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Bachelor thesis
Which social and urban factors are conducive to the entrepreneurial society? A cross-country
empirical investigation of the Florida hypothesis
Charlotte Verschoor
332905
This thesis is supervised by
Ruben de Bliek
Jul 28, 2014
Erasmus Universiteit Rotterdam
Department of Applied Economics
Abstract
In this paper, the influence of urbanization and diversity on innovative entrepreneurship is analysed.
According to Richard Florida's central thesis from "The Rise of the Creative Class" (2002) and "Cities
and the Creative Class" (2005), urbanization and diversity are the foundation of innovative
entrepreneurship. The latter boosts economic growth. Over the last decade, the positive influence of
entrepreneurship, and specifically innovative entrepreneurship, is demonstrated. This paper aims to
explain the variance in innovative entrepreneurship between countries using multiple regression
analysis. The relationship between innovative entrepreneurship, urbanization and diversity is
investigated. Innovative entrepreneurships is measured using the Acs and Szerb (2010) Aspiration
index. This paper confirms the influence of urbanization, but finds no statistical evidence concerning
diversity
or
an
interaction
effect.
2
1. Introduction
Entrepreneurship is one of the crucial factors for economic growth (Acs et al., 2009). A country that
adapts to the entrepreneurial economy more rapidly displays higher economic growth rates (Thurik,
2009). Since the 1970s, the role of entrepreneurship changed and the new consensus is that small firms
can be innovative as well. Therefore, during the last decade extensive research has been done
concerning policy effects promoting entrepreneurship (Thurik, 2009).
If an entrepreneurial economy is something to strive for, what are the fundamental factors required in
a region to embrace innovative entrepreneurship? One of the most important factors is the opportunity
to exchange knowledge. Knowledge spill overs in a region due to clustering will increase the
innovation rates in the environment. Formal or informal meetings in a cluster allow tacit information
to be shared. Participants with partial information can engage in mutual trading of information,
improving the knowledge of the environment (McCann, 2013). Then again, what is a good breeding
ground to promote the exchange of knowledge? Much research has been conducted on the influence of
urbanization on entrepreneurship. According to Rahmann and Fatima (2011) the spatial dimensions in
entrepreneurial activity suggest that economic growth generated by entrepreneurial activities is
bounded in the geographical location where it starts. The effect of growth dampens as we move away
from city centres. Therefore, the rate of urbanization seems to be of influence on the knowledge
exchange in countries. Richard Florida investigated the impact of a diverse and creative society on
economic growth. In his book, “Rise of the Creative Class” (2002) , he states that a region benefits
from the presence of the creative class. The creative class are people who have jobs forcing them to be
creative. Florida makes a distinction between the super creative core and the creative professionals.
The super-creative core is focused on problem finding, finding an unfulfilling equilibrium and change
that. Entrepreneurs are part of the super-creative core, but the super-creative core can be found in
many other parts of the market like research, engineering, design and arts. Creative professionals are
more focused on problem solving, they deal with problems that need a knowledge intensive approach.
Creative professionals can be found in healthcare, education, finance and law. To nourish the growth
of this creative class in a region, cities need to be open and diverse.
This paper will focus on the influence of urbanization, diversity and the interaction between those
variables on the level of innovative entrepreneurship in different countries. To measure the amount of
innovative entrepreneurship, the Aspiration index of Acs and Szerb (2010) will be used.
The remainder of this paper is organized as follows: Section 2 consist of a theoretical framework
explaining research findings concerning entrepreneurship, urbanization and diversity. In section 3 the
data used will be discussed, in section 4 the methodology and findings are presented, in section 5 a
conclusion is drawn, section 6 addresses some of the limitations of this paper and section 7 contains
the reference list.
2. Theoretical framework
2.1 Entrepreneurship.
The concept of entrepreneurship is discussed in scientific literature more than several times since
Schumpeter’s recognition that entrepreneurship is the cause of economic development (Schumpeter,
1934). Hull et al. (1980), for instance, state that entrepreneurs are people managing a firm and are
facing risks to generate profit. A clear definition of entrepreneurship has not been made yet. One states
an entrepreneur is someone who is managing a business, others state entrepreneurship is the act of
facing risks and acting on opportunities or an entrepreneur is someone undertaking activities involved
in organization creation (Gartner, 1988). Without a clear definition, entrepreneurship is very broad and
measurable in many ways. This paper will focus on the positive influence of entrepreneurship on
economic growth and development. Hence, in this paper, the following definition of entrepreneurship
will be used: “Entrepreneurship describes the combination of a context in which an opportunity is
situated, a set of personal characteristics required to identify and pursue this opportunity, and the
creation of a particular outcome” (Martin & Osberg, 2007).
