45
NEEDS IN MICRO AND MACRO PERSPECTIVE
ARIZONA STATE UNIVERSITY
ENT 305 - PRINCIPLES OF ENTREPRENEURSHIP
WEEK 1
4.1 INTRODUCTION:
In March 2000, the Lisbon Agenda was formulated with the aim of making the EU the
most competitive economy in the world by 2010. Entrepreneurship was given an important
role in realizing this strategy: "If Europe is to become the most competitive economic region
in the world, it is also important to create a more favorable climate for entrepreneurship."
Recently, the European Commission has launched an ambitious strategy to support
entrepreneurship by "changing the way society views entrepreneurs", encouraging "more
people to become entrepreneurs", "enabling SMEs and entrepreneurs to remain competitive",
"improving financial flows for SMEs and entrepreneurs" and "creating a more SME-friendly
regulatory and administrative framework" (Commission of the European Communities 2003).
Similar policies have been adopted by most countries over the past decades, which has
spawned a wealth of academic research on entrepreneurship and small businesses. However, it
remains unclear what the role of entrepreneurship should be compared to other drivers of
economic development: how policy measures aimed at supporting entrepreneurship at the
micro level can be incorporated into the realization of macro policy objectives such as those
envisaged by Lisbon. What agenda - and what type of research - is needed to answer these
overarching questions. The aim of this contribution is to provide a framework for addressing
these issues.
This chapter is organized around the underlying premise that, from a long-term
perspective, the allocation and exploitation of society's innovative resources is more important
than the optimal allocation of productive resources to a particular technology. I explain by
defining the concept of entrepreneurship, emphasizing the innovative dimension of this
concept. With this background, it goes on to place entrepreneurship in a broader policy
context. This section offers a framework for formulating and linking key policy-relevant
research questions. It is argued that, as part of a growth strategy, entrepreneurship should be
seen in the context of alternative and complementary drivers of economic development.
Section 3 provides a brief review of relevant research, which shows that there are serious gaps
46
in linking entrepreneurship and other drivers of economic change.
4.2 ENTREPRENEURSHIP: A TWO-DIMENSIONAL CONCEPT:
The entrepreneurship literature abounds with definitions of entrepreneurship, and
entire papers have been devoted to sorting out the differences between them (see for example,
Gartner (2001) for an interesting review). It is customary to include the definitions put
forward by classical authors such as Jean-Babtiste Say (1816) who stated that the entrepreneur
"brings together all the means of production and finds in the value of the product... the
reconstitution of all the capital he uses, and the value of the wages, interest, and rent he pays,
as well as the profits that belong to him." Another standard reference is of course Schumpeter
(1934), who defines the entrepreneur by his capacity to "make new combinations".
Schumpeter pointed out that such new combinations can "take several forms", e.g. new goods,
new qualities of existing goods, new processes, new geographical markets, new sources of
supply, etc. With this definition Schumpeter sought to cover innovation as broadly as
possible, not just market innovation (as in Kirzner's (1979) arbitrary view of the
entrepreneur).
Some authors tend to identify entrepreneurship with the formation of new ventures.
This is for example the case with Howard Gartner's (1988) recent definition of
entrepreneurship as the creation of new organizations. For the purpose of this contribution, I
will combine the start-up and innovation dimensions and define entrepreneurship as the
creation of new ventures centered on new processes, products or services. Moreover, for
reasons that will become clear soon I would like to exclude intrapreneurship from this
definition.
As shown in Table 4.1 below, the new firm formation element serves to distinguish
between entrepreneurship and (other forms of) business innovation. Although difficult to
operationalize, the innovative element is important from the point of view of distinguishing
between entrepreneurship and self-employment in established industries. Finally,
intrapreneurship implies that new (innovative) firms are founded by existing firms. Arguably,
intrapreneurship should be seen as a specialized form of entrepreneurship. Terms such as self-
employment can then be coined to cover the formation of new innovative ventures by
individuals or groups of individuals. The main reason for sticking to a narrower definition
(despite the terminological convenience) is that intrapreneurship involves its own set of
problems and possibilities. The process of forming a new enterprise by an existing company
differs in several ways from the creation of a new venture "from scratch".
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4.3 ENTREPRENEURSHIP IN CONTEXT:
How do, or should, policymakers, who want to stimulate economic growth and
development and are equipped with the above definitions and classifications, consider the role
of entrepreneurship? What kind of research questions do they (we) want to ask? Three types
of questions naturally arise. We can refer to them as input, interaction, and output questions
(see Figure 4.1 below). Input questions are concerned with how to stimulate (or how to avoid
inhibiting) entrepreneurship, intrapreneurship, business innovation and start-ups. Questions
like these can be addressed by (often rather nebulous) impact analyses that focus on the
capacity of different policy measures to actually stimulate whatever drivers are targeted. A
wide variety of different policy measures have been designed for this purpose and it is
expected that policymakers will be particularly interested in studies that explore their impact
and efficiency.
