Description
With this particular detailed outline resolve global entrepreneurship monitor special report alicia coduras a global perspective.
GLOBAL ENTREPRENEURSHIP MONITOR SPECIAL REPORT:
ALI CI A CODURAS MARTÍ NEZ, JONATHAN LEVI E, DONNA J. KELLEY,
RÖGNVALDUR J. SÆMUNDSSON AND THOMAS SCHØTT
A Global Perspective on Entrepreneurship Education and Training
Gl obal Ent r epr eneur shi p Moni t or
Speci al Repor t
A Global Perspective on Entrepreneurship
Education and Training
Alicia Coduras Martínez, Jonathan Levie,
Donna J. Kelley, Rögnvaldur J. Sæmundsson
and Thomas Schøtt
Acknowledgements
This Special GEM Report on Entrepreneurship Education and
Training is the outcome of nine months of collaboration between
the authors, all of whom are members of different national GEM
teams. It would not have been possible without the efforts of each
participating national team that gathered data on this special
topic in 2008, and the authors wish to thank these national
teams and their sponsors, all of whom are listed in the Appendix.
Thanks are also due to the core administrative GEM team,
including Marcia Cole at Babson College and Chris Aylett
at London Business School. GEM’s Research Director, Dr.
Niels Bosma, has provided constructive criticism and advice
throughout this period.
Dr. Thomas Schøtt would like to thank his collaborators in
GEM’s Social Network Group, Sung-sik Bahn (Republic of
Korea), Paulo Alberto Bastos Jr. (Brazil), Nezameddin Faghih
(Iran) and Olga Rastrigina (Latvia), and recognize their
contribution as co-authors of the part of the Report devoted to
this topic.
© 2010 by Alicia Coduras Martínez, Jonathan Levie, Donna J. Kelley,
Rögnvaldur J. Sæmundsson, Thomas Schøtt and the Global Entrepreneurship
Research Association (GERA).
2
Table of Contents
EXECUTIVE SUMMARY 5
THE GEM RESEARCH PROGRAM 7
GLOSSARY 8
1 INTRODUCTION 9
2 CURRENT ISSUES IN ENTREPRENEURSHIP EDUCATION AND TRAINING 11
2.1 The Nature of Entrepreneurship Education and Training 11
2.2 Entrepreneurship Education and Training and Economic Development 12
2.3 Does Entrepreneurship Education and Training Make a Difference? 14
3 THE STATE OF ENTREPRENEURSHIP EDUCATION AND TRAINING: EXPERT OPINIONS 16
3.1 The Level and Quality of Entrepreneurship Education and Training as Perceived by National Experts 16
3.2 Entrepreneurs’ Need for Assistance and the Adequacy of Training Provision Outside the
Formal Education System 18
4 PREVALENCE AND SOURCES OF TRAINING IN STARTING A BUSINESS 20
4.1 Prevalence Rates of Trained Individuals in the Working-Age Population 20
4.2 Sources of Training in Starting a Business 23
4.3 Demographics of Trained Individuals 27
5 THE RELATIONSHIP BETWEEN TRAINING IN STARTING A BUSINESS AND
ENTREPRENEURSHIP 30
5.1 Issues in Measuring the Effect of Training on Entrepreneurial Behavior 30
5.2 Training in Starting a Business and Involvement in Entrepreneurial Activity 30
5.3 Gain from Training: GEM’s Core Measure of the Effect of Training in Starting a Business 34
6 THE USE OF ADVISORS BY ENTREPRENEURS 39
6.1 Types of Advisors 39
6.2 Use of Advisors by Trained and Untrained Entrepreneurs 41
7 CONCLUSIONS AND IMPLICATIONS FOR POLICY, EDUCATORS AND PRACTICE 43
7.1 Conclusions 43
7.2 Implications for Policy, Educators and Practice 43
7.3 Suggestions for Further Research 44
APPENDIX 45
REFERENCES 51
GEM NATIONAL TEAMS 2008 54
ABOUT THE AUTHORS 60
GEM SPONSORS AND CONTACTS 61
SAMPLE CHARACTERISTICS 62
ENDNOTES 63
3
Table of Contents
LIST OF TABLES
Table 1 GEM Countries Participating in the 2008 Education and Training Special Topic Focus, Grouped by Level of Economic
Development 13
Table 2 Prevalence of Formal Training, by Country and Economic Group, Ordered by Prevalence of School Training 25
Table 3 Prevalence of Informal Start-Up Training, by Country and Economic Group 26
Table 4 Prevalence of Training in Starting a Business in the Total Working-Age and Among Early-Stage Entrepreneurial Population 32
Table 5 Gain from Training in Early-Stage Entrepreneurial Activity (TEA) for 37 Countries, by Country and Economic Group,
Ordered by Increasing Gain in TEA Rate from Training 35
Table 6 Percentage of Advisor Type Networks That Include a Particular Advisor Type 40
Table 7 Summary Statistics on Advisor Types Used by Entrepreneurs in Iran, Brazil, Latvia, Republic of Korea and Denmark 41
Table 8 Average Number of Advisor Types per Sphere of In?uence Identi?ed by Trained and Untrained Entrepreneurs,
by Country 41
Table 9 Average Number of Advisor Types Identi?ed by Trained and Untrained Entrepreneurs, by Country 42
Table 10 Average Ratings by National Experts on the State of In-School and Non-School Entrepreneurship Education
and Training in a Sample of GEM Nations, 2005–2008 45
Table 11 Prevalence of Start-Up Training (In-School and Non-School), by Country and Economic Group (Percentage of
Working-Age Population) 46
Table 12 Prevalence of Start-Up Training (Formal and Informal), by Country and Economic Group (Percentage of
Working-Age Population) 47
Table 13 Gain from Training in Entrepreneurial Awareness, Attitudes, Intention and Activity for 38 Countries, by Country and
Economic Group, Ordered by Increasing Gain from Training in Activity 48
Table 14 Gain from Training in Entrepreneurial Awareness, Attitudes, Intention and Activity for 31 Countries, by Country
and Global Region, Ordered by Increasing Gain from Training in Activity 49
Table 15 Linear Multiple Regression Showing Effect of Compulsory Training Versus No Training in Starting a Business on the
Variety of Entrepreneurs’ Advisor Types, Controlling for Education Level, Gender, Age, Stage of Business and Country 50
LIST OF FIGURES
Figure 1 The GEM Theoretical Model 14
Figure 2 Average Ratings by National Experts on the Level of Entrepreneurial Framework Conditions in Their Countries,
by Economic Group 17
Figure 3 Average Ratings by National Experts on the State of In-School Entrepreneurship Education and Training in a Sample
of GEM Nations for the Years 2005–2008 17
Figure 4 Average Ratings by National Expert on the State of Non-School Entrepreneurship Education and Training in a Sample
of GEM Nations for the Years 2005–2008 18
Figure 5 Experts’ Average Evaluations in 30 GEM Countries Regarding Entrepreneurs’ Need for External Assistance with
Planning Prior to Start-Up and the Suf?ciency of Entrepreneurship Education and Training Provided by Public
and/or Private Agencies, by Country 19
Figure 6 Average Level of Training in Starting a Business in the Adult Working-Age Population (18–64 Years) Across
All 38 Participating Countries 20
Figure 7 Percentage of the Adult Working-Age Population (18–64 Years) That Received Training in Starting a Business,
by Country, Ordered by Increasing Prevalence 21
Figure 8 Percentage of the Adult Working-Age Population (18–64 Years) That Received Start-Up Training, by Country
and Economic Group, Ordered by GDP 21
Figure 9 Levels of Voluntary and Compulsory Start-Up Training, by Country and Economic Group, Ordered by Level
of Voluntary Training 22
Figure 10 Prevalence of In-School and Non-School Training, by Economic Group, Ordered by Frequency of In-School Only Training 24
Figure 11 Prevalence of Formal and Informal Start-Up Training, by Country and Economic Group, Ordered by Frequency
of Formal Only Training 24
Figure 12 Age Distribution of Trained and Untrained Individuals, by Economic Group 27
Figure 13 Gender Distribution of Trained and Untrained Individuals, by Economic Group 28
Figure 14 Education Distribution of Trained and Untrained Individuals, by Economic Group 29
4
Figure 15 Income Distribution of Trained and Untrained Individuals, by Economic Group 29
Figure 16 Proportion of Trained vs. Untrained Individuals Involved in Early-Stage Entrepreneurial Activity (TEA), and
Those Not Involved (Non-TEA) 31
Figure 17 Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population
Within the Factor-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals 33
Figure 18 Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population Within the
Ef?ciency-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals 33
Figure 19 Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population Within the
Innovation-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals 33
Figure 20 Gain from Training in Entrepreneurial Awareness, Attitudes, Intention and Activity for 38 Countries, by Economic Group 35
Figure 21 Proportion of Countries in Which the Gain from Training Is Statistically Signi?cant, by Economic Group and Type of
Entrepreneurial Orientation 36
Figure 22 Gain from Training in Entrepreneurial Awareness, Attitudes, Intention and Activity for 32 Countries, by Global Region 37
Figure 23 Proportion of Countries in Which the Gain from Training is Statistically Signi?cant, by Global Region and
Type of Entrepreneurial Orientation 38
Table of Contents
5
Executive Summary
In 2008 the Global Entrepreneurship Monitor set
out to investigate the prevalence and sources of
entrepreneurship education and training, and the
effect of this training on starting a business. Thirty-
eight national teams participated in this study, adding
specialized questions to the standard GEM Adult
Populations Surveys (APS). In addition, 30 countries
added questions to the National Expert Surveys
(NES).
This report expands on the eight-page education and
training section found on pages 41-48 of the Global
Entrepreneurship Monitor 2008 Executive Report.
After a brief literature review, we present expert
opinions on the current state of entrepreneurship
education and training in 30 countries. The report
then details the level and sources of training received
by the adult population (18-64) in the 38 countries
surveyed by GEM. By examining data from the
APS, GEM is able to develop profiles of individuals
most and least likely to have received training.
Additionally, we present new information on the
effects of training on an individual’s entrepreneurial
awareness, attitudes, intentions and activity in each of
the participating countries. Then, five GEM countries
provide insights about the types of advisors used by
entrepreneurs. The report concludes with possible
implications of these new findings and suggests areas
for further research.
To facilitate analysis, participating nations are
classified into three groups with similar levels of
economic development, from the lowest level “factor-
driven” group, to the middle level “efficiency-driven”
group, and then to the highest level “innovation-
driven” group. The 38 participating countries are
not a random sample of countries in these groups, so
readers should interpret the results with this in mind.
In Chapter 2, a review of the literature reveals that
entrepreneurship education and training has grown
rapidly in recent decades. However, little comparative
data exists on how many people receive training
in business start-up activity, whether some people
are more likely to receive training than others and
whether the training makes any difference in their
subsequent entrepreneurial behavior.
Chapter 3 shows that since 2000, GEM National
Expert Surveys have gathered data that consistently
demonstrates experts’ dissatisfaction with aspects
of entrepreneurship education and training in
their countries. They tend to rate the adequacy
of entrepreneurship education and training in
primary and secondary schools lower than any
other entrepreneurship framework condition. In
most participating countries in 2008, experts agreed
that entrepreneurs needed external assistance
with starting businesses. Satisfaction with external
assistance tended to vary by level of economic
development. In Germany, Finland, Republic of
Korea, Ireland, Spain and the United States, experts
tended to agree that public and/or private agencies
outside the formal education system provide adequate
entrepreneurship education and training. Experts in
other participating GEM countries were less positive.
Chapter 4 shows the proportion of working-age
individuals who have received training in starting a
business in 38 countries. More than one-fifth of the
working-age population (21%) across these countries
has received training in starting a business. Country-
level prevalence rates vary considerably, even between
countries with similar levels of economic development.
Most countries show a level between 10% and 30%.
For most countries, though not all, more than half
of the trained population engaged in this training
voluntarily, rather than being required to do so. A
large majority of those who received start-up training
did so as a part of their formal education in school,
college or university. On average, around 80% of
those who have received training have done so during
their formal education. This high proportion of
formal training reveals the important role the formal
education system plays in entrepreneurship training.
In most countries, training at school is more prevalent
than training at the tertiary level.
Slightly more than 60% of those who have received
training, on average, have received informal training,
either exclusively or in addition to formal training.
This high level of informal training suggests that,
despite having obtained formal entrepreneurship
education or training, people may also want focused
“not for credit, but for real” training. The most
frequent source of informal training in most of the
countries is self-study, followed by informal university
programs and courses offered by business associations.
The final section of Chapter 4 demonstrates
demographic differences between trained and
untrained individuals. Start-up training rates vary
according to an individual’s age, gender, education
and income. In all three economic groups, younger
individuals are more likely to have received training
in starting a business. This probably reflects the
recent rise in entrepreneurship training offered in
the formal education system. People from wealthier
households and better-educated people are also more
likely to have received training. Such individuals
may have more opportunities to avail of training.
In most countries, men are more likely than women
to have volunteered for training. In less well-
developed countries, women tend to have had fewer
opportunities for compulsory training than men.
6
Executive Summary
Chapter 5 analyzes the impact of training on an
individual’s propensity for entrepreneurial attitudes
or behavior. GEM data are ideally suited to address
methodological issues that previous studies have
found difficult to overcome, including self-selection
into training, time delay in demonstrable effects,
lack of control groups and the role of an individual’s
background and context. By comparing those who
had only compulsory training to those who had
no training, and controlling for an individual’s
demographic background and country-specific
conditions, a “gain from training” was demonstrated
using multivariate statistical analysis. This gain from
training varies by context. Training is most effective
in contexts with favorable institutional environments,
where the training-induced positive skills, perceptions
and intentions can be translated into action. Training
appears to be particularly effective in western
European countries with low rates of early-stage
entrepreneurial activity, such as Belgium, France,
Germany and the United Kingdom, where significant
gains equal to a doubling of the odds of engaging in
early-stage entrepreneurial activity were recorded
among trained individuals.
Chapter 6 presents a study of the links between
training and the use of advisors in five GEM countries
with highly different country contexts. While in four
of these countries (Brazil, Latvia, Republic of Korea
and Denmark) trained individuals tended to have
more advisors, this was not true in Iran. The type
of advisor chosen (from five spheres of influence:
private, job, experience, professional and market) also
varied. Advisors who were family and friends were
more common advisors in Brazil and Iran. Advisors
from other spheres were more prominent in Republic
of Korea and Denmark. Latvia took an intermediate
position.
Chapter 7 makes several conclusions: The amount and
type of training varies widely across countries, and
this is not necessarily linked to a country’s state of
economic development. However, the impact of such
training does vary according to the level of economic
development. It appears to have greatest effect on
early-stage entrepreneurial activity in countries
with favorable institutional contexts. This finding
fits the GEM model, which predicts that training in
starting a business is most effective and relevant in
innovation-driven countries. It supports the argument
that factor-driven countries in particular should not
invest large-scale resources in training programs
if basic framework conditions are not adequate. An
alternative explanation for the findings is that the
quality of training may vary by country context, and
that less-developed economies have lower quality
forms of training. There is some support for this
view from the collective opinions of experts in these
countries. It is likely that both explanations are valid,
but further research needs to be done on how forms of
training vary by country and which forms of training
are most effective.
7
The GEM Research Program
Since its first comparative national surveys in 1999,
the Global Entrepreneurship Monitor (GEM) research
consortium has contributed toward building and
enhancing global understanding about the attitudes,
activity and aspirations of entrepreneurs and
environmental factors that help them flourish. By
improving knowledge about entrepreneurship, GEM
helps governments, businesses and educators around
the world design policies, develop programs and
provide assistance to help enterprising individuals
generate new jobs and wealth in an increasingly
global business environment.
The GEM project focuses on three main objectives:
• To measure the scale and scope of entrepreneurial
activity and analyze how this differs across
countries
• To uncover factors determining national levels of
entrepreneurial activity
• To identify policies that may enhance the national
level of entrepreneurial activity
The Global Entrepreneurship Monitor was conceived
in 1997 by Michael Hay of London Business School
(LBS) and Bill Bygrave of Babson College. LBS and
Babson funded a prototype study that year. Ten
national teams conducted the first GEM Global
study in 1999 with Paul Reynolds as the Principal
Investigator. Since then, more than 64 national teams
have participated in GEM through a consortium
headed by the Global Entrepreneurship Research
Association (GERA), which is a not-for-profit
organization governed by representatives of the
national teams, the two founding institutions and
sponsoring institutions. Led by a central coordination
team, this consortium administers an annual Adult
Population Survey (APS) of at least 2,000 individuals
aged between 18 and 64 in each participating country.
In addition, GEM national teams conduct National
Expert Surveys (NES) to obtain insights about
particular factors impacting entrepreneurship in each
country.
GEM aims to be the leading source of information and
analysis about entrepreneurship across the globe. The
study employs an original methodology that has been
continually refined over ten years. Data collection
follows strict quality control procedures. This
strong methodology, among other distinct features,
contributes to the project’s uniqueness and value for
those seeking to benchmark and make comparisons
about entrepreneurship among nations.
Each economy participating in the GEM project
has a national academic team, which selects a
local survey vendor to conduct the APS and then
monitors the process for quality control. The GEM
central coordination team and its specialized staff
ensure that each team follows strict GEM research
standards. This ensures data quality and allows for
the harmonization of data across all participating
countries. All teams and vendors therefore adopt the
same methodology.
Quality control is similar in the NES and includes
an oversight role by the central coordination team.
National teams conduct this survey in accordance
with the specific procedures and policies established
by the GEM consortium. The NES process includes
the selection of at least 36 experts, covering nine
framework conditions that influence a nation’s
entrepreneurial environment: financial support,
government policies and programs, education and
training, R&D transfer, access to commercial and
professional infrastructure, internal market dynamics,
access to physical infrastructure and social and
cultural norms. Interviews are conducted with at least
four experts in each of the nine areas.
GEM publishes annual global reports and GEM
national teams publish individual country-level
reports. In addition, GEM publishes special reports
on topics including women in entrepreneurship,
high-growth ventures and entrepreneurial finance.
This special report on entrepreneurship education
and training draws on additional questions
developed around this topic for the GEM 2008 APS
questionnaire. These questions were approved by the
GERA annual assembly and reviewed by the central
coordination team.
8
Entrepreneurship education is the building of knowledge and skills either “about” or “for the purpose of”
entrepreneurship generally, as part of recognized education programs at primary, secondary or tertiary-level
educational institutions.
Entrepreneurship training is the building of knowledge and skills in preparation for starting a business.
In-school training specifically refers to training conducted within primary and secondary education programs
in any nation.
Non-school training comprises any courses offered outside primary and secondary education programs,
provided by any type of institution: universities, business schools, public institutions, chambers of commerce,
trade unions, employers or any other entity.
Compulsory training is defined as programs either in school or after school that an individual has taken but
did not freely elect to take; it is training required to complete or graduate from a particular program or to obtain
some other benefit, such as a grant or official business registration.
Voluntary training is training undertaken by choice.
Formal training includes any course that is part of an official education program, whether compulsory or
voluntary. This includes primary or secondary education and tertiary-level certificate, diploma or degree
programs.
Informal training operates outside formal programs, for example, non-credit bearing courses at a university,
local business organization or a government agency.
Gain from training is the increased odds of engaging in entrepreneurial behavior due to training, rather than
a consequence of some prior desire to behave entrepreneurially.
In the 2008 GEM Executive Report, GEM countries were classified into three different phases of economic
development, following the framework employed by the Global Competitiveness Report (Porter and Schwab,
2008; Porter, Sachs and McArthur, 2002):
Factor-driven countries tend to have economies that are primarily extractive in nature, and their
governments should focus on basic requirements such as primary education and basic governance.
Efficiency-driven countries are—or should devote more attention to—driving down labor costs as basic
requirements are met.
Innovation-driven countries are wealthier economies that are becoming less price-competitive and need to
focus on providing the conditions that allow opportunity-based entrepreneurship and innovation to flourish.
APS is the GEM Adult Population Survey: a random sample of the working-age population in a country.
NES is the GEM National Expert Survey: a selected sample of individuals who are deemed expert in at least
one Entrepreneurial Framework Condition (EFC) or aspect of the environment for entrepreneurship. GEM
recognizes nine major EFCs, of which three, including entrepreneurship education and training, have two major
components. Typically, in each country’s NES, at least four experts are identified per EFC, of which one is an
entrepreneur, two are providers of that EFC and one is an expert observer.
Glossary
9
In the closing decades of the 20th century,
entrepreneurship gained increased recognition
among economists as a significant driver of
improvements in societal welfare. Across the globe,
governments have acknowledged the importance
of their roles in motivating individuals, businesses
and related stakeholders to perceive and develop
new opportunities that can promote positive
change and create economic growth in their
societies (Blenker, Dreisler and Kjeldsen, 2008).
This entrepreneurial spirit is now seen as the
main source of innovations in nearly all industries,
leading to the birth of new enterprises and the
growth and renewal of established organizations.
The impact of entrepreneurship education and
training on individual attitudes, actions and
ambitions is of particular interest to policy makers,
educators and practitioners. It is generally believed
that individuals who perceive they have the skills
and knowledge to start a business are more likely to
do so. However, as the next chapter demonstrates,
GEM expert surveys in most countries suggest
that entrepreneurship education and training,
both in school and outside of school, is inadequate.
Recognizing this concern among hundreds of
experts across the globe, the GEM consortium
chose education and training as its special topic for
2008. Of the 43 countries participating in the 2008
survey, 38 added questions about entrepreneurship
education and training to their Adult Population
Surveys and 30 countries added questions to their
National Expert Surveys. This report expands on
the initial findings from these surveys reported
in the GEM 2008 Executive Report (Bosma et al.,
2008).
The importance of entrepreneurship education and
training was stressed in a recent (2009) report by
the Global Education Initiative (GEI) of the World
Economic Forum (WEF):
“…while education is one of the most important
foundations for economic development,
entrepreneurship is a major driver of innovation
and economic growth. Entrepreneurship education
plays an essential role in shaping attitudes, skills
and culture–from the primary level up. ...We believe
entrepreneurial skills, attitudes and behaviors can
be learned, and that exposure to entrepreneurship
education throughout an individual’s lifelong
learning path, starting from youth and continuing
through adulthood into higher education–as well
as reaching out to those economically or socially
excluded–is imperative.” (p.7–8)
Many studies have addressed the supply side
of entrepreneurship education and training, for
example: teacher and student evaluations of
program effectiveness (Hegarty, 2006; Cheung,
2008), national and regional reviews of the
availability and nature of programs (Levie, 1999;
Autio, 2007) and assessments of the value of
entrepreneurship education in general (Shinnar,
Pruett and Toney, 2008). The WEF report
(WEF, 2009) cited above describes a range of
entrepreneurship programs across the world—
including government, NGO and multinational
initiatives—and at a range of education levels
from primary schools to universities, as well as
non-school initiatives. While these studies provide
useful information on what education and training
is offered, they do not tell us who takes this
training and what trained individuals gain from
their training.
GEM is in a unique position to provide information
on the frequency and impact of entrepreneurship
education and training among different countries.
GEM polls individuals, rather than firms, so it
is well placed for exploring entrepreneurship
education and training among people. Because
GEM does not rely on business registrations, it
can reveal insights about individuals that have
engaged in both formal (registered) and informal
(unregistered) entrepreneurial activity. GEM can
also capture the impact of training in starting a
business on entrepreneurial awareness, attitudes,
intentions and activity.
In addition, while many studies have been
conducted in one or a few countries, this report
analyzes APS data on training in starting a
business from 38 countries spanning a range
of economic development levels. The data is
harmonized to allow for comparisons among these
countries. This is supplemented by NES data
from 31 countries on the insights and opinions
of entrepreneurs, policy makers, debt and equity
providers and other experts on the state of
entrepreneurship education and training in their
countries.
The 2008 APS survey asked respondents if they had
ever taken part in training in starting a business
in school (in-school training) or outside of school
(non-school training). For non-school training,
survey interviewers asked respondents to identify
the main provider of the program. They also asked
respondents whether their training was voluntarily
or compulsory (for example, a required part of a
school or government program). This distinction
enables us to identify outcomes that could not be
due to self-selection. In other words, it permits us to
measure more accurately the “gain from training,”
or increased odds of engaging in entrepreneurial
behavior that is due to the training itself rather
than a consequence of some prior desire to behave
entrepreneurially.
1 Introduction
10
Introduction
Readers should be aware of several data limitations,
which include the following:
• The surveyed population spans a broad age range,
from 18 to 64 years. The age distribution of those
receiving training in a country may be a function
of the nation’s age profile and should be considered
when making comparisons between countries.
• Cultural factors and economic development level,
as well as specific government policies, can affect
the nature and impact of education and training
generally.
• The sources of training for each respondent are not
a guide to the type or the quality of training received
by individual respondents.
• The countries in the database are not necessarily
representative of the economic groups from which
they are drawn. Thus, while this is perhaps the
largest global study of both the prevalence, sources
and effect of training in starting a business and
the expert views of the state of entrepreneurship
education and training in their countries to date,
there is much more work to do.
In summary, the goals for this report are the
following:
(1) demonstrate national differences in perception by
experts of the current quality and availability of
entrepreneurship education and training in their
countries;
(2) demonstrate differences in the prevalence and
nature of entrepreneurs and non-entrepreneurs
who have received training in starting a business
across countries;
(3) demonstrate the impact of training on
entrepreneurial awareness, attitudes, intentions
and activity; and
(4) identify implications for policy makers, educators
and practitioners.
The next chapter provides an overview of
entrepreneurship education and training literature
drawn from the current literature on the subject.
