1. 1
Revisiting Schumpeter: Understanding the conditions associated with variation in the
assumption of entrepreneurial risk
ABSTRACT
Schumpeterian theory on entrepreneurship has been regarded as “the most fascinating as well as
the most promising theory of entrepreneurship that we have”, but that more development of this
theory is necessary so that it can meet its full potential (Swedeberg. 2007: 2). Our study aims to
develop Schumpeter’s theory on economic development by examining the conditions under
which family, government, and banking institutions are more likely to assume the
risk/uncertainty associated with entrepreneurial behavior. We argue that environmental
uncertainty, the formality-informality of the enterprise, the spread of distancing demolishing
technologies, and availability of financing from banks influence which institutional actor is more
likely to assume the risk/uncertainty associated with entrepreneurial behavior. We develop and
test our hypotheses using a sample of 9565 new ventures from the Hashemite Kingdom of
Jordan. Overall, the study contributes to Schumpeterian theory on entrepreneurship, as well as to
theory at the nexus of institutional theory and entrepreneurship by understanding the
environmental conditions that support the institution or practice of entrepreneurship (Tolbert et
al. 2011). Results support our hypotheses.
Keywords:
Entrepreneurship; Institutions; Economic Development
Introduction

2. 2
There has been an increasing amount of discussion for the need for theoretical
development and extension within the field of entrepreneurship (cite). Despite a substantial
amount of the theoretical work in the field of Entrepreneurship has emerged more recently, the
theory of Entrepreneurship initially proposed by Schumpeter in 1917 has continued to influence
the field. Despite a vast number of more recent theories of entrepreneurship, Swedberg has
argued that of “all the theories of entrepreneurship that exist, Schumpeter’s theory is still, to my
mind, the most fascinating as well as the most promising theory of entrepreneurship that we
have” (2007: 2). He goes on to argue that despite the promise of Schumpeter’s theory, further
understanding would be necessary before an extended theory can be developed. The aim of this
paper is to contribute to that effort by examining the variations in institutional sources of funding
used by entrepreneurs to start new ventures in a developing economy. Building on Schumpeter’s
view that entrepreneurial risk falls on the bank or other source of credit, we seek to identify
conditions or factors that may encourage entrepreneurs to prefer alternatives to prevailing formal
financial institutions for the provision of financing and bearing the risk/uncertainty associated
with new venture formation. Specifically, we acknowledge the role of the family institution and
the role of government institutions as major alternative institutional actors capable of assuming
the risk/uncertainty associated with entrepreneurship in developing economies.
Using data provided by the Jordanian Ministry of Planning and International Cooperation
we analyze the variation in funding sources used by entrepreneurs to start new ventures in the
country of Jordan from 2002-2013, we test hypotheses grounded in the Institutional perspective
in order to identify the conditions that influence this variation. This would extend Schumpeter’s
theory of entrepreneurship by including the family and the government as institutions actively
assuming risks/uncertainty related to entrepreneurial behavior, and by demarcating conditions

3. 3
under which a certain institution (the family, government, or bank) may assume that role more
prevalently in a developing context.
Theory and Hypotheses
Entrepreneurship and Schumpeter’s theory
Generally, entrepreneurial activity refers to the activities by which economic
opportunities are discovered, evaluated, and exploited (Shane and Venkatraman, 2000). The
heart of most entrepreneurial activity is the founding of a new organization, and the analysis of
entrepreneurial activity, therefore, often includes concepts such as independent business
ownership and self-employment (Gartner, 1988; Low and MacMillan, 1988; Shook et al., 2003;
Parker, 2009). While other views of entrepreneurship identify other entrepreneurial actions such
as introducing a new product, creating a new market, or reorganizing an existing market, the
current study will focus on the entrepreneurial act of organizational creation in order to exploit
some type of economic opportunity (Schumpeter, 1934). Acts of entrepreneurship can range
from actions of calculated risk to actions of uncertainty (Knight, 1921; Mazzucato, 2014).
Schumpeter’s economic model postulates that for entrepreneurship to occur within an
economic system, two central actors must come together: the entrepreneur, and the financier who
assumes the risk or uncertainty of the entrepreneur’s activities. Within this model, Schumpeter
focuses on banking institutions as the primary institutional actor that assumes the risk for
entrepreneurial activity (Schumpeter, 1934; +handbook and page). Banks, however, are only one
of many possible institutions, formal or informal, that could link with the entrepreneurial actor
and assume the risk/uncertainty of organizational creation. Noticeably absent from Schumpeter’s