With Conditions:
•
Opportunity cost of self-
work
•
Business Failure
•
Destruction
creativity
As mentioned in the Introduction, the European Commission's strategy to support
entrepreneurship focuses on changing the way society views entrepreneurs, encouraging more
people to become entrepreneurs, enabling SMEs and entrepreneurs to remain competitive,
increasing the flow of finance to SMEs and entrepreneurs, and creating a more SME-friendly
regulatory and administrative framework. For example, while an element of creativity is
included in the Commission's definition of entrepreneurship, the section on measuring
entrepreneurship is unilaterally concerned with incentives for entrepreneurs. Thus, the main
emphasis is implicitly placed on the new firm formation dimension.
The question of interaction relates first of all to the allocation of resources and
attention to the drivers of economic renewal and revitalization. In addition, interesting policy
issues relate to the interaction between the two. For example, inventors may generate great
ideas that they cannot - or do not want to - commercialize themselves. At the same time, they
may be reluctant to pass on these ideas to established firms that have the technological skills,
marketing know-how and management competencies to realize them for fear of their ideas
48
being "stolen". Transaction costs are high in these markets.
Finally, the output question relates to the impact of entrepreneurship or innovation.
to long-term growth, national competitiveness, employment, or similar policy objectives.
4.4 RESEARCH AND RESEARCH GAPS:
There are quite a few examples of the first type of research, especially if impact
studies conducted by ministries and other public agencies are included. For example, a study
in Scotland (Scottish Enterprise 2000) showed that the so-called business birth rate strategy
has largely failed to increase the level of start-up activity, which has consistently been below
the UK average. Interestingly, a comprehensive analysis by Teasdale and McVey (2001)
concluded that the most likely explanation for this lies in macroeconomic conditions (such as
interest rates, business confidence, etc.). This finding significantly changes the "independent
variable" perspective on entrepreneurship that we will return to below. An equally important
assessment of policies to support entrepreneurship in Australia can be found in Parker (2000).
For a more comprehensive study, covering ten countries, see Stevenson and Lundström
(2001).
It is difficult to find research that explicitly addresses the discussion of where or when
to choose support for one over the other. As early as 1956, John Kenneth Galbraith believed
in it;
"There is no fiction more delightful than a technical change that is the product of the
incomparable ingenuity of a little man forced by competition to use his wits to improve his
environment. Unfortunately it is a fiction. Technical developments have long been the
preserve of scientists and engineers. To be honest, most of the cheap and simple inventions
have already been made."
(Galbraith 1956 p. 86)
In the 1980s, Sidney Winter argued that we should recognize the existence of two very
different technological regimes. He made a distinction between the entrepreneurial regime
and the routine regime, pointing out that "An entrepreneurial regime is one that favors an
influx of innovation and does not favor innovative activity by established firms; a routine
regime is one where the opposite is true."
(Winter 1984 p.297).
A deep and concrete understanding of the growth potential and demarcation lines
49
separating these broadly defined regimes seems necessary to make rational decisions about
what and how to support them (for example, to realize the Lisbon Agenda). Of course, there is
enormous variation within each regime. The entrepreneur in the entrepreneurial regime may
be a specialized supplier of components to one or a few large customers in the routine regime;
he may have started an express mail business, or produce takeaway soup. He may also have
built his business in an upcoming sector, which will gradually become part of the routine
regime with entry barriers high enough to deter new entrants. The evolution of the windmill
industry in Denmark is a good example (see for example Raghu and Karnøe 2003). The large
number of new companies established in the early stages of the "Kondratieff ICT wave" (and
also in bio-technology) is another example.
Perhaps one of the main obstacles to efficient policy-making in this area is the
complexity of the elements that make up entrepreneurial opportunities. As mentioned in the
Introduction, the European Commission aims to foster an entrepreneurial spirit, or a culture
that recognizes the value of entrepreneurs. Similar objectives can be found in the policies of
many member states, and these may have some impact. Thus, an analysis of regional
employment growth in Denmark during 1980-1993 shows that in this period growth was
strongly correlated with new firm formation, which in turn can be attributed to the level of
self-employment in 1980 (Søgaard 1997). While the absence of such culture may inhibit
entrepreneurship, the presence of such culture is only one of several contextual factors that
may or may not facilitate the formation of new and innovative firms. Other factors include
managerial and technological competencies, institutional frameworks that offer financial
opportunities, IPR protection, etc. Some researchers (Venkataraman 1997; or Shane 2000)
have emphasized the role of prior knowledge (both tacit and explicit) in discovering
entrepreneurial opportunities. The point here is that a number of factors must be present at the
same time for the opportunity to materialize.
This lucky combination of technological skills, market knowledge, managerial
competence and funding that underpins new venture success is a rare combination. Often one
or more elements are absent or too fragile to allow the new venture to succeed. As Westhead
and Birley observed in a study of business failures in the UK, "the majority of new firms will
die in their formative years" (Westhead and Birley 1994, p. 56).
