBEFIELLTFRITSKLUEELVReal unit labour costsReal compensation peremployee 
                                                      
 
 
                                                      
unemployment,  as  shown  by  simple  cross-time 
scatter  plots  (Graph  I.3).  The  aggregate  picture 
hides  considerable  heterogeneity  across  countries 
(Graph I.4). (12) Still, in virtually all countries, wage 
growth in 2016 and 2017 was slower than or equal 
to  what  would  be  expected  on  the  basis  of  its 
historical 
unemployment. 
Countries in which wage growth remained furthest 
below  the  historical  relationship  are  Belgium, 
Spain, and Finland.  

relationship  with 

low  core 

Different  reasons  contribute  to  explaining  the 
observed  subdued  wage  growth.  These  reasons 
include 
inflation,  weak  productivity 
developments,  "sticky"  inflation  expectations,  a 
reduction  in  hours  worked  per  employee,  and, 
especially  in  countries  where  labour  resources 
remain  underutilised,  the  effect  of  remaining 
"slack"  in  the  labour  market  and  pent-up  wage 
deflation. (13)   

Graph I.3: Phillips curve for EA19 2000-18 

Source: European Commission, AMECO database 

In what follows, these arguments will be reviewed 
in  more  detail.  While  the  analysis  focuses  on  the 
euro  area,  the  findings  are  likely  to  apply  to  non-
euro  area  countries  as  well.  Many  of  the  results 

(12)  In  some  countries  such  as  AT  and  SK,  no  negative  relationship 
between unemployment and wage inflation is observed at all. This 
phenomenon  has  been  noted  earlier,  e.g.  by  Bhattarai, K.  (2016) 
Unemployment-inflation trade-offs in OECD countries.  Economic 
Modelling, 58: 93-103. 

(13)  This  implies  that  wages  are  growing  slower  during  the  recovery 
because they were unable to decline considerably during the crisis 
(to  the  value  consistent  with  high  unemployment)  as  a  result  of 
downward  nominal  wage  rigidities  (Yellen,  2014;  Daly  and 
Hobijn,  2015).  See  Yellen,  J.  (2014),  "Labour  Market  Dynamics 
and  Monetary  Policy";  speech  at  the  Federal  Reserve  Bank  of 
Kansas  City  Economic  Symposium,  Jackson  Hole,  Wyoming; 
Daly,  M.C.,  Hobijn,  B.  (2015)  Why  is  Wage  Growth  so  Slow? 
FRBSF  Economic  Letter  2015-01,  Federal  Reserve  Bank  of  San 
Francisco.  

12 | Quarterly Report on the Euro Area 

presented  are  drawn  from  early  research,  and 
further  monitoring  and  analysis  is  needed  to 
corroborate their robustness. Results are also likely 
to  differ  depending  on  the  perspective  that  is 
taken,  i.e.  whether  the  euro  area  is  considered  on 
aggregate,  or  whether  analysis  zooms 
in  on 
individual countries. 

I.3.2.  Traditional measures of slack, 

productivity and inflation 

the  output  gap,  a 

European  Commission  analysis  focusing  on  the 
euro  area  confirms  the  important role  of standard 
measures  of  slack  in  explaining  wage  growth  but 
also that these measures are insufficient to explain 
recent  developments.  A  regression  which  only 
traditional  slack 
includes 
indicator, 
growth 
captures  observed  wage 
reasonably  well  for  much  of  the  sample  period 
(Graph  I.5,  line  PV1). (14)    However,  it  fails  to 
explain why the rapid narrowing of the output gap 
since 2014 has not been matched by higher growth 
in compensation per employee in 2015-2017. Using 
other  measures  of  economic  slack,  such  as  the 
unemployment gap, leads to similar results.  

Low  productivity  growth  is  weighing  on  wage 
growth. Productivity growth, typically an important 
driver of wage growth, has been sluggish in recent 
years.  Whereas  real  productivity  per  person 
employed  over  the  period  2004-2007  grew  on 
average by 1.3% a year in the euro area, this slowed 
down  during  the  crisis  to  around  0.3%  over  the 
period  2008-2012;  to  recover  to  0.7%  on  average 
over  the  period  2013-2017.  The  shortfall  of 
investment  is  likely  to  have  reduced  productivity 
growth during the crisis. 

More  recently, 
the  structure  of  employment 
creation may have contributed to low productivity 
developments, as job creation has been particularly 
strong  in  lower-productivity  sectors. (15)  On  the 
other hand, a decline in labour productivity growth 
has  already  been  observed  since  the  mid-1990s  in 
the euro area. (16) 

(14)  For more details on the underlying regression model, see Box II.1. 
(15)  ECB  (2015)  What  is  behind  the  recent  rebound  in  euro  area 

employment? Economic Bulletin, Issue 8, December 2015. 

(16)  Gomez-Salvador,  R.,  Musso,  A.,  Stocker,  M.,  Turunen,  J.  (2006) 
Labour  productivity  developments 
in  the  euro  area.  ECB 
Occasional Paper No. 53, October 2006; Andrews, D., Criscuolo, 
C.,  Gal,  P.  (2017)  The  best  vs  the  rest:  the  global  productivity 
slowdown  hides  an  increasing  performance  gap  across  firms. 
VoxEU, 27 March 2017. 

  
 
 
                                                      
                                                      
I. Wage dynamics in the EMU 

Graph I.4: Phillips curves for individual euro area countries (2000-18) 

Source: European Commission, AMECO database 

Volume 17 No 3 | 13 

 
 
 
 
low 

Adding  productivity  growth  on  top  of  the  output 
gap  as  an  explanatory  variable  in  the  regression 
enhances  the  overall  model  fit  (Graph  I.5,  line 
level  of  productivity  growth 
PV2).  The 
observed in the current recovery has been pushing 
wage  growth  down  compared  with  the  immediate 
pre-crisis  period.  However,  this  effect  remains 
relatively  small  and  reduces  the  gap  between 
observed and estimated wage growth over the past 
three years only modestly. (17) 

Nominal  wage  growth  reflects  past  inflation  and 
inflation  expectations.  Workers  account  for  price 
developments  in  their  wage  demands  to  protect 
their  purchasing  power.  Inflation  has  been  low  in 
recent  years,  not  only  because  of  weak  wage 
growth,  but  also  as  a  result  of  low  energy  and 
unprocessed food prices. Price inflation can have a 
lasting  impact  on  wages,  if  inflation  expectations 
are  "sticky"  and  wage  negotiations  backward 
looking.  

Graph I.5: Compensation per employee: 
realised and estimated growth in the euro 
area 

(1)  PV1:  comp/employee  on  constant  and  OG  (Box  II.2  reg. 
1);  PV2:  comp/employee  on  constant,  OG  and  productivity 
growth  (Box  II.2  reg.  2);  PV3:  comp/employee  on  OG, 
productivity growth, core inflation and SPF (Box II.2 reg. 3) 
Source: Source: DataInsight, Commission calculations 

Controlling 
inflation 
expectations  leads  to  significant  improvements  in 

inflation  and 

for  past 

(17)  Schwellnus  et  al.  (2017)  find  that  over  the  past  two  decades, 
aggregate  labour  productivity  growth  in  most  OECD  countries 
has  decoupled  from  real  median  compensation  growth,  implying 
that raising productivity is no longer sufficient to raise real wages 
for the typical worker. This decoupling is explained by declines in 
both labour shares and the ratio of median to average wages. See 
Schwellnus,  C.,  A.  Kappeler  and  P.  Pionnier  (2017),  Decoupling 
of  wages  from  productivity  –  macro  facts,  OECD  Economics 
Department Working Papers, No. 1373. 

14 | Quarterly Report on the Euro Area 

the  model  fit.  If,  in  addition  to  the  output  gap, 
backward  and  forward-looking  inflation  measures 
are  included  in  the  model  (and  no  constant  is 
included),  both  inflation  variables  are  significant 
and  help  explain  a  considerable  part  of  the  low 
wage growth registered over the recent period. The 
gap  between  observed  and  fitted  growth  rates 
identified  in  the  previous  specifications  largely 
disappears (Graph I.5, PV3). Adding a constant to 
the  specification  improves  the  model  fit  slightly, 
but  comes  to  the  detriment  of  the  inflation 
expectations  variable  becoming  insignificant.  This 
latter  finding  supports  the  view  that  the  constant 
actually  captures  a  large  share  of  the  information 
otherwise  provided  by  forward  looking  inflation 
variables,  suggesting  that  inflation  expectations  in 
the euro area wage formation process have a strong 
sticky component. 

To  account  for  possible  non-linearities,  a  time-
varying  parameter  version  of  the  wage  Phillips 
curve has also been estimated.  The results suggest 
visible  changes  in  the  estimated  coefficient  of  the 
baseline model over time. In particular, the results 
point  to  an  increasing  tendency  towards  a  more 
backward  looking  wage  formation  system  during 
the first decade of the euro. The non-linear model 
similarly  points  to  a  slight  flattening  of  the  wage 
Phillips curve since about 2011. (18)  

I.3.3.  Broader measures of labour 

underutilisation  

Traditional  measures  of  slack  such  as 
the 
unemployment  rate  may  underestimate  the  extent 
of  underemployment  in  the  post-crisis  world.  (19) 
Available  data  suggest 
that  discouraged  and 
underemployed  or  involuntary  part-time  workers 
constitute  a  significant  part  of  the  population  in 
some  countries  of  the  euro  area  and  may  exert 
additional  downward  pressures  on  wages.  The 
effect  of  these  factors  is  not  straightforward  to 
identify  empirically  as  a  result  of  data  availability 

(18)  Similar  results  have  been  reported  in  European  Commission 
(2017),  Labour  Market  and  Wage  Developments  in  Europe. 
Annual  Review  2017,  Directorate-General  for  Employment, 
Social Affairs and Inclusion 

(19)  See  e.g.  ECB  (2017a)  Assessing  labour  market  slack.  Economic 
Bulletin Issue 3; Coeuré, B. (2017), Scars or scratches? Hysteresis 
in the euro area, ECB, 19 May 2017; Ciccarelli, M. and C. Osbat 
(2017), Low inflation in the euro area. Causes and consequences, 
ECB  Occasional  paper  series,  No  181;  European  Commission, 
2017,  as  above;  IMF  (2017)  Recent  wage  dynamics  in  advanced 
economies: drivers and implications, Chapter 2, World Economic 
Outlook,  August  2017;  Bell,  D.,  Blanchflower,  D.  (2018) 
Underemployment in the US and Europe. NBER WP 24927. 

-6-303601234200020022004200620082010201220142016% of trend GDPyoy %-changeactual comp/employeePV 1PV 2PV 3EA output gap  
 
 
                                                      
                                                      
I. Wage dynamics in the EMU 

issues  (notably  long  time  series  data  on  these 
broader  measures).  That  being  said,  Commission 
analysis  suggests  that  the  additional  explanatory 
power provided by these labour market measures is 
relatively low, although it could be more significant 
in  some  Member  States  where  the  increase  in 

underemployed  part-time  workers  since  the  crisis 
has been very large. (20) 

(20)  European Commission (2017), as above. 

Volume 17 No 3 | 15 

Box I.1: Estimating wage growth using an augmented Phillips curveA new Keynesian wage Phillips curve (WPC) for the euro area is estimated,(1) taking in its standard specification the following form:  𝑡𝑤=𝑐𝑜𝑛𝑠𝑡+𝛼𝑔𝑎𝑝𝑡+𝛽𝑝𝑟𝑜𝑑𝑡+𝛾𝑡−2𝑐+𝛿𝐸𝑡𝑡+4+𝜀𝑡 Where wt denotes quarter-on-quarter wage growth measured by compensation per employee(2) and gap the level of the output gap based on trend real GDP published in DG ECFIN's AMECO database. prod denotes quarter-on-quarter changes in labour productivity defined as real output per employee, ct-2 is a backward-looking inflation measure (lagged by two quarters)(3) and Ett+4 1-year ahead inflation expectations obtained from the ECB's Survey of Professional Forecasters (SPF). t is an independently and identically distributed error term.  Various specifications of the WPC in its broadest form are estimated. This includes specifications on the one hand relying only on the output gap or labour productivity growth as explanatory variables and more detailed ones which also reflect particular labour market situations or time variations in the constant using dummy variables. The regressions underlying the predicted relationships in Graph II.4 are presented in Table 1. (4)      Different robustness checks are carried out (but not reported here). Model specifications using the unemployment gap as an alternative measure of economic slack result in a deterioration of the overall fit as the variable is not highly significant. If the unemployment rate is used, results are comparable to the standard specification based on the output gap. A broader measure of the unemployment rate, i.e. one including underemployed part-time workers or discouraged workers, is available for a very limited time span covering only the period 2008 to 2017. The output gap is therefore retained as preferred slack variable as it provides a more compressive assessment of the state of the economy in the cycle. Moreover, it allows for more straightforward interpretations of the constant (i.e. it largely captures inflation expectations).                                                            (1) See e.g. Galí, J. (2011) The Return of the Wage Phillips Curve, Journal of the European Economic Association, 9(3): 436-461. (2) Although compensation of employees diverges somewhat from wages actively negotiated between social partners, it is the most encompassing measure of labour costs as it includes employees' remuneration as well as social contributions paid by the employer. (3) Core inflation (measured in annual percentage changes of the HICP index excluding energy and unprocessed food as per the EC definition) is used as it leads to better results regarding model fit and regressor significance compared to headline inflation.  (4) For more details and results, see European Commission (2018c) Wage dynamics in Europe, background note prepared by the Commission for the EPC/EMCO Joint Seminar on Wage Developments and Dynamics of January 31 2018. Table 1:p-values in italicsReg. 1Reg. 2Reg. 3Constant0,510,490,00%0,00%Output gap (level, %)0,070,080,040,02%0,01%0,35%Labour productivity (qoq %-change)0,130,218,51%0,06%Core inflation (yoy %-change, 2 quarter lag)0,109,38%Inflation expectations 1 year ahead (SPF1, %)0,200,14%Sample period95Q2 - 17Q195Q2 - 17Q199Q1 - 17Q1R²0,150,180,34Adjusted R²14,22%16,21%31,42% 
                                                      
 
 
 
 
 
I.3.4.  Structural labour market characteristics  

pressure 

on  wage 

While  structural 
labour  market  reforms  can 
contribute  to  sustainable  job  creation  and  growth, 
in  the  short  term,  they  may  (temporarily)  exert 
growth. (21)  
downward 
Commission  analysis  suggests 
that  structural 
unemployment  in  the  euro  area  has  declined  over 
the  period  2013-2017  by  almost  1  ppt,  helped  by 
structural  labour  market  reforms  that  have  been 
undertaken. (22)  This  decline  has  been  associated 
with a small temporary fall in wage growth. These 
results  are 
line  with  findings  from  other 
studies. (23) 

in 

in 

in 

the 

Though  the  effects  are  difficult  to  quantify,  some 
studies  have  posited  that  other  ongoing  structural 
changes 
labour  market  are  exerting 
downward  pressure  on  wages.  Key  drivers  that 
literature  are 
the 
to 
have  been  referred 
globalisation, 
technological  progress,  declining 
unionisation,  and  the  emergence  of  new  forms  of 
employment.  Increased  trade  and  globalisation 
have reinforced workers' exposure to international 
competition,  and  this  may  have  a  negative  impact 
on  real  wages. (24)  Some  types  of  workers  are 
particularly vulnerable as a result of ongoing trends 
such as the de-routinisation of jobs and skill-biased 
technological progress. IMF finds that institutional 
factors  such  as  declining  union  density  and 
coverage  of  collective  bargaining  agreements  and 
the  decentralisation  of  such  agreements  can 
weaken  workers'  bargaining  power. (25)  Their 
analysis  suggests 
that  automation  may  have 
weighed  on  nominal  wage  growth,  although  the 
impact  has  been  limited.  BIS  provides  suggestive 
evidence of the fact that the fall in pricing power of 

(21)  Labour economics theory predicts that, under the assumption of 
imperfect  competition,  where  firms  set  their  prices  as  a  fixed 
mark-up  over  their  marginal  cost  and  face  a  downward  sloping 
demand curve in the short run, and workers' labour supply slopes 
upward, the increase of labour supply at a given wage will have a 
negative impact on real wages in the short run. In the longer run, 
however, firms will raise investment in order to take advantage of 
the  cheaper  work force  (and/or  because  the central  bank  lowers 
the  interest  rate  to  bring  inflation  back  to  its  target),  and  labour 
demand  will  increase  proportionally,  bringing  real  wages  back  to 
their  original 
(2005) 
Macroeconomics: imperfections, institutions, and policies. Oxford 
University Press).   

(e.g.  Carlin,  W.,  Soskice,  D. 

level 

(22)  see European Commission (2018c), as above. 
(23)  such  as  Duval,  R.,  Furceri,  D.  (2016)  The  Effects  of  Labor  and 
Product  Market  Reforms:  The  Role  of  Macroeconomic 
Conditions and Policies. Mimeo, International Monetary Fund. 
(24)  see e.g. for the US: Autor, D., Dorn, D., Hanson, G. (2013) The 
China  Syndrome:  Local  Labor  Market  Effects  of  Import 
Competition  in  the  United  States.  American  Economic  Review, 
103(6): 2121-2168. 
(25)  IMF (2017) as above 

16 | Quarterly Report on the Euro Area 

workers  (stemming  from  reduced  employment 
protection, union density and union coverage) is a 
possible  explanation  for  the  flattening  of  the 
Phillips curve.  (26)(27) Another factor that has been 
blamed  for  exerting  drag  on  wage  growth  is  the 
increase  in  non-standard  forms  of  work.  Some 
researchers have pointed at the low quality of jobs 
in  several  advanced 
created  since 
rates  of 
relatively  high 
economies,  with 
part-time 
(involuntary) 
and 
positions. (28)  These  non-standard 
forms  of 
lower 
employment  may  be  associated  with 
bargaining  power  for  workers.  (29)    Some  have 
argued  that  these  structural  trends  trigger  a 
decoupling  between  real  wages  and  productivity 
growth, reflected in a declining labour share. (30)  

the  crisis 

temporary 

I.3.5.  Trends in hours worked 

A structural downward trend in hours worked per 
employee  is  likely  to  contribute  to  subdued  wage 
growth  as  well  as  far  as  annual  earnings  are 
considered.  Between  2000  and  2017,  the  annual 
hours worked per employee declined by more than 
5%  (Graph  I.6).  This  does  not  just  reflect  cyclical 
conditions;  there  is  also  a  long-term  structural 
trend in lower hours worked. (31) Increased labour 
market participation of women and older workers, 

(26)  BIS  (2017),  87th  Annual  Report,  Box  IV.A:  Exploring  the  wage 

Phillips curve. Bank for International Settlements, Basel. 

(27)  The  analyses  by  IMF  and  by  BIS  include  countries  outside  the 
EU, which means that the results are not necessarily driven by EU 
countries.  Moreover,  the  BIS  report  does  not  report  detailed 
regression  results,  such  that  the  magnitude  of  the  identified 
impact is difficult to assess. 

(28)  Between  the  beginning  of  2012  and  Q2  2017,  4.4  million  jobs 
have  been  created  in  net  terms  of  which  29%  were  temporary 
contracts and 64% were part-time jobs. At the same time, a high 
share of non-standard labour contracts among newly created jobs 
is  not  unusual  by  historical  standards,  particularly  in  the  early 
stages of a recovery. 

(29)  see  e.g.  European  Commission  (2017)  as  above  and  Haldane, 
A.G. (2017) Work, wages and monetary policy. Speech by A. G. 
Haldane, Chief Economist, Bank of England at National Science 
and Medium Museum, Bradford, 20 June 2017. At the same time, 
some  of  the  structural  changes  reported  in  this  paragraph  were 
already observed in the pre-crisis period, so it is not clear that they 
would be able to explain the apparent decoupling between wages 
and the business cycle in the ongoing recovery. 

(30)  see  e.g.  for  evidence  from  the  US:  Elsby,  M.W.  L.,  Hobijn,  B., 
Sahin, A. (2013) The Decline of the U.S. Labor Share, Brookings 
Papers  on  Economic  Activity  47(2),  1-63;  Acemoglu,  D., 
Restrepo,  P.  (2016).  The  Race  between  Machine  and  Man: 
Implications  of  Technology  for  Growth,  Factor  Shares,  and 
Employment,  NBER  Working  Paper  No.  22252;  Kehrig,  M., 
Vincent,  N.  (2017)  Growing  Productivity  without  Growing 
Wages: The Micro-Level Anatomy of the Aggregate Labor Share, 
Economic Research Initiatives at Duke Working Paper No. 244..     
(31)  Alesina et al. (2006) show that annual hours per employed person 
were  already  on  a  decline  in  the  1960s  (see  Alesina,  A.,  Glaeser, 
E., Sacerdote, B., 2005. Work and leisure in the US and Europe: 
Why so different? NBER Macroeconomics Annual, pp. 1–64) 

  
 
                                                      
                                                      
to 

who  work  less  hours  than  prime  age  men  on 
average,  may  contribute 
this  observation. 
However,  the  reduction  in  hours  worked  is  also 
visible  for  prime  age  male  workers,  possibly 
reflecting, at least partially, better work-life balance 
of 
opportunities. (32)  The 
employment 
from 
manufacturing  to  the  service  sector,  where  part-
time  employment  is  more  common  (and  often 
involuntary), is likely to play a role as well. (33)     

in  many 

economies 

structural 

shift 

Graph I.6: Trends in hours worked in the 
euro area, 2000-17 (index: 2000=100) 

I. Wage dynamics in the EMU 

the  crisis.  When 

wage  rigidities  or  "pent-up"  wage  inflation:  in  the 
absence  of  downward  wage  flexibility,  employers 
are  unable  to  reduce  wages  in  line  with  soaring 
the 
unemployment  during 
economy  recovers,  wage  increases  are  held  back 
until  the  "pent-up"  wage  cuts  are  worked  off  by 
inflation  and  productivity  growth. (34)  Most  of  the 
evidence in favour of this argument has been based 
on  US  data.  However,  it  is  likely  to  be  equally  (if 
not  more)  relevant  for  the  European  context, 
where the existence of nominal wage rigidities has 
been documented extensively. (35) 

always 

indicating 

significant) 

coefficient  on 

Commission  analysis  indeed  finds  a  positive  (but 
not 
the 
interaction  between  low  inflation  and  economic 
slack, (36) 
inflation 
that 
environment,  nominal  wage  rigidities  cause  wage 
growth  to  be  higher  during  economic  downturns 
than in a higher inflation environment. This brings 
about  some  inertia  in  wage  growth  when  the 
economy  picks  up  again,  as  firms  make  up  for 
corrections not done during the crisis. 

in  a 

low 

Source:  European  Commission,  based  on  Eurostat 
[nama_10_a10_e] 

I.3.6.  Downward nominal wage rigidities 

Wage  moderation  during  the  latest  recovery  may 
also  partially  be  explained  by  downward  nominal 
wage  rigidities.  Wage  rigidities  have  long  been 
considered  a  factor  that  may  interfere  with  a 
smooth  functioning  of  the  labour  market.  Such 
rigidities  can  have  different  origins, 
including 
government  regulations  such  as  minimum  wages, 
the  use  of  fixed-term  nominal  wage  contracts 
between  employers  and  employees,  and  other 
behavioural  factors  that 
lead  both  employers 
and/or employees to focus on nominal rather than 
real wages.  

Some  have  observed  that  wage  growth  was 
stronger  than  expected  during  the  crisis,  and 
weaker than expected at the onset of the recovery. 
This  has  been  argued  to  be  the  result  of  nominal 

(32)  Bodnár, K. (2018) Labour supply and employment growth. ECB 

Economic Bulleting, Issue 1/2018 – Article. pp. 35-59. 

(33)  European Commission (2017: Box I.1.1) shows that the structural 
reduction  in  hours  worked  per  employee  tends  to  accelerate 
during recessions. 

I.4.  Wage dynamics and rebalancing in the 

euro area 

Labour cost developments have an impact on cost 
competitiveness and may therefore have important 
implications for developments of the trade balance 
and  the  current  account. (37)  If  not  offset  by 
productivity  developments  or  matched  in  partner 
countries,  wage 
price 
shocks 
competitiveness.  All  else  equal,  unit  labour  cost 
(ULC)-based REERs (38) increase (fall) in the event 
of  shocks  leading  to  higher  (lower)  unit  labour 
costs,  and  theory  predicts  that  this  will  lead  to  a 
deterioration  (improvement)  of  the  trade  balance 
and  the  current  account  balance.  Most  empirical 
estimates  indeed  point  to  a  negative  impact  of 
REER  increases  on  the  current  account  balance 

influence 

(34)  see Daly and Hobijn (2015), as above; Yellen (2014), as above.  
(35)  see e.g. Marotzke, P., Anderton, R., Bairrao, A., Berson, C., Tóth, 
P.  (2017)  Asymmetric  wage  adjustment  and  employment  in 
European firms. ECB Working Paper No. 2103. Wage Dynamics 
Network, European Central Bank 

(36)  European Commission (2018c), as above 
(37)  See footnote 10 
(38)  The  real  effective  exchange  rate  (REER)  is  a  measure  of  a 
country's  price  or  cost  competitiveness  relative  to  its  principal 
competitors in international markets. It is calculated as a weighted 
average of bilateral exchange rates against currencies of competing 
countries, deflated using a cost deflator (such as unit labour costs) 
or  a  price  deflator  (e.g.  the  consumer  price  index).  As  a  result, 
changes  in the  REER  reflect  not  only  exchange  rate  movements 
but also cost/price trends. A rise in the indicator means a loss of 
competitiveness. 

Volume 17 No 3 | 17 

859095100105110115200020012002200320042005200620072008200920102011201220132014201520162017Employment (based on persons)Employment (based on hours worked)Annual hours worked per employee 
 
                                                      
                                                      
over  the  medium  term. (39)  The  overall  impact  of 
changes  in  labour  costs  on  the  current  account 
depends  on  other  transmission  channels  beyond 
price  competitiveness  and  on  general  equilibrium 
interactions.  Exogenous  changes  in  wage  rates  or 
labour  taxes  can  for  example  affect  the  current 
account  balance 
impact  on 
through 
disposable income, domestic and import demand.  

their 

rather 

developments  in  the  former  deficit  countries  – 
increases  due  to 
partly  reflecting  productivity 
labour  shedding 
than  nominal  wage 
adjustment. (40)  Several  among  the  latter  (such  as 
Italy, Spain, and Ireland) have succeeded in turning 
their current account deficit into a surplus by 2014. 
This  observation  is  consistent  with  a  causal  link 
between  competitiveness  and  the  current  account 
balance. 

Since the establishment of the monetary union, and 
in particular in the run-up to the crisis, imbalances 
have developed within the euro area. In the initial 
stages  of  the  monetary  union,  the  decline  in  risk 
premia on interest rates led to a surge in net capital 
inflows in some countries of the euro area (such as 
Spain,  Portugal,  Greece,  Ireland).  This  was 
inflation 
followed  by  overheating  and  strong 
dynamics,  resulting 
losses, 
growing current account deficits and large negative 
net international investment positions. At the same 
time, other countries (such as Germany) increased 
and 
their  current  account 
surpluses, even during the crisis (Graph I.7).  

in  competitiveness 

largely  sustained 

the 

that 

(below) 

pressure 

In  theory,  internal  imbalances  can  be  re-absorbed 
through 
to  cyclical 
reaction  of  wages 
conditions.  If  a  shock  drives  output  in  a  given 
in  other 
country  much  above 
members  of  a  monetary  union,  stronger  (weaker) 
wage 
deterioration 
(improvement)  of  price  competitiveness  and  then 
to  weaker  (stronger)  growth  via  an  adjustment  of 
net exports. In a currency union, however, there is 
no automatic adjustment mechanism in response to 
external  imbalances.  The  adjustment  to  cyclical 
divergences may either work in favour of or against 
the correction of external imbalances. 

leads 

to 

a 

in 

In  the  pre-crisis  period,  the  response  of  wages  to 
labour  market 
the  domestic 
tightness 
exacerbated 
external 
imbalances through higher inflation and falling net 
exports.  Since  the  start  of  the  crisis,  imbalances 
have come down, helped by supportive labour cost 

accumulation 

the 

of 

(39)  This  suggests 

that 

typically, 

the  so-called  Marshall-Lerner 
condition  is  satisfied,  i.e.  import  and  export  elasticities  are  large 
enough  to  compensate  for  the  reduced  relative  local-currency 
price of imports associated with real exchange rate appreciations. 
Nevertheless,  estimates  of  current  account  elasticities  are 
notoriously uncertain due to well-known difficulties in estimating 
trade  elasticities  (see  e.g.  Imbs,  J.,  Mejean,  I.  (2017)  Trade 
elasticities. Review of International Economics, 25: 383-402). The 
semi-elasticity of the current account balance (measured as % of 
GDP) to the  percentage change  in the  REER  is  estimated  to  lie 
between  0.1  and  0.7  (see  IMF  (2018),  External  Sector  Report: 
Tackling Global Imbalances amid Rising Trade Tensions, Table 2) 

18 | Quarterly Report on the Euro Area 

Graph I.7: NULC in euro area deficit and 
surplus countries, 2000-2019, annual % 
change 

(1) Aggregate NULC growth rates reflect population-weighted 
averages. Figures for 2018-20 are based on ECFIN’s Autumn 
2018 
the 
forecast.  Belgium,  Germany,  Luxembourg, 
Netherlands,  Austria  and  Finland  are  referred  to  as  'surplus' 
countries.  'Deficit'  countries  are  all  other  euro  area  Member 
States.  This  classification  is  based  on  the  current  account 
situation  around  2008.  All  surplus  countries  recorded  a 
current  account  position  balanced  or  in  surplus  over  the 
2000-2012  period  (the  only  exceptions  being  DE  and  AT 
before  2002  and  FI  after  2010),  while  all  deficit  countries 
recorded  a  deficit  between  2000  and  2012.  This  grouping  of 
countries  is  in  line  with  the  methodology  of  the  2018  Alert 
Mechanism Report. 
Source: Source: European Commission based on AMECO 

substantial 

consequences  of 

The adjustment process has however been painful. 
The  current  account  improvement  partly  reflected 
the 
a  domestic  demand 
contraction.    The  onset  of  the  crisis  triggered  an 
increase  in  credit  risk  for  countries  that  had  been 
inflows, 
receiving 
resulting in a significant disruption in these inflows. 
This  contributed  to  a  closing  current  account 
deficit  and  at  the  same  time  to  a  contraction  of 
domestic  demand,  which  was  associated  with  a 
reduction  in  labour  cost  growth  and  a  strong 
increase  in  unemployment.  At  the  same  time,  the 
net  international  investment  positions  in  these 

foreign  capital 

(40)  ECB  (2014)  Economic  and  Monetary  Developments:  Output, 
Demand and the Labour Market. Monthly Bulletin, January 2014. 

-2-1012345672000200120022003200420052006200720082009201020112012201320142015201620172018*2019*2020*'Surplus'countries'Deficit' countries  
 
                                                      
 
                                                      
countries  remain  negative  and 
large  and  are 
generally associated with large stocks of private or 
government  debt  and  constitute  a  vulnerability, 
pointing at a need for further rebalancing efforts. 

The  unit  labour  cost  growth  differentials  between 
surplus  and  formerly  deficit  countries,  observed 
since the crisis, are gradually winding down. This is 
the  result  of  the  recovery  of  wage  growth  from 
very low rates in formerly deficit countries coupled 
with  weak  productivity  gains,  while  wage  growth 
has remained moderate in surplus countries in spite 
of relatively tight labour market conditions.  

