Helping unemployed creating their own work in the new economy : PES support to start ups.
Date: 2017-09-06
Institutions: Directorate-General for Employment, Social Affairs and Inclusion
Subjects: EU employment policy, aid to undertakings, employment service, fight against unemployment, integration into employment, job application, job creation, long-term unemployment, public service, report, start-up, unemployed person, unemployment

Helping unemployed creating their 
own work in the new economy 
PES support to start ups 

Written by ICON-INSTITUT Public Sector GmbH 
Marjolein Peters 
May-2017 

Social 
Europe 

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Directorate-General for Employment, Social Affairs and Inclusion 
Directorate B — Employment 
Unit B.1 — Employment Strategy 
Contact: Ulrike Storost 

E-mail:  EMPL-PES-SECRETARIAT@ec.europa.eu 

European Commission 
B-1049 Brussels 

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Helping unemployed creating their 
own work in the new economy 

PES support to start ups 

Directorate-General for Employment Social Affairs and Inclusion 
European Network of Public Employment Services 

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This  document  has  been  prepared  for  the  European  Commission  however  it  reflects  the  views  only  of  the 
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Luxembourg: Publications Office of the European Union, 2017 

ISBN: 978-92-79-71862-5 
doi: 10.2767/442443 
© European Union, 2017  

Reproduction is authorised provided the source is acknowledged. 

The  European  Network  of  Public  Employment  Services  was  created  following  a  Decision  of  the  European 
Parliament  and  Council  in  June  20141.  Its  objective  is  to  reinforce  PES  capacity,  effectiveness  and  efficiency. 
This  activity  has  been  developed  within  the  work  programme  of  the  European  PES  Network.  For  further 
information: http://ec.europa.eu/social/PESNetwork. 

This  publication  has  received financial  support from  the  European  Union  Programme  for  Employment 
and  Social 
consult: 
http://ec.europa.eu/social/easi. 

information  please 

(2014-2020). 

Innovation 

further 

"EaSI" 

For 

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CONTENTS 

1 

Introduction 

1.1 
1.2 
1.3 
1.4 

Background 
Study objectives 
Focus and methodology 
The report 

2  A changing context 

2.1 
2.2 

The importance of self-employment for EU labour markets 
Self-employment for non-traditional groups 

The unemployed 

2.2.1 
2.2.2  Women 
2.2.3 
2.2.4 
2.2.5 
2.2.6 

Young people 
Migrants 
Older people 
People with disabilities 

2.3 

New forms of work and self-employment 

2.3.1 
2.3.2 
2.3.3 
2.3.4 

Defining self-employment 
Real vs fake self-employment 
New forms of work 
A new employment status? 

3  PES support for start-ups 

3.1 
3.2 

PES and their in role start-up support 
Barriers to becoming self-employed 

Generic barriers 
The unemployed 

3.2.1 
3.2.2 
3.2.3  Women 
3.2.4 
3.2.5 
3.2.6 
3.2.7 

Young people 
Migrants 
Older people 
People with disabilities 

3.3 
3.4 

Start-up support addressing barriers 
PES Support for start-ups 

3.4.1 
3.4.2 
3.4.3 
3.4.4 
3.4.5 
3.4.6 

Development of start-up incentives 
Expenditure on start-up incentives 
Participation in start-up incentives 
Targeted measures for start-ups 
Overview of measures by type and target group 
Monitoring & Evaluation systems in PES 

4  The effectiveness of start-up support for the unemployed 

4.1 
4.2 

Introduction 
Primary effects 

4.2.1 
4.2.2 
4.2.3 
4.2.4 
4.2.5 

Indicators for effectiveness 
Start-up rates 
Other employment effects 
Sustainable integration 
Adverse effects 

Creaming 
Deadweight 

4.2.6 

Precarious and bogus self-employment 

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European Network of Public Employment Services 

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4.3 

Secondary and macro effects 

4.3.1 
4.3.2 
4.3.3 
4.3.4 

Indicators for effectiveness 
Overall macro impacts 
Additional job creation 
Displacement 

4.4 

Effectiveness by type of measure 

4.4.1 
4.4.2 
4.4.3 
4.4.4 
4.4.5 

Selection and targeting increase effectiveness 
Financial support and the need for an integrated approach 
Coaching and mentoring 
Other measures 
Infrastructure for entrepreneurship 

4.5 

Effectiveness for specific groups 

The significance of personal characteristics 

4.5.1 
4.5.2  Women 
4.5.3 
4.5.4 
4.5.5 
4.5.6 

Young people 
Migrants 
Older people 
People with disabilities 

5  Conclusions and recommendations 

5.1 
5.2 

The rationale behind start-up support 
Start-up support 

5.2.1 
5.2.2 
5.2.3 

Programme design 
Programme delivery 
Start-up and accompanying measures 

5.3 
Start-up support for specific groups 
5.4 
Start-up support and new forms of work 
5.5  Monitoring and evaluation of start-up measures 

5.5.1 
5.5.2 

Considerations and recommendations for monitoring and evaluation 
Evaluation criteria when assessing start-up incentives 

References 

Annex   Indicators for monitoring and evaluation of start-up incentives 

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1  Introduction 

1.1  Background 

Public Employment Services (PES) support for the unemployed who want to move to self-
employment or start a business has been critically followed. Fears that people ‘driven to’ 
self-employed  would  be  less  likely  to  succeed  and  uncertainties  about  potential 
displacement effects of such support have given rise to research on these subjects. 

Start-up  sort  remains  a  small  category  within  the  ALMP  offer,  but  the  economic  crisis 
provided an impetus for these schemes and nowadays some eight out of ten PES in the 
EU  (plus  Norway  and  Iceland2)  have  one  or  more  so-called  start-up  incentive  schemes, 
mostly aimed at all the unemployed. Although economic recovery is well on its way in the 
EU,  unemployment  (nearly  23  million  were  unemployed  in  the  second  quarter  of  2015) 
and inactivity (91 million) are still high and job creation is still a major political concern 
(OECD/EU, 2016). 

Two other developments underline the potential and importance of self-employment as a 
way  out  of  unemployment,  but  they  also  show  how  the  nature  of  self-employment  is 
evolving, as presented below. 

The crisis has brought to the fore the relevance of self-employment as an opportunity for 
unemployed,  especially  in  countries  hard-hit  by  the  crisis.  In  situations  where  more 
traditional  job  opportunities  have  been  virtually  non-existent  for  a  long  time,  self-
employment  becomes  one  of  the  few  remaining  alternatives.  Policy  makers  also 
recognised that groups with a lower income and an inferior labour market position were 
traditionally  under-represented  amongst  the  self-employed.  From  this,  an  interest 
developed  in  what  was  termed  ‘inclusive  entrepreneurship’.  With  societies  furthering 
entrepreneurship  amongst  women,  young  people,  migrants3,  older  workers,  and  people 
with disabilities, a need has developed for the PES to review and, if necessary, redefine 
their role in this area. 

At the same time, an increasing diversification of work forms has drawn attention to the 
darker side of the more precarious forms of work thus created. New forms of work often 
appear  in  a  grey  area  where  workers  find  themselves  somewhere  between  being  an 
employee  or  self-employed.  Recently,  the  discussions  and  legal  action  on  the 
‘collaborative  economy’,  notably  on  platforms  such  as  Uber,  have  once  again  raised 
concerns  about  self-employment  for  groups  already  in  a  weak  position  in  the  labour 
market.  The  Commission  Communication  on  establishing  a  European  Pillar  of  Social 
Rights4  earlier  this  year  drew  attention  to  both  the  provision  of  assistance  for  finding 
work and being self-employed as well as protection for those in precarious employment. 
The Commission launched a consultation on new protection for people in a-typical work, 
such  as  the  collaborative  economy.5  Whether  this  has  any  implications  on  public 
programmes  supporting  self-employment  is  another  question  to  be  examined  by  public 
authorities, including PES. 

2  

3  

4  
5  

This  report  refers  to  the  28  EU  Member  States,  as  well  as  Norway  and  Iceland  where 
information  was  available  for  these  countries.  With  the  three  PES  in  Belgium,  the  total 
number of PES covered by the study amounts to 30. 
The term migrants as used in this report encompasses all foreign born or people born from 
foreign  citizens  and  encompasses  other  terms  used  such  as  ‘ethnic  minorities’  and 
‘immigrants’. 
26 April 2017, COM(2017) 250 final 
Delivering  on  the  European  Pillar  of  Social  Rights  -  Questions  and  Answers,  European 
Commission - Fact Sheet, http://europa.eu/rapid/press-release_MEMO-17-1005_en.htm 

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European Network of Public Employment Services 

                                           
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1.2  Study objectives 

The  changing  context,  summarised  above,  calls  for  a  review  of  existing  PES  support  in 
this area as well as an assessment of the possible implications for PES resulting from the 
experience gained so far, and the implications for the PES. This study therefore aims to 
provide  a  summary  of  the  lessons  drawn  in  available  evaluations  and  good  practice 
reviews,  aimed  at  making  this  information  accessible  to  PES.  The  current  scope  of 
information  on  the  topic  is  too  wide  and  diverse  for  most  PES  to  be  able  to  invest  the 
staff time needed to access it directly, assess it critically and identify the ideas relevant 
to  their  work.  Highlighting  relevant  conclusions  and  pointing  out  their  possible 
implications  will  provide  a  basis  for  PES  needing  to  navigate  the  increasingly  globalised 
and  digitalised  world  of  self-employment,  understand  its  rules  and  effectively  guide 
jobseekers wishing to enter it. 

1.3  Focus and methodology 

The study focuses on PES6 support for setting up a new business, rather than support for 
entrepreneurship  in  general.  The  review  focuses  on  start-up  incentives  for  the 
unemployed,  but  also  draws  lessons  from  general  policies  for  the  support  and 
development  of  small  and  medium-sized  enterprises  (SMEs).  It  covers  all  measures 
offered  by  PES.  First  of  all,  this  includes  the  actual  start-up  incentives  (programmes 
favouring  the  setting  up  of  a  new  self-employment  or  entrepreneurial  activity  by 
unemployed  workers)  such  as  subsidised  grants,  microfinance  opportunities  and  the 
possibility  of  converting  unemployment  benefits  into  start-up  grants.  The  report  also 
reviews the evidence on other services accompanying these start-up incentives, such as 
information and sign-posting, guidance, mentoring and counselling and training. 

Although  the  unemployed  may  create  small  businesses  that  in  turn  might  create 
employment  opportunities  for  others,  this  study  does  not  look  into  those  cases,  and 
instead  it  focuses  on  the  larger  group  that  becomes  self-employed  that  remain  micro 
companies, i.e. those with zero employees. 

A key feature of the study is that it draws on existing information to provide a common 
and  unique  framework  of  analysis.  Policies  and  practices  to  support  the  unemployed 
setting themselves up in self-employment have been mapped and studied extensively in 
recent  years,  not  just  by  the  European  Commission  and  the  OECD,  but  also  at  national 
inclusive 
level.  Key  publications 
entrepreneurship (OECD/EU 2013-2016) and EU labour market peer reviews in this field 
(EEO 2010, Duell 2011, EEPO 2014). A full list of references is annexed to this report. 

include  those  on  missing  entrepreneurs  and 

1.4  The report 

This report summarises the existing information, extracting and presenting knowledge in 
a way that is the most relevant to PES. An important section of the report is reserved for 
valuable lessons that can be identified in existing evaluations and practices. In addition, 
the  descriptive  part  focuses  on  classification  and  typologies,  in  terms  of,  for  example, 
measures and target groups. For detailed information, reference is made to the existing 
sources. 

The role of PES in supporting start-ups is reviewed in the light of the importance of self-
employment  (measures),  the  effectiveness  of  various  measures  in  relation  to  different 
target  groups,  and  the  possible  policy  issues  and  implications  emerging  from  lessons 
learned and contextual developments identified. 

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Their  role  in  the  field  is  also  defined  in  relation  to  actions  from  other  stakeholders 
supporting self-employment 

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2  A changing context 

2.1  The importance of self-employment for EU labour markets 

Although  the  vast  majority  of  the  EU  working  population  are  employees,  slightly  over 
14% are self-employed. More than two thirds of this group are ‘own-account’ workers. In 
other words, roughly one in ten workers (10.3%) are self-employed without employees.7 
The share of own-account workers in employment ranges from 4.7% in Denmark to close 
to  a  quarter  in  Greece.  These  figures  illustrate  the  variation  in  enterprise  structure  of 
Member  States,  with  certain  sectors  having  a  higher  prevalence  of  self-employed  than 
others.  However,  the  business  environment  and  cultural  factors  also  impact  self-
employment in different countries. 

Carrasco  R  and  Ejrnæs  M  (2012)  compared  labour  market  conditions  and  self-
employment in Denmark and Spain, being the countries with the lowest (Denmark) and 
the  highest  (Spain)  rates  of  self-employment.  They  found  that  unemployment  was  a 
driving  force  for  self-employment  in  Spain,  especially  for  people  not  in  receipt  of 
unemployment benefits, mothers with small children and people on very low wages. Such 
patterns  were  not  found  in  Denmark.  This  suggests  that  low  wage  levels,  low  social 
security  coverage  and  small  amounts  of  unemployment  benefit,  as  well  as  high 
unemployment  rates,  tend  to  push  people  into  self-employment  thereby  increasing  the 
self-employment rates. 

As would be expected, the global economic crisis had a significant negative impact on the 
creation of new enterprises. According to Eurofound (2011), this decline stabilised again 
after 2009, but at a lower level compared with the numbers before the crisis. The crisis 
also led to increasing numbers of bankruptcies in many countries. Post-crisis recovery in 
enterprise  creation  rates  has  been  slow  and  the  first  indications  of  a  turning  point 
emerged as late as 2015 (OECD, 2016). 

These developments affected not only the self-employed, but also employees working for 
companies.  This  in  turn  contributed  to  the  decline  in  employment  growth  and  the 
extremely high unemployment rates that marked the crisis. 

An  IPPR  report  in  early  2015  concluded  that  self-employment  in  Europe  constitutes  an 
important part of the labour market. Yet it also signalled that self-employment in Europe 
did  not  increase  at  the  same  rate  as  employment  in  general.  Southern  and  eastern 
European  countries  had  high  self-employment  rates  but  overall  employment  had  not 
recovered.  In  northern  and  western  European  countries  the  proportion  of  self-employed 
workers  had  not  increased,  although  employment  was  growing.  The  OECD  (2016) 
pointed out that OECD self-employment rates and the number of self-employed remained 
below pre-crisis values in many OECD countries by the end of 2015. 

Furthering self-employment not only provides a means of compensating for these trends, 
it  also  helps  bottom-up  initiatives  that  may  identify  niche  markets  and  find  innovative 
solutions.  The  European  Commission  and  the  OECD  launched  a  project  on  Inclusive 
Entrepreneurship  in  Europe.  It  aims  to  further  business  creation  and  self-employment 
amongst the ‘26 million people in the European Union that are unemployed and actively 
seeking work’.8 

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Eurostat  Labour  Force  data,  2015,  from  http://ec.europa.eu/eurostat/statistics-
explained/index.php/Labour_market_and_Labour_force_survey_(LFS)_statistics#Self-
employed 
http://www.oecd.org/cfe/leed/inclusive-entrepreneurship.htm 

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2.2  Self-employment for non-traditional groups 

The joint OECD/EU project aims to further entrepreneurship amongst specific groups that 
are traditionally under-represented amongst the self-employed and who encounter more 
problems  in  finding  or  keeping  work.  Besides  the  unemployed  in  general,  three  obvious 
target  groups  in  this  respect  are  women,  youth  and  older  workers.  Migrant  workers  on 
the other hand, are an important target group for entrepreneurship policies because they 
are already more likely to become self-employed while facing difficulties entering regular 
employment. A less common groups of potential self-employed are disabled. The findings 
of  the  project  for  each  group  is  discussed  briefly  below,  with  some  additional  evidence 
from other sources. 

During  the  economic  crisis,  unemployment  rates  increased  for  all  target  groups  of 
inclusive  entrepreneurship  policies,  but  young  people  were  especially  badly  hit.  In 
addition,  activity  rates  were  significantly  lower  for  these  groups  (OECD/European  Union 
2015). 