However, transaction costs in the market for a product, process or business idea are
very high, and barriers in transferring such new ideas to others for professional refinement and
commercialization may be the real cause behind many business venture failures. In contrast,
the successful entrepreneurs studied by Sarasvathy (2001) are skilled at committing to
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external stakeholders and mobilizing their complementary resources in the entrepreneurial
process. In conclusion, while there is a wealth of literature on networks, on the creation of
virtual or imaginary organizations, etc., there is a lack of literature on the 'interaction problem'
in Figure 4.1 especially when it comes to the choice between realizing a business opportunity
by oneself and passing it on to others.
However, when it comes to the output side, i.e. the number of jobs or companies
new jobs created, a great deal of research has been conducted. In fact, it could be argued that
the current focus on entrepreneurship and small businesses is driven by research such as that
of Birch (1979), who found that no less than 2/3 of new (net) jobs in the US between 1969
and 1976 were established in small firms with fewer than 20 employees. Subsequent research
has changed this picture in various ways. Studies from other countries (and other periods)
provide less impressive results, and their validity has been questioned on methodological
grounds, for example by Davis et al. (1996). The objections raised by Davis and his
colleagues focused solely on statistical issues and the practical significance of these criticisms
was largely rejected by Davidson et al. (1998).
However, what is implicit in most of these studies and certainly in their interpretation
is an incremental understanding of job creation, and largely ignores the relationship between
job creation in some firms and job creation or destruction in other firms (e.g. Commission of
the European Communities 2003 p.9). From the perspective of mainstream economic theory,
the activities of both small and large firms are expected to have multiplier effects throughout
the economy. Conversely, the transfer of activities to smaller, more specialized and hence
more efficient firms can have both negative and positive impacts on employment. However,
these system effects are often overlooked, not only in policy documents but also in the
research literature on the subject (Søgaard 2006).
The compositional fallacy inherent in the additive approach is more than just an
academic problem. As we will see below, there are very good reasons why the
macroeconomic implications of entrepreneurship-for example, in terms of the number of jobs-
cannot be estimated simply by the number of jobs in new, small, or entrepreneurial firms.
Even deer are part of a larger ecosystem and policies that ignore this are bound to be
misguided.
Cross-regional or national studies that link self-employment or entrepreneurship to
growth at the regional or national level are less susceptible to this criticism. Quite a number of
similar studies have been conducted at the regional level over the years (see e.g. Hart and
Harvey 1995), but the most systematic studies at the national level have been conducted at the
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regional level. The macro level was made possible by Dutch researchers Carree, van Stel,
Thurik and Wennekers (e.g., Carree, et al., 2002; Carree and Thurik 2003, 2006).
Their research shows that the optimal level of business ownership is
in terms of generating economic growth. Although most countries have sub-optimal levels of
self-employment, there appears to be a "diminishing returns to scale". This may reflect the
alternative costs of self-employment. Even in terms of creating new jobs, some people may be
more productive as employees than as self-employed.
However, the optimal level of self-employment is not stable over time. As Carree and
Thurik observe, "from about 1870 to 1970, corporate laboratories affiliated with large
manufacturing companies were increasingly responsible for commercial research and
development" (Carree and Thurik 2003 p. 457). However, this trend was later reversed. The
trend towards larger companies began to change in the 1970s, which is often seen as a
response to the relative growth of the service sector in the most developed countries.
Moreover, as indicated above, this trend reversal may be related to the early stages of
Kondratieff's ICT wave. A more comprehensive discussion of these issues is beyond the scope
of this contribution. However, a deeper understanding of the forces and mechanisms seems
necessary to assess the possible role of entrepreneurship in the future.
At the theoretical level, several contributions have been made to integrate innovation
and entrepreneurship into macroeconomic (endogenous) growth theory. For example, the
work of Aghion and Howitt (1997) shows how creative destruction can discourage investment
in research and development by suppressing expected monopoly profits. However, it would be
wrong to claim that the dynamics of entrepreneurship and innovation have now been
organically integrated into the new growth theory. Of course, the review of entrepreneurship
research presented in this section is far from exhaustive. Nevertheless, it points to a number of
tentative conclusions.
First, there is little research to support the overall `allocation' dimension in Figure 4.1.
We cannot say what policy mix is most beneficial from the point of view of stimulating
economic growth. Second, a fair amount of research has been done on the so-called direct
policy impact (i.e. the impact of various policy measures on entrepreneurship, new firm
formation, and so on). Third, the interactions or possible interactions between the four drivers
in Figure 4.1 do not seem to have been carefully studied. Finally, there are some studies on
the `output side', (i.e., on the impact of the mentioned drivers on overall economic
performance), but these studies are conducted at a fairly high level of abstraction and tend to
treat entrepreneurship as a single independent variable.
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These shortcomings can be explained by the fact that, with few exceptions, the fields
of entrepreneurship research, innovation research, and economics seem to have a separate life.
