Youth Entrepreneurship: Latent Entrepreneurship, Market
Failure and Enterprise Support
Francis. J. Greene
Working Paper No. 87 - June 2005
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2
Youth Entrepreneurship: Latent Entrepreneurship, Market
Failure and Enterprise Support
Introduction
For the last twenty-five years, public policy makers have sought to increase the
entrepreneurial capacity of young people. Initially, this was a response to the
endemic youth unemployment of the early 1980s (Greene, 2002), but more latterly
there has been a concern to bridge the gap between the world of work and education
(Straw and Blair, 1991). Hence, in the UK, there have been a variety of schemes (e.g.
School ‘Compacts’, the Technical and Vocational Educational Initiative and
Education Business Partnerships) that sought in the 1980s and 1990s to prepare
students for work. There have also been schemes, run by voluntary providers such as
Young Enterprise, or by the UK government (e.g. Mini Enterprise in Schools Project,
Enterprise Awareness in Teacher Education, Education and Enterprise Initiative) that
were designed to improve the entrepreneurial awareness of teenagers. The latest
iteration of this process is the Davies report (2002) which advocated the compulsory
introduction of five days of entrepreneurial learning for secondary level students at a
cost of £60 million by 2005/06 (HM Treasury, 2002).
At the post secondary level, there has been a long term concern about the supply of
young graduate entrepreneurs (Gibb et al, 1984; Scott and Twomey, 1988). Since the
1980s, then, there have been a number of university based schemes (e.g. Graduate
Enterprise Programme, Enterprise in Higher Education and the Science Enterprise
Challenge).
There is also a plethora of enterprise schemes designed to specifically help young
people to start and run their own businesses. Perhaps the best known examples of
such schemes are the Prince’s Trust, Shell Livewire, the New Deal for Young People
(UK), Law 44 (Italy), Youth Business Initiative (Australia) and Atlantic Canada. In
fact, it is estimated that there are at least 68 major initiatives specifically targeted at
young people in Europe (European Commission, 2003).
What all of these schemes are designed to do is to increase the entrepreneurial
capacity of young people and increase their take up of such options. This discussion
paper considers the likely basis for such support. It considers young people to be
aged 18-24 because much of the available information is about this age group rather
than specific groups within it (e.g. graduates). The empirical international evidence
suggests that young people find their entry into the labour market complex and
protracted. It is also clear, again based on UK, EU and US data, that there are high
levels of latent entrepreneurship amongst young people. Available evidence suggests
that these high levels of latent entrepreneurship are not translated into concomitant
levels of young people setting up and running their own business.
The second part of this briefing, therefore, provides empirical evidence to suggest that
market failures prevent increased awareness of entrepreneurship and the take up of the
entrepreneurial option by young people. Such evidence is often taken as a
justification for interventions to promote entrepreneurship or support entrepreneurship
3
amongst younger people. What, however, is suggested in the third part of the
briefing, is that care must be taken in evaluating any support (Storey, 2003). Existing
general studies of self-employment take-up (e.g. Blanchflower and Meyer, 1994;
Tackey, 1999; and Williams, 2004) already show that only certain groups of young
people are likely to take up the entrepreneurial option (e.g. whites, males, older
individuals). What is also clear from the third part of this discussion paper is that
there is limited evidence for the utility of particular enterprise support schemes.
Section 1: The Basis for Public Support
There are two reasons for supporting entrepreneurship by young people. One is that
markets work inefficiently. Because there is insufficient competition, consumers are
ill-informed, there is some divergence between social returns and private returns or
there is an unwillingness for payment to reflect demand, market failures are likely to
result. This manifests itself in terms of information asymmetries or finance gaps
(Storey, 2003). The second reason for supporting youth enterprise is that public
policy makers desire a social outcome that the market may have failed to supply. For
example, business are interested increased profits for themselves (private returns)
whilst policy-makers are more interested in increased employment (social returns).
