Entry barriers and their macroeconomic impact in the EU : an assessment using QUEST III.
Date: 2017-11-22
Institutions: Joint Research Centre
Subjects: EU Member State, business policy, economic consequence, economic model, financing, macroeconomics, market, market access, research and development, research report

 Entry barriers and their macroeconomic 
impact in the EU: an assessment using 
QUEST III 

Benedetti-Fasil, C. 

Sanchez-Martinez, M. 

Christensen, P. 

Robledo-Böttcher, N. 

2017  

EUR 28857 EN 

 
 
 
 
 
 
 
This  publication  is  a  Technical  report by  the  Joint  Research  Centre  (JRC),  the  European  Commission’s  science 
and  knowledge  service.  It  aims  to  provide  evidence-based  scientific  support  to  the  European  policymaking 
process. The scientific output expressed does not imply a policy position of the European Commission. Neither 
the  European  Commission  nor  any  person  acting  on  behalf  of  the  Commission  is  responsible  for  the  use  that 
might be made of this publication. 

Contact information  
Name: Miguel Sanchez-Martinez 
Address: CDMA building, office 04/183, 21 Rue du Champ de Mars, 1050, Bruxelles 
Email: miguel.sanchez-martinez@ec.europa.eu 
Tel.: +32 229 60391 

JRC Science Hub 
https://ec.europa.eu/jrc 

JRC108932 

EUR 28857 EN 

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ISBN 978-92-79-75759-4 

ISSN 1831-9424 

doi:10.2760/722488 

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How to cite this report: Benedetti-Fasil, C., Sanchez-Martinez, M., Christensen P., Robledo-Böttcher, N., "Entry 
barriers  and  their  macroeconomic  impact  in  the  EU:  an  assessment  using  QUEST  III",  EUR  28857  EN, 
Publications Office of the European Union, Luxembourg, 2017, ISBN 978-92-79-75759-4, doi:10.2760/722488, 
JRC108932. 

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Contents 

Foreword .............................................................................................................. 1 

Acknowledgements ................................................................................................ 2 

Abstract ............................................................................................................... 3 

1  Introduction ...................................................................................................... 4 

2  Definitions and literature review .......................................................................... 6 

2.1  What are entry barriers? ............................................................................... 6 

2.2  How are entry, exit and entry barriers modelled in macroeconomics? A theoretical 
perspective ....................................................................................................... 7 

2.3  Overview of the empirical literature on the impact of entry barriers ................... 9 

3  The macroeconomic impact of Entry Barriers in Member States: a quantitative analysis 
using QUEST III .................................................................................................. 10 

3.1  Entry barriers and risk premia in QUEST III .................................................. 11 

3.1.1  QUEST III simulations ........................................................................ 13 

3.1.2  Policy scenario I: lower entry costs ...................................................... 15 

3.1.3  Policy scenario II: lower entry costs and risk premia .............................. 18 

4  Concluding Remarks ........................................................................................ 23 

References ......................................................................................................... 24 

List of figures ...................................................................................................... 27 

List of tables ....................................................................................................... 28 

i 

Foreword 

This  publication  is  a  Technical  report  by  the  Joint  Research  Centre  (JRC),  the  European 
Commission’s science and knowledge service. It aims to provide evidence-based insights 
into  the  role  and  macroeconomic  played  by  entry  barriers  across  the  EU,  in  order  to 
support policymaking in this area. The scientific output expressed does not imply a policy 
position of the European Commission. Neither the European Commission nor any person 
acting on behalf of the Commission is responsible for the use that might be made of this 
publication. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Acknowledgements 

First of all, we would like to thank Pr. Giammario Impullitti for his invaluable revision of 
this  paper.  We  thank  colleagues  at  DG  Joint  Research  Centre  (JRC)  for  their  invaluable 
comments and suggestions, as well as  Janos Varga  from DG for  Economic and Financial 
Affairs  (ECFIN)  for  his  assistance  with  the  QUEST  III  simulations  as  well  as  his  support 
and comments for this paper. QUEST III is a model developed by DG ECFIN. 

Authors 

Sanchez-Martinez, Miguel. Unit B.7 "Knowledge for Finance, Growth & Innovation", 
DG Joint Research Centre, European Commission 

Benedetti-Fasil, Cristiana. Unit B.7 "Knowledge for Finance, Growth & Innovation", 
DG Joint Research Centre, European Commission 

Christensen, Peder. Unit B.7 "Knowledge for Finance, Growth & Innovation", 
DG Joint Research Centre, European Commission 

Robledo-Böttcher, Nicolas. Unit B.7 "Knowledge for Finance, Growth & Innovation", 
DG Joint Research Centre, European Commission 

2 

 
 
 
 
 
Abstract 

Entry  barriers  make  markets  less  contestable  and  thereby  reduce  competition,  resulting 
in  lower  TFP,  GDP  and  employment  growth.  Following  the  Lisbon  strategy,  Member 
States  increasingly  adopted  measures  to  reduce  the  costs  of  starting  a  business.  This 
paper  quantifies  the  macroeconomic  impact  of  such  policies  and  identifies  the  main 
structural  characteristics  still  driving  the  differences  across  Member  States.  In  general, 
countries  with  high  entry  barriers  and  a  less  developed  R&D  sector  seem  to  benefit 
proportionally more from a reduction of the so-called red tape barriers.  Growth  of  GDP, 
TFP  and  employment  could  be  further  enhanced  by  also  improving  access  to  finance. 
Countries with a more developed R&D sector experience stronger growth in the long run 
when  the  reduction  of  the  red  tape  barriers  is  accompanied  by  an  improved  access  to 
finance. 

3 

 
1  Introduction 

The entry of new firms to markets and the transformation of new ideas into marketable 
products  are  at  the  core  of  economic  growth  and  higher  productivity  through  the 
reallocation  of  resources  from  shrinking  and  exiting  firms  to  new  entrants  and  growing 
firm.12 A study from the European Commission, covering FR, IT, DE, IE, PT, and ES over 
1997-2003 period, estimated that a 1% increase in the entry rate of firms would increase 
GDP  growth  by  0.6%  and  employment  growth  by  2.67%  based  on  data  over  the  1997-
2003 period.3  

Reflecting the importance of firm  entry for a dynamic business environment, one  of the 
main  pillars  of  the  Entrepreneurship  2020  Action  Plan  is  to  create  a  more  dynamic 
business  environment  in  which  entrepreneurs  can  more  easily  execute  their  business 
ideas,  flourish  and  grow.  The  Action  Plan  comprises  a  series  of  measures  that,  among 
other  objectives,  facilitate  access  to  finance,  reduce  the  regulatory  burden  to  start  and 
manage an enterprise, and ease bankruptcy procedures. 

Following  the  launch  of  the  Lisbon  Strategy,  most  Member  States  began  to  reduce  the 
costs of starting a business (see Ciriaci (2014, table III.2, t)4. Nevertheless, the levels of 
entry  barriers  are  still  very  heterogeneous  across  Member  States  and    some  countries 
like  IT,  CY,  MT,  and  PL  have  costs  to  start  a  business  that  are,  relative  to  income  per 
capita,  up  to  70  times  higher  than  the  best  EU  performers,  i.e.  DK,  UK,  and  IE  (Ciriaci 
2014,  Table  III.1).5  The  OECD's  (2015)  indicator  on  product  market  regulation  also 
shows  countries'  heterogeneity  on  barriers  to  entrepreneurship  (see  Figure  1).6  Over 
time,  most  countries  have  made  considerable  progress  in  removing  entry  barriers, 
although  this  progress  has  slowed  down  since  2008.  Hence,  in  several  Member  States 
policy  makers  still  have  space  for  significant  interventions  directed  towards  creating  a 
more  dynamic  and  competitive  industry.  As  a  result,  policies  in  favour  of  SMEs,  in 
particular policies that may create the conditions for the flourishing of the so-called High 
Growth  Innovative  Enterprises  (HGIE)  are  receiving  greater  attention.  Likewise,  an 
important  policy  issue  is  to  understand  and  measure  the  impact  of  policies  aimed  at 
reducing entry barriers.7 Both large companies and Small- and Medium-sized Enterprises 
(SMEs)  benefit  from  a  reduction  in  entry  barriers.  However,  large  companies  are  often 
better able to cope with entry barriers than SMEs due to having access to a larger pool of 
resources,  including  easier  access  to  finance.  Consequently,  policies  aiming  at  a 
reduction  of  entry  barriers  notably  aim  at  supporting  SMEs  and,  in  particular,  young 
enterprises, as these are the type of firms most often deterred by entry barriers. This is a 
particularly important policy issue in order to increase productivity and growth, as most 
of  the  job  creation  by  young  firms  is  carried  out  by  new  firms  entering  the  market 

1  For  instance,  Nicoletti  and  Scarpetta  (2003)  using  a  panel  of  18  OECD  countries  between  1984  and  1998, 
were  the  first  to  estimate  that  lower  entry  barriers  would  result  in  a  faster  catch-up  with  the  technology 
frontier. This is now widely established in the empirical literature. 