In general, entrepreneurship research is oriented micro, utilizing various social science
disciplines (including psychology), whereas the mainstream economic approach is systems
and discipline-oriented (mono). Both innovation and entrepreneurship research are generally
multidisciplinary in nature. The sharp divide between these lines of research is clearly a
problem in the current context. First of all, understanding the relationship between
entrepreneurship and economic growth is an obvious prerequisite for policy making.
Therefore, the task of establishing this linkage at the theoretical level is potentially one of
great practical importance. However, this is no small task. In fact, it is an effort that can - and
certainly should - be undertaken by entire research programs. The main aim of this
contribution is to identify the major gaps between the different approaches and suggest
possible ways to bridge them.
4.5 INNOVATIVE DIMENSION:
As revealed in the brief overview in the previous section, we still have a long way to
go to integrate the very different approaches in entrepreneurship and growth studies in an
organic and coherent way. The accepted orthodoxy in mainstream economics has always
focused on the optimal allocation of productive resources through the operation of the
Invisible Hand market.
As mentioned above, from a long-run perspective, the optimal allocation of society's
productive resources is a matter of comparative indifference compared to the optimal
allocation of innovative resources. Conventional economics has recognized this over the
years, and as Kamien and Schwartz observe, "few argue that perfect competition allocates
resources efficiently to technical change." (Kamien and Schwartz 1975 p. 2). (Kamien and
Schwartz 1975 p. 2). The reason for this problem can of course be found in the public good
nature of new products and process knowledge.
However, perhaps due to the difficulty of estimating the scope of this problem, few
know how far we are from the optimal allocation and exploitation of society's innovative
resources. Therefore, it may be worthwhile to present a simulated version of the problem to
provide some background for considering the extent to which a market economy will reward
innovators and entrepreneurs from the point of view of microeconomic theory. I will try to
illustrate this problem using numerical examples, based on a simple Cournot competition
model. The mathematics underlying these examples is presented in the Appendix at the end of
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this chapter. Ideally, we need to integrate the micro approach into a macroeconomic context,
by examining its implications for aggregate income, investment, consumption, and so on.
Carree and Thurik (2003) provide a telling illustration of how this can be done. A purely
microeconomic approach is chosen here, to focus on the important innovative resource
allocation issues. The simulation exercise presented below illustrates a story in four
"chapters", which are believed to reflect typical real-world developments. In the "chapters"
First, new markets were created and innovators enjoyed a monopoly on the production of new
goods. But this happy situation does not last long. After some time, competition emerges,
imitating the production costs incurred by the innovator but not his initial expenditure on
innovation. To keep things simple, the cost of imitation is ignored.
In the second 'chapter' of the story, one member of the oligopoly develops a process
improvement that reduces variable or fixed production costs. Adam Smith observed, in The
Wealth of Nations, that with 'prudent management' a dyer could profit from a trade secret for
many years and even pass it on to his children and grandchildren (Smith 1978 p. 163). This is
hardly possible today. Empirical studies conducted by Mansfield in the early 1980s
(Mansfield et al., 1981; Mansfield 1985) showed that even process knowledge is often
disseminated to competitors within a few years. In the third chapter a new product is launched
that is a replacement for an existing product. Again, the innovator may or may not enjoy a
monopoly. The underlying assumption is that prospective profits for the innovator are likely
to lie in the interval between monopoly and the extremes of oligopolistic competition.
In this simple Marshallian model, the potential welfare gain, W, from innovation
amounts to:
W = (Potential change) consumer surplus + profit - innovation costs
We might expect that a rational regulator, in trying to provide the right incentives to
innovate, would come as close as possible to the cardinal rule that innovators should benefit
from innovation when the potential net benefits are positive and vice versa. Therefore, it is
worthwhile to consider the costs of innovation in relation to the gross benefits (i.e. consumer
surplus plus profits). Unfortunately, consumer surplus cannot be observed in real life.
Therefore, it is very difficult to assess how close or far the economy is in applying this
"golden rule" in practice. Hence the relevance of the simulation exercise.
To begin with, let's consider the golden rule in relation to monopolists. Suppose the
demand curve is given by P = 100 - 1.5 × Q and assume no competitors enter the market. For
54
a fixed cost C = 100, a variable unit cost c = 10, and an innovation cost equal to 20% of the
potential (gross) benefit of innovation, Fig. 4.2 below illustrates who benefits and who loses,
depending on the market situation.
In the monopoly situation in Figure 4.2, entrepreneurs realize just over half (51%) of
the potential social gains, while consumers realize about 41%, and the rest are (modest)
deadweight losses. The golden rule clearly does not apply. Even if a monopoly position can
be secured, innovation costs that exceed 61% of the total gross profit will hurt innovators in
that market. This percentage is inversely proportional to the size of the market.