Entrepreneurs will create new, more satisfying, market equilibriums. For instance, before
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Apple computers were not ‘personal’. If any change in a programme needed to be done, a customer
went to a programmer and waited a while before they could work further, there was no faster option
and this was an equilibrium, not a very fulfilling one. After Apple, much more could be done with a
computer at home; the personal computer has entered the market creating a new, more fulfilling,
equilibrium. Therefore, innovation is an important aspect of entrepreneurship. Zhao (2005) has shown
that innovation and entrepreneurship are complementary. A high ratio of entrepreneurship will
therefore have a positive influence on the competiveness of a region and therefore positively
influencing the economic growth. Entrepreneurship contributes income, jobs, R&D and innovations,
generating economic benefits that are often larger than the private benefits reaped by the entrepreneurs
themselves (Van Praag and Versloot, 2007)
Van Stel et al. (2010) state entrepreneurship consists of two types; necessity entrepreneurship and
innovative entrepreneurship. Necessity entrepreneurs are pushed to become an entrepreneur, because
the labour market gives them no other option. Their first aim is to generate income instead of bringing
novel ideals to the market. The U-shaped curve of the level of entrepreneurship is explained by this
distinction. Countries with a low GDP have high amounts of necessity entrepreneurs, while countries
with a high GDP have a much higher share of opportunity entrepreneurs. This corresponds with the
three stages of economic development according to Porter (2003).
Entrepreneurship has not always been associated with economic growth. Till the 1970s, a decline in
the rate of entrepreneurship was noticeable, big firms were mass-producing and they seemed to be the
most cost-effective, enjoying the benefits of economies of scale. Over the last three decades, the
development in ICT and the effect of globalization lead to lower costs for small business and gave
entrepreneurship a boost (Audretsch & Thurik, 2001). Competition was not solely based on costeffectiveness anymore; innovation became a way to compete on the market as well. With the new
developments, innovation became less restricted to the R&D departments of large firms, the
entrepreneurial economy could arise. According to Audretsch and Thurik (2001) entrepreneurship is
necessary for economic growth in modern economy and the idea of the entrepreneurial economy is
“based on the socio-economic mindset of thinking in terms of opportunities rather than in terms of
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resources” (Audretsch and Thurik, 2001). The contract between the entrepreneurial economy and the
managed economy is that the latter is focused on exploitation and the entrepreneurial economy is more
focused on exploration. The entrepreneurial economy is more innovative, because creative destruction
comes more often from entrepreneurs. Creative destruction is the process of breaking a product life
cycle by inventing a better one that will be adapted by the market. Instead of continuously optimizing
the product, replacing it with a complete new product. For instance CD’s and the MP3-players.
According to Spulber (2012) the reason entrepreneurs are more creative destructive is that higherquality inventions result in entrepreneurship and lower-quality inventions result in technology transfer
to other firms. Spulber shows that innovations with a possibility of entrepreneurship will lead to
increasing R&D expenditures. There is a higher motivation for the inventor if they can exploit their
product as an entrepreneur instead of selling it to a large company.
Similar to the definition of entrepreneurship, a clear-cut and broadly agreed upon operationalization of
entrepreneurship is also absent. Scholars emphasizing the role of entrepreneurs participating in
activities involving organization creation, finding new start up rates of firms a way to measure
entrepreneurial activity (Van Stel and Storey, 2004; Audretsch and Keilbach, 2005). Other studies that
focus on the innovative role as an entrepreneur will distinguish between businessmen entering the
market with standardized products and entrepreneurs bringing a new product to the market. Moreover,
the quantity of self-employment is seen as a method to measure entrepreneurship as well (Georgellis
and Wall, 2000). In this paper, the role of the entrepreneur is characterized as being innovative and as
someone bringing a new product or new technique to the market, thus measuring the number of selfemployed will not be sufficient. Even though most data is corrected for agricultural firms, the start of a
local super market will have the same economic impact as a pharmaceutical start up according to most
data. Acs and Szerp (2010) acknowledged this problem and explained the current data focuses on
quantitative entrepreneurship, whereas a shift to qualitative entrepreneurship would be preferable.
How entrepreneurship will be measured with use of the Global Entrepreneurship and Development
Index developed by Acs and Szerb will be discussed in section three, data.
2.2 Urbanization.
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Urbanization is the shift of people moving from a rural to an urban area. An urban area is a region
with high population density and with a high supply of various amenities compared to the surrounding
environment. Urbanization can also be a state, a percentage of the population living in cities compared
to the total population. Global urbanization rates are shown in figure 1. The darkest parts show
countries where the population almost entirely lives in urban areas. The developing countries in Africa
and South-East Asia are much less urbanized than the developed countries.
Figure 1. Urbanization Rates
Source: http://www.unicef.org/sowc08/docs/sowc08_table_StatisticalTables.pdf
Ever since the late fourteenth century and early fifteenth century, emerging relationships between
industrialization, urbanization and economic development were connected with the development of
certain areas, starting in Western Europe. The rise of urban growth as an economic engine stopped in
the early twentieth century with the World Wars and the Depression. Countries became closer and
focused on more independency of international trade. This marked the end of the first major phase of
global urbanization. In the latter decades of the twentieth century, urbanization started to occur due to
reintegration of the global economy, now featured with an increasing importance of cities and
agglomeration economies on account of the change in the spatial transaction costs (McCann, 2013).
Urbanization leads to the existence of place-based ecosystems critical for economic development.
Cities work as an open economy with a high rate of capital, labour and idea mobility. Cities attract
human capital. Jacobs (1969) has shown that the rise of cities is the first requirement for economic
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development, that this causality is asymmetric and that the industrial mix and the possible interindustry relationships are the primary source of urban productivity. The industrial mix is important
because the most important knowledge transfers come from outside the core industry. Porter (1990)
argues that knowledge spill-overs stimulate growth and that local competition forces firms to adapt
quickly to new innovations.