2 Several papers asses the growth contribution of the reallocation of resources from exiting to entering firms. 
For instance, Luttmer (2007) and Gabler and Licandro (2009) estimate that this selection effect can explain 
between 20% to 50% of US GDP growth.  These estimates are consistent with Scarpetta et al. (2002) who 
find that entry and exit contributed to between 20% to 40% of aggregate productivity growth in a panel of 
OECD countries.  

3  See  European  Commission  (2005),  "Impact  of  market  entry  and  exit  on  EU  productivity  and  growth 

performance", European Economy 222.  

4 The World Bank definition of the costs of starting a business comprises three main elements; the number of 
procedures,  the  number  of  days  and  the  cost  as  percentage  of  income  per  capita  necessary  to  start  a 
business. These are the so-called red tape entry barriers.  

5  For  instance,  the  costs  of  starting  a  business  as  a  percentage  of  income  per  capita  is  0.2%  in  Denmark 
compared  to  14.2%  in  Malta.  Cross-country  differences  in  entry  barriers  partially  explain  cross-country 
differences in the size of entering firms as shown by Bartelsman et al. (2005).   

6 The OECD developed a series of economy-wide indices to measure countries regulatory frameworks and their 
changes over time. The Product Market Regulation index is a synthesis of three indexes on state control, 
barriers  to  entrepreneurship,  and  barriers  to  trade  and  investment.  See  Nicoletti  et  al.  (1999)  for  an 
explanation on how they are constructed.  This ranking of countries differs with respect to the World Bank's 
Doing Business because of the different definition of entry costs used by the two institutions. 

7  At  the  European  level,  Sapir  (2004)  stressed  that  too  much  policy  attention  is  paid  to  incumbent  firms  to    

ensure fair competition, whereas entrants and young firms tend to be neglected.   

4 

                                           
(Haltiwanger  et  al.,  2013).  Similarly,  Criscuolo  et  al.  (2014)  in  a  study  with  18  OECD 
countries estimate that the share of total employment creation due to SMEs that are less 
than  three  years  old  is  quite  high  relative  to  their  size  (varying  from  60%  to  around 
28%, as shown in Figure 2 below).  

Firm size is also closely related to business dynamics. The European Commission Product 
Market Review (2013) highlights a non-linear relationship between firm size at both entry 
and exit and an efficient allocation of resources between and within firms.  In particular, 
they find that on average an increase in the size of a firm, when entering the market, of 
1  employee  is  associated  with  an  increase  in  efficiency  by  1.6%.  In  addition  such  a 
relation  exhibits  an  inverted  U-shape,  peaking  with  10  employees  at  entry.8  This 
indicates that policies that support an increase in the average size of small start-ups give 
rise to efficiency gains.  

Figure  1  below  shows  the  distribution  of  administrative  burdens  on  start-ups  and 
regulatory protection of incumbent firms across OECD countries in 2013. Figure 2 depicts 
the  extent  to  which  (young)  SMEs  contribute  to  job  creation,  destruction  and 
employment in OECD countries. 

Figure 1.  Barriers to entrepreneurship in 2013 - source OECD (2015) 

Figure 2. Young SMEs contribute disproportionately to job creation - source Criscuolo et 
al. (2014)  

8 The empirical analysis uses Eurostat data from 2000-2010 and includes most Member States.  

5 

 
 
                                           
Against this backdrop, this paper carries out a horizontal quantification across 17 Member 
States of the potential macroeconomic impact of a reduction in entry barriers in terms of 
fixed  costs  and  financial  constraints.  This  examination  will  be  carried  out  using  the 
European  Commission's  QUEST  III  model.9  The  goal  is  to  combine  qualitative  and 
quantitative analysis to critically assess: (i) the role of entry barriers in Member States to 
determine  GDP,  productivity  and  employment,  and  (ii)  structural  characteristics  that 
cause different magnitudes and persistence levels of the impact of an increase in product 
competition within countries. Hence, the paper will support the policymaking process by 
identifying  the  structural  areas  in  which  improvements  can  be  made  to  foster  a  more 
dynamic business sector and, ultimately, economic growth.  

2  Definitions and literature review 

2.1  What are entry barriers? 

The  definition  of  entry  barriers  is  a  topic  widely  discussed  in  the  literature.  Although 
many  definitions  have  been  put  forward,  there  is  still  disagreement  on  what  exactly 
should be understood as entry barriers. Among the widest definitions is that proposed by 
Bain  (1956  p.  3).  He  defines  entry  barriers  as  "advantages  of  established  sellers  in  an 
industry over potential entrant sellers, these advantages being reflected in the extent to 
which  established  sellers  can  persistently  raise  their  prices  above  a  competitive  level 
without attracting new firms to enter the industry".   

A significant number of elements underlie Bain's definition. He stresses the importance of 
three  barriers:  (i)  economies  of  scale,  (ii)  product  differentiation,  and  (iii)  absolute  cost 
advantage.  Economies  of  scale  imply  that  when  firms  enter  the  market  they  are  either 
too small, and hence face a fixed cost disadvantage with respect to incumbents, or they 
enter at an efficient scale leading to a depressing effect on prices. Product differentiation 
allows incumbents to charge higher prices than entrants for instance due to brand loyalty 
or  advertising.  Finally,  an  absolute  cost  advantage  allows  incumbents  to  sell  profitably 

9 QUEST III is a Dynamic Stochastic General Equilibrium model developed by DG Economic and Financial Affairs 
(DG ECFIN). 

6 

 
 
                                           
below the costs of potential entrants. This may be due to a combination of economies of 
scale  and  brand  loyalty  or  to  know  how  and  specific  technologies  developed  by 
incumbents as well as Intellectual Property Rights and trademarks.  

A  much  narrower  definition  is  proposed  by  Stigler  (1968  p.  67),  who  defines  entry 
barriers as  "a cost  of producing (at some  or every  rate  of  output) which must be borne 
by  a  firm  seeking  to  enter  an  industry  but  it  is  not  borne  by  firms  already  in  the 
industry". In other words, Stigler recognizes as entry barriers only the cost disadvantage 
due to entry regulations, i.e., the so-called red tape barriers. He also criticises the idea of 
scale economies and capital requirements as entry barriers. In his view, scale economies 
are  not  entry  barriers  if  entrants  and  incumbents  have  equal  access  to  technology. 
Similarly,  capital  requirements  are  not  entry  barriers  unless  incumbents  never  faced 
them.    

Several authors have provided alternative definitions of entry barriers which are more or 
less restrictive but within the upper bound defined by Bain (1956) and the lower bound 
defined  by  Stigler  (1968)10.  New  elements  in  the  definition  are  included  in  Shepherd 
(1979) who distinguishes between exogenous and endogenous entry barriers. Exogenous 
barriers are intrinsic to the market and neither incumbents nor entrants are able to affect 
them.  Some  examples  of  exogenous  barriers  are  government  policies,  incumbent  cost 
advantages due to technology acquisition, R&D intensity, access to distribution channels, 
customers'  switching  costs,  and  entrants  need  for  capital.  On  the  other  hand, 
endogenous barriers are a result of incumbents' competition and market strategies aimed 
at  impeding  firm  entry,  e.g.  advertising,  aggressive  marketing  strategies  and  predatory 
prices.  Exogenous  and  endogenous  barriers  may  amplify  each  other,  thereby  increasing 
their respective impact on markets' competitive structure and dynamics.   

McAfee  et  al.  (2004)  suggested  an  even  wider  definition  than  Stigler's  by  positing  that 
"an economic barrier to entry is a cost that must be incurred by a new entrant and that 
incumbents  do  not  or  have  not  had  to  incur".  This  means  that  entry  barriers  can  also 
include costs, such as brand loyalty, that are not labelled as  red tapes. Additionally, the 
authors  distinguish  between  primary  entry  barriers  such  as  IPR  or  brand  loyalty  and 
ancillary  barriers  that  are  not  barriers  per  se  but  reinforce  other  potential  barriers  to 
entry such as economies of scale.  

The academic debate around entry barriers and their definition has not always addressed 
practical  issues  in  support  of  actionable  policy  measures.  This  void  has  been  filled  by 
guidelines  developed  by  the  countries'  competition  enforcement  agencies.  For  instance, 
the  European  Guidelines  on  the  Assessment  of  Horizontal  Mergers  (2004)  defines  entry 
barriers as "specific features of the market, which give incumbent firms advantages over 
potential  competitors".  This  is  a  broad  definition  that  includes  three  main  types  of 
barriers:  (i)  technical  advantages  such  as  preferential  access  to  natural  resources, 
innovation  and  R&D,  IPR,  access  to  technology,  economies  of  scale  and  scope, 
distribution  and  sales  networks;  (ii)  legal  advantages  such  as  a  restricted  number  of 
licences,  tariff  and  non-tariff  trade  barriers;  (iii)  barriers  resulting  from  the  established 
market  position  of  the  incumbents  such  as  advertising  costs,  brand  loyalty,  reputation, 
and customer switching costs.   