2.2.1  The unemployed 

According to OECD/European Union (2015) data, the number of unemployed people who 
use  self-employment  as  a  way  back  into  the  labour  market  is  small.  Only  2.1%  of  the 
unemployed  in  the  European  Union  in  2013  tried  to  become  self-employed.  Again,  this 
figure depends a lot on the country concerned, with a share as low as 0.7% in the Slovak 
Republic,  going  up  to  7.0%  in  Romania.  Since  the  beginning  of  the  crisis  in  2008,  this 
percentage has been increasing slowly but steadily. 

No less than 5% of the ‘inactive’ and 4.5% of ‘ employees in 2013 made the transition to 
becoming  ‘self-employed  without  employees’  in  2014.  Only  2.7  %  of  the  unemployed 
made a similar transition. The transition to becoming self-employed with employees was 
made by 0.7%, compared to 1.2% and 3% for former inactive and employees (European 
Commission 2016c). 

2.2.2  Women 

According to OECD/EU (2016) women, despite similar levels of education and skills, were 
less  likely  to  be  a  new  business  owner  than  men  in  the  European  Union  between  2009 
and 2013 (1.8% vs. 3.5%). Women are also less likely to be self-employed. On average, 
5.1% of employed men aged 15-24 are self-employed, compared with 3.6% for women, 
while  29.2%  of  employed  men  aged  55+  are  self-employed  compared  with  15.9%  for 
women (OECD 2016). 

Women and men also differ when it comes to the characteristics of their self-employment 
(OECD 2016): 

•  Self-employed  men  are  two  and  a  half  times  more  likely  to  employ  others  than 
self-employed women, and they work on average eight hours per week more than 
self-employed  women.  Both  self-employed  men  and  women  tend  to  work  more 
than employees, especially the self-employed who are themselves employers. 
In  a  majority  of  countries,  70%  or  more  of  self-employed  women  work  in  the 
services sector, while the share for men is around 50%. 

• 

•  The share of employees who have a second job as self-employed is very low, but 

virtually always higher for men than for women. 

In  addition,  according  to  the  OECD/European  Union  (2015)  report  on  missing 
entrepreneurs: 

●  Self-employed  women  worked  more  hours  per  week  in  2013,  on  average  in  the 
European Union, than those who were employees, but fewer hours than men who 
were self-employed. 

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●  The  median  number  of  hours  worked  per  week  by  self-employed  women  varied 
greatly  across  European  Union  countries  in  2013.  Self-employed  women  worked 
the  greatest  number  of  hours  per  week  in  Austria  and  Belgium,  exceeding  50 
hours per week. 

●  Self-employed  women  with 

their  own  employees  on  average  worked 

approximately 3 hours per week more than those without employees. 

●  Self-employed  women  earned  slightly  less  than  self-employed  men  in  the 

European Union in 2012. 

●  Women  who  worked  as  employees  earned  approximately  EUR  4,200  more  per 

year than women who worked in self-employment in 2012.9 

2.2.3  Young people 

Youth  (15-30  years  old)  in  the  EU  were  more  likely  to  be  new  business  owners  than 
adults  between  2009  and  2013  (2.9%  for  youth  against  2.6%  for  adults),  but  their 
businesses  seem  to  have  low  survival  rates.  (OECD/EU  2016).  Youth  (15-24  years  old) 
were,  however,  much  less  likely  than  adults  (15-64  years  old)  to  be  self-employed  in 
2013.  In  the  European  Union,  the  self-employment  rate  for  youth  was  4.2%  relative  to 
14.4% for adults (OECD/European Union (2015). 

With  regard  to  the  characteristics  of  youth  and  their  companies  (OECD/European  Union 
2015): 

●  Very  few  self-employed  youth  have  employees.  In  the  European  Union,  only 

● 

81,200 (10.5%) had at least one employee in 2013. 
In most  European Union countries, the majority of young people do not feel that 
they have the knowledge and skills to start a business. 

●  Over the 2009 to 2013 period, young people (18-30) in the European Union were 
slightly less likely than adults to believe that they have the knowledge and  skills 
to start a business (36% vs. 41%). 

●  However,  in  several  European  Union  countries,  the  youth  were  just  as  likely,  or 
slightly  more  likely,  than  adults  to  believe  that  they  had  the  skills  for 
entrepreneurship.  For  example,  more  than  50%  of  the  youth  in  the  Slovak 
Republic reported that they had the knowledge and skills to start a business. 

2.2.4  Migrants 

According to the IPPR (2015), migrants tend to be self-employed more often than other 
workers, as they often face barriers when trying to find work as an employee. An OECD 
(2010) study on immigrants already noted that they are more likely to be self-employed 
than  the  indigenous  population  in  many  OECD  countries,  based  on  data  from  2007. 
Countries  that  stood  out  in  this  respect  were  Belgium,  France,  Nordic  countries,  and 
particularly, countries in central and Eastern Europe. This was subsequently confirmed in 
the  OECD  entrepreneurship  report  (2013)  that  revealed  that  in  OECD  countries  around 
13%  of  foreign-born  workers  are  self-employed.  Between  2005  and  2010  migrants 
consistently represent around 12% of the self-employed not working in agriculture.  

In the European Union 6.6% of self-employed people were born outside of their country 
of  residence,  and  almost  half  of  this  group  outside  of  the  European  Union 
(OECD/European  Union  2015).  The  self-employment  rate  of  foreign-born  people  in  the 
EU is slightly lower than the self-employment rate for people born within their country of 
residence  (14.1%  vs.  15.3%).  The  ‘foreign-born’  self-employed  were  also  less  likely  to 
have employees (24.7% vs. 28.5%). 

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Based on an analysis of median annual incomes. 

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Self-employed  immigrants  also  seem  to  have  a  higher  level  of  educational  attainment 
than self-employed natives (OECD 2013). For the UK (UKCES 2011), it is suggested that 
ethnic  minorities  actually  make  use  of  their  cultural  and  other  endowments  related  to 
their  background,  to  better  penetrate  the  market  in  countries  they  or  their  parents 
originally came from. 

2.2.5  Older people 

Older  people  (50-64  years  old)  were  less  likely  to  be  a  new  business  owner  in  the 
European  Union  between  2009  and  2013.  For  older  people,  the  rate  for  setting  up  new 
businesses depends very much on the country they live in. (OECD/EU 2016). 

For  adults  overall,  the  percentage  was  2.6%,  for  older  people  it  amounted  to  1.6% 
OECD/EU  (2016).  Nevertheless,  self-employment  increases  with  age.  In  most  OECD 
countries  self-employment  rates  are  higher  in  older  age  groups,  for  both  women  and 
men.  Amongst  young  men  (15-24)  the  average  self-employment  rate  amounts  to  5.1% 
of  employed  men,  compared  to  29.2%  for  men  aged  55  and  older.  For  women  these 
figures amount to 3.6% and 15.9% respectively. Men are more often self-employment in 
all age groups, but the difference is highest in the age group 55+ (OECD, 2016). 

With  regard  to  the  characteristics  of  older  self-employed  and  their  companies 
(OECD/European Union 2015): 

●  The  degree  to  which  older  self-employed  people  hire  employees  varies  greatly 

across Member States. 

●  Older people believe they have the knowledge and skills to start a business. This 
is to about the same degree as working age adults in general say they do (2009 -
2013, 39% vs. 41%). 

●  This  proportion  does  vary  substantially  across  countries,  ranging  from  30%  in 

Italy to 50% in Austria. 

●  The size and growth rates of businesses operated by older people tend to be small 

across the EU (OECD, 2016). 

2.2.6  People with disabilities 

The  labour  market  position  of  people  with  disabilities,  including  their  share  of  self-
employment, is poorly documented. According to the OECD/European Union (2014), the 
available  data,  however,  suggests  that  people  with  disabilities  are  more  likely  to  be 
unemployed or inactive. It would also seem that people with disabilities that are working 
are often found in low-skilled, low-paying occupations. On the other hand, if people with 
disabilities  are  working  they  appear  to  be  self-employed  to  the  same  degree  as  other 
workers,  based  on  data  from  the  European  Union  Statistics  on  Income  and  Living 
Conditions (EU-SILC). 

Self-employment  rates  of  people  with  disabilities  vary  across  Member  States,  but  also 
according  to  their  type  of  impairment  or  disability  and  its  severity.  People  who  are 
severely  limited  in  their  daily  activities  are  more  likely  to  be  self-employed. 
Musculoskeletal problems for example. seem to be a contributing factor to choosing self-
employment over working as an employee. Based on evidence from the UK, it seems that 
self-employed  people  with  disabilities  are  more  likely  to  work  alone  and  operate  as  a 
home-based business (OECD/European Union 2014). 

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2.3  New forms of work and self-employment 

2.3.1  Defining self-employment 

Statistics  typically  capture  self-employment  by  asking  workers  to  assess  their  situation 
themselves.  Eurostat  defines  the  self-employed  as  people  ‘who  are  the  sole  owners,  or 
joint  owners,  of  the  unincorporated  enterprises  in  which  they  work,  excluding  those 
unincorporated  enterprises  that  are  classified  as  quasi-corporations’.10  A  further 
distinction  can  be  made  between  employers  (self-employed  with  employees)  and  own-
account workers (self-employed without employees). 

The  definition  highlights  the  risk-taking  element  of  self-employment,  as  owning  an 
unincorporated business can create unlimited liability for its owners.  The definition does 
not  include  people  that  work  self-employed  part-time  when  paid  employment  as  an 
employee  is  their  main  activity.  The  OECD  uses  a  similar  definition  in  its  publication 
series Entrepreneurship at a Glance, but it also includes unincorporated businesses. 

Key  characteristics  of  self-employed  work  include  independence  and  autonomy,  the 
absence  of  the  typical  hierarchical  employment  relationship,  and  by  contrast,  the  fact 
that the person is in a position to make the operational decisions affecting the enterprise. 

It  is  important  to  recognise  that  the  above  definitions  encompass  a  variety  of  self-
employed workers. These e.g. include (UKCES 2011): 

•  Entrepreneurs and small business proprietors;  
• 

Independent  professional  workers  (in  the  arts  and  liberal  professions,  for 
example); 

Farmers; 

•  Skilled manual craft-workers; 
• 
•  Some categories of home-workers or ‘outworkers’; 
• 

‘Labour only’ subcontractors (e.g. in the construction industry, although recent tax 
changes are likely to have reduced this component of self-employment). 

2.3.2  Real vs fake self-employment 

Low  or  erratic  earnings  are  often  a  feature  of  starting-up  a  business.  Continued  low 
income, however, means that the self-employed cannot build up the necessary reserves 
for the future. They are likely to fall into poverty if the business fails or when they reach 
retirement age. The risk that this situation might occur is markedly higher where people 
have  been  pushed  into  self-employment.  For  these  people,  there  is  no  pre-selection  in 
terms of their motivation and skills, so the risk of unsustainability is increased. 

For several years authors (from Böheim and Mühlberger in 2009 to Westerveld in 2017) 
have  pointed  to  the  fact  that  ‘disguised  employees’  or  ‘bogus  self-employed’  are  found 
amongst  the  self-employed.  This  discussion  is  linked  to  concerns  about  the  precarious 
nature  of  these  jobs  and  to  the  involuntary  or  necessity-driven  nature  of  the  choice  to 
become self-employed. 

On  the  other  hand,  the  UKCES  (2011)  report  also  cited  research  that  highlights  the 
importance  of  positive  motivations  such  as  lifestyle  reasons  (e.g.  relating  to  balancing 
family  and  working  life)  and  occupational  norms  (i.e.  the  nature  of  an  individual’s 
profession). The opportunities to start a business, financial or otherwise, constitute other 
pull factors. 

10  

http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:Self-employed 

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2.3.3  New forms of work 

Eurofound  (2015)  has  prepared  an  extensive  overview  of  new  forms  of  work  that 
emerged  or  became  much  more  prominent  since  2000.  To  be  included  in  the  overview, 
employment had to meet one or more of the following criteria: 

•  A  new  relationship  between  employers  and  employees  different  from  the 

established one-to-one employment relationship 

•  The provision of work on a discontinuous or intermittent basis or for very limited 

periods of time rather than on a continuous or regular basis 

•  Networking and cooperation arrangements between the self-employed. 

These new  forms of work  could be, but did not have to be, characterised by ‘a place  of 
work other than the premises of the employer’ and ‘strong or prevalent support of ICT’. 

From the nine new forms of  work  Eurofound identified, three  specifically related to self-
employment: portfolio work, crowd employment and collaborative employment11: 

•  Crowd  employment  is  a  new  form  of  work  made  possible  by  ICT.  It  is  mainly 
characterised  by  not  being  location-bound.  Buyers  and  sellers  of  services  or 
products are brought together by virtual platforms. Work can be shared between 
sellers because larger tasks can be broken down to smaller jobs. 

•  Portfolio  work  is  work  done  by  self-employed  people  working  for  a  large  number 

of clients, providing small amounts of work for each of them. 

•  Collaborative  employment  refers  to  business  partnerships  that  go  beyond 
traditional  business  partner  relationships  in  order  overcome  the  limitations 
imposed  on  those  forms  of  economic  activity  by  their  smaller  scale  compared  to 
larger competitors. Freelancers, the self-employed or micro enterprises cooperate 
to overcome limitations of size and professional isolation. 

These  new  forms  were  dominant  in  southern  European  countries  (Cyprus,  Greece, 
Portugal and Spain), the Baltic states (Latvia and Lithuania), Denmark and Germany and 
generally involve the self-employed. New employment forms for both employees and the 
self-employed  were  found  in  Austria,  Belgium,  France,  Hungary,  Italy,  Norway,  Sweden 
and  the  UK.  In  the  other  European  countries  new  forms  of  work  tend  to  relate  to 
employees. 

Maselli  et  al  (2016)  developed  an  overarching  framework  starting  from  the  on-demand 
economy and distinguishing three sub-groups: 

•  The true sharing economy, providing a temporary access to under-utilised assets 

between consumers; 

•  Platforms where one can conduct an auction or a contest to receive a service; 
•  The product service economy, which is a business-to-consumer relationship. 

Wage  levels  vary  considerably  across  platforms.  This  may  partly  be  explained  by  the 
relative  newness  of  the  phenomenon.  As  a  result  of  workers  may  have  a  poor  idea  of 
their  market  value.  It  may  also  be  a  sign  that  workers  in  geographical  areas  with  low 
demand for their skills make use of opportunities elsewhere in the world, even in regions 
with  lower  price  levels.  With  regard  to  working  conditions  Maselli  and  her  colleagues 
point  out  that  the  system  transfers  stress  and  pressure  from  employers  to  the  self-
employed  for  several  reasons.  The  first  reason  is  that  platforms  are  demand-driven  or 
client-driven.  This  means  that  outsourcing  becomes  very  compressed  in  time  as  a large 
pool of workers is contacted at the same time, with increased competition as a result. All 
contacts are more or less immediately in effect, a feature of the use of a virtual platform. 

11  

Voucher-based  and  ICT-based  mobile  work  are  applicable  for  both  employees  and  self-
employed, but seem less relevant (vouchers) or are overlapping with the other two groups 
(ICT). 

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Other  factors  besides  the  high  competition  and  the  short-term  deadlines  that  Maselli  et 
al. mention are ‘the unpredictability of the demand, the need to keep skills extremely up-
to-date,  the  need  to  constantly  engage  in  self-promotion  and  the  uncertainty  of  the 
remuneration’ as stress-contributing factors. 

The on-demand economy tends to lead to precarious employment. While some jobs pay 
very  well  and  precariousness  is  not  unique  to  this  sector,  some  clear  risks  are  also 
visible.  Job  security  and  social  protection  are  clearly  limited  within  this  type  of 
employment.  Also,  it  would  seem  that,  increasingly,  traditional  forms  of  employment 
carried out by  employees  are turned into jobs for the  self-employed.  Maselli et al. used 
Eurostat LFS data to show a structural increase in the share of contingent workers from 
27.4% in 2002 to 32% in 2014. 

Several other publications do not distinguish between these three forms. Names such as 
collaborative  economy  and  crowd  work  are  used  interchangeably,  as  are  other  phrases 
like  ‘sharing  economy’,  ‘platform  economy’,  ‘on-demand  economy’,  ‘Uber-economy’  or 
‘gig  economy’.  In  its  Communication  on  the  collaborative  economy  last  year,  the 
European  Commission  points  out  that  the  sector,  as  well  at  its  definitions,  is  changing 
(European Commission, 2016d). It defines the collaborative economy in a broad sense as 
‘business models where activities are facilitated by collaborative platforms that create an 
open marketplace for the temporary usage of goods or services often provided by private 
individuals’.  The  definition  encompasses  service  providers,  the  users  of  these  services 
and  intermediaries.  The  definition  furthermore  states  that  ‘the  collaborative  economy 
transactions  generally  do  not  involve  a  change  of  ownership  and  can  be  carried  out  for 
profit or not-for-profit’. 

