Regulation of Entry and Innovative Entrepreneurship - Matteo Consonni

Universiteit Leiden Campus Den Haag
MSc in Public Administration
Specialization in Governing Markets: Regulation and Competition
Regulation of Entry and Innovative
Entrepreneurship
The Impact of Entry Regulation on the Support to
Innovative Entrepreneurship During 2007-2013
Cohesion Policy
Student: Matteo Consonni
Supervisor: Dr. Maarja Beerkens
––––––––––––––––––––––––––––– Academic Year 2014-2015 –––––––––––––––––––––––––––––

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Table of Contents
Summary 4
1. Introduction 7
1.1 Research Puzzle 7
1.2 Policy Implementation 10
1.3 Research Question 11
1.4 Academic Relevance 11
1.5 Social Relevance 13
2. Theory 15
2.1 Innovation and Entrepreneurship 15
2.2 The Market of Innovative Entrepreneurship 16
2.3 The Role of Governments and the Importance of Institutions 17
2.4 Entry Regulation and Entrepreneurship 19
2.5 Entrepreneurship and Economic Growth 20
2.6 One Size Does Not Fit All 21
2.7 Hypotheses 22
3. Research Design 23
3.1 Quantitative Analysis 23
3.1.1 Dependent Variables 23
3.1.2 Independent Variables 25
3.1.3 Method 28
3.2 Qualitative Analysis 29
4. Analysis 32
4.1 Quantitative Results 32
4.2 Qualitative Results 39
4.2.1 Italy 40
4.2.2 United Kingdom 42
4.2.3 Italy and United Kingdom Compared 44
5. Conclusions 45
5.1 Summary and Findings 45
5.2 Answer to the Research Question 46
5.3 Academic and Social Relevance 47
5.4 Limitations of the Study 48
5.5 Suggestion for Future Research 48
References 50
Appendix 53

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Summary
Between 2007 and 2013, the European Commission supported the growth of 97,640 start-
ups by investing €86.4 billion in research and innovation. The ways the money invested has
been exploited and the numbers of start-ups supported differ among member states. This
thesis is aimed at understanding how entry regulation policies of European countries
influenced the number of start-ups supported by Structural Funds made available by
European Union (EU) Cohesion Policy between 2007 and 2013. It hypothesises that low-
entry-regulated countries, such as the United Kingdom, supported more start-ups than high-
entry-regulated countries, such as Italy.
The large amount of existing literature on the market of innovation and entrepreneurship,
the role of governments and institutions in that market, and the links between regulation and
innovative entrepreneurship set the basis for this analysis. According to Boadway and
Tremblay (2003), the free market of innovative entrepreneurship in Europe failed because of
the barriers to entry established by governments and existing firms. When the market failed,
the government intervened to correct the failure. Consequently, European funds designed to
promote innovation as part of the EU Cohesion Policy and Euro 2020 strategy represent the
subsidies introduced by the EU to correct the market failure of the free market of innovative
entrepreneurship.
The attention has therefore been focused on the reasons that lead to the different number
of start-ups supported by Structural Funds made available from EU Cohesion Policy 2007-
2013 – i.e. the reason why the start of innovative entrepreneurship has been larger in some
countries than others. According to Boettke and Coyne (2007), entrepreneurship is a
characteristic of human action and can be found at any point in time. What matters for the
spread of innovative entrepreneurship are institutions. More precisely this thesis is aimed at
investigating to what extent entry regulation influenced the number of start-ups supported by
Structural Funds in the 2007-2013 period of Regional Policy. Klapper, Laeven, and Rajan
(2004) claimed that entry regulation hampers the creation of new firms. They compared
high-entry-regulated Italy and the low-entry-regulated United Kingdom and discovered that
firms start out larger when young in Italy, but grow more slowly so that firms in the United
Kingdom are about twice as large by age ten. Moreover, the regulation of entry is not

5

associated with higher quality products and higher profitability of firms (Djankov et al.,
2000). This research paper contributes to the literature on innovative entrepreneurship and
entry regulation by applying academic evidence of the impact of entry regulation on start-ups
of innovative entrepreneurship in the frame of subsidies provided by EU Cohesion Policy
2007-2013 to overcome barriers to entry that market.
Moreover, investigating the outcomes of EU Cohesion Policy in terms of start-ups
supported provide an overview of the spread of innovative entrepreneurship among member
states. Since opportunity entrepreneurship has a positive and significant effect on economic
development (Acs, 2006), understanding the factors that may limit the start-up of new
enterprises with financial assistance of Structural Funds give important policy suggestions for
incoming period of Cohesion Policy 2014-2020 in order to reach the results of Europe 2020
strategy.
To test the hypothesis, both a quantitative and a qualitative analysis were conducted. The
quantitative analysis focused on matching entry regulation with the results of EU Cohesion
Policy 2007-2013 in terms of start-ups supported, in order to have an overview of the impact
of the former on the latter. To define entry regulation the study of Djankov et al (2000) has
been taken into account. The qualitative analysis investigated five entrepreneurs from high-
entry-regulated Italy and five entrepreneurs from low-entry-regulated United Kingdom as
two case studies, to understand how entry regulation directly influenced the experience of
starting up a business and to explore whether other factors may have explained the different
outputs of Cohesion Policy in terms of start-ups supported beyond the regulation of entry.
According to the quantitative analysis, the claim that entry regulation hampers the creation
of new firms (Klapper, Laeven, and Rajan, 2004) is confirmed in the frame of start-ups
supported among European countries during EU Cohesion Policy 2007-2013. The
scatterplots illustrate that countries with the lowest rates of procedures to register a business,
time required to register a business, and cost of business start-up procedures generally set up
more start-ups in EU Cohesion Policy 2007-2013 than countries with the highest rates of the
same indicators. Spearman correlation coefficients show moderate to weak negative
correlations between the number of start-up supported per 100,000 population by Structural
Funds from EU Regional Policy between 2007 and 2013 and the various indicators for
regulation of entry. Furthermore, when considering as dependent variable Investment in

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Innovation & RTD per Start-Up Supported, Spearman coefficient with all the independent
variables shows moderate positive correlation between the dependent variable and the
explanatory variables that represent the regulation of entry. These results generally show that
higher levels of regulation of entry is a predictable factor of lower numbers of start-ups
supported by Structural Funds made available by EU Regional Policy between 2007 and
2013.
The qualitative analysis confirmed the expected differences regarding the experiences of
entering the market of innovative entrepreneurship in the low-entry-regulated United
Kingdom and high-entry-regulated Italy. The different entry regulations of the two countries
influenced differently experiences of starting businesses in Italy and the United Kingdom.
While entry regulation seems to discourage the experience of starting up a business in Italy,
this can not be claimed in the case of the United Kingdom. While many factors were
underlined by Italian respondents as problems during the process of starting up a business,
the process of business creation in the United Kingdom is considered relatively easy by
respondents. Entry regulation and the three measures theorised by Djankov et al (2000) were
not mentioned by any of the interviewed from the United Kingdom while respondents from
Italy mentioned high costs, slow and long bureaucratic procedures, and excessive regulation
as main factors that hamper their entry into the market of innovative entrepreneurship.
Finally, in both countries, government intervention and Structural Funds made available by
EU Cohesion Policy were not mentioned as possible solutions to facilitate the process of
starting a business. Money and fundraising were mentioned by all the interviews as a
challenge faced during entrepreneurial activity but public funds were not considered a
possible solution to these problems; private funding was generally considered easier to
obtain.
Finally, according to results and theoretical background, it can be concluded that entry
regulation can be an important obstacle for innovative entrepreneurship. Additional funds to
support early stage start-ups might solve some of the problems – i.e. the credit flow problem.
Nonetheless, as Boettke and Coyne (2007) stated, the institutional framework matters.
Accordingly, if countries want to encourage the growth of innovative entrepreneurship,
regulation of entry should be reconsidered in order to create a start-up friendly environment.

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1. Introduction
1.1 Research Puzzle
The European Union Regional Policy, also referred as EU Cohesion Policy, is the EU’s
main investment policy. It targets all regions and cities in the European Union in order to
support job creation, business competitiveness, economic growth, sustainable development,
and improve citizens’ quality of life (European Commission, 2015). Regional Policy is
delivered in three main funds: the European Regional Development Fund (ERDF), the
Cohesion Fund (CF), and the European Social Fund (ESF). Together with the European
Agricultural Fund for Rural Development (EAFRD) and the European Maritime and
Fisheries Fund (EMFF), they make up the European Structural and Investment (ESI) Funds.
Regional Policy has a strong impact in many fields. Its investments help deliver many EU
policy objectives and complement EU policies such as those dealing with education,
employment, energy, the environment, the single market, and research and innovation. In
particular, Regional Policy provides the necessary investment framework to meet the goals of
the Europe 2020 strategy for smart, sustainable, and inclusive growth in the European Union
by 2020 (European Commission, 2015). EU Regional Policy is divided in three periods: the
first one from 2000 to 2006, the second one from 2007 to 2013, and the last one from 2014 to
2020. Each period has been set with different strategies and budgets.
In the 2000-2006 period, a budget of €213 billion was set for the 15 existing members. In
2004, €22 billion was added for new member countries. Between 2007 and 2013, a budget of
€347 billion was set: 25% marked for research and innovation and 30% for environmental
infrastructures and measures to combat climate change. Finally, in order to reach the goals
and address the diverse development needs in all EU regions, €351.8 billion – almost a third
of the total EU budget – has been set aside for Cohesion Policy for 2014-2020 (European
Commission, 2015).