However, competitors tend to enter profitable markets, and the number of competitors
depends on the slope of the demand curve. In this particular example, there is room for no
more than six competitors including the innovator. Unlike the innovator, competitors are not
burdened by innovation costs, and comparing the black columns for the innovator and its
competitors shows that the innovator will probably be eliminated. Now, turn to the second
oligopoly model. A symmetric oligopoly has been formed here, and an innovation is
suggested that reduces the unit cost of the variable (thus increasing the scale of output) (from
10 to 2). In a `monopoly' situation, one member of the oligopoly has developed an innovation
and is the only one to implement it. New symmetric oligopolies arise when innovations leak to
competitors. As above, innovation costs are assumed to be up to 20% of potential gross profits
- and even with monopoly guarantees, the innovator will lose out if these costs exceed 50%.
As shown in Figure 4.3, consumers may actually experience losses from cost-saving
innovations in the case of `monopoly'. A technological monopoly allows the innovator to
capture market share, resulting in one competitor leaving the market. As a result of this
concentration, market prices increase beyond pre-innovation levels. Again, if the innovation is
copied by a competitor, then the innovator loses out in all respects. Alternatively, consider the
implications of reducing fixed costs (thus lowering returns to scale) by changing the cost
structure from C = 100 to C = 40, while keeping variable costs at c = 10. In Figure 4.4, neither
competitors nor consumers are affected by this change as long as the innovator keeps the
innovation for itself. However, the realization of the potential benefits of this innovation is
small, only 7% in fact.
As before, innovation costs have been set at 20% of total gross benefits. Spending
above 26% will cause innovators to lose money even in a `monopoly' situation.
In this case, when the innovation leaks to competitors, it may have a strong impact on
the industry structure, allowing more new entrants and increasing competition. Even in the
best case, this harms the profits of both the innovator and its competitors, and the real
55
beneficiaries are consumers.
If total costs are assumed to reflect the number of jobs in the industry, then both cost-
saving innovations will tend to reduce employment in the sector. Finally, in the fourth
"chapter" of this short history, a new and superior product is introduced. Suppose the two
markets are related such that
𝑃𝑥 = 𝑎 - 𝑘𝑍 - 𝑏𝑋
when
𝑃𝑧 = 𝑢 - 𝑘𝑋 - 𝑣𝑍
Further, suppose the new product is superior to X (i.e., u > a) and is an imperfect
substitute of X. More specifically, suppose a = 100, u = 150, b = v = 1.5 and k = 1. For
simplicity, the production cost is assumed to be the same for both X and Z (C = 100, c
= 10). Innovation expenditure amounts to 20% of maximum gross benefits (in addition to
consumer surplus and profits). Note that oligopolistic excess capacity costs are considered
socially necessary. Figure 4.5 below shows who benefits from the innovation. In the left
column, the entrepreneur (producer Z) enjoys a monopoly on the production of Z, while in the
right column, competitors have entered the market.
It is assumed here that innovation expenditure amounts to 20% of gross benefits. In a
monopoly situation, the entrepreneur will be rewarded as long as his innovation costs are
below 60% of the gross benefits of the innovation. Despite the losses incurred by the 'old'
competitors (who are producing the original good X) is relatively small, in this example the
losses they incur are sufficient to reduce their number from 6 to 3. The case illustrated in
Figure 4.5 is particularly pertinent to the development of information goods. If protection of
good "X" effectively prevents innovation of good "Z", then intellectual property rights
designed to encourage innovation may have the opposite effect. This argument is made in the
context of software development, where the ability to use existing software as input into the
development of new versions is critical. But the problem applies more generally.
Of course, the results of the exercise should be treated with caution. For example, it is
clear that Bertrand's oligopoly model would give different results. Moreover, the use of the
theoretically more appropriate variation in compensation versus Marshall's consumer surplus
would have yielded (small) differences. A number of factors can serve to mitigate the
innovation disincentives revealed in this exercise. For example, research on absorption
capacity and innovation spillovers suggests that these can strengthen the incentives of
established firms to invest in research and development. In addition, the costs of imitation are
56
likely to be non-negligible. But again, the impact of uncertainty and costs of law enforcement,
strategic patents, etc. have not been taken into account. Such costs may be considerable. For
example, according to Harbaugh and Khemka (2000, p.5), "A check conducted in September
1999 by the Business Software Alliance (BSA) found more than two million websites
worldwide offering, linking to, or discussing pirated software under the standard term
"warez". Similarly, BSA recently found over 368,000 web pages offering "patches" or
"crackz" to defeat copy protection measures". The flip side of this compliance problem is seen
in the high enforcement costs associated with detecting and addressing violations.
Conclusion:
Against the backdrop of the Lisbon Agenda, this contribution questions the dominant
discourse linking entrepreneurship and growth. Starting from the premise that the allocation
and exploitation of society's innovative resources in the long run is more important than the
optimal allocation of productive resources to specific technologies, three tentative conclusions
can be drawn.
First, it seems that greater emphasis should be placed on the innovative (rather than
start-up) dimension of entrepreneurship. It is unclear how and to what extent entrepreneurship
with little or no innovative content is considered to contribute to overall growth. Although
statistics show a high failure rate of newly established firms, we do not know to what extent
new firms actually create their own demand and to what extent they give up or survive at the
expense of existing firms.