One of the benefits of starting a company in an urbanised area is the existence of agglomeration
economies (Marshall, 1920). Agglomeration economies are local economies of scale that can increase
the profitability of the firm compared to other possible locations. Agglomeration economies are not
simply increasing returns to scale because of large-scale production; Kaldor (1970) has shown that
agglomeration economies benefit from the cumulative advantages accruing from the growth of the
industry itself through the development of skills and know-how.
The main advantages of agglomeration economies are established by Marshall (1920): Knowledge
spill-overs, non-traded local inputs and a local skilled labour pool. Knowledge spill-overs occur in
cities because communication between people is more extensive; ideas flow quickly from person to
person. Through spying, imitation, and rapid inter-firm movement of highly skilled labour, ideas are
quickly disseminated among neighbouring firms (Gleaser et al., 1991). Non-traded local inputs are
local provisions of specialist’s goods and services like high-developed infrastructure or testing firms.
These amenities are only present when the costs of the provision can be spread out to the many firms
within that region. A specialised cluster with many firms benefit from the supply of non-traded local
inputs is needed. Therefore, these inputs do not always exist in cities. A local skilled labour pool is of
positive influence on the returns of firms because a firm can expand the labour force more easily, it
can reduce the recruitment costs and there are more workers available to carry out tasks correctly.
Rahman and Fatima (2011) state entrepreneurship is more dependent of the urban area than the
country the urban area is situated in. Also, entrepreneurship has a spatial dimension characteristic; the
level of new firm creation is dependent on the entrepreneurial capital in a region. Entrepreneurial
capital is defined as the capacity of the society to create new firms (Audretsch and Keilbach, 2005).
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Starting a new business is not something an individual does all by himself; the regional milieu
influences the probability of someone becoming an entrepreneur. For instance, the willingness of and
individual to face the risks of starting a new firm, the willingness of banks to provide loans, the ease to
gain venture capital and the attitudes of society towards entrepreneurship (GEM monitor, 2006).
Knowledge spillovers in cities are captured in new firm formation on the account of entrepreneurial
activity. Starting a new business in an urban area has a positive influence on the performance of the
firm according to Renski (2011): “External economies of localization and diversity can also have
beneficial effects on the performance of new businesses in the years immediately following their
birth.”
Therefore, urbanization is a variable to take in consideration to understand the level of innovative
entrepreneurship in a country.
Hypothesis 1 Urban development is positively associated with innovative entrepreneurship.
2.3 Diversity.
With increasing globalization, developed countries societies are changing. The society faces an
accumulation in social and ethic heterogeneity. The percentage of immigrants is growing in all
advanced countries (Putnam, 2007). The trend is towards a more diverse society and the discussion
rises whether this has a positive influence on the economic development in a region. According to
Putnam, countries need time to adjust to higher levels of ethnical fractionalization. This means that in
a society, more ethnic groups are present. An ethnic group are people identifying with each other
because common grounds like nationality, cultural heritage and race. Fractionalization means that the
more fractionalized a society is, the higher the probability two random people belong in a different
ethnic group. This discussion about the benefits of diversity doesn’t stop by immigration percentages.
Diversity is researched in separate dimensions. The diversity of amenities in the Consumer City theory
9
of Glaeser (2001), the positive influence of diversity of creative people by Florida (2002) and the ‘love
of variety’ theory of Fujita et al (1999).
Measuring cultural diversity is possible in many ways. Most authors use the ‘Melting Pot Index’
(Florida, 2002) or a derivative of this index, which measures diversity with the ethnic background of
inhabitants of a region. Lee et al. (2004) use the Gay Index to measure broader openness to diversity.
This paper will use the Melting Pot Index. Therefore, cultural diversity will be measured based on the
level of immigrants, bringing different cultures to the region.
Cultural diversity may be an important aspect of urban diversity, influencing the local production and
consumption (Alesina and La Ferrara, 2004). Whether this has a positive impact is debatable. Ethnic
diversity can lead to political instability, oppression of minorities and racism, but diverse cities like
New York are very innovative and creative. For instance, Ottaviano & Peri (2006) state that a more
multi-cultural urban environment makes native inhabitants more productive, measured by the average
wage received and average rent paid by US-citizens. Both Putman (2007), Florida (2012) and
Ottoviano and Peri (2006) agree that tolerance in the society has an influence on the rate regions can
benefit from cultural diversity. Whereas Putman (2007) shows that tolerance has a timeframe, the
tolerance index will grow over time and over generations, Ottaviano and Peri (2006) state that higher
educated will possibly be more tolerant due to early exposure to different cultures and the ability to
travel. Therefore, people with a higher exposure to culture and news are more appreciative to cultural
differences. Florida (2012) doesn’t write about the origin of tolerance, but he states tolerance, or
openness to diversity, is an additional source of economic advantage. Tolerant cities have low entry
barriers, are more open to newcomers and are more adaptive to new economic arrangements, this
cities will also have more people taking the risk of founding a firm, leading to increased economic
growth. Entrepreneurial individuals will seek for tolerant cities to drop anchor.
Audretsch et al. (2010) show the impact of diversity on entrepreneurship. Cultural diversity has a
positive and highly significant impact on technology oriented start-ups in general, technology oriented
services and high tech start-ups. Their tests suggest that the diversity of firms in a region is of lesser
10
influence on the entrepreneurship rate than the diversity of people. Therefore, cultural diversity will
form an ideal breeding ground for technology-oriented start-ups.