2.2  How  are  entry,  exit  and  entry  barriers  modelled 

in 

macroeconomics? A theoretical perspective 

The macroeconomic debate on entry barriers is focused on their impact on firm turnover, 
entry-exit dynamics at the industry level, and how these affect innovation incentives, and 
thereby  the  main  macroeconomic  aggregates,  such  as  TFP  and  GDP  growth.  Given  the 
importance  of  firm  entry  and  exit  as  a  link  to  connect  entry  barriers  and  economic 
growth, the following discussion revolves around models of firm dynamics. 

10 For instance, see Ferguson (1974), Fisher (1979), Weizsacker (1980), Gilbert (1989) and Carlton and Perloff 

(1994). 

7 

                                           
The literature modelling entry and exit and their macroeconomic impact is based on the 
Schumpeterian concept of  creative destruction (Schumpeter, (1942)).  11 The  key idea is 
that  growth  is  driven  by  new  innovations  or  product  varieties  that  replace  old 
technologies or varieties. In this sense, entry and exit play an important role since they 
facilitate  innovation  by  transferring  resources  from  less  to  more  productive  firms.  This 
reallocation is known as selection effect and generates between productivity growth. This 
is different from the so-called within productivity growth, which refers to the increase in 
firm productivity because of factors intrinsic to individual firms, such as the acquisition of 
new technologies or restructuring as a response to entrants' competitive pressure.  

There  are  four  main  types  of  models  dealing  with  entry  and  exit:  (i)  passive  learning 
models,  (ii)  active  learning  models,  (iii)  vintage  capital  models,  (iv)  life-cycle  models. 
Jovanovic  (1982)  introduces  the  first  model  of  passive  learning  in  which  heterogeneous 
firms  enter  the  industry,  after  incurring  a  sunk  entry  cost,  without  knowing  their  true 
cost.  Firms  are  subjected  to  productivity  shocks,  learning  over  time  about  true 
productivity.  Efficient  firms  stay  in  the  market,  inefficient  ones  exit.  Survivors  exhibit  a 
larger  size  and  higher  growth  rates  than  exiting  firms  and  the  model  converges  to  an 
equilibrium  featuring  no  entering  and  exiting  of  firms.  The  seminal  contribution  of 
Hopenhayn  (1992)  represents  a  major  step  forward  in  the  literature  on  heterogeneous 
firms  and  entry  and  exit  by  allowing  for  an  equilibrium  in  which  entry  and  exit  are 
positive,  and  by  taking  into  account  industry  characteristics  (e.g.,  entry  barriers, 
demand, and productivity shocks) affecting firm turnover and the industry’s productivity 
distribution.  

In  the  models  of  active  learning,  such  as  Ericson  and  Pakes  (1995)  and  Lentz  and 
Mortensen (2008) a firm enters the market by paying a sunk cost and actively invests in 
innovation to increase its productivity. The success of its investment depends on whether 
its competitors manage to realize successful investments. When the firm is unsuccessful, 
in terms of productivity and relative to the other firms, this leads eventually to the exit of 
the firm from the market.  

Campbell  (1998)  proposes  an  alternative  model  based  on  vintage  capital  in  which  new 
technology is embodied in more  recent vintages.  In these types of models, entry is key 
for the adoption of new technologies and thus high entry barriers hinder their adoption. 
Similarly, in the models of Aghion and Howitt (1992) and Grossman and Helpman (1992) 
potential new firms invest in R&D to upgrade or create new varieties and when successful 
they  enter  the  market,  thereby  replacing  existing  firms.  In  these  models,  innovation 
investments are often equivalent to entry costs.  

Finally, Klepper (1996) models firm entry over the product cycles. In this class of models, 
entry,  exit  and  innovation  depend  on  the  maturity  of  the  industry.  Young  industries 
display  high  turnover  and innovation,  which  slows  down  as  the  maturity  of  the  industry 
increases.  

More  recent  models  with  firm  heterogeneity  include  Peretto  (1996)  and  Impullitti  and 
Licandro (2016). These papers present endogenous growth models where a reduction in 
entry  costs  increases  the  number  of  firms  in  the  industry,  thereby  reducing  (variable) 
price  markups.  This  pro-competitiveness  effect  of  lower  entry  barriers  raises  static 
efficiency,  and  by  increasing  the  market  size  of  surviving  firms,  it  also  promotes  the 
incentives for these firms to invest in innovation, leading to higher aggregate productivity 
growth. 

Regarding  the  effects  of  entry  barriers  on  unemployment,  Felbermayr  and  Prat  (2011) 
show,  in  the  same  modelling  framework  with  heterogeneous  firms,  that  product  market 
regulations  (PMR)  can  condition  average  aggregate  productivity  in  the  economy  by 
sheltering unproductive firms from competition. But these regulations might as well force 
these firms out of the market too. Thus, the sign of the effect depends on the nature of 

11 Schumpeterian growth theory was firstly formalized in a tractable model in the seminal work of Aghion and 
Howitt  (1992).  Similar  models  of  Schumpeterian  growth  have  been  also  developed  by  Segerstrom  et  al. 
(1991) and Grossman and Helpman (1991).  

8 

                                           
the  PMR.  When  regulations  increase  barriers  to  entry,  the  lower  competitive  pressure 
faced  by  entrants  allows  incumbent  less  productive  firms  to  remain  in  the  market, 
thereby  reducing  average  productivity  and  increasing  the  unemployment  rate.  On  the 
other hand, when PMR increase fixed operating costs, less productive firms will be forced 
to leave the market, increasing productivity and reducing unemployment. 

A  common  characteristic  of  these  models  is  that  entry  barriers  are  modelled  as  sunk 
costs,  i.e.  irreversible  costs  that  are  paid  only  once  upon  entry,  thus  affecting  only  the 
entry  decision,  and  that  cannot  be  recovered  in  the  event  of  exit.  That  is,  potential 
entrants  compare  the  cost  of  entry  with  the  present  discounted  value  of  future  profits 
and  enter  the  market  only  if  the  latter  is  greater  or  equal  to  the  initial  cost.  In 
endogenous  growth  models,  entry  costs  are  often  interpreted  as  an  investment  in 
innovation that with some probability will materialize in a new (horizontal innovation) or 
better (vertical innovation) product that may either add to or displace existing ones. 12  13 
In equilibrium, the so-called  free  entry condition holds: firms will be willing to pay sunk 
costs until they are equal to the present discounted value of future profits.   

From a more general theoretical point of view, the relationship between entry rates and 
growth is not straightforward. On the one hand, a decrease in entry barriers (modelled as 
a  decrease  in  sunk  entry  costs)  induces  more  firms  to  enter  the  market,  increasing 
competition and thus tends to positively affect the equilibrium growth rate. On the other 
hand,  it  requires  a  reallocation  of  resources  (labour)  from  incumbents  to  entrants.  This 
reduces the resources available to incumbents, negatively affecting their profitability and 
innovation intensity. This channel thus tends to reduce the aggregate equilibrium growth 
rate  instead.  Moreover,  the  erosion  of  incumbents'  profitability  translates  into  a  lower 
expected profit for entrants impacting negatively on the number of entrants. This trade-
off  is  present  for  instance  in  Acemoglu  and  Cao  (2015)  and  Acemoglu  et  al.  (2015).  In 
particular,  they  find  that  a  subsidy  to  entry  results  in  only  a  marginal  increase  in  U.S. 
GDP,  whereas  the  combination  of  a  policy  that  incentivizes  innovation  by  both 
incumbents  and  entrants  financed  by  a  tax  on  the  operational  costs  of  incumbents  can 
have  relevant  growth  effects  (in  the  order  of  3.1%).  On  the  contrary,  subsidizing  only 
incumbent R&D would significantly reduce growth because it deters entry of high-quality 
firms and therefore reduces the selection effect.  

2.3  Overview  of  the  empirical  literature  on  the  impact  of  entry 

barriers  

The  recent  availability  of  firm-level  data  in  several  countries  has  stimulated  a  growing 
body  of  empirical  literature  that  studies  the  effect  of  entry  barriers  on  firm  entry  and 
growth as well as the impact of policies designed to favour entry and a more competitive 
economy. Using a panel of ten OECD countries Bartelsman et al. (2005) find that about 
20%  of  firms  enter  and  exit  every  year  in  each  country  and  that  these  firms  can  be  of 
different  sizes.    Moreover,  the  authors  observe  that  successful  start-ups  grow  faster  in 
the  U.S.  than  in  Europe  due  to  lower  entry  barriers,  which  leads  in  turn  to  higher 
competition,  productivity  and  growth  of  firms.  Klapper  et  al.  (2006)  working  on  a  panel 
of  71  countries  confirm  a  significant  negative  correlation  between  entry  barriers, 
intended  as  entry  regulations,  and  firm  entry  and  business  density.  This  correlation  is 
especially strong in countries with a stable political climate and good governance.  