These two factors may be linked but an impetus behind public support is to encourage
individuals and firms to meet social goals.
This urge to meet social goals is particularly important in relation to young people.
Schemes such as the Prince’s Trust were, for example, specifically set up in response
to the riots of the early 1980s. These riots were, themselves, blamed upon the fact
that youth unemployment was high (Morton, 1988). This problem persists today. In
the UK, for instance, the unemployment rate (October-December, 2004) for young
people (18-24 year olds) stood at 10.9%. In contrast, the rate for older individuals
(25-49 year olds) was 3.4% for the same period (Source: Labour Force Survey, 2005).
Much the same pattern is also evident internationally. In the EU-15, for instance,
youth unemployment runs at nearly three times the rate of older people (31.2% as
opposed to 11.9%). The situation is much the same in Japan and the US where youth
unemployment rates are more than double that of older people (11.8% and 4.4% (US);
9.5% and 4.2% (Japan)) (Source: European Commission, 2005).
It is also clear that young people’s transitions into the labour market are becoming
more complex and protracted. Statistics Canada (1998) suggest that in 1988, the
transition from secondary schooling to full-time work took six years. By 1998 this
transition took eight years. White (1999), using Australian evidence, has also
indicated that much of the work undertaken by young people is in terms of part-time
employment which traditionally has been of poorer quality than full-time
employment. Grant and Dupuy (1999) further argue that young people are ‘last hired,
first fired’.
Perhaps unsurprisingly, young people have increasingly sought to delay their
transition into work by undergoing longer spells of education. DfES (2004) statistics,
for example, show that nearly three-quarters of young people now enter tertiary level
education. The same data also shows that just over ½ million higher education
qualifications were awarded in 2002/2003 with the bulk of these, some 273,000 being
4
first degrees1. The issue, however, is that there is evidence to suggest that not all of
these graduates will necessarily find employment in ‘graduate’ employment. For
example, AGR estimate that there were 13,026 graduate vacancies for 2004 (Source:
AGR, Winter, 2004). Final year graduates are also pessimistic: only 35% of finalists
believed they would either start a graduate job or be looking for a graduate job after
leaving university (Source: High Fliers Research, 2004).
Blanchflower and Oswald (1998), therefore, suggest that there are five impetuses
behind supporting youth entrepreneurship: 1) it promotes innovation; 2) it creates
jobs; 3) it increases competition in the market place; 4) young entrepreneurs are
responsive to new opportunities and trends; 5) with entrepreneurship goes increased
self-reliance and well-being.
Happily, such outcomes are in line with young people’s perceptions of the appeal of
owning and running their own business. Figure 1 shows, for instance, that although
young people (18-24) in the UK perceive slighter fewer opportunities for the starting
up a business in the following six months, they are more likely to expect to set up a
business in the next three years.
Figure 1: UK GEM 2003: UK adults (18-64) Propensities towards Entrepreneurship
Lots of good opportunities for Start ups in next 6 months
Expects to do Start up in 3 years
45
40
35
Percentage
30
25
20
15
10
5
0
18-24 YRS
25-34 YRS
35-44 YRS
45-54 YRS
55-64 YRS
Source: GEM 2003/Author’s own calculations
Similarly, further GEM evidence (Figure 2) indicates that young people are more
likely to believe that entrepreneurship represents a good career choice and that it
brings status. Such evidence is also supported by a range of other studies (Cannon et
al., 1988; Rosa and McAlpine, 1991; Rosa, 1994; Blanchflower and Oswald, 1998;
the Davies Report, 2002). Interestingly, however, Figure 2 also shows that younger
people are less likely to believe that there is enough media coverage of new
businesses.
1
The other sorts of qualifications were: 94,400 sub-degree qualifications, 11,800 PhD or equivalents
and 131,900 Masters/other postgraduate level.