Hypthesis 2 There is a positive correlation between diversity and innovative entrepreneurship.
2.4 Interaction effect urbanization and diversity.
Richard Florida (2012) assumes that the presence of a high rate of members of the Creative Class in a
region will increase the innovation rate so that cities and regions that provide a welcoming and open
environment to creative people will benefit economically. This Creative Class has a high demand for
an open and diverse society to exchange knowledge and get inspired, thus they choose certain places
to live because they are tolerant, diverse, and open to creativity. Florida (2012) shows that the larger a
city’s population, the greater the innovation and wealth per person. He uses the study of Bettencourt et
al. (2007) to state that when the population in a city doubled, the attributes as innovation, patent
technology, the number of super creative and the gross domestic product more than doubled at the
same time. Moreover, Florida’s theory about the Creative Class is focused on how putting creative
members together in a city or urbanized region will promote economic growth. Therefore,
urbanization is an important aspect of Florida’s theory.
Glaeser (2001) explains with his Consumer City theory the need for a diverse supply of amenities to
attract high-educated people who will form a base for knowledge exchange. High-educated people
have a greater demand for income elastic goods. One of these amenities is speed, the ease with which
people can transport themselves in a city. Transport cost of goods is expected to fall according to
Glaeser (2001), but opportunity costs of transporting people, and with that human capital, will rise.
Urbanization is an exigency. Another amenity is the need for a high variety of consumer services and
goods. Hence, to attract high-educated people, entrepreneurship can be promoted; entrepreneurs have
the opportunity to supply diverse goods with a high threshold and high range in the city. Christaller
(1966) shows that an industry oriented towards a local market will not appear in the market until the
maximum distance at which the good can be sold dependent on the willingness of consumers to travel
for the good, is greater than the distance which corresponds to the minimum quantity of good
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produced under efficiency rules. Therefore, location of entrepreneurship is dependent on the
consumer. This is a stimulation of the demand side of entrepreneurship. The demand side of
entrepreneurship is influenced by the diversity of consumer’s tastes dependent on globalization or
changing standards of living (Freytag and Thurik, 2007).
Alesina, Baqir and Hoxby (2000) also researched the existence and growth of cities and diversity: The
formation of local jurisdictions emerges from a trade off between the benefits of scale and the costs of
racial heterogeneity. These authors look both at recent evidence and at historical evidence on the
formation and break down of school districts, special districts and cities. The trade-off between
economies of scale and racial heterogeneity tends to be larger in magnitude and more robust
empirically than the trade-off between economics of scale and income heterogeneity.
Considering the relevant literature, I expect to find a positive interaction effect between urbanization
and diversity, and innovative entrepreneurship.
Hypothesis 3 There is a positive interaction effect between urbanization and diversity on innovative
entrepreneurship.
3. Data
3.1 Innovative entrepreneurship.
As mentioned before, the level of innovative entrepreneurship is hard to measure. Levels of TEA, selfemployment or venture creation are considered good measurements for the level of entrepreneurship
in a country. Unfortunately, these indicators are not distinguishing innovative entrepreneurship from
entrepreneurship contributing nothing novel to the market. The latter will have less impact on the
economic development in a country and is therefore not the variable to take in consideration in this
paper. To determine the influence of urbanization and diversity on the level of innovative
entrepreneurship another measurement needs to be applied. In this paper a sub-index of the Global
Entrepreneurship and Development Index (GEDI) developed by Acs and Szerb (2010) will be used.
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To understand the use of the sub-index, the GEDI will be explained briefly. The GEDI is an index that
distinguishes the individual and institutional influence on entrepreneurship and according to Acs and
Szerb (2010) the aim is to find a suitable measure or indicator for the level of entrepreneurship in an
economy before embarking on policy initiatives. Therefore, the authors separate three sub-indexes:
entrepreneurial attitudes, entrepreneurial activity and entrepreneurial aspirations. Entrepreneurial
attitudes are defined as the general disposition of a country’s population toward entrepreneurs,
entrepreneurship, and business start-ups. The Global Entrepreneurship Monitor (2005) investigated
this attitudes using a questionnaire containing questions about the prosperity of entrepreneurship.
Entrepreneurial activity is defined as the start-up activity in the medium- or high-technology sector
initiated by educated entrepreneurs in response to business opportunities in a somewhat competitive
environment, corresponding with the middle of the S-shaped curve of entrepreneurial activity in
countries, the efficiency-driven stage.
The last sub-index, entrepreneurial aspirations, is the most valuable index for this paper. Acs and
Szerb (2010) have mapped the intentions of entrepreneurs that are part of the TEA in a country. TEA
stands for Total Early-stage Entrepreneurial Activity. Early-stage entrepreneurs are the percentage of
the population who are nascent entrepreneurs or own, for at least a part, of a firm younger than 3,5
years. The aspiration index reflects the innovation and high-growth intentions of these entrepreneurs.