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Figure 1. Number of Start-Ups Supported by EU Cohesion Policy Instruments in 2007-2013. (Source: European
Commission, 2015.)
Sustainable growth is increasingly related to the capacity of regional economies to
innovate and transform, adapting to an ever changing and more competitive environment.
This means that a much greater effort needs to be put into creating the eco-systems that
encourage innovation, research and development (R&D), and entrepreneurship, as stressed by
the Europe 2020 strategy and its Innovation Union flagship initiative (European Commission,
2011).
The promotion of innovation is therefore a central feature in the Cohesion Policy
programmes for 2007-2013, where approximately €86.4 billion or nearly 25% of the total
allocation went towards innovation. This commitment is further strengthened in the new
2014-2020 programme period, where 30% of the total allocations will be deployed for
innovation. In the future, smart specialisation strategies will also mobilise the innovation
potential of all EU regions (European Commission, 2015).
As the European Commission states, macro-economic research points out that innovation
contributes between two-thirds and four-fifths of economic growth in developed countries. In
other words, about 85% of productivity growth in advanced economies is driven by
innovation. However, statistics confirm large disparities between EU member states and
regions in the fields of innovation and R&D as well as a persistent gap compared to its main

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competitors at global level. Europe needs to become more inventive, reacting more quickly to
changing market conditions and consumer preferences in order to become an innovation-
friendly society and economy (European Commission, 2014).
Consequently, between 2007 and 2013, EU Cohesion Policy instruments provided €86.4
billion – almost 25% of the total, to R&D and innovation (European Commission, 2015).
From this total:
§ €50.5 billion to R&D in a narrow sense;
§ €8.3 billion to entrepreneurship, including €5.2 billion for advanced support services
for firms and €3.2 billion to support self-employment and business start-ups;
§ €13.2 billion to innovative information and communication technologies and;
§ €14.5 billion to human capital.
In order to increase transparency and to promote debate on the performance of EU
funding, the European Commission makes available an open data platform that provides
information about the investments made and the results obtained from EU Cohesion Policy.1
In this paper the attention is focused on the data regarding the number of start-ups supported
by Regional Policy instruments in the 2007-2013 period. This goal has been measured by
tracking the number of enterprises created receiving financial aid or assistance – consultancy
or guidance, from Structural Funds or Structural Funds financed facilities. The legal form of
enterprises may be various – e.g. self employed person, partnerships, et cetera.
In 2007-2013, 97,640 start-ups were supported by Structural Funds from EU Cohesion
Policy. As seen in Figure 1, there are big differences in the number of enterprises created
receiving financial aid or assistance between member states. The United Kingdom leads the
chart with a gap of more than 20,000 start-ups supported than Sweden – the second country
in this rank. The numbers vary from 0 to 39,453 among the 23 countries, with a median of
4,225. Moreover, taking into account demography and the breakdown in Innovation &
Research and Technological Development of available budgets for each country, we can
compute the number of start-ups supported per 100,000 population and the amount of funds
invested in that area per start-up supported. Also in these circumstances numbers vary a lot.
In the case of breakdown in innovation & RTD, it is clear that funds have been addressed to
1
https://cohesiondata.ec.europa.eu,
accessed
June
2015.

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fields other than innovative entrepreneurship. Nonetheless, these computations allow taking
into account the divers populations and the different amount of money that member states
invested in the field. The aim of this thesis is, therefore, to investigate the factors that might
have influenced the outcomes of EU Cohesion Policy 2007/2013 in terms of number of start-
ups supported. Since the numbers of start-ups supported and the ways money invested has
been exploited differ among member states, this thesis is aimed at understanding why some
countries seem to be better than others in supporting the growth of innovative
entrepreneurship.
1.2 Policy Implementation
The implementation of Regional Policy is split into eight stages.2
Firstly, the budget for
the policy and the rules for its use are jointly decided by the European Council and the
European Parliament on the basis of a proposal from the Commission. In addition to common
rules for the European Structural and Investment Funds (ERDF, ESF, CF, EAFRD and
EMFF) there are also rules which are specific for each Fund. Secondly, the principles and
priorities of cohesion policy are distilled through a process of consultation between the
Commission and the EU countries. Each Member State produces a draft Partnership
Agreement, which outlines the country's strategy and proposes a list of programmes. In
addition to this Member States also present draft operational programmes (OP), which cover
entire Member States and or regions. There will also be cooperation programmes involving
more than one country. Thirdly, the Commission negotiates with the national authorities on
the final content of the Partnership Agreement, as well as each programme. The programmes
present the priorities of the country and/or regions of the cooperation area concerned.
Workers, employers and civil society bodies can all participate in the programming and
management of the OPs. Fourthly, the Member States and their regions implement the
programmes. This means selecting, monitoring, and evaluating hundreds of thousands of
projects. This work is organised by “managing authorities” in each country and/or region.
Fifthly, the Commission commits the funds – to allow the countries to start spending on their
programmes. Sixthly, the Commission pays the certified expenditure to each country. Then
the Commission monitors each programme, alongside the country concerned. Finally, both
the Commission and the member countries submit reports throughout the programme period.
2
http://ec.europa.eu/regional_policy/en/policy/how/stages-‐step-‐by-‐step.

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Summarising, the European Council, European Parliament, and European Commission set
the budget and the rules for the use of funds. Both the Commission and EU countries decide
principles and priorities of the Cohesion Policy. Member states list an agreement in which
they propose a strategy for reaching the objectives of the policy and are responsible for
implementation and allocation of funds. Therefore, the reasons of the different use and
outcomes of available funds by member states can be looked into the different ways countries
allocate and implement the funds. As mentioned above, the aim of this thesis is to investigate
the outcome of EU Cohesion Policy 2007-2013 in terms of the different number of start-ups
supported by member states with available funds for Innovation and RTD. According to
policy implementation of European Union Cohesion Policy, the legal norms that shape the
allocation and implementation of Structural Funds – i.e. the different regulatory systems –
play a central role in the way funds are addressed. Consequently, regulation has been
investigated in this paper as a factor influencing the number of start-ups supported by
Regional Policy 2007-2013. The framework for implementing Structural Funds has been the
starting point for a broader discussion about the relation between regulatory frameworks and
the growth of innovative entrepreneurship.
1.3 Research Question
Entrepreneurship is an important engine for growth and development. The EU provides
Structural Funds within EU Regional Policy for innovative entrepreneurship to overcome the
barriers to market entry. Data regarding the number of start-ups supported by Structural
Funds of European Cohesion Policy 2007-2013 are the starting point for this thesis.
Considering the different population of each member state and the different amounts of
money invested in Innovation & Research and Technological Development, the main
question concerns the causes that lead some countries to support more start-ups than others.
In this frame the number of start-ups supported is a variable taken into account to represent
the concept of the spread of innovative entrepreneurship.
According to the literature on the topic, entry regulation of member states is the variable
considered to affect the support of innovative entrepreneurship. Considering the study of
Klapper, Laeven, and Rajan (2004), Italy and the United Kingdom are the two countries
considered as case studies because of their high-entry-regulated and low-entry-regulated

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economies. Summarising, the research question of this thesis is: to what extent the regulation
of entry influenced the number of start-ups supported by Structural Funds from EU Cohesion
Policy 2007-2013?
1.4 Academic Relevance
There is a large amount of existing literature on the market of innovation and
entrepreneurship, the role of governments and institutions in that market, and the links
between regulation and innovative entrepreneurship. Joseph Schumpeter’s definition of
entrepreneurship as suggested by Bull and Willard (1993) for academic and policy-making
purposes is dated 1943. From that year the forms of how innovation cross entrepreneurship
have changed till the modern start-up. What has not changed is the importance that
entrepreneurship has for the society and the academic attention to this theme.
According to the theoretical background presented by Boadway and Tremblay (2003), the
free market of innovative entrepreneurship in Europe failed because of the barriers to entry
established by governments and existing firms. When the market fails, the government
intervenes to correct the failure. Consequently, European funds designed to promote
innovation as part of the European Union Cohesion Policy and Euro 2020 strategy, represent
the subsidies introduced by EU to correct the market failure of the free market of innovative
entrepreneurship. In this research the attention is focused on the reasons that lead to the
different number of start-ups supported by Structural Funds made available from EU
Cohesion Policy 2007-2013 – i.e. why the start of innovative entrepreneurship is larger in
some countries than others. According to Boettke and Coyne (2007), entrepreneurship is a
characteristic of human action and can be found at any point in time. What might influence
the spread of innovative entrepreneurship, instead, are institutions. Amorós (2009) stated that
the quality of institutions is a relevant factor for the distribution and type of entrepreneurial
activities.
More precisely this thesis aims to investigate to what extent entry regulation influenced
the number of start-ups supported by Structural Funds in the 2007-2013 period of Regional
Policy. Klapper, Laeven, and Rajan (2004) claimed that entry regulation hampers the creation
of new firms. In this regards, they compared high-entry-regulated Italy and the low-entry-
regulated United Kingdom and found out that firms start out larger when young in Italy, but

13

grow more slowly so that firms in the United Kingdom are about twice as large by age ten.
Moreover the regulation of entry is not associated with higher quality products and higher
profitability of firms (Djankov et al., 2000). Therefore, the academic reasons to carry out this
research are to give empirical and theoretical explanation to the results of EU Cohesion
Policy in terms of start-ups supported by financial aid or assistance in 2007-2013 and
contribute with the results to the existing literature on the topic of innovation,
entrepreneurship, and entry regulation.
1.5 Social Relevance
As Amorós stated in 2009, the last few years registered a prominent flourishing of
empirical studies on the determinants of new business creation and its effect on the economy.
The enduring claim that entrepreneurial activity promotes economic growth and development
has been confirmed in many studies (Minniti, 2008; Acs & Szerb, 2007; Carree & Thurik,
2003; Acs, 2006). As aforementioned, the aims of EU Cohesion Policy are to support job
creation, business competitiveness, economic growth, sustainable development, and improve
citizens’ quality of life. Moreover, as the European Commission (2015) stated, the promotion
of innovation is considered a central feature in the Regional Policy programmes in which,
between 2007 and 2013, EU Cohesion Policy instruments provided €86.4 billion – almost
25% of the total, to R&D and innovation. Out of this total, €8.3 billion were devoted to
entrepreneurship.
There is no ideal model for innovation policy (Tödtling & Trippl, 2005; Minniti, 2008),
and policy strategies, with respect to entrepreneurship, need to be tailored to the specific
institutional contexts of each economic region (Wagner & Sternberg, 2004). Accordingly,
investigating the outcomes of EU Cohesion Policy in terms of start-ups supported might
provide an overview of the spread of innovative entrepreneurship among member states.
Moreover, opportunity entrepreneurship – an active choice to start a new enterprise based on
the perception that an unexploited or underexploited business opportunity exists – has a
positive and significant effect on economic development. On the other hand, necessity
entrepreneurship – having to become an entrepreneur because you have no better option – has
no effect on economic development (Acs, 2006). Understanding the factors that may have
limited the start-up of new enterprises with financial assistance of Structural Funds will give

14

important policy suggestions for incoming period of Cohesion Policy 2014-2020 in order to
reach the results of Europe 2020 strategy.