Second, when it comes to more innovative forms of entrepreneurship, simple
simulation experiments show that the relationship between entrepreneurship and employment
depends strongly on the nature of the innovation at its center. While the creation of
completely new markets or the introduction of complementary products can indeed add to
total activity, entrepreneurship based on cost-saving innovations can actually reduce overall
employment, at least in the short to medium term. Hence, it is clear from the above that
treating entrepreneurship as a single independent variable, practically synonymous with the
concept of self-employment, is unsatisfactory. The type and importance of innovation
underlying new firms must be taken into account, as well as the costs of alternative start-ups.
Third, as part of a growth strategy, entrepreneurship should be seen in the context of
alternative and complementary drivers of economic development. A brief review of relevant
research shows that there are serious gaps in linking entrepreneurship and other drivers of
economic change. Fourth, if the proposition that long-term competitiveness depends on the
57
optimal allocation of innovative resources is correct, then this suggests that the second-best
form of appropriation governing innovation incentives may be far from meeting the "golden
rule" standard. This calls for innovative revisions to the IPR system, especially with regard to
new information technologies. Simple microeconomics suggests that in a competitive
environment, too many innovative entrepreneurs are likely to fail due to feasibility issues. In
principle, even highly socially desirable innovations can bankrupt their creators because of
this. Apart from some anecdotal evidence, we don't know how often this happens, but
Sarasvathy's finding that successful entrepreneurs tend to adhere to the "affordable loss
principle" is quite consistent with lessons from theoretical models. In summary, there appears
to be a serious need to adopt a more holistic basis for informing and assessing policies to
stimulate entrepreneurship and a shift in focus towards the innovation dimension of this
important phenomenon.
SOCIAL CAPITAL AND REGIONAL ENTREPRENEURSHIP
5.1 INTRODUCTION:
In the history of economic analysis, various variables have been considered to explain
the progress of a country. Traditionally, mostly quantitative variables have been considered.
During the twentieth century with the introduction of endogenous growth models and
improved statistical methods and data information, qualitative variables have been quantified.
Examples include: democracy, corruption, rule of law, social capital, and entrepreneurship.
These variables now have quantitative measures that are used in analyzing many economic
issues.
Social capital is not a new concept. The name "social capital" was formulated by
Hanifan (1920) in the first decade of the twentieth century. Earlier economists have also
considered the concept of social capital. For example, in the writings of Adam Smith (1776)
we can find references to this concept and its impact on productivity and economic growth.
Alfred Marshall (1890), among others, is also another example worth considering. Social
capital is produced and accommodated in social relationships; it does not reside in material
objects owned by individuals. It is the result of behavioral strategies undertaken consciously
or unconsciously by individuals seeking to gain current and/or future advantages (Bourdieu
1986).
On the other hand, entrepreneurial activity is one way to increase employment and
58
production. It means, among other things, that someone discovers the possibility of making
some profit and then decides to invest. However, this is not a new variable. In the economic
literature one can find several references to this concept.
Therefore, entrepreneurship has a positive impact on economic growth. It is therefore
interesting to know the factors that enhance entrepreneurship. Several things have been
considered, mainly related to public policy and economic behavior. However, social capital
can have a relevant role in the process, as the existence of established organizations can
actively encourage the pursuit and development of new activities. And social capital plays a
relevant role in this drive, sometimes facilitating the resources needed to create new
businesses. This book will discuss social capital and entrepreneurship in the Spanish region.
5.2 DEFINITION OF SOCIAL CAPITAL
The concept of social capital was mainly developed by sociologists and economists
who have recently introduced it in their analysis. More recently, the concept has been
introduced in the analysis of economic growth (for a more extensive analysis of the concept,
see Fornoni et al., 2008). Different definitions of social capital have been discussed in the
literature. This conceptual vagueness has had two main consequences. First, it has facilitated
its use among the social sciences. Second, it is an obstacle to empirical and theoretical social
capital research. For example, Coleman (1990) highlights the social structure of entities and
their ability to facilitate some individual activities; Narayan and Prichett (2000) consider the
economic impact and reinforcement of relationships between individuals; Burt (1992)
highlights contacts between individuals and the possibility of using other types of capital;
Portes (1998) considers the capacity of individuals to use scarce resources and the attributes of
their membership in networks. Putnam (1993) distinguishes between connecting relationships
between different individuals that have a positive impact on society and exclusive
relationships that have a negative impact on economic growth. Finally, Woolcock and
Narayan (2000) define social capital as the norms and networks that enable people to act
collectively, reflecting both individualistic and communal notions of social capital.
In general, according to Durlauf and Fafchamps (2005, pp. 1643-1645) three main
groups of definitions can be distinguished:
1. Definitions that emphasize the social impact of beneficial capital on social aggregates. In
this group, the definitions of Coleman (1990) and Putnam et al. (1993) can be included.
Putnam et al.'s definition emphasizes certain forms of informal social organization,
including trust, norms and networks. Coleman (1988) defines three different forms of
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social capital: (1) obligations, expectations and trust in social relationships; (2)
information channels; and (3) effective norms and sanctions.