12 This branch of the endogenous growth literature focuses on the competitive and dynamic nature of innovation 
driven by firm's incentives to invest in R&D. This approach takes into account the positive externality that 
current  innovations  have  on  future  progress  and  also  the  negative  externality  for  rivals  who  lose  their 
market  share  or  are  forced  to  exit  the  market.  The  latter  externality  is  known  as  the  business  stealing 
effect  which,  when  not  internalized  by  the  private  or  public  sector,  could  lead  to  market  inefficiencies 
raising  important  questions  for  the  policy  maker.  The  business  stealing  effect  is  also  related  to  the 
replacement  effect  discussed  firstly  by  Arrow  (1966).  He  argues  that  when  a  monopolistic  incumbent 
innovates he partly replaces his own monopoly rents. This gives an advantage to a potential entrant who 
will invest more because it does not have pre-existing rents to replace. 

13  In  these  models,  vertical  innovation  can  often  be  interpreted  either  as  process  or  as  product-quality 

innovation. Horizontal innovation can be interpreted as new product varieties.  

9 

                                           
Nicoletti and Scarpetta (2003) are the first to consider the impact of a reduction in entry 
barriers  on  productivity  growth  across  18  OECD  countries  and  23  industries  between 
1984 and 1998. Their focus is on the impact of product market deregulations that affect 
entry and on privatization policies.  In particular, they  estimate that lower  entry barriers 
would  result  in  a  faster  catch-up  with  the  technology  frontier  in  the  manufacturing 
industry,  but  also  that  the  catch-up  is  slower  the  shorter  the  distance  to  the  frontier. 
Hence,  entry  liberalization  increases  productivity  growth  especially  in  countries  that  lie 
relatively far from the technology frontier.  

A  recent  OECD  study  (Bravo-Biosca  et  al.  (2013))  attempts  to  explain  cross-country 
differences  in  firm  growth  dynamics.  Using  data  on  ten  OECD  countries,  the  authors 
observe  that  dynamic  and  growing  industries  are  associated  with  higher  financial 
development,  stronger  competition 
in  the  banking  sector  and  better  contract 
enforcement.  For  our  purposes,  their  findings  imply  that  difficulties  in  access  to  capital 
constitute  a  very  important  barrier  to  entry  and  to  growth  for  start-ups.  Policies  that 
hinder  industry  dynamics  include  strong  employment  protection  legislations  and  high 
R&D fiscal incentives, which constitute advantages for incumbents.     

Overall,  the  empirical  literature  confirms  that  market  deregulation  positively  affects 
productivity  and  employment  (See  Djankov  (2008)).14  However,  the  reach  of  this 
measure depends crucially on country-specific characteristics such as industry structure, 
legislation and institutional make-up. 

3  The macroeconomic impact of Entry Barriers in Member 

States: a quantitative analysis using QUEST III 

QUEST  III  is  a  DSGE  (Dynamic  Stochastic  General  Equilibrium)  model.  It  was  originally 
developed by the Directorate General for  Economic and Financial Affairs (DG  ECFIN) for 
the analysis of fiscal and monetary policies, but the model has ever since been extended 
in  various  ways.  It  has  been  calibrated  for  28  Member  States  as  a  "three  country 
model".15  

We  proceed  by  simulating  two  scenarios  for  each  Member  State.  First,  we  analyse  the 
impact of a reduction of the value of fixed entry costs corresponding to 0.1% of GDP per 
capita.  In  a  second  simulation  exercise,  we  add  to  the  reduction  of  fixed  costs,  a 
reduction of the risk premium for intangibles proportional to the degree  of dispersion of 
this  parameter  in  the  sample  of  28  Member  States.  The  analysis  of  the  differences  in 
outcomes  for  the  individual  Member  States  sheds  light  on  how  different  macroeconomic 
contexts impact on the effectiveness of a reduction in entry barriers and improved access 
to finance.    

However, this approach has a number of drawbacks. First, the current version of QUEST 
III  models  innovation  as  being  dependent  on  R&D  through  the  patents  generated  by 
R&D.  Thus,  it  does  not  account  for  investments  and  innovations  which  do  not  result  in 
patents.  This  is  a  somewhat  limited  view  of  both  R&D  and  innovation.  Second,  for  long 
time horizons the simulations are likely to underestimate the impact of R&D, because the 
model cannot very well account for break-through innovations. Third, the conclusions will 
depend  on  how  well  the  model  reflects  the  transmission  mechanisms  in  the  individual 
Member  States.  Fourth,  some  Member  States  have  already  made  considerable  progress 
on entry barrier reductions and have well developed financial systems. For these Member 
States further improvements are likely to be small due to low marginal returns of further 

14 Djankov (2008) reviews 201 papers published in refereed journals studying the link between entry regulation 
and entrepreneurship, productivity and corruption. He concludes that there is an important and statistically 
significant positive relationship between deregulation, on one side, and entry rates and productivity, on the 
other.  

15 i.e. the model distinguishes between the particular Member State being modelled, the rest of the Euro Area 

(EA) and the rest of the world outside the EA (including the rest of the EU).  

10 

 
                                           
 
improvements. Fifth, there may be a discrepancy between the estimated entry barriers in 
the  model  and  the  actual  entry  costs  faced  by  individual  firms  which  depend  on  size, 
geographical location and other country specific characteristics which the model does not 
account for. Still, with these caveats in mind, as we are mainly interested in highlighting 
the  macroeconomic  factors  impacting  the  effectiveness  of  entry  barrier  reductions  in 
combination with improved access to finance, the cross-country comparison made below 
is  interesting,  since,  as  also  pointed  out  in  Bravo-Biosca  et  al.  (2013),  it  highlights  the 
potential for further improvements across countries.   

The  sections  below  discuss  how  entry  barriers  are  modelled  in  QUEST  III  and  the 
mechanisms through via which a shock to entry barriers impacts GDP, employment and 
productivity. The typology and magnitude of entry barriers are country-specific and often 
a  heritage  of  countries'  past  legislations,  economic  structures  and  institutions.  As  a 
consequence, to understand their impact on entrepreneurship and industry dynamism it 
is  necessary  to  frame  them  in  the  context  of  each  Member  State.  In  the  next 
subsections,  we  discuss  and  analyse  the  main  mechanisms  behind  the  propagation  of 
entry barriers shocks as well as the results of simulating the macroeconomic impact of a 
policy reform addressed to reduce  such barriers.  We then provide an explanation of the 
cross-country differences based on the fundamentals of each Member States' economy.  

3.1  Entry barriers and risk premia in QUEST III 

As The treatment of entry barriers in QUEST III is very similar to the approach followed 
in  the  entry  and  exit  models  discussed  in  the  previous  section.  In  particular,  QUEST  III 
models  entry  barriers  as  sunk  costs  paid  by  intermediate  firms  upon  entry  (see  for 
instance, Jovanovic (1982) Hopenhayn (1992), Ericson and Pakes (1995) and Lentz and 
Mortensen (2008)). This is a good way to represent the administrative burdens that firms 
bear  upon  entry,  but  it  is  only  a  simplified  representation  of  entry  barriers  as  such, 
because  it  does  not  explicitly  consider  issues  such  as  market  structure  or  the 
technological advantages of incumbents.16  

Access  to  capital  is  modelled  separately  from  the  cost  of  entry.  Start-ups  are  often 
constrained  by  limited  access  to  capital,  which  impacts  negatively  on  their  birth  rate 
(European Commission, (2013)). This is particularly severe in some Member States, such 
as Malta, Lithuania and Romania. Hence, an improved access to finance could in principle 
reinforce the impact  of  a reduction in entry barriers.  In the  case  of  QUEST  III,  financial 
constraints can be partially captured by a risk premium on intangibles. This risk premium 
can be interpreted as a proxy  of a  country's financial development: when the degree  of 
financial development in a country is low (high) an investor has few (many) opportunities 
to  diversify  their  portfolio,  and  thus,  the  risk  borne  by  them  are  higher  (lower).  This  is 
reflected in a high (low) value of the (calibrated) risk premium.  

In QUEST III, both entry costs and the risk premium are modelled as sunk costs that are 
ultimately  borne  by  intermediate  good  firms  in  equilibrium.  Changes  in  these  two 
parameters  show  commonalities  in  their  transmission  mechanisms.  A  reduction  of  entry 
barriers  stimulates  entry  in  the  intermediate  sector  and  the  demand  for  new  patents. 
This  leads  to  an  increase  of  R&D  activities  and  hence  a  reallocation  of  high-skilled 
workers  from  the  production  sector  to  the  R&D  sector,  which  explains  a  short-term 
reduction  in  GDP  and  a  long  term  increase  in  real  wages.  Over  time,  the  enhanced 
productivity  effect  of  heightened innovation  outweighs  the  effect  of  the  outflow  of  high-
skilled  workers,  yielding  a  net  increase  in  TFP  and,  hence,  GDP.  Employment  reacts 
positively  on  impact  due  to  a  higher  demand  for  high-skilled  workers  from  the  R&D 
sector  and  then,  as  real  wages  increase,  the  size  of  this  effect  gets  progressively 
reduced. 