The  post-crisis  reduction  of  most  current  account 
deficits  has  not  been  matched  by  significant 
progress  in  terms  of  reducing  large  surpluses. 
Countries  with  large  surpluses  like  Germany  and 
the  Netherlands  have  actually  seen  their  surpluses 
grow  considerably  since  2001.  As  a  result  of  the 
simultaneous  reduction  of  large  deficits  and  the 
lack of correction in large surpluses, the euro area 
as  a  whole  has  gradually  moved  to  a  current 
account  surplus  exceeding  3%  of  GDP.  This 
contributes to the aggregate surplus position of the 
Eurozone and (in combination with other factors) 
to  low  price  inflation,  making  the  intra-euro  area 
low 
rebalancing  process  more  difficult.  In  a 
inflation/high  debt  environment, 
it  has  put 
pressure on deficit countries to pursue deflationary 
policies  to  regain  competitiveness  and  aggravated 
the employment and social costs of the adjustment.  

From  this  perspective,  stronger  wage  growth  in 
these  creditor  countries  would  arguably  support 
domestic  demand  and  aggregate  demand  in  the 
euro area, and contribute to the economic recovery 
and 
the 
rebalancing,  while 
competitiveness adjustment of deficit countries. 

easing 

the 

I.5.  Policy instruments that influence wage 

developments  

Although wage developments are mainly the result 
of  the  interaction  between  market  forces  and  the 
institutions  underpinning  collective  bargaining, 
governments  can  influence  these  dynamics  in  in  a 
number  of  ways,  including  through  the  setting  of 
minimum  wages  and  government  wages,  the  tax 
and  benefit  system,  the  steering  of  collective 
bargaining 
in  the  private  sector  via  tripartite 
agreements  and  social  pacts,  or,  where  collective 
bargaining  is  regulated  by  law,  the  review  of  the 
legislated  frameworks  regulating  wage  setting  in 
social  partners.  Structural 
consultation  with 

I. Wage dynamics in the EMU 

reforms  can  also  influence  wage  and  labour  cost 
developments, albeit in a more indirect way. Since 
these  different  instruments  interact  in  different 
their 
ways  with 
effectiveness  in  steering  wage  developments  and 
their  impact  on  the  rest  of  the  economy  varies  as 
well. (41)   

the  economy, 

the  rest  of 

I.5.1.  Minimum wages 

is 

their  potential 

A  statutory  minimum  wage  is  a  policy  instrument 
that directly affects wages, particularly for workers 
in a weak bargaining position. (42) They set a floor 
to  earned  labour  income,  and  compress  the  wage 
distribution  from  below.  In  some  countries, 
statutory wage floors are combined with additional 
sectoral  wage  floors  negotiated  between  social 
partners.  Minimum  wage  policies  have  attracted  a 
vigorous  debate  in  the  literature.  A  major  issue  of 
impact  on 
contention 
employment.  Some  argue,  based  on  a  competitive 
labour market  assumption where  workers  are  paid 
according  to  their  productivity,  that  imposing  a 
wage  floor  will  price  low-skilled/low-productive 
workers out of the market. Others argue, based on 
a  monopsonistic  labour  market  assumption,  that 
imposing  a  wage  floor  can  actually  expand 
employment,  as  firms  will  increase  their  output  in 
response to a reduction of their profit margins per 
unit  produced. (43)  The  empirical  literature  has 
found  evidence  in  favour  of  both  hypotheses, 
underlining  the  importance  of  the  context  (e.g.  in 
terms of the level of the minimum wage compared 
to  the  rest  of  the  wage  distribution,  and  the 
proportion of the workforce that is covered by it), 
but  seems  to  broadly  converge  on  the  conclusion 
that the aggregate employment effects of observed 
minimum  wages  increases  have  been  minor,  if 
significant at all (e.g. Neumark, 2017; Allegretto et 
al.,  2011). (44)  Slightly  more  negative  but  still 
modest  effects  have  been  found  for  employment 

(41)  For  instance,  policies  that  help  raising  labour  demand  and 
employment  are  more  likely  to  stimulate  output  in  the  own 
economy and in the rest of the euro area, see e.g. IMF (2015). 
(42)  OECD (2015) Focus on minimum wages after the crisis: Making 
them  pay.  Directorate  for  Employment,  Labour  and  Social 
Affairs, Paris: OECD Publishing. 

(43)  For a review of the theoretical arguments and empirical evidence, 
see  European  Commission  (2016),  Labour  Market  and  Wage 
Developments  in  Europe.  Annual  Review  2016,  Directorate-
General for Employment, Social Affairs and Inclusion. 

(44)  Neumark, D. (2017) The employment effects of minimum wages: 
some  questions  we  need  to  answer.  NBER  Working  Paper  No. 
23584;  Allegretto,  S.  A.,  Dube,  A.  and  Reich,  M.  (2011),  Do 
Minimum  Wages  Really  Reduce  Teen  Employment?  Accounting 
for  Heterogeneity  and  Selectivity  in  State  Panel  Data.  Industrial 
Relations: A Journal of Economy and Society, 50: 205–240. 

Volume 17 No 3 | 19 

 
                                                      
of  specific  groups  such  as  low-skilled,  young, 
and/or female workers. (45) 

Other have found no spillover effects; or that they 
only matter in the short run. (51)  

frameworks 

vary 
setting 
Minimum  wage 
considerably  across  countries,  with  possible 
implications 
for  wage  developments.  Some 
countries  in  the  EU  do  not  have  a  statutory 
minimum  wage  at  all. (46)  Where  minimum  wages 
exist,  governments  are  typically  formally  involved 
in  establishing  the  procedure  of  minimum  wage 
setting,  but  their  scope  for  influencing  the  level 
varies.  In  some  countries,  such  as  Estonia,  the 
statutory  minimum  wage  is  mostly  negotiated 
between  social  partners,  with  very  little  discretion 
from the government's side. At the other extreme, 
the 
is 
the  minimum  wage 
in  Bulgaria.  In  other 
government's  discretion 
countries,  minimum  wages  are  established 
in 
tripartite  negotiations  involving  the  government 
the 
partners; 
and 
recommendation  of  experts  and/or  based  on 
analysis  that  takes  into  account  economic  and 
social criteria, labour market conditions, and other 
relevant dimensions. (47)   

set  at 

largely 

social 

upon 

the 

or 

Usually only a small proportion of the labour force 
is  covered  by  the  (increased)  minimum  wage  and 
therefore  directly  affected.  The  minimum  wage 
may  however  also  have  some  more 
indirect 
spillover effects on wage growth further up in the 
wage  distribution,  for  example  because  other 
workers might demand wage increases to preserve 
existing  wage  differentials (48)  and/or  because 
social  partners  use  the  minimum  wage  as  a 
reference for sectoral wage negotiations. Positional 
income concerns and fair wage considerations may 
also play a role. (49) The empirical literature (mostly 
based  on  US  data)  has  found  evidence  of  small 
effects  on  wages  beyond  the  quintiles  that  are 
directly  affected  by  minimum  wage  increases. (50) 

(45)  Neumark,  D.,  Wascher,  W.L.  (2007)  Minimum  wages  and 
employment, Foundations and Trends in Microeconomics: 3(1-2): 
1-182. 

(46)  Eurofound  (2017)  Statutory  minimum  wages  in  the  EU  2017. 

Dublin: Eurofound. 

(47)  European  Commission  (2016)  provides  an  overview  of  different 
observed  minimum  wage  setting  institutions  and  the  ensuing 
implications for wage developments. 

(48)  Bossler, M. and Gerner; H.-D. (2016) Employment effects of the 
new German minimum wage. IAB Discussion Paper 10/2016. 
(49)  Falk,  A.,  Fehr,  E.,  Zehnder,  C.  (2006).  Fairness  perceptions  and 
reservation wages—the behavioral effects of minimum wage laws. 
Quarterly Journal of Economics, 121(4), 1347-1381. 

(50)  Card, D., Krueger, A.B. (1995), Myth and Measurement: The New 
Economics  of  the  Minimum  Wage,  Princeton  University  Press; 
Autor, D. H., Manning, A., Smith, C.L. (2016). The Contribution 
of  the  Minimum  Wage  to  US  Wage  Inequality  over  Three 

20 | Quarterly Report on the Euro Area 

Minimum wage floors can also have indirect effects 
on  the  economy.  For  example,  minimum  wages 
can induce investment in (physical and/or human) 
capital  to  offset  the  increased  cost  of  labour. 
Minimum  wages  can  also  cushion  fluctuations  in 
the aggregate demand during economic downturns, 
by helping to avert risks of wage deflation.  

I.5.2.  Institutional settings of collective 

bargaining frameworks 

of 

rules 

aspects 

through 

collective 

Different 
bargaining 
institutions may have a bearing on wage outcomes. 
Key dimensions are (a) the level at which collective 
agreements are concluded (at the national, regional, 
sectoral,  or  firm-level);  (b)  union  density;  and  (c) 
is  covered  by  collective 
provisions  on  who 
agreements 
on 
(e.g. 
representativeness  as  a  condition  for  extension  or 
on  the  conditions  for  exemptions); (52)  (d)  the 
framework for coordinating wage bargaining across 
the economy; (e) the frequency at which wages are 
re-negotiated,  including  provisions  on  retro-  and 
ultra-activity, (53)  and  possible  indexation  clauses. 
The  level  at  which  collective  agreements  are 
concluded and the size of the workforce for which 
they  apply  (through  extension  provisions)  matter 
for the extent to which wages can respond to firm-
in 
level, 

regional  differences 

sectoral 

and 

Decades:  A  Reassessment.  American Economic  Journal:  Applied 
Economics,  8(1):  58-99;  Arpaia,  A.,  and  Van  Herck,  K.,  (2017) 
Wage  distribution  spillovers  from  minimum  wages  increases  in 
France, DG Employment and Social Affairs. Analytical Webnote 
1/2017;  Vodopivec,  M.  (2015)  The  employment  and  wage 
spillover  effects  of  Slovenia's  2010  minimum  wage  increase. 
European Scientific Journal, Special Edition, July 2015: 82-109. 
(51)  Dickens, R., Manning, A. (2004) Has the national minimum wage 
reduced  UK  wage  inequality?  Journal  of  the  Royal  Statistical 
Society: Series A (Statistics in Society) 167(4): 613-626; Neumark, 
D.,  Wascher,  W.L.  (2008).  Minimum  Wages.  Cambridge,  MA: 
MIT Press. 

(52)  For  an  interesting  analysis  on  how  these  rules  affect  bargaining, 
see  e.g.  Hijzen,  A.,  Martins,  P.S.,  Parlevliet,  J.  (2017)  Collective 
bargaining  through  the  magnifying  glass:  a  comparison  between 
the Netherlands and Portugal. IMF Working Paper WP/17/275. 

(53)  Retro-activity  means  that  a  collective  agreement  can  be  applied 
retro-actively. This can have significant implications in the case of 
firm  liquidity  constraints.  While  in  some  countries,  retro-activity 
only applies to signatory firms, in other countries, it applies to all 
covered  firms.  Ultra-activity  implies  that  collective  agreements 
remain  valid  after  their  expiry  date,  in  the  absence  of  a  new 
collective agreement. It is meant to ensure continuity, but can also 
act  as  a  disincentive  to  renegotiate  (by  the  partner  expecting  a 
worse bargaining position in new negotiations) (see Hijzen et al., 
2017,  as  above;  and  OECD  (2017)  Collective  bargaining  in 
OECD  and  accession  countries:  the  duration,  ultra-activity  and 
retro-activity of collective agreements. Paris: OECD Publishing). 

  
 
                                                      
 
                                                                                 
productivity  and  labour  market  tightness.  Union 
density  can  influence  the  bargaining  power  of 
workers in wage negotiations and as a result have a 
positive  impact  on  wage  outcomes.  The  extent  to 
which unions internalise needs of "outsiders" (be it 
the  unemployed  or  those  on 
less  favourable 
contract  types)  also  matter.  This  is  typically  not 
the 
under  direct  government  control,  but 
government  may  exert  some  influence  in  the  case 
of tripartite agreements. (54)   

the  other  hand, 

The frequency at which wages are re-negotiated has 
a  relevant  interaction  with  inflation.  On  the  one 
hand,  higher 
inflation  makes  more  frequent 
renegotiations  necessary  to  maintain  purchasing 
frequent  wage 
power.  On 
adjustments tend to make inflation more persistent. 
Similarly, a relevant role in this respect is played by 
the  presence  of 
indexation 
mechanisms  enshrined  in  law  or  in  collective 
contracts,  and  the  legal  framework  and  practice 
followed for negotiating and renewing contracts. 

ex-post  wage 

Theoretical predictions on the impact of the degree 
of  centralisation  are  ambiguous. (55)  Some  have 
argued that decentralisation weakens the power of 
trade union and hence that it would result in lower 
wage demands. Others have argued that centralised 
wage  negotiations  are  more  likely  to  take  into 
account  possible  negative  externalities  (e.g.  on 
employment  or  on  real  wages  if  higher  wage 
to  consumer  prices), 
demands  pass 
resulting  in  more  moderate  wage  demands.  Both 
views  are  reconciled  in  Calmfors  and  Driffill’s 
(1988) integrated framework which argues that the 
highest  wage  levels  are  obtained  when  collective 
bargaining is done at an intermediate level (e.g. the 
sectoral  level). (56)  In  an  increasingly  globalised 
world,  however,  these  arguments  may  be  losing 
relevance,  as  prices  and  wages  are  increasingly 
under  pressure  from  developments  abroad  and 

through 

(54)  For example, Dolado and Bentolilla (1993) observe a positive link 
between the number of fixed-term contracts (the "outsiders") and 
the  real  wages  (and  hence  the  implied  market  power)  of 
permanent workers (the "insiders"). 

(55)  Borghijs,  A.,  Ederveen,  S.,  de  Mooij,  R.  (2003)  European  Wage 
Coordination:  Nightmare  or  dream  to  come  true?  European 
Network of Economic Policy Research Institutes Working Paper 
No. 20. 

(56)  Calmfors,  L.,  and  John  Driffill,  J.  (1988),  Bargaining  structure, 
corporatism and macroeconomic performance, Economic Policy, 
6, 13-61. 

I. Wage dynamics in the EMU 

therefore more likely to closely follow productivity 
developments. (57)  

strategies 
formal 

important 
beyond 

involving  bilateral  or 

for  wage 
are 
There 
coordination 
centralisation. 
Coordination  can  refer  to  horizontal  coordination 
(across  sectors),  and  this  can  be  achieved  in  an 
in  the  case  of  "peak-level 
explicit  way  (e.g. 
coordination" 
trilateral 
agreements  or  social  pacts)  or  in  an  implicit  way, 
for  instance  through  regular  interaction  between 
sectoral trade unions or through "wage leadership" 
or  "pattern  bargaining",  where  some  sectors  base 
their  negotiations  on  agreements  made  in  other 
sectors. (58)  Coordination  can  also  refer  to  vertical 
coordination, such as in the case where lower level 
agreements  can  only  improve  upon  conditions 
negotiated at higher levels. Some have argued that 
wage  coordination  reduces 
the  sensitivity  of 
inflation to domestic output, thus keeping inflation 
in check when unemployment is low, and reducing 
the 
high 
unemployment during economic downturns, (59) in 
line  with  the  impact  of  nominal  wage  rigidities  as 
discussed before.  

inflation-dampening 

impact 

of 

More  effective  coordination  between 
social 
partners  helps  achieving  macroeconomic  goals 
such  as  increasing  resilience,  stabilising  inflation, 
tackling  unemployment,  and  correcting  external 
imbalances. (60)  Governments  can  foster  such 
coordination  and  good  social  partner  relationships 
more  broadly  by  supporting  bi-  and  tripartite 
agreements,  providing  platforms 
regular 
discussions between social partners and promoting 
a shared understanding of the main challenges. (61) 
The  government  can  also  influence  bargaining 
through flanking measures such as tax concessions 
to support net wages at times of wage moderation. 

for 

(57)  Camarero,  M.,  D’Adamo,  G.,  Tamarit,  C.  (2016)  The  role  of 
institutions  in  explaining  wage  determination  in  the  Eurozone:  a 
panel  cointegration  approach.  International  Labour  Review, 
155(1): 25-56. 

(58)  see e.g. European Commission (2011), Labour Market and Wage 
Developments  in  Europe.  Annual  Review  2011,  Directorate-
General  for  Employment,  Social  Affairs  and  Inclusion;  Traxler, 
F.,  Blaschke,  S.,  Kittel,  B.  (2001)  National  labour  relations  in 
internationalised  markets:  a  comparative  study  of  institutions, 
change and performance, Oxford University Press. 

(59)  Rovelli, R. (2016) Wage coordination in new and old EU member 

states. IZA World of Labor 2016: 222. 

(60)  see  e.g.  Ball,  L.,  Romer, D. (1991)  Sticky  Prices  as  Coordination 
Failure.  American  Economic  Review,  81(3):  539-552;  Blanchard,  O., 
Wolfers, J. (2000), The Role of Shocks and Institutions in the Rise 
of  European  Unemployment:  the  Aggregate  Evidence  Economic 
Journal, 110: 1–33. 

(61)  see Hijzen et al. (2017), as above. 

Volume 17 No 3 | 21 

 
                                                      
                                                      
Certain  features  of  collective  bargaining  systems 
can  contribute  to  building  trust  between  social 
partners,  such  as  the  inclusiveness  of  bargaining 
parties,  effective  procedures  for  extensions  and 
incentives 
for 
exemptions,  built-in 
regular 
to  generate 
and  mechanisms 
renegotiation, 
ownership 
social 
accountability 
partners  (e.g.  by  ensuring  transparent  access  to 
information on negotiated working conditions and 
effective  enforcement  of  the  agreement  through 
independent labour inspectorates). (62)  

among 

and 

to  adjust 

firm-specific  and 

The question of which wage setting institutions are 
most  compatible  with  a  resilient  economy  has  no 
clear-cut answer. From a resilience perspective, the 
focus  is  not  necessarily  on  the  level  of  wages  but 
more  on  the  speed  of  adjustment.  Some  authors 
have  argued  that  a  combination  of  national  and 
firm-level  bargaining  seems  attractive  to  ensure 
macro-flexibility. (63)  Firm-level  bargaining  allows 
to 
wages 
local 
developments.  On 
the  other  hand,  national 
agreements  (in  which  governments  are  often 
involved  alongside  social  partners)  can  support 
adjustment  in  response  to  major  macroeconomic 
shocks:  by  providing  guidance  for  average  wage 
growth,  such  agreements  can  avert  wage  deflation 
while  taking  into  account  the  interaction  between 
wage  developments  and  (un)employment. (64)  At 
the same time, other efficient forms of wage setting 
institutions  can  also  be  found,  and  details  with 
are 
regard 
operationalised  matter  a  lot.  Moreover,  collective 
bargaining 
in 
institutions  are  deeply 
countries'  history  and  underlying  social  norms; 
hence,  in  order  to  succeed,  trust  between  social 
partners  might  be  more 
important  than  any 
particular bargaining structure.  

to  how  bargaining 

regulations 

rooted 

Well-functioning collective bargaining systems also 
play an important role in mitigating inequality, and 
ensuring that the benefits from productivity growth 
are shared fairly. (65) It is important to ensure that 

(62)  IMF  (2016)  Time  for  a  supply-side  boost?  Macro-economic 
effects  of  labour  and  product  market  reforms  in  advanced 
economies, Chapter 3, World Economic Outlook, April 2016. 
(63)  Blanchard,  O.,  Jaumotte,  F.,  Loungani,  P.  (2013)  Labor  Market 
Policies  and  IMF  Advice  in  Advanced  Economies  during  the 
Great Recession, IMF Staff Discussion Note. SDN/13/02. 
(64)  Examples include the Wassenaar Agreement in the Netherlands in 
1982;  the  Moncloa  Pact  in  Spain  in  1977,  the  Alliance  for  Jobs 
(Bündnis  für  Arbeit)  in  Germany  in  1998;  and  the  more  recent 
2016 Competitiveness Pact in Finland. 

(65)  The  Right  to  Fair  Wages  is  one  of  the  20  key  principles  of  the 
European Pillar of Social Rights, which was launched on April 26 
2017. 

22 | Quarterly Report on the Euro Area 

wages are set in a transparent and predictable way 
according  to  national  practices  and  respecting  the 
autonomy  of  social  partners.  In  this  context,  a 
stable  industrial  relations  environment  plays  an 
important role in delivering the trust that is needed 
to adopt, both in good and in bad times, innovative 
bargaining solutions with the support of the social 
partners. 

I.5.3.  Public sector wages 

Public  employment (66)  represents  a  considerable 
share  of  total  employment and  hence  public  wage 
dynamics  can  have  relevant  impacts  on  aggregate 
wage  developments.  Public  wage  dynamics  may 
spill  over  to  the  private  sector  through  different 
channels,  and  especially  so  in  the  presence  of  a 
large  public  sector.  An  increase  in  public  sector 
wages  makes  government  jobs  more  attractive—
especially if there is already a positive public sector 
premium  and  other  job  characteristics  (such  as 
employment  protection  regulations)  are  more 
favourable  too—crowding  out  employment  in  the 
private  sector  and  exerting  upward  pressure  on 
wages and productivity in the private sector. (67) By 
increasing  the  value  of  being  employed  in  the 
public 
the 
bargaining position of workers in the private sector 
and  trigger  imitation  effects  between  public  and 
private  wages. (68)  Public  wage  increases  can  also 
have  a  positive  impact  on  demand,  and  as  such 
foster  private  sector  employment.  On  the  other 
hand,  if  private  wage  increases  are  not  supported 
by increases in labour productivity, they may exert 
upward pressure on unit labour costs. (69) 

sector,  higher  wages 

strengthen 

(66)  The  government  wage  bill  represents around  10%  of total GDP 
in Europe: 11% on average over the period 1999-2012  in the EU; 
slightly  above  10%  in  the  euro  area  in  2014  (see  European 
Commission  (2014)  Government  wages  and  labour  market 
outcomes. European Economy Occasional Papers 190; and Pérez, 
J.J.,  Aouriri,  M.,  Campos,  M.M.,  Celov,  D.,  Depalo,  D., 
Papapetrou,  E.,  Pesliakaité,  J.,  Ramos,  R.,  Rodríguez-Vives,  M. 
(2016)  The  fiscal  and  macroeconomic  effects  of  government 
wages and employment reform. ECB Occasional Paper Series No. 
176).  

(67)  Helpman,  E.  (1976)  Macroeconomic  policy  in  a  model  of 
international 
restriction.  International 
Economic Review, 17: 641-654; Algan, Y., Cahuc, P., Zylberberg, 
A.  (2002).  Public  employment  and  labour  market  performance, 
Economic Policy, 17 (34), 7-66. 

trade  with  a  wage 

(68)  Afonso,  A.,  Gomes,  P.  (2008)  Interactions  between  private  and 
public  sector  wages.  European  Central  Bank  Working  Paper 
Series  No.  971;  Ardagna,  S.  (2007).  Fiscal  policy  in  unionised 
labor  markets,  Journal  of  Economic  Dynamics  and  Control,  21 
(5), 1498-1534. 

(69)  Lane, P.R., Perotti, R. (1998) The trade balance and fiscal policy in 
the  OECD.  European  Economic  Review,  42(3-5):  887-895; 
Rovelli (2016), as above. 

  
 
                                                      
                                                      
in 

institutions 

In  practice,  wage  setting 
the 
government  sector  vary  considerably  across  the 
EU. (70) A key distinction is that in some countries, 
government  wages  are  mostly  set  by  legislative 
action;  while  in  others  they  are  set  by  collective 
bargaining.  As  a  consequence,  governments  have 
direct  control  on  wage  setting  in  the  former  case, 
while wage setting in the public sector results from 
interactions  with  wage  formation  in  the  private 
sector  in  the  latter  case.  More  generally,  dynamic 
interactions  between  private  and  public  wages  can 
be  quite  complex  depending  on  the  specific 
characteristics  of  wage  bargaining  in  both  sectors 
which influence their leadership behaviour in wage 
setting. (71)    For  example,  research  has  found  that 
public  sector  wages  exert  a  stronger  impact  on 
private  wages 
the  government’s 
involvement  in  collective  bargaining,  the  more 
centralised and coordinated is collective bargaining, 
the  larger  the  public  sector  and  the  lower  the 
external  openness  to  trade  is. (72)  In  countries 
where  government  wages  are  set  by  collective 
bargaining, wages in the manufacturing sector have 
been  found  to  be  better  aligned  with  productivity 
and  more  responsive  to  unemployment,  possibly 
because bargaining processes are generally closer to 
the  market 
government 
decisions. (73)  

the  greater 

unilateral 

than 

I. Wage dynamics in the EMU 

generate  a  wedge  between  labour  cost  and  take-
home pay and can therefore drive up labour costs 
and/or  drive  down  net  wages  and  disposable 
income.  The  wage  impact  of  a  change  in  the  tax 
wedge 
is  country-  and  context-specific. (75)  It 
depends  on  the  relative  responsiveness  of  labour 
demand and supply, and falls typically on the least 
elastic  side  of  the  market. (76)  In  the  presence  of 
downward  nominal  wage  rigidities,  labour  tax 
reductions are likely to be passed on to the worker, 
as gross wages cannot be reduced. The institutional 
the 
framework 
interaction  of  taxation  with  other  institutional 
factors  (e.g.  the  tax  treatment  of  unemployment 
benefits) also play a role.  

for  wage  negotiations  and 

Empirical evidence shows that the largest share of 
the tax burden on labour is borne by the employee 
in the form of lower wages. (77) This is observed to 
apply  even  more  strongly  to  countries  with  more 
centralised  bargaining  systems  and  in  countries 
where  social  security  benefits  are  more  tightly 
linked to contributions, presumably because labour 
income 
unions 
protection  in  their  wage  demands. (78)  In  other 
words,  workers  and  labour  unions  are  more  likely 
to  recognise  the  provided  insurance  as  non-wage 
benefits  in  this  case,  moderating  the  impact  on 
labour supply and wage demands.  

the  benefits  from 

internalise 

I.5.4.  Tax and benefits policies 

While  their  impact  is  less  direct  and  relatively 
complex,  labour  tax  policies  can  influence  wages 
through  different  channels.  Personal  income  tax 
liabilities and social security contributions (whether 
payable  by  employees  or  by  employers) (74) 

(70)  For  a  survey  of  collective  bargaining  institutions  in  the  public 
service and their effect on labour market outcomes see European 
Commission (2014). 

(71)  See e.g. D'Adamo (2014) for a review of wage spillovers between 
the public and the private sector in 10 European Union member 
states over the period 2000-2011. 

(72)  Lamo,  A.,  Pérez,  J.  J.,  Schuknecht,  L.  (2012),  Public  or  Private 
Sector  Wage  Leadership?  An 
International  Perspective. 
Scandinavian  Journal  of  Economics,  114:  228–244;  Lamo  A., 
Perez  J.J.,  Schuknecht  L.  (2013),  Are  government  wages 
interlinked with private sector wages? Journal of Policy Modeling, 
35(5), 697-712. 

(73)  Marzinotto, B., Turrini, A. (2017) Co-movements between public 
and  private  wages  in  the EU:  what  factors  and  with  what  policy 
implications? IZA Journal of European Labor Studies, 6(2). 
(74)  While the statutory incidence of a tax may be relevant for political 
and  short-term  economic  reasons,  it  should  not  have  an  impact 
on  wage  levels  over the  longer term. See  European Commission 
(2015) Study on the effects and incidence of labour taxation. Final 
Report.  Working  Paper  No.  56,  Taxation  Papers;  Kugler,  A., 
Kugler,  M.,  Herrera  Prada,  L.O.  (2017)  Do  payroll  tax  breaks 
stimulate  formality?  Evidence  from  Colombia's  reform.  NBER 
Working Paper 23308. 

Governments  sometimes  use  fiscal  devaluations 
(i.e. tax system adjustments as to increase the cost 
of imports relative to exports) as an instrument to 
regain  competitiveness.  In  a  currency  union, 
economies cannot rely on nominal depreciations or 
devaluations  to  improve  competitiveness.  A  fiscal 
devaluation  can  to  some  extent  mimic  a  nominal 

(75)  Melguizo,  Á.,  González-Páramo,  J.M.  (2013)  Who  bears  labour 
taxes  and  social  contributions?  A  meta-analysis  approach. 
SERIEs, 4(3): 247-271. 

(76)  Theory  predicts  that  if  labour  demand  is  completely  elastic,  an 
increase in the tax wedge will fall fully on the worker in the form 
of a lower net wage. If labour demand is fully inelastic, it will fall 
fully on the employer in the form of higher labour costs. For any 
intermediate elasticity of labour demand, the costs will be shared 
between  workers  and  employers;  and  the  more  elastic  labour 
supply is, the lower the share of the tax burden will be borne by 
the  worker  (European  Commission,  2015).  The  response  to  a 
change  in  the  tax  wedge  can  be  asymmetric,  e.g.  if  wages  are 
downwardly rigid but can increase flexibly (Kugler et al., 2017).  
(77)  See  European  Commission  (2015),  as  above;  Gruber,  J.  (1997) 
The Incidence Of Payroll Taxation: Evidence From Chile, Journal 
of Labor Economics, 15(3): S72-S101; Ooghe, E., Schokkaert, E., 
Flechet, J. (2003) The Incidence of Social Security Contributions: 
An Empirical Analysis. Empirica, 30(2): 81-106. 

(78)  see Melguizo and González-Páramo (2013), as above; Ooghe et al. 
(2003),  as  above;  Summers,  L.,  J.  Gruber,  and R.  Vergara (1993) 
Taxation  and  the  Structure  of  Labor  Markets:  The  Case  of 
Corporatism, Quarterly Journal of Economics 58, 385–411. 

Volume 17 No 3 | 23 

 
                                                      
                                                      
devaluation: imports can be made more costly and 
exports cheaper by financing a tax cut on domestic 
production  (e.g.  by  reducing  the  tax  burden  on 
labour)  through  the  increase  of  the  value-added 
standard tax (VAT) rate. (79) Earlier analyses by the 
European  Commission  and  by  the  ECB  conclude 
that fiscal devaluations can accelerate real exchange 
rate  adjustments  and  thus  contribute  positively  to 
regaining  competitiveness,  but  the  impact  is  likely 
to be small and short-lived. (80) As such, it cannot 
be  used  as  a  substitute  for  structural  reforms  that 
address fundamental  problems  underlying  external 
imbalances and weak growth. Still, as it presents a 
shift  towards  more  growth-friendly  taxation,  a 
fiscal  devaluation  can  have  wider  economic 
benefits. (81)   

Generous  unemployment  benefits  (both  in  terms 
of their levels or replacement rates and in terms of 
their  duration)  are  expected  to  raise  workers' 
reservation  wage,  and 
therefore  also  wage 
demands.  If  not  accompanied  by  cost-effective 
activation policies, they may have a negative impact 
on  labour  supply  as  well. (82)  These  factors  may 
strengthen  the  bargaining  power  of  unions  and 
workers  and  lead  to  higher  wages  as  a  result.  On 
the  other  hand,  if  workers  incorporate  in  their 
income 
the  benefits 
wage  demands 
protection provided by the social security system or 
from  public  goods  provided  with  the  help  of 
labour taxes, the negative effects on labour supply, 
and the upward pressure on wage demands may be 
mitigated to some extent. (83) 

from 

I.5.5.  Other structural reforms in product and 

labour markets 

Changes  in  product  market  and  labour  market 
regulations  may  also  have  an  indirect  impact  on 
wage formation. A well-known example in the area 
of  labour  market  regulations  are  regulations  on 

(79)  Hohberger,  S.,  Kraus,  L.  (2016)  Is  fiscal  devaluation  welfare 

enhancing? Economic Modelling, 58: 512-522. 

(80)  See European Commission (2013) Study on the impacts of fiscal 
devaluation.  Working  paper  36,  Taxation  Papers;  ECB  (2011) 
Economic  and  Monetary  Developments:  Fiscal  Developments. 
Monthly Bulletin, December 2011, box I2. 