2. Definitions that consider social capital in terms of relationships or interdependence
between individuals. In this group, the definitions of Putnam (2000), Ostrom (1990) and
Bowles and Gintis (2002) can be included, among others.
3. Some definitions of social capital. Fukuyama's (1995) definition only includes certain
shared norms and values that must be considered as a group.
According to Bourdieu (1986, p. 249) the volume of social capital in a society depends on the
extent of network connections to be mobilized and the volume of capital owned by individuals
in the network. Therefore, the main feature that distinguishes social capital from other
institutional relationships is that social capital is the result of an investment strategy that
focuses on the formation and maintenance of networks. And these investments can create new
relationships and/or change existing ones. Thus, the accumulation of social capital depends on
ongoing exchanges within a social relationship.
Considering the second group, the general definition is that social capital includes social
networks and the norms associated with these networks that create value in individuals
(Putnam and Goss 2003, p. 14). So, in this concept, it does not only consider institutions, but
also the behavior of economic actors in society by considering the cooperation between them.
In this case, different elements and values have to be included such as honesty, mutual
agreement... which is the most important element of the network increases productivity and
ultimately economic growth. Social capital then implies increased trust and cooperation
between individuals leading to a more prosperous society, facilitating people-to-people
contagion and the acceptance and assimilation of new technologies. In many instances, it also
helps families to transfer financial resources to their members and in this way obtain funds to
finance their knowledge and the acquisition of their investments (Fukuyama 1995; Putnam
1993; Woolcock 2002; Woolcock and Narayan 2000). Therefore, if this definition is accepted,
social capital has an indirect impact on economic growth, as social capital implies the
implementation of adequate legal structures (Chhibber 2000, pp. 299-306).
The concept of social capital is difficult to measure as it is a very ambiguous concept. Data
There are very few studies on this subject, making empirical research difficult. One possibility
is to consider the behavior of some social institutions, such as families, political
associations.... In terms of local data, it is sometimes quite difficult to obtain such
information. Therefore, it is common to use data on families and the use of technologies that
facilitate relationships between individuals.
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Finally, it is interesting to note that some economists, such as Arrow (2000) and Solow
(2000), consider that social capital is not a relevant factor and can be included in the broad
concept of human capital. However, other authors consider social capital to be different from
other forms of capital. In this regard, Robison et al. (2002) state that the main difference is
that social capital exists in a social relationship. In contrast, human capital usually resides in
individuals only, but this does not mean that the creation of human capital is not collective.
5.3 ENTREPRENEURSHIP AND SOCIAL CAPITAL
Recently, the economic growth literature has emphasized not only quantitative factors
but also qualitative factors. An increase in empirical data supports this possibility and
entrepreneurship is one of the factors included in the analysis. Entrepreneurial activity has a
positive influence on economic growth because it requires a group of interested peopleto take
therisk of using their funds to establish new firms and businesses. However, it is also
necessary to take into account the indirect impactshown byHolcombe (1998). According to
him, certain entrepreneurial behaviors not only encourage other entrepreneurs to follow their
example, but also create new opportunities that can be explored by third parties.
Of course, an adequate environment or climate is needed to support these activities. In
this case, the "rule of law", protection of private property, degree of freedom, trade
agreements, etc., are necessary conditions to create such an environment (Harper 1998; North
1994; Bahmani-Oskooee and Nasir 2002). Additional factors such as adequate social capital
are also required to enhance entrepreneurial activities that will positively impact investment
and economic growth, as shown in Figure 5.1.
In general, the literature considers the importance of social capital in the field of
entrepreneurship to be associated with the fact that they provide resources, access to resources
or emotional support (Birley 1985; Lin 2001). In this case, its relevance is due to the fact that
entrepreneurship is associated with innovation and competitive advantage. Therefore, not only
public policy initiatives that encourage the emergence of new businesses are needed, but also
the presence of established organizations that actively encourage the pursuit and development
of new activities. And social capital plays a relevant role in this impetus, sometimes
facilitating the resources necessary to create new businesses.
In this case, there are two direct benefits that social capital brings to entrepreneurs:
resources and information. Individuals can obtain financial resources from parents and other
family members. These resources are cheaper than resources obtained from financial
institutions, making the investment process easier. Also, individuals can obtain formation and
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education financed by the family. This increased formation is also important for developing
enterprises as it not only facilitates the assimilation and introduction of technological
advances but also deals with modifications in the economic environment in a more effective
manner. However, such formation can also have a negative impact from a labor perspective.
Improved education can increase wages and, as mentioned earlier, discourage entrepreneurial
activity, leading to wage earners rather than entrepreneurs. Social capital facilitates access to
information which is also a relevant factor of entrepreneurial opportunities, increasing the
relevance and quality of information (Adler and Kwon 2002; Burt 1992; Shane and
Venkataraman 2000).