Even  with  this  broad  definition,  the  collaborative  economy  remains  small.  However,  the 
sector  has  been  growing  rapidly  since  2013  and  it  has  already  become  an  important 
factor  in  some  sectors.  In  2015,  the  gross  revenue  from  collaborative  platforms  and 
providers  was  estimated  to  be  EUR  28  billion  in  the  EU.  Projections  of  the  collaborative 
economy  include  estimates  as  higher  than  EUR  160-572  billion  (European  Commission, 
2016d). The European Parliament (EP 2016) found that platform work does not seem to 
attract the unemployed or the inactive. Instead it seems to supplement the income of the 
under-employed or the self-employed who are not in full—time employment. 

Key  issues  to  be  addressed,  according  to  the  Communication,  include  market  access 
requirements,  liability  regimes,  the  protection  of  users,  taxation,  and  the  rights  and 
social protection of workers in the collaborative economy. 

In  its  research  agenda  on  the  collaborative  economy,  the  European  Commission’s  Joint 
Research Centre identified the following open issues to be addressed (JRC, 2016): 

•  When  developing  policies  and  regulations,  take  into  account  the  variety  of 

platforms existing in the collaborative economy; 

•  Collect, process and disseminate data on the collaborative economy; 
•  Take measures to ensure the trustworthiness and transparency of platforms, e.g. 

through rating systems; 

•  Conduct research on the functioning and impact of digital labour market platforms 

on labour markets; 

•  Adjust social policies to fit the atypical forms or work common in the collaborative 

economy. 

2.3.4  A new employment status? 

An advantage of the collaborative economy is that it offers opportunities for people who 
have difficulty finding more  regular employment to  earn an income. However, the more 
flexible  working  arrangements  with  individual  tasks  performed  on  an  ad-hoc  basis  may 

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create uncertainty on the applicability of employment and social protection legislation for 
workers.  The  applicability  depends  on  the  definition  of  an  employment  relationship,  but 
distinction between the self-employed and workers is no longer as clear as it used to be. 

The  commission  Communication  (European  Commission,  2016d)  refers  to  the  EU  level 
definition applied by the Court of Justice (CJEU). It defines an ‘employment relationship’ 
as  starting  from  the  performance  of  services  for  someone  else,  while  being  under  the 
direction  of  that  other  person,  and  receiving  remuneration  for  this  work.  The  features 
that define someone as employee or self-employed thus centre around the existence of a 
subordination  link,  the  nature  of  work,  and  remuneration.  The  actual  definition  differs 
between Member States. Therefore the Communication calls on Member States to:  

 ‘- assess the adequacy of their national employment rules considering the 
different needs of workers and self-employed people in the digital world as well as 
the innovative nature of collaborative business models; 

- provide guidance on the applicability of their national employment rules in light 
of labour patterns in the collaborative economy.’ 

Schmid (2010) makes  a plea for  recognising that the standard  employment relationship 
is  changing  because  societies  are  changing.  The  increasing  employment  participation  of 
women, the rise  of  ‘mature’ aged workers, and the desire to  open the labour market to 
persons with restricted work capacities, all contribute to an increasing need for variability 
in  employment  relations.  Addressing  the  associated  risks  and  drawbacks  requires  new 
forms  of  social  security  or  a  more  flexible  standard  employment  relationship  through 
adaptations in labour law and ‘social law’. He also advocates policies that systematically 
support  or  encourage  trial  and  error  processes,  during  which  workers  can  experiment 
with combinations of (dependent) employment and self-employment. 

A  specific  group  of  self-employed,  with  relatively  good  work  and  income  prospects,  are 
higher  educated  professionals,  such  as  journalists,  designers,  ICT  specialists  and 
consultants.  Research  commissioned  by  EFIP  (2013),  a  European  organisation 
representing ‘highly skilled self-employed individuals who work for themselves but do not 
employ  others’,  urges  policy-makers  to  recognise  that  independent  professionals  (iPros) 
are  a  distinct  group  in  their  own  right,  neither  SMEs  nor  entrepreneurs  nor  ‘sham’  self-
employed.  The  recommendations  from  the  study  also  include  an  appeal  to  ensure  that 
policy  and  legal  developments  do  not  negatively  impact  iPros  and  that  iPros  are  not 
disproportionately penalised through fiscal and other regimes. 

Based  on  their  analysis  of  UK  LFS  data,  Böheim  and  Mühlberger  (2009)  find  that 
dependent self-employed workers12 constitute a group distinct from both employees and 
independent self-employed workers. This group is characterised by a more volatile labour 
market attachment and necessity driven entrepreneurship. They are also likely to stay in 
the  labour  market,  either  as  employed  or  self-employed,  and  unlikely  to  create 
employment for others as employers. 

It  is,  however,  not  always  easy  to  classify  crowdworkers  as  either  employees  or  self-
employed, neither for policy makers and courts, nor for the workers themselves. Perhaps 
a  special  status  is  needed  to  solve  this  problem.  Maselli  et  al.  (2016)  point  out  that 
‘looking for an appropriate categorisation can become a trap’ and suggest decoupling the 
link between benefits and rights from the employment relationship, effectively proposing 
a move from employee social security to universal social protection schemes. 

12  

Dependent  self-employment  is  defined  as  a  working  relationship  where  the  worker  is 
formally  self-employed  yet  under  conditions  of  work  similar  to  those  for  dependent 
employees. (Eichhorst et al. 2013) 

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It should, finally, be noted that the platform-based new forms of work are not bound by 
geographic  limitations  or  national  borders.  This  provides  an  additional  challenge  when 
considering the suggestions above. 

3  PES support for start-ups 

3.1  PES and their in role start-up support 

Globally  speaking  there  are  two  reasons  for  PES  to  include  start-up  incentives  in  their 
ALMP  offer:  firstly  to  support  economic  development  and  secondly  to  support  the 
employment  of  job-seeking  clients.  EEPO  in  this  respect  refers  to  the  two  key  policy 
rationales:  start-up  as  entrepreneurship  policy  and  start-up  as  an  activation  policy 
(EEPO, 2014). 

As 99% of companies are SMEs - and the majority of these are micro enterprises - self-
employment  is  a  key  factor  in  job  creation.  Promoting  entrepreneurship  will  help  the 
creation and survival of SMEs, thereby contributing to growth and investment in the EU. 
Furthering  ‘Jobs,  growth  and  investment’  is  one  of  the  ten  political  priorities  of  the 
Juncker Commission. PES can play a specific role by supporting groups in society that are 
less likely to become self-employed on their own initiative and face specific barriers that 
require targeted measures or combinations of measures. Unemployed people, as well as 
specific groups such as youth and people with disabilities, are less likely to become self-
employed than workers and inactive people, as explained in section 2.2. 

Self-employment also constitutes a way out of unemployment, especially when jobs are 
scarce. For this reason support for start-ups is a logical part of the ALMP package offered 
by PES. Groups  which are less likely to become self-employed to a large  extent overlap 
with groups that have a larger distance to the labour market. These groups differ in their 
perception  of  their  ability  to  become  self-employer  and  in  their  desire  to  do  so.  Youth 
more  often  than  adults  prefer  self-employment  to  dependent  employment  (45%  vs. 
37%) and more often (41% vs. 30%) see this as a feasible activity (OECD/EU, 2016). In 
line with these findings the Youth Employment Package, including the Youth Guarantee, 
is  specifically  aimed  at  increasing  the  availability  of  start-up  support  services  for  young 
people.  Furthermore,  compared  to  men,  women  less  often  prefer  self-employment  to 
employment  and  less  often  consider  it  to  be  a  feasible  option  for  them.  Compared  to 
adults in general, older people on the other hand more often feel that self-employment is 
not  a  feasible  choice  for  them.  They  do,  however,  not  differ  with  regard  to  their 
preference for (self-) employment based  on gender.  Lifestyle choices, financial situation 
and  the  opportunity  cost  of  time  may  help  explain  these  different  choices.  However, 
there  are  also  real  differences  in  opportunities  and  barriers  across  age  and  gender 
groups. 

3.2  Barriers to becoming self-employed 

3.2.1  Generic barriers 

The  OECD/EU  (2016)  good  practice  compendium  shows  how  people  perceive  these 
barriers. When people were asked to clarify why they do not believe it would be feasible 
for them to become self-employed, the most frequently cited reason was access to start-
up  financing  (21%  of  adults  in  the  European  Union).  Other  important  reasons  include  a 
lack  of  skills  to  become  self-employed  (8%),  no  business  idea  (7%)  and  difficulty 
reconciling  self-employment  with  family  responsibilities  (6%).  People  also  worry  about 
the  risk  of  failure  and  its  legal  and  social  consequences  (5%)  and  the  administrative 
difficulties (4%). 

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The  importance  of  barriers  and  the  weight  attributed  to  these  barriers  depends  on 
personal characteristics, and would need to be identified and assessed on a case by case 
basis. 

3.2.2  The unemployed 

The 2014 European Employment Policy Observatory Review (EEPO, 2014) identified four 
main  groups  of  barriers  to  entrepreneurship  for  unemployed  people  wanting  to  start  a 
business: 

●  The risks associated with the income uncertainty of entrepreneurship 
●  Lack of access to finance/capital resources 
●  Lack of entrepreneurial skills 
●  Need for business consultancy 

Another  specific  barrier  for  the  unemployed  is  that  they  lack  the  professional  network 
that comes with a job (OECD/EC, 2015). The longer people are unemployed, the weaker 
the links with former colleagues and partners will become. The long-term unemployed in 
addition often already deal with many other problems, ranging from housing to health, a 
baseline situation which makes it harder to embark upon a challenging initiative such as 
setting up your own business. 

3.2.3  Women 

Women  are  generally  known  to  have  smaller  and  less  varied  networks  than  men.  Their 
network also less often includes business services providers or entrepreneurs (OECD/EC, 
2015). 

Another  specific  barrier  that  women  encounter  is  the  difficulty  of  reconciling  self-
employment with family responsibilities. They report this barrier more often than men, as 
well  as  a  lack  of  business  ideas.  Women  and  men  do  not  differ  in  the  degree  to  which 
they report financial and skills barriers (OECD 2016). 

Kautonen  raises  the  issue  of  caring  responsibilities,  which  in  the  case  of  older  self-
employed  people  pertains  to  their  parents  and  relatives.  This  barrier  affects  women  in 
particular,  as  they  may  more  often  be  found  in  carer  positions.  He  also  points  out  that 
being  self-employed  may  provide  the  flexibility  that  actually  helps  combine  work  and 
caring responsibilities. 

3.2.4  Young people 

Young  people  face  some  specific  barriers  because  of  their  age.  They  have  greater 
difficulty  in  raising  external  finance  because  they  lack  savings  and  collateral.  They  also 
more often lack the skills to run a business (EEPO 201413, OECD/EC 2015, OECD 2016). 
As a result it is harder for them to be credible to among financers, suppliers, customers 
and so on. 

Young  people  are  often  thought  not  to  be  sufficiently  aware  of  the  requirements  and 
opportunities  of  entrepreneurship.  Education  systems  mostly  prepare  students  for  paid 
employment,  rather  than  cultivate  entrepreneurial  attitudes  and  skills.  They  lack  prior 
work experience and have limited business networks and business-related social capital. 
Due to limited resources, young people are more likely to start their business in sectors 
with low barriers to entry where competition is fierce (OECD/European Union, 2012a). 

The young population is of course a mixed population. Some groups of young people may 
in fact be very well endowed with entrepreneurial skills and access to resources, e.g. the 
children  of  the  self-employed.  At  the  other  end  we  find  groups  facing  relatively  strong 

13  

Quoting from OECD/The European Commission (2013) 

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barriers,  such  as  young  people  from  migrant  families,  young  people  living  in  deprived 
areas, youth from low income families, and youth with low education levels. Perhaps the 
facing  the  greatest  barriers  are  the  NEETs  -  youth  Not  in  Employment,  Education  or 
Training (OECD/European Union, 2012a). 

3.2.5  Migrants 

On  the  one  hand,  it  has  been  argued  that  migrant  entrepreneurs  may  have  difficulty 
understanding  regulatory  requirements  and  may  be  forced  to  rely  upon  non-bank  and 
informal finance (EEPO 201414). 

On  the  other  hand,  another  OECD/EC  report  (2015)  also  points  to  the  fact  that  many 
ethnic minority and migrant communities show a strong entrepreneurial orientation. This 
indicates  they  have  role  models  as  well  as  access  to  community-based  support. 
Immigrant entrepreneurs also have opportunities resulting from knowledge and networks 
relating to the country they or their family originally came from. 

It stands to reason that newly arrived immigrants may have difficulty building networks 
(OECD/The European Commission, 2014). 

Support  provided  for  ethnic  minority  and  migrant  entrepreneurs  needs  to  take  into 
account  that  “over-crowding”  in  specific  business  sectors  associated  with  diverse  ethnic 
groups  may  occur,  that  migrant  entrepreneurs  often  operate  in  sectors  that  are 
characterised by long working hours, and the fact that migrant groups generally have a 
mistrust of government and public initiatives (OECD/EC 2015). 

Many  countries  impose  restrictions  on  the  labour  market  participation  of  refugees  (IMF, 
2016).  In  the  UK,  for  example,  they  can  only  apply  for  vacancies  in  certain  narrowly 
defined  “shortage”  occupations.  In  Norway,  self-employment  is  prohibited  for  refugees. 
In  Germany,  employers  must  prove  for  each  vacancy  that  they  were  not  able  to  find 
German nationals, EU citizens or  recognized refugees (except if the refugees have  skills 
in  bottleneck  vacancies).  These  restrictions  also  prohibit  refugees  from  becoming  self-
employed until they receive entry or a work permit in the country. 

3.2.6  Older people 

Older  people  are  much  less  likely  to  report  barriers  to  self-employment  than  youth  and 
core  age  adults  (OECD,  2016).  Some  generic  barriers  are  less  problematic  for  older 
people; other generic barriers impact older workers in specific ways. Older entrepreneurs 
benefit from the expertise they have gained over time, but they do not always have the 
necessary  entrepreneurship  skills.  Older  people’s  skills  may  be  outdated  or  they  may 
have  low  levels  of  digital  literacy.  Older  people  who  have  been  away  from  the  labour 
market  for  a  longer  period,  through  unemployment  or  retirement,  may  have  difficulty 
keeping  up  or  updating  their  networks.  Retraining  when  moving  to  another  sector  may 
also  be  harder  for  older  people.  In  many  cases,  financing  is  less  of  a  problem  for  older 
people becoming self-employed (OECD/European Union, 2012, OECD/EC, 2015). 

Barriers to self-employment that are specific to old age include health problems, financial 
disincentives  in  benefits  and  pension  schemes,  age  discrimination,  the  ‘opportunity  cost 
of  their  time’  (a  higher  preference  for  leisure  time),  a  lack  of  awareness  of  business 
opportunities  and  the  steps  involved  in  setting  up  a  business,  and  a  lack  of  information 
tailored  to  their  needs  in  its  content  and  presentation  (OECD/European  Union,  2012). 
With  regard  to  information  needs,  the  Kautonen  (2013)  study  refers  to  ‘overly-complex 
and not understandable information published on the websites of different governmental 

14  

Quoting from OECD/The European Commission (2013) 

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bodies and support agencies’ and that ‘the new concepts and terms on information sites 
and platforms (only) address the younger, media-savvy and well-educated generation’. 

3.2.7  People with disabilities 

People with disabilities, especially those with mental and physical disabilities, are likely to 
encounter discrimination by employers. Self-employment therefore may constitute one of 
the few entry points into the labour market for them (OECD/European Union, 2014). 

At the same time, according to EEPO 201415, people with disabilities have more difficulty 
gaining  entrepreneurial  experience  and  skills,  and  may  be  constrained  by  state  welfare 
policies  (OECD/European  Commission,  2013).  Kautonen  (2013)  quotes  from  qualitative 
studies  carried  out  in  the  UK  that  illustrate  that  disability  schemes  also  have  perverse 
effects  on  their  willingness  to  become  self-employed.  The  Incapacity  Benefits  regime 
stipulates  that  if  an  individual  gives  up  their  status  as  an  Incapacity  Benefits  recipient, 
and then starts a business which fails, then this person will return to regular job-seeker 
status on lower benefits. 