4. 4
consideration of major possible actors assuming the risk/uncertainty of entrepreneurship are
government institutions.
Despite views that government institutions are slow, low-risk, and static institutions,
recent work on innovation and entrepreneurship has noted the state’s pivotal role in the early
investment of high risk and uncertain economic endeavors (Mazzucato, 2014). The US
biopharmaceutical industry, for example, emerged and was guide by government investment and
spending, not primarily by private financial institutions (Mazzucato and Dosi, 2006).
Understanding economic dynamism, therefore, would be incomplete without understanding the
conditions that encourage entrepreneurial risk to be assumed by government institutions and not
financial institutions.
In addition to formal institutions, both financial and state, it is important to consider the
informal institutions which shape economic activity and entrepreneurship. For example,
Polanyi’s (1957) seminal work analyzing the economy as an instituted process highlights the
importance of understanding the greater social institutions within which economic activity is
embedded:
The human economy, then, is embedded and enmeshed in institutions, economic and
noneconomic. The inclusion of the non-economic is vital. For religion or government
may be as important for that structure and functioning of the economy as monetary
institutions or the availability of tools and machines themselves to lighten the toil of
labor. (p250)
Although Schumpeter recognizes that individuals could provide new venture capital, he neglects
to discuss which individuals and under what conditions. Given the family’s institutionalized role
in society, our study will build on Schumpeter’s theory by understanding the conditions under
which entrepreneurs may choose this central social group as its financier over bank or

5. 5
government institutions. To do this, we consider the nature of the family institution in light of
events occurring in the entrepreneur’s external environment.
Overlooking these institutional alternatives limits the utility of Schumpter’s theory given
the foundation roles that the institutions of family and government play in shaping economy and
society. Organizational performance is strongly affected by its institutional linkages. Baum and
Oliver (1991), for example, analyzed the impact of institutional linkages on the failure of
organizations in the childcare industry from 1971 to 1987, and they found that organizations with
linkages to governmental institutions had significantly higher survival rates in this industry.
More recently, Pahnke, Katila, and Eisenhardt (2015) examined how VCs, CVCs, and
government agencies affected the ease by which new firms moved down the path from
innovation to revenue. Their study found that new ventures performed more effectively when
VCs were the funding partner that assumed the risks associated with the enterprise. Furthermore,
they found that the reason was not so much due to the resources, power, or incentives of the
funding partner, but rather due to the specific type of institutional logic which the funding
partner brought to the enterprise through the relationship. Venture capitalists were influenced by
a professional logic that is characterized by norms “for deep engagement with client-
entrepreneurs…VCs actively and even aggressively work with their entrepreneurial partners to
achieve product innovations” (Pahnke et al., 2015). Yet, while there are studies discussing
organizational linkages and funding partners, to the author’s knowledge studies have not directly
addressed this glaring omission in Schumpeter’s theory in an attempt to officially propose
changes that develop its utility. Furthermore, notably absent from these studies is the inclusion of
the family as an institution assuming the risks or uncertainty of entrepreneurship. Evidence
suggests that the family institution is the social actor which most often assumes the risk of

6. 6
entrepreneurship (Zahra, 2005). Zahra and Sharma (2003), for example, conducted a
multinational study of new venture formation and found that the family was a key source of
funding for new ventures. Moreover, according to the Family Firm Institute, 85% of new
ventures are financed using family money (European Family Business, 2012). Finally, in the
United States, “family owners risked over US$86 trillion in family assets - not business assets-
for the sake of their businesses” in 1996 (Olson et al., 2003).
The aforementioned descriptive statistics strongly suggests that the family institution is
still a primary social actor which assumes the risk related to new venture formation in both
developed and developing economies. However, as mentioned earlier, the prevalence of the
family-funded entrepreneurship is still largely unexplained (Carney et al. 2013; Mishra &
McConaughy, 1999; Anderson et al., 2003). Thus, our study attempts
The financier, therefore, could be a range of institutional actors: traditional banking
institutions, other financial institutions (VC, private equity), government institutions, and the
family institution among others. It becomes critical, therefore, to understand the environmental
conditions that could predict the prevalence of one institutional actor acting as financier over
other actors, as well as understanding whether that actor’s assumption of the financier role under
those conditions actually increases that new organizations performance under those conditions
(ie survivability and profitability). As stated earlier, the current study focuses on hypothesizing
the conditions under which family-funded entrepreneurship is more prevalent.
Hypotheses
The developing world is dominated by multi-generational, extended, and tribal family
structures which are typically patriarchal and hierarchical with regards to age and sex