11
2 Current Issues in Entrepreneurship Education and Training
2.1 THE NATURE OF
ENTREPRENEURSHIP EDUCATION
AND TRAINING
Individuals may participate in entrepreneurship
education and training at various points in their lives,
and this education and training may take different
forms. For example, all primary school pupils in
Scotland receive “enterprise education,” which is not
specifically about training in starting a business, but
about being enterprising and entrepreneurial in a
more general sense. In some universities, students
may receive education “about” entrepreneurship.
This education is not designed to provide training in
starting a business. Instead, new venture creation is
the context of an academic education, not the goal.
Some university students experience a mix of “about”
and “how-to” in entrepreneurship classes. At the other
end of the spectrum, an employer or a government
agency may offer training in starting a business to
employees about to lose their jobs.
In this report, entrepreneurship education is defined
in broad terms as the building of knowledge and
skills “about” or “for the purpose of” entrepreneurship
generally, as part of recognized education programs
at primary, secondary or tertiary-level educational
institutions. Entrepreneurship training is defined as
the building of knowledge and skills in preparation
for starting a business. Thus, the purpose of
entrepreneurship training is very specific, unlike the
purpose of entrepreneurship education, which can be
much broader.
Complicating the picture further, individuals may
receive education about/for entrepreneurship and/
or training in starting businesses in primary and
secondary school, during college or university studies.
These courses may be part of a formal education
program that grants certificates or degrees, or they
may involve non-credit courses. Other informal
training programs operating outside the mainstream
education system include courses, seminars or
other types of training offered by local business
organizations, employers or a government agency.
Some argue that the earlier people are exposed to
entrepreneurship, the more likely they will become
entrepreneurs in some form during their lives
(WEF, 2009). Evidence of this can be seen in the
higher prevalence of entrepreneurial activity among
individuals whose parents have been self-employed or
running their own businesses (Henley, 2007). It could
be surmised that children of entrepreneurs develop
particular perceptions and skills from observing their
parents and participating in family business activities.
Perhaps some education and training programs can
substitute for this learning.
This raises issues about which types of
entrepreneurship education and training approaches
work best. It may depend on the educational context,
for example: whether one is learning in primary or
secondary (grade) school, colleges or universities
or non-school training programs. Most authors
agree, however, that experiential learning, or
“learning by doing,” is more effective for developing
entrepreneurial skills and attitudes than traditional
methods like lectures (European Commission, 2008;
Walter and Dohse, 2009). Several studies carried out
in innovation-driven countries, including Singapore
(Tan and Ng, 2006), Sweden (Rasmussen and
Sørheim, 2005), and the United Kingdom (Raffo et
al., 2002) show that entrepreneurs learn best with an
experiential learning approach.
Another consideration is about what to teach. A
survey of entrepreneurs by Sexton (1997) revealed
the ten most desired topics for achieving and
managing fast growth. These were primarily business
concerns, such as selling, financing growth, managing
cash flow and hiring and training employees. Yet
entrepreneurship education and training may need to
be much broader. It can impact attitudes, help people
recognize opportunities and think creatively, and
enable them to build leadership skills and confidence
(Stevenson and Gumpert, 1985). Recognizing this,
a recent European Commission Report (2008)
suggested that the goal of entrepreneurship education
should be to promote creativity, innovation and
self-employment. Entrepreneurship education and
training therefore entails more than the development
of particular business skills. It can influence an
individual’s motivation to strive for something that
might otherwise seem impossible or too risky. In
short, it can create positive perceptions and desire
among individuals to start businesses.
A further issue is where to teach entrepreneurship.
Entrepreneurship is inherently multidisciplinary
in nature. While entrepreneurship education and
training requires the teaching of numerous business
skills, non-business students may benefit from this
training. The European Commission (2008) questions
whether business schools are the most appropriate
place to teach entrepreneurship, given its view that
the most innovative and feasible ideas are likely to
come from the technical and creative disciplines.
Similarly, Katz (2003) declared that growth in
entrepreneurship education and training is likely to
come from outside business schools.
The requirements of educating “for” entrepreneurship
call into question the usefulness of traditional
education practices, implying a need for a mindset
shift from mainstream education and training
routines (WEF, 2009). New teaching pedagogies and
cross-disciplinary content present challenges for
educators and institutions. Sorgman and Parkison
(2008) state that many schoolteachers are unprepared
12
Current Issues in Entrepreneurship Education and Training
for these new challenges. As the WEF Global
Education Initiative report (WEF, 2009) indicates,
changing existing school systems will take time.
Multidisciplinary business content and experiential
approaches will need to be integrated into the basic
training that teachers receive. They conclude that
“training the trainers” may be as great an effort as
developing the curriculum.
On the supply side, university PhD programs are
not providing enough faculty to meet the demand for
entrepreneurship education (Katz, 2003; EC, 2008).
Many tertiary institutions, where their statutes
permit, rely on “adjunct faculty,” business people who
teach entrepreneurship part-time. Current faculty,
locked into narrow disciplinary structures, may not
adapt well to the requirements of entrepreneurship
education (Janssen, Eeckhout and Gailly, 2005).
Additionally, internal funding systems in multi-
faculty institutions may hinder the availability of
entrepreneurship education beyond business schools.
Consequently, the development of effective programs
for entrepreneurship likely requires more than
adding new courses. Institutional-level considerations
may therefore play a key role in the development of
entrepreneurship education in an economy.
Educators and policy makers may need to consider
how to broaden access and increase the scale and
scope of entrepreneurship training, beyond university
locations and other on-site programs. This may
require greater use of technology. Internet-based
learning, for example, may extend a program’s
geographic reach or satisfy high demand (Solomon,
Duffy and Tarabishy, 2002; Hegarty, 2006).
Creative computer applications may attract and
hold the interest of some people, influencing their
attitudes toward—and their understanding of—
entrepreneurship.
While the requirements and challenges of
entrepreneurship education and training are
numerous, there are also many opportunities for
influencing perceptions and developing the skills and
ambitions of current and potential entrepreneurs.
This report addresses fundamental questions about
the differences in entrepreneurship training among
different economies around the world, and it estimates
the impact of training in starting a business on
entrepreneurial awareness, attitudes, intentions
and activity. The remainder of this chapter provides
background on three main economic groupings of
countries and reviews current understanding about
the impact of entrepreneurship training.
2.2 ENTREPRENEURSHIP EDUCATION
AND TRAINING AND ECONOMIC
DEVELOPMENT
In GEM research, countries are classified into three
groups based on their levels of economic development.
The GEM theoretical model shows three sets of
economic framework conditions: those that constitute
the basic requirements for economic activity, those
that enhance efficiency, and those that promote
entrepreneurship and innovation. As countries
progress economically, there is a shift in the relative
importance of these three sets of economic framework
conditions. This method of classifying economies has
been used in the Global Competitiveness Reports for
some time (Porter, Sachs and McArthur, 2002; Porter
and Schwab, 2008).
In “factor-driven” countries with mainly extractive
type economic activity, Porter and Schwab argue that
the focus of government should be on enhancing the
basic requirements of economic development, such as
stable government, basic infrastructure and primary
health care and education. With the exception of well-
managed countries that are especially well endowed
with natural resources, such as Saudi Arabia, most
entrepreneurial activity in factor-driven countries
may be necessity-driven, and government attention
is best focused on providing a basic foundation for
enabling this activity, rather than, for example,
providing sophisticated training in opportunity-driven
entrepreneurship.
As an economy develops, and as the employment
of relatively cheap labor becomes an increasingly
less viable source of advantage, necessity-driven
entrepreneurship declines and governments may start
to pay more attention to entrepreneurship. The most
developed nations, no longer able to depend on low
labor costs, must instead compete in ways that are
more creative. For the governments of such countries,
high quality basic factors and efficiency enhancers
are generally present at sufficient levels. The quality
and quantity of entrepreneurship and innovation then
becomes a source of national competitive advantage.
One of the primary entrepreneurial framework
conditions recognized by GEM is the nature and
level of entrepreneurship education and training.
According to the GEM model, the relative importance
of entrepreneurship education and training increases
as economies develop economically.
Table 1 shows the 38 countries participating in the
education and training special topic grouped into
factor-driven, efficiency-driven and innovation-
driven economies. Although the sample of countries
crosses many geographic regions and levels of
economic development, it is not necessarily evenly
13
representative of the world. The factor-driven
countries in the sample represent only 10% of the
factor-driven countries in the world, and half of them
were classified by the 2008 Global Competitiveness
Report as in transition to the efficiency-driven group.
The sample contains 40% of the world’s efficiency-
driven economies and 45% of the innovation-driven
economies. The United States, Canada, Australia
and New Zealand were absent from the sample of
innovation-driven countries.
The GEM Model, shown in Figure 1, illustrates
three sets of framework conditions that influence
entrepreneurship, which in turn impact
national economic growth. These three sets are
basic requirements, efficiency enhancers and
entrepreneurship and innovation. As the GEM Model
shows, entrepreneurial education and training is
represented as a specific entrepreneurial framework
condition affecting entrepreneurial attitudes,
activity and aspirations—and, as a result, economic
development.
Much has been written about entrepreneurship
education and training in innovation-driven
economies, starting primarily in the 1980s and
accelerating after the turn of the century as interest
in entrepreneurship increased and the contribution of
new businesses to the growth of a national economy
gained recognition. Entrepreneurship education,
in fact, has its roots in what are now classified as
innovation-driven countries; the first efforts to deliver
entrepreneurship courses were attributed to Shigeru
Fujii of Kobe University in Japan in 1938 (Solomon et
al., 2002) and Myles Mace at Harvard Business School
in 1947 (Katz, 2003).
Current Issues in Entrepreneurship Education and Training
Table 1—GEM Countries Participating in the 2008 Education and Training Special Topic Focus,
Grouped by Level of Economic Development
FACTOR-DRIVEN EFFICIENCY-DRIVEN INNOVATION-DRIVEN
Bolivia Argentina Belgium
Bosnia and Herzegovina (+) Brazil Denmark
Colombia (+) Chile Finland
Ecuador (+) Croatia (+) France
Egypt Dominican Republic Germany
India Hungary (+) Greece
Iran Iceland
Jamaica Ireland
Latvia Israel
Macedonia Italy
Mexico Japan
Peru Republic of Korea
Romania Slovenia
Serbia Spain
South Africa United Kingdom
Turkey
Uruguay
Note: The (+) indicates economies in transition to the next level of economic development.
In the innovation-driven countries, it was commonly
thought that entrepreneurship could not be taught.
Many still believe that education and training are
not necessary for starting buisnesses. People like
Bill Gates and Steve Jobs, both dropping out after
a few years of college, made for interesting news
stories. It became apparent, however, that these did
not represent typical entrepreneurs, particularly
for businesses with knowledge-based products and
services. Many governments in innovation-driven
economies have since declared their commitment to
entrepreneurship education, identifying it as a key
priority (Kyro, 2006; Sorgman and Parkison, 2008).
In these wealthier economies, entrepreneurship
education is considered relatively established, and
attention has turned toward assessing existing
programs, sharing best practices, identifying
constraints and providing recommendations. There
have been numerous studies evaluating training,
school and university education programs in countries
such as the United Kingdom (Birley and Gibb,
1984; Gibb, 1987; Jones-Evans et al., 2000), Sweden
(Klofsten, 2000), German-speaking countries (Klandt,
2004), Australia (Jones and English, 2004) and Oman
(Khan and Almoharby, 2007)—to name a few.
14
Current Issues in Entrepreneurship Education and Training
Figure 1—The GEM Theoretical Model
Source: 2009 GEM Global Report
Social,
Cultural,
Political
Context
Basic Requirements
- Institutions
- Infrastructure
- Macroeconomic Stability
- Health and Primary
Education
New Branches,
Firm Growth
Established Firms
(Primary Economy)
National
Economic
Growth
(Jobs and
Technical
Innovation)
Efficiency Enhancers
- Higher education and
Training
- Goods Market Efficiency
- Labor Market Efficiency
- Financial Market
Sophistication
- Technological
Readiness
- Market Size
Innovation and
Entrepreneurship
- Entrepreneurial Finance
- Government Policies
- Government
Entrepreneurship
Programs
- Entrepreneurship
Education
- R&D Transfer
- Commercial, Legal
Infrastructure for
Entrepreneurship
- Internal Market
Openness
- Physical Infrastructure
for Entrepreneurship
- Cultural, Social Norms
Aspirations:
Growth
Innovation
Social Value Creation
Activity:
Early-Stage
Persistence
Exits
Entrepreneurship
From GEM
National
Expert Surveys
(NES)
From GEM
Adult Population
Surveys (APS)
From Other
Available
Sources
Attitudes:
Perceived Opportunities
Perceived Capacity
Katz (2003) declared that entrepreneurship education
has reached maturity in the United States and
that future expansion lies elsewhere. Indeed, the
field may experience its greatest growth outside
the innovation-driven countries. For example,
Li et al. (2003) reported that entrepreneurship
education has been well received in China, but is
still a relatively new practice in higher institutions.
Here, entrepreneurship education is an emerging
concept. Yet it may have a significant role to play in
transitioning entrepreneurial activity from necessity-
to opportunity-based in the efficiency-driven countries,
in addition to enhancing innovation and international
competitiveness.
In factor-driven countries, training may be offered as
part of a social or government campaign to improve
skills and create jobs: for example, Finweek reports
on a program in Namibia (Finweek, 2007). In these
poorer countries, providing a basic education to as
many people as possible is a major concern of policy
makers. Entrepreneurship education and training is
likely to take different forms than in the innovation-
driven or efficiency-driven countries. As previous GEM
reports show, in these countries entrepreneurship
rates tend to be high, but mainly necessity-based and
with low-growth aspirations.
2.3 DOES ENTREPRENEURSHIP
EDUCATION AND TRAINING MAKE A
DIFFERENCE?
While there is extensive literature on
entrepreneurship education and training, evidence
demonstrating the influence of training on
entrepreneurial activity is still lacking (Béchard and
Grégoire, 2005). Greater understanding is needed
about how programs and learning strategies help
develop skills that lead to the formation of new
ventures (Garavan and O’Cinneide, 1994). The WEF
Global Education Initiative report argued that there
is strong evidence that entrepreneurship can boost
economic growth and, in turn, alleviate poverty.
However, it did not identify studies specifically linking
entrepreneurship education to economic growth (WEF,
2009).
Can entrepreneurship education or training impact
one’s entrepreneurial orientation? Many studies have
indicated a link between entrepreneurship and both
need for achievement and internal locus of control
(a belief in one’s ability to control one’s destiny).
Hansemark (1998), for example, found that these
15
two traits were higher among enrollees in a one-year
entrepreneurship program in Sweden compared to
those not receiving training. While acknowledging
these studies, one also needs to question whether
entrepreneurship is a function of stable traits or
learned behaviors. Past research has, for the most
part, failed to identify a consistent set of personality
traits associated with entrepreneurship, other than
the two aforementioned traits. This is likely good
news for educators, policy makers and practitioners,
given that traits are generally considered inborn and
unchangeable. As such, most of the literature on the
impact of entrepreneurship education and training
is oriented toward the influence of education on the
perception of skills, attitudes and intent to start
businesses.
A recent study for the Small Business Administration
Office of Advocacy (Summit Consulting, 2009)
found that university graduates who have taken
entrepreneurship courses are more likely to select
careers in entrepreneurship, work in small businesses
and develop patented inventions or innovative
processes, services or products. Researchers
have suggested that education and training for
entrepreneurship should positively influence actions
by enhancing the skills required to start and grow a
venture (Honig, 2004; Summit Consulting, 2009). For
example, education and training can enhance one’s
cognitive ability for managing the complex process of
opportunity recognition and assessment (DeTienne
and Chandler, 2004). Classes that provide role models
and examples of the entrepreneurship process can
equip individuals with the ability to recognize, assess
and shape opportunities (Fiet, 2000).
In contrast, Gatewood (1993) saw potential negative
effects. Focusing on public sector venture assistance,
she suggested that while these programs can
improve the abilities and problem-solving approaches
of potential founders, they could discourage
entrepreneurs who are refused assistance. Moreover,
those receiving training may not start their businesses
because they may realize they do not have the right
skills or that they do not have a viable opportunity,
thus preventing learning by doing.
Perhaps the aforementioned research indicates
that training can help ensure that those businesses
actually started will be more successful. If high SME
failure rates are a consequence of a lack of training,
as Ibrahim and Soufani (2002) suggest, perhaps
training can weed out inexperienced entrepreneurs or
those with an infeasible opportunity. This, however,
places the burden on sound screening and training
practices in the early stages, when uncertainty is
highest. Even then, concepts that are screened out of
programs may result in missed opportunities, because
capable entrepreneurs may shape poor-quality ideas
into more viable ones. In addition, entrepreneurs gain
experience that creates new learning and builds skills.
This in turn raises a question about the exclusiveness
of programs: Should they be selective or encourage
broad participation? It also casts doubt on the effect
of training: Are higher success rates among selective
programs due to the pre-screening or the training
itself?
While knowledge and skills can increase the success
of a venture, these resources will not be put to use
if the inspiration to start a business is not present
in the beginning. Attitudes and intentions are
important in boosting the chance individuals will
attempt an entrepreneurial endeavor at some point
in their lives (Souitaris et al., 2007). Studies on the
influence of education and training on attitudes have
found a positive link to interest in entrepreneurship,
attitudes toward entrepreneurship and perception
of the feasibility of starting a business. Examples
include post-secondary education in Northern Ireland
(Hegarty, 2006), university students in England
(Souitaris et al., 2007) and Germany (Walter and
Dohse, 2009) and secondary school pupils enrolled
in an entrepreneurship program in Australia
(Peterman and Kennedy, 2003). However, other
studies have observed a decrease in intentions after
entrepreneurship education programs, for example, in
a Dutch school (Oosterbeek et al., 2009) and a German
university (Weber et al., 2009). Other studies show
that prior exposure to entrepreneurship and prior
intentions can change the effect of entrepreneurship
training programs (e.g., Fayolle et al., 2006).
These country-level studies provide tantalizing
glimpses of possible relationships between
entrepreneurship education and training and
subsequent behavior. However, it is not at all clear
from the literature whether people on average
experience a gain from training in terms of their
awareness of or attitudes toward entrepreneurship,
their entrepreneurial intentions or indeed their
entrepreneurial activity. The next chapter reviews
the state of entrepreneurship education and training
across the world, as seen by carefully selected experts
in each of 31 countries.
Current Issues in Entrepreneurship Education and Training
16
3.1 THE LEVEL AND QUALITY OF
ENTREPRENEURSHIP EDUCATION AND
TRAINING AS PERCEIVED BY NATIONAL
EXPERTS
GEM national teams conduct National Expert Surveys
(NES) in their countries, polling a selected sample
of individuals who are deemed expert in at least one
Entrepreneurial Framework Condition (EFC), or
aspect of the environment for entrepreneurship. The
principal EFCs recognized by GEM are: financial
support for entrepreneurs, public policy support,
bureaucracy and taxes, government programs,
entrepreneurship education and training, R&D
transfer, access to professional and commercial
infrastructure, internal market dynamics and
barriers, access to physical infrastructure and services
and, finally, cultural and social norms. Typically, four
experts are identified per EFC, of which one is an
entrepreneur, two are providers of that EFC and one
is an expert observer.
The results of this survey add insights on key
framework conditions that can impact the
entrepreneurial process in an economy. In this
chapter, the expert opinions collected by 31 national
teams are summarized. On average, each national
team interviewed 42 experts, with a minimum of 31
and a maximum of 80 experts interviewed. Only one
team interviewed fewer than 35 experts.
In each country, experts were presented with a series
of statements designed to capture their views on
a range of entrepreneurial framework conditions.
They were asked to state their level of agreement or
disagreement with each statement along a 5-point
scale, from 1 representing “strongly disagree” to
5 representing “strongly agree.” With respect to
entrepreneurship education and training, they were
asked to state their opinions on two issues: (1) the
adequacy of formal entrepreneurship education and
training provided at primary and secondary schools
and (2) the adequacy of entrepreneurship education
and training offered through a variety of sources
beyond primary and secondary schooling, such as
colleges and universities, government and professional
programs, etc.
Figure 2 shows the average unweighted ratings of
experts by economic group on these two issues in
relation to the other entrepreneurship framework
conditions measured. In each economic group,
entrepreneurship education in primary and
secondary schools received the worst evaluation by
the experts. The average economic group rating for
this EFC increases with increasing level of economic
development, reflecting a general improvement in
EFCs as countries develop economically.
Entrepreneurship education and training in schools
has received low ratings every year since expert
surveys commenced in 2000. Figure 3 shows the
results for the period 2005 to 2008 for a selection of
countries (for raw data, see Table 10 in the Appendix).
In most countries, the ratings are consistent from year
to year, even though the pool of experts changes. Two
exceptions are Spain and the United States, where
expert ratings have become more negative. Clearly,
this issue is of concern to experts.
Experts rate the level of non-school training higher
than in-school training, and it tends to rank in the
middle range of all EFCs. In absolute terms, however,
it only approaches a neutral rating on average in the
efficiency-driven economic group. This suggests that
experts in many countries feel that this EFC could be
improved. Figure 4 shows the evolution of ratings for
this EFC over the 2005 to 2008 period in a selection
of countries (see Table 10 in the Appendix for raw
data). The ratings are consistent over time in most
countries, although in Brazil the ratings appear to
have improved.
3 The State of Entrepreneurship Education and Training: Expert Opinions
17
The State of Entrepreneurship Education and Training: Expert Opinions
Figure 2—Average Ratings by National Experts on the Level of Entrepreneurial Framework Conditions in Their
Countries, by Economic Group
Source: GEM National Expert Survey 2008
Figure 3—Average Ratings by National Experts on the State of In-School Entrepreneurship Education and
Training in a Sample of GEM Nations for the Years 2005–2008
Source: GEM National Expert Survey 2005–2008
1
1.5
2
2.5
3
3.5
4
4.5
5
I
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
R
&
D
T
r
a
n
s
f
e
r
R
e
g
u
l
a
t
i
o
n
s
,
T
a
x
G
o
v
e
r
n
m
e
n
t
P
r
o
g
r
a
m
s
F
i
n
a
n
c
i
a
l
S
u
p
p
o
r
t
I
n
t
e
r
n
a
l
M
a
r
k
e
t
B
u
r
d
e
n
s
P
o
l
i
c
y
S
u
p
p
o
r
t
N
o
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
C
u
l
t
u
r
a
l
a
n
d
S
o
c
i
a
l
N
o
r
m
s
P
r
o
f
e
s
s
i
o
n
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
I
n
t
e
r
n
a
l
M
a
r
k
e
t
D
y
n
a
m
i
c
s
P
h
y
s
i
c
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
I
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
R
e
g
u
l
a
t
i
o
n
s
,
T
a
x
R
&
D
T
r
a
n
s
f
e
r
F
i
n
a
n
c
i
a
l
S
u
p
p
o
r
t
P
o
l
i
c
y
S
u
p
p
o
r
t
G
o
v
e
r
n
m
e
n
t
P
r
o
g
r
a
m
s
I
n
t
e
r
n
a
l
M
a
r
k
e
t
B
u
r
d
e
n
s
C
u
l
t
u
r
a
l
a
n
d
S
o
c
i
a
l
N
o
r
m
s
P
r
o
f
e
s
s
i
o
n
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
N
o
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
I
n
t
e
r
n
a
l
M
a
r
k
e
t
D
y
n
a
m
i
c
s
P
h
y
s
i
c
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
I
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
R
e
g
u
l
a
t
i
o
n
s
,
T
a
x
R
&
D
T
r
a
n
s
f
e
r
I
n
t
e
r
n
a
l
M
a
r
k
e
t
B
u
r
d
e
n
s
N
o
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
P
o
l
i
c
y
S
u
p
p
o
r
t
F
i
n
a
n
c
i
a
l
S
u
p
p
o
r
t
I
n
t
e
r
n
a
l
M
a
r
k
e
t
D
y
n
a
m
i
c
s
C
u
l
t
u
r
a
l
a
n
d
S
o
c
i
a
l
N
o
r
m
s
G
o
v
e
r
n
m
e
n
t
P
r
o
g
r
a
m
s
P
r
o
f
e
s
s
i
o
n
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
P
h
y
s
i
c
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
Factor-Driven Efficiency-Driven Innovation-Driven
Note: Framework conditions are ordered from the lowest to the highest evaluation within each economic group. The measures range from 1 = poor to 5 = excellent. Total number of countries in sample: 31.
1
2
3
4
5
B
r
a
z
i
l
I
t
a
l
y
C
h
i
l
e
G
r
e
e
c
e
S
l
o
v
e
n
i
a
I
r
e
l
a
n
d
D
e
n
m
a
r
k
S
p
a
i
n
F
i
n
l
a
n
d
N
o
r
w
a
y
U
n
i
t
e
d
S
t
a
t
e
s
2005
2006
2007
2008
18
The State of Entrepreneurship Education and Training: Expert Opinions
Figure 4—Average Ratings by National Expert on the State of Non-School Entrepreneurship Education
and Training in a Sample of GEM Nations for the Years 2005–2008
Source: GEM National Expert Survey 2005–2008
1
2
3
4
5
B
r
a
z
i
l
D
e
n
m
a
r
k
G
r
e
e
c
e
N
o
r
w
a
y
I
t
a
l
y
F
i
n
l
a
n
d
C
h
i
l
e
S
l
o
v
e
n
i
a
I
r
e
l
a
n
d
S
p
a
i
n
U
n
i
t
e
d
S
t
a
t
e
s
2005
2006
2007
2008
3.2 ENTREPRENEURS’ NEED FOR
ASSISTANCE AND THE ADEQUACY OF
TRAINING PROVISION OUTSIDE THE
FORMAL EDUCATION SYSTEM
In 2008, of the 31 countries completing the NES
surveys, 30 included two additional items. The
first item elicited expert opinions on whether
entrepreneurs in general in their country needed
external assistance in planning their businesses prior
to start-up. The second item covered the adequacy of
entrepreneurship education and training provided
by public and/or private agencies independent of the
formal education system. Figure 5 shows the average
ratings by experts on these items in each country. The
results show a perceived need for external assistance
for entrepreneurs starting businesses, with Brazil,
Iran and Mexico reporting the highest levels. Only
Finland received a neutral rating on this issue.