The  key  equation  via  which  these  two  parameters  enter  the  model  is  the  free  entry 
condition  of  intermediate  firms.  Free  entry  means  that  intermediate  firms  will  enter  the 

16 Out of all the definitions of entry barriers presented in the previous section, this definition is arguably more in 

line with Stigler's (1968) definition, 

11 

                                           
market and thus buy new patents until the value of profits in a given period  equals the 
entry costs plus the net value of patents. That is,  

𝑃𝑅𝑡

𝑥 =

𝐴
𝐴𝑃𝑡
𝑖𝑡
𝐷𝐸𝐹𝑡

+ 𝐹𝐶𝐴(𝑖𝑡

𝐴 + 𝐶𝑡

𝐴), 

𝑥,  the  price  for  licencing  a  patent,  𝑃𝑡

where  the  relevant  variables  are:  the  level  of  entry  costs,  𝐹𝐶𝐴,  the  profit  earned  by 
𝐴,    the  GDP  deflator,  𝐷𝐸𝐹𝑡  and  the 
design/firm  x,  𝑃𝑅𝑡
𝐴.17  This  equilibrium  equation  shows  that  high  entry 
user  cost  of  intangible  capital,  𝑖𝑡
barriers must be compensated for by high expected profits or by a lower licencing price 
for  the  patent,  or  by  a  combination  of  both,  for  the  decision  to  enter  the  market  to  be 
economically feasible. 

Profits of intermediate firms are positively related to the inverse of the mark-up charged 
by final good producers, 𝜂𝑡

𝑦, and negatively related to the numbers of patents issued, 𝐴𝑡: 

𝑃𝑅𝑡

𝑥 = (

1−𝜃

𝜃

)

𝑐𝑥𝑡
𝑘𝑃𝑡
𝑖𝑡
𝐷𝐸𝐹𝑡

= (1 − 𝜃) 𝑝𝑡

𝑥𝑥𝑡
𝐷𝐸𝐹𝑡

= (1 − 𝜃)

𝑦(1−𝛼)(𝑌𝑡+𝐹𝐶𝑌)
𝜂𝑡
𝐴𝑡 𝐷𝐸𝐹𝑡

, 

where  𝜃  is  the  elasticity  of  substitution  between  intermediate  good  inputs  in  the  final 
good  production  function,  𝛼  is  the  fixed-cost-adjusted  elasticity  of  labour  in  final  good 
technology, 𝑌𝑡 is aggregate output from the final good sector,  𝐹𝐶𝑌 are fixed costs in final 
𝑐  is  the  price  index  of  final  goods,  and 
good  production,  𝑖𝑡
𝐷𝐸𝐹𝑡  is  the  GDP  deflator  in  year  t.  As  each  intermediate  firm  buys  only  one  patent  to 
produce  one  intermediate  product,  the  number  of  patents  equates  the  number  of 
intermediate  firms  and  represents,  together  with  the  mark-up,  a  measure  of  market 
competition.  It  follows  from  the  previous  equation  that  the  more  concentrated  markets 
are, the higher the profits for each intermediate producer.    

𝑘  is  the  user  cost  of  capital,  𝑃𝑡

The price of patents, determined optimally in the R&D sector, is positively related to the 
unit labour cost of researchers and inversely related to the elasticity of R&D with respect 
to research labour,  𝜆: 

𝐴 =

𝑃𝑡

𝐷𝐸𝐹𝑡
𝜆

𝑊𝑡

𝐻𝐿𝐴,𝑡
𝛥𝐴𝑡

+   𝑀𝐴𝐷𝐽𝑡, 

𝜑 𝐿𝐴𝑡

𝜆  is the new knowledge (patents) produced in period t using research 
where 𝛥𝐴𝑡 = 𝜈𝑡𝐴𝑡−1
labour, 𝐿𝐴,𝑡, and the domestic stock of knowledge,  𝐴𝑡, with 𝜈𝑡 representing the efficiency 
𝐻the wage paid to high-skilled workers and where 
level of the R&D production function, 𝑊𝑡
𝑀𝐴𝐷𝐽𝑡 stands for the marginal adjustment costs incurred by the firm when employing one 
more  researcher.18  Lastly,  φ  represents  the  elasticity  of  the  current  domestic  stock  of 
knowledge with respect to the past of domestic stock of knowledge. 

An important variable affected by the risk premium is the user cost of intangible capital, 
𝐴.  
𝑖𝑡

𝐴 =
𝑖𝑡

(1 − 𝜏 𝐴)(1 + 𝑖𝑡 − (1 + 𝑔𝑃𝐴)(1 + 𝜋𝑡+1

𝐴 )(1 − 𝛿 𝐴)) − 𝑡𝐾𝛿 𝐴

(1 − 𝑡𝐾)

+ 𝑟𝑝𝑡

𝐴 + 𝜀𝑡

𝑟𝑝𝐴

𝑟𝑝𝐴

𝐴  and  𝜀𝑡

  represent  the  risk  premium  and  the  shock  associated  with  it, 
where  𝑟𝑝𝑡
respectively. It follows that a positive shock to the risk premium impacts the user cost of 
capital  positively  and  linearly.  In  the  combined  entry  barrier  and  risk  premium  shock 
discussed in section 3.2.2. below, the shock parameter 𝜀𝑡

 is lowered. 

𝑟𝑝𝐴

Substituting the expressions for the profits of intermediate firms, the price of patents and 
the knowledge production function into the free entry condition, we can rewrite the latter 
as follows: 

𝐴 is an auxiliary term related to the change of the price of patents over time. 

17 𝐶𝑡
18  The  efficiency  level  𝜈𝑡  depends,  among  other  things,  on  the  foreign  stock  of  R&D  of  each  country's  main 

trading partners. 

12 

 
 
                                           
(1 − 𝜃)

𝑦(1−𝛼)(𝑌𝑡+𝐹𝐶𝑌)
𝜂𝑡
𝐴𝑡 𝐷𝐸𝐹𝑡

= 𝑖𝑡

𝐴 (

𝐻𝐿𝐴,𝑡
𝑊𝑡
𝜑
𝜆 𝜈𝑡𝐴𝑡−1

𝜆 +
𝐿𝐴𝑡

 𝑀𝐴𝐷𝐽𝑡
𝐷𝐸𝐹𝑡

) + 𝐹𝐶𝐴(𝑖𝑡

𝐴 + 𝐶𝑡

𝐴). 

This equation shows the most important structural parameters and variables affecting the 
net impact and transmission of shocks to entry barriers, namely,  fixed entry costs,  FCA, 
the  elasticity  of  R&D  with  respect  to  research  labour,  λ,  the  efficiency  of  the  R&D 
production function, 𝜈, and the share of high skilled workers devoted to research, 𝐿𝐴,𝑡.  

The structural parameters of the model are of particular importance as they capture the 
fundamental or deep characteristics of each economy. They are time invariant and can be 
shocked to understand how the variables in the economy would change as a reaction to a 
change in the economic fundamentals. For instance, a proportional shock to  entry costs 
will  impact  Member  States  unevenly  and  the  differences  can  be  explained  in  turn  by 
differences  in  the  values  of  structural  parameters.  Hence,  the  understanding  of  such 
parameters  is  key  to  explaining  the  model  transmission  mechanisms  and  cross-country 
differences.  

Entry costs are directly calibrated following the methodology developed by Djankov et al. 
(2002), who estimate the costs that new firms need to incur before starting to operate. 19 
In  contrast,  the  calibration  of  the  parameters  of  the  knowledge  production  function 
results from the restrictions imposed on the equilibrium equations of the model to ensure 
the existence of a balanced growth path. In particular, λ is obtained from available data 
on  the  wage  share  of  R&D  labour  in  total  R&D  spending  whereas  𝜈𝑡  is  directly  derived 
from  the  knowledge  production  function  after  estimating  the  other  elasticities, 
normalizing  the  initial  stock  of  domestic  and  international  knowledge,  calibrating  the 
growth rate of ideas and initializing the share of research labour.20  

3.1.1  QUEST III simulations 

In QUEST III, high entry barriers preclude some intermediate good producing firms from 
entering  the  market.  This  results  in  a  low  demand  for  patents  and  a  low  level  of 
intangible  capital.  As  a  result,  the  marginal  productivity  of  intangible  capital  is  higher 
than in an equilibrium with more patents, due to decreasing returns to the accumulation 
of ideas. Ceteris paribus, a shock that reduces entry barriers yields higher output effects 
the higher the marginal productivity of intangible capital, i.e. the higher the initial level of 
entry  barriers.  A  similar  argument  holds  for  the  share  of  research  labour.  High  entry 
barriers are associated with a small share of labour devoted to research and hence with 
relatively  high  marginal  productivity  of  labour,  again  owing  to  diminishing  returns.  This 
also  means  that  the  effect  on  output  will  be  larger  when  entry  barriers  are  reduced.  In 
both  cases  the  output  effect  is  amplified  by  higher  R&D  efficiency  levels,  𝜈,  and  higher 
elasticities of R&D with respect to researchers. These considerations constitute a starting 
point  to  understand  cross-country  differences  in  the  propagation  of  shocks  to  entry 
barriers. Differences in the magnitude of impacts are better understood by investigating 
the  role  played  by  the  different  variables  and  parameters  involved.  Table  1  reports  the 
values of key structural parameters and the initial steady state values of key variables for 
each Member State. 

