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.
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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
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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
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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
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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.
Mean
Maximum
Minimum
Std. Dev.
Observations
LN INNOVATIVE
ENTREPRENEUR
1.43
13.97
0.01
2.24
57
URBAN
POPULATION
73.03
ETHNIC
FRACTIONA-
LISATION
0.32
100.00
30.93
0.75
0.0002
15.79
57
0.24
57
LANGUAGE
FRACTIONA-
LISATION
0.24
0.87
0.0003
0.23
57
Table 1:
Descriptive statistics
RELIGION
FRACTIONA-
LISATION
0.34
0.86
0.005
0.24
57
CORRUPTION
CONTROL
0.62
2.41
-1.08
1.10
57
LEGAL
STRENGTH
6.07
10.00
1.00
2.51
57
EDUCATIONAL
ATTAINMENT
9.65
12.68
4.90
1.87
57
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:
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ln(𝑖𝑛𝑛𝑜𝑣𝑎𝑡𝑖𝑣𝑒⁡𝑒𝑛𝑡𝑟𝑒𝑝𝑟𝑒𝑛𝑒𝑢𝑟) = 𝛽
0
+ 𝛽
1
⁡ (𝑢𝑟𝑏𝑎𝑛⁡𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛) + 𝛽
2
(𝑒𝑑𝑢𝑐𝑎𝑡𝑖𝑜𝑛) + 𝛽
3
(𝑐𝑜𝑟𝑟𝑢𝑝𝑡𝑖𝑜𝑛⁡𝑐𝑜𝑛𝑡𝑟𝑜𝑙) + 𝛽
4
(𝑙𝑒𝑔𝑎𝑙⁡𝑠𝑡𝑟𝑒𝑛𝑔𝑡 ℎ
)
+ 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
CONSTANT
Coefficient
-6.40
URBAN POPULATION
EDUCATIONAL ATTAINMENT
CORRUPTION CONTROL
LEGAL STRENGTH
R-squared
0.02
0.28
0.44
0.16
0.72
0.70 Adjusted R-squared
Table 2: regression outcomes for hypothesis 1.
Prob.
0.00
0.02
0.001
0.01
0.01
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.
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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
C
Coefficient
-4.282667
Prob.
0.0000
URBAN POPULATION 0.056462
ETHNIC FRACTIONALIZATION -1.421097
R-squared 0.413440
Adjusted R-squared 0.392859
0.0000
0.0478
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.
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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
C
URBAN POPULATION
LANGUAGE
FRACTIONALIZATION
R-squared
Adjusted R-squared
Table 4: regression outcomes language
Coefficient
-5.639418
0.065473
1.028571
0.388831
0.367003
Prob.
0.0000
0.0000
0.1800
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.
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Dependent Variable: LN INNOVATIVE ENTREPRENEUR
Variable
C
Coefficient
-5.344104
Prob.
0.0000
URBAN POPULATION
Adjusted R-squared
Table 5: regression outcomes religion
0.055955
RELIGION FRACTIONALIZATION 1.869071
R-squared 0.442945
0.423050
0.0000
0.0084
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.
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URBAN
POPULATION
URBAN
POPULATION 1.000000
RELIGION
FRACTIONA-
LIZATION
LANGUAGE
FRACTIONA-
LIZATION
ETHNIC
FRACTIONA-
LIZATION
RELIGION
FRACTIONA-
LIZATION 0.103890
LANGUAGE
0.103890 -0.303521 -0.263907
1.000000 0.275382 -0.013941
FRACTIONA-
LIZATION -0.303521 0.275382 1.000000 0.540949
ETHNIC
FRACTIONA-
LIZATION -0.263907 -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
Coefficient
-6.21
Prob.
0.00
0.03
-0.69
0.02
0.31
URBAN POPULATION
ETHNIC FRACTIONALIZATION
RELIGION
FRACTIONALIZATION
LANGUAGE
FRACTIONALIZATION
EDUCATION
CORRUPTION CONTROL
LEGAL STRENGTH
R-squared
Adjusted R-squared
Tabel 7: regression outcomes hypotheses 2
0.32
0.71
0.27
0.40
0.13
0.73
0.69
0.60
0.33
0.003
0.03
0.04
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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
CONSTANT
Coefficient Prob.
-6.23 0.00
URBAN POPULATION
INTERACTION ETHNIC
INTERACTION RELIGION
0.03
-0.01
0.002
0.03
0.36
0.81
INTERACTION LANGUAGE
EDUCATION
CORRUPTION CONTROL
LEGAL STRENGTH
R-squared
Adjusted R-squared
0.01
0.27
0.40
0.14
0.73
0.69
0.30
0.002
0.03
0.03
Table 5: regression outcomes hypothesis 3
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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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