Figure 5 indicates that, in six economies (Germany,
Finland, Republic of Korea, Ireland, Spain and the
United States), experts believe that public and/or
private agencies provide adequate entrepreneurship
education and training outside the formal education
system. The remaining countries report low or
moderate perceptions on this factor. Only in Germany
and Finland is the level of informal education and
training rated higher than perceptions about the need
for assistance in starting businesses. For the other
countries, perceptions about the adequacy of training
offered do not match the perceived need for assistance.
The unusually positive result for Finland is
noteworthy. As Kyro (2006) reports, Finland’s
government has committed to entrepreneurship
education throughout its school system. A report from
Publications of the Ministry of Education, Finland
(2009:9) states: “The aim of the Ministry of Education
is to enhance an entrepreneurial spirit among Finns
and make entrepreneurship a more attractive career
choice.” This may have led Finnish experts to rate
their country’s assistance as sufficient. It is also
consistent with the APS survey results in the next
chapter, which show that Finland has the highest
level of entrepreneurship training among the 38
countries surveyed.
19
Figure 5—Experts’ Average Evaluations in 30 GEM Countries Regarding Entrepreneurs’ Need for External
Assistance with Planning Prior to Start-Up and the Suf?ciency of Entrepreneurship Education and Training
Provided by Public and/or Private Agencies, by Country
Source: GEM National Expert Survey 2008
The State of Entrepreneurship Education and Training: Expert Opinions
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
B
r
a
z
i
l
I
r
a
n
M
e
x
i
c
o
S
p
a
i
n
C
o
l
o
m
b
i
a
N
o
r
w
a
y
M
a
c
e
d
o
n
i
a
E
g
y
p
t
D
e
n
m
a
r
k
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
C
r
o
a
t
i
a
A
r
g
e
n
t
i
n
a
C
h
i
l
e
T
u
r
k
e
y
S
o
u
t
h
A
f
r
i
c
a
B
o
s
n
i
a
a
n
d
H
e
r
z
e
g
o
v
i
n
a
I
r
e
l
a
n
d
I
t
a
l
y
U
n
i
t
e
d
S
t
a
t
e
s
P
e
r
u
B
o
l
i
v
a
S
e
r
b
i
a
U
r
u
g
u
a
y
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
E
c
u
a
d
o
r
S
l
o
v
e
n
i
a
J
a
m
a
i
c
a
G
r
e
e
c
e
G
e
r
m
a
n
y
F
i
n
l
a
n
d
Entrepreneurs Need Assistance with Plans Prior to Start-Up Public and Private Agencies Provide Sufficient Entrepreneurship Education and Training
NOTE: 1=strongly disagree; 2=somewhat disagree; 3=neither agree nor disagree; 4=somewhat agree; 5=strongly agree
In addition to being asked to rate their agreement
with a range of items, experts were also asked to list
positive and negative aspects of the environment for
entrepreneurship and make recommendations. The
frequency with which experts mentioned an EFC
provides another guide to its relative importance.
In 2008, across 30 countries, 30% of mentions of
constraints included the state of entrepreneurship
education and training. This was the third most
frequently mentioned constraint, after financial
support and government policies. It constituted over
half of constraints mentioned in Egypt and South
Africa, compared with only 15% in Finland, 8% in
Argentina and none in Iran.
Surprisingly, entrepreneurship education and
training was the second most frequently cited EFC
in relation to positive aspects of the environment for
entrepreneurship. This suggests that while provision
across most countries may be inadequate, there are
good initiatives in many countries. On average, 25% of
mentions of positive developments or initiatives were
in the domain of this EFC. Over half of mentions of
activities that fostered entrepreneurship in the United
States described positive aspects of entrepreneurship
education and training in the country, compared with
2% in Germany, 5% in South Africa, 6% in Iran and
7% in Turkey.
Experts were asked to make recommendations to
improve the environment for entrepreneurship in their
country. On average, 49% of the recommendations
across the 30 countries were about entrepreneurship
education and training—more than any other
EFC. The exception was Iran, where only 5% of
recommendations related to this EFC. By contrast,
71% of Turkish recommendations and 68% of South
African recommendations were in this area.
In conclusion, it is clear that in most countries,
entrepreneurship experts regard the provision
of entrepreneurship education and training as
inadequate. However, in all countries at least one
expert mentioned examples of good practice in this
area.
20
4 Prevalence and Sources of Training in Starting a Business
4.1 PREVALENCE RATES OF TRAINED
INDIVIDUALS IN THE WORKING-AGE
POPULATION
This chapter provides a report on the proportion of
working-age adults who have received training in
starting a business in the adult population across
the 38 participating countries. Survey respondents
reported if they had ever received training in starting
a business, either during primary or secondary school,
or outside school. GEM compares these rates across
countries and economic groups, noting the proportions
of voluntary and compulsory training. In addition
to providing an estimate of the relative demand for
training in a country, this information is valuable
in estimating the effect of training on subsequent
entrepreneurial behavior.
Figure 6 shows the average prevalence rate of
working-age individuals who have received training
in starting a business across the 38 countries for
which data are available. In total, an average of 21%
of working-age adults in these countries have received
training in starting a business at some point in their
lives. Of those receiving training, the majority (62%)
engaged in this training voluntarily (13% of the total
working-age population). Twenty percent of trained
individuals had received only compulsory training
(4% of the working-age population), while 14% had
received both voluntary and compulsory training (3%
of the working-age population). This indicates that
training in starting a business is done mainly through
self-selection. As mentioned above, this has important
implications for the assessment of cause and effect,
discussed in Chapter 5.
Figure 6 — Average Level of Training in Starting a Business in the Adult Working-Age Population (18–64 Years)
Across All 38 Participating Countries
Source: GEM Adult Population Survey 2008
Have Not Received Training
79%
Have Received Training
21%
Voluntary Training 13%
Compulsory Training 4%
Both Types 3%
Not Classified 1%
The country average summary of training depicted
in Figure 6 needs cautious interpretation, for several
reasons. First, factor-driven countries are under-
represented in the sample. Second, country-level
prevalence rates vary widely, even among countries
with similar levels of economic development. Figure
7 presents the proportion of working-age people
who have received training in starting a business,
by country, in increasing order of prevalence. The
results show wide variation, from 6% in Turkey to
49% in Finland. Most countries, however, fall within
the range of 10% to 30%. High levels of training
were reported in five countries (Belgium, Slovenia,
Colombia, Chile and Finland), where more than 30%
of the adult population has received training. At the
low end, five countries (Turkey, Egypt, Dominican
Republic, Romania and Brazil) reported training
levels of less than 10%.
The wide variation in entrepreneurship training levels
evident in Figure 7 indicates that country-level factors
may be more important than practices or customs
in different global regions. Figure 8 shows training
levels for the three economic groups, organized by
GDP level within the groups. As this figure shows,
the uneven distribution pattern seen geographically
is also evident in economic orderings. Within groups
of countries that are at a similar stage of development
(factor-driven, efficiency-driven and innovation-
driven), there is a high level of variation, with at least
one country with high training levels in each group
(Colombia, Chile and Finland).
21
Prevalence and Sources of Training in Starting a Business
Figure 7—Percentage of the Adult Working-Age Population (18–64 Years) That Received Training in Starting a
Business, by Country, Ordered by Increasing Prevalence
Source: GEM Adult Population Survey 2008
Figure 8—Percentage of the Adult Working-Age Population (18–64 Years) That Received Start-Up Training, by
Country and Economic Group, Ordered by GDP
Source: GEM Adult Population Survey 2008
0%
10%
20%
30%
40%
50%
60%
T
u
r
k
e
y
E
g
y
p
t
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
R
o
m
a
n
i
a
B
r
a
z
i
l
S
e
r
b
i
a
I
s
r
a
e
l
I
n
d
i
a
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
S
o
u
t
h
A
f
r
i
c
a
M
e
x
i
c
o
I
t
a
l
y
G
r
e
e
c
e
J
a
p
a
n
A
r
g
e
n
t
i
n
a
F
r
a
n
c
e
U
n
i
t
e
d
K
i
n
g
d
o
m
B
o
l
i
v
i
a
M
a
c
e
d
o
n
i
a
B
o
s
n
i
a
a
n
d
H
e
r
z
e
g
o
v
i
n
a
J
a
m
a
i
c
a
G
e
r
m
a
n
y
S
p
a
i
n
D
e
n
m
a
r
k
U
r
u
g
u
a
y
H
u
n
g
a
r
y
I
r
e
l
a
n
d
I
c
e
l
a
n
d
E
c
u
a
d
o
r
C
r
o
a
t
i
a
L
a
t
v
i
a
I
r
a
n
P
e
r
u
B
e
l
g
i
u
m
S
l
o
v
e
n
i
a
C
o
l
o
m
b
i
a
C
h
i
l
e
F
i
n
l
a
n
d
P
e
r
c
e
n
t
a
g
e
o
f
t
h
e
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
I
n
d
i
a
E
g
y
p
t
B
o
l
i
v
i
a
E
c
u
a
d
o
r
B
o
s
n
i
a
a
n
d
H
e
r
z
e
g
o
v
i
n
a
C
o
l
o
m
b
i
a
G
r
o
u
p
A
v
e
r
a
g
e
T
u
r
k
e
y
P
e
r
u
M
a
c
e
d
o
n
i
a
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
J
a
m
a
i
c
a
S
e
r
b
i
a
I
r
a
n
S
o
u
t
h
A
f
r
i
c
a
U
r
u
g
u
a
y
A
r
g
e
n
t
i
n
a
B
r
a
z
i
l
R
o
m
a
n
i
a
M
e
x
i
c
o
C
h
i
l
e
C
r
o
a
t
i
a
L
a
t
v
i
a
H
u
n
g
a
r
y
G
r
o
u
p
A
v
e
r
a
g
e
I
s
r
a
e
l
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
S
l
o
v
e
n
i
a
G
r
e
e
c
e
J
a
p
a
n
I
t
a
l
y
S
p
a
i
n
U
n
i
t
e
d
K
i
n
g
d
o
m
G
e
r
m
a
n
y
F
r
a
n
c
e
B
e
l
g
i
u
m
F
i
n
l
a
n
d
I
c
e
l
a
n
d
D
e
n
m
a
r
k
I
r
e
l
a
n
d
G
r
o
u
p
A
v
e
r
a
g
e
P
e
r
c
e
n
t
a
g
e
o
f
t
h
e
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
y
e
a
r
s
)
Factor-Driven Efficency-Driven Innovation-Driven
22
Next, the level of voluntary and compulsory training is
examined. Individuals engaged in voluntary training
have, by definition, chosen to take it, perhaps relative
to other pursuits. Compulsory training, on the other
hand, represents a required activity. For example,
individuals could be required to take a course to
complete a degree or certificate program, or to satisfy
requirements relating to registering a business or
receiving assistance or funding.
Figure 9 shows the breakdown in compulsory versus
voluntary training by economic group. In factor-
driven countries, less than one-fourth of trained
individuals had received any compulsory training. In
the other two groups, between one-third and one-half
of those who received training had taken compulsory
training. This is consistent with the GEM theoretical
model, where improving basic requirements like
infrastructure, health and primary education take
greater priority in factor-driven economies. Factor-
driven countries tend to show higher levels of early-
stage entrepreneurial activity, but this is likely to be
more necessity-based and less growth-, innovation-
and international-based.
Some countries demonstrate relatively high
proportions of compulsory training. In Denmark, for
example, over 65% of those trained received both
compulsory and voluntary training, with an additional
15% receiving only compulsory training. So four-fifths
of trained individuals in Denmark were required to
take training in starting a business. In Hungary,
almost 60% of those who received training did so
only on a compulsory basis (with an additional 14%
receiving both compulsory and voluntary training).
Other countries reporting a relatively high level of
compulsory training include Jamaica, Croatia and
Latvia in the efficiency-driven group, and Iceland,
Ireland and Slovenia in the innovation-driven group.
There seems to be no relationship between early-
stage entrepreneurial activity rates and the ratio of
compulsory to voluntary training. For example, among
innovation-driven countries, Denmark and Slovenia
have low rates of early-stage entrepreneurial activity,
while Ireland and Iceland have high rates. All show
high ratios of compulsory to voluntary training.
Prevalence and Sources of Training in Starting a Business
Figure 9—Levels of Voluntary and Compulsory Start-Up Training, by Country and Economic Group, Ordered by
Level of Voluntary Training
Source: GEM Adult Population Survey 2008
0%
10%
20%
30%
40%
50%
E
g
y
p
t
I
n
d
i
a
B
o
l
i
v
i
a
B
o
s
n
i
a
a
n
d
H
e
r
z
e
g
o
v
i
n
a
E
c
u
a
d
o
r
C
o
l
o
m
b
i
a
G
r
o
u
p
A
v
e
r
a
g
e
T
u
r
k
e
y
R
o
m
a
n
i
a
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
S
e
r
b
i
a
H
u
n
g
a
r
y
S
o
u
t
h
A
f
r
i
c
a
B
r
a
z
i
l
M
e
x
i
c
o
J
a
m
a
i
c
a
A
r
g
e
n
t
i
n
a
C
r
o
a
t
i
a
L
a
t
v
i
a
M
a
c
e
d
o
n
i
a
I
r
a
n
U
r
u
g
u
a
y
P
e
r
u
C
h
i
l
e
G
r
o
u
p
A
v
e
r
a
g
e
D
e
n
m
a
r
k
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
I
s
r
a
e
l
F
r
a
n
c
e
I
t
a
l
y
U
n
i
t
e
d
K
i
n
g
d
o
m
J
a
p
a
n
G
r
e
e
c
e
I
c
e
l
a
n
d
I
r
e
l
a
n
d
S
p
a
i
n
G
e
r
m
a
n
y
S
l
o
v
e
n
i
a
B
e
l
g
i
u
m
F
i
n
l
a
n
d
G
r
o
u
p
A
v
e
r
a
g
e
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
Only Voluntary Both Voluntary and Compulsory Only Compulsory Not Classified
23
Prevalence and Sources of Training in Starting a Business
In summary, more than one-fifth of the working-age
(18–64 years) population across the 38 participating
countries had received training in starting a business
as of mid-2008. The country-level prevalence rate
varies considerably. Most countries show a level
between 10% and 30%, with a few countries having
higher or lower prevalence rates. On average, there
is not a significant difference in level or variability
between the three economic groups. For most
countries, but not all, more than half of the trained
population engaged in training voluntarily.
4.2 SOURCES OF TRAINING IN
STARTING A BUSINESS
This section investigates how sources of start-up
training vary across countries and economic groups.
In an examination of training sources, a distinction
is made between “in-school” and “non-school”
training. In-school training is training provided as
part of primary or secondary education. Non-school
training comprises sources beyond primary and
secondary schooling, such as colleges, universities,
public agencies, chambers of commerce, trade unions
and employers. Secondly, “formal” and “informal”
training are defined. Formal training is received as
part of a formal education, e.g. primary or secondary
education, or as part of a tertiary-level certificate,
diploma or degree program. Informal training refers
to all other types of training. These might include
non-credit evening courses at a university, local
business organization or a government agency. These
dimensions provide different perspectives on the
nature of the training system in each country.
These distinctions are important because they can
capture the extent to which a government is providing
entrepreneurship training through the formal
education system and how early that training occurs
in a person’s schooling. Additionally, they capture
the relative importance of informal training sources,
which may help people at a time when they are
more directly engaged in starting businesses, rather
than focused on their education generally. A closer
examination of informal sources can reveal whether
informal training is concentrated through one or
many suppliers—whether it is the responsibility of
universities, private organizations, government or
other sources.
Figure 10 shows the prevalence of training broken
down into in-school and non-school training, organized
by frequency of in-school only training within
economic groups. The level of in-school training in
the adult population varies across countries: from
2% of the adult population in Turkey to around 25%
in Belgium, Chile and Slovenia. Non-school training
ranges from 4% in Egypt and Turkey to 40% in
Finland. Only 30% of trained individuals in Japan and
Serbia received in-school training, compared to around
75% in Ecuador, Jamaica and Belgium.
From Figure 10, it is seen that, on average, the
proportion of non-school training to total training is
similar (68-69%) across the three economic groups
(this includes “non-school only” and “both in-school
and non-school”). However, the proportion of in-
school training is highest (62%) in the factor-driven
economies and lowest (52%) in the innovation-driven
economies (including “in-school only” and “both in-
school and non-school”). The proportion of individuals
that received training from both sources in relation
to total training is also highest in the factor-driven
economies (31%) and lowest in the innovation-driven
economies (21%). These results imply that in-school
and non-school training are roughly equally important
sources of training in the factor-driven economies,
but the relative importance of non-school training is
greater in more developed economies. See Table 11 in
the Appendix for further details on sources of start-up
training.
As Figure 11 shows, most trained individuals have
had formal training, and of these, most have had
informal training in addition to formal training.
Individuals who have had only informal training are
more rare. The prevalence of individuals with formal
training varies from 4% of the adult population in
Serbia and Turkey to 40% in Finland. For informal
training, the range is from 4% in Egypt, Turkey
and Romania to 35% in Finland. The prevalence of
individuals with both types ranges from 1% in Serbia
to 27% in Finland.
24
Prevalence and Sources of Training in Starting a Business
Figure 10—Prevalence of In-School and Non-School Training, by Economic Group, Ordered by Frequency of In-
School Only Training
Source: GEM Adult Population Survey 2008
Figure 11—Prevalence of Formal and Informal Start-Up Training, by Country and Economic Group, Ordered by
Frequency of Formal Only Training
Source: GEM Adult Population Survey 2008
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
0%
10%
20%
30%
40%
50%
B
o
l
i
v
i
a
I
n
d
i
a
E
g
y
p
t
B
o
s
n
i
a
a
n
d
H
e
r
z
e
g
o
v
i
n
a
C
o
l
o
m
b
i
a
E
c
u
a
d
o
r
G
r
o
u
p
A
v
e
r
a
g
e
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
T
u
r
k
e
y
S
e
r
b
i
a
C
r
o
a
t
i
a
B
r
a
z
i
l
R
o
m
a
n
i
a
S
o
u
t
h
A
f
r
i
c
a
U
r
u
g
u
a
y
P
e
r
u
A
r
g
e
n
t
i
n
a
M
e
x
i
c
o
M
a
c
e
d
o
n
i
a
L
a
t
v
i
a
I
r
a
n
C
h
i
l
e
J
a
m
a
i
c
a
H
u
n
g
a
r
y
G
r
o
u
p
A
v
e
r
a
g
e
J
a
p
a
n
I
t
a
l
y
G
r
e
e
c
e
I
s
r
a
e
l
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
U
n
i
t
e
d
K
i
n
g
d
o
m
F
r
a
n
c
e
D
e
n
m
a
r
k
S
p
a
i
n
G
e
r
m
a
n
y
F
i
n
l
a
n
d
I
r
e
l
a
n
d
I
c
e
l
a
n
d
S
l
o
v
e
n
i
a
B
e
l
g
i
u
m
G
r
o
u
p
A
v
e
r
a
g
e
In-School Only Both In-School and Non-School Non-School Only
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
0%
10%
20%
30%
40%
50%
B
o
l
i
v
i
a
I
n
d
i
a
E
g
y
p
t
B
o
s
n
i
a
a
n
d
H
e
r
a
e
g
o
v
i
n
a
C
o
l
o
m
b
i
a
E
c
u
a
d
o
r
G
r
o
u
p
A
v
e
r
a
g
e
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
T
u
r
k
e
y
S
e
r
b
i
a
B
r
a
z
i
l
C
r
o
a
t
i
a
R
o
m
a
n
i
a
S
o
u
t
h
A
f
r
i
c
a
U
r
u
g
u
a
y
P
e
r
u
A
r
g
e
n
t
i
n
a
M
e
x
i
c
o
M
a
c
e
d
o
n
i
a
I
r
a
n
C
h
i
l
e
L
a
t
v
i
a
J
a
m
a
i
c
a
H
u
n
g
a
r
y
G
r
o
u
p
A
v
e
r
a
g
e
J
a
p
a
n
I
t
a
l
y
I
s
r
a
e
l
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
F
r
a
n
c
e
G
r
e
e
c
e
U
n
i
t
e
d
K
i
n
g
d
o
m
D
e
n
m
a
r
k
S
p
a
i
n
G
e
r
m
a
n
y
I
r
e
l
a
n
d
I
c
e
l
a
n
d
F
i
n
l
a
n
d
S
l
o
v
e
n
i
a
B
e
l
g
i
u
m
G
r
o
u
p
A
v
e
r
a
g
e
Only Formal Both Formal and Informal Only Informal
25
Table 2—Prevalence of Formal Training, by Country and Economic Group, Ordered by Prevalence
of School Training
Source: GEM Adult Population Survey 2008
Prevalence and Sources of Training in Starting a Business
The high level of overlap between formal and informal
training indicates that both formal and informal
systems are important sources of entrepreneurship
training and suggests that they complement each
other. See Table 12 in the Appendix for formal and
informal training prevalence rates for each country.
Table 2 provides a more detailed view of formal
training in the participating countries. It shows that
school training as a proportion of total formal training
ranges from 43% in Greece to 90% in Mexico.
COUNTRY
A
TRAINING IN
SCHOOL ONLY
B
TRAINING AT TERTIARY
LEVEL ONLY
C
BOTH SCHOOL AND
TERTIARY TRAINING
D
SCHOOL TOTAL
(A+C)
E
TERTIARY TOTAL (B+C)
F
RATIO OF TOTAL SCHOOL TO
TOTAL TERTIARY (D/E)
Factor-Driven
Colombia (+) 29% 41% 30% 59% 71% 0.8
Bolivia 41% 35% 24% 65% 59% 1.1
India 41% 27% 32% 73% 59% 1.3
Bosnia and Herzegovina (+) 67% 23% 10% 77% 33% 2.3
Egypt 65% 23% 13% 77% 35% 2.2
Ecuador (+) 57% 18% 24% 82% 43% 1.9
Group Average 50% 28% 22% 72% 50% 1.6
Ef?ciency-Driven
Uruguay 42% 41% 17% 59% 58% 1.0
Latvia 44% 39% 16% 61% 56% 1.1
Peru 38% 36% 25% 64% 62% 1.0
Turkey 59% 36% 5% 64% 41% 1.6
Chile 44% 33% 23% 67% 56% 1.2
Argentina 61% 27% 13% 73% 39% 1.9
Iran 61% 25% 14% 75% 39% 1.9
Serbia 73% 24% 2% 76% 27% 2.8
South Africa 52% 22% 26% 78% 48% 1.6
Jamaica 66% 19% 15% 81% 34% 2.4
Macedonia 67% 19% 14% 81% 33% 2.5
Dominican Republic 70% 17% 13% 83% 30% 2.8
Romania 60% 17% 23% 83% 40% 2.1
Croatia (+) 56% 17% 27% 83% 44% 1.9
Hungary (+) 79% 15% 6% 85% 21% 4.1
Brazil 74% 11% 15% 89% 26% 3.4
Mexico 73% 10% 17% 90% 27% 3.4
Group Average 60% 24% 16% 76% 40% 2.2
Innovation-Driven
Greece 33% 57% 9% 43% 67% 0.6
Japan 31% 55% 15% 45% 69% 0.7
Finland 27% 53% 20% 47% 73% 0.6
Israel 49% 43% 9% 57% 51% 1.1
Denmark 55% 40% 5% 60% 45% 1.3
Iceland 53% 39% 7% 61% 47% 1.3
United Kingdom 51% 39% 11% 61% 49% 1.2
Republic of Korea 54% 36% 11% 64% 46% 1.4
Spain 47% 33% 20% 67% 53% 1.3
Italy 56% 32% 12% 68% 44% 1.5
Ireland 55% 29% 16% 71% 45% 1.6
Germany 59% 27% 14% 73% 41% 1.8
Slovenia 56% 22% 22% 78% 44% 1.8
France 60% 22% 19% 78% 40% 1.9
Belgium 66% 16% 19% 84% 34% 2.5
Group Average 50% 36% 14% 64% 50% 1.4
(+) Nations in transition to next stage of competitiveness
26
Prevalence and Sources of Training in Starting a Business
Training at tertiary level as a proportion of total
formal training ranges from 21% in Hungary to 73%
in Finland. In most countries, in-school training is
more prevalent than training at the tertiary level. On
average, this ratio is higher for the efficiency-driven
economic group than for the other two, but there is
also a wide variation within each group. Tertiary-level
training is more prevalent than in-school training
in only four countries: Colombia, Greece, Japan and
Finland.
Table 3 provides a more detailed view of informal
training sources in the participating countries. The
most frequent source of informal training in most of
the countries is self-study, with up to 88% (Croatia)
of those receiving informal training citing this source.