Acs and Szerb (2010) designed five pillars to map the intentions of early stage entrepreneurs: Product
innovation, process innovation, internationalization, high growth and risk capital. With these five
pillars the capability of the entrepreneur is measured to produce and sell something that is considered
new and innovative to the customer. The percentage Acs and Szerb (2010) found reflects the amount
of the entrepreneurs that are part of the TEA and have the intention, put effort, to introduce new
products and services to the market, penetrate foreign markets and am for high-growth. An aspiration
index score of one means that every early-stage entrepreneur in a country considers himself innovative
or that he aspires innovation. They see opportunities to entry the market. If a country scores zero on
the aspiration index, most entrepreneurs focus on exploitation, supplying products that are not new to
the customer. Even though the index does not reflex the amount of innovative firms, the index shows
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the amount of entrepreneurs considering themselves innovative and this can give a good indication of
the size of innovative entrepreneurship in a country. Therefore, using this sub-index as the percentage
of innovative new firms in a country is a good approximation. To determine the extent of new
innovative firms as a dependent variable, the aspiration index can be multiplied by the amount of new
firms in a country, giving in indication of the amount of new innovative firms and this will be
logarithmic transformed to address the problem of normality. The amount of new firms is estimated by
the World Bank (2010) and is corrected for the population, the GEDI aspiration index is measured in
2010 as well.
3.2 Independent variables
To test the first hypothesis, the percentage of people living in an urban area is the measurement for the
rate of urbanization. The source of this percentage is the World Bank. To measure diversity is not that
straightforward. Lee et al. (2004) and Florida (2012) used two measurements determining diversity:
the Melting Pot Index and the Gay Index. The Gay Index wasn’t significant at times and is hard to
calculate. Therefore, the Melting Pot Index is used, which was more of significant influence in their
analysis. The Melting Pot Index measures diversity according to the cultural background of the
population. This is reflected in ethnic background, religion and different languages spoken among
inhabitants. The variables are constructed as indexes of fractionalization. Fractionalization measures
the probability of two random inhabitants being different from each other, in this case when the
inhabitants have a different ethnic background or religion or are speaking another language. Therefore,
if every inhabitant has a different ethnic background, the fractionalization rate will be one. Are all
inhabitants homogeneous, the fractionalization rate will be zero. The source of these rates is the data
constructed by Alesina et al. (2003) in their article Fractionalization. The correlation between those
variables for diversity will probably be quite large; people with distinctive ethnic backgrounds have a
higher probability of also having distinct religions. Moreover, the interaction effect between diversity
and urbanization will be measured multiplying the urbanization percentage with all the three diversity
indicators separately.
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3.3 Control Variables
The following variables are control variables: Education, corruption and legal strength. This variables
are all structural variables influencing the probability of becoming an entrepreneur. Education is a
useful control variable that has proven is influence in several researches, for instance, Bowen and De
Clercq (2008). According to Whitley (1999) entrepreneurs are influenced by the institutional context
in a country, in specific institutions that develop individuals’ competences and skills. Education is one
of the most influential institutions. Entrepreneurs can benefit from a good educational system where
they gain a sense of autonomy and insight to recognize entrepreneurial opportunities (Verheul et al.,
2002). The relationship between educational attainment and the probability of becoming an
entrepreneur is also researched by Calvo and Wellisz (1980). Their research shows that educational
attainment influences the managerial ability, which in turn increases the probability of selection into
an entrepreneurial career. Reynolds, Hay, and Camp (1999) found that a country’s level of
entrepreneurial activity is positively related to its investment in post-secondary education. Scholars not
only researched the effect of educational attainment to the amount of entrepreneurs, but also on the
quality of the new businesses. Van der Sluis et al. (2008) show that the entrepreneur’s performance
has a positive relationship with schooling: the higher the type of schooling and the more years of
education, the higher the chances of better performance. The source of the data used is the Barro and
Lee (2010) Educational Attainment Dataset. The outcome stands for the average years of attending
education in each country. In this case, the data states that the higher the average years of attending
education, the higher the positive influence on innovative entrepreneurship.
Corruption is another control variable. Corruption is the extent in which public power is misused to
gain individually from situations by the use of bribes or a biased allocation of public funds (Choi and
Thum, 2005). The presence of corruption influences the reliability of parties in economic transactions
and is hereby increasing the transaction costs. Sachs and Warner (1995) show that higher levels of
corruption are associated with lower productivity and lower output growth across countries. The
presence of corruption can reduce the level of innovative entrepreneurship because it increases the
level of uncertainty and the allocation of entrepreneurial effort. Scholars have proven that
15
entrepreneurs will be discouraged to invest in high-risk start-ups when corruption is present in a
country (Bowen and De Clercq, 2008). According to Baumol (1990) entrepreneurs in regions with
much corruption face a continuously changing and unpredictable environment and they have a higher
probability of losing their investments. The source of the data on corruption is from the Worldwide
Governance Indicator (2013) and the quality of corruption control is given by an estimate of
governance which ranges from approximately -2.5 for weak governance concerning corruption to 2.5
for strong governance performance. This scale reflects the perceptions of the extent to which public
power is exercised for private gain, including both petty and grand forms of corruption, as well as
"capture" of the state by elites and private interests.
The last control variable is the legal strength. The rule of law affects the strength of property rights
and has an impact on the worthiness of investment opportunities. Capital constraints are more likely to
affect younger, more entrepreneurial firms according to King and Levine (1993). They show that
better functioning legal environments promote greater development of financial markets. Desai et al.
(2003) show that greater fairness and stronger property rights are significantly associated with higher
rates of entry. The source of this data is the World Bank and the strength of legal rights index
measures the degree to which collateral and bankruptcy laws protect the rights of borrowers and
lenders and thus facilitate lending. The index ranges from 0 to 10, with higher scores indicating that
these laws are better designed to expand access to credit.