7. 7
(Abudabbeh, 1996). The families are also intensely collectivistic. Successes and failures of one
family member is the success or failure of the family as whole, and all members cooperate to
secure a family livelihood as well as improve family reputation within the community (Barakat,
1993). For this reason, certain pursuits, such as entrepreneurship, which are considered normal
individualistic pursuits by Western standards, are subject to intense scrutiny by family leaders.
Furthermore, given the extended nature of the family, that family leader is often an uncle or
cousin rather than one’s father (Abudabbeh, 1996). Therefore, theories based on interactions
between Western nuclear families and business enterprises are not likely to provide the ample
explanations needed to explain the prevalence of family-funded business activity in many
emerging markets. Thus, several “opportunities for conceptualization exist throughout the world
in family-owned business research” (Wortman, 1994).
We argue that the primary driver of family-funded entrepreneurship is the presence of
uncertainty rather than risk to be assumed by funding institutions given the environment. Acts of
entrepreneurship can be undertaken in environments that range from calculated risk to
uncertainty (Knight, 1921; Mazzucato, 2014; Guseva and Rona-Tas, 2001). We suggest this
level of uncertainty may be influenced by either an endogenous or exogenous shock to the
environment. In Guseva and Rona-Tas’ (2001) study comparing the creation of credit card
markets in the United States and Russia, they argued and found that if there exists in the
environment formal institutions that can create “similarity across cases, similarity over time, and
sufficiently large numbers of past observations” then entrepreneurial actors will be able to
operate in environments of calculable risk as opposed to environments of uncertainty. The
authors also found that in the absence of formal institutions reducing uncertainty to calculable
risk, entrepreneurial actors (in this case banks seeking to create a credit card market in Russia)

8. 8
resorted to utilizing informal family ties in order to create the new market because of the high
degree of trust in family (Guseva and Rona-Tas, 2001). We apply Guseva and Rona-Tas’
theoretical model to the entrepreneurial act of organizational creation. Under conditions where
the environment allows entrepreneurs to operate through calculable risk, entrepreneurship funded
by formal institutions such as financial institutions and government institutions will be more
prevalent. However, under conditions where the environment is characterized as uncertain, then
entrepreneurship funded by the family institution will be more prevalent. In other words, when
exogenous shocks create a level of uncertainty that formal institutions cannot reduce to
calculable risk, entrepreneurs will link to informal institutions such as the family in order to have
their entrepreneurial action funded, thereby increasing the prevalence of family-funded
entrepreneurship.
We suggest that this is due to the unique institutional logic which the family institution
brings to the enterprise. The stewardship perspective postulates that families are “deeply
preoccupied with assuring the continuity or longevity of the enterprise and its mission, and
therefore invest in building the business for the long run benefit of various family members”
(Miller et al. 2008). In addition, families are argued to be more adept at developing a community
culture that results in loyal employees, and they are able to create strong connections with other
firm stakeholders who become critical for the sustainment of the firm during times of crises
(Arregle et al., 2007; Davis et al., 1997; Das and Teng, 1998; Tsui-Auch, 2004). As such we
predict that exogenous shocks to the environment will influence the rate of family-funded
entrepreneurship as a response to increased uncertainty.
Hypothesis 1a (H1a): An exogenous shock will lead to an increase in assumption of
entrepreneurial risk by the family Institution.