(81)  In  cases  where  fiscal  devaluations  would  have  negative  impacts 
for equity, this can be addressed by focusing income tax cuts on 
lower income groups (European Commission, 2013, as above). 
(82)  With  less  generous  unemployment  benefits,  an  increase  in 

unemployment benefit generosity is less binding. 

(83)  Rosen,  S.  (1986)  ‘The  Theory  of  Equalising  Differences’,  in  O. 
Ashenfelter and R. Layard, eds., Handbook of Labor Economics 
I.  Amsterdam:  Elsevier;  Summers,  L.  (1989)  Some  Simple 
Economics  of  Mandated  Benefits,  American  Economic  Review 
79(2), 177–183. 

24 | Quarterly Report on the Euro Area 

to 

lead 

trigger 

should 

deregulation 

dismissal costs. Research has established that firms 
can  compensate  for  the  future  expected  costs  of 
dismissal by reducing the entry wage of the worker, 
so that the expected cumulative wage bill from the 
employment relationship remains unaffected. (84) If 
this  is  the  case,  theory  predicts  that  employment 
protection 
a 
proportional  increase  in  wages. (85)  On  the  other 
hand,  a  reduction  in  firing  costs  from  high  levels 
may 
of 
unemployment,  which  might  have  short-run 
negative  impacts  on  aggregate  demand  in  periods 
of  economic  slack. (86)  These  effects  may  be 
mitigated by devising reform packages that support 
workers  during  transitions  between  different  jobs, 
including  with  effective  unemployment  benefits 
and  activation  policies  as  per  the  "securiflex" 
model.  Employment  protection  reforms  can  also 
be  devised  to  reduce  labour  market  segmentation, 
which  can  also  have  a  positive  impact  on  wage 
developments. (87) 

temporary 

increase 

a 

can 

deregulation 

Product  market 
foster 
competition and reduce mark-ups, although the full 
effects usually take time to materialise. By reducing 
consumer  prices,  and  raising  productivity  and 
output, such reforms can have a positive impact on 
real wages. Creating favourable conditions for firm 
entry,  exit  and  growth  can  also  raise  productivity 
(e.g. by promoting allocative efficiency).  

Raising productivity is the most sustainable way to 
support  wage  growth  and  aggregate  demand.  In 
addition  to  labour  and  product  market  reforms, 
adequate investment in human capital, research and 
innovation  can  boost  productivity  and  wage 
growth  at  the  same  time.  Investment  in  human 
capital  can  moreover  help  mitigating  the  possible 
loss  of  bargaining  power  stemming  from  de-
technological 
routinisation 
change,  as  skilled  (unskilled)  labour  is  more  likely 
to be a complement to (substitute of) capital. (88)     

skills-biased 

and 

(84)  Lazear,  E.  P.  (1988)  Employment-at-will,  job  security,  and  work 
incentives. In: Hart, R.A. (ed.) Employment, Unemployment, and 
Labor Utilisation. Unwin Hyman: Boston. 

(85)  Garibaldi, P.,  Violante, G.  L.  (2005).  The  employment  effects  of 
severance  payments  with  wage  rigidities.  The  Economic  Journal, 
115(506), 799-832. 

(86)  e.g. Duval and Furceri (2016), as above. 
(87)  e.g. European Commission (2017), as above. 
(88)  Berman,  E.,  Bound,  J.,  Machin,  S.  (1998).  Implications  of  skill-
biased technological change: international evidence. The Quarterly 
Journal  of  Economics,  113(4),  1245-1279;  Sala,  H.,  Trivín,  P. 
(2017).  The  Effects  of  Globalisation  and  Technology  on  the 
Elasticity of Substitution, IZA Discussion Papers 10898. 

  
 
                                                      
                                                      
suggests 

A  case  study  using  the  Commission's  global 
macroeconomic  model 
that 
structural  factors  can  have  a  significant  impact  on 
wage  formation.  The  analysis  shows  important 
contributions of productivity-increasing investment 
and  labour  market  rigidities  to  explaining  wage 
developments in Italy and Spain. (89)   

indeed 

I.6.  Conclusions 

is  entering 

The  euro  area 
its  sixth  year  of 
uninterrupted economic growth, and is expected to 
continue  growing,  albeit  at  slightly  slower  pace. 
The impact of the recovery is also observed in the 
labour  market,  with  employment  surpassing  pre-
crisis  levels  since  2017  and  unemployment  rates 
approaching levels prior to the recession and set to 
decline to 7.5% by 2020.   

At  the  same  time,  nominal  wage  growth (90)  was 
not picking up until recently in line with what one 
would  expect  based  on  its  historical  relationship 
with standard indicators of slack. This note has set 
out  different  reasons  that  contribute  to  the 
observation of subdued wage growth. The analysis 
in Box I.1 illustrates the role of weak productivity 
developments,  low  core  inflation,  and  "sticky" 
inflation  expectations.  In  some  countries,  where 
unemployment  remains  high  compared  to  pre-
crisis  levels,  labour  market  slack  and  "pent-up" 
wage 
to  exert  downward 
pressure on wage growth. Other structural changes 
such  as  downward  trends  in  working  hours  per 
employee  and  the  possible  role  of  globalisation, 
technological  progress  and  declining  unionisation 
have been discussed as well. 

inflation  continue 

In  the  post-crisis  period,  the  adjustment  of  wages 
to diverging domestic cyclical developments across 
euro area countries has been supportive of external 
rebalancing.  Nevertheless,  this  effect  seems  to  be 
weakening  in  recent  years,  as  a  result  of  the 
recovery of wage growth from very low rates in net 
debtor  countries  coupled  with  weak  productivity 
gains, while wage growth has remained moderate in 
surplus  countries  in  spite  of  the  recovery  gaining 
pace. From this perspective, stronger wage growth 
in  countries  with  a  strong  and  persistent  current 
account  surplus  would  arguably  support  domestic 
demand  and  aggregate  demand  in  the  euro  area, 
and  contribute  to  the  economic  recovery  and  the 

(89)  See European Commission (2018c), as above. 
(90)  Measured in terms of nominal compensation per employee 

I. Wage dynamics in the EMU 

rebalancing,  while  easing 
adjustment  of 
vulnerable  as  a  result  of 
international investment positions. 

those  countries 

the  competitiveness 
remain 
that 
large  negative  net 

Wage  growth  in  the  euro  area  has  accelerated  in 
2018, helped by the closure of the output gap, the 
surge in labour shortages in several Member States, 
and  the  gradual  increase  of  core  inflation  that  has 
started  to  feed  into  wage  negotiations.  Looking 
ahead,  with  growth  slowing  down  amid  economic 
uncertainty,  wage  growth  is  forecast  to  slightly 
decelarate  again  by  2019.  In  the  absence  of 
structural  changes,  sluggish  labour  productivity 
growth  and  the  downward  trend  in  hours  worked 
per  employee  may  as  well  continue  to  exert 
downward pressure on wage growth in the future. 
Developments 
global 
competition (e.g. in the framework of global supply 
chains), the emergence of new forms of work, and 
the structural shift towards the service sector (with 
lower  union  density)  are 
to  continue, 
potentially  weakening  workers'  bargaining  power 
growth.  Low  union 
and 
membership  among  young  workers  might  as  well 
further exacerbate the de-unionisation trend. (91) 

therefore  wage 

increasing 

related 

likely 

to 

Governments have some instruments at hand with 
which they can directly or indirectly influence wage 
developments,  even  though  the  brunt  of  wage 
formation  results  from  the  interplay  of  market 
forces. Wage growth is influenced by the presence 
of  statutory  minimum  wages,  the  institutional 
settings  of  collective  bargaining 
frameworks, 
policies  regarding  the  setting  of  public  sector 
wages,  and  tax  and  benefits  policies.  Other 
structural  reforms  in  product  and  labour  market 
can play a role as well, e.g. through their impact on 
(e.g.  dismissal  costs), 
non-wage 
innovation  and 
segmentation,  price  mark-ups, 
productivity.  Since  these  instruments  interact  in 
different  ways  with  the rest  of the  economy,  their 
effectiveness  in  steering  wage  developments  and 
their  impact  on  the  rest  of  the  economy  varies 
greatly  as  well.  Country-specificities  play  an 
important role in this context.  

labour  costs 

Raising productivity can support wage growth, the 
expansion of demand, and sustainable growth  and 
job creation at the same time. This underscores the 

(91)  European  Commission 

intergenerational 
fairness  through  social  dialogue,  chapter  5  of  Employment  and 
Social  Developments  in  Europe  2017.  Directorate-General  for 
Employment, Social Affairs and Inclusion. 

(2017),  Fostering 

Volume 17 No 3 | 25 

 
                                                      
                                                      
importance  of  productivity-increasing  structural 
reforms, such as reforms that make labour markets 
more adaptable and responsive in order to improve 
allocative  efficiency,  reforms  that  make  product 
markets  more  open  and  competitive,  and  reforms 
that  improve  the  overall  business  environment, 
with  stimulating  conditions for  firm  entry,  growth 
and innovation. Adequate investment in human 

capital,  research  and  development  is  key  as  well, 
along  with  measures  that  ensure  the  efficient 
formation  of  skills  in  initial  as  well  as  post-
compulsory  education  and  training  for  individuals 
of  all  ages.  These  structural  reforms  not  only 
strengthen the supply side of the economy, but can 
also  boost  demand  through  increased  real  wages 
and higher investment.     

26 | Quarterly Report on the Euro Area 

  
 
 
II. Determinants of economic resilience in the euro area: 
An empirical assessment of policy levers 

This  section  investigates  which  structural  characteristics  matter  most  for  a  country's  economic 
resilience. This is done econometrically by comparing the capacity to absorb and recover from common 
shocks across the euro area Member States. The section aims at identifying a set of factors as diverse 
and specific as possible in order to guide future policy actions. The results suggest that factors related 
to  the  well-functioning  of  markets  matter  most.  For  instance,  creating  environments  that  foster 
entrepreneurship increases the ability to adapt and recover from exogenous shocks. Price controls both 
amplify  shocks  and  slow  down  the  recovery.  A  higher  stock  of  non-performing  loans  and  a  weaker 
competition  in  the  banking  sector  affect  negatively  an  economy's  absorption  as  well  as  recovery 
capacity.  Some  structural  factors  such  as  economic  openness  appear  to  have  different  impact  on  the 
shock  absorption  capacity  and  the  recovery  capacity  in  the  face  of  a  common  shock.  Such  findings 
reiterate  the  need  to  pursue  vigorously  policies  and  structural  reforms  including  those  that  take 
advantage  of  synergies  and  complementarities  such  as  between  a well-functioning  Banking  Union  and 
Capital Markets Union which increases risk-sharing and a further opening to international trade. Finally, 
the  macro-econometric  results  also  imply  that  more  analysis  is  needed  to  understand  better  specific 
transmission mechanisms such as active labour market policies.  (92) 

II.1. Introduction 

(93)  This 

The  Five  Presidents'  Report  highlights 
the 
importance  of  the  notion  of  convergence  towards 
is  a 
resilient  economic  structures. 
necessary  (but  not  sufficient)  condition  for  the 
well-functioning  of  the  Economic  and  Monetary 
Union  and 
real 
long  run.  Increasing  the 
convergence 
resilience of the economy will reduce the risk that a 
country  deviates 
real 
significantly 
convergence path. 

for  promoting 
in  the 

sustainable 

from 

its 

However,  economic  resilience  is  a  very  broad 
concept and attempts to narrow it down were done 
only  recently. (94)  Likewise,  the  empirical  evidence 
about  the  determinants  of  resilience  at  country 
level is also rather scarce. (95) However, it is crucial 
to  understand  those  to  inform  the  policy-making 
and guide the structural reforms.  

This  section  assesses  empirically  how  different 
factors affect economic resilience at the level of the 
euro area Member States in order to identify policy 
levers that can be used to strengthen it.  

Strengthening  resilience  entails  acting  on  three 
elements:  i)  reducing  the  economies'  vulnerability 
to  shocks;  ii)  increasing  their  shock-absorption 
capacity; and iii) increasing their ability to reallocate 
resources and recover from the shocks. (96)  

This  section  focusses  on  the  latter  two  elements, 
namely it aims at identifying the structural features 
of economies that make them able to weather the 
impact  of  adverse  shocks  both  in  the  short-  and 
medium-term.  The  factors  affecting  the  first 
element have already been examined elsewhere (97) 
by  identifying  the  short-term  vulnerabilities and 
imbalances  (98)  that  affect  the  likelihood  that  an 
economy gets hit by a shock.     

(92)  This  article  has  been  prepared  by  Maya  Jolles,  Eric  Meyermans 
and Bořek Vašíček. The authors wish to thank Dris Rachik for his 
help  running  the  Bayesian  model  averaging  (BMA)  and  an 
anonymous referee for useful comments. 

(93)  See Juncker, J-C, in close cooperation with Tusk, D, Dijsselbloem, 
J.,  Draghi,  M.  and  M.  Schultz  (2015),  Completing  Europe's  
Economic and Monetary Union. 

(94)  See,  for  instance,  Alessi,  L.,  Benczur,  P.,  Campolongo,  F., 
Cariboni,  J.,  Manca,  A.  R.,  Menyhert  B.  and  A.  Pagano  (2018), 
'The  resilience  of  EU  Member  States  to  the  financial  and 
the  characteristics  of  resilient 
economic  crisis.  What  are 
behaviour?', JRC Working Papers JRC111606; Canton E., Mohl P., 
Reut  A.  and  M.  Ward-Warmedinger  (2016),  'How  to  make  the 
Economic and Monetary Union more resilient?', Quarterly Report on 
the  Euro  Area,,Vol.  15(3),  pages  7-18;    G20    (2017),  'Note  on 
Resilience Principles in G20 countries'. 

(95)  Sondermann, D. (2018), 'Towards more resilient economies: The 
role  of  well-functioning  economic  structures',  Journal  of  Policy 
Modeling,  Vol. 40, No. 1, pp 97-117 

(96)  Giudice  G.,  Hanson  J.  and  Z.  Kontolemis  (2018),  'Economic 
resilience in EMU', Quarterly Report on the Euro Area, Vol. 17, No. 
2, pp. 9-15 presents an extensive but non-exhaustive taxonomy of 
factors that could have an impact on the three building blocks of 
economic resilience. While the authors offer a broad framework, 
they  do  not  empirically  compare  the  relative  importance  of  the 
different factors. 

(97)  See,  for  instance,  Röhn  O.,  Caldera  Sánchez  A.,  Hermansen  M. 
and  M.  Rasmussen  (2015),  'Economic  resilience:  A  new  set  of 
vulnerability  indicators  for  OECD  countries',  OECD  Economics 
Department Working Papers No. 1249. Hermanssen M. and O. Röhn 
(2015),  'Economic  resilience:  The  usefulness  of  early  warning 
indicators  in  OECD  countries',  OECD  Economics  Department 
Working Papers No. 1250. 

(98)  Contrary  to  shocks  which  are  exogenous,  imbalances  tend  to  be 
policy-driven  and  build  up  over  time  until  they  become 
unsustainable.  A  rich  literature  has  aimed  at  identifying  the 
progressive accumulation of imbalances.  

Volume 17 No 3 | 27 

 
                                                      
                                                      
This section is structured as follows. Sub-section 2 
briefly  describes  the  analytical  framework  used  to 
estimate the impact of various factors affecting an 
economy's  capacity  to  absorb  and  recover  from 
common  shocks.  Sub-section  3  identifies  factors 
that  may  potentially  affect  an  economy's  shock 
absorption  and  recovery  capacity,  including    i) 
the  diversity  and 
structural  factors  such  as 
openness  of  the  economy,  ii)  factors  affecting  the 
functioning  of 
labour,  product  and  financial 
markets,  iii)  macro-economic  conditions,  and  iv) 
factors  affecting  the  quality  of  non-economic 
institutions  such  as  governance.  Sub-section  4 
provides  estimates  of  the  significance  of  these 
factors.  The 
last  section  draws  some  policy 
conclusions. 

Finally, it is important to note that the subsequent 
analysis provides empirical results within the limits 
set by data availability and by the use of a reduced 
form  econometric  analysis. As  such the  analysis  is 
less  suited  to  provide  a  full  understanding  of  the 
micro-economic  transmission  mechanisms  that 
affect an economy's resilience such as active labour 
market  policies  that  are  specifically  targeted  to 
specific groups like the young, the low skilled and 
the  long-term  unemployed.  Further  analysis  and 
development of this framework would be useful. 

II.2. A framework for empirical analysis 

Graph  II.1  summarises  the  variety  in  cyclical 
behaviour  among  euro  area  Member  States  in 
terms  of  amplitude  and  persistence  of  the  output 
gap. (99) While the output gap widened significantly 
at  the  onset  of  the  Global  Financial  Crisis  in  all 
euro  area  Member  States,  it  persisted  at  a  much 
stronger pace in the Member States hardest hit by 
the crisis. To the extent that this was triggered by a 
common  shock  with  the  same  intensity,  this 
pattern may reflect differences in resilience.  

The aim of this section is to investigate empirically 
the  factors  that  may  have  contributed  to  these 
disparities.  The  significance  and  relative  importance  of 
these factors (detailed in sub-section II.4 below) is 
evaluated by comparing the impact of and recovery from 

(99)  Other measures could be used. For instance, Caldera Sánchez A., 
Rasmussen M. and O. Röhn (2016), 'Economic Resilience: What 
Role  for  Policies?',  Journal  of  International  Commerce,  Economics  and 
Policy,  Vol.  7,  No.  2  pp.  1-44,  identify  economic  resilience  as  a 
lower  occurrence  of  severe  recession.  Elbourne  A,  Lanser  D., 
Smid B. and M. Vromans (2008), 'Macroeconomic resilience in a 
DSGE  model',  CPB  Discussion  Paper  No.  96  use  the  level  of 
expected discounted utility as a measure of resilience. 

28 | Quarterly Report on the Euro Area 

common  shocks  across  the  euro  area  Member 
States  (for  which  sufficient  data  are  available  as 
well  as  a selected  group  of non-euro  EU Member 
States) (100) over the period from 1998 to 2015. (101)  

Graph II.1: Output gap dynamics across the 
euro area 

includes 

(1)  Core  EA  includes  DE,  AT,  NL  and  FR.  EA  Member  States 
hardest  hit 
PT. 
(2)  The  output  gap  measures  the  gap  between  actual  GDP 
and  potential  GDP  as  percentage  of  potential  GDP  and  is 
measured in this section as AMECO variable AVGDGP. 
Source: Authors' estimates based on AMECO data. 

ES,  EL,  CY 

and 

IE, 

For  this  purpose,  an  output  gap  autoregressive 
econometric  equation  is  estimated  in  panel  setting 
whereby each country's absorption capacity (measured 
by  the  response  coefficient to  the  common shock 
in the equation) and the speed of recovery (measured by 
the  response  coefficient  of the  lagged  output  gap) 
depend 
structural 
characteristics (See Box II.1 for more details on the 
specification).  

country 

specific 

on 

In  reality,  each  economy 
is  subject  to  both 
idiosyncratic and common shocks. Moreover, the shocks 
can  be  of  different  nature  such  as  productivity 
shock, confidence shock or change in preferences. 
Importantly, shocks are not directly observable and 
have to be estimated. In this empirical framework, 
the resilience of Member States is tested in case of 
common  shocks.  Namely,  an  economy  is  more 
resilient  than  another  if  after  being  hit  by  a 
common  shock  it  performs  better.  Given  that  the 
purpose  of  the  analysis  is  to  identify  structural 
characteristics  that  make  countries  better  weather  
adverse  developments,  it  is  necessary  to  draw  on 

(100) I.e., BE, DE, IE, ES, FR, IT, LU, NL, AT, PT, FI, CZ, DK, HU, 

PL, SE and UK. 

(101) The sample size is set by data availability. 

-10-8-6-4-20246200020022004200620082010201220142016EA Member States hardest hitCore EAEA  
 
                                                      
 
                                                      
II. Determinants of economic resilience in the euro area: An empirical assessment of policy levers 

the  cross-country  experience.  This  can  be  most  easily 
done in case of general common shocks, i.e. shocks of 
the  same  size  without  identifying  the  exact  nature 
of  the  shock.  However,  it  can  be  assumed  that 
most  of  the  results  hold  also  for  idiosyncratic 
shocks.  Box  II.1  shows  estimates  of  such  general 
common 
the  Member  States 
shocks hitting 
between 1994 and 2017.  

II.3. Factors affecting the shock absorption 
capacity and persistence of shocks 

Previous research tested the significance of a range 
of  broad  factors  (e.g.  product  market,  labour 
market,  taxation)  that  are  most  relevant  for 
economic  resilience  without  exploring the  detailed 
factors  that  can  be  linked  to  concrete  structural 
reforms.  For  instance,  some  authors  report  that  a 
high  level  of  product  market  regulation  weakens 
industries' resilience to adverse shocks. (102) For the 
euro area Member States, it was reported that well-
functioning 
labour  and  product  markets  and 
political  institutions  improve  an  economy's  shock 
absorption  capacity.  (103)  The  analysis  examining 
possible  trade-offs  between  growth  and  economic 
resilience, did not find trade-offs as far as product 
and  labour  market  reforms  are  concerned,  but 
indicated that trade-offs may appear in the areas of 
financial market and macro-prudential policies. (104) 
Finally,  some  authors report  that  a  low  protection 
of temporary contracts, political stability, regulatory 
quality and pre-crisis fiscal space were found to be 
the  most  relevant  for  a  swift  recovery,  whereas 
unemployment 
employment 
protection  legislation  do  not  seem  to  increase 
economic resilience. (105) 

benefits 

and 

This section provides an assessment of factors at a 
more  disaggregated  level.  The  factors  affecting 
in  several 
resilience  are  classified 
economic 
categories  -  ranging  from  very  broad  structural 
factors  such  as 
to 
international  trade  and  institutional  characteristics 
like  the  level  of  corruption,  to  very  specific 
characteristics  including  the  regulation  of  labour 

the  economy's  openness 

markets  as  well  as  short-term  macroeconomic 
conditions such as interest rates. Here it should be 
noted  that  while  there  are  many  potential  factors, 
they do not necessarily point in the same direction. 
In  some  cases  the  same  factor  can  have  positive 
impact  on  absorption  while  negative  on  recovery. 
Box II.2  briefly  describes  the  indicators  which  are 
used  to  measure  these  factors.  As  previously 
discussed, it can be reasonably assumed that these 
factors have an impact on resilience in broad terms, 
i.e.  they  contribute  to  a  country’s  capacity  to 
weather adverse shocks irrespectively of the shock 
origin (idiosyncratic, common) and type. 

II.3.1.  Product markets  

Competitive product markets are important drivers 
of economic resilience as well-functioning product 
markets  generate  more  rapid  adjustments  also 
shifting the adjustment burden from quantities (i.e. 
output) 
impact  on 
competitiveness.    

to  prices  which  has  an 

barriers 

including 

Several factors affect the degree of competition in 
product  markets (106) 
to 
entrepreneurship such as  licenses and permit systems 
and  administrative  burdens,  barriers  to  trade  and 
investment such as differential treatment of foreign 
suppliers  and  barriers  to  FDI  as  well  as  state 
control  such  as  price  controls  and  government 
involvement in network industries. 

More  specifically,  entrepreneurship  framework 
conditions  have  a  direct  impact  on  the  entry  and 
exit  of  firms  which  is  especially  important  during 
the recovery as it helps to reallocate resources. (107) 
State  control,  especially  price  controls  and  strict 
regulation  of  network  industries  and  professional 
services may limit especially an economy's recovery 
capacity. 

(102) Canova,  F.,  Coutinho,  L.  and  Z.  Kontolemis  (2012),  'Measuring 
the macroeconomic resilience of industrial sectors in the EU and 
assessing  the  role  of  product  market  regulations',  European 
Economy Occasional Papers 112 

(103) Sondermann (2018), op. cit. 
(104) Caldera Sánchez A., Rasmussen M. and O. Röhn (2016), op.cit. 
(105) Brůha J. and O. Kucharčuková (2017), 'An Empirical Analysis of 
Macroeconomic  Resilience:  The  Case  of  the  Great  Recession  in 
the  European  Union',  Working  paper  series  10,  Czech  National 
Bank 

(106) Following  the  classification  of  the  OECD  Product  Market 
Regulation  Indicator.  See,  for  instance,  Koske,  I.    et  al.    (2015), 
'The  2013  update  of  the  OECD's  database  on  product  market 
regulation: Policy insights for OECD and non-OECD countries',  
OECD Economics Department Working Papers No. 1200. 

(107) See Andrews and Saia (2017), 'Coping with Creative Destruction: 
Reducing  the  Costs  of  Firm  Exit',  OECD  Economics  Department 
Working Papers, No. 1353. 

Volume 17 No 3 | 29 

 
                                                      
                                                      
(Continued on the next page) 

30 | Quarterly Report on the Euro Area 

 Box II.1: Estimating absorption and recovery capacity in case of common shock.A. Estimation of common shocks The first step in the analysis of resilience is identification of adverse episodes, which were common to all countries in the sample (common shocks) in order to link cross-country divergences to their resilience rather than to different size of shocks hitting them. However, shocks cannot be observed and must be estimated. Specifically, the common shocks are estimated in a panel model describing real GDP growth (see e.g. Sondermann, 2018) as  𝑑𝑙𝑛 𝐺𝐷𝑃𝑖,𝑡 = 𝛿𝑡𝐷𝑈𝑀𝑡+ 𝜌𝑖𝐷𝑈𝑀𝑖+𝑣𝑖,𝑡  for a sample from 1998 until 2015 and covering 17 countries (1), with GDP being real GDP, 𝐷𝑈𝑀𝑡 a time dummy, 𝐷𝑈𝑀𝑖, a country dummy, and with v the stochastic term.  The common shock is captured by the standardised estimates of 𝛿𝑡, while the idiosyncratic shock is captured by 𝜌𝑖+𝑣𝑖,𝑡. (2) The graph below shows estimates as by how much the common shock induced observed GDP growth to deviate from its trend growth.   Graph 1: Estimates of common shocks  Source: Authors' estimates. B. Specification of output gap dynamics  The following econometric equation is used to estimate the Member States' absorption and recovery capacity in response to a common shock          𝑌𝑖,𝑡=  𝛽 𝑆𝐻𝑂𝐶𝐾_𝐶 𝑡  + 𝛽𝑙 𝑍𝑖,𝑙,𝑡 𝑆𝐻𝑂𝐶𝐾_𝐶 𝑡 𝑘𝑙=1             impact of common shock  + structural factors  affecting its absorption                       + 𝛼𝑌𝑖,𝑡−1      +  𝛼𝑗𝑍𝑖,𝑗,𝑡 𝑌𝑖,𝑡−1 𝑘𝑗=1          recovery from past output gaps +  structural factors affecting recovery                     +  𝛾𝑖,𝑚 𝑄𝑖,𝑚,𝑡− 𝑄 𝑖,𝑚 𝑛𝑚=1  +  𝑢𝑖,𝑡                          impact macro-economic policy variables   + stochastic component with Y the output gap; Z the structural factors affecting absorption and recovery such as product market regulation; SHOCK_C a common shock; Q the macro-economic variables affecting output gap such as                                                            (1) I.e., BE, DE, IE, ES, FR, IT, LU, NL, AT, PT, FI, CZ, DK, HU, PL, SE and UK. (2) Implicit assumptions estimating these common shocks are that common and idiosyncratic shocks are not correlated with each other and that shocks are exogenous. On endogenous shocks that emerge from within the system, see for instance Minsky, H. (1986), Stabilizing an Unstable Economy, Yale University Press  and Wolf, M. (2015), The Shifts and the Shocks: What We've Learned--and Have Still to Learn-from the Financial Crisis, Penguin Books   
 
 
 
 
 
 
II. Determinants of economic resilience in the euro area: An empirical assessment of policy levers 

Box (continued) 

Volume 17 No 3 | 31 

interest rates; Q ̅ equilibrium value of macro-economic variable;  and with i a country index, t time index, k number of structural factors and m number of macro-economic variables. The contribution of each factor 𝑍𝑖,𝑗,𝑡 to the absorption and recovery is measured by, respectively, 𝛽𝑗 𝑍𝑖,𝑗,𝑡  and 𝛼𝑗 𝑍𝑖,𝑗,𝑡 having a positive or negative value and indicating whether they amplify/dampen the impact of a shock, or speed-up/delay the recovery.  The total absorption and recovery capacity is measured by collecting all terms, i.e. 𝛽+ 𝛽𝑙 𝑍𝑖,𝑗,𝑡 𝑘𝑙=1 for the absorption capacity and 𝛼+ 𝛼𝑙 𝑍𝑖,𝑗,𝑡 𝑘𝑙=1 for the recovery capacity. The latter is expected to have a value between 0 and 1, a lower value indicates a faster recovery. Several issues have to be taken into account when estimating the above equation. First, the explanatory variables may be strongly correlated with each other as they are often changed as part of a reform package (i.e. multicollinearity). Second, the explanatory variables may be correlated with the random component as for instance reforms are introduced or delayed in response to the state of the business cycle (i.e. simultaneity). (3)  Third, the error terms of the equations do not have the same distribution as their variance may differ across Member States. In addition, they may also be cross-sectionally correlated as well as serially correlated. (4)  Fourth, as common and idiosyncratic shocks are assumed to be orthogonal, the omission of the latter type of shocks in the regression does not induce a missing-variables bias. Fifth, to save on the degrees of freedom no country fixed effects have been included but the dependent and explanatory variables were demeaned.  Moreover, by construction the lagged output gap and shock should be uncorrelated. In period t the shock is by definition "news" (i.e. uncorrelated with any variable from the past including the lagged output gap as well as past "news"). Furthermore, time varying interactions between explanatory variables may call for the inclusion of both base variables separately to avoid a missing variables bias. See, for instance Aitken and West (1991) (5). However, here it should be remembered that the dependent variable (i.e. the output gap) is on average equal to zero (over the business cycle). The explanatory variables, i.e. the shock and lagged output gap interacting with a broad set of factors, are also on average equal to zero. Including a factor on its own not interacting with the shock or lagged output gap (which is on its own different from zero) would then imply that "in equilibrium" the output gap would not be closed. As such, the regression analysis does not include base variables separately. Finally, a low significance level for a point estimate for a factor does not necessarily mean that the factor is irrelevant as a low  level of significance may arise because of  multi-collinearity or because the considered indicators vary only in very limited ranges over time and across countries (and regression analysis is based on variation of indicators).  C. Bayesian Model Averaging Another issue related to estimation of aforementioned equation is model uncertainty. Namely, there are many potential explanatory variables. First, putting all of the potential variables into one regression might inflate the standard errors if irrelevant variables are included. Second, using sequential testing to exclude unimportant variables might deliver misleading results since there is a chance of excluding the relevant variable each time the test is performed. Bayesian model averaging (BMA) takes into account model uncertainty by considering the model combinations and weighting them according to their model fit. (6) The robustness of a variable in explaining the dependent variable can be expressed by the probability that a given variable is included in the regression. It is referred to as the posterior inclusion probability (PIP).                                                            (3) Problems of simultaneity have been addressed by taking 3-year average moving averages of the interaction variables, except for the instrumentalised variables that include short-interest rate, public debt, private debt and the real effective exchange. Note also, that the lagged dependent variable appear always in an interaction term rather than separately. Therefore, the regression is not a standard dynamic panel that would require use of GMM-type of estimators such as Arellano-Bond. (4) These problems have been addressed by applying an appropriate generalised least squares estimator. However, as in this exercise the number of time periods is low compared to number of cross sections it will have to be assumed that covariance matrices of random components are constant over time. The latter assumption will affect the efficiency, but not consistency of the estimates. (5) Aitken, L. and S. West (1991), Multiple regression: testing and interpreting interactions, Sage Publications. (6) A vast literature uses model averaging to address these issues, in economics notably in the domain of determinants of economic growth (Fernandez et al., 2001, Feldkircher and Zeugner, 2009, Moral-Benito, 2011).  
 