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2. Theory
There is a large amount of existing literature on the market of innovation and
entrepreneurship, the role of governments and institutions in that market, and the links
between regulation and innovative entrepreneurship. In this research the attention is focused
on the reasons that lead to the different number of start-ups supported by Structural Funds
made available from EU Cohesion Policy 2007-2013 – i.e. why the start of innovative
entrepreneurship is larger in some countries than others. Accordingly, the second chapter of
this thesis aimed to compose the theoretical background to answer the research question.
Firstly, an overview of the academic context for innovation and entrepreneurship is provided.
Secondly, the market of innovative entrepreneurship and its failure are explained. Thirdly,
relevance of the role of governments and the importance of institution accordingly to market
of innovative entrepreneurship and its failure are presented. In the fourth section, academic
relevance underlines the link between entry regulation and entrepreneurship. Moreover, the
impact of entrepreneurship on economic growth is explained. Finally, the need for taking into
account local regulations is put in academic context. A section containing the hypotheses that
leaded to the answer of the research question closes the chapter.
2.1 Innovation and Entrepreneurship
In the literature, and also in empirical context, innovation and entrepreneurship are two
concepts that often walk together. Stam (2008) suggested that entrepreneurship comes from
the intersection between innovation and self-employment. This definition is taken as a
starting point in this thesis. As suggested by the placement of entrepreneurship funds under
the area of innovation and RTD by European Commission, by supporting the growth of start-
up, Structural Funds support the growth of innovation, not only entrepreneurship. The field of
this paper is therefore innovation policies. The objective of innovation policies is to
encourage and facilitate the generation, application, and diffusion of new ideas (Stam, 2008).
By and far, as Acs (2006) suggested, the most popular vehicle for exploiting newly
discovered opportunities is the independent start-up.
Over 200 years of the study of entrepreneurship have provided many definitions of the
word entrepreneur (Bull & Willard, 1993). Historically, entrepreneurship has at least two

16

meanings. First, it refers to owning and managing a business. Second, entrepreneurship refers
to the behaviour of seizing an economic opportunity. Entrepreneurship is what happens at the
intersection of history and technology (Acs & Audretsch, 2003). It consists of all the
opportunities that have not been exploited (Acs, 2006). In their study “Towards a Theory of
Entrepreneurship”, Bull and Willard (1993) recommended the adoption of Schumpeter’s
definition of entrepreneurship for academic and policy-making purposes. The Schumpeter
economic outcome-based concept (from 1936) outlines that an entrepreneur creates value by
carrying out new combinations of ideas, causing discontinuity. Bull and Willard then offered
a tentative of entrepreneurship theory, extracted from anecdotal observations and extant
literature, in which they stated that a person will carry out a new combination causing
discontinuity under conditions of: task related motivation, expertise, expectation of personal
gain, and a supportive environment. The aim of this thesis is to investigate, according to Bull
and Williard’s (1993) statements, the supportive environment in which EU Cohesion Policy
operated in 2007-2013 period, with regards to innovative entrepreneurship.
2.2 The Market of Innovative Entrepreneurship
When speaking about the market of innovative entrepreneurship, this thesis refers to the
system in which innovation is exchanged between entrepreneurs and the society. The
allocation of goods in the free market of start-up entrepreneurs is not perfect. When
innovating entrepreneurs consider entering an industry, various forms of market failure can
arise. The possibilities of market failure arise mainly because of the unique characteristics
that this market possesses: innovation. When entrepreneurs bring with them new products,
new technologies, and new talents, that may compete and threaten the existence of existing
firms and raise a non-Pareto optimal situation in which the better-off individual is causing a
worse-off individual. Consequently, existing firms and government policies impose barriers
to entry to difficulties in appropriating the benefits of the innovation they bring to the market.
These barriers to entry can then give rise to inefficiencies and market failure in the field of
innovative entrepreneurship (Boadway and Tremblay, 2003).
The failure of the innovative entrepreneurship market consists specifically of the
inefficient allocation of innovation between entrepreneurs and society. To be precise, there is
a gap between the demand for innovation and the supply. In ideal conditions, the demand for
innovation should cover the costs for its supply and foster it in the free market. However, the

17

direct costs of procedures, and indirect costs linked to the fulfilment of bureaucratic
procedures and information investigation, violate the assumption that free market entry is
costless. As such, funding and access to capital to overcome entry market barriers are
fundamental.
According to the theoretical background presented by Boadway and Tremblay (2003), the
free market of innovative entrepreneurship in Europe failed because of the barriers to entry
established by governments and existing firms. When market fails, the government intervenes
to correct the failure. Consequently, European funds designed to promote innovation as part
of the European Union Cohesion Policy and Euro 2020 strategy, represent the subsidies
introduced by EU to correct the market failure of the free market of innovative
entrepreneurship. If it is considered that the failure is caused by governmental action during
the process of setting procedures, the market failure can be considered as a governmental
failure instead. Nonetheless, as previously mentioned, the number of start-ups supported by
Structural Funds varies a lot among member states (Figure 1). Considering that and the fact
that entrepreneurship is a characteristic of human action and can be found at any point in time
(Boettke and Coyne, 2007), the attention is shifted on the different barriers to entry set by
European countries.
2.3 The Role of Governments and the Importance of Institutions
According to Boadway and Tremblay' (2003), there ought to be, in principle, a role for
public policy to encourage innovative entrepreneurship. But how should governments
intervene to stimulate this market? Minniti (2008) claimed that only the market can determine
the optimal amount of entrepreneurship. Governmental policies can, however, contribute
actively to the development of an institutional setting that encourages productive
entrepreneurship. As Stam (2008) suggested, the prerogative that governments should care
about the spread of innovation and the growth of entrepreneurship is largely accepted. In
order to tackle the key problems affecting the growth of innovation, government
interventions should stimulate seed capital and early stage capital to avoid financial
constraints to invest in the development of new technology (Stam, 2008). Structural Funds
devolved to support start-ups in EU Regional Policy 2007-2013 represent European
intervention to stimulate the birth and growth of innovative entrepreneurship to invest in the
development of innovation and new technologies.

18

The renewed need for effective entrepreneurship policies rekindled the debate about how
government can foster entrepreneurial activity (Minniti, 2008). As mentioned before,
entrepreneurship is a characteristic of human action and can be found at any point in time.
What matters for the spread of start-ups are institutions, that dictates the ultimate effect of
entrepreneurship on the economy via the allocation of entrepreneurial resources (Boettke &
Coyne, 2007). The total supply of entrepreneurs has been found to be relatively constant
across societies. The productive contribution of entrepreneurial activity varies because of its
allocation between desirable activities (Baumol, 1996). Accordingly, more necessary and
required activities contribute positively in terms of productivity of entrepreneurial activity.
Since entrepreneurship is the mechanism through which economic growth takes place,
institutions – such as the policy environment – need to allocate entrepreneurial efforts. The
government has, therefore, the power of influencing entrepreneurial activity (Minniti, 2008).
Furthermore, according to Amorós (2009), entrepreneurship is the outcome of human
behaviour and the institutional environment. In this case, government institutions will either
enhance or not enhance entrepreneurial activities. The quality of institutions is, therefore, a
relevant factor for the distribution and type of entrepreneurial activities. As government
institutions can clearly influence the rate of entrepreneurship, unnecessary barriers and
controls that hamper entrepreneurial activities could be removed.
Concluding, as Audretsch (2004) suggests, the mandate for public intervention in the
market of innovative entrepreneurship can only be the result of fundamental market failures.
According to the literature on the topic, European intervention on the market of innovative
entrepreneurship is accepted as a way to allocate entrepreneurial resources. One of the central
goals of public policy common among all modern economies is the generation of growth and
the creation of employment. Empirical evidence surveyed in the work of Carree and Thurik
(2003) suggested that countries which have experienced an increase in entrepreneurial
activity have also enjoyed higher rates of growth (Carree & Thurik, 2003). Consequently,
governments seeking to stimulate their economies should reduce constraints on
entrepreneurship (Acs et al., 2004; Minniti, Bygrave, & Autio, 2005). Moreover, as Minniti
(2008) claimed, government policy should shape the institutional environment in which
entrepreneurial decisions are made (Minniti, 2008).