Table 1. Cross-country values of selected parameters and initial steady state values of 
key variables 

19  In  particular,  the  authors  carry  out  a  very  thorough  data  work  to  construct  a  measure  of  the regulation  of 
entry  (expressed  in  GDP  per  capita  terms)  across  a  very  large  number  of  countries  based  on  costed 
measures of the total number of procedures and the time it takes to complete them as well as the actual 
administrative costs incurred (e.g., registration fees). For a detailed discussion, please see Djankov et al. 
(2002). 

20  For  a  more  detailed  explanation  of  the  parameter  calibration  and  estimation  procedure,  see  D'Auria  et  al. 

(2009).  

13 

 
 
 
                                           
𝐹𝐶𝐴 

𝑟𝑝𝐴 

𝜆 

𝜈 

𝐿𝐴,0 

R&D 
intensity 
(% GDP) 

0.063 

0.006 

0.398 

0.213 

0.034 

0.012 

0.060 

0.005 

0.465 

0.309 

0.027 

0.010 

0.054 

0.075 

0.645 

1.282 

0.009 

0.004 

0.144 

0.057 

0.551 

1.077 

0.006 

0.002 

0.100 

0.015 

0.496 

0.484 

0.022 

0.010 

0.048 

0.006 

0.496 

0.298 

0.032 

0.012 

0.011 

0.003 

0.473 

0.255 

0.036 

0.016 

0.022 

0.035 

0.482 

0.416 

0.016 

0.007 

0.058 

0.044 

0.652 

1.301 

0.010 

0.004 

0.090 

0.044 

0.777 

1.745 

0.014 

0.007 

0.049 

0.0009 

0.441 

0.231 

0.036 

0.015 

0.019 

0.007 

0.526 

0.404 

0.026 

0.010 

AT 

BE 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

0.064 

0.067 

0.672 

1.598 

0.009 

0.004 

HU 

0.084 

0.028 

0.595 

0.776 

0.016 

0.006 

IE 

IT 

LU 

LT 

LV 

MT 

NL 

PL 

PT 

RO 

SE 

SI 

SK 

0.016 

0.035 

0.569 

0.580 

0.017 

0.008 

0.153 

0.021 

0.777 

1.752 

0.015 

0.007 

0.046 

0.031 

0.594 

0.659 

0.014 

0.008 

0.015 

0.045 

0.582 

0.751 

0.011 

0.006 

0.030 

0.073 

0.738 

2.027 

0.008 

0.005 

0.179 

0.043 

0.773 

2.091 

0.009 

0.006 

0.057 

0.017 

0.547 

0.431 

0.022 

0.011 

0.196 

0.029 

0.542 

0.738 

0.011 

0.004 

0.028 

0.034 

0.773 

1.700 

0.015 

0.007 

0.041 

0.069 

0.879 

7.658 

0.004 

0.002 

0.025 

0.0003 

0.335 

0.152 

0.040 

0.014 

0.016 

0.008 

0.477 

0.331 

0.028 

0.011 

0.045 

0.046 

0.685 

1.439 

0.010 

0.005 

UK 

0.013 

0.015 

0.495 

0.363 

0.019 

0.010 

14 

 
 
 
 
3.1.2  Policy scenario I: lower entry costs 

The first policy scenario, simulated individually for  each Member State, is a  reduction in 
the  value  of  fixed  entry  costs  for  intermediate  firms  equal  to  0.1%  of  GDP.21  In  each 
simulation,  the  shock  is  applied  to  the  fixed  costs  of  a  given  country  only;  the  other 
Member  States  and  the  rest  of  the  world  are  only  indirectly  affected  via  trade  and 
financial links.22 The following graphs show the impulse response functions (IRF) of GDP, 
employment and TFP for the 28 Member States.  

Figure 3. Response of GDP to a reduction in fixed costs equal to 0.1% of GDP 

0.018

0.016

0.014

0.012

0.01

0.008

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.006

0.004

0.002

0

-0.002

0.018

0.016

0.014

0.012

0.01

0.008

0.006

0.004

0.002

0

-0.002

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

AT

BE

BG

CY

CZ

DE

DK

IE

IT

LT

LU

LV

MT

NL

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.018

0.016

0.014

0.012

0.01

0.008

0.006

0.004

0.002

0

-0.002

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.018

0.016

0.014

0.012

0.01

0.008

0.006

0.004

0.002

0

-0.002

EE

EL

ES

FI

FR

HR

HU

PL

PT

SE

RO

SI

SK

UK

21  Even  though  the  original  entry  barrier  costs  are  calculated  in  GDP  per  capita  terms  in  Djankov  (2008),  all 
quantities in the model are expressed in terms of GDP (which is the numeraire). Hence the reason for the 
choice of the size of the shock in GDP terms instead of GDP per capita. 

22 The version of QUEST III model that is used for the simulations is a three-country model characterizing an 
individual  Member  State  versus  EU27  and  the  rest  of  the  world.  Thus,  it  is  not  possible  to  study  cross-
country interactions or spillovers generated by common deregulation policies.  

15 

 
 
 
 
 
                                           
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 4. Response of aggregate employment to a reduction in fixed costs equal to 0.1% of GDP 

0.0014

0.0012

0.001

0.0008

0.0006

0.0004

0.0002

0

0.003

0.0025

0.002

0.0015

0.001

0.0005

0

0.016

0.014

0.012

0.01

0.008

0.006

0.004

0.002

0

0.002

0.0018

0.0016

0.0014

0.0012

0.001

0.0008

0.0006

0.0004

0.0002

0

AT

BE

BG

CY

CZ

DE

DK

IE

IT

LT

LU

LV

MT

NL

0.0025

0.002

0.0015

0.001

0.0005

0

-0.0005

Figure 5. Response of TFP to a reduction in fixed costs equal to 0.1% of GDP  

AT

BE

BG

CY

CZ

DE

DK

0.014

0.012

0.01

0.008

0.006

0.004

0.002

0

16 

PL

PT

RO

SE

SI

SK

UK

EE

EL

ES

FI

FR

HR

HU

EE

EL

ES

FI

FR

HR

HU

 
 
 
 
 
 
 
 
0.016

0.014

0.012

0.01

0.008

0.006

0.004

0.002

0

IE

IT

LT

LU

LV

MT

NL

0.016

0.014

0.012

0.01

0.008

0.006

0.004

0.002

0

PL

PT

RO

SE

SI

SK

UK

The  IRFs  above  display  trajectories  that  are  consistent  with  the  previously  discussed 
mechanics of the model and show some cross-country differences. In all Member States, 
upon  impact,  employment  and  TFP  react  positively  and  then  progressively  converge  to 
permanently higher levels, due to the reallocation of resources towards the R&D sector, 
which  fosters  higher  growth  in  the  transition  back  to  the  steady  state.  GDP  does  not 
necessarily increase upon impact for the reasons mentioned above, but follows the same 
progressive upward-sloped path. 

From  Table  1  we  can  observe  that  Poland,  Malta  and  Italy  exhibit  the  highest  entry 
barriers  among  all  countries,  while  also  characterized  by  very  low  R&D  intensity  and 
initial  low  quantity  of  researchers.  The  high  marginal  return  on  intangible  capital  and 
researchers' productivity result in a lower short term reduction in GDP and in a long term 
trajectory  characterised  by  a  higher  slope  compared  to,  for  example,  Slovenia  and 
Portugal. As another example, the efficiency level of the Italian R&D production function, 
coupled  with  a  relatively  high  value  of  the  share  of  researchers  in  total  labour, 
constitutes an advantage, as comparatively fewer researchers are needed to increase the 
production of knowledge, thereby relaxing the pressure on wages and sustaining a higher 
level  of  employment  also  in  the  long  run.  Nevertheless,  due  to  comparatively  higher 
wages  in  Italy,  the  Italian  TFP  reacts  less  than  the  Maltese  and  the  Polish  leading  to  a 
slightly higher GDP response for Poland and Malta in the very long-run. 

Denmark is characterised by the lowest level of fixed costs and the highest share of initial 
research labour and R&D intensity in the sample. Given this leadership position, a shock 
to fixed costs has only a marginal impact on GDP, which exhibits an increase of 0.003% 
after  20  years  from  the  initial  shock.  Total  employment  reacts  positively  upon  impact, 
mainly due to an increase in the share of employed low and medium skilled-workers. The 
long-term effect on employment is negligible, increasing around 0.001% with respect to 
the  baseline  scenario.  The  initial  high  share  of  R&D  employment  mitigates  the  negative 
impact  on  GDP  resulting  from  the  reallocation of  high-skilled labour  from  the  final  good 
sector to the R&D sector. This also implies a comparatively moderate impact on TFP.   