The  OECD/EU  policy  brief  on  entrepreneurship  for  people  with  disabilities  presents  a 
substantial  list  of  specific  barriers  faced  by  people  with  disabilities  when  starting  a 
business (OECD/European Union, 2014). They include: 

●  Lack of confidence and limited aspirations; 
●  The ‘benefits trap’; 
●  Lack of relevant business knowledge and skills; 
●  Limited access to start-up capital due to low personal financial resources  savings 

(for example home ownership); 

●  Consumer discrimination; 
● 
●  A lack of appropriate business support services tailored to their needs. 

Increased labour costs (e.g. assistants to deal with limitations due to a handicap); 

3.3  Start-up support addressing barriers 

The needs described in the previous sections call for different policy responses. The main 
concern for unemployed people wanting to start their own business is the lack of income 
security.  This  applies  in  particular  to  the  initial  stages  of  business  creation.  Many 
schemes  therefore  include  financial  support.  This  aims  to  help  people  with  their  living 
costs  when  setting  up  the  business  as  well  as  access  to  loans  for  capital  equipment. 
Financial  support  both  in  terms  of  income  and  access  to  capital  are  crucial.  Income 
security measures in the initial stages of the business are, however, more important than 
the  receipt  of  block  loans  or  subsidies  for  investment  in  the  business.  A  lack  of 
entrepreneurial skills and knowledge are key barriers for the unemployed. Training is an 
obvious  response  to  this,  but  mentoring  and  coaching  a  well  as  business  development 
support  are  equally  relevant  in  this  respect.  Facilitating  networking  addresses  barriers 
related  to  customers  and  suppliers,  but  contacts  with  other  entrepreneurs  will  also 
contribute  to  skills  and  information  gaps.  Welfare  bridges  such  as  ‘incubators’  address 
combinations of barriers (EEPO, 2014). 

The  table  below  lists  the  six  main  policy  approaches  for  supporting  the  unemployed  in 
starting their own business: 

15  

Quoting from OECD/The European Commission (2013) 

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Table 1 

Policy approaches for start-ups by unemployed 

Financial support 

Training 

•  Grants 
•  Bank loan 
•  Credit guarantee schemes 
•  Microcredit, a subset of microfinance, 
•  Financial education 
•  Functional/technical  skills, 

including 

financial  management, 

human resource management and market research 

•  Soft  skills,  such  as  interpersonal  skills  including  networking  and 
persuasion/selling,  awareness  of  their  own  skills  gaps  and 
strengths 

•  Knowledge  ‘for’  and  ‘in’  (functional/technical),  e.g.  employment 
legislation,  compliance  with  tax  requirements,  knowledge  of 
potential financing sources and arrangements 

•  An understanding of self-employment, including awareness of the 

risks and benefits of self-employment 

•  Drafting business plans 
•  Advice and support to bring the business onto the market 

•  Coaching 
•  Mentoring 

•  Access to peer networks 
•  Access to sector relevant networks (customers, suppliers) 

Business 
development 
support 
Coaching and 
mentoring 

Networking 

Welfare bridges 

•  Sign-posting 
•  Business counselling 
•  Incubators 

Source: based on OECD/EU (2016), EEPO (2014), UKCES (2011 

Not included in the above overview above are measures stimulating entrepreneurship in 
general,  such  as  measures  to  reduce  bureaucracy  and  administrative  burdens  and 
favourable conditions for the self-employed in terms of tax and social security regimes.  

3.4  PES Support for start-ups 

3.4.1  Development of start-up incentives 

In  2014  all  of  the  29  countries  reviewed16  in  the  EEPO  had  some  form  of  start-up 
incentives  for  the  unemployed  at  the  national  and/or  regional/local  level.  These 
incentives  have  always  constituted  a  small  share  of  the  ALMPs  offered  by  PES. 
Nevertheless,  in  over  one  third  of  the  countries  reviewed  (Denmark,  Greece,  Spain, 
France, Hungary, Portugal, Slovenia, Finland, Sweden and the United Kingdom), they had 
already  been  there  since  the  mid-1980s.  They  came  to  the  fore  more  recently,  after 
1995, in Estonia and in Lithuania. 

Between  2008  and  2010  Member  States  included  incentives  for  self-employment  and 
business  start-ups  as  part  of  the  measures  proposed  to  deal  with  the  consequences  of 
the crisis. Overall, the number of users and the take-up of start-up incentives remained 
virtually the same. However, nine countries increased their spending between 2007 and 
2011  (Estonia,  Spain,  France,  Hungary,  Austria,  Portugal,  Slovenia,  Slovakia,  and 
Finland). Of these countries,  Estonia, France,  Hungary, Portugal, Slovenia, and Slovakia 
increased  their  spending  by  50%  or  more.  With  0.114%  of  GDP  spent  on  start-up 
incentives  in  2011,  this  type  of  measure  is  by  far  the  most  prominent  in  Spain  (EEPO, 

16  

EU28 plus Iceland 

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2014). Some other countries (Belgium, Croatia, Latvia, and Iceland) introduced start-up 
incentives or programmes later, in response to of the crisis. 

3.4.2  Expenditure on start-up incentives 

In 2011, EU Member States spent approximately EUR 205 billion on active labour market 
policy interventions, i.e. 1.9% of their combined GDP. Start-up incentives only constitute 
a  small  proportion,  approximately  2%,  of  the  budget  at  the  European  Union  level 
(OECD/European  Union,  2015).  For  2014,  no  aggregate  data  are  available  at  the  EU 
level,  but  the  share  of  start-up  incentives  seems  to  have  risen  considerably  (OECD 
2016).  The  proportion  of  ALMPs  spent  on  start-up  incentives  still  varies  considerably 
across Member States. Start-up incentives are a sizeable important measure in terms of 
expenditure  in  various  eastern  and  southern  European  countries.  Spain  almost  spends 
one quarter of its ALMP budget on this type of measure. Other countries where start-up 
incentives  are  important  in  terms  of  expenditure  are  Poland,  Croatia  and  Slovenia, 
followed by Estonia, Greece, Bulgaria and Slovakia. 

Table 2  Expenditure  on  start-up  incentives  per  person  wanting  to  work  in  2014  (in 

PPS*) 

Start-up 
(Cat 7) 
11.9 
17.2 
16.8 
- 
80.8 
28.1 
- 
38.5 
170.6 
161.5 
29.7 
27.1 
0.2 
2.2 
13.8 
4.2 
19.5 
- 
- 
24.6 
128.4 
3.6 
0.1 
84 
24 
52.2 
36.8 
- 
- 

BE 
BG 
CZ 
DK 
DE 
EE 
IE 
EL 
ES 
FR 
HR 
IT 
CY 
LV 
LT 
LU 
HU 
MT 
NL 
AT 
PL 
PT 
RO 
SI 
SK 
FI 
SE 
UK 
NO 

incentives 

ALMPs (Cat 2-7) 

2,666  
246  
1,290  
6,872  
1,959  
285  
3,159  
457  
708  
3,180  
234  
549  
194  
248  
549  
5,182  
2,108  
327  
2,584  
2,739  
871  
1,042  
55  
733  
402  
3,380  
5,157  
-  
4,001  

of 

start-up 
Share 
incentives in ALMPs (%) 
0.4% 
7.0% 
1.3% 
- 
4.1% 
9.8% 

8.4% 
24.1% 
5.1% 
12.7% 
4.9% 
0.1% 
0.9% 
2.5% 
0.1% 
0.9% 
- 
- 
0.9% 
14.7% 
0.3% 
0.2% 
11.5% 
6.0% 
1.5% 
0.7% 
- 
- 

Source: Own calculations, based on data from European Commission (2016) 
*  Purchasing  Power  Standard.  This  is  an  artificial  currency  unit  that  eliminates  the  effect  of  price 
level differences across countries created by fluctuations in currency exchange rates. 

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3.4.3  Participation in start-up incentives 

Countries  with  relatively  high  percentages  of  participants  to  a  large  extent  overlap 
countries where expenditure on start-up incentives is high. Spain and Slovenia have the 
highest  proportion  of  ALMP  participants  in  start-up  incentives.  Estonia,  France,  Croatia, 
Lithuania and Slovakia also have comparatively high shares. 

Start-up incentives are less often used by young people, with the exception of Poland. In 
Portugal,  Germany,  Austria  and  Latvia  the  share  of  young  participants  in  start-up 
incentives is very low.  In  Hungary and Slovakia, it is high compared to  other countries, 
but still the overall proportion of ALMP participants is less than two thirds of the share for 
all ages. Women generally make the  same use  of  start-up incentives as men, and  even 
slightly  more  than  men  in  Latvia.  Their  participation  rates  are  lower  than  men’s 
participation rates in Portugal, and Austria, Poland, Slovenia, and Slovakia. 

Table 3 

Participants in start-up incentives as share of ALMPs (in %) 

All 
2 

3.9 
0 
2.7 
12.9 
0 

24.1 
11.8 
12.8 
0 
0.1 
1.1 
12.7 
0 
0.9 
0 
0 
2.3 
8.8 
3.4 

29.7 
15.5 
3.9 
0.7 

BE 
BG 
CZ 
DK 
DE 
EE 
IE 
EL 
ES 
FR 
HR 
IT 
CY 
LV 
LT 
LU 
HU 
MT 
NL 
AT 
PL 
PT 
RO 
SI 
SK 
FI 
SE 
UK 
NO 

Under 25 (%) 
0.6 

Women (%) 
2.1 

0 
0.3 
4.5 
0 

4.5 
3.4 
0 

0.2 

0 
0.5 
0 
0 
0.3 
15 
0.2 

12.9 
10 
1.8 
0.3 

0 
2.5 
11.9 
0 

11.3 
8.6 
0 

1.2 

0 
0.9 
0 
0 
1.9 
7.7 
2.4 

26.4 
13.1 
3.5 
0.8 

Source: Based on data from European Commission (2016) 

3.4.4  Targeted measures for start-ups 

A recent report on PES capacity (Peters, 2016) showed that in 2016 PES17 rely on one or 
more instruments specifically designed for target groups. Most use these to target three 
to  four  specific  groups,  notably  young  people,  LTU  and  older  jobseekers.  A  smaller 

17  

For the Dutch PES, no information was available as most of the ALMPs are administered by 
municipalities or implemented by private bodies. 

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number  target  people  with  disabilities.  In  addition,  most  of  the  changes  in  ALMPs  were 
aimed at targeting the offer towards specific client sub-groups. New measures also show 
a  stronger  emphasis  on  work-based  ALMPs.  Five  Member  States  introduced  new 
measures  for  self-employment  in  the  preceding  year.  In  2016  eight  PES  (Belgium- 
Actiris,  Cyprus,  Finland,  Hungary,  Italy,  Poland,  Portugal  and  Sweden)  offer  start-up 
incentives to specific groups of unemployed in their country. All of them included young 
people as their target group, some also long-term unemployed (Hungary and Sweden) or 
older workers (Belgium- Actiris, Hungary and Sweden). 

3.4.5  Overview of measures by type and target group 

According  to  the  European  Employment  Policy  Observatory  (EEPO,  2014),  in  2014 
financial  support  was  the  main  type  of  support  provided  across  Europe.  Fifteen  Member 
States  offered  non-repayable  grants  or  subsidies,  eight  Member  States  offered  income 
support  during  the  launch  phase  of  the  business,  and  in  eleven  Member  States 
unemployment benefits continued during the start-up. Generally, eligibility criteria and a 
viable  business  plan  are  required  to  qualify  for  financial  support  to  avoid  abuse  of  the 
schemes.  

Almost  all  countries  offer  more  than  one  financial  support  measure.  In  eleven  countries 
financial support is combined with other types of support, such as training or coaching. 

Start-up  incentives  across  Europe  are  generally  not  restricted  to  specific  types  of 
business  or  sectors,  and  measures  usually  target  unemployment  benefit  recipients  and 
the  registered  unemployed  in  general  rather  than  specific  groups.  If  specific  groups  are 
targeted, these are more often young people. 

Table 4 Overview of measures in use across 29 European Countries in 201418 

Type of measure 

Non-repayable grants or subsidies 

Countries where such 
measures are in use 
BE,  BG,  CZ,  DE,  EE,  EL,  ES, 
HU, LT, PL, PT, AT, SE, SK, FI 

No of 
countries 
15 

Link to unemployment benefit (UB): 
Conversion of UB 
Replacement of UB 
Income support during launch phase 
UB continued or graduated during support  DK  (continued)  —  FR,  NL 

5 
BG, ES, FR, LU, PT 
BE, DE, AT, FI, UK 
5 
BE, DE, HU, LV, AT, SE, UK, IS  8 
3 

Preferential loans 

Tax and social security exemptions 
Combined  measures  (financial  incentives 
combined with training, coaching, etc.) 
Specific target groups: 
Women 
People with disabilities 
Young people 

Other disadvantaged groups 

Source: EEPO (2014), table 2.2 

(graduated) 
BE, BG, ES, FR, LV, LT, NL, AT, 
PT, SK, UK 
ES, FR, LT, RO 
BG, HR, LV, MT, NL, PT, AT, SI, 
FI, UK, and IS 

DE, EL, CY, PL, FI 
BE, BG, CZ, FR, LT, NL, PL, SK 
BE, EL, FR, IT, LT, LV, LU, MT, 
PL, PT, RO, SK, FI 
HU, PL 

11 

4 
11 

5 
8 
13 

2 

18   Note that for some measures in 2014 the information may not (yet) have been available when 
the  EEPO  report  was  published  or  classification  may  be  done  differently  by  more  recent 
standards. For Poland e.g. PES offers consulting and training services for those who received 
loans (combined measure), as well a preferential loans. On the other hand, while PES support 
is tailored to needs, there is no specific assistance for disabled or other disadvantaged groups. 
24 

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More  recently,  new  measures  aimed  at  supporting  self-employment  were  introduced  in 
several  Member  States.  They  include  the  deployment  of  specific  counsellors  for 
jobseekers who want to become self-employed, financial measures, as well as measures 
specifically designed for women and for youth. 

Recently introduced start-up measures: 

-  The use of specialised self-employment counsellors (HR). 
-  Slovenia  introduced  a  subsidy  programme  for  formerly  unemployed  highly 

educated women who have become self-employed. 

-  Actiris (Belgium) offers an example of a comprehensive set of measures for older 
workers with more common measures such as training and assistance in starting 
a business, but also including outplacement for those aged 45 and over. 

-  Several start-up incentives were launched in Hungary  
- 

From  1st  March  2016,  the  national  “Self-employment  National  Revolving  Fund” 
was  launched  in  Italy.  It  aims  to  support  young  people  that  could  not  find 
financing  from  traditional  sources  who  intend  to  start  self-entrepreneurship  and 
self-employment activities. 

-  Pôle  emploi  (France)  has  introduced  in  2016  a  specific  service  to  promote 
entrepreneurship  and  to  provide  jobseekers  with  start-up  support,  hints  and 
methodology.  This  service  “Activ’Crea”  is  carried  out  by  specialised  external 
providers. 

Source: Peters, 2016 

3.4.6  Monitoring & Evaluation systems in PES 

Viertelhauzen  et  al  (2012)  analysed  the  way  PES  monitor  and  evaluate  their  activities. 
They  find  that  at  the  time  almost  all  PES  in  EU/EEA  countries  used  a  performance 
measurement system to monitor the performance of their organisation. 

Many  PES  had  adopted  management  by  objectives  principles  that  drove  this  process. 
Some  three  quarters  of  the  PES  agree  targets  with  external  parties,  such  as  Ministries, 
and/or internally with regional and local offices. The benchmarking of local offices is also 
common practice.  

PES  use  very  different  sets  of  indicators.  These  mostly  focus  on  outputs  and  results 
rather  than  impacts.  Customer  satisfaction  is  measured  in  most  PES,  although  on 
different occasions and with different frequencies. 

A clear majority of PES use data warehouses for the compilation of data collected by the 
PES. These sometimes also include data collected by other public organisations.  

The primary source of information of PES is administrative data. This data usually comes 
from  intake  interviews  and  follow-up  contacts  with  clients.  Administrative  data  can  also 
be  provided  by  other  public  organisations  like  the  social  security  or  tax  administration 
organisations where employees are usually registered.  

The  tracking  of  clients  on  a  structural  basis  often  does  not  happen  as  a  result  of  high 
costs  and  practical  problems,  and  sometimes  because  of  legal  impediments  related  to 
privacy.  As  a  result,  PES  need  to  rely  mostly  on  survey  outcomes  to  measure  their 
performance. 