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2.4 Entry Regulation and Entrepreneurship
Academic evidence suggests that governments should intervene to support innovative
entrepreneurship by removing obstacles that hamper entrepreneurial activities. The attention
is now focused on entry regulation, i.e. the set of procedures governing the entry of new or
international ventures. Baumol (1996), in his paper “Entrepreneurship: Productive,
Unproductive, and Destructive”, claimed that regulation should allocate productive,
unproductive, and destructive entrepreneurship. In the text it is hypothesised that productive
contribution of the society’s entrepreneurial activities varies much more because of the
allocation between productive activities such as innovation and unproductive activities such
as organised crime. This allocation is influenced by the payoffs that society offers.
Accordingly, the allocation of productive and unproductive activities influences the
productivity of the contribution that entrepreneurship gives to society. This implies that
policy can influence the allocation of entrepreneurship more effectively than it can influence
it supply. But to what extent entry regulation is good for entrepreneurship? Puia and Minnis
(2007) suggested that the regulation of entry is particularly important for entrepreneurship.
Accordingly, it has been proved that countries where levels of entrepreneurship are higher
tend to be associated with lower levels of entry regulations.
Using a comprehensive database of European firms, Klapper, Lauven, and Rajan (2006),
studied the effect of market entry regulations on the creation of new limited firms. They
found that costly regulation hampers the creation of new firms, especially in industries that
should naturally have high entry, like the market of innovative entrepreneurship.
Subsequently, they compared high-entry-regulated Italy and the low-entry-regulated United
Kingdom. They found that firms start out larger when young in Italy, but grow more slowly
so that firms in United Kingdom are about twice as large. This suggests that Italy has small
firms not because there is too much entry but because there is too little (Klapper et al., 2006).
According to Desai et al. (2003), entry regulation has a negative impact on firm entry.
Klapper et al. (2006) results claim that the value added per employee in naturally “high-
entry” industries grow more slowly in countries with high entry barriers. However, the effects
of entry regulations are seen primarily in developed countries or countries where there is little
corruption. In developing countries or countries where corruption is a serious problem – e.g.
Italy – entry regulations are unlikely to help screen out offenders. To the extent that such

20

regulations increase the cost of entry, there should be merit to reduce the regulatory
requirements substantially.
Finally, with a study on the regulation of entry of start-up firms in 75 countries, Djankov
et al (2000) suggested that regulation of entry is not associated with higher quality products,
better pollution, or health outcomes. Nor is strongly associated with higher profitability of
firms. On the other hand, stricter regulation of entry is associated with sharply higher levels
of corruption and a greater relative size of the unofficial economy. To measure entry
regulation they took into account three variables: the number of procedures that firms must
go through, the official time required to complete the process, and its official costs. They
concluded that entry appears to be regulated more heavily by the less attractive governments
in terms of innovative entrepreneurship, and such regulation leads to unattractive outcomes.
The principal beneficiaries of those regulations, if any, are politicians and bureaucrats.
To conclude, theoretical relevance suggests that high levels of entry regulation have a
negative impact on firm entry. Consequently, high entry regulation of member states is a
factor influencing the outcomes of countries that supported low numbers of start-ups with
Structural Funds of EU Cohesion Policy 2007-2013. The EU offers a solution for one specific
aspect of market failure in innovative entrepreneurship – i.e. access to capital. This, however,
is expected to have a negative correlation with the level of regulation of member states.
Moreover, academic literature on the link between entrepreneurship and economic growth
raise social relevance on the issue.
2.5 Entrepreneurship and Economic Growth
In the latest years, the enduring claim that entrepreneurship is an important engine for
growth and development has been confirmed in many studies. The creation of new ventures
may contribute to the economic performance of countries and regions because entrepreneurial
activities introduce innovation, create competition, and enhance rivalry (Audretsch &
Keilbach, 2004; Wong, Ho, & Autio, 2005). As Acs (2006) stated, entrepreneurs create new
businesses, and new businesses in turn create jobs, intensify competition, and potentially
increase productivity through technological changes. High measured levels of
entrepreneurship will thus translate directly into high levels of economic growth.
Entrepreneurship is the mechanism through which economic growth takes place (Minniti,

21

2008). It is positively related to growth in terms of size and age and it is at the heart of
national advantage (Carree & Thurik, 2003).
More comprehensively, Acs and Szerb (2007) stated there was a U-shaped relationship
between the level of development and the rate of entrepreneurship. A positive effect of
entrepreneurial activity was found for highly developed countries. A negative effect was
found for developing nations. This suggested that in developed countries entrepreneurship
has a positive effect on economic growth, while in developing countries there is a negative
relation between economic growth and entrepreneurial activity. Moreover, entrepreneurship
can contribute to economic growth by serving as a mechanism that permeates the knowledge
filter. Acs (2006) set a distinction between “necessity entrepreneurship”, which is having to
become an entrepreneur because you have no better option, from “opportunity
entrepreneurship”, which is an active choice to start a new enterprise based on the perception
that an unexploited or underexploited business opportunity exists. He concluded that
necessity entrepreneurship has no effect on economic development while opportunity
entrepreneurship has a positive and significant effect (Acs, 2006).
Hence, by understanding the reasons that hamper the support of innovative
entrepreneurship by Structural Funds made available by EU Regional Policy 2007-2013, it
would be possible to underline factors that obstruct growth and development among member
states. Moreover, according to Acs’ (2006) view of necessity and opportunity
entrepreneurship, Amorós (2009) concluded that the quality of institutions that contribute to
entrepreneurial environment has significant and positive effects on opportunity
entrepreneurship. Similarly, it has significant and negative effects on necessity
entrepreneurship. Consequently, it has been important in this thesis to distinguish between
necessity and opportunity start-ups supported by EU Cohesion Policy 2007-2013 instruments.
2.6 One Size Does Not Fit All
In the frame of a European Policy – such as the Regional Policy, crossing national and
regional regulations – it is important to point out that an ideal model does not exist for
innovation policies (Tödtling & Trippl, 2005). If entrepreneurial efforts are to be allocated to
productive activities, policy strategies, with respect to entrepreneurship, need to be tailored to
specific institutional context of each economic region (Wagner & Sternberg, 2004). Policy

22

design, as Minniti (2008) claimed, needs to take into account local differences. Accordingly,
it is important to assess the different impacts of high and low regulations of entry that
member states adopt when facing Structural Funds to support innovative entrepreneurship in
the frame of Regional Policy 2007-2013.
In the wake of strong competition from developing countries, the issue of policies aimed
at the internationalisation of entrepreneurial ventures have also attracted significant attention
from various governments, and many countries regulate or restrict the movement of
international business (Djankov et al., 2000). Most of those policies constrain the creation of
tariffs or tax regimes that avoid penalising venture capital profits, and in instruments such as
export credits and export guarantees (Minniti, 2008). Accordingly, EU Cohesion Policy
should take into account local entry regulation in the allocation of its funds, in order to
allocate them to productive entrepreneurship and have the best outcomes in terms of
innovative entrepreneurship supported with Regional Policy instruments.
2.7 Hypotheses
Nurturing and growing innovative start-ups have become an important point on the political
agenda (Clarysse & Bruneel, 2007). Innovation ranks highly in policy agendas today, both in
the fields of industrial and regional policy (Tödtling & Trippl, 2005). As stated in the
presented theoretical framework, the aim of this thesis has been to understand to what extent
entry regulation of European member states influenced the outcomes of EU Regional Policy
2007-2013 in terms of number of start-ups supported by Structural Funds. Italy and the
United Kingdom have been taken into account as examples of high-entry-regulated and low-
entry-regulated countries according to the study of Djankov et al (2000). Theoretical
relevance is to add academic significance to the theme of entry regulation and innovative
entrepreneurship. Social relevance is to provide evidence of the regulatory instruments
hampering economic growth and development. The hypothesis of the quantitative analysis of
this thesis is that high level of entry regulation leads to fewer start-ups supported with
Structural Funds made available by EU Cohesion Policy. Considering qualitative analysis,
the hypothesis is that entrepreneurs in high-entry-regulated environment – such as Italy,
experienced regulation as a major barrier to start a business while entrepreneurs in low-entry-
regulated environment – such as United Kingdom, generally face less complications in the
experience of starting up a business.

23

3. Research Design
The aim of this research paper has been to evaluate the influence of the regulation of entry
the market of innovative entrepreneurship on the number of start-ups supported with
Structural Funds from EU Cohesion Policy in 2007-2013. The hypothesis of this thesis is that
low-entry-regulated countries supported more start-ups than high-entry-regulated countries.
In order to reach this purpose both a quantitative and a qualitative analysis have been
conducted. The quantitative analysis focused on matching the entry regulation with the
results of EU Cohesion Policy 2007-2013 in terms of start-ups supported, in order to have an
overview of the impact of the former on the latter. Conversely, the qualitative analysis
investigated high-entry-regulated Italy and the low-entry-regulated United Kingdom to better
understand how entry regulation directly influences the experiences of starting up a business
and to explore whether other factors may explain the different outputs of Cohesion Policy in
terms of start-ups supported beyond the entry regulation.
3.1 Quantitative Analysis
The aim of the quantitative analysis has been to investigate the impact of the entry
regulation on the results of EU Cohesion Policy 2007-2013 in terms of number of start-ups
supported. Dependent variables, independent variables, and method of the analysis are now
presented in order to allow replicate the study.
3.1.1 Dependent Variables
To test the effect of entry regulation on innovative entrepreneurship during 2007-2013 EU
Regional Policy, two dependent variables have been considered in different analyses: the
number of start-ups supported per 100,000 population by Structural Funds during that period
and the amount of money invested in innovation & RTD divided by the number of start-ups
supported in the same period.
The data regarding the number of start-ups supported by European Union Cohesion Policy
2007-2013 is retrieved from the open data platform made available from European

24

Commission that provides information about the investments made and the results obtained.3
The number of start-ups supported is measured by tracking the number of enterprises created
which received financial aid or assistance, i.e. consultancy or guidance from Structural Funds
or Structural Funds financed facilities. The legal form of enterprises may be various – e.g.
self-employed person or partnerships. In order to consider the demographic differences of
member states and to make the analysis more accurate, the number of start-ups supported has
been related to data about the population of European countries made available from Eurostat
database in 2014. 4
This has been done to have an indirect control of countries size in the
analyses – small countries cannot create as many start-ups as large countries regardless of
entry requirements. As a result, the first dependent variable considered in quantitative
analysis is the number of start-ups supported per 100,00 population by Structural Funds. In
Table 1 it is possible to see a descriptive statistic of the dependent variables that have been
considered in the quantitative analysis.
Table 1. Descriptive Statistics of Dependent and Independent Variables.
Mean S.D. Min Max
Number of Start-Ups
Supported per
100,000 Population
26,9 44,93 0 184,84
Amount of Money
Invested in
Innovation & RTD
per Number of Start-
Ups Supported
Procedures to Start a
Business (number)
Time Required to
Start a Business
(days)
Cost of Business
Start-Up Procedures
(% of GNI per
capita)
77.779.795
6,27
18,95
5,99
241.978.002
2,6
15,05
5,72
22.694
3
4
0,06
992.400.000
12,43
67,5
19,6
Cases (N) 23
3
https://cohesiondata.ec.europa.eu/en/stat/goals/yiiu-‐w39m/77ex-‐fmpt/2vfw-‐tpvr.