5
Figure 2: UK GEM 2003: UK adults (18-64) Attitudes towards New Businesses
People Want Uniform Living Standards
Successful New Business Leads to Status
Starting New Business a Good Career Choice
Lots of Media Coverage of New Businesses
90
80
70
Percentage
60
50
40
30
20
10
0
18-24 YRS
25-34 YRS
35-44 YRS
45-54 YRS
55-64 YRS
Source: GEM 2003/Author’s own calculations
Finally, international survey evidence, this time from the Eurobarometer survey of EU
and US adults also suggests that a majority of young people in the UK have a
preference towards self-employment. Figure 3 shows also shows that the EU average
is also above 50% of young people, although this varies from just over 30% in
Finland to circa 80% in Portugal.
Figure 3: Young People's (15-24) Preferences for Self-Employment in the EU and US
(2002)
90
80
70
Percentages
60
50
40
30
20
10
Av
er
ag
e
Av
er
ag
e
EU
IT
AL
Y
PO
R
TU
G
AL
U
SA
SP
AI
N
IR
EL
AN
D
G
R
EE
C
E
BE
LG
IU
M
G
ER
U
M
N
AN
IT
ED
Y
KI
N
G
D
O
M
FR
AN
C
E
D
EN
M
A
R
K
SW
ED
EN
AU
S
TR
IA
FI
N
LA
N
N
ET
D
H
ER
LA
N
LU
D
S
X
EM
BO
U
R
G
0
Country
Source: Eurobarometer 2002/Author’s own calculations
6
These high preferences may be anticipated in such countries as Italy, Spain and
Portugal as these have traditionally had high rates of self-employment. It is also
perhaps unsurprising that the US, with a rate above 70%, is higher than the UK given
that its strength of its entrepreneurial culture. These countries aside, it would appear
that young people in the UK and Ireland are the most positive in the rest of the EU
about self-employment opportunities.
Such empirical findings suggest that latent entrepreneurship rates amongst young
people, at least for the UK, are high. Similar empirical evidence, however, indicates
that the actual up-take of self-employment by younger people is low. Greene (2002),
for example, indicated that Labour Force Survey (LFS) rates of self-employment for
males were lower in 2001 than they were in 1983. Similarly, female self-employment
rates had flattened rather than increased markedly over the 1990s. GEM data also
tells much the same storey with older people (35-55 year olds) being three times more
likely to own and run a business as younger people (18-24 year olds). Further
evidence is also evident from Barclays Bank data. Figure 4 shows the percentage
breakdown of start-ups, by age, between 1995 and 2003. It is evident from Figure 4
that youth entrepreneurship rates never break the 10% barrier. In other words, out of
approximately 463,000 new starts in 2003, some 31,000 of these were by young
people.
Figure 4: Percentage of Start-Ups by Age Groups (16-24, 24-44 and 45+), 19952003
16-24
25-44
45+
80
70
60
Percentage
50
40
30
20
10
0
1995
1996
1997
1998
1999
2000
2001
2002
2003
Source: Barclays Bank SME team, 2004
International evidence confirms that young people are less likely to be self-employed.
EU LFS data (Figure 5) indicates that across the EU the actual take-up of selfemployment is tiny when compared to older individuals. Further evidence, this time
from GEM (Figure 6) suggests that the TEA rate for young people in the UK is about
2% whilst it is much higher amongst major competitors such as Germany and the US.