9. 9
Hypothesis 1b (H1b): An exogenous shock will lead to a decrease in the assumption of
entrepreneurial risk by formal institutions
Social institutions also play a role in maintaining, coordinating, and controlling informal
markets (London and Hart, 2004). Using Rona-Tas and Guseva’s (2014) terminology, social
institutions provide the generative principles through which informal entrepreneurs create new
markets, as well as the functional principles through which they are maintained and perpetuated.
Given that the family is the primary informal institution in society, we argue that it has a central
role in coordinating and funding entrepreneurship in informal markets. Thus, we hypothesize
that:
Hypothesis 2 (H2): Informal entrepreneurial activity is more likely to have its risk assumed by
the family institution.
To further analyze this relationship between the formal and informal institutional
environments and the associated risk and uncertainty it is important to recognize the limits or
boundaries where the formal ends and informal begins. The influence or reach of these formal
risk-based institutional environments into the uncertain informal institutional environment may
be enhanced by “distance demolishing technology” (Scott, 2009 pg.xiii). Distancing
demolishing technologies constitute those technologies which significantly reduce a person’s
social and geographical proximity to formal society (Muir, 2012). Major examples of distancing
demolishing technologies include railroads, roads, airpower, the telephone, and most recently,
the internet (Scott, 2009 pg xiii). For this reason we predict that increases in internet servers will
expand the boundaries of these formal institutional environments into the informal and uncertain
environment. This will in turn decrease reliance on the informal family institution and increase
reliance on formal institutions. Initial reasoning suggests that extending the formal institutional
environment through more internet servers would increase assumption of risk for both bank and
government institutions. But a contextual understanding of prevailing institutional norms in our

10. 10
developing contexts suggests that “the majority of Jordanian banks do not conduct transactions
online” as sufficient trust has not been developed in the security and encryption necessary for
financial transactions over the internet (Alwamleh, et. al., 2003). Given that social factors shape
the diffusion of innovations (Tolbert and Zucker, 1983), we predict that government institutions
will more prevalently assume entrepreneurial risk as a result of the spread of a distancing
demolishing technology:
Hypothesis 3 (H3): An increase in internet servers within the country will lead to a decrease in
the assumption of entrepreneurial risk by the family institution
Hypothesis 3b (H3b): An increase in internet servers within the country will lead to an increase
in the assumption of entrepreneurial risk by government institutions
*** needs shaping**The prevalence of family-funding will occur independent of the availability
of capital from formal institutions as it is not a matter of available supply but of demand which is
driven by the preferences of entrepreneurs in uncertain conditions. For example a variation of
capital available from banks may influence the use of funding from other formal institutions but
will have little effect on the prevalence of entrepreneurs using family funding. Following this
reasoning we would hypothesize that the supply of capital that banks have available to lend
would influence the rate at which entrepreneurs procure financing from only formal institutions
such as the Government. However it should not influence the prevalence of entrepreneurs using
informal institutions such as family as a source of funding.
Hypothesis 4a (H4a): An increase in the ratio of bank capital to assets will not affect the
likelihood that entrepreneurial risk will be assumed by the family institution
Hypothesis 4b (H4b): An increase in the ratio of bank capital to assets will increase the
likelihood that entrepreneurial activity will be assumed by the government.
ResearchContext

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To test these hypotheses we are using data on SMEs from the Hashemite Kingdom of Jordan.
Jordan is an emerging market context where family structure is still extended, grounded in non-
western cultural scripts, and an environment where access to resources is gained largely through
family social capital rather than financial capital. The country is a constitutional Monarchy
formed after World War I. Control of the territory has given by the colonial powers to the
Hashemite family from the Arabian Gulf as recompense for their willingness to lead battles
against the Ottoman Empire (Cleveland and Bunton, 2009). The country is bordered by Iraq,
Syria, and Israel-Palestine, which places it in a unique position given that it is bordered by the
most notable political conflicts in the world (Palestinian-Israeli conflict, Iraq War, Syrian Civil
War, and ISIS). Combined with its resourced starved natural environment (little fresh water and
oil sources), Jordan is a developing nation characterized by a high degree of uncertainty.
Research based on Jordanian data should contribute to providing practical theory that explains
family business creation and growth in uncertain emerging markets. Furthermore, in addition to
contributing to an important empirical gap in the literature, research in extreme contexts such as
Jordan, can often reveal more information than typical contexts because they activate more
actors and basic mechanisms which can then be used to inform more typical contexts (Flyvbjerg,
2006; Eisenhardt, 2007).
Data
The data for our study comes from an organization called IRADA and from the World Bank.
IRADA was established in 2002 for the purpose of economic and social development by
supporting Jordanian SMEs. The organization was financed by the Ministry of Planning and
International Cooperation (MoPIC) in order to contribute to King Abdullah’s development goals,
and has been administered by the Royal Scientific Society since 2006. IRADA has 36 centers