 
 
 
The  impact  of  product  market  regulation  on  the 
economy's absorption and recovery capacity is not 
unambiguous. For example, on the one hand, more 
stringent  product  market  regulation  may  lead  to 
higher  price mark-ups that allow firms to cushion 
the  employment 
impact  of  price  fluctuations 
initially.  (108)  On  the  other  hand,  however,  more 
stringent  product  market  regulation  slows-down 
the  recovery  as  it  hinders  the  reallocation  of 
resources  by  hindering,  for  instance,  the  entry  of 
new firms. (109) 

In addition, deepening the Single Market including the 
transposition and application of directives, impacts 
Member  States' 
strengthens 
resilience  as 
opportunities  to  increase  product  diversification 
and 
cross-border 
flexibility,  while 
convergence  towards  best  practices  in  terms  of 
market  openness, 
insolvency  frameworks  and 
business  regulations  may  speed  up  the  recovery. 
(110) 

price 

it 

Finally, product markets affect resilience also in an 
indirect  way  because  well-functioning  product 
markets  allow  for  a  better 
transmission  of 
monetary and fiscal policy impulses. (111)  

II.3.2.  Labour markets  

The  composition  of  the  labour  force  represents  a  key 
structural feature of labour market as a high share 
in  total  employment  of  experienced  high-skilled 
workers  and  self-employment  creates  a  stronger 
capacity  to  absorb  and  adapt  to  shocks. (112)  Self-

(108) See, 

for 

instance,  OECD 

'Understanding  Policy 
Interactions  and  Complementarities,  and  their  Implication  for 
Reform  Strategies',  Chapter  6  in  2006  OECD  Employment 
Outlook.  

(2006), 

(109) See  also,  Duval  and  Vogel  (2008),  op  cit.  for  additional  empirical 
evidence.  Canova,  F.,  Coutinho,  L.  and  Z.  Kontolemis  (2012), 
'Measuring  the  macroeconomic  resilience  of  industrial  sectors  in 
the  EU  and  assessing  the  role  of  product  market  regulations', 
European  Economy  Occasional Papers  112  report  that  a  high  level  of 
PMR makes industries less resilient to adverse shocks.  

(110) See, for instance, Jolles M. and E.  Meyermans (2018), ' Economic 
resilience,  the  Single  Market  and  EMU:  a  self-reinforcing 
interaction', Quarterly Report on the Euro Area, Vol. 17, No. 1, pp. 7-
22, also emphasising that deepening of the Single Market should 
be complemented by a well-functioning  Banking Union and the 
Capital Markets Union. 

(111) Pelkmans  J.,  Acedo  Montoya  L.  and  A.  Maravalle  (2008),  'How 
product  market  reforms  lubricate  shock  adjustment  in  the  euro 
area', European Economy Economic Papers No. 341. 

(112) For instance, Liang, J. and S. Goetz (2016), 'Self-employment and 
trade  shock  mitigation',  Small  Business  Economics,  Vol.  46,  No.  1, 
pp. 45-56, analysing data at the US regional level, report that the 
marginal impacts of Chinese import penetration on job losses are 
localities  with  higher  self-employment  rates, 
dampened 
reflecting their stronger propensity to be flexible and absorb new 
knowledge when a shock hits the economy.   

in 

32 | Quarterly Report on the Euro Area 

employment  may  also  be  a  mechanism  to  escape 
unemployment  when  the  economy  gets  hit  by  an 
adverse shock. (113) 

Another  important  feature  is  flexibility  of  wages 
and  prices.  When  wages  and  prices  are  rigid  most 
of  the  adjustment  falls  on  quantities,  including 
output and employment – especially in the case of 
persistent shocks. Labour markets institutions have 
a  direct  impact  on  macro-economic  adjustment. 
(114)  However,  their  impact  on  absorption  and 
recovery  does  not  necessarily  point  in  the  same 
direction.  

linked 

effects 

For  example,  out-of-work  income  support  could 
help  to  stabilise  aggregate  demand  if  the  shock 
would  induce  lay-offs  -  thereby  tempering  the 
impact  of  the  shock  on  consumption  and  limiting 
hysteresis 
persistent 
unemployment  spells  that  would  aggravate  the 
long-run  growth  potential. (115)  However,  a  too 
generous  or  protracted  out-of–work 
income 
support  may  increase  workers'  reservation  wage 
which  in  turn  may  hinder  labour  reallocation. (116) 
(117) In addition, the effective use of such schemes 
during  a  downturn  is  conditioned  by  the  available 
fiscal space. (118)  

to 

Strict  Employment  Protection  Legislation  (EPL) (119) 
may  temper  the  firing  of  labour  in  the  face  of  an 

(113) Such  endogeneity  implies  then  that  in  the  empirical  analysis 
instrumental variables are used if the share of self-employment in 
total employment is included as explanatory variable.    

(114) For instance, Blanchard and Wolfers (2000), 'The Role of Shocks 
and  Institutions  in  the  Rise  of  European  Unemployment:  The 
Aggregate  Evidence',  NBER  Working  Paper  No.  7282,  provide 
empirical evidence on the interactions between shocks and labour 
market institutions - albeit in their analysis the dependent variable 
is the unemployment rate. 

(115) See, for instance, Meyermans, E. and P. Nikolov (2017), ' Long -
term  labour  market  effects  of  the  Great  Recession',  Quarterly 
Report on the Euro Area, Vol. 16, No. 3, pp. 41-56.. 

(116) Apart  from  raising  workers'  reservation  wage,  out-of-work 
income  support  may  also  increase  workers  time  for  job  search 
thereby  improving  job  matching  –  which  in  turn  may  improve 
potential productivity. 

(117) See,  for  instance,  Bassanini  and  Duval  (2006),  'Employment 
Patterns  in  OECD  Countries:  Reassessing  the  Role  of  Policies 
and  Institutions',  OECD  Economics  Department  Working  Paper  No. 
486  report  a  positive  effect  of  unemployment  benefits  on  the 
persistence  of  unemployment.  But  Brůha  et  al.  (2017)  op  cit.  do 
not  find  evidence  that  generous  unemployment  benefits  make  a 
difference. 

(118) See,  for  instance,  Hijzen,  A.,  Kappeler,  A.,  Pak,  M.  and  C. 
Schwellnus  (2017), 
'Labour  market  resilience:  The  role  of 
structural  and  macroeconomic  policies',  in  OECD  Employment 
Outlook 2017 

(119) The  OECD  EPL  indicator  captures  the  strictness  of  the 
Employment  Protection  Legislation  through  18  indicators  that 
cover  three  broad  areas:  1.Employment  protection  of  regular 
workers  against  individual  dismissal;  2.Specific  requirements  for 

  
 
                                                      
                                                      
 
II. Determinants of economic resilience in the euro area: An empirical assessment of policy levers 

adverse  shock  which  in  turn  may  temporarily 
support  employment  and  aggregate  demand. 
However,  it  could  also  delay  any  necessary  labour 
reallocation  during  the  recovery  phase. (120)  A  less 
restrictive  EPL  could  on  the  other  hand  increase 
job turn-over as well as income insecurity, so that, 
in the absence of adequate unemployment benefits, 
aggregate consumption would be adversely affected 
by  precautionary  savings  –  slowing  down  the 
recovery. (121)   

Active labour market policies (ALMP) (122)  also impact 
economic  resilience  especially  during  the  recovery 
as  they  cover  a  whole  range  of  policies  that 
facilitate  labour  reallocation  such  as  training  of 
workers  as  well  as  guidance  and  counselling 
provided  by  public  employment  services  (PESs). 
(123) Graph  II.2  shows  that  there  are  notable 
differences  across  Member  States  in  terms  of 
expenditure  on  public  employment  services  and 
training. 

Collective  bargaining  is  a  key  determinant  of  wage 
flexibility  whereby  both  highly  centralised  and 
highly  decentralised 
the 
alignment  of  wages  and  productivity,  while  a  high 
degree of coordination of bargaining can moderate 
wage increases.  (124)  At the same time, bargaining 

strengthen 

regimes 

collective  dismissals;  and  3.Regulation  of  temporary  forms  of 
employment. 

(120) Duval  and  Vogel  (2008),  op.  cit.  show  that  strict  labour  and 
product  market  regulation  initially  may  dampen  the  impact  of  a 
common  shock  but  make  it  more  long-lasting.  In  Biroli  P.,  
Mourre G. & A. Turrini (2010), 'Adjustment in the Euro Area and 
Regulation  of  Product  and  Labour  Markets:  An  Empirical 
Assessment', European Economy - Economic Papers 2008 - 2015 
428,  Directorate  General  Economic  and  Financial  Affairs  (DG 
ECFIN), European Commission, the authors show that the EPL 
indeed  dampens  the  adjustment  and  increases  the  persistence  of 
the  shock.  EPL  tends  to  lead  to  more  nominal  wage  rigidity  as 
shown  in  Holden.  S.  and  F.  Wulfsberg  (2005),  'Downward 
Nominal  Wage  Rigidity  in  the  OECD,'  Memorandum  10/2005, 
Oslo  University,  Department  of  Economics.  At  a  more  granular 
level,  Brůha  et  al.  (2017),  op.cit.,  report  that  low  protection  of 
contracts positively impact economic resilience. 

(121) Hence,  the  need  to  explore  the  empirical  significance  of  other 
drivers such as income support for the unemployed and access to 
credit markets. See, for instance, Koeniger, W. and J. Prat (2007), 
'Employment protection and labour market turnover', VoxEU. 
(122) See, for instance, European Semester Thematic Factsheet, Active 
at 

Labour 
https://ec.europa.eu/info/sites/info/files/european-
semester_thematic-factsheet_active-labour-market-policies_en.pdf  
(123) Bassanini  and  Duval  (2006),  op.  cit.,  examine  unemployment 
patterns, so not strictly at economic resilience, and found specific 
interactions  across  policies  and  institutions  to  be  very  robust, 
namely  between  unemployment  benefits  and  public  spending  on 
active labour market programmes 

Policies 

Market 

(124) For instance, Eurofound (2015), 'Pay in Europe in different wage-
bargaining  regimes',  reports  that  a  higher  degree  of  coordination 
and  centralisation  tempers  nominal  unit  labour  cost  growth  but 
has no significant impact real unit labour cost.  

could  increase  rigidities  in  adjustment  to  localised 
developments in case of excessive centralisation or 
being  unable  to  smoothen  wage  adjustment  over 
excessive 
in 
time 
decentralisation. 

case  of 

sectors 

and 

Graph II.2: Expenditure on Public 
Employment Services (PES) and training  
2015 (% of GDP) 

(1) Data for EL and LT missing. 
Source: OECD:  

Finally, 
labour  market  duality  may  hinder  an 
economy's  capacity  to  absorb  and  recover  from  a 
shock  because  of  increased  employment  volatility. 
An excessive adjustment burden falls on workers at 
the  margin  of  the  labour  market  through  the 
deregulation  of  temporary  contracts,  development 
of  agency  work  and  other  contracts  of  limited 
duration.  Indeed,  the  prevalence  of  fixed-term 
contracts 
to  highly  protected 
permanent ones) is found to increase the response 
of  unemployment 
shocks  while 
decreasing its persistence (125).  It is related to other 
aforementioned features such as EPL or collective 
bargaining.  

(as  opposed 

to  output 

II.3.3.  Financial markets  

to  smoothen 

Well-functioning  financial  markets  help  economic 
agents 
their  consumption  and 
investment  in  the  face  of  shocks. (126)  However, 
several factors may limit this capacity whereby it is 

(125) Kosior,  A.,  Rubaszek,  M.,  and  Wierus,  K.  (2016),  'The  potential 
effects  of  labour  market  duality  for  countries  in  a  monetary 
union.' International Labour Review, 155(4), 509-534. 

(126) By  channelling  savings  and  borrowing  across  regions  and  over 
time - provided intertemporal budget constraints are respected. 

Volume 17 No 3 | 33 

00.10.20.30.40.50.60.7ATFIFRDEBEPTIENLITESSILULVSKELLTPESTraining 
                                                                                 
 
                                                      
important  to  distinguish  between  financial  system 
long-term characteristics from vulnerabilities. (127)   

For instance, a high stock of non-performing loans may 
hinder  the  absorption  of  shocks  as  it  limits  the 
banking sector to provide new loans. At the same 
time,  a  severe  shock  may  adversely  affect 
borrowers' ability to repay their debts. (128) In turn, 
this  increase  in  non-performing  loans  weakens 
banks' 
the 
economy's  capacity  to  absorb  shocks. (129)    Graph 
II.3  shows  strong  differences  in  terms  of  non-
performing  loans  (as  percentage  of  total  gross 
loans) across Member States as well as over time in 
some Member States. (130)  

lending  capacity  and 

thus  also 

While the financial sector has the potential to help 
absorb shocks,  it  may  itself  be  a source  of shocks 
or  intensify  the  amplitude  of  credit  cycles.  For 
example,  excessive  credit  expansion  followed  by  a 
housing bubble and burst and sudden reversal may 
lead  banks  to  curtail  lending  and  increase  lending 
spreads. (131) 

found 

it  was 

In case of the long-term characteristics of financial 
intermediation, 
that  a  higher 
stringency  of  capital  adequacy  requirements  for 
banks,  greater  reliance  of  a  domestic  banking 
system on deposits, and openness to non-domestic 
banks  decrease 
to  financial 
contagion.   Access  to  multiple  sources  of  funding 
may in turn reduce the persistence of the effects of 
shocks. (132)   

the  vulnerability 

Banking  sector  competition  is  a  crucial  structural 
variable  that  may  improve  the  allocative  efficiency 

(127) Caldera Sánchez et al. (2016) report a trade-off between efficiency 

and crisis-risk with regards to financial market policies.   

(128) See, for instance, Berti, K., Engelen, C.  and  B.  Vašíček (2017), 
'A macroeconomic perspective on non-performing loans (NPLs)', 
Quarterly Report on the Euro Area, Vol. 17, No. 1, pp. 8-21. 

(129) In  the  econometric  analysis  this  interaction  has  been  taken  into 
account  using  instrumental  variables.  In  general,  in  this  section 
variables  are  instrumentalised using  lagged  variables  with  lags  up 
to  3  years.  More  specifically,  for  non-performing  loans  the 
instrumental variables include lagged output gap and other lagged 
financial variables such as public debt and household debt. 

(130) Due 

to  differences 

in  national  accounting, 

taxation,  and 
supervisory regimes, these data are not strictly comparable across 
countries.  Data  retrieved  from  the  Federal  Reserve  Bank  of  St. 
Louis covering for most Member Sates the full 1998-2015 period. 
ECB data on non-performing loans only start as of 2007.  

(131) See, for instance, Kanngiesser, D., Martin, R., Maurin, L. and D. 
Moccero (2017), 'Estimating the impact of shocks to bank capital 
in the euro area', ECB Working Paper Series No 2077.  

(132) Ahrend, R. and A. Goujard (2012), 'International Capital Mobility 
and Financial Fragility - Part 3. How Do Structural Policies Affect 
Financial Crisis Risk?: Evidence from Past Crises Across OECD 
and Emerging Economies, OECD Working Papers No. 966, 

34 | Quarterly Report on the Euro Area 

level  of  financial  development 

of capital as well as investment, which in turn may 
speed  up  the  recovery. (133)  However,  beyond  a 
threshold 
the 
financial sector may ignite  a  reallocation of highly 
skilled from  the  real  to  the  financial  sector and  
give  rise  to  excessive  increases  in  mortgage  credit 
which  both  are 
less  conducive  to  economic 
resilience. (134)     

Graph II.3: Gross non-performing  debt 
instrument 
(as % of total gross debt instruments) 

(1)  Ratio  of  non-performing  debt  instruments  (payments  of 
interest  and  principal  past  due  by  90  days  or  more)  to  total 
gross  debt  (total  value  of  loan  portfolio).  Debt  instruments 
include  both  loans  and  other  securities  (namely  bonds).  The 
data  on  NPL  ratios  are  available  only  from  2014.  The 
difference between these two ratios is mostly around 1 p.p. 
Source: ECB (Consolidated Banking Data) 

Finally,  some  types  of 
international  financial 
integration,  such  as  international  bank  lending, 
tend  to  amplify  contagion  shocks  and  increase 
crisis risk. (135) In other words, an optimal balance 
between  banking  sector  and  capital  market 
integration 
to  withstand  sudden 
reversals  in  financial  flows  (e.g.  bank  credit)  by 
adjustments  in  other  parts  of  the  financial  system 
(e.g. equity funding). 

required 

is 

(133) In  the  econometric  analysis,  market  power  will  be  measured  by 
the  Lerner  index  which  measures  the  difference  between  output 
prices  and  marginal  costs.  An  increase  in  the  Lerner  index 
indicates  a  deterioration  of  the  competitive  conduct  of  financial 
intermediaries. Source, World Bank. 

(134) See,  for  instance,  Popov,  A.  (2017),  'Evidence  on  finance  and 

economic growth', ECB Working Paper Series No. 2115. 

(135) See,  for  instance  the  identification  of  structural  policies  that 
increase  or  decrease financial  crisis  risks  in  Ahrend  and  Goujard 
(2012)  Ahrend, R.  and  A.  Goujard (2012),  “International  Capital 
Mobility  and  Financial  Fragility  -  Part  1.  Drivers  of  Systemic 
Banking  Crises:  The  Role  of  Bank-Balance-Sheet  Contagion  and 
Financial  Account  Structure”,  OECD  Economics  Department 
Working Papers, No. 902. 

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II. Determinants of economic resilience in the euro area: An empirical assessment of policy levers 

II.3.4.  Structural factors 

economic 

conditions 

Diversification  of  economic  activity  (136)  allows  the 
economy  to  be  more  flexible  in  adapting  to 
changing 
thereby 
strengthening  the  capacity  to  absorb  and  recover 
from  shocks.  However,  strong 
inter-linkages 
between  economic  activities  or  diversification  in 
activities  showing  strong  cyclicality  such  as 
manufacturing and construction may limit the gains 
from diversification.  (137) 

specialisation  may  make 
vulnerable to country specific shocks. (140)   

economies  more 

Graph II.4: Trade openness and export 
diversification (2015) 

The  economy's  openness  to  international  trade  allows 
sharing  some  of  the  adjustment  burden  with  the 
rest  of  the  world  as  it  strengthens  economies' 
capacity  to  absorb  and  recover  from  shocks, 
especially,  in  the  case  of  an  idiosyncratic  shock. 
However, when a common shock hits not only the 
domestic  market  but  also  export  markets  the 
absorption capacity may be tempered. In addition, 
trade  openness  may  affect  the  effectiveness  of 
other  adjustment  channels  as  it  is,  for  instance, 
more  difficult 
in  a  more  open  economy  to 
stimulate  domestic  demand  expansion  as  it  spills 
out through the import channel. (138)  

(1)  Trade  openness  =  (exports  +  imports)/  GDP  in  current 
prices.  Export  diversification  as  measured  by  Hirschman 
Herfindahl Index  which is equal to  sum  of squared shares of 
each  product  in  total  export.  A  country  with  a  perfectly 
diversified  export  portfolio  will  have  an  index  close  to  zero, 
whereas  a  country  which  exports  only  one  export  good  will 
have a value of 1 (least diversified). 
Source: Authors' estimates based on AMECO and WB. 

Closely related to a Member State's trade openness 
is  its  type  of  exports.  For  instance,  Graph  II.4 
shows  a  positive  correlation  between 
trade 
openness  and 
specialisation, 
the  degree  of 
suggesting that Member States with strong market 
openness  have  a  strong  specialisation  in  their 
exports,  i.e.  less  diversified  export  portfolio. (139) 
More  specifically,  research  suggests  that  inter-
intra-industry) 
(as  opposed 
industry 

trade 

to 

income  decreases  compared 

With  stronger  income  inequality (141)  leading  to  more 
income  concentration  at  the  top,  the  fall  in 
aggregate  demand  may  be  smaller  when  hit  by  an 
adverse shock because high income earners have a 
lower  propensity  to  cut  their  expenditures  when 
income 
their 
earners  at  the  lower  end. (142)  At  the  same  time, 
however, the adverse impact may get aggravated if 
lower income groups do not have savings or access 
to credit to absorb a negative shock. In addition, if 
higher  income  inequality  would  lead  to  fewer 
opportunities  for  training  for  the  workers  at  the 
lower end of the income distribution, the recovery 
may also be adversely affected. 

to 

(136) Several indicators have been proposed to measure diversification. 
See  Wundt,  B.    (1992),  'Reevaluating    Alternative    Measures    of  
Industrial  Diversity    as    Indicators    of  Regional    Cyclical  
Variations', The Review of Regional Studies, Vol. 22, No. 1, pp. 59-73. 
Here an indicator based on sectoral employment shares is used. 
(137) See, for instance, Martin, R. (2012), 'Regional economic resilience, 
hysteresis  and  recessionary  shocks',  Journal  of  Economic  Geography, 
Vol. 12, No. 1, pp. 1–32.. Moreover, the impact of diversification 
on  growth  potential  is  not  unambiguous.  On  the  one  hand, 
diversification  reduces  specialisation  in  those  activities  in  which 
Member  States  have  a  comparative  advantage  thereby  lowering 
overall  productivity  growth.  On  the  other  hand,  stronger 
resilience  through  diversity  may  create  stronger  incentives  to 
innovate and invest which may improve potential growth. 

(138) See,  for  instance,  Spilimbergo,  A.,  et  al.  (2008),  'Fiscal  Policy  for 
the Crisis', IMF Staff Position Note, SPN/08/01. Sutherland, D., 
et al. (2010), 'Counter-cyclical Economic Policy', OECD Economics 
Department Working Papers No. 760.  

(139) As measured by the Hirschman Herfindahl Index. 

(140) Krugman,  P.  (1981),  'Intraindustry  Specialisation  and  the  Gains 
from Trade', Journal of Political Economy, Vol. 89, No. 5, pp. 959-73 
(141) Chen, T et al. (2018), ' Inequality and Poverty Across Generations 
IMF  Staff  Discussion  Notes 
in 
SDN/18/01  report  that  overall  income  inequality  has  remained 
broadly  stable  in  the  EU  over  the  past  decade  but  disparities  in 
poverty  and  income  inequality  across  generations  have  increased 
markedly. 

the  European  Union', 

(142) See, for instance, Carroll, C., Slacalek, J. and  K. Tokuoka (2014), 
'The  Distribution  of  Wealth  and  the MPC:  Implications  of  New 
European  Data',  The  American  Economic  Review,    Vol.  104,  No.  5, 
pp.  107-111  using    data  for  15  European  countries  from  the 
Household  Finance  and  Consumption  Survey  report 
that 
spending of unemployed  individuals and households earning low 
income    and  holding  little  wealth  is  more  sensitive  to    shocks. 
This may be triggered by the fact that people at the lower end of 
the income distribution are often liquidity and credit constrained.   

Volume 17 No 3 | 35 

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36 | Quarterly Report on the Euro Area 

 Box II.2: Data on factors.The table below summarizes briefly how the structural factors examined in this section have been measured. Only structural factors with sufficient sample size (i.e. covering the 1998-2015 period) are shown. This excludes, for instance, indicators referring to insolvency regime, contract enforcement and the efficiency of the judiciary. Table A:  Indicators  The OECD PMR has three levels of sub-aggregation, i.e. state control (which includes public ownership and Involvement in business operations), barriers to entrepreneurship (which includes complexity of regulatory procedures, administrative burdens on start-ups and regulatory protection of incumbents) as well as barriers to trade and investment (which includes explicit barriers to trade and investment and other barriers to trade and investment). (1) In turn, these sub-indicators can be disaggregated further. Multicollinearity between these indicators and insufficient degrees of freedom may lower the efficiency of the point estimates in the regression analysis.                                                             (1) The OECD product market regulation (PMR) indicators have been published for most OECD countries every 5 years between 1998 and 2013 – for SI, SK as of 2008 and for CY, LT, LV and MT as of 2013. Missing years have been interpolated. Index scale of 0-6 from least to most restrictive. Factor IndicatorSourceFactorIndicatorSourceCOMMON SHOCKStochastic disturbance arising outside the economic system  Own estimatesB. Competition  in banking sectorLerner index A measure of market power in the banking market. It compares output pricing and marginal costs (that is, markup). An increase in the Lerner index indicates a deterioration of the competitive conduct of financial intermediaries. (GFDD_OI_04)     World Bank  retrieved via FRED OTPUT GAPGap between actual and potential gross domestic product at 2010 reference levels (AVGDGP)AMECOIV. STRUCTURAL FACTORSI. PRODUCT MARKETSA. Trade openness(exports + imports) / GDP in current pricesbased on AMECOProdcut Market Regulation (PMR) See text below. Index scale of 0-6 from least to most restrictive.OECDB. Export diversification Hirschman Herfindahl Index It is the sum of squared shares of each product in total export. A country with a perfectly diversified export portfolio will have an index close to zero, whereas a country which exports only one export will have a value of 1 (least diversified).  World Bank Trade IndicatorsII. LABOUR MARKETSC. Employment diversificationSum of squared deviation of sectoral employment share from 1 divided by number of sectorsOwn estimatesA. Employment policies aggregate of items belowD. InequalityGini coefficient of equivalised disposable income - EU-SILC survey [ilc_di12]. Scale form 0 to 100, with 0  perfect equality and 100 perfect inequality.Eurostat-  public employment services (PES)PES and administration - Public expenditure as a percentage of GDPOECD-  employee training Training  - Public expenditure as a percentage of GDPOECDV. MACRO-ECONOMIC CONDITIONS-  start-up incentives for unemployedStart-up incentives  - Public expenditure as a percentage of GDPOECDA. Nominal interest rateNominal short-term interest rates (ISN)(cid:10)AMECO-  out-of-work support Out-of-work income maintenance and support - Public expenditure as a percentage of GDPOECDB. Real effective exchange rateReal effective exchange rates, based on unit labour costs (total economy), Performance relative to the rest of 37 industrial countries: double export weights (XUNRQ). An increase (decrease)refers to an appreciation (depreciation)AMECOB. Employment protection legislation (EPL)Employment protection.  Index scale of 0-6 from least to most restrictive. OECDVI. INSTITUTIONAL QUALITYC. Wage bargaining levelThe predominant level at which wage bargaining takes place.   Ranging from 1 =  predominantly  local or company level to 5 = predominantly central or cross-industry level ICTWSS databaseA. Government EffectivenessReflects perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. The data ranges from approximately -2.5 (weak) to 2.5 (strong) governance performance.World Bank  Worldwide Governance Indicators (WGI) projectD. Wage bargaining coordinationcoordination of wage-setting.  Ranging from 1 = fragmented  to individual firms or plants to 5 = maximum coordination ICTWSS databaseB. Regulatory QualityReflects perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. The data provided ranges from approximately -2.5 (weak) to 2.5 (strong)  performance.World Bank Worldwide Governance Indicators (WGI) projectIII. FINANCIAL MARKETSC. Control of CorruptionReflects perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests.The data provided ranges from approximately -2.5 (weak) to 2.5 (strong)  performance.World Bank Worldwide Governance Indicators (WGI) projectA. Non-performing loansBank nonperforming loans to gross loans (%) Ratio of defaulting loans (payments of interest and principal past due by 90 days or more) to total gross loans (total value of loan portfolio). The loan amount recorded as nonperforming includes the gross value of the loan as recorded on the balance sheet, not just the amount that is overdue. (GFDD_SI_02)World Bank  retrieved via FRED   
 
 
 
 
 
 
 
 
II. Determinants of economic resilience in the euro area: An empirical assessment of policy levers 

II.3.5.  Macro-economic conditions 

II.3.6.   Institutional quality 

also 

affect 

Macro-economic 
the 
conditions 
economy's  absorption  capacity.  First,  the  fiscal 
stance affects an economy's capacity to respond to 
adverse  shocks  in  aggregate  demand.  A  strong 
structural fiscal balance (143) (in combination with a 
sustainable  public  debt  level)  creates  room  for 
counter-cyclical  public  measures  and  automatic 
stabilisers in the case of a temporary shock. (144)  

Second,  the  private  sector  debt  level  may  also 
affect  an  economy's  capacity  to  withstand  shocks 
as  a  high  private  debt  may  not  only  limit  the 
capacity to borrow to smoothen consumption over 
time, but it may also be so high that it pushes the 
private sector into pro-cyclical deleveraging, i.e. the 
so-called balance sheet recession. (145)  

Third,  the  way  changes  in  the  interest  rate  are 
transmitted will also affect the absorption capacity. 
In case of an adverse common shock, interest rates 
would  likely  be  cut (146) but  such  cuts  may  have  a 
different  impact  on  domestic  interest  rates  if 
financial markets are fragmented and the monetary 
transmission channel is impeded.  

Finally,  nominal  and  real  (effective)  exchange  rate 
depreciations  may  create  room  to  increase  net 
exports. However, in a currency union the nominal 
exchange  rate  of  the  common  currency  will 
primarily  respond  to  developments  at  the  level  of 
the  currency  union  as  a  whole.  By  contrast,  real 
effective  exchange  rates  may  respond  to  domestic 
conditions  such  as  nominal  unit  labour  costs  – 
which often show a strong rigidity. (147)  Its impact 
on  economic  resilience  will  then  also  depend  on 
the  economy's  structural  features  such  as  the  size 
of its tradable and non-tradable sectors.  

Several  empirical  studies  report  that  institutional 
quality (148)  has  an  important  impact  on  both 
macro-economic  stability  and  potential  growth. 
(149)  

However,  determining  causality  in  this  context  is 
not  always  clear-cut. (150)  For  instance,  OECD 
(2013)  (151)  argues  that  while  a  strong  correlation 
can  be  found  between  perceived  corruption  and 
output  level,  this  relationship  is  difficult  to  assess 
because  corruption  may  compensate  for 
the 
shortcomings  of  regulatory  systems  that  dampen 
economic growth. 

II.4. An econometric analysis of the absorption 

and recovery capacity: Illustrative results 

II.4.1.  The empirical method 

The empirical analysis in this section is based on an 
unbalanced  data set (152)  that covers more  than  20 
explanatory  variables  as  potential  determinants  of 
resilience  for  a  period  ranging  from  1998  until 
2015.  These  variables  interact  with  the  lagged 
dependent  variable,  i.e.  the  lagged  output  gap,  (to 
identify  determinants  of  recovery  capacity)  as  well 
as 
identify 
determinants of shock absorption capacity) so that 
in principle more than 40 explanatory variables can 
equation 
the 
be 
underpinning  the  empirical  analysis  -  as  described 
in Box II.2. This poses then a problem of degrees 
of freedom and multicollinearity. 

the  common  shock  variable 

regression 

included 

(to 

in 

To deal with these problems the following strategy 
was  implemented.  First,  several  panel  regressions 
were  performed  using  a  prior  beliefs  rooted  in 
economic  theory  to  select  the  relevant  factors 
affecting shock absorption and recovery. However, 
this  approach  has  its  limitation  as  some  indicators 

(143) Measured by AMECO indicator UBLGBP: Net lending (+) or net 
borrowing  (-)  excluding  interest  of  general  government  adjusted 
for the cyclical component: Adjustment based on potential GDP  
(144) However,  for  instance,  Guerini  et  al  (2017),  ‘The  Janus-Faced 
Nature of Debt: Results from a Data-Driven Cointegrated SVAR 
Approach’,  LEM  Papers  Series  2017/04,  argue  that  increases  in 
public debt may crowd-in private investment.  Hijzen et al. (2017), 
op.  cit.,  show  that  automatic  fiscal  stabilisers  contributed  to 
labour market resilience during the Great Recession 

(145) Koo,  R.  (2014),  The  Escape  from  Balance  Sheet  Recession  and 

the QE Trap: A Hazardous Road for the World Economy. 

(146) Provided  monetary  authorities'  room  for  manoeuvre  is  not 

constrained by the zero lower bound. 