4
http://ec.europa.eu/eurostat/data/database.

25

Since the number of start-ups supported with Structural Funds in member states is an
absolute number that does not take into account the different amount of money that each
member state devoted to entrepreneurship, to make the analysis even more accurate this data
has also been matched with the breakdown in Innovation & RTD in the 2007-2013 period of
EU Cohesion Policy of each member state. The breakdown in Innovation & RTD is a data
made available by European Commission that shows the amount of money invested in this
field. Since it is not possible to have precise data about the amount of money that each
country invested in entrepreneurship, the breakdown in Innovation & RTD has been taken
into account to have an overview on the different amount of money invested in the field.
More precisely, the amount of money that each country invested in innovation and research
and technological development has been divided with the number of start-ups supported with
Structural Funds made available by European Commission. The matched data allows
therefore understanding of the amount of money each country invested in Innovation & RTD
per start-up supported. Both this final data and the number of start-ups supported by
Structural Funds of Regional Policy are considered dependent variables in the analyses.
Concluding, in quantitative analysis both number of start-ups supported per 100,000
population and amount of money invested per start-up supported by Structural Funds have
been considered as dependent variables. This has been done in order to take into account
demographic differences and the different amount of money that each country invested in
supporting innovative entrepreneurship. Since it is not possible to know the precise amount
of money that each country devolved to entrepreneurship, the second dependent variable is
considered because it takes into account at least the different amount of money that each
country invested in innovation and research and technological development.
3.1.2 Independent Variables
To measure entry regulation the study of Djankov, La Porta, Lopez-de-Silanes, and
Shleifer (2000) has been taken into account. The authors defined entry regulation using three
measures: the number of procedures that firms must go through, the official time required to
complete the process, and its official cost. In their research design, to define the number of
procedures that firms must go through, they kept track of all the procedures that are required
by law to start a business. A separate step in the start-up process counted as a procedure only
if it required that the entrepreneur interacts with outside entities: state and local government

26

offices, lawyers, auditors, notaries, company seal manufacturers, etc. Each office that the
entrepreneur visited counted as a separate procedure. The “same building” criterion has been
used to consider offices in different buildings as distinct. To measure time, they collected
information on the sequence in which procedures were completed and relied on official
figures to determine how many business days it took to complete each step. They adopted a
“perfect efficiency” approach when estimating the length of the registration process. Finally,
they estimated the cost of entry regulation based on all identifiable official expenses: fees,
costs of procedures and forms, photocopies, fiscal stamps, legal and notary charges, etc.
The three variables considered by Djankov et al (2000) are considered in this thesis to
define entry regulation for the same purpose. Since the paper of those authors is fifteen years
old, their data about number of procedures that firms must go through, the official time
required to complete the process, and its official cost are not considered. Nonetheless, the
same approach to design entry regulation is replicated by retrieving data in the updated form
that follows.
The number of procedures to start a business is retrieved from the World Bank. The World
Bank made available a database on the number of start-up procedures required to start a
business, including interactions to obtain necessary permits and licenses and to complete all
inscriptions, verifications, and notifications to start operations.5
The database concerns
businesses with specific characteristics of ownership, size, and type of production. Since this
data is available on a yearly basis in order to compare with the total number of start-ups
supported by Structural Funds of European Union on EU Cohesion Policy 2007-2013, an
average of the data between 2007 and 2013 is considered.
Regarding the time required to start a business, the World Bank provides the same data in
terms of days.6
Time required to start a business is the number of calendar days needed to
complete the procedures to legally operate a business. If a procedure can be sped up at
additional cost, the fastest procedure, independent of cost, is chosen.
5
http://data.worldbank.org/indicator/IC.REG.PROC/countries.

6
http://data.worldbank.org/indicator/IC.REG.DURS/countries.

27

Finally, to retrieve the cost of starting up a business, the data “Cost of business start-up
procedures” made available by World Bank is considered.7
The cost to register a business is
normalised by presenting it as a percentage of gross national income (GNI) per capita.
In Table 1 it is possible to see a descriptive statistic of the independent variables that have
been used to define entry regulation of European countries. The numbers are very different
among member states underlining very different situations and consequently different levels
of entry regulation. The number of procedures to start a business the number varies from the
3 of Sweden and Finland to the 12.43 of Greece with a mean average of 6.27 across Europe.
Differences are even wider for the other two variables. Starting a business in Europe may
take from 4 days (Belgium) to 67.5 days (Romania) with an average of 18.95. Finally, the
cost of business start-up procedures goes from 0.06% of GNI per capita in Denmark to 19.6%
in Greece with an average of 5.99%. The data has been retrieved by making an average of
available numbers between 2007 and 2013 – according to the period of EU Cohesion Policy.
In Table 2 it is possible to see a complete overview of dependent and independent
variables used. Countries such as Bulgaria, Croatia, Cyprus, and Ireland are not included in
the analysis because of the lack of data regarding the number of start-ups supported by
Structural Funds (Bulgaria, Croatia, and Cyprus) and the breakdown in Innovation and
Research and Technological Development (Ireland). The table shows all the member states
considered in the quantitative analyses, the number of start-ups they supported with
Structural Funds, the breakdown in Innovation & RTD in million €, the consequent amount
of money that each country invested in Innovation & RTD per start-up supported, and the
three independent variables.
7
http://data.worldbank.org/indicator/IC.REG.COST.PC.ZS.

28

Table 2. Country Level Data on Entrepreneurship and Entry Regulation.
Member State Start-Ups
Supported
per 100,000
Population
(number)
Breakdown
in Innovation
& RTD
(million/€)
Investments
in Innovation
& RTD per
Start-Up
Supported
(million/€)
Procedures
to Register a
Business
(number)
Time
Required to
Register a
Business
(days)
Cost to
Register a
Business (%
of GNI per
capita)
Austria 0,8 355,8 5,232 8 25 5,1
Belgium 22,62 299 0,118 3 4 5,26
Czech Rep. 0,06 3971,7 661,95 9,14 19,36 9,07
Denmark 63,67 158,7 0,044 4 5,71 0,06
Finland 118,96 468,2 0,072 3 14 1,01
France 2,31 2213,7 1,457 5 6,57 0,94
Germany 1,28 4936 4,764 9 15,86 5,01
Greece 21,42 2437,1 1,043 12,43 18,71 19,6
Hungary 20,85 2125,9 1,033 4,29 6,14 9,6
Italy 6,71 6065,5 1,488 6,43 8,14 17,5
Latvia 45,37 752,8 0,829 5,14 15,14 2,24
Lithuania 0 992,4 - 6,29 21,14 2,24
Luxemburg 0 18 - 6 20,57 3,84
Malta* 4 76,2 4,482 11 39,5 11,73
Netherlands 32,22 299,6 0,055 5,57 7 5,57
Poland 4,16 9303,6 5,885 6,86 31,43 15,96
Portugal 5,03 4505,1 8,581 4,57 4,07 4,73
Romania 0,53 1127,8 10,640 5,29 67,5 3,09
Slovakia 6,02 1299,9 10,483 6,57 18,43 2,27
Slovenia 0,31 1012,6 59,565 3,57 15,57 1,23
Spain 16,11 5559,2 0,742 10 45 10,6
Sweden 184,84 404,6 0,023 3 16 0,57
United
Kingdom
61,35 1913,6 0,049 6 11,07 0,67
* Malta: data regarding procedures to register a business, time required to register a business, and cost to
register a business not available before 2011.
3.1.3 Method
In order to model the relationship between the scalar dependent variable and the
explanatory variables, Spearman correlation coefficient has been used. At first scatterplots
have been designed to give graphical evidence about the relations between the considered

29

variables among the different member states. Consequently, the dependent variables – i.e. the
number of start-up supported per 100,000 population by Structural Funds and the investments
in Innovation & RTD per start-up supported – have been matched with each independent
variable – i.e. procedures to register a business, time required to register a business, and cost
of business start-up procedures – to test the correlation between each explanatory variable
and the dependent variables. Successively, a multiple linear regression analysis has been
conducted to model the relationship between the independent variables that form entry
regulation and the dependent variable. Because of the small sample size, next to multiple
regression analysis, rank transformed regression analyses have been conducted. According to
Cronan, Empley, and Perry (1986) and Headrick and Rotou (2001), the rank regression
technique is more theoretically correct than conventional multiple regression and produces a
better model with more accurate results with small samples and in context of multiple
regression analysis when the assumption of normality is violated. In all the analyses, by
underlining the Spearman coefficients, the coefficients of determination, the standard errors,
and the p levels, it has been possible to test whether or not the explanatory variables are
related to the dependent variables and whether or not the model used explains the data.
Spearman coefficient has been considered in the simple linear regression analyses because of
the small sample taken into account and to take care of non-normality in the sample –
including possible outliers.
3.2 Qualitative Analysis
The qualitative analysis aimed to confirm the theory regarding the impact of entry
regulation on innovative entrepreneurship and the results of quantitative analysis and to
explore whether other factors may explain the different outputs of Cohesion Policy in terms
of start-ups supported beyond the entry regulation. In order to do that, I analysed how the
different barriers to enter the market of innovative entrepreneurship imposed by government
and existing firms and the funds provided by EU Cohesion Policy in 2007-2013 period
influenced the experience of starting up a business. Two countries have been chosen as case
studies: a high-entry-regulated country such as Italy and a low-entry-regulated country such
as the United Kingdom – according to the study of Klapper, Lauven, and Rajan (2006).
Interviews have been conducted with five entrepreneurs from Italy and five entrepreneurs
from United Kingdom; a list of the interviewees with the dates of interviews is available in
the Appendix. Answers have been coded to reach the purpose of the analysis. This