The next most common source of informal training
across the data set is informal university programs,
followed by courses offered through business
associations. The least frequently mentioned sources
are training programs provided by public agencies and
those offered through employer initiatives.
Table 3—Prevalence of Informal Start-Up Training, by Country and Economic Group
Source: GEM Adult Population Survey 2008
COUNTRY PERCENTAGE OF INFORMAL TRAINING SOURCE
University, College
Local Business
Associations
Public Agencies Employer Self-Studies Other Online
Factor-Driven
Bolivia 9.1 (34.6) 8.2 (24.1) 4.6 (16.6) 10.3 (27.9) 45.9 (86.5) 11.4 (26.0) 6.1 (21.0)
Bosnia and Herzegovina (+) 2.9 (28.9) 2.4 (24.1) 1.5 (15.1) 4.5 (45.3) 8.6 (86.2) 1.8 (18.2) 2.0 (20.1)
Colombia (+) 10.7 (37.9) 6.1 (21.5) 5.5 (19.6) 5.3 (18.7) 23.8 (84.5) 7.2 (25.4) 3.5 (12.3)
Ecuador (+) 4.6 (32.5) 4.3 (30.5) 2.7 (19.0) 3.5 (24.3) 10.5 (73.1) 3.8 (26.9) 2.3 (16.1)
Egypt 1.4 (37.0) 1.1 (28.0) 1.7 (43.6) 1.3 (34.0) 2.4 (62.0) 0.5 (12.0) 1.0 (27.0)
India 2.7 (26.3) 2.9 (28.8) 2.8 (27.9) 2.2 (22.1) 4.9 (48.9) 3.6 (35.8) 1.4 (13.6)
Ef?ciency-Driven
Argentina 5.8 (54.0) 5.7 (52.9) 2.3 (21.4) 4.2 (39.2) 9.4 (86.6) 1.7 (16.0) 2.4 (21.5)
Brazil 2.0 (31.5) 4.4 (71.2) 1.1 (17.7) 1.0 (16.1) 2.3 (35.5) 2.3 (35.5) 0.5 (6.5)
Chile 11.3 (35.8) 8.5 (26.8) 10.9 (34.4) 11.8 (37.5) 25.7 (80.8) 14.4 (45.4) 19.9 (61.5)
Croatia (+) 9.7 (25.7) 7.7 (19.1) 4.8 (12.1) 12.8 (26.3) 53.9 (87.7) 10.0 (18.8) 12.4 (22.5)
Dominican Republic 6.9 (41.6) 6.2 (29.0) 3.3 (17.4) 6.4 (33.6) 53.5 (55.5) 0.9 (8.0) 1.1 (10.1)
Hungary (+) 1.9 (28.9) 0.9 (14.1) 1.5 (22.7) 0.9 (14.1) 1.4 (21.1) 0.1 (0.8) 0.3 (3.9)
Iran 4.0 (22.1) 2.4 (13.0) 9.2 (50.3) 3.1 (17.2) 9.8 (53.7) 3.4 (18.3) 1.8 (9.3)
Jamaica 2.8 (36.0) 1.2 (15.6) 2.7 (33.7) 1.3 (16.1) 4.5 (55.9) 0.6 (7.0) 0.6 (0.5)
Latvia 5.1 (32.0) 2.3 (14.7) 3.2 (20.3) 4.2 (25.9) 12.6 (78.4) 1.5 (9.7) 6.8 (39.4)
Macedonia 3.5 (33.5) 3.1 (29.7) 1.8 (17.0) 3.3 (31.9) 8.2 (79.1) 2.4 (23.1) 2.3 (21.4)
Mexico 1.7 (18.3) 2.4 (26.5) 1.5 (16.5) 3.0 (31.5) 3.6 (38.5) 2.4 (25.2) 0.9 (8.7)
Peru 12.5 (53.2) 6.5 (27.4) 5.2 (21.4) 7.7 (33.0) 17.3 (65.6) 7.7 (33.3) 4.6 (17.5)
Romania 1.4 (32.9) 1.1 (26.8) 0.8 (18.3) 1.5 (36.2) 2.8 (65.7) 1.7 (40.0) 0.7 (15.7)
Serbia 1.4 (19.5) 1.0 (13.5) 2.4 (32.3) 1.2 (16.5) 2.8 (37.6) 0.5 (6.8) 0.8 (11.3)
South Africa 4.4 (51.1) 3.3 (38.4) 2.6 (69.1) 2.9 (35.5) 5.6 (65.2) 2.2 (25.8) 0.8 (9.4)
Turkey 1.0 (24.0) 0.6 (14.7) 0.7 (17.7) 1.5 (37.5) 2.7 (67.7) 0.7 (17.7) 0.7 (17.7)
Uruguay 9.5 (54.2) 9.4 (53.1) 3.9 (22.2) 6.6 (37.5) 12.9 (74.0) 4.3 (24.3) 3.4 (19.1)
Innovation-Driven
Belgium 4.7 (32.3) 3.0 (20.5) 4.4 (30.3) 2.0 (13.9) 7.7 (53.3) 4.0 (27.4) 1.1 (7.3)
Denmark 3.4 (22.1) 3.4 (22.1) 4.3 (27.4) 2.0 (13.5) 5.0 (33.3) 1.6 (10.9) 1.5 (9.9)
Finland 10.8 (30.6) 5.7 (16.2) 7.7 (21.6) 3.8 (10.9) 30.5 (86.4) 8.0 (22.6) 4.8 (12.8)
France 2.1 (17.2) 5.5 (45.3) 4.8 (39.3) 1.8 (15.2) 8.2 (67.2) 4.0 (33.0) 2.5 (20.3)
Germany 1.8 (13.9) 7.5 (57.2) 4.2 (32.5) 4.7 (35.7) 10.2 (78.5) 3.2 (24.2) 0.8 (6.1)
Greece 1.3 (12.1) 4.2 (38.1) 2.6 (23.7) 2.1 (19.2) 7.9 (72.4) 1.1 (9.8) 1.8 (16.7)
Iceland 4.4 (25.7) 2.6 (15.2) 2.8 (16.4) 4.5 (26.2) 14.2 (82.5) 4.2 (24.5) 7.8 (44.6)
Ireland 6.9 (40.5) 4.6 (26.7) 6.5 (38.1) 5.0 (29.3) 13.7 (80.5) 1.0 (5.8) 1.5 (8.8)
Israel 3.3 (41.0) 3.4 (41.4) 3.1 (35.9) 2.7 (33.1) 5.8 (71.7) 1.5 ( 17.9) 0.8 (10.3)
Italy 5.2 (22.2) 7.1 (32.3) 2.4 (7.2) 6.3 (26.8) 29.3 (80.1) 1.8 (8.6) 1.8 (15.0)
Japan 8.7 (60.7) 2.7 (18.8) 1.8 (12.6) 4.6 (31.9) 12.1 (84.4) 2.4 (16.7) 3.7 (25.6)
Republic of Korea 3.9 (44.1) 2.7 (30.1) 1.4 (15.8) 1.6 (18.2) 4.4 (49.4) 1.0 (11.4) 1.4 (12.4)
Slovenia 9.2 (45.5) 6.4 (31.7) 5.2 (25.8) 6.3 (31.0) 15.5 (76.8) 3.5 (17.9) 10.8 (51.2)
Spain 8.0 (56.4) 6.2 (43.8) 5.6 (39.5) 4.8 (33.7) 10.0 (70.2) 7.2 (50.6) 5.7 (39.4)
United Kingdom 4.5 (36.6) 3.2 (26.3) 3.1 (25.5) 3.0 (24.8) 9.6 (78.3) 0.6 (5.1) 1.2 (9.5)
(+) Nations in transition to next stage of competitiveness
Note: Percentages shown are for the adult population aged 18-64 years and, in parentheses, as a percentage of those receiving any informal training
27
Use of online programs is most frequent in Chile (62%
of those receiving informal training) and Slovenia
(51%). Frequency of use does not imply popularity.
In Chile, online training is linked with business
registration. Another notable pattern is the low
frequency of government programs. Few countries
show a high level of public agency training. Exceptions
are South Africa with 69% and Iran with 50% of those
receiving informal training.
In summary, both levels of in-school versus non-school
training and levels of formal versus informal training
vary widely across economies and levels of economic
development. The high proportion of formal training
reveals the importance of schools, colleges and
universities in delivering this framework condition.
In most countries, more people have received formal
training from schools than from tertiary-level
institutions, indicating that schools have a broader
reach. The degree of overlap between formal and
informal training suggests that formal training on
its own is not enough for many people. A demand
for informal training also exists, perhaps shortly
before, during or after a venture is started. Finally,
people have a variety of choices for pursuing informal
training. The high frequency of self-study suggests
that many individuals either cannot access or afford
organized training—or perhaps doubt its efficacy.
4.3 DEMOGRAPHICS OF TRAINED
INDIVIDUALS
This section describes the individuals who have and
have not received training in starting a business,
comparing them in terms of age, gender, education
and income across economic groups.
Figure 12 compares the age profiles of trained and
untrained individuals in each of the three economic
groups. Unsurprisingly, populations age as countries
develop; with better health care and education, people
live longer. However, there are differences between
the age profiles of trained and untrained individuals
in all three economic groups. Trained individuals are
more likely to be found in the two younger age ranges
(18–24 years and 25–34 years) and less likely to be in
the three older age ranges. This suggests that training
in starting a business may have increased in recent
decades and, in particular, provision for younger
people may have increased, possibly through the
formal education system.
Figure 12—Age Distribution of Trained and Untrained Individuals, by Economic Group
Source: GEM Adult Population Survey 2008
31%
20%
27%
19%
18%
12%
31%
26%
30%
26%
26%
21%
18%
24%
20%
22% 24%
25%
14%
18%
15%
19% 18%
23%
6%
12%
8%
15% 14%
20%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Trained Untrained Trained Untrained Trained Untrained
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
18-24 Years 25-34 Years 35-44 Years 45-54 Years 55-64 Years
Prevalence and Sources of Training in Starting a Business
28
Prevalence and Sources of Training in Starting a Business
Figure 13 shows that trained individuals are
more likely to be men than women, and untrained
individuals are more likely to be women than men in
all three economic groups. This is not surprising since
in many countries, women show lower entrepreneurial
intentions and activity than men, and so they are
less likely to seek training voluntarily. While similar
proportions of men and women had taken voluntary
training in some countries, only in Latvia and
Hungary were women significantly more likely than
men to have volunteered for training. The proportion
of men and women who have taken compulsory
training also varied widely by country. However,
on average in factor-driven countries, for every ten
men with compulsory training there were seven
women, compared with eight women in efficiency-
driven countries and nine women in innovation-
driven countries. Because voluntary training was
more prevalent than compulsory training, the gender
difference in training prevalence is mainly due to
lower rates of voluntary training among women, and
this did not appear to vary with increasing economic
development (in all three economic groups, for every
ten men who had volunteered for training, there were
eight women).
Figure 13—Gender Distribution of Trained and Untrained Individuals, by Economic Group
Source: GEM Adult Population Survey 2008
57%
48%
55%
49%
56%
49%
44%
52%
45%
51%
44%
51%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Trained Untrained Trained Untrained Trained Untrained
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
Male Female
Figure 14 shows that individuals with at least some
post-secondary school education are more likely to
have received training in starting a business. In most
countries, this is true for voluntary and compulsory
training. Such individuals have spent more time in the
formal education system, so they are more likely to
have had more training opportunities. However, this
group tends to be more entrepreneurial anyway—more
likely to see a need to learn about starting a business
and more likely to see value in such training.
29
Prevalence and Sources of Training in Starting a Business
Figure 14—Education Distribution of Trained and Untrained Individuals, by Economic Group
Source: GEM Adult Population Survey 2008
Figure 15—Income Distribution of Trained and Untrained Individuals, by Economic Group
Source: GEM Adult Population Survey 2008
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
1% 3% 0% 0% 0% 0%
20%
43%
19%
41%
17%
27%
37%
27%
35%
32%
27%
26%
23%
12%
21%
14%
26%
21%
20%
15%
26%
13%
30%
26%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Trained Untrained Trained Untrained Trained Untrained
Factor-Driven Efficiency-Driven Innovation-Driven
No Secondary Some Secondary Secondary Degree Some Post-Secondary Graduate
Figure 15 shows that the profile of untrained
individuals is less wealthy than the profile of
trained individuals. This association is stronger in
factor-driven or efficiency-driven countries than in
innovation-driven countries. In addition to the obvious
reason, training may help make individuals wealthier,
individuals from wealthy households may have more
opportunity to engage in training and wealthier
households can afford further education for their
children. Moreover, poorer individuals may not have
the time or money to devote to training.
31%
44%
27%
37%
31%
35%
35%
34%
36%
38%
37%
36%
34%
22%
38%
26%
32%
29%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Trained Untrained Trained Untrained Trained Untrained
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
LOWEST 33%TILE MIDDLE 33%TILE UPPER 33%TILE
30
5 The Relationship Between Training in Starting a Business and Entrepreneurship
5.1 ISSUES IN MEASURING
THE EFFECT OF TRAINING ON
ENTREPRENEURIAL BEHAVIOR
This chapter considers the relationship between
training and entrepreneurial awareness, attitudes,
intention and activity. Previous chapters
have reported on the frequency and nature of
entrepreneurship education and training across
economies and economic groupings. The sources of
training and demographic information about those
trained have also been revealed. In this chapter the
question posed in Section 2.3 will be addressed: Does
entrepreneurship education and training make a
difference?
The literature reviewed in Section 2.3 indicates
a lack of evidence demonstrating the influence of
training on entrepreneurial activity (Béchard and
Grégoire, 2005). There is some evidence, however,
that entrepreneurship education and training may
enhance skills (DeTienne and Chandler, 2004; Honig,
2004; Summit Consulting, 2009) and attitudes
(Peterman and Kennedy, 2003; Hegarty, 2006;
Souitaris et al., 2007; Walter and Dohse, 2009) toward
entrepreneurship. In conclusion, there was a need
to explore the relationships between this training
and awareness, attitudes, intention and activity
across multiple countries, using large, representative
samples in each.
Many research studies on entrepreneurship training
have had difficulty assembling adequate control
groups to demonstrate effects, due to cost and data
protection issues (Summit Consulting, 2009). GEM
conducts random samples of the entire working-age
population in a wide range of countries. By asking
random samples of the population questions about
their awareness, attitudes, intention and activity, and
then, later in the interview, asking them questions
about any training in starting a business they may
have had, many sampling biases are avoided and
natural control groups are created.
It is natural to assume that those who want to start
businesses would seek out information on how to
proceed. They might therefore seek training as part of
their search. If one were to compare these people with
those who did not take training, observed differences
in awareness, attitudes, intention or activity might
not just be due to their training, but to their prior
orientation as well. For example, business school
students tend to self-select into this type of education
and, most often, into entrepreneurship training
once they are enrolled in business school. Because
individuals were asked whether their training was
voluntary or compulsory or both, GEM can isolate
those who had voluntary training and remove them
from analyses of cause and effect, eliminating self-
selection bias to a considerable degree.
By noting all the training that a representative
sample of individuals received in their lives so far,
and analyzing a broad array of outcomes, the GEM
data address the issues of timing that have hampered
progress in research on the effect of entrepreneurship
education and training. People may receive
entrepreneurship education and training at various
times in their lives, whether at school, university
or beyond their formal education. In addition, the
effects may be deferred rather than instantaneous.
For example, in the short term, graduates of
entrepreneurship education may recognize the need
to amass specific knowledge (Fiet and Pankaj, 2008),
yet decide to defer action until they understand their
chosen industry better. The GEM data also accounts
for differences in how individuals learn. This learning
can range from traditional education to experiential
immersion in the phenomenon—through a placement
or internship in an actual company, for example. GEM
surveyed individuals about the full range of possible
training sources, from primary school onward, which
enables inclusion of all combinations of training. In
addition, by measuring demographic characteristics
of each individual in each sample, GEM can control
for age group, gender, education, working status and
other effects that might mask the training effect.
Finally, GEM can address limitations due
to differences in context. In some countries,
entrepreneurship is widespread, easily observable
and culturally acceptable. In others, few individuals
start businesses; any training that exists in these
countries may provide a more significant source of
learning. By surveying many countries, GEM can
discern the differences in cause and effect that might
be contextual.
This combination of advantages in the GEM
methodology provides a unique opportunity to make a
baseline contribution to the knowledge of the impact
of entrepreneurship training. In addition, it can reveal
opportunities for more focused follow-up research.
5.2 TRAINING IN STARTING A
BUSINESS AND INVOLVEMENT IN
ENTREPRENEURIAL ACTIVITY
The GEM APS survey assesses the proportion
of working-age individuals in an economy that
are in the process of starting a business (nascent
entrepreneurs) or owners of new businesses (under
42 months old). This is the basic GEM measure of
31
The Relationship Between Training in Starting a Business and Entrepreneurship
early-stage entrepreneurial activity (TEA). As Figure
16 illustrates, across the 38 countries, entrepreneurs
are more likely to have received training in starting
a business (33%) than the rest of the working-age
population (20%). This difference is statistically
significant and suggests that current early-stage
entrepreneurial activity is associated, at least to some
degree, with past training in starting a business.
Figure 16 — Proportion of Trained vs. Untrained Individuals Involved in Early-Stage Entrepreneurial Activity
(TEA), and Those Not Involved (non-TEA)
Source: GEM Adult Population Survey 2008
Table 4 compares the proportion of the whole working-
age population and the proportion of early-stage
entrepreneurs who have received training in each
nation, in three economic groups, ordered by relative
frequency of training. Training prevalence varies
widely across countries, but the proportion of trained
individuals and trained early-stage entrepreneurs
is higher on average in innovation-driven countries.
Around one-fifth of working-age individuals in factor-
driven and efficiency-driven countries are trained; this
rises to around one-third of early-stage entrepreneurs.
This compares with around one-quarter of working-
age individuals and two-fifths of early-stage
entrepreneurs in innovation-driven countries.
The third column in Table 4, reproduced in graphical
form in Figures 17–19, shows that in both factor-
driven and efficiency-driven countries, as the
level of training in the working population as a
whole increases, so does the level of training in the
population of early-stage entrepreneurs, but at a
declining rate. In other words, the conversion of
trained individuals to entrepreneurs appears to be
higher in countries with a low rate of training than in
countries with a high rate of training. This suggests
that there may be diminishing returns to training
in terms of conversion to entrepreneurial activity as
training becomes widespread in these populations.
A different pattern is seen in innovation-driven
countries (Figure 19), where the ratio increases—as
training becomes widespread—then levels off and
declines only when over a fifth of the working-age
population has been trained. This suggests that
increasing the quantity of training may generate
increasing returns to entrepreneurial activity in
innovation-led countries, up to a point. This pattern
seems to fit the GEM model, which suggests that
improving the entrepreneurship education and
training EFC would be most effective in innovation-
driven countries.
80%
67%
20%
33%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90&
100%
Non-TEA TEA
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
Trained Untrained
32
The Relationship Between Training in Starting a Business and Entrepreneurship
Table 4—Prevalence of Training in Starting a Business in the Total Working-Age Population and Among
Early-Stage Entrepreneurs
Source: GEM Adult Population Survey 2008
COUNTRY
PERCENTAGE TRAINED
INDIVIDUALS AGED 18-64
PERCENTAGE TRAINED NASCENT AND NEW
ENTREPRENEURS
RATIO OF TRAINED ENTREPRENEURS TO
TRAINED INDIVIDUALS
Factor-Driven
Egypt 7.6 14.0 1.8
India 13.4 23.0 1.7
Bolivia 19.1 30.8 1.6
Bosnia and Herzegovina 20.0 31.4 1.6
Ecuador 27.2 39.4 1.4
Colombia 40.1 53.5 1.3
Group Average 21.2 32.0 1.5
Ef?ciency-Driven
Turkey 6.3 15.1 2.4
Dominican Republic 7.7 15.8 2.1
Romania 8.7 16.1 1.9
Brazil 9.4 20.4 2.2
Serbia 10.2 20.8 2.0
South Africa 13.9 22.7 1.6
Mexico 16.2 24.8 1.5
Argentina 17.5 29.0 1.7
Macedonia 19.1 36.2 1.9
Jamaica 21.0 37.4 1.8
Uruguay 24.1 40.2 1.7
Hungary 24.5 40.7 1.7
Croatia 28.1 42.3 1.5
Latvia 28.3 42.4 1.5
Iran 29.1 50.4 1.7
Peru 29.6 55.0 1.9
Chile 42.6 61.1 1.4
Group Average 19.8 33.6 1.7
Innovation-Driven
Israel 12.8 17.5 1.4
Republic of Korea 13.6 21.8 1.6
Italy 16.5 28.1 1.7
Greece 17.0 30.3 1.8
Japan 17.4 31.3 1.8
France 18.1 35.0 1.9
United Kingdom 18.4 37.8 2.1
Germany 21.1 41.2 2.0
Spain 22.0 44.3 2.0
Denmark 22.6 45.0 2.0
Ireland 26.1 46.6 1.8
Iceland 26.8 51.7 1.9
Belgium 33.6 55.4 1.6
Slovenia 35.8 58.2 1.6
Finland 48.6 69.6 1.4
Group Average 23.4 40.9 1.7
33
The Relationship Between Training in Starting a Business and Entrepreneurship
Figure 17—Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population Within the
Factor-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals
Source: GEM Adult Population Survey 2008
Figure 18—Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population Within the
Ef?ciency-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals
Source: GEM Adult Population Survey 2008
Figure 19—Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population Within the
Innovation-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals
Source: GEM Adult Population Survey 2008
1
1.5
2
2.5
0 5 10 15 20 25 30 35 40 45
Percentage of Trained Individuals in the Adult Population (18-64 Years)
R
a
t
i
o
n
o
f
P
e
r
c
e
n
t
a
g
e
o
f
T
r
a
i
n
e
d
E
n
t
r
e
p
r
e
n
e
u
r
s
t
o
T
r
a
i
n
e
d
I
n
d
i
v
i
d
u
a
l
s
1
1.5
2
2.5
0 5 10 15 20 25 30 35 40 45
Percentage of Trained Individuals in the Adult Population (18-64 Years)
R
a
t
i
o
o
f
P
e
r
c
e
n
t
a
g
e
o
f
T
r
a
i
n
e
d
E
n
t
r
e
p
r
e
n
e
u
r
s
t
o
T
r
a
i
n
e
d
I
n
d
i
v
i
d
u
a
l
s
1
1.5
2
2.5
0 10 20 30 40 50 60
Percentage of Trained Individuals in the Adult Population (18-64 Years)
R
a
t
i
o
o
f
T
r
a
i
n
e
d
E
n
t
r
e
p
r
e
n
e
u
r
s
t
o
T
r
a
i
n
e
d
I
n
d
i
v
i
d
u
a
l
s
34
The Relationship Between Training in Starting a Business and Entrepreneurship
5.3 GAIN FROM TRAINING: GEM’S
CORE MEASURE OF THE EFFECT OF
TRAINING IN STARTING A BUSINESS
The core measure of effect used in analyzing the
GEM training data is “gain from training.” The gain
from training is a numerical measure that estimates
effect while controlling for issues that have hampered
previous studies in this area (noted in Section 5.1).
To address the self-selection problem, GEM compares
the effect of having had compulsory training versus
not having had any training on entrepreneurial
awareness, attitudes (such as skills perception,
opportunity perception or fear of failure), intention
to start a business and early-stage entrepreneurial
activity, controlling for the demographic background
of an individual. Large random samples of the
working-age population provide natural controls.
Gain from training is a country-based measure that
can be interpreted at a group or individual level. First,
it can be thought of as the increase in the proportion
of people in the country who have a characteristic,
such as a particular attitude, because of compulsory
training (but not voluntary training) in starting a
business, controlling for demographic differences (age
group, gender, education and working status). Thus, a
gain of two would mean the following: If two samples
of people were taken—differing in that one group
had received only compulsory training in starting a
business and the other had not—one would find that
twice as many people in the compulsory training
group would have a particular attitude, compared to
people in the other group.
Second, it can be thought of as the increase in the
odds that individuals with a given set of demographic
characteristics will have a particular entrepreneurial
orientation if they have ever taken compulsory
training (but not voluntary training) versus
individuals with identical demographic characteristics
but without such training. As an example, a gain of
two would indicate that individuals’ chances of having
a particular orientation are doubled if they have taken
compulsory training.
Table 5 reports the gain from training in TEA rates for
each country for which sufficient data were available.
Tables 13 and 14 in the Appendix display country
estimates of gain from training in starting a business,
grouped by level of economic development and by
principal global region. The estimates of gain are for
raising awareness of new business entrepreneurs,
improving three different entrepreneurial attitudes
(opportunity perception, start-up skills self-perception
and fear of failure), increasing intent to start a
business within the next three years and increasing
early-stage entrepreneurial activity. For each country,
the gain from training and level of significance (none,
low, moderate or high) are reported.
Since compulsory training is relatively rare in many
countries, it is possible that non-significant results are
due to the small sample size. Therefore, the figures
provided display economic group averages (Figures
20 and 21) and geographical global region averages
(Figures 22 and 23). For each country group, the
figures report the average gain (Figures 20 and 22)
and percentage of countries in which the significance
level of the gain from training is at least moderate
(p
With this particular detailed outline resolve global entrepreneurship monitor special report alicia coduras a global perspective.