(147) For more details on developments in nominal unit labour cost see 
Vanderplas,  A.  (2018),  'Wage  dynamics  in  the  EMU',  Quarterly 
Report on the Euro Area, Vol.. 17, No. 3 

Indicators  which  covers 

(148) Institutional  quality  is  often  measured  by  the  World  Bank 
six  dimensions  of 
Governance 
governance including  regulatory quality, rule of law, and control 
of corruption (which are also part of the subsequent analysis). 
(149) See, for instance, Acemoglu, D., Johnson, S. and J. A. Robinson 
(2005),  ‘Institutions  as  a  Fundamental  Cause  of  Long‐Run 
Growth,’  in:  Aghion,  P.  and  S.  N.  Durlauf  ﴾eds.﴿,  Handbook  of 
Economic Growth, Volume 1A.  

(150) Edward L. Glaeser, E., La Porta, R., Lopez-de-Silanes, F. and A. 
Shleifer (2005), 'Do Institutions Cause Growth?',  NBER Working 
Paper No. 10568 report findings for a reverse causality suggesting 
that growth and human capital accumulation lead to institutional 
improvement and not the other way around. 

(151) See OECD (2013), 'Issues Paper on Corruption and Growth'.  
(152) See Box 2 for more details on data sources. 

Volume 17 No 3 | 37 

 
                                                      
                                                      
indicators  measuring 

may  show  a  strong  degree  of  collinearity  at  their 
lowest level of disaggregation as is the case of the 
product  market 
indicator,  which 
regulation 
includes  at  its  lowest  level  of  disaggregation,  for 
instance, 
administrative 
burdens on corporations, sole proprietor firms and 
in  services  sectors.  Next,  a  Bayesian  model 
averaging (BMA) technique was applied that allows 
identifying  the  most  robust  variables  (in  this  case, 
determinants  of  resilience)  from  a  very  large  pool 
of  potential  factors  based  on  statistical  selection 
criteria  -  as  explained  in  Box  II.3.  This  method 
allows testing even large set of variables at a more 
disaggregated  level  (for  example,  one  can  test  not 
only  the  main  structural  characteristics  of  the 
labour market but numerous fairly detailed features 
thereof)  and  provides  the  ranking  of  relative 
importance of such variables. 

II.4.2.  Factors' impact on resilience  

Stricter  barriers  to  entrepreneurship  affect  both 
dimensions of resilience adversely – albeit at a low 
level  of  significance. (154)  However,  a  further 
disaggregation of this indicator suggests a trade-off 
between  absorption  and  recovery  for  its  different 
components - as reported in Table B. For example, 
the  estimates  suggest  that  stricter  regulation  of 
start-ups is particularly detrimental to the recovery 
but  may  strengthen  the  absorption  capacity  – 
indicating  that  making  it  easier  to  replace  existing 
firms  by  new  firms  may  lower  output  on  impact 
but give a growth impetus during the recovery.  

Graph II.5: Factors affecting absorption 
capacity of common shocks 

in 

(Graph 

resilience, 

II.6)  using 

This  sub-section  aims  at  reporting  on  the  factors 
that have been identified as the most significant in 
terms  of 
explaining  economic 
contribution  to  an  economy's  shock  absorption 
capacity  (Graph  II.5)  and  to  recovery  capacity 
respectively 
the  panel 
regressions  (153)  and  Bayesian  Model  Averaging 
(BMA).  Box  II.3  reports  detailed  results  of  panel 
regression  both  at  aggregated  (Table  A)  and  more 
detailed level of disaggregation for product market 
regulation  and  active  employment  policies  (Table 
B),  and  results  of  BMA  with  ranking  the  most 
relevant  factors  selected  from  the  entire  pool  of 
potential  determinants  (Table  C).  Below,  the 
individual  factors  are  presented  according  to  the 
classification  followed  in  sub-section  II.3,  while 
Box  II.2  describes  how  these  factors  have  been 
measured. 

increased 

Product  markets:  The  estimation  results  suggest 
that 
control  such  as  stronger 
regulation  of  network  industries  and  price  setting 
has  an  unambiguous  negative  impact  on  both  the 
absorption and recovery capacity.  

state 

(1) Estimates based on variant V5 of Table B in Box II.3, and 
evaluated 
2008-2014. 
(2) The  scale on the Y-axis  measures the ppt.  change  in the 
output gap. 
Source: Authors' estimates. 

period 

the 

for 

The  estimates  suggest  against  expectations  that 
to  trade  and  investment  such  as 
stricter  barriers 
differential  treatment  of  foreign  suppliers  and 
barriers  to  FDI (155)  may  weaken  the  impact  of  a 
common  shock  and  speed  up  the  recovery. 
Although  the  former  effect  does  not  show  a  high 
level  of  significance, 
to  be 
interpreted with care as the effects of trade barriers 
on economic resilience, like on growth (156), are not 

this  finding 

is 

(154) Interpreting  the  point  estimates  in  Table  3  of  Box  II.3  it  should 
be  remembered  that  the  OECD  product  market  regulation 
indicators  have  a  scale  form  0  to  6,  i.e.  from  least  to  most 
restrictive.   

(155) More  specifically,  such  regulation  refers  to  less  favourable  tax 
treatment  of 
in  public 
procurement  as  well  as  special  government  rights  in  the  case  of 
acquisition  of  equity  by  foreign  investors.  For  more  details,  see 
Koske, I. et al. (2015), op cit. 

suppliers,  discrimination 

foreign 

(156) See  Rodrik,  D.  and  Rodriguez,  F  (1999)  'Trade  Policy  and 
Economic  Growth:  A  Skeptic’s  Guide  to  the  Cross-National 
Evidence',  NBER  Working  Paper  No.  7081,  the  authors  warn 

(153) For  each  of  the  factors  shown  in  this  and  the  following  graphs, 
the  impact  on  the  absorption  and  recovery  is  estimated  by 
multiplying the point estimate (of variant V5 in Table B of Box 2) 
with  the  2008-2014  sample  average.  In  this  unbalanced  dataset 
some  years  may  be  missing  for  some  countries  when  estimating 
the  average.  For  instance,  the  Lerner  index  measuring  bank 
completion  is  not  available  for IE  and  FI  as  of  2011.  In case  of 
missing data, the average is calculated over the available data. 

38 | Quarterly Report on the Euro Area 

-0.3-0.2-0.100.10.20.30.4Highervalue  =weaker absorption  
 
                                                      
 
                                                      
 
II. Determinants of economic resilience in the euro area: An empirical assessment of policy levers 

inclusion  probability)  in  terms  of  reducing  the 
impact of a shock. (160) 

Graph II.6: Factors affecting recovery 
capacity from common shocks 

straightforward. One  interpretation  could  be  that 
during shock absorption, low barriers to FDI may 
intensify  competition  and  make  FDI  more 
responsive  to  local  economic  conditions,  thereby 
amplifying the impact of a shock. For the recovery 
phase,  the  estimated  dampening  effect  of  lower 
barriers 
reflect 
is  more  puzzling  and  may 
econometric  issues.  (157)  Furthermore,  while  a 
differential  treatment  of  foreign  suppliers  may 
speed up the recovery as it favours local suppliers it 
has  also  negative  feedback  on  potential  output 
the  efficient 
it  adversely  affects 
growth  as 
allocation  of  resources  across  the  euro  area  and 
limits  recovery  via  exports.  In  any  case,  this 
ambiguous  finding  on  the  impact  of  barriers  in 
trade  and  investment  on  economic  resilience  calls 
for further research.  

Labour  markets:  The  estimation  results  show 
only  a  limited  impact  of  employment  policies  on 
both  shock  absorption  and  on  the  recovery.  The 
estimates  suggest  that  employment  protection  legislation 
and  active  labour  market  policies  have  only  a  small 
impact on the economy's absorption and recovery 
capacity while research reported elsewhere suggests 
that  spending  on  active  labour  market  policies 
responding  strongly 
in 
unemployment  may  promote  a  quick  return  to 
work  in  the  recovery.  (158) The  analysis  applied  in 
this  section,  which  focusses  mainly  on  aggregated 
variables, seems to be less suited to capture the rich 
dynamics  of  active  labour market  policies targeted 
at  specific  groups  of  workers,  such  as  long-term 
and  youth  unemployed. (159)  However,  the  BMA 
analysis reveals that detailed features of the labour 
and 
markets,  namely  out-of-work 
employee training rank high (in terms of posterior 

to  cyclical 

increases 

support 

against  expecting  an  unambiguous  relationship  between  trade 
openness and growth. 

(157) Such  as  a  lack  of  variability  of  these  indicators  over  time  and 

missing variables. 

(158) For instance, OECD (2017), 'Chapter 2. Labour market resilience: 
The  role  of  structural  and    macroeconomic  policies'  in  OECD 
Employment  Outlook  2017,  reports  that  after  one  year,  an 
increase  in  active  labour  market  spending  of  1%  of  GDP  would 
reduce  the  unemployment  rate  by  almost  2  percentage  points 
compared  with  less  than  half  a  percentage  point  for  public 
spending overall. 

(159) For  instance,  the  components  of  labour  market  policies  such  as 
training,  public  employment  services  and  out-of-work  support 
show  a  low  significance.  This  low  level  of  significance  may  be 
triggered  by  multicollinearity  between 
the  disaggregated 
components  of  labour  market  policies  (that  move  in  tandem)  as 
well  as  by  the  use  of  instrumental  variables.  This  calls  then  for 
analysis at more disaggregated level  – which is beyond the scope 
of this section.   

(1) Estimates based on variant V5 of Table B in Box II.3, and 
evaluated 
2008-2014. 
(2) The scale on the Y-axis measures the ppt. contribution of 
a specific factor to the total recovery speed.  
Source: Authors' estimates. 

period 

the 

for 

Financial markets: The estimates for the financial 
sector  support  the  hypothesis  that  an  increases  in 
the share of non-performing loans in total gross loans 
(161) and a weakening in the banking sector competition 
(162)  affect  negatively  an  economy's  absorption  as 
well as recovery capacity. 

Structural  factors:  The  estimation  results  show 
that sectoral diversity in domestic production had a rather 
small impact on resilience during the sample period 
considered in this section. However, diversification 
in  exports  or  its  corollary  –  international  trade 
specialisation - has an opposite significant effect on 
the  capacity  to  absorb shocks  and  on the  capacity 
to  recover.  The  econometric  results  suggest  that 
stronger  specialisation  (in  terms  of  products)  in 
exports  strengthens  the  capacity  to  absorb  a 
common  shock,  but  weakens  the  capacity  to 
recover.  Indeed,  specialisation  allows  for  a  better 
exploitation  of  comparative  advantages  and 

(160) However,  such  ranking  does  not  give  an  indication  of  its  total 
impact  on  absorption  or  recovery  -  which  is  equal  to  the  point 
estimate multiplied with the value of the variable. 

(161) Covering defaulting loans with payments of interest and principal 

past due by 90 days or more. 

(162) As  measured  by  the  Lerner  index  measuring  the  difference 
between  output  prices  and  marginal  costs.  An  increase  in  the 
Lerner index indicates a deterioration of the competitive conduct 
See 
of 
https://fred.stlouisfed.org/tags/series?t=lerner+index%3Bworld
+bank. 

intermediaries. 

financial 

Volume 17 No 3 | 39 

-0.3-0.2-0.100.10.20.3Higher value =  slower recovery  
                                                                                 
 
                                                      
capacity significantly, but it weakens the absorption 
capacity  –  which  may  suggest  that  with  an 
ineffective  administration  zombie  firms  remain 
longer in business which lowers the impact of the 
shock,  but  slows  down  the  recovery.  The  BMA 
results  confirm  that  good  governance  which 
includes  quality  of  public  and  civil  services,  and 
independence  from  political  pressures,  as  well  as 
the 
and 
policy 
implementation ranks high among the factors that 
speed-up  the  recovery.  This  suggests  that  broad 
institutional  characteristics  of  a  country  can 
determine its capacity to withstand adverse shocks 
alongside the structural characteristics of economic 
nature.  

formulation 

quality 

of 

II.4.3.  Member States' performance 

Member  States'  overall  shock  absorption  and 
recovery  capacities  are  represented  in  Graph  II.7 
and Graph II.8 respectively. 

Graph II.7  shows  Member  States'  overall  capacity 
to absorb a common shock – which combines the 
impact  of  all  individual  factors  in  a  country. 
Member  States  recording  a  high  value  for  this 
parameter  will  experience  a  stronger  output  loss 
when hit by a common shock than Member Sates 
recording a low value.  

Graph II.7: Shock absorption capacity in 
case of common shock 

(1) Estimates based on variant V5 of Table B in Box II.3, and 
2008-2014. 
evaluated 
(2) The  scale on the Y-axis  measures the ppt.  change  in the 
output gap. 
Source: Authors' estimates. 

period 

the 

for 

economies of scale, which in turn creates room to 
lower prices. As such, when export markets are hit 
by a common shock it would be easier to offset the 
decrease  in  external  demand  by  price  adjustments 
when  exports  are  specialised.  By  contrast,  during 
the 
recovery  when  all  export  markets  are 
rebounding,  opportunities  for  exports  increase 
because overall demand increases. In other  words, 
during the absorption period the estimation results 
suggest that it is price effects that affect exports (so 
that  specialisation  matters),  while  in  the  recovery 
period  it  is  scale  effects  (so  that  specialisation  is 
less 
in  a  context  of 
disintegration  of  the  value  chain  across  countries, 
an  export  specialisation  (in  terms  of  products) 
could also confer an advantage in case of common 
shocks,  based  on  the  position  in  the  value  chain. 
The  parts  of  the  value  chains  that  are  less 
substitutable  (for 
is  so 
countries 
technologically 
produce them) would therefore be less sensitive to 
common shocks. (163)  

instance  a  part  that 
that 

important).  Besides, 

complex 

few 

The economy's openness to international trade also seems 
to  have  an  opposite  impact  on  shock  absorption 
and on the recovery capacity, which also confirmed 
by the BMA analysis. In case of a common shock 
the  openness  of  the  economy  will  amplify  the 
impact  of  the  shock  (i.e.  weaken  the  absorption) 
because  the  shock  does  not  only  affect  adversely 
the  domestic  market  but  also 
the  export 
markets. (164)  Such  adverse  outcomes  may  then  be 
tempered  by  policies  and  reforms  that  strengthen 
the  economy's  absorption  capacity, 
including 
through  prudent 
fiscal  policies  and  better 
functioning  automatic  fiscal  stabilisers  as  well  as 
through  a  well-functioning  Banking  Union  and 
Capital Markets Union which increase risk-sharing. 
However,  stronger  openness  as  well  as  a  more 
diversified  export  portfolio  may  speed-up  the 
recovery. (165)  

Finally, in terms of institutional quality, the estimates 
from  the  panel  regression,  suggest  that  good 
governance  strengthens  the  economy's  recovery 

(163) See for instance Timmer M., Los B., Stehrer R. and G. De Vries 
(2013)  'Rethinking  competitiveness:  The  global  value  chain 
revolution', VoxEU. 

(164) Important  to  note  that  the  latter  adverse  mechanism  would  not 

occur in case of a country-specific shock. 

(165) Here it should be remembered that while diversification improves 
the absorption capacity it limits a country's potential to specialise 
in  those  goods  and  services  it  has  a  comparative  advantage, 
suggesting  a  trade-off  between  stability  and  potential  growth.  In 
turn, stability may increase the incentives to invest and innovate, 
which increases potential growth. 

40 | Quarterly Report on the Euro Area 

00.20.40.60.811.2atfidefrnlptitesbeieluHigher value = weaker absorption  
 
                                                      
 
 
II. Determinants of economic resilience in the euro area: An empirical assessment of policy levers 

Graph II.8: Recovery capacity in case of 
common shock 

disaggregated level the impact of individual factors 
on resilience.  

Nevertheless,  some  results  suggest  that  further 
empirical  research  is  needed.  For  instance,  the 
reduced  form  macro-econometric  approach  is  less 
suited to capture the rich dynamics between active 
labour  market  policies  that  support  the  most 
vulnerable  workers  and  the  economy's  capacity  to 
withstand  shocks.  Nor  is  it  well  suited  to  capture 
the impact of labour market dualism on resilience. 

If  Member  States  of  the  euro  area  display  similar 
performances  in  terms  of  the  absorption  and 
recovery  from  common  shocks  then  common 
policy  tools such  as  the  common  monetary  policy 
become  more  effective.  Such  convergence  would 
not  only  provide  stronger  stability  in  terms  of 
income  and  employment,  but 
it  would  also 
strengthen  the  long  term  growth  potential  as  it 
limits hysteresis effects linked to, for instance, long 
unemployment  spells  and  the  underutilisation  and 
underinvestment of capital. 

The  empirical  analysis  highlighted  that  there  are 
notable  differences  among  the  euro  area  Member 
States  (for  which  sufficient  data  are  available)  in 
terms of both absorption and recovery capacity.  It 
also  showed  that  performances  in  terms  of  these 
two capacities are not necessarily fully in sync with 
each  other.    For  example,  the  panel  regression 
results  suggest  that  in  case  of  a  common  shock 
strong openness to international trade weakens the 
absorption  capacity  as  export  markets  are  also 
adversely  affected  by  the  common  shock;  but  it 
may  induce  a  faster  recovery  due  to  the  same 
strong openness to international trade. 

Such  findings  suggest  then  that  the  economies 
more  open  to  international  trade  should  pursue 
more  vigorously  policies  and 
that 
strengthen  the  economy's  absorption  capacity, 
including through prudent fiscal policies and better 
functioning  automatic  fiscal  stabilisers  as  well  as 
through  a  well-functioning  Banking  Union  and 
Capital Markets Union which increase risk-sharing.  

reforms 

While  Member  States  may  be  hit  by  common 
shocks that are beyond their control, it is primarily 
within  Member  States  that  reforms  to  foster 
convergence 
resilient  economic  structures 
should start.   

to 

At  national 
level,  a  well-functioning  business 
environment  has  a  key  role  to  play  to  promote 

Volume 17 No 3 | 41 

(1) (1) Estimates based on variant V5 of Table B in Box II.3, 
and 
2008-2014. 
(2) The scale on the Y-axis measures total recovery speed. 
Source: Authors' estimates.  

evaluated 

period 

the 

for 

The  chart  suggests  that  Luxembourg  experienced 
the strongest impact when hit by a common shock. 
In the case of Luxembourg, this reflects to a large 
extent  its  strong  openness  to  international  trade 
and  the  fact  that  a  common  shock  not  only 
adversely  affects  its  domestic  market  but  also  its 
export  markets.  Ireland  also  recorded  a  weak 
absorption capacity for a common shock but here 
it  was  primarily  a  combination  of  trade  openness 
and  relative  high  level  of  non-performing  loans. 
Austria  and  Finland  showed  a  strong  absorption 
capacity for common shocks reflecting partly their 
weaker 
trade  openness  and  relative  stronger 
exports specialisation. 

Graph  II.8  shows  Member  States'  overall  capacity 
to  recover  from  a  shock.  While  Luxembourg  has 
the weakest capacity to absorb a common shock, it 
has the strongest capacity to recover – this is to a 
large extent due to its strong openness to trade. By 
contrast  while  Portugal  does  withstand  common 
shocks  better  than  several  other  Member  States  it 
requires  more  time  to  recover  –  as  its  lower 
openness to international trade limits the impact of 
the  common shock  but makes  it  more  difficult  to 
recover. 

II.5. Conclusions and policy implications 

This section investigated the empirical significance 
of a selected set of structural factors that affect the 
euro  area  economies'  capacity  to  absorb  and 
recover from a common shock. Its value added is 
that  it  is  a  first  attempt  to  assess  at  a  more 

00.10.20.30.40.50.60.70.80.91ludeatitfinlbefrieesptHigher value = slower recovery 
 
for 

that 

calls 

foster 

streamlining 

economic  resilience.  More  specifically,  creating 
environments 
entrepreneurship 
increases  the  ability  to  adapt  and  recover  from 
exogenous  shocks.  The  administrative  burdens  on 
startups are particularly detrimental to the recovery, 
which 
administrative 
procedures  for  start-ups  in  countries  that  are  still 
performing  badly  on  this.  Price  controls  both 
amplify shocks and slow down the recovery. Even 
so, increases in the share of non-performing loans 
in total gross loans and a weakening of competition 
the  banking  sector  affect  negatively  an 
in 
economy's absorption as well as recovery capacity. 
But as the euro area economies are interconnected, 
there  are  some  spillover  effects 
justify 
complementarities  between  the  EU  and  national 
policies to increase economic resilience. 

that 

shock-absorption 

Some EU policy priorities have a direct impact on 
significant  drivers  of 
and 
recovery.  The  policy  levers  are  no  longer  only 
purely  national.  Namely,  the  measures  aimed  at 
improving the functioning of the Single Market in 
areas  such  as  the  regulation  of  network  industries 
shall  also  positively  affect  the  recovery  capacity. 
Another  dimension  of  the  Single  Market,  which 
particularly  affects  the  amplification  of  shocks,  is 
the financial system. The EU non-performing loans 
reduction  package  (March  2018)  and  diverse 
proposals  of  the  Capital  Market  Union  represent 
initiatives  that  strengthen  resilience  of  the  EU 
financial systems, and consequently have a positive 
impact  on  macroeconomic  resilience  of  the  EU, 
the euro area and individual Member States. 

42 | Quarterly Report on the Euro Area 

  
 
II. Determinants of economic resilience in the euro area: An empirical assessment of policy levers 

(Continued on the next page) 

Volume 17 No 3 | 43 

 Box II.3: Econometric results.Staring from the specification discussed in Box II.1, the reference regression (labelled V1 in Table A) is specified in terms of aggregate factors including the indicator measuring total product market regulation, employment protection legislation and labour market policies, non-performing loans and competition in the banking sector, openness to international trade, export diversification and diversification of production.  Several variants of this reference regression have been estimated. First, the interaction between factors and the nature of the shock is further explored (Tale A), next the aggregate indicators are further disaggregated (Table B and C).  This stepwise approach is dictated by concerns of multicollinearity and lack of degrees of freedom when too many explanatory variables would be included in an equation. As such, due regard should be given to possible omitted variables biases interpreting the estimation results of each of the variants.  I. Panel regression results  Table A below shows a selected set of estimation results for an unbalanced sample covering the 1998-2015 period for euro area Member States for which sufficient data are available as well as a selected group of non-euro EU Member States. (1)   Table A:  Panel regression – Interaction variants                                                             (1) I.e. BE, DE, IE, ES, FR, IT, LU, NL, AT, PT, FI, CZ, DK, HU, PL, SE and UK. For the other euro area Member States the data on product market regulation did not cover a sufficient long period; some EL data on labour market policies not available.  Dependent variable : Output gapV1V2V3V4V1V2V3V4BaseShock asymmetryRecovery asymmetryFactors sample averageBaseShock asymmetryRecovery asymmetryFactors sample averageFactorsShock (absorption) lagged output gap (recovery) 0.01 0.05 0.02 0.05 *** 0.63 *** 0.74 *** 1.17 *** 1.12 ***( 0.36)( 1.58)( 0.76)( 2.91)( 4.04)( 3.89)( 4.80)( 7.09)I. Product markets- Product Market Regulation (PMR)  0.11 ** 0.24 *** 0.11 ** 0.07 0.04 0.05-0.14 * 0.05( 2.30)( 2.63)( 2.04)( 0.99)( 0.68)( 0.75)(-1.75)( 0.71)II. Labour markets- Employment policies 0.00-0.00 * 0.00 *** 0.00 ***-0.00 ***-0.00 **-0.00 ***-0.00 ***( 1.62)(-1.73)( 2.63)( 2.70)(-4.51)(-2.26)(-4.78)(-6.77)- Employment protection legislation (EPL) 0.05 ** 0.04 0.06 ** 0.03-0.03-0.05-0.04-0.11 ***( 2.02)( 0.87)( 2.13)( 0.81)(-1.04)(-1.62)(-0.84)(-3.21)III. Financial markets- Non-performing loans 0.01 *** 0.01 0.01 0.02 *** 0.01 ** 0.00 0.01 **-0.01( 3.31)( 1.35)( 1.56)( 3.38)( 2.57)( 0.92)( 2.07)(-1.06)- Bank competition  (Lerner) 0.56 *** 0.32 0.60 *** 0.90 *** 0.34 *** 0.30 **-0.13-0.23  (high value for low competition) ( 4.32)( 1.56)( 4.37)( 3.26)( 3.04)( 2.26)(-0.66)(-0.98)IV. Structural Factors A  Trade openness 0.24 *** 0.49 *** 0.25 *** 0.22 ***-0.19 ***-0.21 *** 0.04-0.35 ***( 13.31)( 5.04)( 10.04)( 6.20)(-6.93)(-6.34)( 0.41)(-8.81)B. Export diversification -3.21 ***-3.14 ***-3.44 ***-3.47 *** 2.19 *** 2.44 *** 1.56 * 4.85 ***   (Hirschman Herfindahl Index, 0 to 1, with 1  least diversified)(-7.48)(-3.93)(-7.38)(-4.98)( 4.38)( 3.70)( 1.81)( 6.87)C. Employment diversification 0.89-3.33 0.68 0.90 0.22-0.38-3.18 *-2.43 **( 1.01)(-1.34)( 0.75)( 0.81)( 0.20)(-0.29)(-1.72)(-2.34)Correction for negative shock (use of slope dummy)Shock (absorption) lagged output gap (recovery)-0.04-1.00 ***(-0.66)(-2.78)- Product Market Regulation (PMR) -0.24 ** 0.45 ***(-2.10)( 3.80)- Employment policies 0.00 *** 0.00 **( 2.83)( 2.06)- Employment protection legislation (EPL) 0.06 0.01( 1.07)( 0.16)- Non-performing loans 0.00-0.01( 0.30)(-1.01)- Bank competition  (Lerner) 0.56 0.66 **  (high value for low competition) ( 1.65)( 2.53)- Trade openness-0.27 ***-0.19 *(-2.63)(-1.88)- Export diversification -1.00-0.11   (Hirschman Herfindahl Index, 0 to 1, with 1  least diversified)(-0.89)(-0.09)- Employment diversification 4.81 * 4.76 *( 1.75)( 1.73)V. Macro-economic conditions A. Short-term interest rate-0.31 ***-0.36 ***-0.38 ***-0.35 ***(-6.47)(-6.47)(-7.11)(-9.24)B. Nominal effective exchange rate 0.16-0.11 0.64-1.46( 0.17)(-0.10)( 0.63)(-1.54)Diagnostic statisticsNumber of observations 232 232 232 232Number of explanatory variables 20 29 29 20Adjusted R-squared 0.848859 0.853605 0.856770 0.855470Durbin-Watson 1.63 1.72 1.69 1.75Note: slope dummy = 1 if negative shock, =0 if positive shock. Mutiplying the slope dummy with the explanatory variable provides an asymmetric response .Shock asymmetry: only asymmetric resposne for  absorption; recovery assymmetry: only asymmetric resposne for recovery.  ABSORPTION (interaction with shock)RECOVERY (interaction with lagged output gap) 
 
 
 
 
 
Box (continued) 

44 | Quarterly Report on the Euro Area 

(Continued on the next page) 

 Focussing on variant V1 of Table A, as explained in the main text, most of the point estimates have the expected sign.  While this variant assumes a symmetric impact of the factors for a negative as well as positive common shock, variant V2 in Table A allows for an asymmetric impact – making use of slope dummies. (2) Comparing these regression results, suggests, for instance, that stricter product market regulation and stronger openness to international trade improves the absorption capacity when the economy is hit by a negative common shock. (3) Variant V3 shows regression results assuming asymmetry in the recovery which suggests, for instance, that stricter product market regulation delays the recovery.  (4)  Variant V4 shows point estimates for time-invariant interactions whereby the reference regression (V1) is re-estimated setting the structural factors equal to their sample average. Except for the diversification of the employment composition the qualitative nature of the estimates does not change.   Table B provides some evidence on further disaggregation of the aggregates in variant V1 of Table A. A further disaggregation of the product market regulation indicator shows that some of its components show some significance (see Variant V5 in Table B). This is especially the case for state control (which includes price regulation and regulation of network industries) which shows a positive point estimate for its interaction with the lagged output gap indicating that stronger state control slows down the recovery. Nevertheless, the indicator related to barriers to trade which includes barriers to FDI and different treatment of foreign suppliers, shows a significant negative sign suggesting that stricter regulation in this field would speed up recovery.  At an even stronger level of disaggregation, Variant V6 in Table 1 shows that looking at the detail of barriers to entrepreneurship the complexity of regulatory procedures has a significant negative impact of absorption capacity, while the administrative burdens on start-ups significantly slows down the recovery. Nevertheless, a high administrative burden also tempers the absorption capacity. The latter may indicate that as it takes more time to get non-profitable firms out of business, this may temporarily support employment and thus also aggregate demand. A further disaggregation of the barriers to trade and investment (variant V7), confirm also that a differential treatment of foreign suppliers strengthen the shock absorption potential. Finally, further disaggregating of the state control dimension (variant V8) suggests significant adverse impact of price control on absorption and recovery capacity, while stricter regulation of network industries shows a negative adverse impact on the absorption capacity.  The impact of non-performing loans and lack of competition in the banking sector (5) is significant for both the absorption and recovery capacity: a deterioration in these variables significantly amplifies the impact of the shock and significantly delays recovery.  (6)   Employment protection legislation (EPL) has a significant impact on the absorption capacity in most variants, but does not show any significant interaction with the recovery capacity. Moreover, while variants 6 to 8 suggest that labour market polices as a whole have a significant impact on the absorption and recovery capacity, Variant V9 suggests that a further disaggregation of labour market policies does not show significance except for public employment services that speed up the recovery. (7)  The positive sign of the point estimate of the openness to international trade interacting with the common shock suggests that stronger openness amplifies the impact of the common shock, as a common shock not only adversely affects the domestic market but also export markets.   The negative sign of the point estimate of the interaction between openness to international trade and the lagged output gap shows that a stronger openness to international trade speeds up recovery, as it allows the economy to gain more from a recovery in its export markets. (8) The negative value of the point estimate of the interaction between the diversity of                                                            (2) The slope dummy = 1 if negative shock and =0 if positive shock.  (3) In order to save on the degrees of freedom, two variants with a slope dummy were estimated separately, i.e. V2 with slope dummy interacting with factors affecting the absorption, and V3 with slope dummy interacting with factors affecting the recovery.  (4) A similar asymmetric result for PMR is for instance also reported in Duval and Vogel (2007), op cit. (5) As measured by the Lerner indicator which is equal to he difference between output prices and marginal costs (relative to prices). (6) Here it should be remembered that there may be reverse causality, in the sense that a deep downturn may generate an increase in non-performing loans, while in turn this increase may adversely affect the recovery. Reverse causality may also arise for the measure of bank competition as a deep downturn in combination with a financial crisis may affect bank competition. Such potential reverse causality has been addressed using instrumental variables. (7) Such result may be due to multi-collinearity between the factors. (8) Estimating how trade openness would affect the absorption of a country-specific shock would be beyond the scope of this section.   
 