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4  The effectiveness of start-up support for the unemployed 

4.1  Introduction 

Many  authors  notice  a  lack  of  evaluations,  and  especially  good  evaluations,  of  start-up 
incentives. This applies at the national level, but meta-evaluations of start-up incentives 
are often missing or they are not visible at the EU level. 

This may be explained by their small role in ALMPs. In addition, typically a small number 
of participants would make it hard to go beyond outputs and results and identify impacts 
at macro level. Evaluations  of the  effects  of start-up incentives for  specific  groups, with 
the exception of youth, are even more scarce. 

Key EU and international sources on start-up incentives  

Currently  probably  the  main  source  of  information  on  the  effects  of  start-up 
incentives  in  the  European  is  the  joint  project  of  the  European  Commission  and  the 
OECD  on  inclusive  entrepreneurship  in  the  EU.  The  project  has  yielded  extensive 
descriptions of practices in Member States, comparisons of such practices, as well as 
the lessons learned from them, including those resulting from formal evaluations. The 
project  focuses  on  ‘missing  entrepreneurs,  i.e.  groups  less  likely  to  become  self-
employed. These include the unemployed, but also those groups with typically weaker 
labour market positions such as women, youth, migrants, older workers, and people 
with  disabilities.  The  project  has  so  far  resulted  in  four  annual  reports  and  policy 
briefs  on  individual  groups  and  support  measures.  The  latest  annual  report  has  the 
form of a good practices compendium. Further useful sources at EU level include  the 
peer  reviews  on  self-employment  carried  out  under  the  mutual  learning  programme 
on  pathways  to  support  young  people  into  self–employment  (Duell,  2011,  and  the 
European  Employment  Policy  Observatory,  EEPO,  in  2014).  Interesting  comparisons 
of  outcomes  of  start-ups  evaluations  and  their  policy  implications  are  found  in 
research published by IZA (the Institute for Labour Economic based in Germany), e.g. 
Caliendo and Künn (2010, 2012), Caliendo (2016) and Cho et al (2016), the last is a 
world-wide study. An example of a study which also explicitly assessed the quality of 
the  evaluations  themselves  include  a  study  on  start-up  support  for  young  people  in 
the EU by Sara Riso (Eurofound 2016b). 

Many evaluations start from participants and they measure effects at the individual level. 
They are also more likely to focus on the direct and short term effects. The longer-term 
effects  on  participants’  labour  market  position  or  the  eventual  impacts  on  employment 
and unemployment are far less of a focus point in research. In other words, monitoring is 
more  prominent  than  evaluation,  with  a  focus  on  outputs  and  results,  rather  than 
impacts. However, some studies have used modelling to assess impact at the macro level 
too. 

Macroeconomic evaluation of ALMPs – example 

A study by Verónica Escudero is an example of an approach that aims to measure the 
aggregate impact. This approach allowed her to measure both the direct and indirect 
effects  of  ALMPs.  She  compiled  a  database  with  data  from  1985  to  2010.  She  used 
time-series as well as pooled cross-country data, i.e. her survey used new samples in 
different years. She estimated different models to measure the effects of six different 
ALMPs,  and  one  of  them  was  start-up  incentives.  She  looked  at  three  dimensions  of 
their  implementation  (i.e.  the  allocation  of  resources  to  public  administration, 
continuity  and  timing  in  the  implementation  of  programmes)  and  their  impact  on 
unemployment,  employment  and  participation  rates.  She  compared  the  low-skilled 
and  the  overall  population  and  also  looked  at  the  impact  on  the  low-skilled 
unemployed.  She  then  checked  the  results  to  see  if  they  were  not  explained  by  the 
impact  of  context  factors  such  as  demand  conditions,  the  structure  of  the  labour 

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market and differences in institutional arrangements (Escudero V, 2015). 

Many studies report on effects, but do not further examine causality, i.e. the question of 
whether  the  effects  were  really  brought  about  by  the  programme.  When  comparing 
evaluations,  Caliendo  (2016)  for  example  noted  that  causal  effects  on  employment, 
income  and  business  growth  were  often  not  addressed.  Only  a  few  causal  studies  have 
compared  the  results  for  unemployed  workers  who  received  start-up  subsidies  with  the 
results  for  a  control  group.  Although  deadweight  is  not  systematically  addressed  either, 
some tentative conclusions can be drawn from this. At the mid-level and the macro-level, 
potential displacement effects are important but knowledge on this is so far limited. 

The  present  chapter  starts  out  by  discussing  primary  and  secondary  effects  in  general, 
followed by two sections on the effects according to the type of measure and the type of 
target  groups.  The  final  section  presents  lessons  learned  identified  in  evaluations  and 
good practices overviews. 

4.2  Primary effects 

4.2.1  Indicators for effectiveness 

Primary  effects  are  defined  here  as  effects  that  are  directly  attributable  to,  and  occur 
immediately during and after a programme. This section looks at the direct, usually more 
short-term effects of start-up support measures. In most cases this means gross effects, 
but in sections 4.2.6 and 4.2.7 some evidence on net effects is also presented. 

The effectiveness of a measure should be assessed by the achievement of its objectives. 
The  most  common  indicator  by  which  the  success  of  start-up  support  is  judged  is 
therefore the survival rate of the business that was started. When measures  supporting 
the unemployed are considered then labour market integration and the ability to provide 
for  a  decent  living  are  equally  important  indicators.  These  are  closely  related  to  the 
survival rate of the start-up company. 

4.2.2  Start-up rates 

The  overall  trend  in  evaluation  findings  is  that  providing  financial  support  to  the 
unemployed during the start-up phase is successful in the sense that it helps unemployed 
people  start  a  business.  A  majority  of  the  participants  in  such  schemes  continue  their 
business when the support period comes to an end. 

EEPO  (2014)  concludes  that  evaluations  of  start-up  incentives  in  Member  States  show 
that  the  businesses  thus  created  have  ‘satisfactory’  survival  rates,  thereby  creating 
employment  for  the  former  unemployed.  In  general  in  the  EU,  some  three  quarters  of 
participants in schemes promoting start-ups went on to set up their own business. 

Some  of  unemployed  do  return  to  unemployment  after  the  initial  period  of  financial 
support.  However,  this  appears  only  to  apply  to  a  minority.  This  example  is  from  an 
evaluation of the New Enterprise Allowance (NEA) in the United Kingdom. This evaluation 
showed  that  some  80%  of  the  unemployed  starters  continued  their  business  after  26 
weeks,  when  the  allowance  they  received  under  the  NEA  ended.  According  to  the  same 
source,  the  longer-term  survival  rates  of  supported  unemployed  start-ups  are 
comparable to general business survival rates (EEPO, 2014). 

A collection of international evidence (OECD/European Union, 2012a) showed a small but 
growing number of studies showing positive results for start-up support programmes for 
unemployed  people.  This  evidence  amongst  others  came  from  evaluations  of  the 
‘Bridging  Allowance’  and  ‘Start-Up  Subsidy’  in  Germany  and  self-employment  grants 
Sweden.  Both  studies  showed  that  the  programmes  successfully  brought  people  from 

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unemployment into employment. The Swedish study even showed that self-employment 
grants were more likely than wage subsidies to move people out of unemployment in the 
long-term.  The  study  also  presented  evidence  from  Estonia  that  grants  helped  increase 
the survival rates of start-ups in general. 

Finally,  the  most  recent  overview  study,  by  Caliendo  (2016),  concluded  that  for  most 
countries  “survival  rates  appear  to  be  remarkably  high  and  comparable  to  (or  even 
higher than) those for all businesses”. The survival rates found in this study range from 
40%  in  Denmark  (one  year  after  the  subsidy  has  ended)  to  93%  in  Spain  (two  years 
after start-up). The long-term effects (four years and more) are known in only a limited 
number  of  countries.  These  amounted  to  50%  in  the  UK  and  62%  in  Poland  (after  four 
years),  60–70%  in  Germany  (depending  on  the  sub-group,  after  4.5  years),  76%  in 
Spain (after six years), and 36% in Finland and 51% in France (both after eight years). 
This  is  a  positive  and  promising  finding,  even  in  the  absence  of  proper  comparison 
groups. 

If evaluations include a control group, this is usually a group of unemployed people who 
did  not  participate  in  the  programme.  Such  studies  show  that  if  the  unemployed 
participate  in  a  start-up  programme,  then  they  are  more  likely  to  be  employed  than 
unemployed in the control group, even after several years. They are also less likely to be 
unemployed  or  to  receive  welfare.  Studies  in  Germany  and  Sweden  also  show  more 
modest  positive  effects  on  the  income  of  former  programme  participants  (Caliendo, 
2016).  

Some studies (according to EEPO, 2014) suggest that start-up rates also depend on the 
timing  of  the  intervention.  Early  expert  mentoring  and  viability  testing  have  yielded 
higher start-up rates.  

4.2.3  Other employment effects 

Start-up incentives for unemployment do not aim at self-employment as such, but share 
the  broader  labour  market  integration  aims  of  all  ALMPs,  i.e.  employability  and 
employment. The can also be considered (EEPO, 2014) a stepping stone for progression 
to  regular  employment.  This  is  the  result  of  the  skills  that  people  develop  when  going 
through  the  start-up  process.  Starting  a  business  may  also  develop  people’s  networks 
and demonstrate their entrepreneurial attitude and capacities to future employers. 

The  positive  effects  on  employment  are  higher  than  the  start-up  rates  suggest.  In 
addition  to  the  group  of  participants  that  becomes  self-employed,  a  smaller  group  finds 
paid  employment  and  does  not  reappear  on  the  unemployment  registers  after  the 
programme is finished. 

Some  strong  evidence  is  available  on  these  effects  through  studies  using  longitudinal 
studies  and  studies  using  control  groups  (EEPO,  2014).  A  Swedish  analysis  of  2003–
2007,  for  example,  shows  that  beneficiaries  of  start-up  incentives  were  more  likely  to 
obtain  regular,  non-subsidised  jobs  and  were  less  likely  to  come  back  to  the  PES  as 
unemployed.  These  effects  were  still  visible  after  several  years.  Polish  studies  showed 
that some 39% of the unemployed who failed in starting their own business got jobs and 
did not return to unemployment. In Portugal, as few as 43% returned to unemployment. 
Also,  in  the  Netherlands  a  scheme  resulted  in  sustainable  outflow  from  social  security. 
Similar  results  were  more  recently  found  for  German  and  UK  programmes  by  Caliendo 
(2016).  Another  overview  study  (OECD/The  European  Commission,  2014b)  provides 
further evidence, looking at Finland amongst others. 

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4.2.4  Sustainable integration 

The  fact  that  start-up  incentives  are  successful  in  helping  participants  become  self-
employed, and the fact that for many these seem to be lasting effects, continuing when 
the  programme  has  been  completed,  means  that  these  participants  have  secured  a 
livelihood for themselves.  

Another important issue is how much income the new self-employed are able to generate 
from  their  business  and  whether  this  can  be  considered  a  reasonably  or  satisfactory 
income. 

The studies reviewed in this report did not ask the self-employed about their satisfaction 
with the revenues from their business. The EEPO review (2014) notes that income from 
self-employment was found to be small in several studies. However, they also point out 
income is measured during the start-up phase, when investments are being made in the 
expectancy of returns in later years. 

Caliendo  (2016)  observes  that  start-ups  by  unemployed  people  should  be  compared  to 
regular start-ups in order to judge the economic viability of the start-up and provide an 
indicator for the ability to generate a ‘normal’ income for the owner. Unfortunately, such 
studies are not very common and the results are less promising than on start-up  rates. 
The  studies  he  found  range  from  no  observable  differences  to  lower  income,  slower 
growth, and less innovation. 

Finally, it should be noted that the unemployed who succeed in becoming self-employed 
will generally enjoy or lack the same social protection as other self-employed people. In 
as much as their choice for self-employment was a voluntary choice this does not require 
further  discussion.  The  situation  is  different  in  the  case  of  so-called  bogus  self-
employment, as discussed below in section 4.2.6. 

4.2.5  Adverse effects 

Two types of adverse effects are discussed here: creaming and deadweight. These effects 
are interrelated. 

Creaming 

As  is  the  case  for  other  ALMPs,  it  may  be  attractive  for  PES  counsellors  to  select  those 
applicants  for  start-up  incentives  that  seem  the  most  likely  to  succeed.  Whether  this 
creaming is really happening is unknown, but the deadweight effects that occur could be 
partially caused by this phenomenon. 

At  the  same  time,  from  an  economic  perspective,  there  is  a  call  upon  PES  to  actively 
select  promising  future  entrepreneurs  who  will  create  employment  for  themselves  and 
ideally also for others. Start-up incentives may encourage individuals without the proper 
skills  and  qualifications.  This  adverse  selection  (Caliendo,  2016)  is  likely  to  be 
detrimental  to  the  performance  of  businesses  created  in  this  way.  From  an  economic 
point  of  view,  start-ups  from  unemployment  constitute  an  entrepreneurial  risk,  in  the 
sense  that  they  are  likely  to  generate  start-ups  with  a  high  failure  rates  or  minimal 
income. 

In  fact,  many  successful  programmes  have  used  extensive  selection  criteria  and 
procedures  for  participation  (OECD/EU,  2016),  especially  in  the  case  of  more  costly 
measures such as face-to-face coaching or start-up financing. To this end they also  use 
competitive  mechanisms,  such  a  business  plan  competition.  The  risks  associated  with 
such  competitive  mechanisms  are  ‘creaming’  and  ‘deadweight’  effects.  As  a  result,  the 
more disadvantaged groups are less likely to participate. 

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Deadweight 

The evidence on whether participants would have started a company without the financial 
support  is  limited,  but  there  are  several  indications  of  this  effect.  EEPO  (2014)  found 
evidence from Swedish surveys from the 2000 on self-reported deadweight and there are 
more  objective  but  rather  outdated  indications  for  Hungary.  The  second  missing 
entrepreneurship  project  report  (OECD/The  European  Commission,  2014b),  however, 
found  many  estimates  of  deadweight.  These  figures  are  very  wide-ranging,  two  studies 
from  2013  report  deadweight  costs  varying  between  20%  and  70%.  Caliendo  (2016) 
quotes  studies  from  Sweden,  Denmark  and  France  resulting  in  deadweight  estimates 
from 40% to 60%. 

A  proper  assessment  would  need  to  compare  the  deadweight  effects  of  start-up 
incentives to those of other ALMPs. There is some evidence that these effects are similar 
to  most  ALMPs  and  lower  than  for  direct  employment  creation  measures  (OECD/The 
European  Commission,  2014b).  Furthermore,  EEPO  (2014)  suggest  after  reviewing 
evaluation  studies  from  the  Member  States  that  deadweight  loss  seems  to  be  more 
acceptable in the case of start-up grants than for other ALMP measures, including hiring 
subsidies. 

It  is  also  important  to  not  limit  the  identification  of  deadweight  effects  to  starting  a 
business  without  support.  Start-up  subsidies  help  individuals  make  the  transition  to 
having  their  own  business  (EEPO,  2014).  Even  if  participants  had  started  a  business 
without support, the support may still be responsible for their success. The latter requires 
more  complicated  forms  of  analyses,  which  is  why  they  are  often  not  conducted.  As  a 
result,  deadweight  effects  tend  to  be  overestimated  in  evaluations.  Caliendo  (2016) 
concludes  that  potential  deadweight  effects  are  likely  smaller  than  feared.  One  study  in 
particular  found  that  the  deadweight  effects  drops  from  49%  to  21%  (in  general)  and 
from  23%  to  9%  (for  a  narrower  definition  of  people  who  registered  as  unemployed  to 
get the subsidy). 

Factors  that  influence  the  level  of  deadweight  include  the  targeting  of  the  programme, 
but also the type  of participants. EEPO (2014) concludes that deadweight is more likely 
for programmes targeting the better educated unemployed. 

4.2.6  Precarious and bogus self-employment 

The  issue  of  bogus  self-employment  is  debated  far  more  often  than  it  is  properly 
researched.  The  debate  generated  concerns  about  start-up  incentives  and  the  risk  that 
employers could somehow abuse them with participants entering into a situation of false 
self-employment.  These  seem  to  refer  in  particular  to  PES  schemes,  but  especially  to 
general  schemes  that  impose  few  conditions  on  recipients.  Similarly,  some  of  the  self-
employed  are  struggling  to  make  a  living  and  in  danger  of  not  being  able  to  protect 
themselves from the financial impacts of illness, disability or bankruptcy. 