GLOBAL ENTREPRENEURSHIP MONITOR SPECIAL REPORT:
ALI CI A CODURAS MARTÍ NEZ, JONATHAN LEVI E, DONNA J. KELLEY,
RÖGNVALDUR J. SÆMUNDSSON AND THOMAS SCHØTT
A Global Perspective on Entrepreneurship Education and Training
Gl obal Ent r epr eneur shi p Moni t or
Speci al Repor t
A Global Perspective on Entrepreneurship
Education and Training
Alicia Coduras Martínez, Jonathan Levie,
Donna J. Kelley, Rögnvaldur J. Sæmundsson
and Thomas Schøtt
Acknowledgements
This Special GEM Report on Entrepreneurship Education and
Training is the outcome of nine months of collaboration between
the authors, all of whom are members of different national GEM
teams. It would not have been possible without the efforts of each
participating national team that gathered data on this special
topic in 2008, and the authors wish to thank these national
teams and their sponsors, all of whom are listed in the Appendix.
Thanks are also due to the core administrative GEM team,
including Marcia Cole at Babson College and Chris Aylett
at London Business School. GEM’s Research Director, Dr.
Niels Bosma, has provided constructive criticism and advice
throughout this period.
Dr. Thomas Schøtt would like to thank his collaborators in
GEM’s Social Network Group, Sung-sik Bahn (Republic of
Korea), Paulo Alberto Bastos Jr. (Brazil), Nezameddin Faghih
(Iran) and Olga Rastrigina (Latvia), and recognize their
contribution as co-authors of the part of the Report devoted to
this topic.
© 2010 by Alicia Coduras Martínez, Jonathan Levie, Donna J. Kelley,
Rögnvaldur J. Sæmundsson, Thomas Schøtt and the Global Entrepreneurship
Research Association (GERA).
2
Table of Contents
EXECUTIVE SUMMARY 5
THE GEM RESEARCH PROGRAM 7
GLOSSARY 8
1 INTRODUCTION 9
2 CURRENT ISSUES IN ENTREPRENEURSHIP EDUCATION AND TRAINING 11
2.1 The Nature of Entrepreneurship Education and Training 11
2.2 Entrepreneurship Education and Training and Economic Development 12
2.3 Does Entrepreneurship Education and Training Make a Difference? 14
3 THE STATE OF ENTREPRENEURSHIP EDUCATION AND TRAINING: EXPERT OPINIONS 16
3.1 The Level and Quality of Entrepreneurship Education and Training as Perceived by National Experts 16
3.2 Entrepreneurs’ Need for Assistance and the Adequacy of Training Provision Outside the
Formal Education System 18
4 PREVALENCE AND SOURCES OF TRAINING IN STARTING A BUSINESS 20
4.1 Prevalence Rates of Trained Individuals in the Working-Age Population 20
4.2 Sources of Training in Starting a Business 23
4.3 Demographics of Trained Individuals 27
5 THE RELATIONSHIP BETWEEN TRAINING IN STARTING A BUSINESS AND
ENTREPRENEURSHIP 30
5.1 Issues in Measuring the Effect of Training on Entrepreneurial Behavior 30
5.2 Training in Starting a Business and Involvement in Entrepreneurial Activity 30
5.3 Gain from Training: GEM’s Core Measure of the Effect of Training in Starting a Business 34
6 THE USE OF ADVISORS BY ENTREPRENEURS 39
6.1 Types of Advisors 39
6.2 Use of Advisors by Trained and Untrained Entrepreneurs 41
7 CONCLUSIONS AND IMPLICATIONS FOR POLICY, EDUCATORS AND PRACTICE 43
7.1 Conclusions 43
7.2 Implications for Policy, Educators and Practice 43
7.3 Suggestions for Further Research 44
APPENDIX 45
REFERENCES 51
GEM NATIONAL TEAMS 2008 54
ABOUT THE AUTHORS 60
GEM SPONSORS AND CONTACTS 61
SAMPLE CHARACTERISTICS 62
ENDNOTES 63
3
Table of Contents
LIST OF TABLES
Table 1 GEM Countries Participating in the 2008 Education and Training Special Topic Focus, Grouped by Level of Economic
Development 13
Table 2 Prevalence of Formal Training, by Country and Economic Group, Ordered by Prevalence of School Training 25
Table 3 Prevalence of Informal Start-Up Training, by Country and Economic Group 26
Table 4 Prevalence of Training in Starting a Business in the Total Working-Age and Among Early-Stage Entrepreneurial Population 32
Table 5 Gain from Training in Early-Stage Entrepreneurial Activity (TEA) for 37 Countries, by Country and Economic Group,
Ordered by Increasing Gain in TEA Rate from Training 35
Table 6 Percentage of Advisor Type Networks That Include a Particular Advisor Type 40
Table 7 Summary Statistics on Advisor Types Used by Entrepreneurs in Iran, Brazil, Latvia, Republic of Korea and Denmark 41
Table 8 Average Number of Advisor Types per Sphere of In?uence Identi?ed by Trained and Untrained Entrepreneurs,
by Country 41
Table 9 Average Number of Advisor Types Identi?ed by Trained and Untrained Entrepreneurs, by Country 42
Table 10 Average Ratings by National Experts on the State of In-School and Non-School Entrepreneurship Education
and Training in a Sample of GEM Nations, 2005–2008 45
Table 11 Prevalence of Start-Up Training (In-School and Non-School), by Country and Economic Group (Percentage of
Working-Age Population) 46
Table 12 Prevalence of Start-Up Training (Formal and Informal), by Country and Economic Group (Percentage of
Working-Age Population) 47
Table 13 Gain from Training in Entrepreneurial Awareness, Attitudes, Intention and Activity for 38 Countries, by Country and
Economic Group, Ordered by Increasing Gain from Training in Activity 48
Table 14 Gain from Training in Entrepreneurial Awareness, Attitudes, Intention and Activity for 31 Countries, by Country
and Global Region, Ordered by Increasing Gain from Training in Activity 49
Table 15 Linear Multiple Regression Showing Effect of Compulsory Training Versus No Training in Starting a Business on the
Variety of Entrepreneurs’ Advisor Types, Controlling for Education Level, Gender, Age, Stage of Business and Country 50
LIST OF FIGURES
Figure 1 The GEM Theoretical Model 14
Figure 2 Average Ratings by National Experts on the Level of Entrepreneurial Framework Conditions in Their Countries,
by Economic Group 17
Figure 3 Average Ratings by National Experts on the State of In-School Entrepreneurship Education and Training in a Sample
of GEM Nations for the Years 2005–2008 17
Figure 4 Average Ratings by National Expert on the State of Non-School Entrepreneurship Education and Training in a Sample
of GEM Nations for the Years 2005–2008 18
Figure 5 Experts’ Average Evaluations in 30 GEM Countries Regarding Entrepreneurs’ Need for External Assistance with
Planning Prior to Start-Up and the Suf?ciency of Entrepreneurship Education and Training Provided by Public
and/or Private Agencies, by Country 19
Figure 6 Average Level of Training in Starting a Business in the Adult Working-Age Population (18–64 Years) Across
All 38 Participating Countries 20
Figure 7 Percentage of the Adult Working-Age Population (18–64 Years) That Received Training in Starting a Business,
by Country, Ordered by Increasing Prevalence 21
Figure 8 Percentage of the Adult Working-Age Population (18–64 Years) That Received Start-Up Training, by Country
and Economic Group, Ordered by GDP 21
Figure 9 Levels of Voluntary and Compulsory Start-Up Training, by Country and Economic Group, Ordered by Level
of Voluntary Training 22
Figure 10 Prevalence of In-School and Non-School Training, by Economic Group, Ordered by Frequency of In-School Only Training 24
Figure 11 Prevalence of Formal and Informal Start-Up Training, by Country and Economic Group, Ordered by Frequency
of Formal Only Training 24
Figure 12 Age Distribution of Trained and Untrained Individuals, by Economic Group 27
Figure 13 Gender Distribution of Trained and Untrained Individuals, by Economic Group 28
Figure 14 Education Distribution of Trained and Untrained Individuals, by Economic Group 29
4
Figure 15 Income Distribution of Trained and Untrained Individuals, by Economic Group 29
Figure 16 Proportion of Trained vs. Untrained Individuals Involved in Early-Stage Entrepreneurial Activity (TEA), and
Those Not Involved (Non-TEA) 31
Figure 17 Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population
Within the Factor-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals 33
Figure 18 Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population Within the
Ef?ciency-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals 33
Figure 19 Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population Within the
Innovation-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals 33
Figure 20 Gain from Training in Entrepreneurial Awareness, Attitudes, Intention and Activity for 38 Countries, by Economic Group 35
Figure 21 Proportion of Countries in Which the Gain from Training Is Statistically Signi?cant, by Economic Group and Type of
Entrepreneurial Orientation 36
Figure 22 Gain from Training in Entrepreneurial Awareness, Attitudes, Intention and Activity for 32 Countries, by Global Region 37
Figure 23 Proportion of Countries in Which the Gain from Training is Statistically Signi?cant, by Global Region and
Type of Entrepreneurial Orientation 38
Table of Contents
5
Executive Summary
In 2008 the Global Entrepreneurship Monitor set
out to investigate the prevalence and sources of
entrepreneurship education and training, and the
effect of this training on starting a business. Thirty-
eight national teams participated in this study, adding
specialized questions to the standard GEM Adult
Populations Surveys (APS). In addition, 30 countries
added questions to the National Expert Surveys
(NES).
This report expands on the eight-page education and
training section found on pages 41-48 of the Global
Entrepreneurship Monitor 2008 Executive Report.
After a brief literature review, we present expert
opinions on the current state of entrepreneurship
education and training in 30 countries. The report
then details the level and sources of training received
by the adult population (18-64) in the 38 countries
surveyed by GEM. By examining data from the
APS, GEM is able to develop profiles of individuals
most and least likely to have received training.
Additionally, we present new information on the
effects of training on an individual’s entrepreneurial
awareness, attitudes, intentions and activity in each of
the participating countries. Then, five GEM countries
provide insights about the types of advisors used by
entrepreneurs. The report concludes with possible
implications of these new findings and suggests areas
for further research.
To facilitate analysis, participating nations are
classified into three groups with similar levels of
economic development, from the lowest level “factor-
driven” group, to the middle level “efficiency-driven”
group, and then to the highest level “innovation-
driven” group. The 38 participating countries are
not a random sample of countries in these groups, so
readers should interpret the results with this in mind.
In Chapter 2, a review of the literature reveals that
entrepreneurship education and training has grown
rapidly in recent decades. However, little comparative
data exists on how many people receive training
in business start-up activity, whether some people
are more likely to receive training than others and
whether the training makes any difference in their
subsequent entrepreneurial behavior.
Chapter 3 shows that since 2000, GEM National
Expert Surveys have gathered data that consistently
demonstrates experts’ dissatisfaction with aspects
of entrepreneurship education and training in
their countries. They tend to rate the adequacy
of entrepreneurship education and training in
primary and secondary schools lower than any
other entrepreneurship framework condition. In
most participating countries in 2008, experts agreed
that entrepreneurs needed external assistance
with starting businesses. Satisfaction with external
assistance tended to vary by level of economic
development. In Germany, Finland, Republic of
Korea, Ireland, Spain and the United States, experts
tended to agree that public and/or private agencies
outside the formal education system provide adequate
entrepreneurship education and training. Experts in
other participating GEM countries were less positive.
Chapter 4 shows the proportion of working-age
individuals who have received training in starting a
business in 38 countries. More than one-fifth of the
working-age population (21%) across these countries
has received training in starting a business. Country-
level prevalence rates vary considerably, even between
countries with similar levels of economic development.
Most countries show a level between 10% and 30%.
For most countries, though not all, more than half
of the trained population engaged in this training
voluntarily, rather than being required to do so. A
large majority of those who received start-up training
did so as a part of their formal education in school,
college or university. On average, around 80% of
those who have received training have done so during
their formal education. This high proportion of
formal training reveals the important role the formal
education system plays in entrepreneurship training.
In most countries, training at school is more prevalent
than training at the tertiary level.
Slightly more than 60% of those who have received
training, on average, have received informal training,
either exclusively or in addition to formal training.
This high level of informal training suggests that,
despite having obtained formal entrepreneurship
education or training, people may also want focused
“not for credit, but for real” training. The most
frequent source of informal training in most of the
countries is self-study, followed by informal university
programs and courses offered by business associations.
The final section of Chapter 4 demonstrates
demographic differences between trained and
untrained individuals. Start-up training rates vary
according to an individual’s age, gender, education
and income. In all three economic groups, younger
individuals are more likely to have received training
in starting a business. This probably reflects the
recent rise in entrepreneurship training offered in
the formal education system. People from wealthier
households and better-educated people are also more
likely to have received training. Such individuals
may have more opportunities to avail of training.
In most countries, men are more likely than women
to have volunteered for training. In less well-
developed countries, women tend to have had fewer
opportunities for compulsory training than men.
6
Executive Summary
Chapter 5 analyzes the impact of training on an
individual’s propensity for entrepreneurial attitudes
or behavior. GEM data are ideally suited to address
methodological issues that previous studies have
found difficult to overcome, including self-selection
into training, time delay in demonstrable effects,
lack of control groups and the role of an individual’s
background and context. By comparing those who
had only compulsory training to those who had
no training, and controlling for an individual’s
demographic background and country-specific
conditions, a “gain from training” was demonstrated
using multivariate statistical analysis. This gain from
training varies by context. Training is most effective
in contexts with favorable institutional environments,
where the training-induced positive skills, perceptions
and intentions can be translated into action. Training
appears to be particularly effective in western
European countries with low rates of early-stage
entrepreneurial activity, such as Belgium, France,
Germany and the United Kingdom, where significant
gains equal to a doubling of the odds of engaging in
early-stage entrepreneurial activity were recorded
among trained individuals.
Chapter 6 presents a study of the links between
training and the use of advisors in five GEM countries
with highly different country contexts. While in four
of these countries (Brazil, Latvia, Republic of Korea
and Denmark) trained individuals tended to have
more advisors, this was not true in Iran. The type
of advisor chosen (from five spheres of influence:
private, job, experience, professional and market) also
varied. Advisors who were family and friends were
more common advisors in Brazil and Iran. Advisors
from other spheres were more prominent in Republic
of Korea and Denmark. Latvia took an intermediate
position.
Chapter 7 makes several conclusions: The amount and
type of training varies widely across countries, and
this is not necessarily linked to a country’s state of
economic development. However, the impact of such
training does vary according to the level of economic
development. It appears to have greatest effect on
early-stage entrepreneurial activity in countries
with favorable institutional contexts. This finding
fits the GEM model, which predicts that training in
starting a business is most effective and relevant in
innovation-driven countries. It supports the argument
that factor-driven countries in particular should not
invest large-scale resources in training programs
if basic framework conditions are not adequate. An
alternative explanation for the findings is that the
quality of training may vary by country context, and
that less-developed economies have lower quality
forms of training. There is some support for this
view from the collective opinions of experts in these
countries. It is likely that both explanations are valid,
but further research needs to be done on how forms of
training vary by country and which forms of training
are most effective.
7
The GEM Research Program
Since its first comparative national surveys in 1999,
the Global Entrepreneurship Monitor (GEM) research
consortium has contributed toward building and
enhancing global understanding about the attitudes,
activity and aspirations of entrepreneurs and
environmental factors that help them flourish. By
improving knowledge about entrepreneurship, GEM
helps governments, businesses and educators around
the world design policies, develop programs and
provide assistance to help enterprising individuals
generate new jobs and wealth in an increasingly
global business environment.
The GEM project focuses on three main objectives:
• To measure the scale and scope of entrepreneurial
activity and analyze how this differs across
countries
• To uncover factors determining national levels of
entrepreneurial activity
• To identify policies that may enhance the national
level of entrepreneurial activity
The Global Entrepreneurship Monitor was conceived
in 1997 by Michael Hay of London Business School
(LBS) and Bill Bygrave of Babson College. LBS and
Babson funded a prototype study that year. Ten
national teams conducted the first GEM Global
study in 1999 with Paul Reynolds as the Principal
Investigator. Since then, more than 64 national teams
have participated in GEM through a consortium
headed by the Global Entrepreneurship Research
Association (GERA), which is a not-for-profit
organization governed by representatives of the
national teams, the two founding institutions and
sponsoring institutions. Led by a central coordination
team, this consortium administers an annual Adult
Population Survey (APS) of at least 2,000 individuals
aged between 18 and 64 in each participating country.
In addition, GEM national teams conduct National
Expert Surveys (NES) to obtain insights about
particular factors impacting entrepreneurship in each
country.
GEM aims to be the leading source of information and
analysis about entrepreneurship across the globe. The
study employs an original methodology that has been
continually refined over ten years. Data collection
follows strict quality control procedures. This
strong methodology, among other distinct features,
contributes to the project’s uniqueness and value for
those seeking to benchmark and make comparisons
about entrepreneurship among nations.
Each economy participating in the GEM project
has a national academic team, which selects a
local survey vendor to conduct the APS and then
monitors the process for quality control. The GEM
central coordination team and its specialized staff
ensure that each team follows strict GEM research
standards. This ensures data quality and allows for
the harmonization of data across all participating
countries. All teams and vendors therefore adopt the
same methodology.
Quality control is similar in the NES and includes
an oversight role by the central coordination team.
National teams conduct this survey in accordance
with the specific procedures and policies established
by the GEM consortium. The NES process includes
the selection of at least 36 experts, covering nine
framework conditions that influence a nation’s
entrepreneurial environment: financial support,
government policies and programs, education and
training, R&D transfer, access to commercial and
professional infrastructure, internal market dynamics,
access to physical infrastructure and social and
cultural norms. Interviews are conducted with at least
four experts in each of the nine areas.
GEM publishes annual global reports and GEM
national teams publish individual country-level
reports. In addition, GEM publishes special reports
on topics including women in entrepreneurship,
high-growth ventures and entrepreneurial finance.
This special report on entrepreneurship education
and training draws on additional questions
developed around this topic for the GEM 2008 APS
questionnaire. These questions were approved by the
GERA annual assembly and reviewed by the central
coordination team.
8
Entrepreneurship education is the building of knowledge and skills either “about” or “for the purpose of”
entrepreneurship generally, as part of recognized education programs at primary, secondary or tertiary-level
educational institutions.
Entrepreneurship training is the building of knowledge and skills in preparation for starting a business.
In-school training specifically refers to training conducted within primary and secondary education programs
in any nation.
Non-school training comprises any courses offered outside primary and secondary education programs,
provided by any type of institution: universities, business schools, public institutions, chambers of commerce,
trade unions, employers or any other entity.
Compulsory training is defined as programs either in school or after school that an individual has taken but
did not freely elect to take; it is training required to complete or graduate from a particular program or to obtain
some other benefit, such as a grant or official business registration.
Voluntary training is training undertaken by choice.
Formal training includes any course that is part of an official education program, whether compulsory or
voluntary. This includes primary or secondary education and tertiary-level certificate, diploma or degree
programs.
Informal training operates outside formal programs, for example, non-credit bearing courses at a university,
local business organization or a government agency.
Gain from training is the increased odds of engaging in entrepreneurial behavior due to training, rather than
a consequence of some prior desire to behave entrepreneurially.
In the 2008 GEM Executive Report, GEM countries were classified into three different phases of economic
development, following the framework employed by the Global Competitiveness Report (Porter and Schwab,
2008; Porter, Sachs and McArthur, 2002):
Factor-driven countries tend to have economies that are primarily extractive in nature, and their
governments should focus on basic requirements such as primary education and basic governance.
Efficiency-driven countries are—or should devote more attention to—driving down labor costs as basic
requirements are met.
Innovation-driven countries are wealthier economies that are becoming less price-competitive and need to
focus on providing the conditions that allow opportunity-based entrepreneurship and innovation to flourish.
APS is the GEM Adult Population Survey: a random sample of the working-age population in a country.
NES is the GEM National Expert Survey: a selected sample of individuals who are deemed expert in at least
one Entrepreneurial Framework Condition (EFC) or aspect of the environment for entrepreneurship. GEM
recognizes nine major EFCs, of which three, including entrepreneurship education and training, have two major
components. Typically, in each country’s NES, at least four experts are identified per EFC, of which one is an
entrepreneur, two are providers of that EFC and one is an expert observer.
Glossary
9
In the closing decades of the 20th century,
entrepreneurship gained increased recognition
among economists as a significant driver of
improvements in societal welfare. Across the globe,
governments have acknowledged the importance
of their roles in motivating individuals, businesses
and related stakeholders to perceive and develop
new opportunities that can promote positive
change and create economic growth in their
societies (Blenker, Dreisler and Kjeldsen, 2008).
This entrepreneurial spirit is now seen as the
main source of innovations in nearly all industries,
leading to the birth of new enterprises and the
growth and renewal of established organizations.
The impact of entrepreneurship education and
training on individual attitudes, actions and
ambitions is of particular interest to policy makers,
educators and practitioners. It is generally believed
that individuals who perceive they have the skills
and knowledge to start a business are more likely to
do so. However, as the next chapter demonstrates,
GEM expert surveys in most countries suggest
that entrepreneurship education and training,
both in school and outside of school, is inadequate.
Recognizing this concern among hundreds of
experts across the globe, the GEM consortium
chose education and training as its special topic for
2008. Of the 43 countries participating in the 2008
survey, 38 added questions about entrepreneurship
education and training to their Adult Population
Surveys and 30 countries added questions to their
National Expert Surveys. This report expands on
the initial findings from these surveys reported
in the GEM 2008 Executive Report (Bosma et al.,
2008).
The importance of entrepreneurship education and
training was stressed in a recent (2009) report by
the Global Education Initiative (GEI) of the World
Economic Forum (WEF):
“…while education is one of the most important
foundations for economic development,
entrepreneurship is a major driver of innovation
and economic growth. Entrepreneurship education
plays an essential role in shaping attitudes, skills
and culture–from the primary level up. ...We believe
entrepreneurial skills, attitudes and behaviors can
be learned, and that exposure to entrepreneurship
education throughout an individual’s lifelong
learning path, starting from youth and continuing
through adulthood into higher education–as well
as reaching out to those economically or socially
excluded–is imperative.” (p.7–8)
Many studies have addressed the supply side
of entrepreneurship education and training, for
example: teacher and student evaluations of
program effectiveness (Hegarty, 2006; Cheung,
2008), national and regional reviews of the
availability and nature of programs (Levie, 1999;
Autio, 2007) and assessments of the value of
entrepreneurship education in general (Shinnar,
Pruett and Toney, 2008). The WEF report
(WEF, 2009) cited above describes a range of
entrepreneurship programs across the world—
including government, NGO and multinational
initiatives—and at a range of education levels
from primary schools to universities, as well as
non-school initiatives. While these studies provide
useful information on what education and training
is offered, they do not tell us who takes this
training and what trained individuals gain from
their training.
GEM is in a unique position to provide information
on the frequency and impact of entrepreneurship
education and training among different countries.
GEM polls individuals, rather than firms, so it
is well placed for exploring entrepreneurship
education and training among people. Because
GEM does not rely on business registrations, it
can reveal insights about individuals that have
engaged in both formal (registered) and informal
(unregistered) entrepreneurial activity. GEM can
also capture the impact of training in starting a
business on entrepreneurial awareness, attitudes,
intentions and activity.
In addition, while many studies have been
conducted in one or a few countries, this report
analyzes APS data on training in starting a
business from 38 countries spanning a range
of economic development levels. The data is
harmonized to allow for comparisons among these
countries. This is supplemented by NES data
from 31 countries on the insights and opinions
of entrepreneurs, policy makers, debt and equity
providers and other experts on the state of
entrepreneurship education and training in their
countries.
The 2008 APS survey asked respondents if they had
ever taken part in training in starting a business
in school (in-school training) or outside of school
(non-school training). For non-school training,
survey interviewers asked respondents to identify
the main provider of the program. They also asked
respondents whether their training was voluntarily
or compulsory (for example, a required part of a
school or government program). This distinction
enables us to identify outcomes that could not be
due to self-selection. In other words, it permits us to
measure more accurately the “gain from training,”
or increased odds of engaging in entrepreneurial
behavior that is due to the training itself rather
than a consequence of some prior desire to behave
entrepreneurially.
1 Introduction
10
Introduction
Readers should be aware of several data limitations,
which include the following:
• The surveyed population spans a broad age range,
from 18 to 64 years. The age distribution of those
receiving training in a country may be a function
of the nation’s age profile and should be considered
when making comparisons between countries.
• Cultural factors and economic development level,
as well as specific government policies, can affect
the nature and impact of education and training
generally.
• The sources of training for each respondent are not
a guide to the type or the quality of training received
by individual respondents.
• The countries in the database are not necessarily
representative of the economic groups from which
they are drawn. Thus, while this is perhaps the
largest global study of both the prevalence, sources
and effect of training in starting a business and
the expert views of the state of entrepreneurship
education and training in their countries to date,
there is much more work to do.
In summary, the goals for this report are the
following:
(1) demonstrate national differences in perception by
experts of the current quality and availability of
entrepreneurship education and training in their
countries;
(2) demonstrate differences in the prevalence and
nature of entrepreneurs and non-entrepreneurs
who have received training in starting a business
across countries;
(3) demonstrate the impact of training on
entrepreneurial awareness, attitudes, intentions
and activity; and
(4) identify implications for policy makers, educators
and practitioners.
The next chapter provides an overview of
entrepreneurship education and training literature
drawn from the current literature on the subject.
11
2 Current Issues in Entrepreneurship Education and Training
2.1 THE NATURE OF
ENTREPRENEURSHIP EDUCATION
AND TRAINING
Individuals may participate in entrepreneurship
education and training at various points in their lives,
and this education and training may take different
forms. For example, all primary school pupils in
Scotland receive “enterprise education,” which is not
specifically about training in starting a business, but
about being enterprising and entrepreneurial in a
more general sense. In some universities, students
may receive education “about” entrepreneurship.