4. Method and results
To test the hypotheses, multiple regressions using least square estimation will be implemented. A
multiple regression is a way to learn more about the impact of different independent variables on one
dependent variable, in this case the amount of innovative entrepreneurs. To construct the independent
variable, the GEDI Aspiration index is multiplied by the amount of new firms per 1000 inhabitants. A
correction is made for the size of the population to predict the share of innovative entrepreneurship,
instead of the amount of innovative entrepreneurship. The share of innovative entrepreneurship is a
better predictor for the influence on the economic growth. To address the problem of normality, the
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natural logarithm is applied on the share of new innovative firms. The function for the dependent
variable is as follows:
ln⁡(𝑖𝑛𝑛𝑜𝑣𝑎𝑡𝑖𝑣𝑒⁡𝑒𝑛𝑡𝑟𝑒𝑝𝑟𝑒𝑛𝑒𝑢𝑟) = ln(𝑛𝑒𝑤⁡𝑓𝑖𝑟𝑚𝑠 ∗ 𝑎𝑠𝑝𝑖𝑟𝑎𝑡𝑖𝑜𝑛⁡𝑖𝑛𝑑𝑒𝑥)
Using least squares, Eviews will construct a line between all the data points with the least amount of
deviations possible. For each independent variable, a coefficient will be calculated measuring the
influence of an increase of one of the independent variable on the dependent variable, all other
independent variables held the same. All tests are checked for the presence of a normal distribution
with the Jarque-Bera test for normality, non-linearity with the Breusch-Godfrey serial correlation LM
test, heteroskedasticity with the White test and multicolliniarity, using the variance inflation factors.
These tests never showed reason for concern about the quality of the model.
ETHNIC
LANGUAGE
LN INNOVATIVE
URBAN
FRACTIONA- FRACTIONAENTREPRENEUR POPULATION LISATION
LISATION
Mean
Maximum
Minimum
Std. Dev.
Observations
1.43
13.97
0.01
2.24
57
73.03
100.00
30.93
15.79
57
0.32
0.75
0.0002
0.24
57
0.24
0.87
0.0003
0.23
57
RELIGION
FRACTIONA- CORRUPTION
LEGAL
EDUCATIONAL
LISATION
CONTROL
STRENGTH ATTAINMENT
0.34
0.86
0.005
0.24
57
0.62
2.41
-1.08
1.10
57
6.07
10.00
1.00
2.51
57
9.65
12.68
4.90
1.87
57
Table 1:
Descriptive
statistics
4.1 Urbanization
To test whether the level of urbanization influences the amount of new innovative firms, the model
first tests the influence of the urban population and after that, the control variables are added to see if
there are no spurious relationships between the independent variable of new innovative firms and the
dependent variable urbanization. To test the hypothesis, the dependent variable is the amount of
innovative new firms in a country in a year per one thousand inhabitants. Therefore, the dependent
variable is innovative entrepreneurs and forms the following multiple regression:
17
ln(𝑖𝑛𝑛𝑜𝑣𝑎𝑡𝑖𝑣𝑒⁡𝑒𝑛𝑡𝑟𝑒𝑝𝑟𝑒𝑛𝑒𝑢𝑟) = 𝛽0 + 𝛽1 ⁡ (𝑢𝑟𝑏𝑎𝑛⁡𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛) + 𝛽2 (𝑒𝑑𝑢𝑐𝑎𝑡𝑖𝑜𝑛) + 𝛽3 (𝑐𝑜𝑟𝑟𝑢𝑝𝑡𝑖𝑜𝑛⁡𝑐𝑜𝑛𝑡𝑟𝑜𝑙) + 𝛽4 (𝑙𝑒𝑔𝑎𝑙⁡𝑠𝑡𝑟𝑒𝑛𝑔𝑡ℎ)
+𝜀
The outcome, as shown in Table 2, suggests that urbanization is of influence on the size of innovative
entrepreneurship. With a significance level of α=0.05, the results show that urbanisation is of positive
significant influence. The coefficient of the urban population suggest that an increase of one in the
urban population, the expected change in the logarithm of the innovative new firms will increase with
0.02. Correcting for the logarithmic scale, a one unit increase in the urban population results in a 2%
increase in the amount of innovative firms per one thousand inhabitants, since exp(0.02) = 1.020. The
R-squared is quite large, this model explains roughly 0.72 percent of the variation in the amount of
innovative entrepreneurs in different countries. With these results I do not reject hypothesis 1; the
effect of urbanization on innovative entrepreneurship is confirmed.
Dependent Variable:LN INNOVATIVE ENTREPRENEUR
Variable
Coefficient
Prob.
CONSTANT
-6.40
URBAN POPULATION
0.02
0.02
EDUCATIONAL ATTAINMENT
0.28
0.001
CORRUPTION CONTROL
0.44
0.01
LEGAL STRENGTH
0.16
0.01
R-squared
0.72
Adjusted R-squared
0.70
0.00
Table 2: regression outcomes for
hypothesis 1.
4.2 Diversity
To test the second hypothesis, the positive influence of diversity on innovative entrepreneurship is
tested in several ways. Using the different fractionalization indexes containing ethnicity, religion and
language to measure the relationship with innovative entrepreneurship separately. Tabel 7 shows the
combined outcomes of the diversity measurement. This full model shows the same relationships as the
separate regression analysis.