30

methodological approach allowed a systematic and objective testing of the theory that entry
barriers are perceived differently in these two countries and are indeed perceived differently
as obstacles to starting up a business.
Interviews were conducted to test the direct impact of barriers to entry and funds provided
by EU on the process of starting up businesses in the two countries, to explore whether other
factors explain different outputs of Cohesion Policy in terms of start-ups supported, and to
underline the elements that differ Italy and United Kingdom in terms of start-up friendly
environments. Due to time and length limits, five founders of start-ups from Italy and five
founders of start-ups from the United Kingdom were interviewed. To find the respondents,
entrepreneurs were identified through Facebook groups – i.e. “Startup Italia” and “Startup
UK”.
The first five respondents from each country were chosen for the interview stage. This
approach was used to maintain the process of selecting respondents at random. The Italian
sample consisted of five males among who one was under 30 years old, two between 30 and
40 years old, and two between 40 and 50 years old. Moreover, one was based in the north of
the country, two in the centre, and two from the south. Finally, four respondents out of five
were operating in the IT sector while one was in packaging sector. For the UK, the sample
was comprised of five males with three under 30 years old and two between 30 and 40 years
old. Three of them came from the south while two came from the north. Finally, four of the
UK interviewees operated in the IT sector while one operated in the telecommunications
sector. Interviews were conducted in Italian with respondents from Italy and in English with
interviewees from the United Kingdom.
The interview stage focused on three elements. Firstly, underlining how entry regulation
and its three measures – number of procedures that firms must go through, official time
required to complete the process, and its official cost (Djankov et al., 2000) are differently
perceived by entrepreneurs in high and low entry regulated countries. Secondly, to what
extent the measures of entry regulation represent a barrier that might encourage or discourage
the entry in the market of innovative entrepreneurship during the experience of starting up a
business. Lastly, how government intervention and in particular Structural Funds made
available by EU Cohesion Policy 2007-2013 actively helped entrepreneurs in overcoming
barriers raised by entry regulation.

31

The semi-structured format was used as research method to reach the mentioned purposes.
While a structured interview has a rigorous set of questions which does not allow one to
divert, a semi-structured interview is open, allowing new ideas to be brought up during the
interview as a result of what the interviewee says. The interviewer in a semi-structured
interview generally has a framework of themes to be explored. Accordingly, the set of
interviews were prepared with seven questions that allowed space for more exploratory
discussion. Firstly, an ice-breaking question about the reasons that lead the interviewee to
choose the entrepreneurial path was asked – the results linked to the opportunity and
necessity analysis of entrepreneurship carried out by Acs (2007). Secondly, a general
question about the problems faced during the process of starting up a business aimed to
underline the different barriers to enter the market of innovative entrepreneurship
encountered by start-uppers. This question included a sub-question related to the three precise
measures of entry regulation. Thirdly, a question about the possibilities to overcome barriers
to entry paved the way to speak about public subsidies. The fourth question, as a consequence
of the third one, varied on the basis of the previous answer. For the fifth question,
interviewees were asked about their experience of getting funds. Finally, the sixth question
was asked only to respondents that did not mention funds coming from EU before.
Respondents were interviewed individually through Skype. To keep the interviews
manageable in terms of time and length, the maximum range of time considered for the
conversation was around 20 minutes. Furthermore, interviews were recorded and transcribed
with the approval of interviewees. This resulted in ten transcripts of interviews, five for
Italian start-ups and five for start-ups from the United Kingdom. The next stage consisted in
the coding of interviews. This phase allowed highlighting the answers to the questions, the
important elements that allowed the theory testing process that answered the research
question.
In conclusion of the research design chapter, while quantitative analysis allowed
understanding the impact of entry regulation on the outcomes of EU Cohesion Policy 2007-
2013 in terms of start-ups supported with Structural Funds, the qualitative approach
investigated the experience of starting up a business in low and high entry regulated countries
such as Italy and the United Kingdom. A particular attention on a clear distinction between
objective data and their interpretation has been posed in all the analyses. Both analyses
helped answering the research question and reaching the purposes of this thesis.

32

4. Analysis
4.1 Quantitative Results
In order to model the relationship between the scalar dependent variable and the
explanatory variables, Spearman correlation coefficient has been taken into account. At first
scatterplots were designed to give graphical evidence about the relations between the
considered variables before calculations. Successively, the dependent variables – i.e. number
of start-ups supported per 100,000 population by Structural Funds of Regional Policy and
investment in Innovation & RTD per start-up supported by Structural Funds – matched with
each independent variable – i.e. procedures to register a business, time required to register a
business, and cost of business start-up procedures – separately with Spearman correlation
coefficient to test the correlation between each explanatory variable and the dependent
variables. Moreover, a multivariate linear regression analysis was conducted to model the
relationship between the independent variables that form entry regulation and the dependent
variables in order to test whether regulation of entry impacted on the number of start-ups
supported by Structural Funds of EU Cohesion Policy between 2007 and 2013. Because of
the small sample size, next to multiple regression analysis, rank transformed regression
analyses have been conducted. In all the analyses, by underlining the Spearman coefficients,
the coefficients of determination, the standard errors, and the p levels, it has been possible to
test whether or not the explanatory variables are significantly related to the dependent
variables and whether or not the model used explains the data. Considering the smallness of
the dataset, Spearman R was taken into account to take care of the non-normality problem.
To give graphical evidence about the relations between the considered variables before
calculations, scatterplots were designed. Results have been divided in two categories. In the
first category the considered dependent variable is Number of Start-ups Supported per
100,000 population by Structural Funds made available by EU Cohesion Policy instruments
in 2007. This variable was matched with the number of procedures to register a business (i),
the time required to register a business (ii), and the cost of business start-up procedures (iii).
In the second category, the dependent variable that was matched with the explanatory
variables is Investments in Innovation & RTD per Start-Up Supported (million/€). Also in
this case scatterplots were disposed regarding the relation between the dependent variable

33

with the number of procedures to register a business (iv), the time required to register a
business (v), and the cost of business start-up procedures (vi).
Figure 2. Number of Start-Ups Supported per 100,000 population by Structural Funds and independent
variables.
Considering Figure 2, it is possible to note the negative relations between the dependent
variable representing the number of start-ups supported per 100,000 population by EU
Cohesion Policy instruments between 2007 and 2013 and number of procedures to start a
business (i), time to register a business (ii), and cost to register a business (iii). This evidence
suggests that countries where the number of procedures, the time to register, and the costs to
register needed to start a business are higher supported less start-ups in the 2007-2013 period
with Structural Funds made available by the EU. Taking into account Italy and the United
Kingdom (Klapper, Laeven, and Rajan, 2004), the former supported 4,076 start-ups with
Structural Funds between 2007 and 2013 with an average of 6.43 procedures required to start
a business, 8.14 days, and 17.5% of GNI per capita. Similarly, the latter supported 39,453
start-ups that needed to complete an average of 6 procedures to start up, wait 11.07 days, and
spend just the 0.67% of GNI per capita to register their business.
As it is possible to see in Figure 3, there is a positive relation between breakdown/start-ups
and the numbers of procedures to start a business (iv), a slightly positive relation between

34

breakdown/start-ups and time to register a business (v), and a slightly negative relation
between breakdown/start-ups and cost to register a business (vi). Accordingly, in countries
with more procedures required to start a business, the amount of money invested for each
start-up supported is higher. Nonetheless this does not mean that all the money goes into
start-ups – i.e. efficiency, but that in other countries money goes in other activities, not on
start-ups, indicating also different countries priorities. Additionally, considering European
situation, countries where more time is needed to start a business need less money invested to
support start-ups. Finally, it is controversial to note that the tendency regarding
breakdown/start-up and cost to register shows that as long as the cost to register a business
increases, the amount of money invested in Innovation & RTD to generate a start-up
decreases. It can be concluded that there is not a strong casual correlation between the
dependent variable Investments in Innovation & RTD per Start-Up Supported by structural
funds made available by EU Cohesion Policy 2007-2013 and the considered independent
variables to represent entry regulation according to Djankov, La Porta, Lopez-de-Silanes, and
Shleifer (2000). Nevertheless, some indicators – i.e. the number of procedures required to
start a business, seem to be more correlated to the dependent variables. Calculations are
expected to clarify those connections.
Figure 3. Investments in Innovation & RTD per Start-Up supported and independent variables.