7
Figure 5: Youth and All Self-Employment Rates by EU Population, 2002
20
18
16
14
Percentage
12
Young People
All People
10
8
6
4
2
EU
-1
5
Po
rtu
ga
l
y
re
ec
e
G
Ita
l
Sp
ai
n
N
et
he
rla
nd
s
U
K
Fi
nl
an
d
Ire
la
nd
Be
lg
iu
m
tri
a
D
en
m
ar
k
Sw
ed
en
Au
s
ce
G
er
m
rg
Fr
an
bo
u
Lu
xe
m
an
y
0
Source: EU LFS/Author’s own calculations
Figure 6: Total Entrepreneurial Activity of Young People (18-24), EU and US in 2002
0.12
Persons/100 adults
0.1
0.08
0.06
0.04
0.02
Av
er
ag
e
te
s
St
a
Ire
la
nd
U
ni
te
d
Ita
ly
er
m
an
y
en
G
Sw
ed
gd
om
Ki
n
U
ni
te
d
m
D
en
m
ar
k
Be
lg
iu
N
et
he
rla
nd
s
Fi
nl
an
d
Po
la
nd
ce
Fr
an
Sp
a
in
0
Source: GEM 2003/Author’s own calculations
What this section has established is that there are potentially good reasons for
supporting entrepreneurship by young people. Young people’s transactions into their
subsequent careers have become more protracted and complex and the outcomes of
this process are not necessarily in ways that they would see as advantageous. This
promotes inadequate social outcomes. The section has also shown, however, that
8
young people have an appetite for entrepreneurship. The take-up of this employment
route, as evident from the range of empirical evidence presented, is, however,
extremely modest.
Section Two: Empirical Evidence of Market Failures
Theoretically, the difference between expectation and reality may be due to the
presence of market failures. In terms of information asymmetries, Storey (2003)
suggests that there are three reasons why market failures arise:
•
•
•
Imperfection 1: the benefits to individuals of self-employment may be unknown to
them;
Imperfection 2: the benefits to small business owners of expert advice from
outside the firm may be unknown to them; and
Imperfection 3: financial institutions are unable to assess the risks and rewards of
lending to small firms.
There are obvious difficulties in providing information on the existence or otherwise
of such market failures. For instance, if you ask someone who is ignorant about their
potential for entrepreneurship, then it is likely that one indirect product of the question
is that the individual’s awareness of their entrepreneurial potential increases. There
is, however, international evidence that suggests market failures do exist. One such
proxy is apparent from Table 1. Table 1 shows for young people in the EU and US (it
is not possible to disaggregate this into particular countries as the sample sizes are too
small), that nearly two-thirds of young people are ignorant of the entrepreneurial
option. Table 1 also indicates, in line with the earlier evidence, that about a quarter of
them are thinking about such an option. This is higher than all other age groups but it
is also true that this group are the least likely to be running a business (started/taken
over a business).
Table 1: Propensities towards Entrepreneurship
Never came to his/her mind
Is thinking about it
Gave up
Currently taking steps to start
Started/taken over business
No longer an entrepreneur
(dk/n.a.)
Total
15-24
62.4
23.4
4.8
3.0
2.3
0.8
3.3
100.0
25-34
51.5
18.9
11.3
3.9
9.3
3.2
1.9
100.0
Age Range
35-44 45-54 55-64
50.2
54.4
60.6
11.1
8.9
4.0
11.2
9.5
8.0
3.5
1.6
0.6
15.4
14.8
13.0
6.2
7.7
10.9
2.3
3.1
3.0
100.0 100.0 100.0
65+
67.8
1.6
5.0
0.2
4.5
15.2
5.8
100.0
Total
57.2
11.2
8.6
2.2
10.3
7.3
3.2
100.0
Source: Eurobarometer 2002/Author’s own calculations
One obvious explanation for such levels of ignorance and the low rates of actual
entrepreneurship amongst young people is that they lack the necessary human capital
to be credible (Birley, 1985) in setting up and running a business. This lack of human
capital is often correlated with the likelihood that they have limited managerial
experience (Storey, 1994) and little access to fully developed networks (‘know how’
9
and ‘know who’ (Birley, 1985). Data from the European Social Survey suggests that
young people find it onerous to start up their own business. Figure 7 shows that the
mean average is 2.8 (where 1 is extremely difficult, 10 is extremely easy) although
this ranges from Greece (just under 2), to the UK (2.5) through to Finland (just over
4).