18
First, the regression with the urbanization percentage as extra independent variable next to one of the
fractionalization indexes is tested. Later, the control variables are added to the regression. The
regression with urban population and ethnic fractionalization as dependent variables is tested first.
Dependent Variable: LN INNOVATIVE ENTREPRENEUR
Variable
Coefficient
Prob.
C
URBAN POPULATION
ETHNIC FRACTIONALIZATION
-4.282667
0.056462
-1.421097
0.0000
0.0000
0.0478
R-squared
Adjusted R-squared
0.413440
0.392859
Table 3: regression outcomes
ethnicity
As shown in table 3, ethnic fractionalization shows a significant negative coefficient, meaning that
when there are more ethnic groups in a society, the level of innovative entrepreneurship will drop. In
some reports of Florida and Lee (2004) these results were also found, but they argue that their measure
does not differentiate between the well-educated and wealthy immigrants and their less educated and
poor counterparts and thus the effect of the index may become negated. When they correct their model
for human capital, their result becomes significant. Bowen and De Clercq (2008) give another possible
reason, rejecting the hypothesis of Florida by stating that the creative milieu as a social habitat of
entrepreneurs is overemphasized, because the creative class theories fail to take the region’s
opportunity structures into account. Taking a diverse society in account, the needs for the different
groups of entrepreneurs can vary and may depend on different social environments. Alesina and La
Ferrara (2000) show that more ethnic fragmented communities have a lower propensity to trust other
people, what is of influence to the knowledge exchange. They explain this by two possibilities:
different ethnic groups have different preferences of how a group should react to another one and how
it should be run, the other possibility is that people have an aversion to racial mixing. According to
Putman (2007) this latter effect can be of less influence over generations. In the long run, the
successful immigrant societies create new forms of social solidarity and dampen the negative effects
of diversity by constructing new, more encompassing identities.
19
After the control variable education is added to the regression, the effect of ethnic fractionalization
disappears. There is a very strong correlation between ethnic fractionalization and educational
attainment. It can mean that education influences both the dependent and independent variable
separately, resulting in a spurious relationship between ethnic fractionalization and innovative
entrepreneurship. Several scholars researched the relationship between ethnic fractionalization and
education. For instance, La Porta et al. (1999) show that ethnic fragmentation is negatively correlated
with measures of infrastructure quality, illiteracy and school attainment. Easterly (2006) shows that
higher fragmentised communities have lower rates of social capital and this leads to a lower rate of
participation in social activities and he connects this with a lower rate of educational attainment.
Alesina et al. (2001) show an inverse relationship between the size of government social spending and
transfers relative to GDP on one hand, and ethnic fractionalization on the other, this can lead to lower
educational attainment when the ethnic fractionalization index rises.
Dependent Variable: LN
INNOVATIVE ENTREPRENEUR
Variable
Coefficient
Prob.
C
-5.639418
0.0000
URBAN POPULATION
LANGUAGE
FRACTIONALIZATION
0.065473
0.0000
1.028571
0.1800
R-squared
0.388831
Adjusted R-squared
0.367003
Table 4: regression outcomes
language
Second, as shown in table 4, language is put in the model instead of ethnic fractionalization. The
relationship without any control variables is insignificant. There seems to be no crucial effect of the
variety of languages spoken to the amount of innovative entrepreneurs. After adding the control
variables to the model, the effect is still insignificant. Language barriers can increase the barriers of
knowledge exchange, since tacit knowledge is shared in formal as well as informal situations.
20
Dependent Variable: LN INNOVATIVE ENTREPRENEUR
Variable
Coefficient
Prob.
C
URBAN POPULATION
RELIGION FRACTIONALIZATION
-5.344104
0.055955
1.869071
0.0000
0.0000
0.0084
R-squared
Adjusted R-squared
0.442945
0.423050
Table 5: regression outcomes
religion
Last, the religious fractionalization is added to the model, as shown in table 6. It shows the same
results as ethnic fractionalization; a significant effect of religion fractionalization on innovative
entrepreneurship until the control variables are added. Moreover, religion shows a positive coefficient.
According to Alesina et al. (2003), investigating religion, highly fractionalized countries are more
open and tolerant. Therefore, the explanation of Florida (2012) about the Gay index, measuring the
tolerance in a city, is comparable with the theory of Alesina et al. (2003) about the size of religious
fractionalization.
The data shows that ethnic fractionalization is more present in developing countries, whereas higher
rates of religious fractionalization are displayed in developed countries. This is detectable in the
correlation coefficients shown in table 7. There is a small negative correlation between ethnic
fractionalization and religious fractionalization. The correlation is not that strong as the research
Alesina et al. (2003) suggested. They suggest due to higher tolerance in countries that are more
religious fractionalized, the educational attainment is higher and the educational attainment has a
relationship with both fractionalization and innovative entrepreneurship.