 
 
 
 
II. Determinants of economic resilience in the euro area: An empirical assessment of policy levers 

Box (continued) 

(Continued on the next page) 

Volume 17 No 3 | 45 

 exports and the common shock suggests that less diversification lowers the impact of a common shock. However, a more diversified export market increases the recovery speed.  Table B: Panel regression – Disaggregation variants Finally, the point estimates suggest that nominal interest rates tempered the size of output gap significantly, but no significant impact of changes in the real effective exchange rate was found. (9)   II. BMA results  Table 2 below shows results of the variable selection by means of the Bayesian model averaging (BMA) as described in Box II.1. As the BMA routine (10) requires balanced sample, the sample in Table 1 was balanced using linear interpolation.                                                                (9) Additional estimates not shown in Table B suggest that increases in income inequality significantly weakens both absorption and recovery capacity. Good governance strengthens the economy's recovery capacity significantly, but it weakens the absorption capacity - the latter suggesting that with an ineffective administration zombie firms remain longer in business which lowers the impact of the shock, but slows down the recovery. (10) The estimation was performed by BMS package described in Zeugner, S. and M. Feldkircher (2015), 'Bayesian Model Averaging Employing Fixed and Flexible Priors: The BMS Package for R', Journal of Statistical Software, Vol. 68, No. 4, pp. 1-37. Dependent variable: output gapV5V6V7V8V9V5V6V7V8V9 PMR disaggregated Entrepreneurship barriers disaggregatedTrade and investment barriers disaggregatedState control barriers disaggregatedLabour market  policies disaggregated PMR disaggregated Entrepreneurship barriers disaggregatedTrade and investment barriers disaggregatedState control barriers disaggregatedLabour market  policies disaggregatedShock (absorption)  lagged output gap (recovery)-0.02-0.03-0.02-0.03 0.02 0.42 ** 0.25 0.47 ** 0.37 ** 0.68 ***(-1.01)(-1.35)(-0.67)(-1.28)( 0.85)( 2.14)( 1.26)( 2.26)( 1.98)( 4.20)I. PRODUCT MARKETSProdcut Market Regulation (PMR) - aggregate 0.11 ** 0.03  (Index scale of 0-6 from least to most restrictive)( 2.04)( 0.57)A. Barriers to entrepreneurship (aggregate) 0.07 0.03 0.03 0.07 0.07 0.06( 1.45)( 0.55)( 0.55)( 1.40)( 1.24)( 1.29)-  Administrative burdens on startups-0.11 *** 0.23 ***(-2.93)( 6.81)-  Complexity of regulatory procedures 0.09 ***-0.01( 4.55)(-0.57)-  Regulatory protection of incumbents-0.11 *-0.04(-1.70)(-0.63) B. Barriers to trade and investment (aggregate)-0.07-0.11 **-0.08-0.53 ***-0.40 ***-0.46 ***  (Index scale of 0-6 from least to most restrictive)(-1.43)(-2.10)(-1.37)(-7.20)(-5.37)(-6.10)- Differential treatment of foreign suppliers-0.46 ***-0.25 *(-3.86)(-1.79)-barriers to FDI and other barriers 0.06-0.24 ***( 1.50)(-5.49)C. State control (aggregate) 0.08 * 0.20 *** 0.16 *** 0.12 **-0.01 0.10 *  (Index scale of 0-6 from least to most restrictive)( 1.70)( 3.12)( 3.12)( 2.36)(-0.24)( 1.79)- price control 0.04 * 0.08 ***( 1.91)( 3.19)- network industries 0.05 *** 0.02( 2.86)( 0.71)II. LABOUR MARKETS A. Employment policies - aggregate 0.00 *** 0.00 *** 0.00 *** 0.00 ***-0.00 ***-0.00 ***-0.00 **-0.00 **( 2.89)( 4.70)( 3.20)( 3.20)(-3.03)(-4.78)(-2.23)(-1.97)-  public employment services (PES) 0.00-0.00 ***( 1.10)(-3.45)-  employee training  0.00 0.00( 0.56)( 1.34)-  start-up incentives for unemployed-0.00 0.01 **(-0.06)( 2.00)-  out-of-work support -0.00-0.00(-0.16)B. Employment protection legislation (EPL) 0.03 0.06 *-0.05 0.06 ** 0.05 *-0.02-0.02-0.02 0.01-0.03( 1.06)( 1.74)(-1.17)( 2.22)( 1.95)(-0.54)(-0.58)(-0.64)( 0.41)(-1.29)III. FINANCIAL MARKETS A. Non-performing loans 0.01 ** 0.01 *** 0.01 0.01 ** 0.01 *** 0.01 * 0.01 ** 0.01 ** 0.01 * 0.00( 2.44)( 3.31)( 1.17)( 2.33)( 3.10)( 1.94)( 2.08)( 2.34)( 1.93)( 1.43)B.  bank competition  (Lerner) 0.64 *** 0.20 0.49 *** 0.73 *** 0.55 *** 0.34 *** 0.10 0.28 ** 0.41 *** 0.35 ***  (high value for low competition) ( 4.90)( 1.35)( 3.71)( 5.26)( 3.61)( 2.69)( 0.82)( 2.22)( 2.86)( 2.89)IV. STRUCTURAL FACTORS A. Trade openness 0.23 *** 0.19 *** 0.19 *** 0.24 *** 0.24 ***-0.21 ***-0.17 ***-0.22 ***-0.18 ***-0.20 ***( 8.64)( 6.31)( 6.36)( 9.70)( 13.55)(-6.32)(-4.98)(-5.72)(-5.37)(-7.41) B. Export diversification -2.80 ***-1.47 ***-1.46 **-3.41 ***-3.28 *** 2.96 *** 2.00 *** 3.24 *** 1.99 *** 2.55 ***   (Hirschman Herfindahl Index, 0 to 1, with 1  least diversified)(-5.35)(-2.81)(-2.21)(-6.46)(-7.00)( 5.35)( 3.31)( 4.84)( 3.01)( 4.72) C. Employment diversification-0.12 0.12 1.17 0.51 0.55 0.73 3.48 ** 0.81 2.03-0.14V. MACRO-ECONOMIC CONDITIONSA. Nominal interest rate-0.38 ***-0.35 ***-0.36 ***-0.40 ***-0.37 ***(-8.59)(-8.99)(-8.22)(-7.85)(-6.79)B. Real effective exchange rate-0.31-0.78 0.15 0.17-0.10(-0.32)(-0.87)( 0.14)( 0.17)(-0.10)Adjusted R-squared 0.857984 0.869837 0.860613 0.861976 0.852311Durbin-Watson 1.66 1.76 1.67 1.64 1.66Number of observations 232 232 232 232 232Number of explanatory variables 24 28 26 26 26ABSORPTION (interaction with shock)RECOVERY (interaction with lagged output gap) 
 
 
 
 
Box (continued) 

46 | Quarterly Report on the Euro Area 

 The BMA allows for variable ranking by means of their posterior inclusion probability (PIP). PIP captures the extent to which one can assess how robustly a potential explanatory variable is associated with the dependent variable (output gap). Variables with a high PIP can be considered robust determinants of the dependent variable. Hence, BMA is employed to detect the robust determinants of resilience from the list of 40 potential ones. The variables are all those included in the panel regression in Table B plus several additional, typically more disaggregated, variables. In order to include the largest possible set of variables, the BMA selection is performed separately for absorption and for recovery phase. Out of these 40 variables for each phase, Table C shows only those where PIP was higher than 0.1 and considered as robust those with PIP higher than 0.2 (these are discussed below). The post mean (SD) is the mean (standard deviation) of the estimated coefficients averaged over all models (this includes models where the variables was not included, the coefficient is zero in this case).  The results feature several variables that were included in Table B but also a few additional ones (majority of the variables has the expected sign). The negative coefficient of the short-term interest rate suggests that accommodative monetary policy have decisive role when economy is hit by the shock and it needed to speed up the recovery. Employment diversification has at first sight counter-intuitive positive sign (i.e. the higher diversification, the higher impact of shock and the slower recovery). Whereas employment diversification could strengthen resilience in general, at the same time it limits country's opportunities to specialize in those activities where it has a comparative advantage. This second effect seems to clearly dominate here. The trade openness has different impact in each phase. Whereas it slows down the shock absorption, it speeds up the recovery. This suggests that in case of common shock, the more open economies are more affected as their trading partners are affected as well. However, in the mid-term more open economy can rely on export as additional sources of recovery. The absorption phase is further facilitated by specific features of exports, namely by high export market penetration (11) and specialization of exports. On the contrary, it is hindered by high levels of public debt, which prevents more active used of fiscal policy. The recovery in turn facilitated by several variables representing state involvement in the economy. Namely, while quality of regulation speeds up the recovery, the state control of economy slows it down. Interestingly, the public ownership (which is a subcomponent of the state control variable) speeds-up the recovery. Finally, a notable difference with the panel regression is that the BMA ranks high out-of-work support and training during absorption.  Table C: Bayesian model averaging                                                               (11) Export Market Penetration measures the share of the actual number of export relationships (at the country product level) in the maximum possible number of export relationships a country can form given the number of its exports. A low value indicates potential for expansion. AbsorptionPIPPOSTmeanPostSDRecoveryPIPPOSTmeanPostSDST interest rate0.94-0.040.01Regulatory Quality0.34-0.100.14Export market penetration0.75-0.010.01ST interest rate0.24-0.010.01Specialisation of exports0.70-2.972.23Employment diversification0.230.050.80Employment diversification0.560.940.94Public ownership0.21-0.040.08Trade openness0.210.040.09State control0.210.070.14Public debt0.200.000.00Product market regulation (PMR)0.190.080.19Out-of-work support0.12-0.010.04Start-up incentives for unemployed 0.190.250.55Employee training 0.12-0.050.16Trade openness0.18-0.020.05Gini - disposable income 0.100.000.01Governance0.13-0.030.08Bank competition0.120.070.22% change REER0.110.060.21Corruption 0.10-0.010.05Note: PIP is post-inclusion probability indicating that the variable belongs to the true model. Post-mean (SD) is the average estimated coefficient (standard deviation) across the models.Lagged output gap and shock showed high PIP, both should be understood as technical variables  covering variables not included in analysis.   
 
 
 
 
 
 
 
 
 
III. Assessing Prudent NIIP and Current Account 
Positions 

This  chapter  presents  prudential  benchmarks  or  reference  values  for  the  net  international  investment 
position  (NIIP)  in  order  to  help  assess  external  sustainability.  The  results  suggest  that  while  stock 
imbalances persist in some EU countries,  external sustainability risks continue to abate. The empirical 
findings  also  demonstrate  that  the  NIIP  outperforms  other  stock  indicators  for  assessing  external 
sustainability. Moreover, the results suggest that low-income countries face external sustainability risks 
at  ‘less  negative’  NIIP  levels  than  richer  countries.  An  application  to  EU  countries  illustrates  the 
resulting  country-specific  prudential  benchmarks  for  the  headline  NIIP  and  its  debt  component,  which 
can complement the Commission's macroeconomic surveillance toolbox. 

In the EU, several net debtor countries still have legacy NIIPs that surpass prudential benchmarks. But 
the  balanced  current  accounts  in  most  of  these  çountries  imply  that  they  are  on  track  to  return  their 
NIIPs  to  prudent  levels  by  the  mid-2020s.  In  contrast,  EU  creditor  countries  do  not  run  external 
sustainability risks. Yet they continue to run current account surpluses that exceed the level required to 
stabilise their NIIPs at current levels. (166)    

III.1. 

Introduction  

cases.  Nonetheless,  net 

Current account imbalances have shifted since 
the  great  recession,  but  stock  imbalances 
persist  in  Europe.  The  large  current  account 
deficits  recorded  before  2010  have  corrected  in 
international 
most 
investment  positions  (NIIPs)  remain  large  and 
negative  in  a  number  of  countries.  The  NIIP 
measures  the  aggregate  difference  between  total 
foreign assets and liabilities held by all sectors in an 
economy.  These wide NIIP imbalances have been 
an  important  factor  in  the  balance-of-payments 
adjustments  since  2007,  as  they  reflect 
large 
in  debtor 
private-  and  public-sector 
countries.  By  ca.  2015,  these  debtor  countries  had 
weathered  their  sudden  stops  and  stabilised  their 
stock  imbalances;  and  balance-of-payments  risks 
continue  to  abate  since.  The  question  remains, 
though, where these stocks will, and should evolve 
to. Is current account adjustment on the right track 
for  debtor  countries,  or  should  they  run  higher 
surpluses?  

liabilities 

In  contrast  to  current  accounts,  the  academic 
literature provides little guidance for assessing 
NIIPs.  The  bulk  of  it  focuses  on  the  extent  to 
which  a  negative  NIIP  can  be  considered  risky  in 
view of sudden stops. Early warning approaches to 
assess  external  sustainability  have  a  relatively  long 

(166) The  section  was  prepared  by  Stefan  Zeugner.  This  work  was 
developed  in  the  context  of  the  Economic  Policy  Committee 
(EPC). The author wishes to thank Anton Jevčák, as well as EPC 
Members, for useful comments. 

tradition, (167)  but  only  with  more  recent  data 
advances  have  net  foreign  assets,  and the  NIIP  in 
particular,  emerged  as  a  possible  early-warning 
indicator.  Authors  such  as  Catão  and  Milesi-
Ferretti  (2014)  suggest  prudential  lower-bound 
thresholds for NIIPs, beyond which countries may 
face significant external sustainability risks. (168) Via 
its MIP scoreboard, the Commission is among the 
few  policy  institutions  that  apply  a  quantitative 
'alert threshold' for the NIIP at -35% of GDP. (169)  

This  chapter  proposes  a  methodology  for 
estimating 
prudential 
country-specific 
benchmark  values  for  indicators  of  external 
sustainability, with emphasis on the NIIP. The 
prudential benchmark indicates from what level of 
the  indicator,  a  closer  look  at  external  sector 
developments  may  be  warranted.  Although 
conceptually  simple, the  results  are broadly  in  line 
with those from earlier research on the subject, and 
outperform  more  complicated  risk  indicators  such 
as  short-term  debt  liabilities.  The  benchmarks  are 
made  country-specific  by  taking  into  account  the 
capita.  Debt-equity 
country’s 
per 
composition,  however, 
important 
qualifier.  

is  also  an 

income 

(167) For instance, Kaminsky, G., S. Lizondo, and C. Reinhart, (1998), 
Leading  indicators  of  currency  crises,  IMF  Staff  Papers,  45(1), 
1-48. 

(168) Catão,  L.A.V.,  and  G.M.  Milesi-Ferretti 

(2014),  "External 
liabilities  and  crises",  Journal  of  International  Economics  94(1), 
18-32. 

(169) The  NIIP  is  one  of  14  macroeconomic  indicators  in  the 
Scoreboard  for  the  Macroeconomic  Imbalance  Procedure.  The 
alert threshold for the NIIP derives from the first quartile over a 
sample  for  EU  countries  1995-2007.  See  also  European 
Commission 
surveillance  of 
(2012):  Scoreboard 
macroeconomic imbalances, Occasional paper 92.  

the 

for 

Volume 17 No 3 | 47 

 
                                                      
                                                      
that 

Prudential  NIIP  benchmarks  complement  the 
Commission's  macroeconomic  assessment 
toolbox,  but  do  not  replace  tested  approaches 
the  MIP  scoreboard.  The  prudential 
like 
benchmarks  are  one  among  several  new  external 
benchmarks  to  complement  the  Commission's 
analytical  and  qualitative  reviews  of  NIIP  and 
the 
current  account  balances.(170)  Note 
concept of an NIIP prudential benchmark focuses 
on  the  prudential  aspect  of  external  sustainability. 
It  is  thus  inherently  one-sided,  as  it  denotes  an 
NIIP  below  a  certain  value  as  potentially 
"unsustainable"  from  a  debtor’s  perspective.  The 
Commission is currently also working on two-sided 
benchmarks  for  assessing  NIIPs  that  can  be 
relevant  for  both  debtors  and  creditors.  Together, 
benchmarks 
these 
the 
stock 
Commission's 
tools  for  external  sustainability 
assessment,  but  do  not  replace  the  existing  set  of 
external  indicators,  most  notably  the  ones  used  in 
the economic reading of the MIP scoreboard.  

complement 

a 

"required  current 

Country-specific  NIIP  benchmarks  directly 
imply  the  current  account  required  to  reach 
them.  Such 
account" 
benchmark can widen the array of macroeconomic 
analysis  tools  employed 
in  the  Commission's 
macroeconomic surveillance. For countries with an 
NIIP  below  the  prudential  benchmark,  the  latter 
can  be  interpreted  as  a  target  level  that  directly 
implies what current account balance is needed to 
converge  towards  it.  For  countries  that  are  safely 
above the benchmark, external sustainability is of a 
lesser concern, and there is little academic research 
on  where  their  NIIPs  should  converge  to.  The 
the 
most  common  approach 
Commission,  and  the  IMF)  is  to  compute  the 
current  account  balance  that  would  allow  such 
countries to stabilise their NIIPs over the medium 
account" 
"required 
term. (171)  The 
illustrated  in  this  chapter  combines  these  two 
concepts, and denotes the current account required 
to 
the  prudential 
benchmark over the medium-to-long term. 

the  NIIP  above 

(as  used  by 

stabilise 

current 

Gauging  from  the  data,  although  EU  stock 
imbalances  remain  pronounced,  most  debtor 
countries are on track to reach the benchmark 
until  the  mid-2020s.  The  NIIPs  of  several  EU 
countries  remain  too  negative.  However,  most  of 
them  now  run  current  account  surpluses  that 
should allow them to bring their NIIPs to the more 
prudent  levels  within  ten  years.  In  contrast,  most 
'surplus countries' display an NIIP that is strongly 
positive,  with  their  surpluses  contributing  to 
further  increase  their  net  foreign  asset  positions. 
Finally, a few core euro area countries run current 
account balances that are likely to keep their NIIPs 
at moderate levels.  

III.2.  Prudential benchmarks for the NIIP  

The purpose of this approach is to identify an 
NIIP  level  that  signals  external  sustainability 
concerns.  The  benchmark consists  of  a  reference 
value  for  the  NIIP  signalling  that  external  debt 
could  be  excessive.   The  benchmark  can  be 
constructed on the basis of the signalling approach, 
i.e.,  screening  indicators  for  levels  that  can  be 
associated  with  episodes  of  macroeconomic 
instability. 

for 

(as, 

e.g., 

approaches 

The  choice  of  the  prudential  benchmark  is 
based on its signalling power. Following similar 
univariate 
the 
Commission's  S0  indicator (172)),  the  benchmark 
for  each  indicator  is  the  one  that  maximises  its 
"signal  power".  The  optimal  benchmark  value 
should  signal  external  sustainability  concerns 
without  triggering  excessive  false  concerns.  The 
data sample comprises 66 advanced economies and 
emerging economies for the period 1980-2015.(173) 

The  method  can  be  used  to  validate  the 
choices  made  in  the  MIP  scoreboard.  The 
method identifies an unconditional benchmark for 
the  NIIP  at  -25%  of  GDP,  which  is  close  to  the 
indicative threshold from the MIP scoreboard.(174) 
Table  1  shows  that  the  NIIP  has  a  fairly  good 
signal power as an external sustainability indicator, 

(170) These  indicators  have  been  developed  within  a  workstream  on 
stock imbalances, in the LIME Working Group of the Economic 
Policy  Committee  (EPC),  and  found  broad  support  from  EPC 
Members in 2017. 

(171) For  a  Commission  approach,  see  Salto  and  Turrini  (2010, 
"Comparing  alternative  methodologies  for  real  exchange  rate 
assessment";  European  Economy  -  Economic  Papers  427. 
 For a summary of the IMF approach see Phillips, S., L. Catão, L. 
Ricci, R. Bems, M. Das, J. Di Giovanni, D.F. Unsal, M. Castillo, J. 
Lee,  J.  Rodriguez  and  M.  Vargas  (2013),  "The  external  balance 
assessment (EBA) methodology", IMF Working Paper 13/272. 

(172) Berti,  K.,  M.  Salto  and  M.  Lequien  (2012),  "An  early-detection 
index  of  fiscal  stress  for  EU  countries",  European  Economy, 
Economic Paper 475. 

(173) External episodes are identified according to the methodology of 
Catão  and  Milesi-Ferretti  (2014),  which  define  such  episodes  as 
those  with  large  use  of  IMF  resources  and/or  a  “D”  rating  by 
Standard&Poors. 

(174) The  estimation  is  based  on  an  algorithm  that  guarantees  the 
identification of a global maximum for the signal power despite a 
multiplicity of local maxima. 

48 | Quarterly Report on the Euro Area 

  
 
                                                      
                                                      
III. Assessing Prudent NIIP and Current Account Positions 

compared  to  the  alternatives  in  the  Table,  and 
provides  a  balanced  compromise  between  alerting 
to  potential  problems  without  excessively  raising 
concerns. (175)  Moreover,  NIIP 
unjustified 
benchmarks appear to be fairly robust to the choice 
of  the  estimation  sample,  with  estimates  lying 
between -9% and -43% of GDP for a large set of 
possible samples. (176)  

Table III.1: Benchmarks for gauging 
sustainability risk 

investment 
deposits. 

(OI)  mainly  holds 

loans  and 

  NIIP – FDI: Stripping out net direct investment 
from the NIIP leaves "Net Pf. + OI debt", plus 
portfolio  equity  shares  and  mutual  funds, 
reserves and financial derivatives. 

  NENDI:  "NIIP  excluding  non-defaultable 
instruments" is defined here as NIIP minus net 
direct  investment  and  net  portfolio  shares. 
NENDI  thus  comprises  "Net Pf.  + OI debt", 
plus  reserves,  financial  derivatives,  and  mutual 
funds (see below for further detail) 

  Net  ST  debt:  net  short-term  debt  comprises  all 
"Net 

components 

debt 

of 

short-term 
Pf. + OI debt".  

(1)  The  event  sample  used  (dependent  variable)  includes 
elevated risk episodes as  defined in Catão and Milesi-Ferretti 
(2014),  for  66  countries,  1980-2015.  'Benchmark'  denotes 
the  optimal  benchmark  that  maximises  the  signal  power. 
'Signal  power'=1-prob(false  alerts)-prob(missed  episodes). 
'% missed episodes' = share of episodes starts that have not 
total  episode  starts.  
ratio  of 
been  signalled,  as  a 
'% false alerts'  =  share  of  “no  extreme  event”  observations 
that  have  been  wrongly  signalled  as  an  external  episode. 
'# episodes'= number of observations in the sample where an 
episode  starts.  This  compares  to 
'no  extreme  event' 
observations  totalling  between  1750  and  1850  per  indicator. 
The  assessment  of  benchmark  uncertainty  is  based  on  500 
random  draws  with each case omitting 20%  of the countries 
in  the  sample.  'St.dev.  benchmark'  denotes  the  standard 
deviation  of  the  benchmark  over  these  500  random  draws, 
and  thus  illustrates  the  uncertainty  regarding  the  threshold 
estimation for a particular indicator. 'AUROC' is a commonly-
used  statistic  to  assess  an  indicator’s  signalling  quality 
irrespective  of  where  the  benchmark  is  set.  The  closer  the 
AUROC is to one, the better the indicator’s signalling quality.  
Source: Author's estimates. 

for 

An  important  question,  though,  is  whether 
there are indicators that have more information 
content 
external 
sustainability problems than the NIIP. For this 
purpose,  Table III.1  tests  several  other  external 
stock indicators alongside the NIIP. These are (all 
as % of GDP):  

alerting 

against 

  Net Pf.+ OI debt:  Net  portfolio  investment  debt 
(Pf.)  comprises  debt  securities,  while  net  other 

(175) In contrast, the MIP threshold of -35% of GDP was not based on 
a  signalling  exercise,  but  merely  reflects  the  first  quartile  of  EU 
NIIPs between 1995 and 2007.  

(176) This  is  the  confidence  interval  determined  on  the  basis  of  two 
times  the  standard  deviation  of  all  benchmarks  obtained  from 
random perturbations on the sample. The range -45 to -22 results 
from  adding  +/-  two  times  'St.dev.  Threshold'  to  'Threshold'  in 
Table IV.1. 

  ST  debt  liab:  Gross  short-term  (portfolio  and 
other  investment)  debt  liabilities,  i.e.  the  gross 
equivalent 
"Net 
corresponding 
Pf. + OI debt". 

to 

  Debt  liab:  Gross  debt  liabilities,  which  are  the 

counterpart to "Net Pf. + OI debt" 

In  addition,  III.1  comprises  several  interaction 
terms: 

  NIIP/income:  NIIP  divided  by  relative  income 

per capita (see below) 

  NENDI/income:  NENDI  divided  by  relative 

income per capita (see below) 

  NIIP/VIX: NIIP divided by the VIX index that 

proxies global financial risk aversion 

  NENDI/income/VIX: interaction term between 

NENDI/income and the VIX index 

  NENDI/trade  openness:  Higher  trade  openness 
entails  a  higher  ratio  of  current  account 
volatility  to  GDP  volatility,  and  thus  enables 
faster NENDI and NIIP changes.  

The NIIP can be usefully complemented by a 
comparable  indicator  focusing  on  net  debt, 
the  NIIP  excluding  non-defaultable 
namely 
the  headline 
(NENDI).  Among 
instruments 
indicators,  NENDI  is  the  only  one  that  slightly 
outperforms  the  signal  power  of  the  NIIP.  The 
NENDI strips out direct investment and portfolio 

Volume 17 No 3 | 49 

BenchmarkSignal Power% false alerts% missed episode starts# episodesSt.dev.  BenchmarkAUROCNIIP-250.340.220.454680.72NENDI-160.390.200.414640.73NIIP/income-830.480.180.354590.77NENDI/income-780.550.290.164540.79NIIP - FDI120.110.280.614670.49Net Pf.+OI debt-290.310.330.364650.69Net ST debt-830.140.000.8671140.50ST debt liab120.230.150.6113400.58Debt liab250.100.040.8646110.52Reserves60.230.390.384620.63NIIP/VIX-550.390.430.1928130.74NIIP/imports-1310.410.330.2646260.77 
 
 
 
                                                      
shares  from  the  NIIP,  and  thus  comprises  purely 
arms-length  debt,  as  well  as  any  other  component 
that may theoretically be subject to default, such as 
insurance,  mutual  funds,  and  derivatives.  The 
NENDI benchmark is somewhat smaller than the 
NIIP,  although  they  are  not  significantly  different 
from each other. This implies that an NIIP beyond 
-35%  spells  an  elevated  risk,  but  this  risk  is 
stronger if NENDI is also beyond -15% of GDP.  

of  particular  relevance  whether  both  NIIP  and 
NENDI  exceed  their  reference  values  or  not. 
Table III.2  shows  that  in  the  majority  of  external 
the 
episodes,  both 
benchmark.  There  have  been  occasions  when  in 
“normal”  times  both  indicators  exceeded  their 
benchmarks,  but  these  times  typically  preceded 
external  sustainability  concerns,  arising  within  5-
years.  

indicators  were  beyond 

than 

Country-specific benchmarks for the NIIP are 
indicators  of  external  sustainability 
better 
concerns.  The  one-size-fits-all  benchmarks  of 
roughly -35% for NIIP and -15% for NENDI are 
unlikely  to  be  the  most  efficient  reference  values 
for  rich  and  developing  countries  alike,  since  the 
financing  capacity  of  an  EU  country  is  typically 
higher 
that  of  an  emerging  economy. 
Graph III.1  shows  that  for  countries  with  higher 
income per capita, external episodes occur at more 
negative  NIIP  levels  than  they  do  for  poorer 
countries. Conversely, Graph III.1 also shows that 
many  richer  countries  did  not  experience  any 
sustainability  concerns  despite  of  NIIPs  beyond  -
35%  of  GDP  for  a  long  period.  Consequently, 
Table III.1 also explores the benchmarks that arise 
when  the  NIIP  and  NENDI  are  conditional  on 
income per capita. (177) Indeed, the signal power of 
the  such-adjusted  NIIP  and  NENDI  exceeds  that 
of  all  other  indicators  and  conceivable  interaction 
terms.  

When conditional on income per-capita, NIIP 
prudential  reference  values  vary  considerably 
across EU countries. For the aggregate euro area, 
the benchmark lies at -70% of GDP, while for the 
richest  EU  countries,  it  lies  considerably  beyond 
that  level.  For  the  EU  countries  with  the  lowest 
per-capita income, the benchmark is closer to -30% 
of GDP.  

The only alternative indicator with comparable 
signal  power 
income-adjusted  NENDI, 
which mostly represents net debt. (178) It is thus 

is 

(177) More  precisely,  "NIIP/income"  divides  the  NIIP  by  the  relative 
income indicator used by the IMF as in Phillips et al. (2013). This 
indicator  is  defined  as  GDP  in  PPP  divided  by  the  number  of 
working-age  (15-64)  persons,  normalised  by  the  arithmetic  mean 
of the same indicator for Germany, Japan and the US. I.e., relative 
income  of  100%  means  income  per  capita  equal  to  the  average 
over  those  three  countries.  Under  this  measure,  the  relative 
income of the aggregate euro area is at 70%.  

(178) Interestingly, the benchmarks for both are fairly close and do not 
differ  significantly  (for  the euro  area  aggregate,  they  are  at  -70% 
for  the  income-adjusted  NIIP  and  -66%  for  income-adjusted 

50 | Quarterly Report on the Euro Area 

Table III.2: Combined signal power of 
income-adjusted NIIP and NENDI 

(1)  Left  column  shows  external  episodes  based  on  the 
definition  by  Catão  and  Milesi-Ferretti  (2014),  for  66 
countries,  1980-2015.  Right  column  refers  to  "normal" 
observations.  For  each  column,  percentages  denote  in  how 
many  cases  income-adjusted  NIIP  and/or  income-adjusted 
NENDI  were  beyond  the  NIIP/income  benchmark  from 
Table IV.1. 
Source: Author's estimates.  

A  number  of  additional  robustness  checks 
confirm 
income-adjusted  NIIP 
benchmarks  perform  better  than  most  other 
indicators, and are relatively robust: 

that 

  Robustness to alternative event definitions: In addition 
to external sector stress, the same indicators are 
also  tested  for  fiscal  stress,  as  well  as  elevated 
risks  in  banking  sectors  and  foreign  currency 
markets. (179)  The 
income-adjusted  NIIP 
benchmark  shows  less  signal  power  for  these 
alternative definitions, but still exceed the signal 
power  of 
alternative  balance-of-payments 
indicators.  

  Alternative 

signal 

definition 

power:  The 
of 
benchmarks  for  income-adjusted  NIIP  (and 
NENDI) would not change by more than 15 pp 
of  GDP  if  one  were  to  moderately  alter  the 
importance given to the 'missed events' vs. 'false 
alert' probabilities. 

NENDI, respectively). In this respect, a single benchmark can be 
used for assessing both the NIIP and the NENDI. 

(179) Fiscal stress refers to the data set used in Berti, K., M. Salto and 
M.  Lequien  (2012),  "An  early-detection  index  of  fiscal  stress  for 
EU  countries",  European  Economy,  Economic  Paper  475. 
Currency  events  stem  from  the  dataset  by  Laeven  L.,  and  F. 
Valencia (2012), "Systemic Banking Crises Database: An Update", 
IMF Working Paper 12/163. 