Figure 7: Young People's (14-24) Perceptions of the Difficulty in Starting a Business,
(1 = extremely difficult, 10 extremely easy)
4.50
4.00
Mean Percentage
3.50
3.00
2.50
2.00
1.50
1.00
0.50
Ita
et
ly
he
rla
nd
s
Fi
nl
an
Av d
er
ag
e
N
G
re
ec
e
G
er
m
an
Sw
y
itz
er
la
nd
Au
st
ria
Sp
Lu
ai
xe
n
m
U
bo
ni
te
ur
d
g
Ki
ng
do
m
Ire
la
n
Po d
rtu
ga
l
N
or
w
ay
D
en
m
ar
k
Be
lg
iu
m
Sw
ed
en
0.00
Source: ESS 2004/Author’s own calculations
Further specific evidence of the types of difficulties faced by young people is evident
from Figure 8. This suggests that whilst a majority of young people did not
strongly/agree that fear of failure was a particularly prevalent (ranging from under
30% in Finland, the US, Ireland and the UK to over 50% in Austria and Italy), very
many young people do seem to find the administrative procedures in their relevant
country irksome. Indeed, in all of the countries, more than 50% of young people
believe the administrative procedures to be problematic (mean average is 61%).
Young people find such regulatory burdens particularly difficult in countries such as
Italy, Spain and Portugal (all over 75%) but there are also tricky administrative
burdens in the US (69%) and the UK and Germany (both 62%). Accessing finance,
however, is the biggest of these three issues (mean average of 66%) for young people.
Again, this is a particular problem for young people in Mediterranean countries (e.g.
Portugal 91% and Greece 92%), but is also a significant issue for young people in the
UK, Ireland, Germany and the US (all in the 70-80% range). Finally, specific
evidence for some of the difficulties faced by younger people is provided in Figure 9.
10
Figure 8: Young Person's (15-24) Perceived Barriers to Entrepreneurship: Fear of
Failure, Administrative Procedures and Available Financial Support (Answer Rate:
Strongly Agree/Agree)
available financial support
administrative procedures
fear of failure
100
90
80
Percentage
70
60
50
40
30
20
10
IT
ED
N
U
SA
Av
er
ag
EU
e
Av
er
ag
e
ED
EN
KI
N
G
D
O
M
SP
AI
N
SW
U
LU
IT
AL
XE
Y
M
BO
N
ET
U
R
H
G
ER
LA
N
D
PO
S
R
TU
G
AL
AU
ST
R
IA
BE
LG
IU
M
D
EN
M
AR
K
FI
N
LA
N
D
FR
AN
C
G
E
ER
M
AN
Y
G
R
EE
C
E
IR
EL
AN
D
0
Source: Eurobarometer 2002/Author’s own calculations
Figure 9: UK GEM 2003: UK adults (18-64) Knowledge, Skills & Fears of Failure
Have Knowledge & Skills to do Start-up
Fear of Failure Prevents Start up Effort
70
60
Percentage
50
40
30
20
10
0
18-24 YRS
25-34 YRS
35-44 YRS
45-54 YRS
55-64 YRS
Source: GEM 2003/Author’s own calculations
This, again, uses GEM data for the UK. What Figure 9 shows is that fear of failure is
an issue that concerns all ranges of individuals. However, there are distinct
differences in terms of human capital attributes. Figure 9 suggests that young people
11
recognise that they have less knowledge and fewer skills to set up a business than all
the other age groups.
The evidence in this section, therefore, provides proxies to show that young people
believe that they suffer disproportionately from information imperfections. They are
perhaps a little more ignorant of the entrepreneurial option (imperfection 1), do not
seem to have the requisite networks of support to access expert advice (imperfection
2); and seem to find it extremely difficult to access appropriate finance (imperfection
3).
Section 3: The Value of Enterprise Support
The previous section identified strong prima facie evidence to suggest that the reason
why latent entrepreneurship amongst young people does not translate into actual
entrepreneurship is because of the presence of market failures. It would seem,
therefore, that there are also strong grounds for believing that the interventions
identified in the introduction where appropriate. The purpose of this section is to
review some of the major academic studies of issues related to youth enterprise.