This education is not designed to provide training in
starting a business. Instead, new venture creation is
the context of an academic education, not the goal.
Some university students experience a mix of “about”
and “how-to” in entrepreneurship classes. At the other
end of the spectrum, an employer or a government
agency may offer training in starting a business to
employees about to lose their jobs.
In this report, entrepreneurship education is defined
in broad terms as the building of knowledge and
skills “about” or “for the purpose of” entrepreneurship
generally, as part of recognized education programs
at primary, secondary or tertiary-level educational
institutions. Entrepreneurship training is defined as
the building of knowledge and skills in preparation
for starting a business. Thus, the purpose of
entrepreneurship training is very specific, unlike the
purpose of entrepreneurship education, which can be
much broader.
Complicating the picture further, individuals may
receive education about/for entrepreneurship and/
or training in starting businesses in primary and
secondary school, during college or university studies.
These courses may be part of a formal education
program that grants certificates or degrees, or they
may involve non-credit courses. Other informal
training programs operating outside the mainstream
education system include courses, seminars or
other types of training offered by local business
organizations, employers or a government agency.
Some argue that the earlier people are exposed to
entrepreneurship, the more likely they will become
entrepreneurs in some form during their lives
(WEF, 2009). Evidence of this can be seen in the
higher prevalence of entrepreneurial activity among
individuals whose parents have been self-employed or
running their own businesses (Henley, 2007). It could
be surmised that children of entrepreneurs develop
particular perceptions and skills from observing their
parents and participating in family business activities.
Perhaps some education and training programs can
substitute for this learning.
This raises issues about which types of
entrepreneurship education and training approaches
work best. It may depend on the educational context,
for example: whether one is learning in primary or
secondary (grade) school, colleges or universities
or non-school training programs. Most authors
agree, however, that experiential learning, or
“learning by doing,” is more effective for developing
entrepreneurial skills and attitudes than traditional
methods like lectures (European Commission, 2008;
Walter and Dohse, 2009). Several studies carried out
in innovation-driven countries, including Singapore
(Tan and Ng, 2006), Sweden (Rasmussen and
Sørheim, 2005), and the United Kingdom (Raffo et
al., 2002) show that entrepreneurs learn best with an
experiential learning approach.
Another consideration is about what to teach. A
survey of entrepreneurs by Sexton (1997) revealed
the ten most desired topics for achieving and
managing fast growth. These were primarily business
concerns, such as selling, financing growth, managing
cash flow and hiring and training employees. Yet
entrepreneurship education and training may need to
be much broader. It can impact attitudes, help people
recognize opportunities and think creatively, and
enable them to build leadership skills and confidence
(Stevenson and Gumpert, 1985). Recognizing this,
a recent European Commission Report (2008)
suggested that the goal of entrepreneurship education
should be to promote creativity, innovation and
self-employment. Entrepreneurship education and
training therefore entails more than the development
of particular business skills. It can influence an
individual’s motivation to strive for something that
might otherwise seem impossible or too risky. In
short, it can create positive perceptions and desire
among individuals to start businesses.
A further issue is where to teach entrepreneurship.
Entrepreneurship is inherently multidisciplinary
in nature. While entrepreneurship education and
training requires the teaching of numerous business
skills, non-business students may benefit from this
training. The European Commission (2008) questions
whether business schools are the most appropriate
place to teach entrepreneurship, given its view that
the most innovative and feasible ideas are likely to
come from the technical and creative disciplines.
Similarly, Katz (2003) declared that growth in
entrepreneurship education and training is likely to
come from outside business schools.
The requirements of educating “for” entrepreneurship
call into question the usefulness of traditional
education practices, implying a need for a mindset
shift from mainstream education and training
routines (WEF, 2009). New teaching pedagogies and
cross-disciplinary content present challenges for
educators and institutions. Sorgman and Parkison
(2008) state that many schoolteachers are unprepared
12
Current Issues in Entrepreneurship Education and Training
for these new challenges. As the WEF Global
Education Initiative report (WEF, 2009) indicates,
changing existing school systems will take time.
Multidisciplinary business content and experiential
approaches will need to be integrated into the basic
training that teachers receive. They conclude that
“training the trainers” may be as great an effort as
developing the curriculum.
On the supply side, university PhD programs are
not providing enough faculty to meet the demand for
entrepreneurship education (Katz, 2003; EC, 2008).
Many tertiary institutions, where their statutes
permit, rely on “adjunct faculty,” business people who
teach entrepreneurship part-time. Current faculty,
locked into narrow disciplinary structures, may not
adapt well to the requirements of entrepreneurship
education (Janssen, Eeckhout and Gailly, 2005).
Additionally, internal funding systems in multi-
faculty institutions may hinder the availability of
entrepreneurship education beyond business schools.
Consequently, the development of effective programs
for entrepreneurship likely requires more than
adding new courses. Institutional-level considerations
may therefore play a key role in the development of
entrepreneurship education in an economy.
Educators and policy makers may need to consider
how to broaden access and increase the scale and
scope of entrepreneurship training, beyond university
locations and other on-site programs. This may
require greater use of technology. Internet-based
learning, for example, may extend a program’s
geographic reach or satisfy high demand (Solomon,
Duffy and Tarabishy, 2002; Hegarty, 2006).
Creative computer applications may attract and
hold the interest of some people, influencing their
attitudes toward—and their understanding of—
entrepreneurship.
While the requirements and challenges of
entrepreneurship education and training are
numerous, there are also many opportunities for
influencing perceptions and developing the skills and
ambitions of current and potential entrepreneurs.
This report addresses fundamental questions about
the differences in entrepreneurship training among
different economies around the world, and it estimates
the impact of training in starting a business on
entrepreneurial awareness, attitudes, intentions
and activity. The remainder of this chapter provides
background on three main economic groupings of
countries and reviews current understanding about
the impact of entrepreneurship training.
2.2 ENTREPRENEURSHIP EDUCATION
AND TRAINING AND ECONOMIC
DEVELOPMENT
In GEM research, countries are classified into three
groups based on their levels of economic development.
The GEM theoretical model shows three sets of
economic framework conditions: those that constitute
the basic requirements for economic activity, those
that enhance efficiency, and those that promote
entrepreneurship and innovation. As countries
progress economically, there is a shift in the relative
importance of these three sets of economic framework
conditions. This method of classifying economies has
been used in the Global Competitiveness Reports for
some time (Porter, Sachs and McArthur, 2002; Porter
and Schwab, 2008).
In “factor-driven” countries with mainly extractive
type economic activity, Porter and Schwab argue that
the focus of government should be on enhancing the
basic requirements of economic development, such as
stable government, basic infrastructure and primary
health care and education. With the exception of well-
managed countries that are especially well endowed
with natural resources, such as Saudi Arabia, most
entrepreneurial activity in factor-driven countries
may be necessity-driven, and government attention
is best focused on providing a basic foundation for
enabling this activity, rather than, for example,
providing sophisticated training in opportunity-driven
entrepreneurship.
As an economy develops, and as the employment
of relatively cheap labor becomes an increasingly
less viable source of advantage, necessity-driven
entrepreneurship declines and governments may start
to pay more attention to entrepreneurship. The most
developed nations, no longer able to depend on low
labor costs, must instead compete in ways that are
more creative. For the governments of such countries,
high quality basic factors and efficiency enhancers
are generally present at sufficient levels. The quality
and quantity of entrepreneurship and innovation then
becomes a source of national competitive advantage.
One of the primary entrepreneurial framework
conditions recognized by GEM is the nature and
level of entrepreneurship education and training.
According to the GEM model, the relative importance
of entrepreneurship education and training increases
as economies develop economically.
Table 1 shows the 38 countries participating in the
education and training special topic grouped into
factor-driven, efficiency-driven and innovation-
driven economies. Although the sample of countries
crosses many geographic regions and levels of
economic development, it is not necessarily evenly
13
representative of the world. The factor-driven
countries in the sample represent only 10% of the
factor-driven countries in the world, and half of them
were classified by the 2008 Global Competitiveness
Report as in transition to the efficiency-driven group.
The sample contains 40% of the world’s efficiency-
driven economies and 45% of the innovation-driven
economies. The United States, Canada, Australia
and New Zealand were absent from the sample of
innovation-driven countries.
The GEM Model, shown in Figure 1, illustrates
three sets of framework conditions that influence
entrepreneurship, which in turn impact
national economic growth. These three sets are
basic requirements, efficiency enhancers and
entrepreneurship and innovation. As the GEM Model
shows, entrepreneurial education and training is
represented as a specific entrepreneurial framework
condition affecting entrepreneurial attitudes,
activity and aspirations—and, as a result, economic
development.
Much has been written about entrepreneurship
education and training in innovation-driven
economies, starting primarily in the 1980s and
accelerating after the turn of the century as interest
in entrepreneurship increased and the contribution of
new businesses to the growth of a national economy
gained recognition. Entrepreneurship education,
in fact, has its roots in what are now classified as
innovation-driven countries; the first efforts to deliver
entrepreneurship courses were attributed to Shigeru
Fujii of Kobe University in Japan in 1938 (Solomon et
al., 2002) and Myles Mace at Harvard Business School
in 1947 (Katz, 2003).
Current Issues in Entrepreneurship Education and Training
Table 1—GEM Countries Participating in the 2008 Education and Training Special Topic Focus,
Grouped by Level of Economic Development
FACTOR-DRIVEN EFFICIENCY-DRIVEN INNOVATION-DRIVEN
Bolivia Argentina Belgium
Bosnia and Herzegovina (+) Brazil Denmark
Colombia (+) Chile Finland
Ecuador (+) Croatia (+) France
Egypt Dominican Republic Germany
India Hungary (+) Greece
Iran Iceland
Jamaica Ireland
Latvia Israel
Macedonia Italy
Mexico Japan
Peru Republic of Korea
Romania Slovenia
Serbia Spain
South Africa United Kingdom
Turkey
Uruguay
Note: The (+) indicates economies in transition to the next level of economic development.
In the innovation-driven countries, it was commonly
thought that entrepreneurship could not be taught.
Many still believe that education and training are
not necessary for starting buisnesses. People like
Bill Gates and Steve Jobs, both dropping out after
a few years of college, made for interesting news
stories. It became apparent, however, that these did
not represent typical entrepreneurs, particularly
for businesses with knowledge-based products and
services. Many governments in innovation-driven
economies have since declared their commitment to
entrepreneurship education, identifying it as a key
priority (Kyro, 2006; Sorgman and Parkison, 2008).
In these wealthier economies, entrepreneurship
education is considered relatively established, and
attention has turned toward assessing existing
programs, sharing best practices, identifying
constraints and providing recommendations. There
have been numerous studies evaluating training,
school and university education programs in countries
such as the United Kingdom (Birley and Gibb,
1984; Gibb, 1987; Jones-Evans et al., 2000), Sweden
(Klofsten, 2000), German-speaking countries (Klandt,
2004), Australia (Jones and English, 2004) and Oman
(Khan and Almoharby, 2007)—to name a few.
14
Current Issues in Entrepreneurship Education and Training
Figure 1—The GEM Theoretical Model
Source: 2009 GEM Global Report
Social,
Cultural,
Political
Context
Basic Requirements
- Institutions
- Infrastructure
- Macroeconomic Stability
- Health and Primary
Education
New Branches,
Firm Growth
Established Firms
(Primary Economy)
National
Economic
Growth
(Jobs and
Technical
Innovation)
Efficiency Enhancers
- Higher education and
Training
- Goods Market Efficiency
- Labor Market Efficiency
- Financial Market
Sophistication
- Technological
Readiness
- Market Size
Innovation and
Entrepreneurship
- Entrepreneurial Finance
- Government Policies
- Government
Entrepreneurship
Programs
- Entrepreneurship
Education
- R&D Transfer
- Commercial, Legal
Infrastructure for
Entrepreneurship
- Internal Market
Openness
- Physical Infrastructure
for Entrepreneurship
- Cultural, Social Norms
Aspirations:
Growth
Innovation
Social Value Creation
Activity:
Early-Stage
Persistence
Exits
Entrepreneurship
From GEM
National
Expert Surveys
(NES)
From GEM
Adult Population
Surveys (APS)
From Other
Available
Sources
Attitudes:
Perceived Opportunities
Perceived Capacity
Katz (2003) declared that entrepreneurship education
has reached maturity in the United States and
that future expansion lies elsewhere. Indeed, the
field may experience its greatest growth outside
the innovation-driven countries. For example,
Li et al. (2003) reported that entrepreneurship
education has been well received in China, but is
still a relatively new practice in higher institutions.
Here, entrepreneurship education is an emerging
concept. Yet it may have a significant role to play in
transitioning entrepreneurial activity from necessity-
to opportunity-based in the efficiency-driven countries,
in addition to enhancing innovation and international
competitiveness.
In factor-driven countries, training may be offered as
part of a social or government campaign to improve
skills and create jobs: for example, Finweek reports
on a program in Namibia (Finweek, 2007). In these
poorer countries, providing a basic education to as
many people as possible is a major concern of policy
makers. Entrepreneurship education and training is
likely to take different forms than in the innovation-
driven or efficiency-driven countries. As previous GEM
reports show, in these countries entrepreneurship
rates tend to be high, but mainly necessity-based and
with low-growth aspirations.
2.3 DOES ENTREPRENEURSHIP
EDUCATION AND TRAINING MAKE A
DIFFERENCE?
While there is extensive literature on
entrepreneurship education and training, evidence
demonstrating the influence of training on
entrepreneurial activity is still lacking (Béchard and
Grégoire, 2005). Greater understanding is needed
about how programs and learning strategies help
develop skills that lead to the formation of new
ventures (Garavan and O’Cinneide, 1994). The WEF
Global Education Initiative report argued that there
is strong evidence that entrepreneurship can boost
economic growth and, in turn, alleviate poverty.
However, it did not identify studies specifically linking
entrepreneurship education to economic growth (WEF,
2009).
Can entrepreneurship education or training impact
one’s entrepreneurial orientation? Many studies have
indicated a link between entrepreneurship and both
need for achievement and internal locus of control
(a belief in one’s ability to control one’s destiny).
Hansemark (1998), for example, found that these
15
two traits were higher among enrollees in a one-year
entrepreneurship program in Sweden compared to
those not receiving training. While acknowledging
these studies, one also needs to question whether
entrepreneurship is a function of stable traits or
learned behaviors. Past research has, for the most
part, failed to identify a consistent set of personality
traits associated with entrepreneurship, other than
the two aforementioned traits. This is likely good
news for educators, policy makers and practitioners,
given that traits are generally considered inborn and
unchangeable. As such, most of the literature on the
impact of entrepreneurship education and training
is oriented toward the influence of education on the
perception of skills, attitudes and intent to start
businesses.
A recent study for the Small Business Administration
Office of Advocacy (Summit Consulting, 2009)
found that university graduates who have taken
entrepreneurship courses are more likely to select
careers in entrepreneurship, work in small businesses
and develop patented inventions or innovative
processes, services or products. Researchers
have suggested that education and training for
entrepreneurship should positively influence actions
by enhancing the skills required to start and grow a
venture (Honig, 2004; Summit Consulting, 2009). For
example, education and training can enhance one’s
cognitive ability for managing the complex process of
opportunity recognition and assessment (DeTienne
and Chandler, 2004). Classes that provide role models
and examples of the entrepreneurship process can
equip individuals with the ability to recognize, assess
and shape opportunities (Fiet, 2000).
In contrast, Gatewood (1993) saw potential negative
effects. Focusing on public sector venture assistance,
she suggested that while these programs can
improve the abilities and problem-solving approaches
of potential founders, they could discourage
entrepreneurs who are refused assistance. Moreover,
those receiving training may not start their businesses
because they may realize they do not have the right
skills or that they do not have a viable opportunity,
thus preventing learning by doing.
Perhaps the aforementioned research indicates
that training can help ensure that those businesses
actually started will be more successful. If high SME
failure rates are a consequence of a lack of training,
as Ibrahim and Soufani (2002) suggest, perhaps
training can weed out inexperienced entrepreneurs or
those with an infeasible opportunity. This, however,
places the burden on sound screening and training
practices in the early stages, when uncertainty is
highest. Even then, concepts that are screened out of
programs may result in missed opportunities, because
capable entrepreneurs may shape poor-quality ideas
into more viable ones. In addition, entrepreneurs gain
experience that creates new learning and builds skills.
This in turn raises a question about the exclusiveness
of programs: Should they be selective or encourage
broad participation? It also casts doubt on the effect
of training: Are higher success rates among selective
programs due to the pre-screening or the training
itself?
While knowledge and skills can increase the success
of a venture, these resources will not be put to use
if the inspiration to start a business is not present
in the beginning. Attitudes and intentions are
important in boosting the chance individuals will
attempt an entrepreneurial endeavor at some point
in their lives (Souitaris et al., 2007). Studies on the
influence of education and training on attitudes have
found a positive link to interest in entrepreneurship,
attitudes toward entrepreneurship and perception
of the feasibility of starting a business. Examples
include post-secondary education in Northern Ireland
(Hegarty, 2006), university students in England
(Souitaris et al., 2007) and Germany (Walter and
Dohse, 2009) and secondary school pupils enrolled
in an entrepreneurship program in Australia
(Peterman and Kennedy, 2003). However, other
studies have observed a decrease in intentions after
entrepreneurship education programs, for example, in
a Dutch school (Oosterbeek et al., 2009) and a German
university (Weber et al., 2009). Other studies show
that prior exposure to entrepreneurship and prior
intentions can change the effect of entrepreneurship
training programs (e.g., Fayolle et al., 2006).
These country-level studies provide tantalizing
glimpses of possible relationships between
entrepreneurship education and training and
subsequent behavior. However, it is not at all clear
from the literature whether people on average
experience a gain from training in terms of their
awareness of or attitudes toward entrepreneurship,
their entrepreneurial intentions or indeed their
entrepreneurial activity. The next chapter reviews
the state of entrepreneurship education and training
across the world, as seen by carefully selected experts
in each of 31 countries.
Current Issues in Entrepreneurship Education and Training
16
3.1 THE LEVEL AND QUALITY OF
ENTREPRENEURSHIP EDUCATION AND
TRAINING AS PERCEIVED BY NATIONAL
EXPERTS
GEM national teams conduct National Expert Surveys
(NES) in their countries, polling a selected sample
of individuals who are deemed expert in at least one
Entrepreneurial Framework Condition (EFC), or
aspect of the environment for entrepreneurship. The
principal EFCs recognized by GEM are: financial
support for entrepreneurs, public policy support,
bureaucracy and taxes, government programs,
entrepreneurship education and training, R&D
transfer, access to professional and commercial
infrastructure, internal market dynamics and
barriers, access to physical infrastructure and services
and, finally, cultural and social norms. Typically, four
experts are identified per EFC, of which one is an
entrepreneur, two are providers of that EFC and one
is an expert observer.
The results of this survey add insights on key
framework conditions that can impact the
entrepreneurial process in an economy. In this
chapter, the expert opinions collected by 31 national
teams are summarized. On average, each national
team interviewed 42 experts, with a minimum of 31
and a maximum of 80 experts interviewed. Only one
team interviewed fewer than 35 experts.
In each country, experts were presented with a series
of statements designed to capture their views on
a range of entrepreneurial framework conditions.
They were asked to state their level of agreement or
disagreement with each statement along a 5-point
scale, from 1 representing “strongly disagree” to
5 representing “strongly agree.” With respect to
entrepreneurship education and training, they were
asked to state their opinions on two issues: (1) the
adequacy of formal entrepreneurship education and
training provided at primary and secondary schools
and (2) the adequacy of entrepreneurship education
and training offered through a variety of sources
beyond primary and secondary schooling, such as
colleges and universities, government and professional
programs, etc.
Figure 2 shows the average unweighted ratings of
experts by economic group on these two issues in
relation to the other entrepreneurship framework
conditions measured. In each economic group,
entrepreneurship education in primary and
secondary schools received the worst evaluation by
the experts. The average economic group rating for
this EFC increases with increasing level of economic
development, reflecting a general improvement in
EFCs as countries develop economically.
Entrepreneurship education and training in schools
has received low ratings every year since expert
surveys commenced in 2000. Figure 3 shows the
results for the period 2005 to 2008 for a selection of
countries (for raw data, see Table 10 in the Appendix).
In most countries, the ratings are consistent from year
to year, even though the pool of experts changes. Two
exceptions are Spain and the United States, where
expert ratings have become more negative. Clearly,
this issue is of concern to experts.
Experts rate the level of non-school training higher
than in-school training, and it tends to rank in the
middle range of all EFCs. In absolute terms, however,
it only approaches a neutral rating on average in the
efficiency-driven economic group. This suggests that
experts in many countries feel that this EFC could be
improved. Figure 4 shows the evolution of ratings for
this EFC over the 2005 to 2008 period in a selection
of countries (see Table 10 in the Appendix for raw
data). The ratings are consistent over time in most
countries, although in Brazil the ratings appear to
have improved.
3 The State of Entrepreneurship Education and Training: Expert Opinions
17
The State of Entrepreneurship Education and Training: Expert Opinions
Figure 2—Average Ratings by National Experts on the Level of Entrepreneurial Framework Conditions in Their
Countries, by Economic Group
Source: GEM National Expert Survey 2008
Figure 3—Average Ratings by National Experts on the State of In-School Entrepreneurship Education and
Training in a Sample of GEM Nations for the Years 2005–2008
Source: GEM National Expert Survey 2005–2008
1
1.5
2
2.5
3
3.5
4
4.5
5
I
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
R
&
D
T
r
a
n
s
f
e
r
R
e
g
u
l
a
t
i
o
n
s
,
T
a
x
G
o
v
e
r
n
m
e
n
t
P
r
o
g
r
a
m
s
F
i
n
a
n
c
i
a
l
S
u
p
p
o
r
t
I
n
t
e
r
n
a
l
M
a
r
k
e
t
B
u
r
d
e
n
s
P
o
l
i
c
y
S
u
p
p
o
r
t
N
o
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
C
u
l
t
u
r
a
l
a
n
d
S
o
c
i
a
l
N
o
r
m
s
P
r
o
f
e
s
s
i
o
n
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
I
n
t
e
r
n
a
l
M
a
r
k
e
t
D
y
n
a
m
i
c
s
P
h
y
s
i
c
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
I
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
R
e
g
u
l
a
t
i
o
n
s
,
T
a
x
R
&
D
T
r
a
n
s
f
e
r
F
i
n
a
n
c
i
a
l
S
u
p
p
o
r
t
P
o
l
i
c
y
S
u
p
p
o
r
t
G
o
v
e
r
n
m
e
n
t
P
r
o
g
r
a
m
s
I
n
t
e
r
n
a
l
M
a
r
k
e
t
B
u
r
d
e
n
s
C
u
l
t
u
r
a
l
a
n
d
S
o
c
i
a
l
N
o
r
m
s
P
r
o
f
e
s
s
i
o
n
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
N
o
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
I
n
t
e
r
n
a
l
M
a
r
k
e
t
D
y
n
a
m
i
c
s
P
h
y
s
i
c
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
I
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
R
e
g
u
l
a
t
i
o
n
s
,
T
a
x
R
&
D
T
r
a
n
s
f
e
r
I
n
t
e
r
n
a
l
M
a
r
k
e
t
B
u
r
d
e
n
s
N
o
n
-
S
c
h
o
o
l
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
P
o
l
i
c
y
S
u
p
p
o
r
t
F
i
n
a
n
c
i
a
l
S
u
p
p
o
r
t
I
n
t
e
r
n
a
l
M
a
r
k
e
t
D
y
n
a
m
i
c
s
C
u
l
t
u
r
a
l
a
n
d
S
o
c
i
a
l
N
o
r
m
s
G
o
v
e
r
n
m
e
n
t
P
r
o
g
r
a
m
s
P
r
o
f
e
s
s
i
o
n
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
P
h
y
s
i
c
a
l
I
n
f
r
a
s
t
r
u
c
t
u
r
e
Factor-Driven Efficiency-Driven Innovation-Driven
Note: Framework conditions are ordered from the lowest to the highest evaluation within each economic group. The measures range from 1 = poor to 5 = excellent. Total number of countries in sample: 31.
1
2
3
4
5
B
r
a
z
i
l
I
t
a
l
y
C
h
i
l
e
G
r
e
e
c
e
S
l
o
v
e
n
i
a
I
r
e
l
a
n
d
D
e
n
m
a
r
k
S
p
a
i
n
F
i
n
l
a
n
d
N
o
r
w
a
y
U
n
i
t
e
d
S
t
a
t
e
s
2005
2006
2007
2008
18
The State of Entrepreneurship Education and Training: Expert Opinions
Figure 4—Average Ratings by National Expert on the State of Non-School Entrepreneurship Education
and Training in a Sample of GEM Nations for the Years 2005–2008
Source: GEM National Expert Survey 2005–2008
1
2
3
4
5
B
r
a
z
i
l
D
e
n
m
a
r
k
G
r
e
e
c
e
N
o
r
w
a
y
I
t
a
l
y
F
i
n
l
a
n
d
C
h
i
l
e
S
l
o
v
e
n
i
a
I
r
e
l
a
n
d
S
p
a
i
n
U
n
i
t
e
d
S
t
a
t
e
s
2005
2006
2007
2008
3.2 ENTREPRENEURS’ NEED FOR
ASSISTANCE AND THE ADEQUACY OF
TRAINING PROVISION OUTSIDE THE
FORMAL EDUCATION SYSTEM
In 2008, of the 31 countries completing the NES
surveys, 30 included two additional items. The
first item elicited expert opinions on whether
entrepreneurs in general in their country needed
external assistance in planning their businesses prior
to start-up. The second item covered the adequacy of
entrepreneurship education and training provided
by public and/or private agencies independent of the
formal education system. Figure 5 shows the average
ratings by experts on these items in each country. The
results show a perceived need for external assistance
for entrepreneurs starting businesses, with Brazil,
Iran and Mexico reporting the highest levels. Only
Finland received a neutral rating on this issue.