35

Considering calculations, as hypothesized, the relationship between entry regulations and
number of start-ups is negative, varying from weak to moderate. As it is possible to see in
Table 3, considering the outputs related to the dependent variable number of start-ups
supported per 100,000 population, the Spearman coefficients with the independent variable
costs to register a business was included between the values of 0 and -0.3, showing a weak
negative correlation between the dependent variable and the explanatory variable considered.
On the other hand, Spearman coefficient with the independent variables time to register a
business and procedures to register a business were included between -0.3 and -0.7, showing
a moderate negative correlation between number of start-ups supported and those
explanatory variables. In particular, it is possible to notice that, considering the relationship
between number of start-ups and costs to register, the negative correlation is weak with
Spearman coefficient close to 0.2 (R=-0.1966). When considering the relationship of the
dependent variable with procedures to register Spearman coefficient is higher (R=-0.339),
showing already a moderate correlation. Finally, the correlation between number of start-ups
and time required is largely negatively moderate (R=-0.479). It can be concluded that, the
time and the procedures required to register a business have a moderate negative impact on
the number of start-ups supported. Furthermore, there is a weak correlation between the costs
to register a business and the number of start-ups supported. Accordingly, it can be claimed
that 23% of the variance of number of start-ups supported per 100,000 population is
explained by time required to register, 11% by the procedures, and 3% by the costs.
Table 3. Spearman Correlation Coefficients.
Procedures to Register a
Business (number)
Time Required to
Register a Business
(days)
Cost to Register a
Business (% of GNI per
capita)
Start-Ups supported per
100,000 population
(number)
-0,3394269 -0,4797431 -0,1966403
Investments per Start-Ups
supported (million/€)
0,37467532 0,41688312 0,30649351
However, considering the investments in innovation & RTD per start-up supported, the
situation is different. The Spearman coefficient with all the independent variables, as
expected, are positive and included between the values 0.3 and 0.7, showing a moderate
positive correlation between the dependent variable and the explanatory variables. In

36

particular, it is possible to notice that, considering the relationship between investments in
innovation & RTD and procedures to register and time required to register the positive
moderate correlation is around 0.4 in both cases (R= 0.37 and R=0.42). When considering the
relationship of the dependent variable with costs to register Spearman coefficient is slightly
lower (R=0,30), on the limit of positive weak correlation. Moreover, according to the results,
it can be claimed that 9% of the variance of number of start-ups supported per money
invested is explained by entry costs, 17,37% by the time, and 14% by the number of
procedures. It can be concluded that, considering as a dependent variable the amount of
money invested in Innovation & RTD per start-up supported, all the independent variables
considered seem to have a moderate positive impact on the dependent variable.
Table 4. Multivariate Linear Regression Analysis Results. Dependent Variable: Number of Start-Ups Supported
per 100,000 populations.
Coefficient Standard Error P Level
Business
-5,88674 5,05005 0,25817
Time Required to
Register a Business
-0,1768 0,67387 0,79587
Costs to Register a
capita)
-0,90936 2,13637 0,67514
Constant 71,67021 25,4908 0,01155
Note: ****p<0,05; * p< 0,1
Table 5. Rank Transformed Regression Analysis Results. Dependent Variable: Number of Start-Ups Supported
per 100,000 population.
Business
-0,10409 0,34037 0,76307
Time Required to
Register a Business
-0,41612 0,26434 0,13196
Costs to Register a
capita)
-0,03011 0,26335 0,91016
Constant 18,19436 3,39349 0,00004
Note: ****p<0,05; * p< 0,1

37

Taking into account multivariate linear regression analysis, the results are visible in Table
4 and in Table 6. Considering the outputs related to the dependent variable number of start-
ups supported and the independent variables (Table 4), the high P levels made the results
based on Pearson methodology not reliable. Analogously, considering the results of
multivariate linear regression analysis of the explanatory variables with the dependent
variable investments in innovation & RTD per start-up supported (Table 6), the situation is
similar. Considering the outputs related to the dependent variable and the independent
variables in Table 6, it is possible to notice the high rates of P levels that leaded the results
not consistent.
Similarly, considering rank transformed regression analyses, the results are visible in Table 5
and in Table 7. Those analyses have been conducted next to multivariate linear regression
analyses because according to Cronan, Empley, and Perry (1986) and Headrick and Rotou
(2001), the rank regression technique is more theoretically correct than conventional multiple
regression and produces a better model with more accurate results with small samples and in
context of multiple regression analysis when the assumption of normality is violated.
Nonetheless, also this technique underlined no relation among variables. The reason can be
attributed to the small N and the possible strong correlation between the three independent
variables.
Table 6. Multivariate Linear Regression Analysis Results. Dependent Variable: Investments per Start-Up
Supported.
Business
19,51517 18,64558 0,31082
Time Required to
Register a Business
0,90635 2,41633 0,71252
Costs to Register a
capita)
-3,38202 7,97024 0,67697
Constant -44,03426 89,49665 0,62939
Note: ****p<0,05; * p< 0,1
NB: Lithuania and Luxemburg are not counted in the analysis because of the number of start-up supported
which would have compromised the results.

38

Table 7. Rank Transformed Regression Analysis Results. Dependent Variable: Investments per Start-Up
Supported.
Business
-0,0403 0,32506 0,90279
Time Required to
Register a Business
0,35484 0,25976 0,18974
Costs to Register a
capita)
0,23013 0,25532 0,37999
Constant 6,78218 3,61379 0,07686
Note: ****p<0,05; * p< 0,1
NB: Lithuania and Luxemburg are not counted in the analysis because of the number of start-up supported
which would have compromised the results.
In conclusion, quantitative analysis aimed to investigate the impact of entry regulation on
the results of EU Cohesion Policy 2007-2013 in terms of number of start-ups supported.
According to the scatterplots, countries with low rates of procedures to register a business,
time required to register a business, and cost of business start-up procedures generally started
more start-ups in EU Cohesion Policy 2007-2013 than countries with the highest rates of the
same indicators. Spearman correlation coefficients show moderate to weak negative
correlations between the number of start-up supported per 100,000 population by Structural
Funds from EU Regional Policy between 2007 and 2013 and the explanatory variables that,
according to Djankov, La Porta, Lopez-de-Silanes, & Shleifer (2000), represent the
regulation of entry. Time Required to Register a Business is the independent variable that,
among the other, seems to have the stronger negative impact on the Number of Start-Ups
Supported. On the other hand, Costs to Register a Business has a weak negative correlation
with the dependent variable. Furthermore, when considering as dependent variable
Investment in Innovation & RTD per Start-Up Supported the situation is different. The
Spearman coefficient with all the independent variables shows moderate positive correlation
between the dependent variable and the explanatory variables that represent the regulation of
entry. To conclude, the claim that entry regulation hampers the creation of new firms
(Klapper, Laeven, and Rajan, 2004) is confirmed in the frame of start-ups supported among
European countries during EU Cohesion Policy 2007-2013.

39

4.2 Qualitative Results
The interviews were conducted to investigate whether and how entry regulation directly
influenced the experiences of starting businesses in Italy and the United Kingdom. In
addition, they explored whether other factors might explain the different outputs of Cohesion
Policy in terms of start-ups supported, beyond the entry regulation. The interviews gave
valuable insights. As aforementioned, qualitative analysis focused mainly on three elements.
Firstly, underlining how entry regulation and its three measures – number of procedures that
firms must go through, official time required to complete the process, and its official cost
(Djankov et al., 2000) are differently perceived by entrepreneurs in high and low entry
regulated countries. Secondly, to what extent the measures of entry regulation represent a
barrier that might encourage or discourage the entry into the market of innovative
entrepreneurship during the experience of starting up a business. Lastly, how government
intervention and in particular Structural Funds made available by EU Cohesion Policy 2007-
2013 actively helped entrepreneurs in overcoming barriers raised by entry regulation.
4.2.1 Italy
Three interviewees claimed their entry into the market of innovative entrepreneurship was
driven by the necessity of starting a private activity and running their own business, while
two respondents stated that their start-up is a consequence of the innovation they are bringing
in trying to solve an actual problem or lack they saw in the society. Therefore, according to
Acs (2006), it can be claimed that the majority of the interviewed belong to the group
“necessity entrepreneurship” – becoming an entrepreneur because you have no better option.
“In Italy there are no opportunities for entrepreneurs. The support is practically not existent
and when speaking about starting a company costs are incredibly high and bureaucratic
procedures very long and slow.” [Respondent 1]
“The process of starting up a business in Italy is definitely not smooth. Bureaucracy, and
excessive costs are a big problem.” [Respondent 3]
One of the main results is that two respondents out of the five that took part in the
interview stage started their start-up abroad – in the United Kingdom – as a solution to

40

overcome the problems they faced in starting up their business in Italy. Thus, it can be
claimed that the barriers to enter the market of innovative entrepreneurship discouraged the
entry of two Italians respondents out of the five. In this frame, barriers to entry hampered the
start up of new businesses in Italy and lead entrepreneurs to change their country in order to
continue their experience.
“[I] solved the problems related to starting my business in Italy by going abroad and looking
for opportunities outside my country.” [Respondent 1]
“The obstacles are not impossible but the environment is not easy, it is something you have to
overcome. There are problems of environment and mentality but there is not just a single
difficulty. A lot of things together make you waste a lot of time.” [Respondent 4]
Considering the problems faced during the process of starting up a business in Italy, the
main barriers to enter the market of innovative entrepreneurship are underlined as follows.
The main factors that emerged from the interviews were: excessive costs and lack of
economic support, slow and long bureaucratic procedures, excessive regulation and
unfriendly environment for start-ups, and lack of information. Each of those factors were
underlined by at least three respondents during the interviews. Excessive taxation and slow
times of procedures were mentioned by two interviewees. Factors like lack of support by the
government, difficulty in finding office space, unclear laws and regulation, and lack of
human capital emerged from one respondent each. It is important to note that all respondents
faced problems during the process of starting up a business in Italy. Thus, considering this
sample, it can be argued that barriers to entry such as high costs, slow and long bureaucratic
procedures, and excessive regulation hampered the creation of new business in Italy and lead
two interviewees to start up their business abroad.
“I know about public and European funding but I am not interested. They are badly managed
and I don’t want to deal with those people.” [Respondent 2]
“There is not that much money available from pubic and European funds. The situation in
trying to get the money is complex and the procedures are very complicated.” [Respondent
5]