GDP  and  employment  in  Slovenia,  Finland,  Belgium,  France  and  the  Netherlands  react 
only marginally to a shock on entry costs. Similar trajectories are displayed also by Czech 
Republic,  despite  its  higher  entry  costs.  In  this  case,  the  reaction  to  the  shock  is 
hampered by a comparatively higher risk premium on investment in intangibles.  

Portugal and Ireland, characterized by both fairly low entry costs and fairly low shares of 
research labour, react strongly upon impact, displaying negative deviations of GDP from 
baseline  in  the  short  run.  However,  their  long  run  GDP  trajectory  is  steeper  than  the 
Danish one, while TFP and employment react similarly. The effect of the positive long-run 
productivity  effect  of  a  reallocation  of  high-skilled  labour  towards  the  research  sector, 
which causes the initial drop in GDP, is hindered by a relatively high risk premium. This 
slows  down  TFP  growth,  but  sustains  GDP,  at  least  in  the  short-run,  as  the  final  sector 

17 

 
 
 
still benefits from a relatively higher number of skilled-workers whose recruitment in the 
R&D sector is partially blocked by high risk premia.  

Slovakia and Lithuania have relatively low entry barriers and very low R&D intensity and 
labour dedicated to research. On the other hand, they have a relatively high elasticity of 
R&D with respect to research labour and also display a relatively strong efficiency of the 
R&D  production  function.  Consequently,  the  transmission  of  the  shock  is  amplified  and 
exhibits  trajectories  similar  to  Malta  and  Poland,  which  start  with  much  higher  entry 
costs. The same reasoning holds for Spain, whose economy is characterized by fairly high 
entry  costs,  a  fairly low  share  of  researchers  and  R&D  intensity,  but  an  overall  efficient 
R&D technology. 

Germany has a robust R&D sector with a high initial R&D intensity and share of research 
labour.  This  is  reflected  in  the  calibration  of  the  production  function  of  R&D  (i.e.  high  λ 
and 𝜈). A reduction in fixed costs, which are higher than the ones prevailing in Denmark, 
results in a positive long term impact on  GDP, TFP and employment.  This is particularly 
strong  after  20  years  from  the  initial  shock  when  the  trajectories  of  TFP  and  GDP 
becomes  the  steepest  among  all  countries,  owing  to  the  more  important  role  played  by 
structural factors (such as the production technology) in the long-term.  

Romania is a particular case, with the lowest R&D intensity and share of research labour 
employed  in  the  R&D  sector  together  with  fairly  low  initial  entry  costs.  A  reduction  in 
entry barriers boosts entry of intermediate good firms and the demand for new designs. 
The  high  marginal  returns  of  research  labour,  combined  with  a  calibration  of  the  R&D 
production function that indicates an efficient use of the inputs used in R&D production, 
draws many skilled workers from the final good sector to the research sector. However, 
GDP  reacts  positively  already  in  the  short  run  as  the  strong  short-run  increase  in  TFP 
offsets  the  reallocation  effect.  As  TFP  increases,  more  low  and  medium-skilled  workers 
are hired in the final good sector, and total employment reacts comparatively more than 
in other countries. Over time, upward pressure on wages  substantially erodes the initial 
gains  in  employment.  This  process  renders  the  variation  of  employment  in  Romania  in 
the  very  long-run  still  higher  than  in  the  baseline  scenario,  albeit  it  reaches  the  lowest 
deviation with respect to baseline among all countries analysed. 

3.1.3  Policy scenario II: lower entry costs and risk premia 

The  second  policy  scenario  simulated  in  QUEST  III  combines  a  reduction  in  fixed  entry 
costs for intermediate firms equivalent to 0.1% of GDP (scenario I), with reduction in the 
risk  premium  for  intangibles  that is  proportional to  the  degree  of  dispersion  of  its  value 
across  the  sample  of  countries.23  24  As  before,  the  shocks  are  applied  to  each  Member 
State  individually,  while  the  other  Member  States  and  the  rest  of  the  world  stay  the 
same.  The  following  graphs  (Figure  6-8)  show  the  impulse  response  functions  of  GDP, 
employment and TFP for the 28 countries. 

Figure 6. Response of GDP to a reduction of fixed costs in the intermediate goods sector equal to 
0.1% of GDP and a reduction in the risk premium for intangibles proportional to the degree of the 
sample's dispersion. 

23  Intangibles  are  purchased  by  intermediate  firms  and  hence  a  reduction  of  the  risk  premium  can  be 

interpreted as easier access to finance for start-ups.  

24 In particular, the  reduction applied equals the percentage of the maximum value for the risk premium that 
the  difference  between  the  maximum  and  minimum  values  in  the  sample  represents.  This  yields  a 
reduction of about 1% of the initial level of the risk premia in each country. 

18 

 
                                           
0.4

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

-0.05

0.35

0.3

0.25

0.2

0.15

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.1

0.05

0

-0.05

AT

BE

BG

CY

CZ

DE

DK

IE

IT

LT

LU

LV

MT

NL

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.45

0.4

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

-0.05

0.3

0.25

0.2

0.15

0.1

0.05

0

-0.05

EE

EL

ES

FI

FR

HR

HU

PL

PT

RO

SE

SI

SK

UK

Figure 7. Response of aggregate employment to reduction in fixed costs in the intermediate goods 
sector equal to 0.1% of GDP and a reduction in the risk premium for intangibles proportional to the 
degree of the sample's dispersion. 

19 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.035

0.03

0.025

0.02

0.015

0.01

0.005

0

0.07

0.06

0.05

0.04

0.03

0.02

0.01

0

AT

BE

BG

CY

CZ

DE

DK

IE

IT

LT

LU

LV

MT

NL

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.07

0.06

0.05

0.04

0.03

0.02

0.01

0

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.06

0.05

0.04

0.03

0.02

0.01

0

EE

EL

ES

FI

FR

HR

HU

PL

PT

RO

SE

SI

SK

UK

Figure 8. Response of TFP to a 0.1% reduction in fixed costs in the intermediate goods sector 
equal to 1% of GDP and a reduction in the risk premium for intangibles proportional to the degree 
of the sample's dispersion. 

20 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

-0.05

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.3

0.25

0.2

0.15

0.1

0.05

0

AT

BE

BG

CY

CZ

DE

DK

IE

IT

LT

LU

LV

MT

NL

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

e
n

i
l

e
s
a
b
m
o
r
f

.
f
f
i
d
%

0.25

0.2

0.15

0.1

0.05

0

EE

EL

ES

FI

FR

HR

HU

PL

PT

RO

SE

SI

SK

UK

Given  the  similar  nature  of  the  two  shocks,  in  terms  of  the  components  of  the  model 
affected  by  them,  the  impact  of  the  combined  shock  can  be  interpreted  as  an 
amplification of the shock to fixed costs only. As discussed before, this leads  not only to 
considerable gains in the long term for all Member States but also to asymmetries in the 
distribution of those gains across countries and over time. Table 2 reports the differences 
in  GDP  gains  between  the  second  policy  scenario  and  the  first  policy  scenario,  which 
features  only a reduction of entry costs.  In each year, the three countries that  gain the 
least  from  adding  a  shock  on  the  risk  premium  are  highlighted  in  red,  while  the  three 
countries that gain the most are highlighted in bold.  

A  number  of  observations  follow  from  inspection  of  Table  2.  First,  as  expected,  in  the 
long  run  all  Member  States  experience  higher  economic  returns  to  the  joint  shock 
compared  to  the  mere  reduction  of  fixed  costs.  This  holds  because  both  a  reduction  in 
fixed entry costs and risk premia incentivise R&D investment and hence economic growth 
ultimately.  Second,  in  the  short  run,  however,  the  effect  of  the  joint  shock  on  GDP  is 
lower  than  the  effect  of  only  reducing  entry  costs  in  certain  Member  States,  including 
Ireland,  Lithuania,  Portugal  and  Slovakia.  This  short-run  behaviour  points  to  the 
existence  of  greater  incentives  in  these  countries  to  forego  final  good  production  in 
favour of increased R&D employment and hence R&D production, owing to a combination 

21 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
of  factors,  including  relatively  low  high-skilled  employment  levels  in  the  R&D  sector. 
Third,  Bulgaria,  Croatia,  Cyprus,  Malta  and  Poland  are  among  the  countries  that  exhibit 
the  highest  comparative  gains  under  the  second  scenario,  on  the  back  of  higher  risk 
premia  and  a  less  developed  R&D  sector.  Fourth,  Spain  is  the  only  Member  State  that 
experiences lower impacts on income in the short run, but ranks among the top three of 
highest impacts in the long run in the combined shock scenario. The factors behind this 
dissimilar  behaviour  in  the  short  vis-a-vis  the  long-run  horizon  coincide  with  the  ones 
underlined  in  section  3.1.1  (namely,  fairly  high  entry  costs,  a  relatively  low  share  of 
researchers  and  R&D  intensity,  and  an  overall  efficient  R&D  technology),  with  the 
addition  of  a  relatively  high  starting  level  of  the  risk  premium  (9th  highest).  Spain  thus 
exemplifies the (optimal) process of increasing investment in innovation in the short-to-
medium  term,  which  comes  at  the  expense  of  foregoing  economic  growth  in  those 
periods, but in exchange for higher GDP levels relative to other countries in the long run. 