An additional impact that can be added is the creation of a favorable entrepreneurial
environment, which from a historical point of view is sometimes unheard of. Some literature,
both economic and non-economic, shows the entrepreneur as a profit-seeking individual who
acts in his own self-interest. He only seeks to achieve his personal gain without being
interested in the consequences of his activities on other economic agents. In such an adverse
environment, it is quite difficult to incentivize entrepreneurial activity. As stated by Solomon
(2002), entrepreneurs need to use their ingenuity to develop their tasks and by no means do
they lie or try to take advantage of others.
Overall, there are several channels through which to consider the relationship between
entrepreneurship and social capital. Entrepreneurship is closely linked to innovation and
competitive advantage. The importance of entrepreneurship is evident not only in public
policy initiatives that encourage the development of new businesses but also in established
organizations that actively encourage the development and pursuit of new opportunities. It is
therefore expected that there is a positive relationship between social capital and
entrepreneurship and will indirectly also increase economic growth.
5.4 EMPIRICAL ANALYSIS
In this section we attempt an empirical analysis of the relationship between social
capital and entrepreneurship for the case of Spanish regions using data over the period 2000-
2004.
Two equations are estimated: (1) & (2)
𝐸𝑖𝑡 = 𝛽0 + 𝛽1𝑆𝐶𝑖𝑡 + 𝜇,
𝑦𝑖𝑡 = 𝛽2 + 𝛽3𝑃𝐼𝑖𝑡 + 𝛽4 𝐼𝑖𝑡 + 𝛽5𝐸𝑖𝑡 + 𝛽6𝐾𝐻𝑈𝑖𝑡 + 𝜇
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Equation (1) shows the relationship between social capital (SC) and entrepreneurship
(E). As we explained in the previous section, we estimate β1
is positive.
Equation (2) is a growth equation where y denotes GDP, PI is public investment, I is
private investment, E is entrepreneurial activity and KHU is human capital. The expected
signs of the coefficient estimates are positive for all variables, except PI. In this regard, some
authors argue that fiscal policy has a negative impact on private investment as well as on
economic growth, due to crowding-out effects (e.g., Alesina and Rodrick 1994; Bertola 1993;
Perotti 1993; Persson and Tabellini 1994, among others). However, other studies (Bénabou
1996a,b; Bourguignon and Verdier 2000), conclude that redistributive policies will have a
positive impact on investment through various means: increasing public investment (Saint-
Paul and Verdier 1993) or reducing credit market imperfections or liquidity restrictions that
negatively affect physical and human capital investment (Aghion and Bolton 1992; Banarjee
and Newman 1993; Galor and Joseph 1993; Perotti 1993; Piketty 1997).
The main issue is how to measure entrepreneurship and social capital. In the case of
the former, we use the number of businesses created in the region. The information provided
by the TEA (Total Entrepreneurship Activity) index created by GEM (Global
Entrepreneurship Monitor) is the best source that provides data. However, we do not have an
index for the whole region and the whole country period. We therefore decided to use the
number of companies in each region as an alternative measure.
Regarding social capital, we do not have regional information. In empirical studies,
social capital is usually measured by the number or intensity of relationships between
economic actors; or as a general level of 'trust', or as a level of civil society (Durlauf 2002).
Based on these possibilities we decided to build an indicator taking into account one of the
most relevant social institutions, namely the family and possible relationships between
individuals. For this reason we have constructed social capital proxy variables in the form of
number of marriages and internet usage. For each model, the variables are used at their
respective levels and for each year. Each model is estimated using the Ordinary Least Squares
method annually using cross-sectional data of 17 observations from each region. Then data
were pooled across regions over time and the model was re-estimated using 85 observations
from 17 regions over the period 2000-2004. The results are reported in Tables 5.1 and 5.2.
Clearly Table 5.1 shows that social capital has the expected positive coefficient and is highly
significant in all models. Therefore, an increase in social capital will have a positive impact on
entrepreneurship.
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Table 5.2 also shows that all the estimated coefficients follow our theoretical
expectations, except in the case of human capital. Clearly, entrepreneurship has a positive and
significant impact on economic growth. The results from both tables lead us to conclude that
social capital will increase economic growth through its effect on entrepreneurship.
Conclusion:
In this chapter we have analyzed the relationship between social capital and
entrepreneurship. Social capital provides entrepreneurs with information and resources that
are cheaper than those provided by financial institutions. These resources are necessary for
them to develop and support their activities. In this sense, entrepreneurship is closely linked to
innovation and competitive advantage. The importance of entrepreneurship is evident not only
in public policy initiatives that encourage the development of new businesses but also in
established organizations that actively encourage the development and pursuit of new
opportunities. Therefore, a positive relationship between the two factors is expected.
Moreover, since entrepreneurship is considered an important factor that enhances
economic growth, social capital should also show a positive impact on economic growth
indirectly. To test this hypothesis, we conducted an empirical study by taking data from 17
Spanish regions over the period 2000-2004. The results obtained confirm the two main
hypotheses that an increase in social capital increases entrepreneurship. In turn, increased
entrepreneurship will stimulate economic growth.