The  situation  with  regard  to  precarious  and  bogus  self-employment  among  unemployed 
people  receiving  start-up  incentives  is  unknown  and  hard  to  assess.  None  of  the 
evaluation studies reviewed in EEPO (2014) addressed these issues.  

Creating  a  specific  status  ‘in-between’  employed  and  self-employed  could  be  seen  as  a 
basis  for  measures  providing  appropriate  social  protection  and  preventing  bogus  self-
employment.  

Some  Member  States  are  known  to  be  taking  measures  to  prevent  bogus  self-
employment.  In  as  much  these  involve  the  creation  of  a  specific  status  this  has 
sometimes proven to be a solution, but sometimes it has also increased the risk of bogus 

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self-employment.  The  latter  for  example  occurred  when  the  new  status  of  ‘auto-
entrepreneur’  was  introduced  in  France  in  response  to  the  crisis  (EEPO,  2014).  Another 
example of a specific status is the category of ´New self-employed’ (Neue Selbständige) 
in  the  Austrian  General  Social  Insurance  Act,  which  obliges  these  people  to  pay  social 
security contributions. 

Neue Selbständige - Austria 

This category contains a heterogeneous group of workers, such as scientists, artists, 
and  journalists.  They  are  executors  of  clearly  defined  tasks  for  clients  rather  than 
continual  tasks  for  the  same  client.  They  can  also  sub-contract  their  work,  putting 
them  in  a  middle  position,  and  most  labour  law  regulations  do  not  apply  to  them, 
although they have to be part of the sickness, work accident, and pension insurance 
system. 

Source: EEPO (2014) 

Logic  suggests  that  the  targeting  of  programmes  and  the  conditions imposed  impact  on 
the  chances  of  bogus  self-employment  occurring.  In  Finland,  counsellors  at  the 
Employment  and  Economy  Offices  and  the  Enterprise  Agency  perform  initial  checks  to 
see if applicants are not hired solely or predominantly by their previous employer. This is 
repeated  at  regular  intervals  up  to  18  months.  The  requirement  to  develop  a  business 
plan and its assessment can also help avoid bogus self-employment. 

4.3  Secondary and macro effects 

4.3.1  Indicators for effectiveness 

Secondary  effects  are  effects  caused  by  primary  effects  and  so  they  typically  show 
themselves after a longer period of time. Multiple primary effects and multiple secondary 
may occur, which are also likely to interact. An important group of secondary effects are 
impacts  at  the  macro  level,  such  as  the  impact  on  the  employment  or  unemployment 
rates  in  a  geographical  area.  As  start-up  support  can  aim  to  achieve  social  as  well  as 
economic  objectives,  an  additional  contribution  to  employment  through  the  hiring  of 
employees in the newly created firms is expected. In both cases, it is important to take 
into account displacement effects, which is the main potential adverse effect of start-up 
schemes for the unemployed at this level. 

4.3.2  Overall macro impacts 

In  as  much  as  evidence  is  available,  start-up  incentives  are  found  to  be  effective  in 
reducing  unemployment,  and  more  so  than  other  ALMP  policies  (EEPO  2014,  Escudero, 
2015).  At  the  same  time,  their  impact  on  the  unemployment  register  is  small,  because 
the  size  of  the  programmes  is  usually  too  small  to  make  a  substantial  difference, 
especially in  times  of  high  unemployment.  This  applies  to  the  number  of  participants  in 
the  schemes  as  well  as  to  funding  the  schemes.  Although  there  is  a  large  diversity 
between  countries,  it  is  estimated  that  even  in  countries  with  a  long history  of  start-up 
incentives,  they  only  affect  at  most  1%  or  2%  of  people  on  the  unemployment  register 
(EEPO,  2014).  Escudero  (2015)  confirms  that  start-up  incentives  are  more  effective  in 
reducing  unemployment  than  other  ALMPs,  but  she  also  found  that  these  effects  in 
particular apply to the low-skilled. 

Start-up  measures  also  have  a  positive  impact  on  the  employment  rate.  Contrary  to 
ALMPs in general, however, this does not apply to the low-skilled. Based on her (macro) 
analysis,  Escudero  concludes 
incentives,  supported 
employment  and  direct  job  creation  measures  have  better  impacts  in  terms  of  reducing 

training,  employment 

that 

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unemployment,  but  also  in terms  of  increasing  employment  and  participation.  Spending 
in  start-up  incentives,  on  the  other  hand,  is  more  effective  in  reducing  the  total 
unemployment  rate  and  the  unemployment  rate  for  the  low-skilled.  It  also  boosts  the 
employment rate of the overall population. 

4.3.3  Additional job creation 

One  of  the  objectives  of  general  enterprise  policies  is  to  create  jobs  for  employees  by 
furthering  entrepreneurship  and  through  the  creation  of  new  enterprises.  The  latter 
impact  is  relatively  small  in  the  case  of  unemployed  start-ups.  These  businesses  are 
more likely to remain one-person companies.  

Studies in various countries suggest that about 20% of the subsidised self-employed can 
be  expected  to  hire  other  staff  (EEPO,  2014).  In  the  overview  study  by  Caliendo  M 
(2016),  some  17–36%  of  subsidised  businesses  hired  one  employee  or  more.  Most  of 
these businesses still remain small. He observed a large variation in the average number 
of additional jobs created by the new companies. Average numbers range from 1.1 full-
time equivalent jobs per surviving company in Germany to less than 0.5 in France. When 
limiting the analysis to the firms that were hiring employees, the average number of jobs 
created per company ranges from 1.6 to 3.1 full-time equivalents. 

Nevertheless, the combined effects do matter, as an example from Austria illustrates. 

Austria and secondary job creation of start-up programmes 

In  Austria,  22%  of  the  business  start-ups  in  the  UGP  programme  employed  other 
people  in  their  company.  When  the  employment  effects  for  all  40,908  participants 
(2006–2012)  were  extrapolated,  approximately  16,000  additional  jobs  were  created 
for regular full-time employees, 7,000 for marginal employees, 4,900 for free service 
contract  workers,  1,600  for  family  workers,  and  there  were  630  apprenticeship 
places. 

Source: EEPO, 2014 

4.3.4  Displacement 

A  concern  is  whether  subsidised  start-ups  displace  (crowd  out),  i.e.  take  away  turnover 
and eventually employment from existing companies. This may apply in particular when 
demand  is  small,  so  during  economic  downturns.  It  seems  such  effects  have  not  been 
researched, but some countries have tried to prevent them by demanding and assessing 
business ideas from potential programme participants. 

While displacement effects cannot be ruled out (Caliendo M (2016), the overall distortion 
effects  seem  limited  since  most  programmes  provide  financial  support  for  a  short  time 
and  typically  do  not  provide  large  amounts.  This  is  confirmed  by  EEPO  (2014),  which 
concludes that studies do not seem to find any statistically significant displacement effect 
for  start-up  grants,  although  evaluations  do  find  statistically  significant  displacement 
effects of around 35% for other labour demand-oriented labour market policy measures, 
such as hiring subsidies. 

According  to  the  OECD/European  Commission  (2014b),  displacement  should  particularly 
be  taken  into  account  for  large  programmes  and  in  times  of  low  unemployment  rates. 
Displacement  effects  furthermore  depend  on  scheme  design  factors  such  as  the  size  of 
incentive, targeting, eligibility rules, and procedures for screening (EEPO, 2014). 

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4.4  Effectiveness by type of measure 

4.4.1  Selection and targeting increase effectiveness 

Measures are appropriate or effective at different stages of the business life cycle, and in 
particular  during  the  seed  and  start-up  phases.  According  to  the  EEPO  analysis  of 
evaluation  studies  (2014),  rates  of  start-ups  are  likely  to  depend  on  the  point  at  which 
they  intervene  in  the  business  creation  process.  The  studies  refer  in  particular  to 
schemes that use mentoring at an early stage and test the viability of the business being 
created. Expert mentoring, checking the commitment of applicants and requiring a viable 
business plan resulted in higher numbers of interested people making it to start-up level, 
typically almost 50% of the participants. 

Besides start-up rates, the use of selection criteria and the targeting of participants has 
also  been  found  to  increase  growth  and  survival  rates  in  a  study  on  start-up  incentives 
for youth (OECD/European Union, 2012a). More stringent selection criteria, e.g. personal 
characteristics such as higher education levels or prior experience, and a viable business 
plan  are  likely  to  result  in  higher  deadweight  effects,  but  also  in  higher  survival  rates. 
The applicants thus selected will have better entrepreneurial skills and they are also likely 
to be more committed (Eurofound, 2016b) This study uses the findings of the evaluation 
of  a  German  programme  providing  ‘start-up  coaching’  to  illustrate  that  focusing  on  a 
clearly  defined  target  group  of  the  unemployed  increases  the  success  of  start-up 
programmes.  This  is  explained  by  the  fact  that  using  a  targeted  approach  makes  it 
possible to design a programme that is tailored to the specific needs of the target groups. 
In  the  German  case,  this  concerned  matching  of  young  entrepreneurs  with  professional 
coaches  in  the  consolidation  phase.  There  is  less  room  for  tailoring  with  more  general 
start-up support or lump sum grants. The 2014 missing entrepreneurs report (OECD/The 
European  Commission,  2014b)  also  concludes  that  well-targeted  programmes  with 
considerable  training  content  do  have  the  potential  to  improve  the  labour  market 
outcomes  of those targeted, and that well-designed financial incentives might also raise 
employment  at  lower  cost.  Start-up  support  incentives  even  appear  to  be  more  cost-
effective, in this scenario, than other ALMPs for the unemployed. 

4.4.2  Financial support and the need for an integrated approach 

By  definition  start-up  incentives  provide  financial  support,  in  the  form  of  an  income 
(guarantee)  during  the  seed  and  start-up  phases  or  provisions  that  help  acquire  the 
necessary capital. There is some evidence that financing programmes are more effective 
when they are complemented with other forms of support, such as advice, coaching and 
mentoring.  This  evidence  was  found  in  the  evaluations  of  youth  programmes 
(OECD/European Union, 2012a). 

found 

(2015) 

for  programmes 

similar  evidence 

Patel 
supporting  women’s 
entrepreneurship  development.  She  found  that  programmes  that  combine  finance  and 
business  training  were  more  effective  in  supporting  women’s  business  start-up  than 
finance or business training alone. Patel reviewed programmes across ILO countries and 
could  therefore  also  confirm  that  such  combinations  are  effective  in  various  contexts, 
including  those  less  conducive  to  women’s  labour  market  participation.  She  also  points 
out, however, that such combined programmes are more costly, and at risk of not being 
very cost-effective. 

Integrated  packages  of  financial  support,  combined  with  coaching,  mentoring  and 
business  counselling  are  offered  in  various  EU  Member  States  and  they  appear  to  have 

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promising  results19.  An  evaluation  of  a  Finnish  start-up  grant  in  2006,  for  example, 
suggested more support and advice for the applicants would be helpful during the start-
up  process.  The  evaluators  of  ‘Wings  for  business’,  a  small  project  supporting 
unemployed people with a disability in the Wielkopolska region of  Poland, found that all 
22 participants successfully started a company. They believed the coaching and training 
sessions that were provided alongside financial support were one of the reasons for this 
success.  They  also  highlighted  the  fact  that  the  trainers  and  advisers  had  experience  of 
working with potential entrepreneurs starting off as unemployed. The strongest evidence 
comes from an Austrian microcredit programme. Unemployed people - or people who are 
at risk of losing their job - who want to become self-employed can apply for credit, which 
is accompanied by consultancy and training. A 2013 evaluation shows  that around 90% 
of  the  participants  were  still  self-employed  at  the  time  of  the  survey.  On  average,  0.4 
additional workplaces were created by the new enterprises. The evaluation identified the 
individual  support,  advice  and  assistance  as  a  key  success  factor.  This  support  was 
provided at all stages of the start-up. 

The  usefulness  of  different  support  varies  according  to  the  stages  of  the  business 
creation  process.  The  evaluation  of  the  financial  contribution  for  the  Self-Employment 
Scheme  in  the  Slovak  Republic,  for  example,  considered  training  as  the  key  factor  to 
success  at  the  early  stages  when  participants  were  implementing  their  business  plan. 
Business  counselling,  on  the  other  hand,  was  considered  important  during  the  phases 
after  business  start-up.  The  Slovak  scheme  supports  people  in  work  as  well  as  disabled 
people  expressing  an  interested  in  starting  a  business.  Another  example  stems  from  a 
pilot project by the Gdansk Municipal Employment Office ran in 2009 and 2010 - Mature 
Entrepreneur. The project supported unemployed or inactive older people who wanted to 
become self-employed. It offered a variety of support services. As well as a grant and a 
bridging  allowance,  these  services  included  training,  coaching  and  mentoring,  business 
advisory  services,  and  network  opportunities.  Training  was  a  mandatory  component  of 
the  project  and  participants  would  only  receive  financial  support  and  coaching  and 
mentoring  after  completing  this  training.  In  practice,  the  participants  felt  that  this 
requirement kept them from setting up the business. They valued what they learned but 
they  wanted  the  training  to  be  shorter  or  conducted  in  parallel  with  setting  up  their 
business. Whether this lock-in effect was justified by subsequent impacts on employment 
or income is unknown. 

Further  research  is  needed  to  know  which  combination  works  best,  for  which  target 
groups and under which circumstances. 

4.4.3  Coaching and mentoring 

Both coaching and mentoring can be peer-based or professional, and they can be either 
face-to-face  or  online.  Coaching  aims  to  develop  the  skills  of  an  entrepreneur  and  it  is 
more likely to be a short-term relationship between coaches and benefit recipients. In the 
case  of  mentoring  an  experienced  person,  the  mentor  would  assist  the  mentee  in 
developing  skills  and  knowledge,  but  also  in  furthering  their  personal  development. 
Mentoring  focuses  less  on  specific  issues  than  coaching,  and  generally  the  relationship 
will last longer. In the EU, public policy tends to favour mentoring support programmes, 
probably because of the lower  costs associated with such programmes (OECD/European 
Union, 2015). 

19  

The examples provided in this section are derived from OECD/European Union (2015). 

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Coaching and mentoring benefits 

include  action 

The  benefits  of  coaching  and  mentoring,  according  to  the  literature,  are  manifold. 
learning  and  knowledge  absorption  capability  among 
They 
entrepreneurs,  they  help  build  confidence,  motivation,  and  a  range  of  skills  for 
entrepreneurship and they may even include access to resources such as finance and 
better  access  to  suppliers  and  customers.  Although  often  cited,  these  advantages 
have  not  been  extensively  studied  so  far.  More  informal  sources  have  led  to  the 
identification  of  important  factors  determining  success  or  failure.  These  include 
(OECD/European Union, 2015): 

- 

- 

An appropriate matching process between mentees and mentors  

Ease of accessing the mentor (i.e. location of meetings) 

- 
The  relationships  often  begin in  a  face-to-face  manner  but  should  be  allowed 
to  develop  according  to  the  needs  of  each  party.  This  flexibility  can  improve  the 
attractiveness  of  the  support  for  coaches  and  mentors,  as  well  as  for  coaches  and 
mentees 

A  set  of  objectives  developed  for  the  relationship  and  monitoring  of  progress 

- 
towards these goals  

Coaching  and  mentoring  relationships  should  have  a  fixed  duration.  This 

- 
avoids the construction of a relationship of dependence. 

4.4.4  Other measures 

There is and probably always will be a role for information and sign-posting services 
that  alert  people  in  general,  and  vulnerable  groups  and  unemployed  in  particular,  to 
make them aware of entrepreneurship as a career. Information and sign-posting services 
have the advantage of being broadly aimed, having a wide reach, and they are cheaper 
than  other  start-up  services.  They  are  therefore  useful  both  as  a  first  step  and  as  a 
supporting  measure  to  the  above-mentioned  services  (OECD/European  Commission, 
2014b). 

Evidence  on  the  effectiveness  of  training  measures  for  entrepreneurs  was  found,  but 
studies  reviewed  by  Duell  (2011)  point  to  a  number  of  issues  that  need  addressing. 
These  apply  to  entrepreneurship  training  for  young  people  in  general,  but  the  following 
elements  also  apply  to  the  training  of  unemployed  who  embark  on  this  path.  Various 
studies  recommend  that  training  programmes  devote  more  time  to 
teaching 
entrepreneurial skills as well as the (often present) managerial skills. The OECD identified 
three main groups20: 

●  Technical – communication, environment monitoring, problem solving, technology 

implementation and use, interpersonal and organisational skills. 