Some of the studies focus on the factors that promote the self-employment choice,
some others look at perceptions of perceptions of entrepreneurship and small
businesses, whilst three, in particular, look at support schemes designed to support
youth enterprise.
Before this evidence is reviewed, it is appropriate to examine the context in which
evaluations of such programmes occur. This is important because enterprise support
programmes represent the mainstay of approaches to improve the entrepreneurial
capacity of young people. If they are shown not to work, then this sends a clear
policy signal that there is a need for fresh thinking in this area.
A Framework for Evaluation
The basic framework for evaluations in entrepreneurship and small business research
is provided by Storey (2003). He identifies that it is appropriate to consider first the
nature of the objectives (e.g. improve the entrepreneurial capacity of young people
accessing a programme) and then the likely ‘targets’ for such a programme (e.g.
support 1,000 new business start-ups by young people in a given year). Such a
process is not always easy (Greene and Storey, 2004) because resources are often
constrained in the support programme; there is an obvious tension between supporting
evaluations and the operation of the actual programme; and there may be divergent
goals amongst the evaluators and those being evaluated.
Such contingencies often have a bearing on the type of evaluation conducted. Storey
(2003) indicates that there are six basic types of evaluation. Step 1 evaluations simply
enumerate the features (e.g. participant numbers) of a programme. Hence, a
‘successful’ programme may see an increase in terms of its uptake of participants.
Such a measure is influenced by, inter alia, macro-economic conditions. Similar sorts
of issues are evident with Step 2 evaluations which seek to collect information on
recipients’ opinions of the programme. The problem with these ‘happy sheets’ is that
the contentment of recipients is not the same as the economic rationale for the
programme (e.g. increased numbers of start ups). Similar problems are also apparent
12
with Step 3 evaluations which ask recipients to estimate the likely contribution of the
programme. Entrepreneurs tend to be optimistic (de Meza, and Southey, 1996; de
Meza, 2002) and may, therefore, underestimate the likely contribution of the
programme or just simply guess at the contribution that a loan or advice made to the
nascent or actual business.
Three further steps, however, attempt to take account of the ‘additionality’ provided
by the programme. Step 4 compares the performance with assisted and typical firms.
The problem with this approach is what is ‘typical’. To take account of the divergent
nature of firms, Step 5 suggests ‘matching’ firms across a range of indicators (e.g.
age, sector, size) to control for evident biases. This brings the difficulty of sample
selection. Here it is apparent that some nascent and actual firms select into particular
programmes despite appearing to be matched on a range of objective factors. Step 6,
therefore, suggests using sample selection procedures to control for the reasons why
recipients my elect to participate in a particular programme.
Providing full economic appraisals of any schemes is costly and requires a range of
particular skills. Temporal issues also intrude. There are a variety of factors, besides
support, that influence venture creation such as age (Johansson, 2000), gender (Dolton
and Makepeace, 1990; Blanchflower and Meyer, 1994) and prior employment status
(Evans and Leighton, 1989). Enterprise support programmes targeted at young
people face a further barrier in that the gestation period for starting a business can be
as much as three years (Reynolds and Miller, 1992). Equally, entrepreneurial
awareness programmes (e.g. Davies Report, 2002) may only be influential over a
longer time period. This makes it difficult to isolate the specific contribution of such
programmes.
Studies of Youth Entrepreneurship
The first issue to realise is that there are very few studies of youth entrepreneurship.
In this section, two distinct tables are presented. In the first of these tables, Table 2,
seven studies are presented which look at various aspects of youth entrepreneurship.
These studies tend to show that there are a number of stable factors that promote selfemployment amongst younger people. For instance, in studies that provide analyses
of self-employment entry by young people (Blanchflower and Meyer, 1994; Williams,
2004) or graduates (Dolton and Makepeace, 1990) or survival (van Praag, 2003), it is
fairly clear that age, gender, prior experience, motivation and sector (e.g.
construction, agriculture, professional services) all tend to be positively related,
almost regardless of the techniques employed, to the self-employment entry and
success.