% of external episodes% of "normal" observationsBoth indicators beyond threshold60%14%Only NENDI/income beyond threshold0%1%Only NIIP/income beyond threshold20%22%Both indicators within threshold20%63%  
 
                                                      
 
 
 
 
                                                                                 
III. Assessing Prudent NIIP and Current Account Positions 

  Overall, the results compare well with what 
has  been  found  in  recent  literature.  In 
particular,  the  results  corroborate  the  findings 
of Catão and Miles-Ferretti (2014), which stress 
the importance of relative income, as well as the 
debt-equity composition, in both univariate and 
multivariate approaches. (180)  

III.3.  The required current account 

current 

'required' 

The  prudential  NIIP  levels  can  be  seen  as 
target  values  that  imply  what  current  account 
is  necessary  to  reach  them.  Computing  such 
target-derived 
account 
benchmarks  is  conceptually  straightforward.  In 
general, the NIIP at the end of a year  t (𝑁𝐼𝐼𝑃𝑡) is 
given  by  the  previous  year's  level  (𝑁𝐼𝐼𝑃𝑡−1),  plus 
the  current  account  balance  (𝐶𝐴𝑡),  the  capital 
account  balance  (𝐾𝐴𝑡),  and  other  changes.  The 
other  changes (𝑂𝑇𝐻𝑡)  comprise  valuation  changes 
and  some  statistical  effects,  which  tend  to  be 
unpredictable 
the 
world. (181)For the computation of required current 
accounts,  such  other  changes  are  thus  disregarded 
and 𝑂𝑇𝐻𝑡set to zero. 

countries  of 

for  most 

𝑁𝐼𝐼𝑃𝑡 = 𝑁𝐼𝐼𝑃𝑡−1 + 𝐶𝐴𝑡 + 𝐾𝐴𝑡 + 𝑂𝑇𝐻𝑡 

The  capital  account  balance  must  be  taken 
into  account  in  the  analysis  of  EU  countries, 
mostly  due  to  the  structural  funds.  The  capital 
account  balance  is  usually  very  close  to  zero  for 
most  countries,  although  values  beyond  +/-  1  pp 
of  GDP  may  occasionally  be  recorded.  There  is 
one  important  exception,  though:  Within  the  EU, 
several Member States are important net recipients 
of  structural  funds.  This  concerns  in  particular 

(180) The signal power of NENDI/income in Table  is only moderately 
lower their more complicated approach, although one has to note 
that  the  Catão  and  Milesi-Ferretti  (2014)  approach  excludes 
'outliers'  such  as  Ireland,  Luxembourg,  and  Iceland,  whereas  the 
estimates  in  Table  IV.1  do  not.  Note  that  the  benchmarks  for 
NIIP/income and NENDI/income do not significantly change if 
Ireland,  Luxembourg,  or  Ireland  are  excluded  from  the  sample. 
The  relatively  low  standard  deviation  of  these  indicators  over 
sample variations ("St.dev. threshold") illustrates this feature. 
(181) Recent contributions point to predictable valuation effects for the 
US  and  countries  with  largely  dollarised  assets  and/or  liabilities, 
but  not  for  EU  countries.  Cf.  Gourinchas,  P.  O.,  &  Rey,  H. 
(2013).  External  adjustment,  global  imbalances  and  valuation 
effects, NBER working paper 19240. However, several corporate 
financial centres within the EU have displayed protracted negative 
valuation effects for some periods. In particular this concerns the 
Netherlands, where it may be related to share buybacks – see also 
Eggelte,  J.,  R.  Hillibrand,  T.  Kooiman,  and  G.  Schotten  (2014), 
"Getting  to  the  bottom  of  the  Dutch  savings  surplus",  DNB 
Occasional Studies 12(6), De Nederlandsche Bank. 

Member States that joined after 2003, which mostly 
display  persistent  capital  account  surpluses  in 
excess  of  1  pp.  of  GDP.  This  'structural'  capital 
account  surplus  therefore  has  to  be  taken  into 
the  required  current 
account  for  computing 
account  balance.  Consequently, 
required 
the 
current  account  balance  can  be  defined  as  the 
average current account to GDP ratio 𝑐𝑎    that will 
reach  target  NIIP  to  GDP  ratio  T  years  ahead 
𝑛𝑖𝑖𝑝t+T,  based  on  the  current  𝑛𝑖𝑖𝑝t,  expected 
average nominal growth p.a. g, a 'structural' capital 
account  balance  𝑘𝑎    ,  and  a  structural  valuation 
effect  𝑜𝑡ℎ       that  is  expected  to  be  zero.  Given  an 
NIIP target value 𝑛𝑖𝑖𝑝t+T, the computation of the 
current  account  required  to  reach  it  (𝑐𝑎   )  is  thus 
straightforward. 

  𝑐𝑎    = (𝑛𝑖𝑖𝑝t+T −

𝑛𝑖𝑖𝑝t
(1+𝑔)𝑇)

g (1+g)
1−1 (1+g)𝑇

⁄
⁄

− 𝑘𝑎     − 𝑜𝑡ℎ      

A  remaining  question  is  over  what  timeframe 
such  an  NIIP  target  should  be  reached. 
Individual  country  characteristics  determine  when, 
and if, NIIPs should or will surpass its benchmark. 
For the purpose of cross-country comparisons, the 
objective  is  not  to  find  the  optimum  time  frame, 
but  rather  the  'typical'  time  period  for  such  NIIP 
adjustments. The required current account to reach 
the  benchmark  within  a  'typical'  timeframe  allows 
for  gauging  whether  a  country's  current  account 
reflects fast or slow adjustment. There is, however, 
scant  literature  on  the  evolution  of  NIIPs  during 
external adjustment episodes, and no papers with a 
focus  on  the  length  of  the  adjustment  timeframe. 
Fidora,  Schmitz  and  Tcheng  (2017)  identify  stable 
NIIP  adjustment  episodes  be  relatively  uniformly 
distributed  between  2  and  7  years,  with  a  median 
length  of  4.3  years  for  advanced  countries. (182)  In 
many  cases,  this  adjustment  mostly  commences 
near  the  middle  of  intensive  external  episodes, 
which  according  to  the  Catão  and  Milesi-Ferretti 
(2014)  definition  last  mostly  between  2  and  11 
years, with a median of five years. Ding, Schule and 
Sun (2014)  point  out  16  persistent  NIIP 
adjustments 
that 
commenced between 2 years prior and 3 years after 
the start of an external episode (with a median of 1 

episodes, 

external 

after 

(182) Fidora M., M. Schmitz, and C. Tcheng (2017), Reducing large net 
foreign liabilities, ECB working paper 2074. Note, however, that 
NIIP adjustments mostly start only several years after the start of 
an external episode. During the early periods NIIPs as % of GDP 
often  worsen,  as  GDP  declines,  and  current  account  deficits  are 
slow to adjust.  

Volume 17 No 3 | 51 

 
                                                      
                                                      
Graph III.1: External vulnerability episodes, NIIP and NENDI vs relative income. 

(1)  Large  red  labels  denote  episodes  based  on  the  definition  by  Catão  and  Milesi-Ferretti,  2011).  Small  red  labels  denote 
observations  four  years  prior  to  an  episode.  Grey  labels  denote  “normal”  observations.  NENDI  is  defined  NIIP  as  %  of  GDP, 
minus net FDI and portfolio equity shares. Income per capita is defined as in Phillips et al. (2013) as PPP income per working-
age  person,  expressed  as  %  of  the  arithmetic  average  of  Germany,  Japan,  and  the  US.  Data  sample:  available  data  for  66 
countries 1980-2015, corresponding to 2118 observations for NIIP, and 2107 observations for NENDI.   
Source:  Author's estimates. 

Comparing the gaps to prudential benchmarks 
also  suggests  NIIP  adjustments  focusing  on 
the  period  between  2  and  9  years  after  an 
episode.  Graph  III.2,  (right  panel)  shows  the 
distribution  of 
the  gap  between  NIIP  and 
benchmark.  Nine  years  after  an  episode,  the 
distribution  of  these  gaps  resembles  the  pre-
episode  distribution.  This  suggests  that  NIIPs 
typically  require  roughly  a  decade  to  recover.  Yet, 
note  that  a  quarter  of  the  successful  adjustment 
countries  in  Graph  III.2  did  not  display  an  NIIP 
above  the  prudential  benchmark  for  years  past 
such  an  event.  The  distributions  in  Graph  III.2 
cover  episodes  from  advanced  and  emerging 
countries,  with  various  exchange  rate  regimes. 
There are not enough observations from advanced 
economies 
robust  conclusions  on 
adjustment  time  in  an  EU  or  euro  area  context. 
Overall, 
for  NIIP 
adjustment  can  thus  be  assumed  as  ten  years  or 
less, although longer time periods are not unusual.  

timeframe 

to  draw 

'typical' 

the 

year),  and  lasted  between  7  and  20  years  (with  a 
median of 10). 

Graph III.3  shows  how  NIIPs  behaved  in 
successful adjustment episodes. (183) Nine years 
after  an  episode,  the  median  country  returns  its 
NIIP to the same position as five years prior to the 
episode,  both  in  absolute  and  "prudential  gap" 
terms.  While  not  all  countries  saw  sustained  NIIP 
increases  after  such  an  episode,  the  box  plots  in 
Graph  III.2  show  that  they  did  on  average.  For 
more  than  ¾  of  the  episodes  examined,  the  NIIP 
declined more than 13 pp of GDP in the five years 
prior to the event. At the time of the episode, 80% 
of  the  countries  in  the  sample  had  NIIPs  beyond 
the prudential benchmark.  During the initial years 
following  such  an  episode,  most  NIIPs  remain 
stable  at  low  levels,  while  after  4  years,  the 
distribution  widens.    Nine  years  past,  the  median 
country  has  returned  its  NIIP  to  the  event  level, 
although there remains a quarter of cases in which 
the NIIP is at least as negative as during the such 
an episode.  

(183) The  distributions  in  Graph  IV.2  cover  40  external  episodes  for 
countries  with  successful  adjustment.  Here  'successful'  denotes 
external  episodes  that  were  not  followed  by  another  external 
episode for a decade.  

52 | Quarterly Report on the Euro Area 

  
 
                                                      
 
 
III. Assessing Prudent NIIP and Current Account Positions 

Graph III.2: NIIP before and after  the start of an external episode 

(1) Left and right panel depict NIIP minus reference value for the 5 years leading up to, and the 15 years following, the start of 
an external episode as defined as in Catão and Milesi-Ferretti (2014). Distribution only displays 40 non-repeated episodes i.e., 
those not followed by another one within ten years. Left panel shows NIIP minus the NIIP at the time of the event. Right panel 
shows NIIP minus concurrent prudential benchmark. Dots denote maximum and minimum observation in each year. Light blue 
box denotes the range between the second quartile and the median, dark blue box the range between the median and the third 
quartile. Border between boxes denotes median. 'Whiskers' represent the 5% to 95% interval. 
Source:   Author's estimates.   

In  view  of  a  roughly  ten-year  timeframe  for 
NIIP adjustment, the following four "required 
current account" benchmarks are considered: 

indicator  should  provide  the 

Current  account  required  to  stabilise  the  NIIP  (rCAs): 
This 
'structural' 
current  account  that  is  required  to  stabilise  the 
long  term.  The 
NIIP  over  the  medium  to 
Commission's  regularly  updated  "T+10"  forecasts 
provide nominal GDP projections ten years ahead. 
Based  on  these  income  projections,  and  assuming 
stable capital account balances, the NIIP-stabilising 
current 
a 
can  be 
straightforward manner (see equation above). (184)  

computed 

account 

in 

Current  account  required  to  halve  prudential  gap  in  ten 
years  (rCAp20):  For  countries  with  NIIPs  beyond 
the  prudential  benchmark, 
the 
average  current  account  balance  (as  %  of  GDP) 
required  to  halve  the  distance  between  current 

this  provides 

level 

is  subject 

NIIP  and  the  benchmark  within  ten  years. (185) 
While the discussion above suggests a shorter time 
frame,  an  analogy  with  the  Commission's  S1 
indicator for fiscal debt would suggest a time frame 
of  15  years  to  reach  the  benchmark.  Yet  the 
benchmark  NIIP 
to  some 
estimation  uncertainty,  thus  it  could  be  deemed 
appropriate if a country's NIIPs tends towards the 
vicinity of the benchmark within those 15 years. In 
view of these considerations, the rCAp20 used here 
is  defined  as  the  average  current  account  balance 
(as % of GDP) required to halve the gap between 
headline  and  the  prudential  benchmark  within  ten 
years.  Broadly,  this  corresponds  to  the  current 
account  required  to  eliminate  ¾  of  the  prudential 
'gap' within fifteen years.  

(184) Similar  approaches  mostly  focus  on  stabilising  NIIP  a  shorter 
timespan:  For  instance  the  Commission  indicator  introduced  in 
Salto  and  Turrini  (2010)  aims  to  stabilise  the  NIIP  as  %  of 
potential GDP over three years. Yet the crisis has shown that at a 
given  point  in  time,  even  potential  growth  may  not  accurately 
reflect the medium- top long-term income prospects. Such short-
term  changes  matter  in  particular  during  an  external  adjustment 
phase.  In  order  to  smoothen  out  such  short-term  swings,  the 
approach here focuses on ten-year GDP projections. 

(185) The expected benchmark is based on expected relative income ten 
years  ahead,  based  on  the  Commission  T+10  projections,  IMF 
projections  (for  US  and  Japan),  and  UN  population  projections 
(for  working  age  population).  Note,  however,  that  apart  from 
expected  real  GDP  for  the  country  in  question,  these  indicators 
change  slowly,  and  thus  the  expected  benchmark  expected  ten 
years  ahead  for  EU  countries  differs  little  from  the  benchmark 
estimate for 2016. 

Volume 17 No 3 | 53 

-125-100-75-50-250255075-5-3-113579111315Gap between NIIP and prudential threshold, pp of GDPYears (start of episode = 0)NIIP minus prudential threshold-50-250255075-5-3-113579111315NIIPin year t  minus NIIP at start of episode (year 0)Years (start of episode= 0)NIIP minus NIIP at episode start 
                                                      
 
 
                                                      
 
Table III.3: Stock and flow benchmarks as % of GDP, 2016 

% 

as 

All 

for 

2016, 

values 

(1) 
GDP. 
(2) NENDI denotes NIIP minus net FDI and net portfolio equity shares. The 'Prudential NIIP benchmark described above serves 
as a reference value for NIIP and NENDI alike. Headline CA denotes the 2016 current account balance as % of GDP (as reported 
from  national  account  statistics).  'Cycl.  Adj.  CA'  denotes  the  cyclically  corrected  current  account  balance  according  to  the 
Commission  methodology.  'rCAp10'  denotes  the  CA  required  to  reach  the  prudential  benchmark  by  2026  (only  for  countries 
where the NIIP was below the prudential benchmark  in 2016), while rCAp20 displays the CA required to have the gap between 
NIP  and  the  prudential    benchmark    within  10  years.  These  rCA  benchmark  levels  are  based  on  the  Commissions  "T+10" 
nominal output projections, and assume the capital account balance to stay at the median level observed during 2014-16. 'rCA' 
denotes the maximum over rCAs and rCAp10, ie. the required current account to increase the NIIP towards the benchmark, or 
stabilise it above it, over the next ten years. For reference, 'av. capital acc. bal' displays each country's average capital account  
balance over 2014-16. 
Source: Author's estimates.  

country 

2016 

of 

Current  account  required  to  reach  prudential  benchmark 
(rCAp10):  The  vast  majority  of  countries  that  had 
crossed the prudential benchmark had experienced 
an  external  episode  or  other  external  pressure 
within a decade. The need to reach prudential NIIP 
levels  may  therefore  be  more  pressing  than 
suggested by the twenty-year timeframe above. To 
this  end,  Table  III.3  also  displays  the  current 

54 | Quarterly Report on the Euro Area 

account required to reach the prudential benchmark  
within ten years.  

Required current account: This is a combined indicator. 
For  a  debtor  country  below  the  benchmark,  it  is 
the  current  account 
the 
prudential  benchmark  within  ten  years.  However, 
for  countries  with  a 
'safe'  NIIP  within  the 
benchmark,  this  figure  merely  represents  the 

required 

reach 

to 

NIIPNENDIPrudential NIIP benchmarkHead-line CACycl. adj. CAAv. capital acc.bal. 2014-16rCAs: CA to stabilize NIIP over 10YrCAp20: CA to halve pru. gap in 10YrCAp10: CA to close pru. gap in 10YrCA: higher of rCAs & rCAp10BE4958-781.21.5-0.11.61.6BG-5127-344.25.52.5-3.7-2.9-2.3-2.3CZ-2528-550.31.41.7-1.5-1.5DK5616-818.17.7-0.22.22.2DE5440-818.59.10.01.61.6EE-3720-502.03.51.3-3.6-3.6IE-185-239-1174.78.4-1.9-6.9-3.6-0.4-0.4EL-137-128-46-0.5-4.52.4-5.51.25.95.9ES-86-62-611.91.50.4-2.6-1.4-0.2-0.2FR-16-32-74-2.3-2.50.0-0.5-0.5HR-71-26-372.62.60.7-3.1-1.40.10.1IT-15-15-632.62.40.1-0.2-0.2CY-125-138-54-5.7-4.60.3-4.0-0.13.83.8LV-58-9-431.94.22.6-5.1-5.1-5.1-5.1LT-43-15-48-1.11.02.2-2.3-2.3LU23-3536-1654.74.9-1.50.80.8HU-59-11-455.06.43.1-5.2-4.5-3.9-3.9MT47216-627.913.31.41.01.0NL76-17-877.98.0-1.82.32.3AT5-9-792.12.1-0.20.20.2PL-62-23-440.40.91.8-4.3-4.1-3.8-3.8PT-105-66-480.50.81.1-3.7-0.62.72.7RO-50-8-36-2.4-1.82.0-4.2-4.4-4.2-4.2SI-35-21-537.07.80.2-1.6-1.6SK-58-13-490.20.81.2-3.4-5.2-5.6-3.4FI77-74-1.3-1.90.10.10.1SE17-7-884.95.7-0.10.70.7UK2419-73-4.4-3.8-0.10.90.9  
 
 
 
 
 
III. Assessing Prudent NIIP and Current Account Positions 

current  account  required  to  stabilise  the  NIIP.  
Hence,  it  is  given  by  the  higher  of  rCAs  and 
rCAp10. (186)  

III.4.  Results for EU Member States 

Table III.3  shows  the  2016  NIIPs  for  EU 
Member  States  and  compares  them  with  the 
country-specific  prudential  reference  values. 
The  prudential  benchmarks  for  the  NIIP  are 
similar  to  the  ones  for  the  NIIP  excluding  non-
instruments  (NENDI).  Thus  both 
defaultable 
NIIP and NENDI can be gauged against the single 
country-specific  benchmark 
in  Table 
III.3. 

indicated 

to 

  In  Greece,  Ireland,  Cyprus,  and  Portugal, 
both  NIIP  and  NENDI  exceeded  the 
benchmarks  in  2016,  while  Spain  had  a 
it.(187)  Moreover, 
NENDI  very  close 
Bulgaria,  Latvia,  Lithuania,  Hungary,  Romania, 
Poland  and  Slovakia  display  NIIPs  that  are 
close  to,  or  up  to  20  pp  of  GDP  beyond  the 
benchmark.  However  in  all  these  cases,  FDI 
plays  an  important  role  for  external  liabilities, 
and  NENDI  is  thus  at  least  20  pp.  of  GDP 
narrower than the prudential benchmark. In the 
same vein, Croatia's NIIP remains more than 30 
pp.  beyond  the  benchmark,  but  by  2016  its 
NENDI had already returned to its ‘safe’ side.  

  NIIPs  beyond  the  prudential  benchmark 
are  a  legacy  from  the  pre-2008  period. 
Graph III.3  shows  that  NIIPs  have  actually 
improved  in  most,  but  not  all,  Member  States 
that were close to or beyond the benchmark in 
2010. The improvement was particularly strong 
in  small  and  open  economies.  In  several  larger 
and  more  closed  economies,  the  adjustment 
made  a  longer-lasting  dent  on  nominal  GDP 
growth,  and  partly  therefore  NIIP  as  %  of 
GDP  evolved  less  dynamically.  In  Greece  and 
Cyprus,  a  strong  GDP  decline  combined  with 
more persistent current account deficits led to a 
worsening of the NIIP until 2014/15. Note that 

(186) Note  that  current  account  balances  are  not  directly  under  the 
control of the policy maker. The purpose of the required current 
account is to be a reference value to assess external sustainability, 
not a direct policy target.  

(187) Note  that  the  Cypriot  and  Irish  NIIP  are  subject  to  some 
statistical  effects  stemming  from  the  offshoring  of  aircraft  and 
ships in these countries. Adjusting their NIIPs and NENDIs with 
estimates  of  such  effects  renders  these  indicators  closer  to  the 
benchmark  for  both  countries,  but  does  not  suggest  that  both 
countries are yet safely above it. 

almost all EU countries with financial assistance 
programmes  during  2008-2015  had  a  NENDI 
exceeding  the  benchmark  in  2010. (188)  Several 
other  Central  and  Eastern  European  countries 
also substantially adjusted their current account 
balances and NIIPs in the wake of the financial 
crisis,  though  without  resorting  to  financial 
assistance.  Most  of  the  latter  countries  had 
NIIPs  close  to,  or  beyond  the  benchmark 
before  2010,  but  NENDIs  within 
the 
benchmark's  'safe'  range.  By  2016  already,  the 
NIIP  improvement  in  three  of  these  countries 
(Czech  Republic,  Estonia,  Slovenia)  left  them 
with NIIPs within the benchmark. 

  All  other  EU  Member  States  have  NIIPs 
their 
that  are  40  pp  or  more  above 
the 
prudential  benchmark.  For 
benchmark 
external 
vulnerability over the medium term, even if they 
were to run strong current account deficits.  

suggests 

limited 

them, 

In  cyclically  adjusted  terms,  only  Greece  and 
Cyprus  run  current  accounts  significantly 
below  the  level  that  would  return  the  NIIP  to 
the prudential target within ten years.  Based on 
current  output  projections,  Greece  and  Cyprus 
would  remain  beyond  the  prudential  benchmark 
for more than two decades. Note, however, that i) 
the  extent  of  the  Greek  output  gap  amplifies  any 
methodological  uncertainties  regarding  the  cyclical 
adjustment  of  the  Greek  current  account,  and  ii) 
Cyprus  hosts  a  significant  offshore  sector  that 
affects  the  NIIP,  and  its  current  account.  Apart 
from  Greece  and  Cyprus,  only  Portugal  runs  a 
current  account  that  would  return  the  NIIP  to  its 
prudential  reference  value  between  ten  years  and 
fifteen years. The current accounts of all other net 
debtor Member States, if kept stable, would suffice 
to  reach  the  prudential  benchmark  in  less  than  a 
decade. 

(188) During 2008-2015, the following Member States received financial 
assistance  involving  EU  facilities:  Hungary,  Romania,  Latvia, 
Greece, Ireland, Portugal, Cyprus, as well as Spain (which was not 
subject  to  an  IMF-funded  programme).  Among  these  countries, 
only Romania's NENDI had never crossed the benchmark before 
2008. 

Volume 17 No 3 | 55 

 
                                                      
                                                      
Graph III.3: NIIP change 2010-16, for Member States close to or below the benchmark 

Source: For NIIP, NENDI, and Net equity: Eurostat IIP. Net equity is defined as net direct investment plus net portfolio 
investment  shares.  NIIP  excluding  non-defaultable  instruments  (NENDI)  is  defined  as  NIIP  minus  Net  equity.  The 
benchmark 
Note that this graph excludes Ireland, whose NENDI change 2010-16 considerably exceeds the scale. 

income-adjusted 

country-specific 

benchmark 

Table 

from 

NIIP 

the 

is 

IV.3.   

current 

account  deficits 

the  NIIP-stabilising 

France,  Finland,  and  the  UK  run  cyclically 
that 
adjusted 
undershoot 
current 
account  by  2  pp.  Still,  the  NIIPs  of  these  three 
countries  are  fairly  close  to  balance,  and  thus 
remain  considerably  above  prudential  levels.  Even 
if  current  accounts  persist  at  their  cyclically 
adjusted  deficits  for  France  and  Finland,  both 
countries are not likely to bring their NIIPs in the 
vicinity  of  the  prudential  benchmark  over  the 
medium  term.  The  UK's  deficit  falls  short  of  the 
required current account by more than 3 pp. But its 
gross IIP is characterised by large foreign currency 
assets,  combined  with  a  flexible  exchange  rate 
regime.  This  is  exemplified by  the  2015-16 British 
NIIP  improvement  in  the  wake  of  a  currency 
depreciation.  

All  other  Member  States  run  current  accounts 
that  are 
significantly  above  what  any 
benchmark suggests. By 2016, most Central and 
Eastern  European  Member  States  ran  current 
account  surpluses  that  exceeded  either  benchmark 
by 4 pp or more. Most of these Member States may 
even afford to run current account deficits in order 
to  reach  their  prudential  targets,  as  they  are  net 
recipients  of  EU  funds,  and  thus  benefit  from  a 
positive  capital  account  balance.  Among  these 
countries, 
several  countries  with  moderately 
negative  NIIPs  emerged  from  external  adjustment 
episodes by running particularly high surpluses. In 
Bulgaria,  Estonia,  Latvia,  Hungary,  and  Slovenia, 
cyclically  adjusted  surpluses  exceed  the  rCA  by 

56 | Quarterly Report on the Euro Area 

seven  to  ten  pp.  of  GDP.  Graph III.4  shows  that 
these are among the EU countries whose cyclically 
adjusted current account balances were the farthest 
above  the  required  current  account  in  2016.  The 
more  moderate  surpluses  of  the  Czech  Republic, 
Croatia,  Lithuania,  Romania,  and  Slovakia  range 
between two and five pp. above their rCA.  

Moreover,  there  are  the 
familiar  creditor 
countries,  whose  NIIPs  are  strongly  positive: 
Belgium, Denmark, Germany, Netherlands, and to 
some  extent  Sweden.  Of  these,  Belgium's  current 
account  is  roughly  at  its  rCA,  whereas  in  the four 
other  creditor  countries,  the  cyclically  adjusted 
current account exceeds the rCA by 5 pp of GDP 
or more.  

Spain,  Italy,  and  Austria  run  current  accounts 
that are between one and three pp. above their 
rCA.  Both  the  Italian  and  the  Austrian  cyclically 
adjusted current account are somewhat above their 
NIIP-stabilising  levels,  while  the  Spanish  current 
account is slightly above the level that would allow 
its NIIP to reach the prudential benchmark within 
ten years.  Finally, the NIIPs and current accounts 
of Malta, Ireland, and Luxembourg are particularly 
large  corporate, 
affected  by  the  presence  of 
transport  and  financial  sectors  –  something  that 
also  extends  to  the  Netherlands  and  Cyprus  to 
some  degree.  In  these  cases,  comparing  the 
headline  NIIP  to  the  prudential  reference  value 
might  not  be  appropriate.  Several  of 
these 
countries  publish  estimates  that  adjust  current 

-150-130-110-90-70-50-30-10103050101610161016101610161016101610161016101610161016101610161016BGROLVHRPLLTHUEESKCZPTSIELESCY% of GDPNet equityNENDINIIPThreshold  
 
 
III. Assessing Prudent NIIP and Current Account Positions 

accounts and NIIPs for these globalisation effects. 
It  might  be  more  suitable  to  compare  such-
adjusted  current  accounts  to  an  rCA  based  on 
such-adjusted  NIIP  estimates.  Note  that  while 
using  these  adjusted  estimates  would  affect  the 
magnitude  of  the  gaps  visible  in  Table III.3,  they 
do  not  lead to different  conclusions  whether their 
current  account  balances  are  below,  close  to,  or 
above the rCA.   

Graph III.4: Cyclically adjusted vs. required 
current accounts, 2016 

Source:  Commission  services  calculations,  as  in  table 
IV.3.  Readings  above  the  45-degree 
indicate 
cyclically  adjusted  current  account  balances  that  are 
above  the  required  current  account  benchmark  (vice 
versa for observations below). The distance from the 45-
degree  indicates  the  extent  of  the  gap  between  the 
cyclically adjusted and the required current account. 

line 

III.5.  Conclusion 

to 

chapter 

debt.  Compared 

This 
country-specific 
introduces 
prudential  benchmarks  for  the  NIIP  and 
NENDI,  a  comparable  indicator  focusing  on 
one-size-fits-all 
net 
benchmarks  such  as  in  the  MIP  scoreboard,  the 
country-specific benchmark allows for a finer level 
of  detail,  although  it  is  also  subject  to  certain 
statistical  caveats  in  the  case  of  offshore  financial 
centres.  The  NIIP  benchmark,  and  the  "required 
current account" derived from it, can complement 
the  Commission's  toolbox  for  assessing  external 
flows  and  stocks.  They  provide  additional  insight 
for  the  assessment  of  external  sustainability,  and 

are  meant  to  be  read  in  conjunction  with  existing 
tools.  

for  the  NIIP 
The  prudential  benchmark 
implies  a  country-specific  'required  current 
account' benchmark, that would allow a country 
to reach the prudential benchmark within ten years, 
or stabilise its NIIP above it. The prudential NIIP 
benchmark 
account 
required 
complement  do  not  replace  the  Commission's 
toolbox for external sustainability assessment. They 
are  one  among  several  new  benchmarks  that  the 
Commission 
in  macroeconomic 
surveillance.  

applying 

current 

and 

is 

for  some  general 
The  benchmarks  allow 
conclusions  about  EU  Member  States:  15 
Member States currently have NIIPs that are close 
to,  or  beyond,  prudential  reference  values.  Yet  if 
they  manage  to  keep  current  account  balances 
close  to  their  current  levels,  most  of  them  are  on 
track  to  reach  their  respective  prudential  levels 
within a decade or less.   

There  are  several  Member  States  that  run 
persistent  high  surpluses  beyond  their  current 
account benchmarks. Germany, the Netherlands, 
Denmark and Malta (the latter with some caveats), 
have high NIIPs, but run cyclically adjusted current 
account  surpluses  that  are  at  least  5  pp.  of  GDP 
above  the  level  required  to  stabilise  them.  In  the 
wake  of  external  adjustment,  several  smaller 
Member States continue to improve their negative 
NIIPs  at  fast  speed.  Their  cyclically  adjusted 
current  account  surpluses  are  either  more  than  5 
pp. above the NIIP-stabilising benchmark (Estonia 
and  Slovenia),  or  more  than  5  pp.  above  the  level 
required to reach the prudential benchmark within 
ten years (Bulgaria, Latvia, Hungary). In all of these 
Member  States,  the  NIIP  has  been  predominantly 
composed  by  equity  as  of  2016.  Their  NENDI, 
which reflects the NIIP excluding equity, is already 
well within prudential levels.  

Volume 17 No 3 | 57 

 
 
 
 
 
 
 
IV. Cyclical patterns of residential construction 

The large and frequent swings of residential construction investment have an important bearing on the 
business  cycle.  This  chapter  surveys  the  cyclical  pattern  of  residential  construction  investment  in  the 
euro  area  and  selected  Member  States  over  almost  five  decades.  It  uses  a  standard  econometric 
framework to identify main drivers of residential construction in the short- and longer term. In the long 
run,  residential  construction  investment  is  mostly  driven  by  real  per  capita  disposable  income 
developments,  and  in  some  Member  States  also  by  demographic  developments.  In  the  short  run 
residential  construction  activity  responds  positively  to  increasing  house  prices  as  well  as  falling 
unemployment.  Following  the  housing  boom  and  bust  a  decade  ago,  residential  investment  has 
bottomed  out  around  2015  and  is  now  swiftly  catching  up  with  disposable  incomes.  Positive  labour-
market developments and increasing house prices should continue to underpin residential construction 
activity in the near term. This picture is confirmed by additional indicators of near-term developments 
in  residential  construction  such  as  building  permits  and  confidence  in  the  construction  sector.  This 
suggests  a  positive  contribution  of  expanding  residential  construction  to  GDP  growth  this  year. 
However,  residential  construction  growth  may  have  peaked  in  some  Member  States  where  the 
residential construction cycle is already more advanced. (189) 

IV.1. Introduction  

Residential  construction  investment  represented 
only about 6% of GDP in the euro area on average 
in 2000-2017. However, the quite pronounced ups 
and  downs  in  residential  construction  activity  are 
intimately  linked  to  GDP  cycles  in  advanced 
economies.  E.  Leamer  even  titled  articles  on  US 
residential  investment  'Housing  is  the  business 
cycle' and 'Housing really is the business cycle'. (190) 
The housing boom and bust as trigger of the Great 
Recession  has 
in 
reinforced 
understanding the cyclical mechanics of residential 
construction and its links to GDP. 

interest 

the 

Much  of  the  literature  on  the  interaction  of 
residential  construction  and  GDP  focuses  on  the 
US,  for  which  there  is  broad  agreement  that  the 
residential  construction  cycle  leads  the  business 
cycle. (191)  One  source  of  shocks  to  residential 

(189) This chapter was prepared by Björn Döhring. The author would 
like  to  thank  João  Leal  for  help  with  reviewing  the  literature, 
Andras  Chabin  for  assistance  in  setting  up  the  estimations  and 
Reuben  Borg,  Jean-Charles  Bricongne,  Oliver  Dieckmann,  Laura 
González  Cabanillas,  Evelyne  Hespel,  Bertrand  Marc,  Nicolas 
Philiponnet and Andreas Reuter for useful comments. 