41

Moreover, when asking about the strategies that were used to overcome those problems,
none of the interviewees mentioned the possibility of obtaining public funding from the
government or the EU as a way to overcome the lack of money. None of the interviewees
received public funding during the experience of starting a business and when it was directly
asked if the possibility of securing public funding had been taken into account, only one
respondent out of the five answered affirmatively. Trying to get public funds was considered
to be a waste of time by most of the Italian respondents. In addition, bad conditions set by the
government to access funding emerged as the other main factor that kept interviewees away
from this possibility. All interviewees expressed their disappointment in the difficult and
cumbersome procedures to get public funds. Thus, it can be claimed that in this frame the
subsidies introduced at Italian at European level to overcome the aforementioned barriers to
entry faced by Italian startuppers during their process of starting up a business in Italy did not
help this group of entrepreneurs in overcoming barriers to entry raised by entry regulation.
4.2.2 United Kingdom
Three interviewees claimed their entry in the market of innovative entrepreneurship was
driven by the necessity of doing something personal and running their own business, while
two respondents stated that running a start-up is for them an opportunity to solve an actual
problem. Therefore, like Italy, can be claimed that the majority of the interviewed belong to
the group “necessity entrepreneurship” which has no effect on economic development,
differently from opportunity entrepreneurship (Acs, 2006).
A first result is that all the five respondents from UK that took part to the interview stage
started their start-ups in their base country, the United Kingdom. Accordingly, it can be
claimed that entry regulation was not restricted as it was for Italian respondents. None of the
entrepreneurs changed country in order to continue the experience of starting up a business.
This result might already suggest that, for the considered samples, low-entry-regulated
United Kingdom represent a more start-up friendly environment than high-entry-regulated
Italy (Klapper, Laeven, and Rajan (2004).
“Starting a company is easy. The real challenge is raising money and finding customers.”
[Respondent 3]

42

“[I] didn’t face any problem at all in starting my company. You can find a lot of advices
online and the process of registering a company is really easy and cheap.” [Respondent 4]
Considering the problems faced during the process of starting up a business in United
Kingdom, the main result was certainly that, at first, four respondents answered that they did
not face any problem during the process of starting up a business. Thus, it can be argued that
for the considered sample, entry regulation does not raise substantial barriers to entry that
hamper the start up of new businesses in United Kingdom. Assessing the interviews more
thoroughly, three respondents clearly stated that the process of starting up a business was
very easy in United Kingdom and just two factors emerged as possible problems that might
occur: starting a bank account and fundraising. Two respondents mentioned both these
factors. While the first one was identified as relatively easy to overcome, the second
represented a problem generally related to the circumstance of starting up a business.
Moreover, when asked about the biggest obstacles faced during the process of starting up a
business in United Kingdom, finding customers was a factor that emerged the most – four
times, while just one respondent answered: difficulty in finding human capital. Consequently,
it can be claimed that the problems highlighted by respondents in the process of starting up
and running a business in their country are not related to the entry in the market of
innovative entrepreneurship. To conclude, it can be claimed that, considering the interviewed,
the three measures of entry regulation theorised by Djankov, La Porta, Lopez-de-Silanes, &
Shleifer (2000), are not perceived by entrepreneurs from low-entry-regulated United
Kingdom as barriers that hamper the entry into the market of innovative entrepreneurship.
Consequently, entry regulation does not seem to discourage the entry in the market of
innovative entrepreneurship during the experience of starting up a business in United
Kingdom.
“It’s easy to establish a business, the difficult part is to run it well.” [Respondent 1]
“Getting a bank account is a long procedure but the real problem is to find the first
customers and suppliers.” [Respondent 2]
Considering how government intervention and in particular Structural Funds made
available by EU Cohesion Policy 2007-2013 actively helped entrepreneurs in overcoming
barriers raised by entry regulation, it can be noted that none of the interviewees mentioned

43

the possibility of securing public funding from the government or the European Union as a
way to overcome the fundraising problem. Three interviewees said they were focused on
private funding. An important result is certainly that none of the interviewees received public
funding during the experience of starting a business and when it was directly asked if the
possibility of getting public funding has been taken into account, just one respondent out of
five answered that he would take into account this possibility. Trying to get public funds was
considered to be too hard by most of the respondents from United Kingdom. Nonetheless, the
main reason that emerged as the main factor that keep interviewees away from this possibility
is the lack of information around governmental and European public funds. Thus, it can be
claimed that also in this frame the subsidies introduced at British at European level to
overcome barriers to entry did not help entrepreneurs in overcoming the problem of
fundraising.
“I know about public and European funds but they are not for everyone. They are hard to
access and it’s hard to find information about them. I believe in EU funds like I believe in
unicorns.” [Respondent 2]
“Public funds from EU? I just don’t know much about it.” [Respondent 5]
4.2.3 Italy and United Kingdom Compared
In conclusion, it can be claimed that the expected differences regarding the entry in the
market of innovative entrepreneurship in low-entry-regulated United Kingdom and high-
entry-regulated Italy have been confirmed by qualitative analysis. The different entry
regulation of the two countries influenced very differently the experiences of starting up
businesses in Italy and the United Kingdom. While all the interviewed entrepreneurs from
United Kingdom finally started their business in their country, two respondents out of the five
Italians interviewed started their company in United Kingdom as a way to overcome the
barriers to entry the market of innovative entrepreneurship raised by Italian entry regulation.
Consequently, considering the samples, while entry regulation seem to discourage the
experience of starting up a business in Italy, this can not be claimed in the case of United
Kingdom. Moreover, while many factors have been underlined by Italian respondents as
problems during the process of starting up a business, the processes of business creation in
United Kingdom are considered relatively easy by respondents. Entry regulation is not

44

mentioned by any of the interviewed from United Kingdom while respondents from Italy
mentioned high costs, slow and long bureaucratic procedures, and excessive regulation as
main factors that hamper their enter in the market of innovative entrepreneurship. Finally, in
both countries, government intervention and Structural Funds made available by EU
Cohesion Policy are not mentioned as possible solutions to facilitate the process of starting a
business. Money and fundraising has been mentioned by all the interviews as a challenge
faced during entrepreneurial activity but public funds are not associated with a possible
solution to these problems. In these terms, private funding is generally considered easier to
obtain.

45

5. Conclusions
5.1 Summary and Findings
The aim of this thesis has been to understand the extent to which entry regulation of
European countries influenced the number of start-ups supported by Structural Funds made
available by European Union Cohesion Policy 2007-2013. The hypothesis of this thesis is
that entry regulation influences the number of start-ups supported restraining the growth of
innovative entrepreneurship and imposing to entrepreneurs barriers to entry that market. In
this frame, the number of start-ups supported is a variable taken into account to represent the
concept of the spread of innovative entrepreneurship and the final aim has been to determine
the impact of entry regulation on the spread of innovative entrepreneurship.
Investigating the outcomes of EU Cohesion Policy in terms of start-ups supported
provided an overview of the spread of innovative entrepreneurship among member states.
Since opportunity entrepreneurship has a positive and significant effect on economic
development (Acs, 2006), understanding the factors that may have limited the start-ups of
new enterprises with financial assistance of Structural Funds give important policy
suggestions for the incoming period of Cohesion Policy 2014-2020 in order to reach the
results of Europe 2020 strategy.
To reach the conclusions, both a quantitative and a qualitative analysis were conducted.
According to quantitative analysis, the assumption that entry regulation hampers the creation
of new firms seems to be confirmed in the frame of start-ups supported among European
countries during EU Cohesion Policy 2007-2013 (Klapper, Laeven, and Rajan, 2004).
Spearman correlation coefficients show statistically significant moderate and weak negative
correlations between the number of start-up supported by Structural Funds from EU Regional
Policy between 2007 and 2013 and the explanatory variables that represent the regulation of
entry. Time required to register a business is the independent variable that, among the others,
has the stronger negative impact on the number of start-ups supported. On the other hand,
Costs to Register a Business has a weak negative correlation with the dependent variable.
Furthermore, when considering as dependent variable the investment in innovation & RTD
per start-up supported the situation is different. The Spearman coefficient with all the

46

independent variables shows moderate positive correlation between the dependent variable
and the explanatory variables that represent the regulation of entry. These results generally
show that higher levels of regulation of entry is a predictable factor of lower numbers of
start-ups supported by Structural Funds made available by European Union Regional Policy
between 2007 and 2013.
Qualitative analysis confirmed that the different entry regulation of the two countries
influenced the very different experiences of starting up a business in Italy and the United
Kingdom. While entry regulation seems to discourage the experience of starting up a
business in Italy, this can not be claimed in the case of United Kingdom. Moreover, while
many factors have been underlined by Italian respondents as problems during the process of
starting up a business, the process of business creation in United Kingdom is considered
relatively easy by respondents. Entry regulation and the three measures theorised by
Djankov, La Porta, Lopez-de-Silanes, & Shleifer (2000) were not mentioned by any of the
interviewed from United Kingdom while respondents from Italy mentioned high costs, slow
and long bureaucratic procedures, and excessive regulation as main factors that hamper their
entry in the market of innovative entrepreneurship. In this frame, it is interesting to notice
that costs of business start-up procedures – that in qualitative analysis have been highlighted
by Italians respondents as one of the main problems faced in the process of starting up a
business – results in the simple linear regression analysis of the quantitative study as the
independent variable with lower correlation with considered dependent varibles. Finally, in
both countries, government intervention and Structural Funds made available by EU
Cohesion Policy were not mentioned as possible solutions to facilitate the process of starting
a business. Money and fundraising were mentioned by all the interviews as a challenge faced
during entrepreneurial activity but public funds were not associated with a possible solution
to these problems. Private funding was generally considered easier to get.
5.2 Answer to the Research Question
The claims that entry regulation hampers the creation of new firms have been confirmed in
this thesis. Considering quantitative analysis, high regulation is a predictable factor of fewer
start-ups supported with Structural Funds made available by EU Cohesion Policy 2007/2013.
Moreover, qualitative results showed there are substantial differences in the experience of
starting up a business in high-entry-regulated Italy and the low-entry-regulated United

Regulation of Entry and Innovative Entrepreneurship - Matteo Consonni

Regulation of Entry and Innovative Entrepreneurship - Matteo Consonni

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