21
RELIGION LANGUAGE
ETHNIC
URBAN
FRACTIONA- FRACTIONA- FRACTIONAPOPULATION LIZATION
LIZATION
LIZATION
URBAN
POPULATION 1.000000
RELIGION
FRACTIONALIZATION
0.103890
LANGUAGE
FRACTIONALIZATION
-0.303521
ETHNIC
FRACTIONALIZATION
-0.263907
0.103890
-0.303521
-0.263907
1.000000
0.275382
-0.013941
0.275382
1.000000
0.540949
-0.013941
0.540949
1.000000
Table 6: Correlation Coefficients
The full model, containing all three measurements of diversity, gives the same result. All
fractionalization indexes are insignificant due to the impact of the control variables. The control
variable education was added first, this lead to the insignificance. Education is of influence on
innovative entrepreneurship. Religion and ethnic fractionalization are of influence, but taking the
educational attainment into account, the relationship between innovative entrepreneurship and
diversity becomes offset. The control variable education encloses the diversity effect. Moreover, the
adjusted R-squared is lower compared to the model with only the urbanization percentage as
dependent variable next to the control variables. Therefore, leaving diversity out of the model, the
model becomes more valid.
Dependent Variable: LN INNOVATIVE ENTREPRENEUR
Variable
CONSTANT
URBAN POPULATION
ETHNIC FRACTIONALIZATION
RELIGION
FRACTIONALIZATION
LANGUAGE
FRACTIONALIZATION
EDUCATION
CORRUPTION CONTROL
LEGAL STRENGTH
R-squared
Adjusted R-squared
Coefficient
Prob.
-6.21
0.03
-0.69
0.00
0.02
0.31
0.32
0.60
0.71
0.27
0.40
0.13
0.33
0.003
0.03
0.04
0.73
0.69
Tabel 7: regression outcomes
hypotheses 2
22
4.3 Interaction
According to Florida (2012) fractionalization can increase the benefits of urbanization by creating a
more open and tolerant region. Therefore, fractionalization as moderator should increase the effect of
urbanization. When using the same steps to investigate the influence of interaction between
urbanization and fractionalization, the results show almost the same results as when fractionalization
is measured separately. The only aberration compared to the results of hypothesis 2 is that ethnic
fractionalization interaction is now insignificant before adding the control variable. Adding control
variables, the significance of the interaction effect between religious fractionalization and urbanization
disappears. The control variable education encloses the diversity effect. This result indicates the
absence of an interaction effect between urbanization and fractionalization. This can indicate that the
only the presence of urbanization is sufficient to positively influence innovative entrepreneurship,
without any requirements concerning the distribution of its population. Moreover, the results show a
lower adjusted R-squared compared to the model including urbanization only next to the control
variables.
Dependent Variable: LN INNOVATIVE ENTREPRENEUR
Variable
Coefficient
Prob.
CONSTANT
-6.23
0.00
URBAN POPULATION
0.03
0.03
INTERACTION ETHNIC
-0.01
0.36
INTERACTION RELIGION
0.002
0.81
INTERACTION LANGUAGE
0.01
0.30
EDUCATION
0.27
0.002
CORRUPTION CONTROL
0.40
0.03
LEGAL STRENGTH
0.14
0.03
R-squared
0.73
Adjusted R-squared
0.69
Table 5: regression outcomes
hypothesis 3
23
5. Conclusion
This paper seeks to demonstrate the effect of urbanization, diversity and the interaction between those
on innovative entrepreneurship. This subject is of interest because of the benefits innovative
entrepreneurship has on economic development. An entrepreneurial society is something to strive for,
and it is investigated what factors can influence the amount of innovative entrepreneurship. The focus
on urbanization and diversity is motivated by the work of Richard Florida, with his book Rise of the
Creative Class, and the disagreements scholars have concerning this subject. The results suggest that
urbanization is of significant positive influence on the amount of innovative entrepreneurship in a
country, whereas neither diversity nor an interaction effect between diversity and urbanization appears
to be if controlled for the educational attainment. Religion and ethnic fractionalization are of
influence, but taking the educational attainment into account, the relationship between innovative
entrepreneurship and diversity becomes offset. Scholars are discussing about the effect of
fractionalization and economic performance, this paper shows that fractionalization in society is not
beneficial for the amount of innovative entrepreneurship.
6. Limitations
A limitation in this research is the measurement for innovative entrepreneurship. The data is
constructed by multiplying the new firms established in a country in a year per one thousand
inhabitants and the Aspiration index constructed by Acs and Szerb (2010). The Aspiration index
consist of the percentage of TEA focused on innovation and high growth. TEA is the total early stage
entrepreneurial activity. Early-stage entrepreneurs are the percentage of the population who are
nascent entrepreneurs or own, for at least a part, of a firm younger than 3,5 years. This is a
considerably larger share of entrepreneurs than reflected in the new firm creation in one year.
Therefore, a perfect overlap is absent. This wouldn’t be not a problem if the Aspiration index is
constant over time, but there is no research addressing this problem. The entrepreneurial activity
varies over time and shows a pro-cyclical relationship with the business cycle (Koellinger and Thurik,
24
2012). Therefore, assuming the aspiration index is constant is doubtful. However, using this index
gives a good opportunity to compare between countries and further research is needed to establish a
measurement for the size of new innovative firms in a country.
This paper is focused on the differences between countries. According to Rahmann and Fatima (2011)
the spatial dimensions in entrepreneurial activity suggest that economic growth generated by
entrepreneurial activities is bounded in the geographical location where it starts. The effect of growth
dampens as we move away from city centres. Therefore, the variance of innovative entrepreneurship
may be larger when investigating different regions instead of countries.
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