Figure 5 indicates that, in six economies (Germany,
Finland, Republic of Korea, Ireland, Spain and the
United States), experts believe that public and/or
private agencies provide adequate entrepreneurship
education and training outside the formal education
system. The remaining countries report low or
moderate perceptions on this factor. Only in Germany
and Finland is the level of informal education and
training rated higher than perceptions about the need
for assistance in starting businesses. For the other
countries, perceptions about the adequacy of training
offered do not match the perceived need for assistance.
The unusually positive result for Finland is
noteworthy. As Kyro (2006) reports, Finland’s
government has committed to entrepreneurship
education throughout its school system. A report from
Publications of the Ministry of Education, Finland
(2009:9) states: “The aim of the Ministry of Education
is to enhance an entrepreneurial spirit among Finns
and make entrepreneurship a more attractive career
choice.” This may have led Finnish experts to rate
their country’s assistance as sufficient. It is also
consistent with the APS survey results in the next
chapter, which show that Finland has the highest
level of entrepreneurship training among the 38
countries surveyed.
19
Figure 5—Experts’ Average Evaluations in 30 GEM Countries Regarding Entrepreneurs’ Need for External
Assistance with Planning Prior to Start-Up and the Suf?ciency of Entrepreneurship Education and Training
Provided by Public and/or Private Agencies, by Country
Source: GEM National Expert Survey 2008
The State of Entrepreneurship Education and Training: Expert Opinions
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
B
r
a
z
i
l
I
r
a
n
M
e
x
i
c
o
S
p
a
i
n
C
o
l
o
m
b
i
a
N
o
r
w
a
y
M
a
c
e
d
o
n
i
a
E
g
y
p
t
D
e
n
m
a
r
k
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
C
r
o
a
t
i
a
A
r
g
e
n
t
i
n
a
C
h
i
l
e
T
u
r
k
e
y
S
o
u
t
h
A
f
r
i
c
a
B
o
s
n
i
a
a
n
d
H
e
r
z
e
g
o
v
i
n
a
I
r
e
l
a
n
d
I
t
a
l
y
U
n
i
t
e
d
S
t
a
t
e
s
P
e
r
u
B
o
l
i
v
a
S
e
r
b
i
a
U
r
u
g
u
a
y
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
E
c
u
a
d
o
r
S
l
o
v
e
n
i
a
J
a
m
a
i
c
a
G
r
e
e
c
e
G
e
r
m
a
n
y
F
i
n
l
a
n
d
Entrepreneurs Need Assistance with Plans Prior to Start-Up Public and Private Agencies Provide Sufficient Entrepreneurship Education and Training
NOTE: 1=strongly disagree; 2=somewhat disagree; 3=neither agree nor disagree; 4=somewhat agree; 5=strongly agree
In addition to being asked to rate their agreement
with a range of items, experts were also asked to list
positive and negative aspects of the environment for
entrepreneurship and make recommendations. The
frequency with which experts mentioned an EFC
provides another guide to its relative importance.
In 2008, across 30 countries, 30% of mentions of
constraints included the state of entrepreneurship
education and training. This was the third most
frequently mentioned constraint, after financial
support and government policies. It constituted over
half of constraints mentioned in Egypt and South
Africa, compared with only 15% in Finland, 8% in
Argentina and none in Iran.
Surprisingly, entrepreneurship education and
training was the second most frequently cited EFC
in relation to positive aspects of the environment for
entrepreneurship. This suggests that while provision
across most countries may be inadequate, there are
good initiatives in many countries. On average, 25% of
mentions of positive developments or initiatives were
in the domain of this EFC. Over half of mentions of
activities that fostered entrepreneurship in the United
States described positive aspects of entrepreneurship
education and training in the country, compared with
2% in Germany, 5% in South Africa, 6% in Iran and
7% in Turkey.
Experts were asked to make recommendations to
improve the environment for entrepreneurship in their
country. On average, 49% of the recommendations
across the 30 countries were about entrepreneurship
education and training—more than any other
EFC. The exception was Iran, where only 5% of
recommendations related to this EFC. By contrast,
71% of Turkish recommendations and 68% of South
African recommendations were in this area.
In conclusion, it is clear that in most countries,
entrepreneurship experts regard the provision
of entrepreneurship education and training as
inadequate. However, in all countries at least one
expert mentioned examples of good practice in this
area.
20
4 Prevalence and Sources of Training in Starting a Business
4.1 PREVALENCE RATES OF TRAINED
INDIVIDUALS IN THE WORKING-AGE
POPULATION
This chapter provides a report on the proportion of
working-age adults who have received training in
starting a business in the adult population across
the 38 participating countries. Survey respondents
reported if they had ever received training in starting
a business, either during primary or secondary school,
or outside school. GEM compares these rates across
countries and economic groups, noting the proportions
of voluntary and compulsory training. In addition
to providing an estimate of the relative demand for
training in a country, this information is valuable
in estimating the effect of training on subsequent
entrepreneurial behavior.
Figure 6 shows the average prevalence rate of
working-age individuals who have received training
in starting a business across the 38 countries for
which data are available. In total, an average of 21%
of working-age adults in these countries have received
training in starting a business at some point in their
lives. Of those receiving training, the majority (62%)
engaged in this training voluntarily (13% of the total
working-age population). Twenty percent of trained
individuals had received only compulsory training
(4% of the working-age population), while 14% had
received both voluntary and compulsory training (3%
of the working-age population). This indicates that
training in starting a business is done mainly through
self-selection. As mentioned above, this has important
implications for the assessment of cause and effect,
discussed in Chapter 5.
Figure 6 — Average Level of Training in Starting a Business in the Adult Working-Age Population (18–64 Years)
Across All 38 Participating Countries
Source: GEM Adult Population Survey 2008
Have Not Received Training
79%
Have Received Training
21%
Voluntary Training 13%
Compulsory Training 4%
Both Types 3%
Not Classified 1%
The country average summary of training depicted
in Figure 6 needs cautious interpretation, for several
reasons. First, factor-driven countries are under-
represented in the sample. Second, country-level
prevalence rates vary widely, even among countries
with similar levels of economic development. Figure
7 presents the proportion of working-age people
who have received training in starting a business,
by country, in increasing order of prevalence. The
results show wide variation, from 6% in Turkey to
49% in Finland. Most countries, however, fall within
the range of 10% to 30%. High levels of training
were reported in five countries (Belgium, Slovenia,
Colombia, Chile and Finland), where more than 30%
of the adult population has received training. At the
low end, five countries (Turkey, Egypt, Dominican
Republic, Romania and Brazil) reported training
levels of less than 10%.
The wide variation in entrepreneurship training levels
evident in Figure 7 indicates that country-level factors
may be more important than practices or customs
in different global regions. Figure 8 shows training
levels for the three economic groups, organized by
GDP level within the groups. As this figure shows,
the uneven distribution pattern seen geographically
is also evident in economic orderings. Within groups
of countries that are at a similar stage of development
(factor-driven, efficiency-driven and innovation-
driven), there is a high level of variation, with at least
one country with high training levels in each group
(Colombia, Chile and Finland).
21
Prevalence and Sources of Training in Starting a Business
Figure 7—Percentage of the Adult Working-Age Population (18–64 Years) That Received Training in Starting a
Business, by Country, Ordered by Increasing Prevalence
Source: GEM Adult Population Survey 2008
Figure 8—Percentage of the Adult Working-Age Population (18–64 Years) That Received Start-Up Training, by
Country and Economic Group, Ordered by GDP
Source: GEM Adult Population Survey 2008
0%
10%
20%
30%
40%
50%
60%
T
u
r
k
e
y
E
g
y
p
t
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
R
o
m
a
n
i
a
B
r
a
z
i
l
S
e
r
b
i
a
I
s
r
a
e
l
I
n
d
i
a
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
S
o
u
t
h
A
f
r
i
c
a
M
e
x
i
c
o
I
t
a
l
y
G
r
e
e
c
e
J
a
p
a
n
A
r
g
e
n
t
i
n
a
F
r
a
n
c
e
U
n
i
t
e
d
K
i
n
g
d
o
m
B
o
l
i
v
i
a
M
a
c
e
d
o
n
i
a
B
o
s
n
i
a
a
n
d
H
e
r
z
e
g
o
v
i
n
a
J
a
m
a
i
c
a
G
e
r
m
a
n
y
S
p
a
i
n
D
e
n
m
a
r
k
U
r
u
g
u
a
y
H
u
n
g
a
r
y
I
r
e
l
a
n
d
I
c
e
l
a
n
d
E
c
u
a
d
o
r
C
r
o
a
t
i
a
L
a
t
v
i
a
I
r
a
n
P
e
r
u
B
e
l
g
i
u
m
S
l
o
v
e
n
i
a
C
o
l
o
m
b
i
a
C
h
i
l
e
F
i
n
l
a
n
d
P
e
r
c
e
n
t
a
g
e
o
f
t
h
e
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
I
n
d
i
a
E
g
y
p
t
B
o
l
i
v
i
a
E
c
u
a
d
o
r
B
o
s
n
i
a
a
n
d
H
e
r
z
e
g
o
v
i
n
a
C
o
l
o
m
b
i
a
G
r
o
u
p
A
v
e
r
a
g
e
T
u
r
k
e
y
P
e
r
u
M
a
c
e
d
o
n
i
a
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
J
a
m
a
i
c
a
S
e
r
b
i
a
I
r
a
n
S
o
u
t
h
A
f
r
i
c
a
U
r
u
g
u
a
y
A
r
g
e
n
t
i
n
a
B
r
a
z
i
l
R
o
m
a
n
i
a
M
e
x
i
c
o
C
h
i
l
e
C
r
o
a
t
i
a
L
a
t
v
i
a
H
u
n
g
a
r
y
G
r
o
u
p
A
v
e
r
a
g
e
I
s
r
a
e
l
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
S
l
o
v
e
n
i
a
G
r
e
e
c
e
J
a
p
a
n
I
t
a
l
y
S
p
a
i
n
U
n
i
t
e
d
K
i
n
g
d
o
m
G
e
r
m
a
n
y
F
r
a
n
c
e
B
e
l
g
i
u
m
F
i
n
l
a
n
d
I
c
e
l
a
n
d
D
e
n
m
a
r
k
I
r
e
l
a
n
d
G
r
o
u
p
A
v
e
r
a
g
e
P
e
r
c
e
n
t
a
g
e
o
f
t
h
e
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
y
e
a
r
s
)
Factor-Driven Efficency-Driven Innovation-Driven
22
Next, the level of voluntary and compulsory training is
examined. Individuals engaged in voluntary training
have, by definition, chosen to take it, perhaps relative
to other pursuits. Compulsory training, on the other
hand, represents a required activity. For example,
individuals could be required to take a course to
complete a degree or certificate program, or to satisfy
requirements relating to registering a business or
receiving assistance or funding.
Figure 9 shows the breakdown in compulsory versus
voluntary training by economic group. In factor-
driven countries, less than one-fourth of trained
individuals had received any compulsory training. In
the other two groups, between one-third and one-half
of those who received training had taken compulsory
training. This is consistent with the GEM theoretical
model, where improving basic requirements like
infrastructure, health and primary education take
greater priority in factor-driven economies. Factor-
driven countries tend to show higher levels of early-
stage entrepreneurial activity, but this is likely to be
more necessity-based and less growth-, innovation-
and international-based.
Some countries demonstrate relatively high
proportions of compulsory training. In Denmark, for
example, over 65% of those trained received both
compulsory and voluntary training, with an additional
15% receiving only compulsory training. So four-fifths
of trained individuals in Denmark were required to
take training in starting a business. In Hungary,
almost 60% of those who received training did so
only on a compulsory basis (with an additional 14%
receiving both compulsory and voluntary training).
Other countries reporting a relatively high level of
compulsory training include Jamaica, Croatia and
Latvia in the efficiency-driven group, and Iceland,
Ireland and Slovenia in the innovation-driven group.
There seems to be no relationship between early-
stage entrepreneurial activity rates and the ratio of
compulsory to voluntary training. For example, among
innovation-driven countries, Denmark and Slovenia
have low rates of early-stage entrepreneurial activity,
while Ireland and Iceland have high rates. All show
high ratios of compulsory to voluntary training.
Prevalence and Sources of Training in Starting a Business
Figure 9—Levels of Voluntary and Compulsory Start-Up Training, by Country and Economic Group, Ordered by
Level of Voluntary Training
Source: GEM Adult Population Survey 2008
0%
10%
20%
30%
40%
50%
E
g
y
p
t
I
n
d
i
a
B
o
l
i
v
i
a
B
o
s
n
i
a
a
n
d
H
e
r
z
e
g
o
v
i
n
a
E
c
u
a
d
o
r
C
o
l
o
m
b
i
a
G
r
o
u
p
A
v
e
r
a
g
e
T
u
r
k
e
y
R
o
m
a
n
i
a
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
S
e
r
b
i
a
H
u
n
g
a
r
y
S
o
u
t
h
A
f
r
i
c
a
B
r
a
z
i
l
M
e
x
i
c
o
J
a
m
a
i
c
a
A
r
g
e
n
t
i
n
a
C
r
o
a
t
i
a
L
a
t
v
i
a
M
a
c
e
d
o
n
i
a
I
r
a
n
U
r
u
g
u
a
y
P
e
r
u
C
h
i
l
e
G
r
o
u
p
A
v
e
r
a
g
e
D
e
n
m
a
r
k
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
I
s
r
a
e
l
F
r
a
n
c
e
I
t
a
l
y
U
n
i
t
e
d
K
i
n
g
d
o
m
J
a
p
a
n
G
r
e
e
c
e
I
c
e
l
a
n
d
I
r
e
l
a
n
d
S
p
a
i
n
G
e
r
m
a
n
y
S
l
o
v
e
n
i
a
B
e
l
g
i
u
m
F
i
n
l
a
n
d
G
r
o
u
p
A
v
e
r
a
g
e
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
Only Voluntary Both Voluntary and Compulsory Only Compulsory Not Classified
23
Prevalence and Sources of Training in Starting a Business
In summary, more than one-fifth of the working-age
(18–64 years) population across the 38 participating
countries had received training in starting a business
as of mid-2008. The country-level prevalence rate
varies considerably. Most countries show a level
between 10% and 30%, with a few countries having
higher or lower prevalence rates. On average, there
is not a significant difference in level or variability
between the three economic groups. For most
countries, but not all, more than half of the trained
population engaged in training voluntarily.
4.2 SOURCES OF TRAINING IN
STARTING A BUSINESS
This section investigates how sources of start-up
training vary across countries and economic groups.
In an examination of training sources, a distinction
is made between “in-school” and “non-school”
training. In-school training is training provided as
part of primary or secondary education. Non-school
training comprises sources beyond primary and
secondary schooling, such as colleges, universities,
public agencies, chambers of commerce, trade unions
and employers. Secondly, “formal” and “informal”
training are defined. Formal training is received as
part of a formal education, e.g. primary or secondary
education, or as part of a tertiary-level certificate,
diploma or degree program. Informal training refers
to all other types of training. These might include
non-credit evening courses at a university, local
business organization or a government agency. These
dimensions provide different perspectives on the
nature of the training system in each country.
These distinctions are important because they can
capture the extent to which a government is providing
entrepreneurship training through the formal
education system and how early that training occurs
in a person’s schooling. Additionally, they capture
the relative importance of informal training sources,
which may help people at a time when they are
more directly engaged in starting businesses, rather
than focused on their education generally. A closer
examination of informal sources can reveal whether
informal training is concentrated through one or
many suppliers—whether it is the responsibility of
universities, private organizations, government or
other sources.
Figure 10 shows the prevalence of training broken
down into in-school and non-school training, organized
by frequency of in-school only training within
economic groups. The level of in-school training in
the adult population varies across countries: from
2% of the adult population in Turkey to around 25%
in Belgium, Chile and Slovenia. Non-school training
ranges from 4% in Egypt and Turkey to 40% in
Finland. Only 30% of trained individuals in Japan and
Serbia received in-school training, compared to around
75% in Ecuador, Jamaica and Belgium.
From Figure 10, it is seen that, on average, the
proportion of non-school training to total training is
similar (68-69%) across the three economic groups
(this includes “non-school only” and “both in-school
and non-school”). However, the proportion of in-
school training is highest (62%) in the factor-driven
economies and lowest (52%) in the innovation-driven
economies (including “in-school only” and “both in-
school and non-school”). The proportion of individuals
that received training from both sources in relation
to total training is also highest in the factor-driven
economies (31%) and lowest in the innovation-driven
economies (21%). These results imply that in-school
and non-school training are roughly equally important
sources of training in the factor-driven economies,
but the relative importance of non-school training is
greater in more developed economies. See Table 11 in
the Appendix for further details on sources of start-up
training.
As Figure 11 shows, most trained individuals have
had formal training, and of these, most have had
informal training in addition to formal training.
Individuals who have had only informal training are
more rare. The prevalence of individuals with formal
training varies from 4% of the adult population in
Serbia and Turkey to 40% in Finland. For informal
training, the range is from 4% in Egypt, Turkey
and Romania to 35% in Finland. The prevalence of
individuals with both types ranges from 1% in Serbia
to 27% in Finland.
24
Prevalence and Sources of Training in Starting a Business
Figure 10—Prevalence of In-School and Non-School Training, by Economic Group, Ordered by Frequency of In-
School Only Training
Source: GEM Adult Population Survey 2008
Figure 11—Prevalence of Formal and Informal Start-Up Training, by Country and Economic Group, Ordered by
Frequency of Formal Only Training
Source: GEM Adult Population Survey 2008
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
0%
10%
20%
30%
40%
50%
B
o
l
i
v
i
a
I
n
d
i
a
E
g
y
p
t
B
o
s
n
i
a
a
n
d
H
e
r
z
e
g
o
v
i
n
a
C
o
l
o
m
b
i
a
E
c
u
a
d
o
r
G
r
o
u
p
A
v
e
r
a
g
e
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
T
u
r
k
e
y
S
e
r
b
i
a
C
r
o
a
t
i
a
B
r
a
z
i
l
R
o
m
a
n
i
a
S
o
u
t
h
A
f
r
i
c
a
U
r
u
g
u
a
y
P
e
r
u
A
r
g
e
n
t
i
n
a
M
e
x
i
c
o
M
a
c
e
d
o
n
i
a
L
a
t
v
i
a
I
r
a
n
C
h
i
l
e
J
a
m
a
i
c
a
H
u
n
g
a
r
y
G
r
o
u
p
A
v
e
r
a
g
e
J
a
p
a
n
I
t
a
l
y
G
r
e
e
c
e
I
s
r
a
e
l
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
U
n
i
t
e
d
K
i
n
g
d
o
m
F
r
a
n
c
e
D
e
n
m
a
r
k
S
p
a
i
n
G
e
r
m
a
n
y
F
i
n
l
a
n
d
I
r
e
l
a
n
d
I
c
e
l
a
n
d
S
l
o
v
e
n
i
a
B
e
l
g
i
u
m
G
r
o
u
p
A
v
e
r
a
g
e
In-School Only Both In-School and Non-School Non-School Only
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
0%
10%
20%
30%
40%
50%
B
o
l
i
v
i
a
I
n
d
i
a
E
g
y
p
t
B
o
s
n
i
a
a
n
d
H
e
r
a
e
g
o
v
i
n
a
C
o
l
o
m
b
i
a
E
c
u
a
d
o
r
G
r
o
u
p
A
v
e
r
a
g
e
D
o
m
i
n
i
c
a
n
R
e
p
u
b
l
i
c
T
u
r
k
e
y
S
e
r
b
i
a
B
r
a
z
i
l
C
r
o
a
t
i
a
R
o
m
a
n
i
a
S
o
u
t
h
A
f
r
i
c
a
U
r
u
g
u
a
y
P
e
r
u
A
r
g
e
n
t
i
n
a
M
e
x
i
c
o
M
a
c
e
d
o
n
i
a
I
r
a
n
C
h
i
l
e
L
a
t
v
i
a
J
a
m
a
i
c
a
H
u
n
g
a
r
y
G
r
o
u
p
A
v
e
r
a
g
e
J
a
p
a
n
I
t
a
l
y
I
s
r
a
e
l
R
e
p
u
b
l
i
c
o
f
K
o
r
e
a
F
r
a
n
c
e
G
r
e
e
c
e
U
n
i
t
e
d
K
i
n
g
d
o
m
D
e
n
m
a
r
k
S
p
a
i
n
G
e
r
m
a
n
y
I
r
e
l
a
n
d
I
c
e
l
a
n
d
F
i
n
l
a
n
d
S
l
o
v
e
n
i
a
B
e
l
g
i
u
m
G
r
o
u
p
A
v
e
r
a
g
e
Only Formal Both Formal and Informal Only Informal
25
Table 2—Prevalence of Formal Training, by Country and Economic Group, Ordered by Prevalence
of School Training
Source: GEM Adult Population Survey 2008
Prevalence and Sources of Training in Starting a Business
The high level of overlap between formal and informal
training indicates that both formal and informal
systems are important sources of entrepreneurship
training and suggests that they complement each
other. See Table 12 in the Appendix for formal and
informal training prevalence rates for each country.
Table 2 provides a more detailed view of formal
training in the participating countries. It shows that
school training as a proportion of total formal training
ranges from 43% in Greece to 90% in Mexico.
COUNTRY
A
TRAINING IN
SCHOOL ONLY
B
TRAINING AT TERTIARY
LEVEL ONLY
C
BOTH SCHOOL AND
TERTIARY TRAINING
D
SCHOOL TOTAL
(A+C)
E
TERTIARY TOTAL (B+C)
F
RATIO OF TOTAL SCHOOL TO
TOTAL TERTIARY (D/E)
Factor-Driven
Colombia (+) 29% 41% 30% 59% 71% 0.8
Bolivia 41% 35% 24% 65% 59% 1.1
India 41% 27% 32% 73% 59% 1.3
Bosnia and Herzegovina (+) 67% 23% 10% 77% 33% 2.3
Egypt 65% 23% 13% 77% 35% 2.2
Ecuador (+) 57% 18% 24% 82% 43% 1.9
Group Average 50% 28% 22% 72% 50% 1.6
Ef?ciency-Driven
Uruguay 42% 41% 17% 59% 58% 1.0
Latvia 44% 39% 16% 61% 56% 1.1
Peru 38% 36% 25% 64% 62% 1.0
Turkey 59% 36% 5% 64% 41% 1.6
Chile 44% 33% 23% 67% 56% 1.2
Argentina 61% 27% 13% 73% 39% 1.9
Iran 61% 25% 14% 75% 39% 1.9
Serbia 73% 24% 2% 76% 27% 2.8
South Africa 52% 22% 26% 78% 48% 1.6
Jamaica 66% 19% 15% 81% 34% 2.4
Macedonia 67% 19% 14% 81% 33% 2.5
Dominican Republic 70% 17% 13% 83% 30% 2.8
Romania 60% 17% 23% 83% 40% 2.1
Croatia (+) 56% 17% 27% 83% 44% 1.9
Hungary (+) 79% 15% 6% 85% 21% 4.1
Brazil 74% 11% 15% 89% 26% 3.4
Mexico 73% 10% 17% 90% 27% 3.4
Group Average 60% 24% 16% 76% 40% 2.2
Innovation-Driven
Greece 33% 57% 9% 43% 67% 0.6
Japan 31% 55% 15% 45% 69% 0.7
Finland 27% 53% 20% 47% 73% 0.6
Israel 49% 43% 9% 57% 51% 1.1
Denmark 55% 40% 5% 60% 45% 1.3
Iceland 53% 39% 7% 61% 47% 1.3
United Kingdom 51% 39% 11% 61% 49% 1.2
Republic of Korea 54% 36% 11% 64% 46% 1.4
Spain 47% 33% 20% 67% 53% 1.3
Italy 56% 32% 12% 68% 44% 1.5
Ireland 55% 29% 16% 71% 45% 1.6
Germany 59% 27% 14% 73% 41% 1.8
Slovenia 56% 22% 22% 78% 44% 1.8
France 60% 22% 19% 78% 40% 1.9
Belgium 66% 16% 19% 84% 34% 2.5
Group Average 50% 36% 14% 64% 50% 1.4
(+) Nations in transition to next stage of competitiveness
26
Prevalence and Sources of Training in Starting a Business
Training at tertiary level as a proportion of total
formal training ranges from 21% in Hungary to 73%
in Finland. In most countries, in-school training is
more prevalent than training at the tertiary level. On
average, this ratio is higher for the efficiency-driven
economic group than for the other two, but there is
also a wide variation within each group. Tertiary-level
training is more prevalent than in-school training
in only four countries: Colombia, Greece, Japan and
Finland.
Table 3 provides a more detailed view of informal
training sources in the participating countries. The
most frequent source of informal training in most of
the countries is self-study, with up to 88% (Croatia)
of those receiving informal training citing this source.
The next most common source of informal training
across the data set is informal university programs,
followed by courses offered through business
associations. The least frequently mentioned sources
are training programs provided by public agencies and
those offered through employer initiatives.