(190) Leamer,  E.  (2008),  'Housing  is  the  business  cycle,  in  Housing, 
Housing  Finance  and Monetary Policy.  A  symposium  sponsored 
by  the  Federal  Reserve  of  Kansas  City'  Revised  and  updated  for  the 
Encyclopedia of Finance, 2010. Leamer, E. (2014), 'Housing really is 
the business cycle: What survives the lessons of 2008-09?', Journal 
of Money, Credit and Banking, supplement to Vol 47(1). 

(191) E.g.  Leamer  (2014)  op.  cit,  Gjerstad,  S.  and  Smith,  V.  (2010), 
'Household  expenditure  cycles  and  economic  cycles,  1920-2010', 
Chapman  University  Economic  Science  Institute  Working  Paper.  Papers 
that  have  attempted  to  explain  this  theoretically  point  to 
interrelations  of  different  types  of  capital,  e.g.  Fisher,  J.  (2007), 
'Why  Does  Household  Investment  Lead  Business  Investment 
over  the  Business  Cycle?',  Journal  of  Political  Economy  115(1),  141-
168  as  well  as  Davis,  M.  and Heathcote,  J. (2005),  'Housing  and 

is  monetary  policy,  as  residential 
investment 
construction  is  found  to  be  particularly  strongly 
impacted  by  monetary  policy  shocks. (192)  Shocks 
to  residential  construction  activity  may  propagate 
in  the  economy  through  interlinkages  with  other 
sectors and affect GDP over and above the weight 
of the residential construction sector. Input-output 
tables  for  the  US  show  for  instance  that  the 
construction sector buys much more from the rest 
of  the  economy  than  the  other  way  round. (193) 
Drops  in  construction  demand  therefore  swiftly 
spread to other sectors. House price developments 
are  also  set  to  affect  household  demand  through 
wealth effects. 

investment 

For  the  euro  area,  the  evidence  on  a  leading  role 
in  the 
for  residential  construction 
business  cycle  is  less  clear  cut.  Musso,  Neri  and 
Stracca 
residential 
construction  leads  the  business  cycle  in  the  euro 
area.  Álvarez  and  Cabrero  (2010) (195)  point  out 
that this is the case in Spain and Germany, but not 

(2011) (194) 

find 

that 

the  Business  Cycle',  International  Economic  Review  46(3),  751-784. 
Kohlscheen,  E.,  A.  Mehrothra  and  D.  Mihaljek 
(2018), 
'Residential investment and economic activity: evidence from the 
past  five  decades',  BIS  Working  Paper  No  726  look  at  a  panel  of 
OECD countries.   

(192) Erceg,  C.  and  Levin  A.,  (2006),  'Optimal  monetary  policy  with 
durable  consumption  goods',  Journal  of  Monetary  Economics  53(7), 
1341-1359. 

(193) Boldrin,  M.,  Garriga,  C.,  Peralta-Alva,  A.  and  Sánchez  J.  (2013), 
'Reconstructing  the  Great  Recession',  Federal  Reserve  Bank  of  St. 
Luis, Working Paper 2013-006. 

(194) Musso, A., Neri, S. and Stracca, L. (2011), 'Housing, consumption 
and  monetary  policy:  How  different  are  the  US  and  the  euro 
area?', Journal of Banking and Finance 35(11), 3019-14. 

(195) Álvarez, L. and Cabrero, A. (2010), 'Does housing really lead the 
business cycle?' Banco de España Documentos de Trabajo, N° 1024. 

Volume 17 No 3 | 59 

 
                                                      
 
                                                                                 
 
in  France  and  Italy.  Kydland,  Rupert  and  Šustek 
(2016) also find no leading properties of residential 
investment  with  respect  to  GDP  in  France  or 
Belgium. (196)    Concerning  the  propagation  of 
shocks  to  construction,  the  ECB  (2009) (197)  
points  to  the  inputs  from  other  sectors  as  well  as 
the high labour intensity in the construction sector, 
which  implies  relatively  large  employment  effects 
of  construction  cycles.  By  contrast,  wealth  effects 
of house price developments do not seem to play a 
role in the euro area. (198)  Finally, the dynamics of 
the housing sector and its links to overall economic 
activity  vary  across  countries,  reflecting  structural 
features such as land availability, the structure and 
functioning  of 
tax 
treatment  of  housing  and  mortgages  and  local 
planning systems. (199) 

the  banking  sector, 

the 

This  chapter  first  examines  past  cycles  of  real 
residential  construction  investment (200)  in  euro 
area  Member  States  in  terms  of  their  frequency, 
amplitude  and  links  with  GDP  (section  2).  In 
section  3,  a  standard  error-correction  model  is 
developed to identify the trend- and cyclical drivers 
of  residential  construction  investment.  The  model 
is  used  in  section  4  to  analyse  the  residual 
'investment  gap'  and  examine  the  drivers  of 
residential construction investment in recent years. 
The  model  also  allows  conditional  forecasts  for 
residential  construction  for 2018.  These  are  cross-
checked  with  high-frequency 
indicators  not 
covered in the model. Section V.5 concludes. 

IV.2. Past residential construction cycles and 

GDP growth  

Drops  of  residential  construction  activity  are 
frequent  and  often  deep.  Since  1970,  there  have 
been 50 episodes of annual GDP contracting for at 

(196) Kydland, F., Rupert, P. and Šustek, R. (2016), 'Housing Dynamics 
Over the Business Cycle', International Economic Review 57(4), 1149-
1177. See also Ferrara and Vigna, O. (2009), 'Cyclical relationships 
between GDP and housing market in France: Facts and factors at 
play',  Banque  de  France  Document  de  Travail,  N°  268  find  the  same 
for  France  and  for  Italy  Bulligan,  G.  (2010),  'Housing  and  the 
Macroeconomy:  The  Italian  Case',  in:  O.  de  Bondt  et  al  (eds), 
Housing  Markets  in  Europe,  A  Macroeconomic  Perspective, 
Springer, Berlin, Heidelberg. 

(197) ECB Monthly Bulletin, May 2009, box 6. 
(198) Balta,  N.  and  Ruscher,  E.  (2011),  'Household  savings  and 
mortgage  decisions:  the  role  of  the  “down-payment  channel”  in 
the euro area', European Economy, Economic Papers 455. 

(199) ECB  (2003):  Structural  factors  in  the  EU  housing  markets, 

Frankfurt. 

least  one  year  in  the  12  euro  area  Member 
States (201) for which long series of annual data are 
available.  This  compares  to  91  episodes  of  annual 
residential  construction  investment  decreasing  for 
at  least  one  year.  The  standard  deviation  of  GDP 
growth in these countries since 1970 is 3.0. It is 7.8 
for construction investment and 11.5 for residential 
construction.  Counted  from  trough  to  trough,  the 
average  cycle  in  residential  construction  lasts  6 
years (median 5), compared to the average business 
cycle which lasts 11 years (median 9).  

in 

length  of 

the  upswing 

The 
residential 
construction  investment  and  the  length  of  the 
subsequent downturn are positively correlated (202), 
and  downturns  can  be  long-lasting.  Following  the 
excessive  housing  investment  in  the  euro  area  in 
the  run-up  to  the  2008  crisis,  it  took  until  2014 
before 
investment 
bottomed out.  

construction 

residential 

Graph IV.1: Number of 12 MS with a drop in 
construction / residential investment 

Source: AMECO, own calculations. 

GDP  contractions  are  almost  always  associated 
with  a  drop  in  residential  investment  ('associated' 
includes  a  few  cases  where  the  drop  in  residential 
investment  is  in  the  year  before  or  after  the 
contraction  of  GDP).  The  link  between  drops  in 
residential construction and drops in GDP is more 
complex,  as  suggested  by  the  larger  number  of 
contraction  episodes  in  residential  construction. 
Nonetheless,  among  the  55  episodes  before  the 
Great Recession where residential construction in a 

(200) This  differs  from  studies that  look  at housing  cycles  in  terms  of 
house  prices,  e.g.  Philiponnet  and  Turrini  (2017),  Bracke  (2013). 
As  we  study  the  link  to  real  GDP,  focussing  on  volumes  seems 
appropriate. 

(201) i.e. BE, DE, IE, EL, ES, FR, IT, LU, NL, AT, PT and FI. 
(202) This feaure is also present in house prices. Cf. Bracke, p. (2013), 
'How  long  do  housing  cycles  last?  A  duration  analysis  for  19 
OECD countries', Journal of Housing Economics 22, 213-230. 

60 | Quarterly Report on the Euro Area 

02468101214197019721974197619781980198219841986198819901992199419961998200020022004200620082010201220142016constructionresidential c.  
 
                                                      
 
                                                      
Member  State  dropped  by  at  least  5%,  half  are 
associated  with  a  drop  in  GDP  and  almost  all 
others  with  a  substantial  slowdown  compared  to 
previous  years'  GDP  growth  rates.  In  2008-2009, 
housing  investment  dropped  by  more  than  5%  in 
all  examined  Member  States  except  Austria,  and 
GDP dropped across these countries in 2009. 

Graph IV.1 depicts the number of Member States 
(among  the  12)  in  which  residential  construction 
contracted  in  a  given  year.  It  points  to  fairly 
synchronised  housing  downturns  in  1975,  1982, 
1993  and  2001.  In  2009,  residential  construction 
investment  contracted  in  all  12  Member  States, 
followed by another widespread contraction during 
the sovereign debt crisis.  

(2010) (203),  building  permits 

Quarterly growth of residential construction in the 
euro area since 1995 appears to be coincident with 
GDP  growth  rather  than  leading  it  (Table  IV.1). 
Residential  construction  is  leading  employment, 
which is considered a lagging variable with respect 
to  GDP.  In  line  with  the  findings  by  Álvarez  and 
lead 
Cabrero 
residential construction as well as GDP  by two to 
four quarters, reflecting the time lapse between the 
authorisation  to  start  building  and  the  registration 
of  the  actual  construction  activity  in  national 
accounts.  This  makes  building  permits  useful  for 
forecasting  short-term  fluctuations  in  residential 
construction  and  possibly  also  GDP.  Neither  the 
from  DG 
construction  confidence 
ECFIN's  business  surveys  nor  its  forward-looking 
components 
(order  books  and  construction 
expectations)  appear  to  be  leading  indicators  of 
residential construction growth. 

indicator 

Table IV.1: Correlations in quarterly growth 
rates 

IV. Cyclical patterns of residential construction 

IV.3. Drivers of residential construction 

investment 

the 

large  swings 

in  residential 
In  view  of 
investment and their influence on GDP, there is an 
obvious  interest  in  understanding  the  drivers  of 
residential construction. 

Housing  is  special  in  several  respects.  A  house  is 
both  an  asset  and  a  consumption  good;  its  use 
value  depreciates  slowly;  compared  to  financial 
assets its sale is costly, but it can easily be used as 
collateral.  Moreover,  housing  markets  are  subject 
to a number of regulations and policy incentives. In 
already densely populated areas, the supply of land 
is limited and its use often tightly regulated, which 
may  make  housing  supply  inelastic  and  amplify 
price swings. Tax deductibility of mortgages is used 
in some Member States to foster home ownership. 
Piazzesi  and  Schneider  (2016) (204)  survey  the 
literature that deals with the specificities of housing 
and  provide  a  comprehensive  approach 
to 
modelling  households'  demand  for  housing  and 
housing supply. 

It 

includes 

(2011). (205) 

The  present  chapter  focuses  on  a  limited  set  of 
drivers  of  residential  investment  in  an  error-
correction framework, broadly following Carnot et 
al 
demographic 
developments,  disposable  income  and  real  interest 
rates  as  main  determinants  of  housing  demand  in 
the  long  run.  The  real  interest  rate  is  included  in 
the  long-run  relation  as  it  affects  households' 
intertemporal 
(housing) 
investment and consumption. Over a shorter time 
horizon,  house  prices  are  considered  as  (the 
expectation of) higher prices increase the value of a 
house  as  an  asset  as  well  as  the  supply  of  houses. 
The  cost  of  mortgage  credit  also  affects 
affordability,  as  most  households  have  to  incur 
debt  to  acquire  a  house. (206)  Moreover,  the 
unemployment rate is considered as a proxy of the 
uncertainty of households' income streams. 

decisions 

between 

Source: AMECO, Eurostat, BCS and own calculations. 

(203) Op. cit. 

(204) Piazzesi,  M.  and  Schneider,  M. 

(2016):  Housing  and 
macroeconomics,  Handbook  of  Macroeconomics,  Vol.  2B,  pp. 
1547-1640 (ch. 19). 

(205) Carnot, N., Koen, V. and Tissot, B. (2011), Economic forecasting 

and policy, Springer. 

(206) Due to limited data availability, the monetary side of the model is 
somewhat underdeveloped. Ideally one would consider mortgage 
rates  rather  than  bond  yields,  possibly  for  various  maturities 
depending  on  the  mortgage  structures  prevailing  in  different 
countries.  

Volume 17 No 3 | 61 

targetindicator t-5t-4t-3t-2t-1tGDPRC0.090.260.310.400.400.63permits0.240.400.390.400.360.31ERC0.220.390.230.260.170.24RCconf0.150.260.270.340.410.45exp0.120.260.250.230.340.42permits0.300.420.300.480.300.38leadsRC: residential construction; E: employment; conf: constr. confidence; exp: constr. expectations  
 
 
 
                                                      
                                                      
possible.  Only  the  relationship  with  the  higher 
adjusted  R²  is  shown  and  possible  other  variants 
are used as robustness check. The panel estimation 
presented in the fourth column is based on the six 
largest  euro  area  Member  States  (unweighted).  It 
uses country fixed effects and White cross-section 
standard  errors.  The  reunification  dummy  is  not 
statistically  significant  on  top  of  the  country  fixed 
effects. 

taken  from 

The  data  set  includes  real  residential  construction 
investment (RC), real disposable income per capita 
(RDIPC  -  nominal  disposable  income  per  capita 
deflated  with  the  private  consumption  deflator), 
population (POP), the real interest rate (R – the 10 
year  bond  yield  deflated  with  the  GDP  deflator), 
the  unemployment  rate  (U)  and  real  house  prices 
(HPI  –  deflated  with  the  deflator  of  private 
consumption). Except the house price index, which 
is 
the  database  constructed  by 
Philiponnet  and  Turrini  (2017) (207),  all  data  are 
extracted  from  the  AMECO  database  for  1960  to 
2017, for the euro area and its six largest Member 
States. Some data series for Germany prior to 1992 
had  to  be  extrapolated  on  the  basis  of  west-
German data (208). A dummy variable with value 1 
from 1992 on and zero before was therefore added 
to  the  long-run  estimations  for  Germany  and  the 
euro  area  to  cater  for  any  instability  in  the 
reunification.  The 
coefficients 
estimated  coefficients  below  are  however  similar 
whether  the  dummy  is  included  or  not.  Other 
variables  like  mortgage  levels  and  rates  (from  the 
ECB),  or  high-frequency  data  such  as  building 
permits  (Eurostat)  are  only  available  for  more 
recent periods and not for all countries. These are 
introduced in the section on the near-term outlook. 

introduced  by 

for 

the 

Systematically, 

that  are  candidates 

Before  estimating 
the  error-correction  model 
(ECM),  a  simple  autoregressive  (AR(1))  model  is 
estimated  as  benchmark  for  the  euro  area  (first 
column  of  Table  IV.2).  Turning  to  the  ECM,  the 
series 
long-run 
relationship  are  first  tested  for  unit  roots  and 
residential 
cointegration. 
real  disposable 
construction,  population  and 
incomes  are  integrated  of  order  one.  The  real 
interest  rate  is  found  to  have  a  unit  root  in  most 
but  not  all  cases.  The  variables  for  which  the 
Johansen test suggests cointegration are included in 
a  first  estimation  of  the  long-run  relationship. 
Variables  that  are  not  statistically  significant  are 
then  excluded  and  cointegration  tested  again  for 
long-run 
the  remaining  ones.  The  estimated 
relationships  are  presented  in  the  upper  panel  of 
Table  IV.2.  In  some  cases,  several  variants  are 

(207) Philiponnet,  N.  and  Turrini,  A.  (2017),  'Assessing  House  Price 
Dynamics  in  the  EU',  Directorate-General  Economic  and  Financial 
Affairs European Economy Discussion Paper 048. 

(208) Indices  for  RC  and  RDIPC  built  from  growth  rates  for  west 
Germany  (1960-1992)  and  reunified  Germany  1992  onwards. 
There is no consumption deflator for west Germany in AMECO. 
Therefore,  pre-1992  RDIPC  was  deflated  with  CPI.  POP  exists 
for entire DE since 1960. R is the combination of west DE and 
reunified DE (East DE wasn't a market economy). 

62 | Quarterly Report on the Euro Area 

  
 
                                                      
IV. Cyclical patterns of residential construction 

Table IV.2: Estimation outcomes 

(1) Statistical significance at 1% (***), 2%(**) and 5% (*) level (not shown for the error-correction term because of its non-
standard 
distribution). 
(2) The euro area panel includes the 6 largest Member States unweighted. 
Source: AMECO, own calculations 

long-run 

The short-run relationship links the annual growth 
rate of residential investment to the rate of change 
in the long-run determinants, the lagged residual of 
the 
additional 
relationship 
explanatory  factors.  These  include  house  price 
inflation (209),  the  change  of  the  unemployment 
rate, and population growth. Results are presented 
in the lower panel of Table IV.2. 

and 

For  the  majority  of  countries  as  well  as  the  euro 
area, real per capita disposable income is identified 
as  a  major  driver  of  housing  investment  in  the 
longer  run,  sometimes,  but  not  systematically  in 
conjunction  with  demographic  developments. The 
real interest rate is picked up as a long-run driver of 
housing investment only in a few cases. 

inflation 

is  positively  and  quite 
House  price 
robustly  linked  to  housing  investment,  in  other 
words,  housing  investment  slows  down  when 
house  prices  decelerate  or  fall,  in  line  with  the 
findings  by  Kohlscheen  et  al  (2018).(210)  Income 
uncertainty  proxied  by 
the 
unemployment  rate  also  affects  the  residential 

the  change 

in 

(209) The  level  of  house  prices  could  also  be  considered  a  driver  of 
run.  However,  no 

residential  construction 
cointegration relationship is found between the two. 

long 

the 

in 

(210) Op. cit.  

construction  cycle.  Improvements  in  the  labour 
market appear to make households more confident 
to  undertake  a  major  investment  and  take  out  a 
mortgage. Short-term population developments are 
not  generally  found  to  impact  the  residential 
construction cycle.  

the 

volatility 

Considering 
residential 
construction,  the  fit  of  the  estimated  ECMs 
(adjusted R² at 0.5 or more in most cases) appears 
reasonable,  except  for  Germany,  where  it  remains 
close to 0.3.  

of 

contemporaneously, 

The autoregressive benchmark and the ECM in the 
second column are estimated over the period 1978-
2007 in order to perform out-of-sample year-ahead 
forecasts. As the change of the unemployment rate 
and  the  change  of  real  house  prices  enter  the 
model 
is 
conditional.  It uses the unemployment projection 
from 
Spring  European 
Economic  Forecast  of  the  same  year  and  a  naïve 
projection  of  house  price  increases  at  previous 
year's  rate.  This  forecast  is  compared  to  a  naïve 
projection of the growth of residential construction 
investment and the AR(1) benchmark.  

the  Commission's 

forecast 

this 

Forecast  errors  are  substantial  for  any  of  the 
techniques.  Nonetheless,  the  ECM  has  the  lowest 

Volume 17 No 3 | 63 

euro areaAR(1)short samplefull samplepanel1978-20071978-20071978-20171974-2016DEFRITESNLBElong runc1.4***RDIPC0.97***0.97***0.68***0.31***0.61***1.01***0.98***1.00***POP0.62***0.42***0.97***r -0.02***-0.03***dummy 920.12***0.08***0.18***short rundRC lag10.56***0.27*0.40***0.33***0.42***0.030.36*0.30*0.48***0.20dRDIPC0.32*dRDIPC lag 1-0.48*-0.60**-0.47***dU-1.64**-1.52***-1.39***-1.93**-1.31**-2.92*dHPI0.59***0.67***0.36***0.460.38***0.32*0.30*0.43***1.03***dPOP1.23l-r res-0.40-0.24-0.14-0.21-0.03-0.15-0.12-0.24-0.28obs303039258434331384343adj. R²0.140.620.650.500.320.520.510.630.580.56DW1.891.961.821.971.901.692.212.261.802.14Member States  
                                                      
 
 
 
Graph IV.2: Residuals of long-run regression 

Source: AMECO, own calculations 

Root Mean Squared Error at 4.0 against 4.2 for the 
AR(1) and 4.8 for the naïve forecast.  

IV.4. Model-based prospects for residential 

construction 

In  view  of  the  forecast  errors,  point  estimates  of 
residential construction growth should not be over-
interpreted.  However,  the  model  is  useful  insofar 
as  it  points  to  the  likely  structural  and  cyclical 
drivers of residential construction developments at 
a given point in time.  

In  2017,  residential  construction  in  the  euro  area 
expanded  at  a  rate  of  4.2%.  Graph  IV.2  plots  the 
residuals  of  the  long-run  regression  extended  on 
the basis of data from the spring forecast. For the 
euro area, it points to a decreasing gap between the 
current level of residential investment and the level 
implied  by  real  disposable  income,  which  is  its 
main  long-run  determinant  in  the  euro  area.  The 
residual 
housing 
clearly 
overinvestment  in  the  decade  preceding  the  crisis 

displays 

graph 

64 | Quarterly Report on the Euro Area 

followed  by  a  sharp  and  protracted  drop  with  a 
trough  in  2015.  By  2017,  residential  construction 
was  well  on  the  recovery  path.  The  remaining 
difference  between  the  actual  level  of  residential 
construction  investment  and  the  level  implied  by 
disposable  income  points  to  continued  impetus 
behind residential  construction  in  the  euro  area  in 
the medium term. In 2017, residential construction 
gaps,  i.e.  the  level  of  residential  construction 
investment 
long-term  drivers 
identified in section V.3., were most pronounced in 
Spain  and  Italy,  and  to  a  lesser  extent  France.  In 
residential  construction  has 
the  Netherlands 
already moved back well above the level implied by 
demographics.  For  Germany  and  Belgium,  the 
current level of residential construction investment 
is  also  higher  than  suggested  by  its  long-run 
drivers. 

relative 

its 

to 

Graph  IV.3  illustrates  the  contributions  of  the 
residential  construction 
different  drivers  of 
investment.  For 
falling 
unemployment rate has contributed positively since 

the  euro  area, 

the 

-0.15-0.1-0.0500.050.10.1519601963196619691972197519781981198419871990199319961999200220052008201120142017EA-0.4-0.3-0.2-0.100.10.20.319601963196619691972197519781981198419871990199319961999200220052008201120142017DEFR-0.5-0.4-0.3-0.2-0.100.10.20.30.40.519601963196619691972197519781981198419871990199319961999200220052008201120142017ITES-0.5-0.4-0.3-0.2-0.100.10.20.30.419601963196619691972197519781981198419871990199319961999200220052008201120142017NLBE  
 
 
IV. Cyclical patterns of residential construction 

Graph IV.3: Model-based contributions to residential construction growth 

Source: AMECO, own calculations 

2014.  Since  2015,  house  price  inflation  is  also 
contributing  positively  to  residential  construction. 
Moreover,  the  error-correction  model  attempts  to 
close  the  gap  with the  long-term relation,  pushing 
the  projected  growth  of  residential  investment 
higher. 

the 

At 
falling 
level  of  Member  States, 
unemployment  is  also  identified  as  a  positive 
contributor  in  recent  years  for  France,  Spain  and 
Belgium.  House  price  increases  have  underpinned 
recent  residential  construction  in  all  countries 
under  review  except  Italy.  For  Germany,  the 
Netherlands  and  Belgium,  the  model  suggests  a 
dampening  impact  of  the  long-term  relationship 
through the error correction term. 

For  2018,  the  graph  shows  a  conditional  model 
projection.  It  is  based  on  the  change  in  the 
unemployment rate from the Commission's Spring 
2018 forecast and the assumption that house prices 

falling  unemployment 

in 2018 as a whole evolve like in the first quarter, 
for which data are already available from Eurostat 
(nominal  HPI  deflated  with  the  consumption 
deflator  from  the  spring  forecast).  For  the  euro 
area,  the  combination  of  a  remaining  residential 
investment  gap, 
and 
increasing house prices points to continued robust 
growth of residential construction investment. Also 
for  Italy  and  Spain,  the  identified  drivers  of 
residential  construction  points 
to  continued 
growth. For the other Member States under review, 
the  main  medium-term  and  short-term  drivers  of 
residential 
some  growth 
moderation. (211) 

investment 

suggest 

It  should  however  be  recalled  that  the  forecasting 
errors of the model are quite substantial, inter alia 
because  residential  construction  is  much  more 

(211) Note  that  these  model-based  projections  are  not  necessarily 

identical with those that enter the Commission's forecasts. 

Volume 17 No 3 | 65 

-0.14-0.12-0.1-0.08-0.06-0.04-0.0200.020.040.060.082000200120022003200420052006200720082009201020112012201320142015201620172018euro areaAR termReal disp incomeUnemploymentHouse priceserror correctionsimulated RC-0.08-0.06-0.04-0.0200.020.040.060.080.10.122000200120022003200420052006200720082009201020112012201320142015201620172018DE-0.12-0.1-0.08-0.06-0.04-0.0200.020.040.060.082000200120022003200420052006200720082009201020112012201320142015201620172018FR-0.12-0.1-0.08-0.06-0.04-0.0200.020.040.060.082000200120022003200420052006200720082009201020112012201320142015201620172018IT-0.25-0.2-0.15-0.1-0.0500.050.10.150.20.252000200120022003200420052006200720082009201020112012201320142015201620172018ES-0.2-0.15-0.1-0.0500.050.10.150.20.252000200120022003200420052006200720082009201020112012201320142015201620172018NL-0.15-0.1-0.0500.050.10.152000200120022003200420052006200720082009201020112012201320142015201620172018BE 
                                                      
 
leverage.  As  house  prices  have  bottomed  out  in 
2013  and  GDP  growth  has  accelerated,  acute 
deleveraging  pressures  have  receded.  The  Bank 
Lending  Survey  reports  firming  mortgage  credit 
demand 
in  the  second  quarter  of  2018  and 
expectations of increasing demand also in the third 
quarter.  

Graph IV.4: Construction confidence and 
building permits, euro area 

volatile than most of the explanatory variables. It is 
therefore  useful  to  cross-checked  the  drivers  of 
residential  construction  identifies  by  the  model 
include  higher-
with  other  data. (212)  These 
frequency  data  many  of  which  could  not  be 
included in the model for lack of long time series.  

Confidence in the construction sector (213) is high, 
having picked up sharply since 2014. At 6.4 points 
in August 2018, construction confidence stands 1½ 
standard  deviations  above  its  long-term  average 
since 1985. Business managers in construction also 
indicate a backlog of orders slightly above average 
and a strong flow of incoming orders. Confidence 
in  the  construction  sector  is  above  its  long-term 
average  in  all  Member  States  discussed  here.  In 
Germany  and  the  Netherlands,  as  well  as  in  the 
euro  area  as  a  whole,  construction  confidence 
reached record highs in recent months.  

Building  permits 
lead  residential  construction 
growth  by  about  two  quarters,  due  to  the  time  it 
takes for construction to proceed and be recorded 
in  national  accounts.  Monthly  and  even  quarterly 
indices  of  building  permits  are  however  quite 
volatile.  In  the  first  five  months  of  this  year,  the 
number of residential building permits in the euro 
area  increased  at  an  average  annual  rate  of  4%, 
which is slower than in 2017 (7%) and 2016 (17%) 
pointing 
residential 
construction activity. The latest available data point 
to  accelerating  delivery  of  permits  in Belgium  and 
Spain and a moderation in Germany, France, Italy 
and the Netherlands.  

a  moderation  of 

to 

are 

conditions 

ample.  Market 
Financing 
participants do not expect the ECB to hike policy 
interest  rates  before  2019.  The  ECB's  latest  Bank 
Lending  Survey (214)  points  to  easing 
lending 
conditions for  mortgages  in  the second  quarter  of 
2018.  Banks  expected  further  easing  in  the  third 
quarter.  Mortgage  credit  (nominal)  expanded  at 
annual  rates  around  3%  the  first  half  of  2018. 
Household debt as a share of GDP has fallen only 
slightly in the euro area as a whole since the onset 
of the crisis, but it was reduced substantially in the 
the  highest 
countries  where  households  had 

(212) Cf. also ECB Economic Bulletin May 2016, Box 6. 
(213) Residential  construction 
construction activity. 

represents  about  half  of  overall 

(214) See  ECB  (2018),  'The  euro  area  bank  lending  survey.  Second 
at 
quarter 
https://www.ecb.europa.eu/stats/pdf/ecb.blssurvey2018q2.en.pd
f?776aed1b5334351b742031c1d7ef08fb  

2018' 

of 

66 | Quarterly Report on the Euro Area 

Source: Eurostat 

Overall,  high-frequency  data  also  point  to  a 
continuation  of  robust  growth 
in  residential 
construction, which is in line with the model-based 
analysis of growth drivers. 

IV.5. Conclusion 

and 

recessions 

Swings  in  residential  construction  investment  are 
frequent 
are 
large.  GDP 
systematically  associated  with  contractions  of 
residential  investment.  The  link  from  drops  in 
housing  investment  to  GDP  is  however  more 
complex: between 1970 and the early 2000s, when 
in  a  Member  State 
residential  construction 
contracted by 5% or more, GDP dropped in about 
half  of  the  cases  and  slowed  down  in  most  other 
cases.  During  the  Great  Recession,  GDP  and 
housing  investment  dropped  in  all  12  Member 
States examined. There is evidence of construction 
investment  leading  the  business  cycle  in  the  US. 
On  this  side  of  the  Atlantic  that  seems  to  be  the 
case for some Member States, but not for the euro 
area 
residential 
construction  investment  seems  contemporaneous 
to  GDP  in  the  euro  area,  building  permits  are  a 
leading indicator for both.  

aggregate.  Even 

though 

-35-30-25-20-15-10-50510020406080100120140160Jan-10Jul-10Jan-11Jul-11Jan-12Jul-12Jan-13Jul-13Jan-14Jul-14Jan-15Jul-15Jan-16Jul-16Jan-17Jul-17Jan-18Jul-18permits (lhs)confidence (rhs  
 
                                                      
 
of 

drivers 

residential 

A  standard  error-correction  framework  is  used  to 
model 
construction 
investment in the long- and short run in line with 
the  literature.  Real  disposable  income  and  to  a 
lesser  extent  population  growth  and  the  real 
identified  as  drivers  of 
interest  rate  can  be 
residential 
long-run 
investment 
to  a  quickly  narrowing 
relationship  points 
investment gap in residential construction. 

trends.  This 

In  the  shorter  run,  the  unemployment  rate  and 
house  prices  are  additional  drivers  of  residential 
investment.  This  general  pattern  is  rather  similar 
across Member States. 

IV. Cyclical patterns of residential construction 

The  medium-term  and  short-term  drivers  of 
residential construction investment identified in the 
modelling  exercise  point  to  continued  growth  of 
residential  construction  in  the  euro  area.  This 
picture 
is  confirmed  when  higher-frequency 
indicators  are  taken  into  account.  GDP  growth  in 
most  of  the  euro  area  is  thus  set  to  benefit  from 
the  demand  related  to  residential  construction.  At 
the level of the largest Member States, positions in 
the residential construction cycle differ, and this is 
reflected  in  the  conditional  model  projections  for 
residential construction growth this year. 

Volume 17 No 3 | 67 

 
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