Table 2 also shows that Belfield (1999) finds that SMEs do not seem to be perceived
favourably by recent graduates or undergraduates. His univariate analysis suggests
that these two groups believe that SMEs offer poorer wages, fringe benefits and
training when compared to larger sized firms. Young undergraduates and graduates,
however, believe that SMEs offer greater advantages in terms of a more flexible and
dynamic work environment.
13
Table 2: Studies of Youth Enterprise
Dolton &
Makepeace, 1990
Blanchflower &
Meyer, 1994
Location
UK
Australia
& USA
Tackey, 1999
UK
Belfield, 1999
van Praag, 2003
UK
US
Williams, 2004
US
Focus
Graduates/Self-employment
decision
Young people/Selfemployment decision
Technique
Probit
analysis
Probit
analysis
Graduates/Self-employment
decision
Graduates’ views of SMEs
Young people/business
survival
Young people/selfemployment decision &
outcomes
Interviews
and survey
Survey
Regression
analysis
Probit
analysis
Results
Older (+), Children (+), Social Class (+), Male (+)
Australia: Male (+), Older (+), Apprenticeship (+), location (+)
sector (+), Parental Influence (+); US: Male (+), Older (+),
Skilled manual workers (+), years of Schooling (+), Sector (+)
Unemployment (-), independence (+), financial rewards (+),
family background (+), work experience (+)
Wages (-), fringe benefits (-), training (-), work environment (+)
Age (+), experience (+), motivation (+)
Self-employed characteristics: white (+), older (+), sector (+).
Outcomes: earnings (-), educational attainment (-)
14
Stable factors to explain the self-employment decision are also apparent in Table 3.
Where, however, Table 3 differs from Table 2, is that it looks at studies that have been
involved in the evaluation of enterprise support in this way. It classifies these
evaluations in terms of Storey’s steps. Hence, Step 1 studies (Greene and Storey,
2004; Shutt and Sutherland, 2003; and Rosa, 2003) look to account for the ‘impact’ of
particular programmes. Blackburn (1997) has been considered a Step 3 evaluation although it relies on a small unrepresentative sample of interviews - because it seeks
to assess the additionality of support. Meager et al (2003) is a Step 6 study because it
attempts to control for statistical bias by using a matched sample and sophisticated
sample selection techniques to isolate particular parameters.
The results of these studies are interesting. Some support is given for the efficacy of
support either in general (Blackburn, 1997) or for the Prince’s Trust (Shutt and
Sutherland, 2003). Hence, Shutt and Sutherland assert that “Receiving an expansion
loan from the Trust increases the probability that an individual continues to trade at
the time of the survey by 26%.” (p. 100). Such findings are not common. In the Rosa
study the suggestion is that in longitudinally tracing participants in the Graduate
Enterprise Programme of the 1980s, the self-employment survivors do not perform
terribly well: “…most [businesses] remained small, and a minority reverted back to
employment. The types of businesses started, moreover, were not imaginative ‘cutting
edge’ businesses either.” (p. 452). Businesses in this study were also found to be
largely similar to the type of degree programme that the individual followed.
Greene and Storey (2004) also set out, albeit without a control group, to assess the
efficacy of Shell Livewire in the UK. Their results suggest that mentoring has a
positive impact on the self-employment decision. However, by using ordered probit
analysis they are able to identify that satisfaction rates with Shell Livewire fall if the
recipients of such support are already in self-employed. Such pessimistic conclusions
are also evident in Williams (2004) (Table 2) who found future earnings were no
greater amongst self-employed young people. This may be somewhat surprising since
one rationale for being self-employed is that it boosts an individual’s labour market
experience which, ceteris paribus, should lead to higher future earnings.