Table 3—Prevalence of Informal Start-Up Training, by Country and Economic Group
Source: GEM Adult Population Survey 2008
COUNTRY PERCENTAGE OF INFORMAL TRAINING SOURCE
University, College
Local Business
Associations
Public Agencies Employer Self-Studies Other Online
Factor-Driven
Bolivia 9.1 (34.6) 8.2 (24.1) 4.6 (16.6) 10.3 (27.9) 45.9 (86.5) 11.4 (26.0) 6.1 (21.0)
Bosnia and Herzegovina (+) 2.9 (28.9) 2.4 (24.1) 1.5 (15.1) 4.5 (45.3) 8.6 (86.2) 1.8 (18.2) 2.0 (20.1)
Colombia (+) 10.7 (37.9) 6.1 (21.5) 5.5 (19.6) 5.3 (18.7) 23.8 (84.5) 7.2 (25.4) 3.5 (12.3)
Ecuador (+) 4.6 (32.5) 4.3 (30.5) 2.7 (19.0) 3.5 (24.3) 10.5 (73.1) 3.8 (26.9) 2.3 (16.1)
Egypt 1.4 (37.0) 1.1 (28.0) 1.7 (43.6) 1.3 (34.0) 2.4 (62.0) 0.5 (12.0) 1.0 (27.0)
India 2.7 (26.3) 2.9 (28.8) 2.8 (27.9) 2.2 (22.1) 4.9 (48.9) 3.6 (35.8) 1.4 (13.6)
Ef?ciency-Driven
Argentina 5.8 (54.0) 5.7 (52.9) 2.3 (21.4) 4.2 (39.2) 9.4 (86.6) 1.7 (16.0) 2.4 (21.5)
Brazil 2.0 (31.5) 4.4 (71.2) 1.1 (17.7) 1.0 (16.1) 2.3 (35.5) 2.3 (35.5) 0.5 (6.5)
Chile 11.3 (35.8) 8.5 (26.8) 10.9 (34.4) 11.8 (37.5) 25.7 (80.8) 14.4 (45.4) 19.9 (61.5)
Croatia (+) 9.7 (25.7) 7.7 (19.1) 4.8 (12.1) 12.8 (26.3) 53.9 (87.7) 10.0 (18.8) 12.4 (22.5)
Dominican Republic 6.9 (41.6) 6.2 (29.0) 3.3 (17.4) 6.4 (33.6) 53.5 (55.5) 0.9 (8.0) 1.1 (10.1)
Hungary (+) 1.9 (28.9) 0.9 (14.1) 1.5 (22.7) 0.9 (14.1) 1.4 (21.1) 0.1 (0.8) 0.3 (3.9)
Iran 4.0 (22.1) 2.4 (13.0) 9.2 (50.3) 3.1 (17.2) 9.8 (53.7) 3.4 (18.3) 1.8 (9.3)
Jamaica 2.8 (36.0) 1.2 (15.6) 2.7 (33.7) 1.3 (16.1) 4.5 (55.9) 0.6 (7.0) 0.6 (0.5)
Latvia 5.1 (32.0) 2.3 (14.7) 3.2 (20.3) 4.2 (25.9) 12.6 (78.4) 1.5 (9.7) 6.8 (39.4)
Macedonia 3.5 (33.5) 3.1 (29.7) 1.8 (17.0) 3.3 (31.9) 8.2 (79.1) 2.4 (23.1) 2.3 (21.4)
Mexico 1.7 (18.3) 2.4 (26.5) 1.5 (16.5) 3.0 (31.5) 3.6 (38.5) 2.4 (25.2) 0.9 (8.7)
Peru 12.5 (53.2) 6.5 (27.4) 5.2 (21.4) 7.7 (33.0) 17.3 (65.6) 7.7 (33.3) 4.6 (17.5)
Romania 1.4 (32.9) 1.1 (26.8) 0.8 (18.3) 1.5 (36.2) 2.8 (65.7) 1.7 (40.0) 0.7 (15.7)
Serbia 1.4 (19.5) 1.0 (13.5) 2.4 (32.3) 1.2 (16.5) 2.8 (37.6) 0.5 (6.8) 0.8 (11.3)
South Africa 4.4 (51.1) 3.3 (38.4) 2.6 (69.1) 2.9 (35.5) 5.6 (65.2) 2.2 (25.8) 0.8 (9.4)
Turkey 1.0 (24.0) 0.6 (14.7) 0.7 (17.7) 1.5 (37.5) 2.7 (67.7) 0.7 (17.7) 0.7 (17.7)
Uruguay 9.5 (54.2) 9.4 (53.1) 3.9 (22.2) 6.6 (37.5) 12.9 (74.0) 4.3 (24.3) 3.4 (19.1)
Innovation-Driven
Belgium 4.7 (32.3) 3.0 (20.5) 4.4 (30.3) 2.0 (13.9) 7.7 (53.3) 4.0 (27.4) 1.1 (7.3)
Denmark 3.4 (22.1) 3.4 (22.1) 4.3 (27.4) 2.0 (13.5) 5.0 (33.3) 1.6 (10.9) 1.5 (9.9)
Finland 10.8 (30.6) 5.7 (16.2) 7.7 (21.6) 3.8 (10.9) 30.5 (86.4) 8.0 (22.6) 4.8 (12.8)
France 2.1 (17.2) 5.5 (45.3) 4.8 (39.3) 1.8 (15.2) 8.2 (67.2) 4.0 (33.0) 2.5 (20.3)
Germany 1.8 (13.9) 7.5 (57.2) 4.2 (32.5) 4.7 (35.7) 10.2 (78.5) 3.2 (24.2) 0.8 (6.1)
Greece 1.3 (12.1) 4.2 (38.1) 2.6 (23.7) 2.1 (19.2) 7.9 (72.4) 1.1 (9.8) 1.8 (16.7)
Iceland 4.4 (25.7) 2.6 (15.2) 2.8 (16.4) 4.5 (26.2) 14.2 (82.5) 4.2 (24.5) 7.8 (44.6)
Ireland 6.9 (40.5) 4.6 (26.7) 6.5 (38.1) 5.0 (29.3) 13.7 (80.5) 1.0 (5.8) 1.5 (8.8)
Israel 3.3 (41.0) 3.4 (41.4) 3.1 (35.9) 2.7 (33.1) 5.8 (71.7) 1.5 ( 17.9) 0.8 (10.3)
Italy 5.2 (22.2) 7.1 (32.3) 2.4 (7.2) 6.3 (26.8) 29.3 (80.1) 1.8 (8.6) 1.8 (15.0)
Japan 8.7 (60.7) 2.7 (18.8) 1.8 (12.6) 4.6 (31.9) 12.1 (84.4) 2.4 (16.7) 3.7 (25.6)
Republic of Korea 3.9 (44.1) 2.7 (30.1) 1.4 (15.8) 1.6 (18.2) 4.4 (49.4) 1.0 (11.4) 1.4 (12.4)
Slovenia 9.2 (45.5) 6.4 (31.7) 5.2 (25.8) 6.3 (31.0) 15.5 (76.8) 3.5 (17.9) 10.8 (51.2)
Spain 8.0 (56.4) 6.2 (43.8) 5.6 (39.5) 4.8 (33.7) 10.0 (70.2) 7.2 (50.6) 5.7 (39.4)
United Kingdom 4.5 (36.6) 3.2 (26.3) 3.1 (25.5) 3.0 (24.8) 9.6 (78.3) 0.6 (5.1) 1.2 (9.5)
(+) Nations in transition to next stage of competitiveness
Note: Percentages shown are for the adult population aged 18-64 years and, in parentheses, as a percentage of those receiving any informal training
27
Use of online programs is most frequent in Chile (62%
of those receiving informal training) and Slovenia
(51%). Frequency of use does not imply popularity.
In Chile, online training is linked with business
registration. Another notable pattern is the low
frequency of government programs. Few countries
show a high level of public agency training. Exceptions
are South Africa with 69% and Iran with 50% of those
receiving informal training.
In summary, both levels of in-school versus non-school
training and levels of formal versus informal training
vary widely across economies and levels of economic
development. The high proportion of formal training
reveals the importance of schools, colleges and
universities in delivering this framework condition.
In most countries, more people have received formal
training from schools than from tertiary-level
institutions, indicating that schools have a broader
reach. The degree of overlap between formal and
informal training suggests that formal training on
its own is not enough for many people. A demand
for informal training also exists, perhaps shortly
before, during or after a venture is started. Finally,
people have a variety of choices for pursuing informal
training. The high frequency of self-study suggests
that many individuals either cannot access or afford
organized training—or perhaps doubt its efficacy.
4.3 DEMOGRAPHICS OF TRAINED
INDIVIDUALS
This section describes the individuals who have and
have not received training in starting a business,
comparing them in terms of age, gender, education
and income across economic groups.
Figure 12 compares the age profiles of trained and
untrained individuals in each of the three economic
groups. Unsurprisingly, populations age as countries
develop; with better health care and education, people
live longer. However, there are differences between
the age profiles of trained and untrained individuals
in all three economic groups. Trained individuals are
more likely to be found in the two younger age ranges
(18–24 years and 25–34 years) and less likely to be in
the three older age ranges. This suggests that training
in starting a business may have increased in recent
decades and, in particular, provision for younger
people may have increased, possibly through the
formal education system.
Figure 12—Age Distribution of Trained and Untrained Individuals, by Economic Group
Source: GEM Adult Population Survey 2008
31%
20%
27%
19%
18%
12%
31%
26%
30%
26%
26%
21%
18%
24%
20%
22% 24%
25%
14%
18%
15%
19% 18%
23%
6%
12%
8%
15% 14%
20%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Trained Untrained Trained Untrained Trained Untrained
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
18-24 Years 25-34 Years 35-44 Years 45-54 Years 55-64 Years
Prevalence and Sources of Training in Starting a Business
28
Prevalence and Sources of Training in Starting a Business
Figure 13 shows that trained individuals are
more likely to be men than women, and untrained
individuals are more likely to be women than men in
all three economic groups. This is not surprising since
in many countries, women show lower entrepreneurial
intentions and activity than men, and so they are
less likely to seek training voluntarily. While similar
proportions of men and women had taken voluntary
training in some countries, only in Latvia and
Hungary were women significantly more likely than
men to have volunteered for training. The proportion
of men and women who have taken compulsory
training also varied widely by country. However,
on average in factor-driven countries, for every ten
men with compulsory training there were seven
women, compared with eight women in efficiency-
driven countries and nine women in innovation-
driven countries. Because voluntary training was
more prevalent than compulsory training, the gender
difference in training prevalence is mainly due to
lower rates of voluntary training among women, and
this did not appear to vary with increasing economic
development (in all three economic groups, for every
ten men who had volunteered for training, there were
eight women).
Figure 13—Gender Distribution of Trained and Untrained Individuals, by Economic Group
Source: GEM Adult Population Survey 2008
57%
48%
55%
49%
56%
49%
44%
52%
45%
51%
44%
51%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Trained Untrained Trained Untrained Trained Untrained
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
Male Female
Figure 14 shows that individuals with at least some
post-secondary school education are more likely to
have received training in starting a business. In most
countries, this is true for voluntary and compulsory
training. Such individuals have spent more time in the
formal education system, so they are more likely to
have had more training opportunities. However, this
group tends to be more entrepreneurial anyway—more
likely to see a need to learn about starting a business
and more likely to see value in such training.
29
Prevalence and Sources of Training in Starting a Business
Figure 14—Education Distribution of Trained and Untrained Individuals, by Economic Group
Source: GEM Adult Population Survey 2008
Figure 15—Income Distribution of Trained and Untrained Individuals, by Economic Group
Source: GEM Adult Population Survey 2008
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
1% 3% 0% 0% 0% 0%
20%
43%
19%
41%
17%
27%
37%
27%
35%
32%
27%
26%
23%
12%
21%
14%
26%
21%
20%
15%
26%
13%
30%
26%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Trained Untrained Trained Untrained Trained Untrained
Factor-Driven Efficiency-Driven Innovation-Driven
No Secondary Some Secondary Secondary Degree Some Post-Secondary Graduate
Figure 15 shows that the profile of untrained
individuals is less wealthy than the profile of
trained individuals. This association is stronger in
factor-driven or efficiency-driven countries than in
innovation-driven countries. In addition to the obvious
reason, training may help make individuals wealthier,
individuals from wealthy households may have more
opportunity to engage in training and wealthier
households can afford further education for their
children. Moreover, poorer individuals may not have
the time or money to devote to training.
31%
44%
27%
37%
31%
35%
35%
34%
36%
38%
37%
36%
34%
22%
38%
26%
32%
29%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Trained Untrained Trained Untrained Trained Untrained
Factor-Driven Efficiency-Driven Innovation-Driven
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
LOWEST 33%TILE MIDDLE 33%TILE UPPER 33%TILE
30
5 The Relationship Between Training in Starting a Business and Entrepreneurship
5.1 ISSUES IN MEASURING
THE EFFECT OF TRAINING ON
ENTREPRENEURIAL BEHAVIOR
This chapter considers the relationship between
training and entrepreneurial awareness, attitudes,
intention and activity. Previous chapters
have reported on the frequency and nature of
entrepreneurship education and training across
economies and economic groupings. The sources of
training and demographic information about those
trained have also been revealed. In this chapter the
question posed in Section 2.3 will be addressed: Does
entrepreneurship education and training make a
difference?
The literature reviewed in Section 2.3 indicates
a lack of evidence demonstrating the influence of
training on entrepreneurial activity (Béchard and
Grégoire, 2005). There is some evidence, however,
that entrepreneurship education and training may
enhance skills (DeTienne and Chandler, 2004; Honig,
2004; Summit Consulting, 2009) and attitudes
(Peterman and Kennedy, 2003; Hegarty, 2006;
Souitaris et al., 2007; Walter and Dohse, 2009) toward
entrepreneurship. In conclusion, there was a need
to explore the relationships between this training
and awareness, attitudes, intention and activity
across multiple countries, using large, representative
samples in each.
Many research studies on entrepreneurship training
have had difficulty assembling adequate control
groups to demonstrate effects, due to cost and data
protection issues (Summit Consulting, 2009). GEM
conducts random samples of the entire working-age
population in a wide range of countries. By asking
random samples of the population questions about
their awareness, attitudes, intention and activity, and
then, later in the interview, asking them questions
about any training in starting a business they may
have had, many sampling biases are avoided and
natural control groups are created.
It is natural to assume that those who want to start
businesses would seek out information on how to
proceed. They might therefore seek training as part of
their search. If one were to compare these people with
those who did not take training, observed differences
in awareness, attitudes, intention or activity might
not just be due to their training, but to their prior
orientation as well. For example, business school
students tend to self-select into this type of education
and, most often, into entrepreneurship training
once they are enrolled in business school. Because
individuals were asked whether their training was
voluntary or compulsory or both, GEM can isolate
those who had voluntary training and remove them
from analyses of cause and effect, eliminating self-
selection bias to a considerable degree.
By noting all the training that a representative
sample of individuals received in their lives so far,
and analyzing a broad array of outcomes, the GEM
data address the issues of timing that have hampered
progress in research on the effect of entrepreneurship
education and training. People may receive
entrepreneurship education and training at various
times in their lives, whether at school, university
or beyond their formal education. In addition, the
effects may be deferred rather than instantaneous.
For example, in the short term, graduates of
entrepreneurship education may recognize the need
to amass specific knowledge (Fiet and Pankaj, 2008),
yet decide to defer action until they understand their
chosen industry better. The GEM data also accounts
for differences in how individuals learn. This learning
can range from traditional education to experiential
immersion in the phenomenon—through a placement
or internship in an actual company, for example. GEM
surveyed individuals about the full range of possible
training sources, from primary school onward, which
enables inclusion of all combinations of training. In
addition, by measuring demographic characteristics
of each individual in each sample, GEM can control
for age group, gender, education, working status and
other effects that might mask the training effect.
Finally, GEM can address limitations due
to differences in context. In some countries,
entrepreneurship is widespread, easily observable
and culturally acceptable. In others, few individuals
start businesses; any training that exists in these
countries may provide a more significant source of
learning. By surveying many countries, GEM can
discern the differences in cause and effect that might
be contextual.
This combination of advantages in the GEM
methodology provides a unique opportunity to make a
baseline contribution to the knowledge of the impact
of entrepreneurship training. In addition, it can reveal
opportunities for more focused follow-up research.
5.2 TRAINING IN STARTING A
BUSINESS AND INVOLVEMENT IN
ENTREPRENEURIAL ACTIVITY
The GEM APS survey assesses the proportion
of working-age individuals in an economy that
are in the process of starting a business (nascent
entrepreneurs) or owners of new businesses (under
42 months old). This is the basic GEM measure of
31
The Relationship Between Training in Starting a Business and Entrepreneurship
early-stage entrepreneurial activity (TEA). As Figure
16 illustrates, across the 38 countries, entrepreneurs
are more likely to have received training in starting
a business (33%) than the rest of the working-age
population (20%). This difference is statistically
significant and suggests that current early-stage
entrepreneurial activity is associated, at least to some
degree, with past training in starting a business.
Figure 16 — Proportion of Trained vs. Untrained Individuals Involved in Early-Stage Entrepreneurial Activity
(TEA), and Those Not Involved (non-TEA)
Source: GEM Adult Population Survey 2008
Table 4 compares the proportion of the whole working-
age population and the proportion of early-stage
entrepreneurs who have received training in each
nation, in three economic groups, ordered by relative
frequency of training. Training prevalence varies
widely across countries, but the proportion of trained
individuals and trained early-stage entrepreneurs
is higher on average in innovation-driven countries.
Around one-fifth of working-age individuals in factor-
driven and efficiency-driven countries are trained; this
rises to around one-third of early-stage entrepreneurs.
This compares with around one-quarter of working-
age individuals and two-fifths of early-stage
entrepreneurs in innovation-driven countries.
The third column in Table 4, reproduced in graphical
form in Figures 17–19, shows that in both factor-
driven and efficiency-driven countries, as the
level of training in the working population as a
whole increases, so does the level of training in the
population of early-stage entrepreneurs, but at a
declining rate. In other words, the conversion of
trained individuals to entrepreneurs appears to be
higher in countries with a low rate of training than in
countries with a high rate of training. This suggests
that there may be diminishing returns to training
in terms of conversion to entrepreneurial activity as
training becomes widespread in these populations.
A different pattern is seen in innovation-driven
countries (Figure 19), where the ratio increases—as
training becomes widespread—then levels off and
declines only when over a fifth of the working-age
population has been trained. This suggests that
increasing the quantity of training may generate
increasing returns to entrepreneurial activity in
innovation-led countries, up to a point. This pattern
seems to fit the GEM model, which suggests that
improving the entrepreneurship education and
training EFC would be most effective in innovation-
driven countries.
80%
67%
20%
33%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90&
100%
Non-TEA TEA
P
e
r
c
e
n
t
a
g
e
o
f
A
d
u
l
t
P
o
p
u
l
a
t
i
o
n
(
1
8
-
6
4
Y
e
a
r
s
)
Trained Untrained
32
The Relationship Between Training in Starting a Business and Entrepreneurship
Table 4—Prevalence of Training in Starting a Business in the Total Working-Age Population and Among
Early-Stage Entrepreneurs
Source: GEM Adult Population Survey 2008
COUNTRY
PERCENTAGE TRAINED
INDIVIDUALS AGED 18-64
PERCENTAGE TRAINED NASCENT AND NEW
ENTREPRENEURS
RATIO OF TRAINED ENTREPRENEURS TO
TRAINED INDIVIDUALS
Factor-Driven
Egypt 7.6 14.0 1.8
India 13.4 23.0 1.7
Bolivia 19.1 30.8 1.6
Bosnia and Herzegovina 20.0 31.4 1.6
Ecuador 27.2 39.4 1.4
Colombia 40.1 53.5 1.3
Group Average 21.2 32.0 1.5
Ef?ciency-Driven
Turkey 6.3 15.1 2.4
Dominican Republic 7.7 15.8 2.1
Romania 8.7 16.1 1.9
Brazil 9.4 20.4 2.2
Serbia 10.2 20.8 2.0
South Africa 13.9 22.7 1.6
Mexico 16.2 24.8 1.5
Argentina 17.5 29.0 1.7
Macedonia 19.1 36.2 1.9
Jamaica 21.0 37.4 1.8
Uruguay 24.1 40.2 1.7
Hungary 24.5 40.7 1.7
Croatia 28.1 42.3 1.5
Latvia 28.3 42.4 1.5
Iran 29.1 50.4 1.7
Peru 29.6 55.0 1.9
Chile 42.6 61.1 1.4
Group Average 19.8 33.6 1.7
Innovation-Driven
Israel 12.8 17.5 1.4
Republic of Korea 13.6 21.8 1.6
Italy 16.5 28.1 1.7
Greece 17.0 30.3 1.8
Japan 17.4 31.3 1.8
France 18.1 35.0 1.9
United Kingdom 18.4 37.8 2.1
Germany 21.1 41.2 2.0
Spain 22.0 44.3 2.0
Denmark 22.6 45.0 2.0
Ireland 26.1 46.6 1.8
Iceland 26.8 51.7 1.9
Belgium 33.6 55.4 1.6
Slovenia 35.8 58.2 1.6
Finland 48.6 69.6 1.4
Group Average 23.4 40.9 1.7
33
The Relationship Between Training in Starting a Business and Entrepreneurship
Figure 17—Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population Within the
Factor-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals
Source: GEM Adult Population Survey 2008
Figure 18—Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population Within the
Ef?ciency-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals
Source: GEM Adult Population Survey 2008
Figure 19—Ratio of Trained Entrepreneurs to Trained Individuals in the Working-Age Population Within the
Innovation-Driven Economic Group, Ordered by Increasing Percentage of Trained Individuals
Source: GEM Adult Population Survey 2008
1
1.5
2
2.5
0 5 10 15 20 25 30 35 40 45
Percentage of Trained Individuals in the Adult Population (18-64 Years)
R
a
t
i
o
n
o
f
P
e
r
c
e
n
t
a
g
e
o
f
T
r
a
i
n
e
d
E
n
t
r
e
p
r
e
n
e
u
r
s
t
o
T
r
a
i
n
e
d
I
n
d
i
v
i
d
u
a
l
s
1
1.5
2
2.5
0 5 10 15 20 25 30 35 40 45
Percentage of Trained Individuals in the Adult Population (18-64 Years)
R
a
t
i
o
o
f
P
e
r
c
e
n
t
a
g
e
o
f
T
r
a
i
n
e
d
E
n
t
r
e
p
r
e
n
e
u
r
s
t
o
T
r
a
i
n
e
d
I
n
d
i
v
i
d
u
a
l
s
1
1.5
2
2.5
0 10 20 30 40 50 60
Percentage of Trained Individuals in the Adult Population (18-64 Years)
R
a
t
i
o
o
f
T
r
a
i
n
e
d
E
n
t
r
e
p
r
e
n
e
u
r
s
t
o
T
r
a
i
n
e
d
I
n
d
i
v
i
d
u
a
l
s
34
The Relationship Between Training in Starting a Business and Entrepreneurship
5.3 GAIN FROM TRAINING: GEM’S
CORE MEASURE OF THE EFFECT OF
TRAINING IN STARTING A BUSINESS
The core measure of effect used in analyzing the
GEM training data is “gain from training.” The gain
from training is a numerical measure that estimates
effect while controlling for issues that have hampered
previous studies in this area (noted in Section 5.1).
To address the self-selection problem, GEM compares
the effect of having had compulsory training versus
not having had any training on entrepreneurial
awareness, attitudes (such as skills perception,
opportunity perception or fear of failure), intention
to start a business and early-stage entrepreneurial
activity, controlling for the demographic background
of an individual. Large random samples of the
working-age population provide natural controls.
Gain from training is a country-based measure that
can be interpreted at a group or individual level. First,
it can be thought of as the increase in the proportion
of people in the country who have a characteristic,
such as a particular attitude, because of compulsory
training (but not voluntary training) in starting a
business, controlling for demographic differences (age
group, gender, education and working status). Thus, a
gain of two would mean the following: If two samples
of people were taken—differing in that one group
had received only compulsory training in starting a
business and the other had not—one would find that
twice as many people in the compulsory training
group would have a particular attitude, compared to
people in the other group.
Second, it can be thought of as the increase in the
odds that individuals with a given set of demographic
characteristics will have a particular entrepreneurial
orientation if they have ever taken compulsory
training (but not voluntary training) versus
individuals with identical demographic characteristics
but without such training. As an example, a gain of
two would indicate that individuals’ chances of having
a particular orientation are doubled if they have taken
compulsory training.
Table 5 reports the gain from training in TEA rates for
each country for which sufficient data were available.
Tables 13 and 14 in the Appendix display country
estimates of gain from training in starting a business,
grouped by level of economic development and by
principal global region. The estimates of gain are for
raising awareness of new business entrepreneurs,
improving three different entrepreneurial attitudes
(opportunity perception, start-up skills self-perception
and fear of failure), increasing intent to start a
business within the next three years and increasing
early-stage entrepreneurial activity. For each country,
the gain from training and level of significance (none,
low, moderate or high) are reported.
Since compulsory training is relatively rare in many
countries, it is possible that non-significant results are
due to the small sample size. Therefore, the figures
provided display economic group averages (Figures
20 and 21) and geographical global region averages
(Figures 22 and 23). For each country group, the
figures report the average gain (Figures 20 and 22)
and percentage of countries in which the significance
level of the gain from training is at least moderate
(p