Table 2. Percentage point differences in GDP impacts between policy scenario II and 
policy scenario I at different time horizons 

2016 

2017 

2018 

2019 

2020 

2025 

2035 

2065 

2115 

AT 

0.001691 

-0.00282 

-0.00343 

-0.00189 

0.000827 

0.017022 

0.041899 

0.076586 

0.087679 

BE 

0.000421 

-0.00271 

-0.00252 

-0.00057 

0.002187 

0.016441 

0.035838 

0.057369 

0.06174 

BG 

-0.00191 

-0.00021 

0.021018  0.050496  0.081445 

0.196 

0.283988  0.338048  0.346714 

CY 

0.004674  0.009106  0.025936  0.048512 

0.072352  0.162454  0.237228 

0.295076 

0.309996 

CZ 

0.000352 

-0.00897 

-0.00726 

-0.00036 

0.008622 

0.050535 

0.096411 

0.132226 

0.138685 

DE 

-0.00079 

-0.0066 

-0.00753 

-0.00561 

-0.00228 

0.016657 

0.045072 

0.090041 

0.127986 

DK 

0.001507 

-0.00095 

-0.00082 

0.00047 

0.002315 

0.012224 

0.026448 

0.043487 

0.048051 

EE 

-0.00171 

-0.0078 

-0.00207 

0.009591 

0.023779 

0.090545 

0.169142 

0.234395 

0.241569 

EL 

0.003791 

-0.00311 

0.002837 

0.017002 

0.034697 

0.111187 

0.181962 

0.241315 

0.258566 

ES 

0.003136 

-0.01538 

-0.00779 

0.01709 

0.048743 

0.171811  0.254928  0.322792  0.349929 

FI 

5.19E-05 

-2.8E-05 

-4.3E-05 

-2.3E-05 

1.9E-05 

0.000296 

0.000732 

0.001342 

0.001552 

FR 

0.003044 

-0.00492 

-0.00801 

-0.00763 

-0.00528 

0.011499 

0.036431 

0.071286 

0.093077 

HR 

0.017427  0.010536  0.031118  0.061738  0.093339  0.204677  0.289316  0.351308  0.368111 

HU 

0.00486 

-0.0038 

0.004345 

0.019097 

0.035556 

0.10201 

0.162948 

0.202272 

0.209588 

IE 

IT 

-0.0054 

-0.01558 

-0.00982 

0.00449 

0.022274 

0.10244 

0.184761 

0.242026 

0.247993 

0.000607 

-0.00935 

-0.00655 

0.004278 

0.018271 

0.076763 

0.12686 

0.172735 

0.195712 

LT 

-0.00512 

-0.0117 

-0.00459 

0.009208 

0.025322 

0.094742 

0.161814 

0.205183 

0.209663 

LU 

0.00031 

0.001606 

0.011145 

0.024703 

0.039603 

0.102208 

0.160169 

0.187988 

0.18708 

LV 

-0.00249 

-0.00374 

0.013447 

0.039458 

0.067723 

0.16921 

0.23214 

0.270877 

0.278135 

MT 

0.000689 

0.003413  0.026618  0.05651  0.086014  0.179107 

0.229133 

0.25521 

0.258175 

NL 

0.001123 

-0.00721 

-0.0059 

0.00052 

0.009364 

0.053474 

0.104809 

0.147959 

0.155604 

22 

 
 
 
PL 

0.008032 

0.00252 

0.01248 

0.02847 

0.045729 

0.114646 

0.181329 

0.232934 

0.245308 

PT 

-6.4E-05 

-0.01728 

-0.01693 

-0.00503 

0.01188 

0.086109 

0.146803 

0.191566 

0.204176 

RO 

0.006417  0.003792 

0.02228 

0.047767 

0.072163 

0.13363 

0.156927 

0.181096 

0.189328 

SE 

SI 

-2E-05 

-0.00047 

-0.00205 

-0.00396 

-0.00567 

-0.00898 

-0.00827 

-0.006 

-0.00477 

-0.0002 

-0.00603 

-0.00645 

-0.00385 

0.000211 

0.02179 

0.05042 

0.080854 

0.086653 

SK 

-0.00283 

-0.00477 

0.006674 

0.024331 

0.043736 

0.118158 

0.172886 

0.200421 

0.202951 

UK 

-0.00112 

-0.00839 

-0.00918 

-0.00615 

-0.00122 

0.026289 

0.065711 

0.117035 

0.143501 

4   Concluding Remarks 

After  the  launch  of  the  Lisbon  Strategy  in  2000  and  subsequent  actions  such  as  the 
Entrepreneurship 2020 Action Plan, several Member States have introduced measures to 
support entrepreneurship, the creation of new firms and the improvement of productivity 
among  existing  firms,  including  addressing  the  barriers  that  firms  face  for  entering  new 
markets.  This  paper  has:  (i)  framed  these  policy  interventions  in  a  macroeconomic 
context, briefly reviewing the definition of entry barriers, and the macroeconomic models 
and mechanisms through which entry barriers affect GDP, productivity, and employment; 
(ii) quantified the impact of a reduction of entry barriers in  the 28 Member States using 
the European Commission's QUEST III model. 

The  simulations  obtained  with  QUEST  III  show  that  policies  aimed  at  reducing  entry 
barriers  should  be  understood  and  conceived  as  long-term  policies.  The  positive  impact 
on GDP, employment, and productivity becomes sizeable only in the medium to long run. 
Moreover,  in  the  light  of  the  model's  results,  a  mix  of  policy  interventions  combining  a 
reduction  of  administrative  costs  with  improved  access  to  finance  achieves  greater 
benefits  for  all  Member  States  compared  to  implementing  them  individually.  Long  run 
effects  seem  stronger  in  Member  States  with  comparatively  less  developed  R&D  and 
innovation systems and financial sectors.  This points to the need for increased efforts to 
facilitate investment in innovation in these countries in order to maximise the impacts of 
such long-term policies.  

An  important  caveat  is  that  public  policy  cannot  reduce  all  types  of  entry  barriers,  as 
many  barriers  are  a  result  of  inherent  product  features  and  competitive  behaviour  of 
firms as well as countries' past legislations and institutional framework. However, policy 
makers  can  target  regulations  including  the  application  of  competition  laws,  thereby 
mitigating  entry  barriers.  In  some  cases  of  heavily  regulated  markets,  such  as  network 
industries,  public  policy  can  also  play  a  crucial  role  in  opening  up  markets,  but  in  other 
cases, the role of public policy in reducing entry barriers may be quite limited. Therefore, 
the  overall  macroeconomic  impact  of  actionable  policies  depends  on  the  industrial 
structure  of  a  particular  economy.  Understanding  how  sectoral  specificities  and  related 
policies  can  affect  the  macroeconomic  outcomes  of  a  country  is  a  potential  venue  for 
further research. 

23 

 
 
 
 
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26 

 
 
List of figures 

Figure 1. Barriers to entrepreneurship in 2013 - source OECD (2015) ......................... 5 

Figure 2. Young SMEs contribute disproportionately to job creation - source Criscuolo et 
al. (2014) ............................................................................................................. 5 

Figure 3. Response of GDP to a reduction in fixed costs equal to 0.1% of GDP ............15 

Figure 4. Response of aggregate employment to a reduction in fixed costs equal to 0.1% 
of GDP ................................................................................................................16 

Figure 5. Response of TFP to a reduction in fixed costs equal to 0.1% of GDP .............16 

Figure 6. Response of GDP to a reduction of fixed costs in the intermediate goods sector 
equal to 0.1% of GDP and a reduction in the risk premium for intangibles proportional to 
the degree of the sample's dispersion. ....................................................................18 

Figure 7. Response of aggregate employment to reduction in fixed costs in the 
intermediate goods sector equal to 0.1% of GDP and a reduction in the risk premium for 
intangibles proportional to the degree of the sample's dispersion. ...............................19 

Figure 8. Response of TFP to a 0.1% reduction in fixed costs in the intermediate goods 
sector equal to 1% of GDP and a reduction in the risk premium for intangibles 
proportional to the degree of the sample's dispersion. ...............................................20 

27 

 
List of tables 

Table 1. Cross-country values of selected parameters and initial steady state values of 
key variables .......................................................................................................13 

Table 2. Percentage point differences in GDP impacts between policy scenario II and 
policy scenario I at different time horizons ...............................................................22 

28 

 
 
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