●  Business  management  –  planning  and  goal  setting,  decision-making,  human 
resources  management,  marketing,  finance,  accounting,  customer  relations, 
quality control, negotiation, business launch, growth management and compliance 
with regulations. 

●  Personal  entrepreneurial  –  self-control  and  discipline,  risk  management, 
innovation,  persistence,  leadership,  change  management,  network  building,  and 
strategic thinking. 

Generic  and  horizontal  skills  are  also  seen  as  a  valuable  asset  that  can  be  passed  on 
during training. The training should aim to make students more creative and innovative, 
more  pro-active  and  self-confident,  and  better  at  communication,  team  work  and 

20  

Quoted  in:  Analytical  highlight  -  Focus  on  Entrepreneurial  skills,  EU  SKILLS  PANORAMA 
2014, European Commission, April 2015 

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decision-making. The ability to take risks and recognise opportunities are also skills that 
are useful for all workers, but especially for the self-employed (Duell, 2011). 

4.4.5  Infrastructure for entrepreneurship 

It  stands  to  reason  that  the  implementation  of  measures  and  the  design  of  the  support 
infrastructure influence the outcomes of ALMPs, including start-up incentives. 

A study on youth start-up support programmes presented some evidence that changes in 
the  support  structure  can  improve  the  outcomes  of  such  programmes  (OECD/European 
Union, 2012a). However, few studies really focused on youth.  

A  policy  brief  on  sustaining  self-employment  for  disadvantaged  groups  (European 
Union/OECD,  2015b)  draws  attention  to  the  need  for  capacity  building  ‘on  the 
institutional side’. This includes general business support organisations, but also officers 
working within public agencies such as PES. For them capacity building should include the 
ability  to  work  with  potential  entrepreneurs  from  different  and  often  disadvantaged 
groups. 

4.5  Effectiveness for specific groups 

4.5.1  The significance of personal characteristics 

Although  -or  perhaps  because  -  disadvantaged  groups  are  less  likely  to  become  self-
employed, specific groups such as male, middle-aged participants, and participants with 
an  apprenticeship  or  secondary  education  showed  higher  start-up  rates  (EEPO,  2014). 
Caliendo (2016), on the other hand, found that ‘personal variables’ had only a small and 
statistically  insignificant  influence  on  the  effects  of  start-up  subsidies.  He  was  able  to 
perform  very  precise  analyses  because  he  was  working  with  a  combination  of 
administrative  and  survey  data.  However,  it  could  be  that  the  effects  of  personal 
characteristics did not show up in his analysis, because they already exert their influence 
through  other  variables  in  the  database,  such  as  human  capital  attainment,  labour 
market  and  employment  histories.  Caliendo  himself  assumes  that  one  way  or  another 
personal  characteristics  do  indeed  influence  the  outcomes  of  programmes.  He  confirms 
that subsidised start-up programmes seem to be particularly effective for disadvantaged 
groups, e.g. low-educated workers or young people. 

For Germany, Csillag and Fertig (2015) found that that specialised measures for selected 
sub-groups,  such  as  clients  planning  self-employment,  tend  to  have  positive  effects  on 
long-term unemployment. 

4.5.2  Women 

Evidence  on  the  effectiveness  of  start-up  support  for  women  is  scarce.  According  to 
Caliendo and Künn (2012), there are only few studies that show female-specific effects. 
They present evidence from Spain showing high survival rates after two years as well as 
after  five  years.  For  women,  these  depend  primarily  on  personal  characteristics  such  as 
education  and  marital  status.  For  men,  the  effects  depend  above  all  on  their  economic 
situation  (as  the  main  source  of  household  income).  Australian  data  shows  comparable 
survival  rates  for  men  and  women,  but  fewer  hours  for  women.  They  conclude  that  the 
existing  data  shows  that  supporting  unemployed  women  in  their  journey  to  self-
employment  can  be  quite  promising,  and  more  promising  than  traditional  ALMPs.  It 
would also seem that women use self-employment in a flexible way (such as in parallel to 
other jobs, or with fewer working hours). 

Caliendo  and  Künn  (2010,  2012)  themselves  followed  participants in two  German  start-
up programmes –SUS and BA- up to five years after they launched their business. They 

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found that these programmes were able to integrate former unemployed women into the 
labour  market  and  improve  their  income  situation.  They  found  large  and  significant 
employment  effects  for  female  participants  that  were  three  to  four  times  as  large  as 
those  estimated  for  traditional  ALMP  programmes.  In  addition,  the  women  participating 
in  these  programmes  were  more  likely  to  remain  economically  active  and  less  likely  to 
quit  the  labour  force.  Finally,  the  impact  of  start-up  subsidies  on  childbearing  is  less 
detrimental  than  other  ALMPs,  which  suggests  that  these  programmes  and  the  self-
employed lifestyle allows women to realise a better work-life balance. The effects did not, 
however, include a clear increase in working income 56  months after  start-up. Caliendo 
and  Künn  suggest  that  women  become  self-employed  because  there  are  fewer 
opportunities  in  the  regular  labour  market.  Women  do  not  seem  to  make  this  choice  to 
achieve higher incomes. Although the authors do not say so, this is something that may 
apply to other groups participating in start-up schemes. 

4.5.3  Young people 

Evaluations  of  start-up  programmes  aimed  at  young  people  are  limited  in  number, 
especially  those  that  really  allow  reliable  conclusions  on  effectiveness.  Based  on  UK 
evidence in, the OECD/European Union policy brief on youth entrepreneurship (2012a), it 
would  seem  that  mentoring  services  increase  start-up  rates  amongst  young  people. 
According  to  Duell  (2011),  start-up  incentive  programmes  for  young  people  should 
include access to financial resources, as young people are less likely to have accumulated 
such resources in the past and financial services have no objective grounds to trust their 
credibility. 

A  thorough  review  of  evaluations  of  youth  programmes  was  conducted  by  Sara  Riso 
(Eurofound 2016b). She systematically reviewed evaluations of start-up programmes for 
young  people  in,  amongst  others,  France,  Sweden  and  the  United  Kingdom.  She 
concludes that the evidence is mixed and has some serious methodological shortcomings. 
A  clear  outcome  seems  to  be  that  targeting  and  selection  for  participation  in  such 
programmes leads to higher results. In several cases it appears that more sophisticated 
evaluations  of  programmes  show  lower  results,  because  they  show  unintended  side 
effects. Sometimes programmes seem to have few results, but these may still emerge in 
the longer term, i.e. many years later. It should be noted that in this more rigorous meta 
evaluation,  the  results  are  defined  as  effects  caused  by  the  programme  and  always 
compared to a situation where the programme had been absent. 

4.5.4  Migrants 

Evidence on the effectiveness of start-ups for migrants is virtually non-existent at the EU 
level.  An  evaluation  of  the  Swedish  Public  Employment  Service's  start-up  grants  shows 
that the effects of the grants are smaller for people that are foreign born than for those 
born  in  Sweden.  Foreign-born  entrepreneurs  were  also  more  often  than  in  a  position  of 
economic vulnerability (Swedish National Audit Office, 2012) The limited evidence on the 
survival  rates  of  businesses  operated  by  foreign-born  entrepreneurs  is  also  found  in 
France,  where  lower  survival  rates  were  found  for  businesses  operated  by  foreign-born 
entrepreneurs  than  for  those  operated  by  native-born  entrepreneurs  (OECD/European 
Commission, 2014b) 

4.5.5  Older people 

PES  activation  strategies  in  most  Member  States  include  active  measures  to  facilitate 
transitions into self-employment for older workers (Hake B,2011). The Dutch PES is one 
of the PES offering specific programmes for self-employment to older workers who have 
become unemployed. Been and Knoef (2015) found that in the Netherlands end-of-career 

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unemployed individuals are more likely to become self-employed than others. They also 
found that this effect is significantly increasing with age. 

This  age  group  is  also  more  likely  to  seek  a  combination  of  open-ended  part-time 
employment  with  self-employment.  This  has  proven  to  be  a  successful  strategy  for 
enhancing  employment  and  income  security  beyond  the  standard  full-time  employment 
contract  (Hake,  2011).  Older  workers  are  also  prominent  amongst  people  with  portfolio 
careers,  or  they  choose  a  path  involving  alternating  paid  part-time  self-employment, 
periods  of  unpaid  work,  and  the  flexible  transition  into  permanent  retirement  (Hake, 
2011).  Such  portfolio  careers  are  more  common  amongst  unemployed  highly  skilled 
professional workers, often in the media, financial services and creative industries.  

4.5.6  People with disabilities 

Whereas  self-employment  can  be  a  very  suitable  option  for  people  with  disabilities,  the 
disabled tend to be as unaware of the desirability and feasibility of this career choice as 
the  able-bodied.  Studies  also  report  a  fear  amongst  benefit  recipients  of  losing  the 
safeguard of benefits while earning another income. This is can be a real issue, but it is 
also  exacerbated  by  poor  knowledge  of  social  benefit  systems  amongst  this  group 
(OECD/European Union, 2014, Eurofound, 2012b). 

If self-employment does not offer adequate income security depending on the design of 
the relevant social protection schemes, there is a risk of poverty and social exclusion. A 
2003 OECD report addressing this issue mentions ‘cumbersome award periods’ as well as 
the difference in income between work and benefits as possible explanations for the ‘non-
existent  outflow’  from  disablement  benefits  into  work  OECD  (2003).  The  existence  of 
these  benefits  trap  was  more  recently  mentioned  in  various  EU  and  international 
publications  (European  Parliament,  2010,  European  Commission,  2017).  The  OECD/EU 
disability policy brief states that “this trap problem should be addressed by ensuring that 
the welfare system does not cut benefits too quickly on transition to entrepreneurship or 
discriminate unfairly against those disabled people who chose to become entrepreneurs” 
(OECD/European Union, 2014). 

Some countries have rules that allow benefit to be put on hold for a few years and then 
revive  benefits  if  the  work  experience  fails,  some  countries  have  work  incentives  to 
encourage  recipients  of  disablement  benefits  to  find  work.  However,  it  would  seem  that 
the take-up of such schemes is often low. All in all, low outflow may be due above all to a 
lack  of  opportunities  (OECD,  2003).  A  more  recent  report  (Eurofound,  2012b)  mentions 
some examples where benefit systems have been adjusted and tailored to the individual 
situation,  to  ensure  they  do  not  inhibit  entry  or  re-entry  into  employment.  Examples 
include the possibility of combining an incapacity pension with a wage earned from a job 
(Spain), and an ‘income disregard’ scheme allowing people with disabilities to earn up to 
a certain amount per month before losing their disability benefit (Ireland). A 2011 report 
had called for various changes, as people with disabilities in Ireland stood to lose various 
allowances  when  finding  work.  Depending  on  the  individual  situation,  this  could  include 
their medical card (when income is above the upper threshold) or the Household Benefits 
Package, Free Travel, their Mobility Allowance and their Rent Allowance (NDA, 2011). 

There  is  some  evidence  that  targeted  entrepreneurship  training  and  start-up  support 
programmes  can  be  effective  for  people  with  disabilities.  Existing  training  and  start-up 
programmes would partly need to be adapted for people with disabilities, e.g. in terms of 
formats  (such  as  Braille)  and  language,  and  longer  term  support  should  be  available  if 
necessary. Use can nowadays be made of many assistive technologies and improvements 
in  IT  and  Internet  accessibility.  Programmes  for  people  with  disabilities  are,  however, 

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likely to be relatively expensive. Start-up programmes for people with disabilities need to 
address the potential benefits trap (OECD/European Union, 2014). 

5  Conclusions and recommendations 

5.1  The rationale behind start-up support 

Important  considerations  underlying  the  tasks  and  competencies  of  PES  are  the 
transparency  of  labour  markets  and  the  ability  of  various  groups  of  jobseekers  to 
successfully  navigate  their  employment  career.  This  is  confirmed  by  the  fact  that 
supporting vulnerable social groups with high unemployment rates and the integration of 
persons excluded from the labour market as part of the combat against social exclusion 
are explicit objectives in the co-operation between PES in the EU21. 

The  present  overview  study  yields  a  number  of  arguments  for  including  start-up 
incentives in the services offered by PES: 

•  An  overlap  exists  between  groups  specifically  targeted  by  PES,  and  groups  that 
face more than average barriers to becoming self-employed, and these groups are 
often  underrepresented  amongst  the  self-employed  population  in  different 
countries. 

•  Start-up  incentives  have  been  proven  effective  in  bringing  unemployed  and 
specific  labour  market  policy  target  groups  back  to  the  labour  market,  either  as 
self-employed or employed. 
In  certain  respects,  start-up  incentives  are  more  effective  than  other  labour 
market  measures.  The  costs  of  the  actual  start-up  incentives  seem  to  outweigh 
the  benefits.  Accompanying  measures  increase  their  effectiveness,  but  they  also 
negatively impact the cost-benefit ratio. 

• 

Information  on  costs  and  the  relationship  between  benefits  and  costs  is,  as  yet,  not 
properly researched. It is clear, though, that this is an important factor when considering 
scaling up this measure. Two other important considerations are the importance of self-
employment  in  the  national,  regional  and  local  economy  and  the  unemployment  rate. 
High  levels  of  either  could  be  arguments  in  favour  of  the  increased  application  of  this 
type  measure,  even  when  taking  into  account  the  (likely)  unwanted  side  effects.  Self-
employment,  especially  in  the  case  of  people  getting  low  levels  of  benefit,  may  be  the 
only opportunity to gain a certain level of income. It may prove to become a permanent 
route  out  of  unemployment  or  inactivity,  and  it  may  at  least  provide  those  who  tried  it 
with  new  skills  and  demonstrable  work  experience.  Certain  characteristics  of  the 
envisaged self-employment would argue against stimulating self-employment under such 
circumstances. This would notably include the need to make heavy capital investments or 
known abuse of self-employed workers in a specific sector or occupation. 

The information about deadweight and displacement effects is scarce. It is apparent that 
they  do  occur,  however,  deadweight  effects  may  not  be  as  high  as  is  often  assumed. 
These  effects also seem to be more tolerable and more accepted when the problems to 
be addressed are greater. 

Distortion  of  competition  is  unlikely  to  occur  as  a  rule,  because  of  the  relatively  small 
scale of these programmes. However, it makes sense to assess individual business plans 
on potential negative effects, taking into account the occupation and sector concerned. 

21  

Decision No 573/2014/EU of the European Parliament and of the Council of 15 May 2014 on 
enhanced cooperation between Public Employment Services (PES). 

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5.2  Start-up support 

This  section  summarises  the  lessons  that  were  drawn  in  the  meta  evaluations  and  peer 
reviews discussed in the previous chapters. 

5.2.1  Programme design 

Start-up  measures  should  respond  to  the  needs  different  groups  face.  The  programme 
content and design should take account of the different circumstances and preferences of 
specific  groups.  Young  people  are  more  likely  to  encounter  scepticism  on  the  part  of 
financial institutions and mainstream business advisors. Ethnic minorities and immigrants 
are more likely to lack awareness of the support available, but may be able to rely more 
on networks within their ethnic group (OECD/EU, 2016). The support provided in addition 
to financial support, as well as the timing and the channels used, can be adapted to the 
target group’s needs. 

When  designing  start-up  measures,  social  objectives  (the  employment  of  individuals 
disadvantaged 
(supporting 
entrepreneurship per se) should be clearly distinguished and choices should be made on 
their  inclusion  and  weight.  Confusion  over  objectives  and  target  groups  is  a  risk  that 
should be avoided (EEPO, 2014). 

labour  market)  and  economic  objectives 

the 

in 

A targeted approach can be accompanied by a selection process. A key element in such a 
process is the requirement to prepare a business plan, as this will very much help assess 
the viability of the business, as well as the capacities of the applicant. The preparation of 
such a plan is also seen as an opportunity to acquire knowledge and experience that may 
result  in  other  forms  of  employment,  should  the  business  start-up  not  succeed  (BMAS, 
2010). 

5.2.2  Programme delivery 

The correct implementation of policies, with sufficient resources allocated to programme 
administration,  increases  the  positive  effects  of  start-up  programmes  (Escudero,  2015). 
An  important  question  regarding  the  delivery  of  programmes  is  extent  to  which 
programmes  should  be  targeted  for  specific  groups.  Policy  delivery  models  ‘range  from 
full integration into the mainstream provision to the use of specialist agencies delivering 
tailored support to specific target groups’ (OECD/EU, 2016). Roughly speaking, targeted 
delivery will increase the effectiveness of programmes, while more integrated support is 
less costly. 