Similar conclusions are also evident in Meager et al (2003). In terms of the likelihood
of survival, they identify the usual suspects (e.g. male, white, older individuals,
sector) but also suggest that individuals who are risk averse rather than risk loving are
more likely to survive. They also suggest that entrepreneurs serving local markets are
less likely to survive. Crucially, however, and in contradiction to Shutt and
Sutherland (2003), they find that Prince’s Trust support has either no impact on
survival and, indeed, businesses set up without such support were less likely to fail.
Meager et al (2003), though, do find that Prince’s Trust funding does have some
positive impact on earnings. However, in comparison to the control group, they
suggest that “it is striking that respondents from the participant sample had lower
levels of self-employment weekly earnings than their comparison sample counterparts
(p.81, emphasis in original). They also find that mentoring is negatively associated
with self-employment earnings which they suggest may be because poorer performing
businesses are in the greatest need of such support. Their impression, however, of the
additionality of the Prince’s Trust programme is stark:
15
Table 3: Evaluations of Youth Enterprise Support Programmes
Location
Focus
Technique
Blackburn, 1997
UK
Interviews
Shutt and
Sutherland, 2003
UK
Probit analysis
Step 1
Male (+), prior industry experience (+), unemployment (+),
previously self-employed (-), family help (+), Prince’s Trust
loan (+)
Meager et al,
2003
UK
Probit (sample
selection)
analysis
Step 6
Rosa, 2003
UK
Longitudinal
Surveys
Step 1
Survival characteristics: male (+), white (+), age (+), family
background (+) intermediate qualifications (+), risk averse
attitudes (+), sector (+), local markets (-), Prince’s Trust
support (-); earnings: Princes Trust funding (+), mentoring (-)
Degree course (+), earnings (-)
Greene & Storey,
2004
UK
Young Business
Owners
Prince’s
Trust/selfemployment
survival
Prince’s
Trust/selfemployment
outcomes
Graduates/
Graduate
Enterprise
Shell
Livewire/Selfemployment
decision
Evaluation
‘Step’
Step 3
Results
Ordered Probit
analysis
Step 1
Male (+), employed (+), education (+), support (+)
Self-employed characteristics: older (+), male (+).
Outcomes: mentoring (+), self-employment (-)
16
The evaluation does not, therefore, support those who would argue that selfemployment schemes for disadvantaged/unemployed beneficiaries have positive
impacts on participants’ subsequent ‘employability’, and that this can justify
such programmes (irrespective of their business survival rates, and indirect jobcreation impacts) (p. 83).
Conclusions
This discussion paper has achieved three things. First, it has pointed to international
evidence which suggests that there is a deep pool of latent entrepreneurial demand
amongst young people. It has also exposed that there are significant evidence which
suggests that market failures persist and, thereby, inhibit the awareness and take up of
entrepreneurship amongst this population. The third finding of this briefing is that it
has shown, firstly, that there are a number of relatively stable factors such as age,
gender, sector and ethnicity that explain the self-employment choice by young people.
Such results are interesting because it is not uniformly clear that greater levels of
education are correlated with the self-employment decision or with subsequent growth
(Rosa, 2003). These results also present a challenge to policy makers interested in
promoting entrepreneurship within a social inclusivity framework since there would
appear much more work to be done within specific target groups (women, younger
people, ethnic minorities) of an already ‘disadvantaged’ group.
A second implication of this briefing is that there are only a limited number of studies,
particularly within a quantitative framework, that look at youth enterprise decisions.
This obviously suggests further research in this area. However, what is clear from the
final part of this briefing is that there are a variety of ways by which such studies can
be conducted. Studies that rely on fairly low levels of evaluation tend to find positive
outcomes for programmes. However, if the intention is to economically appraise the
additionality of particular programmes the evidence, sparse though it is, suggests that
existing forms of support do not effectively support young entrepreneurs. This raises
obvious questions in terms of the likely direction of support to young people
interested in converting their obvious enthusiasm into setting up and developing their
own business.
17
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