Inclusive  entrepreneurship  policies  and  programmes  should  be  developed  and  delivered 
as  part  of  an  integrated  strategy  (OECD/EU,  2016).  It  is  important  to  align  start-up 
support schemes with tax and social security schemes to avoid a benefit trap and ensure 
complementary policy approaches. Developing a strategic framework of economic policies 
and information on the local economic context  may help create public support for  start-
ups for the unemployed (BMAS, 2010). 

Adequately  delivering  start-up  support  requires  specialist  trainers  and  advisers. 
Therefore,  PES  staff  dealing  with  such  programmes  should  receive  adequate  support 
themselves,  or  external  expertise  should  be  engaged  (OECD/EU,  2016).  Insufficient 
quality  of  managerial  and  entrepreneurial  counselling  offered  by  job  centres  is  listed  as 
one  of  the  constraining  factors  for  effective  start-up  support  to  the  unemployed  (EEPO, 
2014). 

To this end, seeking synergies with other initiatives delivered by agencies and ministries 
with  an  economic  portfolio,  such  as  business  incubators,  has  also  been  advocated.  PES 

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can  cooperate  with  chambers  of  commerce  for  the  provision  of  information,  assistance 
and coaching (BMAS, 2010).  

5.2.3  Start-up and accompanying measures 

A  key  element  of  start-up  incentives  is  the  provision  of  income  security,  e.g.  through 
continued unemployment benefit, disability benefit or other allowances. Providing access 
to capital is also important as disadvantaged groups are likely to encounter barriers when 
approaching  financial  services.  However,  though  it  is  not  explicitly  mentioned  in  the 
literature, the need for  capital is likely to be dependent on the kind of business created 
and  the  availability  of  their  own  financial  means,  as  well  as  the  accessibility  of  external 
resources to target groups. 

In  many  cases  financial  support  will  be  more  effective  when  it  is  combined  with  other 
measures  such  as  training  and  counselling.  Developing  an  appropriate  mix  of  support 
measures should take into account coherence with existing general start-up measures as 
well  as  the  wider  environment  of  business  support.  Actions  creating  a  positive  attitude 
towards  entrepreneurship  amongst  the  target  group  and  sensitising  support  services  to 
their  needs  can  be  part  of  this  package  (e.g.  EEPO  2014,  OECD/  European  Commission 
2014b, BMAS 2010). 

During  the  seed  or  pre-start-up  phase,  the  provision  of  information,  advice,  mentoring, 
and expertise is of particular importance. Business counselling is relevant in the prestart-
up  and  start-up  phase,  guidance  and  coaching  continue  to  be  relevant  throughout  the 
programme. The need for training depends to a large extent on individual characteristics, 
but it is important that entrepreneurial skills are never neglected. Once businesses are up 
and running smoothly, additional services can be considered to promote and support the 
creation of additional employment (EEPO, 2014). 

5.3  Start-up support for specific groups 

Although  various  studies  confirm  that  start-up  incentives  are  effective  in  integrating 
various  groups  of  unemployed,  the  evidence  on  whether  programmes  work  better  for 
some  groups  rather  than  others  is  limited.  The  evidence  presented  in  chapter  4  is 
summarised  in  the  table  below.  Although  women  are  less  likely  to  actually  start  a 
business as a result of following a start-up programme, the programme does succeed for 
those women that start off with more sustainable employment (such as income and the 
ability of the business to survive) than men. This may signify that the initial stages of the 
programme  have  been  more  effective  for  women  in  determining  whether  the  idea  they 
were  pursuing  was  promising  enough.  Furthermore,  start-up  incentives  seem  relatively 
effective for young people and relatively less effective for migrants and ethnic minorities. 
The evidence for both these groups is less conclusive than for women. 

Table 5 

Relative effectiveness of start-up incentives for target groups* 

Women 

Young people  Older people  Migrants 

Start-up rate 

Lower 

No evidence 

Higher 

No evidence 

Survival rate 

Higher 

Income 

Higher 

Higher? 

Higher? 

No evidence 

No evidence 

Lower? 

Lower? 

* As so few start-up programmes for people with disabilities exist, they have not been included in 
this table 

Of course, every sub-population is in turn a population with many sub-groups in itself. In 
addition,  one  individual  has  different  characteristics,  for  example  women  from  migrant 
families, men from deprived areas, young people from low income families, older people 
with low education levels and so on. 

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EUROPEAN COMMISSION 

The  table  on  the  following  pages  provides  policy  makers  with  a  series  of  points  to  be 
taken  into  account  when  designing  start-up  measures.  Anticipating  the  combination  of 
characteristics is important, as are exceptions to the rule when making use of this table. 

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Table 6 

Specific barriers for self-employment for selected target groups 

EUROPEAN COMMISSION 

Women 

Young people 

Older people 

People with disabilities 

Migrants 

Networks 

Smaller and less varied, 
less often including 
business services 
providers or 
entrepreneurs 

Reconciling self-
employment with 
family 
responsibilities 

Financial barriers 

Highly pertinent, but self-
employment may at the 
same time provides more 
flexibility than 
employment 

Not reported by 
themselves, but 
discrimination known from 
general research on 
women entrepreneurship 

Older people that are 
away from the labour 
market for a longer 
period, through 
unemployment or 
retirement, may have 
difficulty keeping up or 
updating their networks 

Difficulty building 
networks (newly arrived), 
benefit from contacts 
amongst their ethnic 
group or in the country 
they or their family 
originally came from. 

Greater difficulty in raising 
external finance because 
they lack savings and 
collateral 

Access to start-up due to 
limited personal financial 
resources such as savings 
and home ownership. 

Forced to rely upon non-
bank and informal 
finance. 

Skills barriers 

More often lacking the 
skills to run a business 

Awareness of 
entrepreneurship 
as employment 
opportunity 

Often not sufficiently 
aware of the requirements 
and opportunities of 
entrepreneurship 

Benefit from expertise 
they gained over time, but 
not always disposing of 
entrepreneurship skills, 
skills may be outdated, 
possibly lower levels of 
digital literacy. Retraining 
may also be harder. 

Lack of relevant business 
knowledge and skills, 
more difficulty gaining 
entrepreneurial 
experience and skills 

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Social security 

Other barriers 

EUROPEAN COMMISSION 

Women 

Young people 

Older people 

People with disabilities 

Migrants 

Financial disincentives in 
benefits and pension 
schemes 

Health problems, age 
discrimination, 
opportunity cost of time, 
lack of awareness of 
business opportunities, 
lack of information 
tailored to them (content, 
presentation). 

Constrained by state 
welfare policies, perverse 
effects on the willingness 
to become self-employed 

Increased labour costs, 
lack of appropriate 
(tailored) business 
support services, 
consumer discrimination. 

Difficulty understanding 
regulatory requirements 

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5.4  Start-up support and new forms of work 

Supporting  start-ups  launched  by  the  unemployed  always  has  a  risk  that  the  desire  to 
become  self-employed  is  at  some  level  necessity-driven,  which  implies  that  support  is 
being  given  to  people  less  suitable  for  this  type  of  employment  and  with  less  viable 
business  ideas.  The  post-crisis  upsurge  of  new  forms  of  work  is  likely  to  provide  a  new 
impetus to societal and political concerns about the quality of jobs created by these start-
up incentives. 

Important  new  forms  of  work  are  collaborative  employment,  crowd  employment,  and 
portfolio  work.  In  more  general  terms,  the  concerns  relate  to  low  income  generated  by 
the new businesses and their overall precariousness or unsustainability. 

So far, no evidence has been collected or found on a possible contribution made by start-
up  incentives  to  the  creation  of  non-sustainable  or  to  ‘bogus’  self-employment,  at  least 
not on a substantial, measurable scale. 

Nevertheless,  PES  cannot  ignore  this  issue  completely  for  a  number  of  reasons.  First  of 
all, bogus self-employment is a small phenomenon, but may be relatively high amongst 
certain  target  groups  (low  skilled,  older  workers)  and  in  certain  sectors.  Also,  the 
possibility  cannot  be  disregarded  that  an  increasing  inflow  of  participants  motivated  by 
opportunities  offered  (such  as  platforms)  does  indeed  happen.  This  may  increase  the 
chances of the creation of precarious and non-sustainable (self-) employment. For certain 
countries,  the  issue  will  be  more  pertinent  than  others,  as  the  new  forms  of  work 
relevant  to  self-employment  are  clearly  dominant  in  some  countries,  and  far  less 
frequent in others.  

PES  cannot,  of  course,  be seen as  supporting the creation of non-sustainable or ‘bogus’ 
self-employment.  It  is  therefore  important  that  they  be  able  to  demonstrate  that  either 
the  issue  is  not  relevant  in  their  case,  or  that  adequate  measures  have  been  taken  to 
counteract  negative  effects.  Such  measures  can  be  included  in  the  selection  and 
targeting, and in the follow-up processes. 

5.5  Monitoring and evaluation of start-up measures 

5.5.1  Considerations and recommendations for monitoring and evaluation 

The  sources  used  in  this  review  already  list  some  recommendations  for  future  research 
and  evaluations.  They  also  draw  attention  to  a  number  of  specific  features  of  start-up 
incentives  that  should  be  taken  into  account.  Building  on  EEPO  (2014)  and  OECD/EU 
(2013) in particular, the following suggestions are made: 

• 

Impacts:  evaluations  should  go  beyond  the  assessment  of  direct  effects  such  as 
start-up and survival rates, and also include secondary effects and wider impacts 
in terms of sustainable labour market integration and social inclusion; 

•  Economic  development,  at  sector  and  local  level,  and  especially  in  the  case  of 
large  programmes  should  be  considered  when  designing  and  evaluating 
programmes.  The  assertion  that  target  groups  for  these  measures  more  often 
start their business in low-growth sectors and saturated markets warrants further 
exploration; 

•  Occupation  and  sector  analysis  are  oddly  absent  in  most  studies  reviewed  here, 
although  it  stands  to  reason  that  they  are  important  determining  factors  for 
successful  business  start-ups.  It  would  make  sense  to  include  them  in  M&E 
exercises; 

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• 

• 

Longitudinal  studies:  longitudinal  research  into  the  impact  of  start-ups  is  needed 
to  properly  evaluate  their  effectiveness  and  compare  the  impacts  with  other 
ALMPs; 
Long-term impacts: this will also help to assess the longer-term effects (survival 
rates, income) and the mid- and macro- level impacts of incentives; 

•  Assessing  causal  relationships  and  macro  effects  requires  highly  technical 
research. As good examples are scarce at present, it would help if methodological 
tools  were  further  developed  at  EU  level,  as  well  as  sharing  experience  and 
expertise,  both  for  those  outsourcing  and  those  conducting  this  type  of 
evaluations; 

•  Relative  impact  on  specific  groups:  evaluations  of  measures  aiming  at  different 
target  groups  and  general  measures  should  systematically  compare  the  effects 
and impacts of start-up incentives on different target groups; 

•  Bogus  self-employment:  measurement  of  this  phenomenon  remains  complicated 
and  currently  evaluation  data  is  not  available  to  fully  understand  the  extent  and 
implications  of  bogus  self-employment  in  the  context  of  start-up  incentive 
schemes. 

•  Costs and benefits: cost and benefits should be compared more systematically. At 
the same time it is important to take an intelligent approach when conducting this 
sort  of  analysis.  As  with  other  measures  targeted  at  groups  facing  specific 
difficulties, costs will be higher than for other unemployed sectors or regular start-
ups. 

•  Baseline  and  benchmarks:  when  assessing  the  effects  of  start-up  incentives  it 
should be clear what they are being assessed against, e.g. other ALMPs, start-up 
incentives  for  other  groups  of  jobseekers,  or  start-up  incentives  aimed  at  the 
general  population?.  Specific  surveys  may  help  create  a  baseline  for  assessing 
progress made through time. 

•  Evaluations should take into account the policy context of start-up incentives and 
include other services provided to the self-employed by the PES, as well as those 
provided by other stakeholders. 

5.5.2  Evaluation criteria when assessing start-up incentives 

In their policy brief on the evaluation of inclusive entrepreneurship the EU and the OECD 
(OECD/EU,  2013)  present  an  overview  of  how  evaluation  criteria  can  be  applied  in  the 
framework of start-up incentives. These can be used when designing an evaluation. The 
type of question asked points to the information to be gathered and the kind of answers 
that can be expected from such an evaluation. The report also provides a useful overview 
of indicators which is annexed to this report. 

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Table 7 

The use of evaluation criteria when evaluating start-up incentives 

Measure  
Relevance  

Effectiveness  

Efficiency  

Impact  

relative 

Definition  
The extent to which the activity 
is  suited  to  the  priorities  and 
policies  of  the  target  group, 
government 
and 
recipient 
(objectives versus needs).  
The  extent 
the 
to  which 
intervention’s  objectives  were 
achieved, or are expected to be 
achieved,  taking  into  account 
their 
importance 
(outcomes versus objectives).  
The  outputs  in  relation  to  the 
inputs.  This  is  an  economic 
term  which  signifies  that  the 
intervention  uses 
least 
costly  resources  in  achieving 
the  desired 
(inputs 
versus outputs).  
The  positive  and  negative 
changes  produced  by  a  policy 
or 
intervention, 
indirectly, 
or 
unintended  (objectives  versus 
outcomes).  

directly 
intended 

results 

the 

Sustainability   Whether  the  benefits  of  an 
activity  are  likely  to  continue 
after 
been 
withdrawn.  

funding 

has 

Example questions  
Is  finance  still  a  barrier  to  female 
entrepreneurship?  Do  changes  in 
regulations  related  to  disablement 
benefits  make  it  impossible  for 
women to start-up businesses?  
Was  the  target  number  of  youth 
enterprises  started?  Did 
they 
survive for two years? 

ways 

efficient 

What  was  the  cost  per  person 
advised?  What  was  the  cost  per 
(for  example)  Roma  job  created? 
What  percentage  of  clients  was 
from the target group? Were there 
more 
of 
implementing the action?  
Is  there  now  a  higher  rate  of 
business  ownership  and  self-
employment  in  the  target  group? 
Is there now a higher employment 
rate  for  the  target  group?  Has 
social inclusion increased?  
scheme 
Will 
established 
senior 
entrepreneurs  be  self-financing? 
Is  the  advice  centre  capable  of 
retaining 
has 
developed?  Is  there  a  need  for 
further public support? 

the  microcredit 

skills 

the 

for 

it 

Source: OECD/EU (2013), table 1 

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Annex 

Indicators  for  monitoring  and  evaluation  of  start-up 

incentives 

Type of 
indicator  
Baseline 
indicators for 
target groups  

Policy activity 
indicators  

Customer 
satisfaction 

Policy output 
indicators 

Policy outcome 
indicators  

Policy impact 
indicators  

Examples  

Typical questions  

Number of business owners 
Number of self-employed 
Business start-up rate 
Rate of entry to self-employment  
Number of people supported by 
policy 
Proportion of beneficiaries from 
target groups  

Participants’ views on quality of the 
programme 
Is the delivery method appropriate?  
Change in the proportion of 
entrepreneurs accessing business 
loans 
Change in the proportion of 
entrepreneurs with business training 
Change in attitudes to 
entrepreneurship and self-
employment  
Rate of business start-ups by ‘policy 
beneficiaries’ 
Rate of entry to self-employment by 
‘policy beneficiaries’ 
Survival rate after 6 months, 1 year, 
3 years 
Employment in businesses created  
Number of beneficiaries in 
employment after a period of time  
Income of beneficiaries after a 
period of time  

Is inclusive entrepreneurial 
activity growing?  
Where are the gaps?  

Are the activities relevant 
to beneficiaries’ perceived 
needs?  
Are the beneficiaries those 
with the greatest need?  
Are there key barriers not 
addressed by the 
programme?  
How far is the policy 
addressing barriers to 
entrepreneurship in the 
target group?  

Does policy support lead to 
business creation?  
Are the businesses 
sustainable?  

Even if the enterprises did 
not survive, has the 
experience benefited the 
beneficiaries of the 
programme? 

Source: OECD/EU (2013), table 4 

Directorate-General for Employment Social Affairs and Inclusion  
European Network of Public Employment Services 

52 

 
 
 
 
 
 
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