12. 12
across the country, and offers services ranging from business plan development to management
advice. IRADA’s services are free, and are widely available to the population. IRADA works
with individuals who want to grow their business, individuals who have a business idea and want
to start a business, as well as with individuals who want to start a business but have no business
idea. In addition, IRADA conducts mass trainings which are act like awareness campaigns in the
community in order to attempt to bring people into IRADA who previously did not think about
starting a business. Where most programs are centered in Amman, IRADA’s centers are
scattered across every region of the country. The spread of IRADA centers means that it pulls in
data on SMEs from areas where data is not usually gathered. Thus, this particular data set is
unique because it draws from both rural and urban populations within the developing country,
people within a community have equal opportunity to interact with IRADA, and data was not
collected by sampling on the dependent variable, which is the case with several family business
studies.
The data, to which IRADA has graciously provided us access, provides information on
about 9565 SMEs between 2002 and 2014. The data on each SME project is very thorough.
IRADA representatives gather information on the owner, the project, and they conduct a
feasibility study regarding the project. In addition, the representatives conduct a monthly follow-
up report on each project for the first year, and then they do bi-monthly follow-up reports.
Variables and Methods
Dependent variables. The dependent variables for our study are three binary variables:
whether or not the new venture is family funded, whether or not the new venture is government
funded, and whether or not the new venture is bank funded. We ran separate regression models
including the independent variables and the control variables on each dependent variable.

13. 13
Independent variables. Our model study has four independent variables: Whether the
venture was founded during a period of exogenous shock, whether the new venture is formal,
number of secure internet servers in the country, and bank capital to assets ratio. We define
exogenous shocks as major economic downturns and armed conflicts that make international
headlines because these types of events are found to contribute to the creation of uncertainty, or
the perception of it (Bloom, 2009; Bachman et al., 2010; Bloom, 2013). As our dataset covers
the years 2002 to 2013, we flagged the years 2008 to 2009 as years of shock because of the Great
Recession, the years 2002 and 2003 as years of shock because of The Second Intifada, the years
2005 and 2006 as years of shock because of the Iraq War, and the years of 2011-2012 as years of
shock because of the Syrian Civil War. The armed conflicts in the time period of our study were
especially impactful on Jordan given that the kingdom shares a border with each of these
conflicts (Second Intifada in Palestine-Israel on the Western border, the Iraq War on the Eastern
border, and the Syrian Civil War on the Northern border), and received substantial number of
refugees from each territory during their respective moments of intense violent conflict.
For each exogenous shock we noted only the year it began and the following year
because populations tend to grow accustomed to the events thereafter. If a company in our
sample was founded in one of the years flagged as a period of exogenous shock, then we coded it
as a 1, and if the new venture was not founded during a period of exogenous shock, then we
coded it as a 0.
As noted earlier, IRADA notes whether a new venture is registered as some formal entity
with the government. Again in the dataset, we coded a company as a 1 if it was registered as
some formal entity with the government, and as a 0 if it was not registered as some formal entity
with the government. From the World Bank we gathered data on the number of secure internet

14. 14
servers in Jordan every year from 2002 to 2013 as well as on the bank capital to assets ratio. The
Bank capital to assets is the ratio of bank capital and reserves to total assets. Capital and reserves
include funds contributed by owners, retained earnings, general and special reserves, provisions,
and valuation adjustments. Capital includes tier 1 capital (paid-up shares and common stock),
which is a common feature in all countries' banking systems, and total regulatory capital, which
includes several specified types of subordinated debt instruments that need not be repaid if the
funds are required to maintain minimum capital levels (these comprise tier 2 and tier 3 capital).
Total assets include all nonfinancial and financial assets.
Control variables. In our models we control for gender, GDP, Mobile phone
subscriptions, labor participation rate, and total new venture foundings. Gender is a binary
variable where female founders are coded as 1 and male founders or foundings of new ventures
by parent organizations are coded as 0. We used World Bank data to record the GDP growth in
Jordan for the years of the study, the number of new mobile subscriptions in the country, and the
labor participation rate. Total new venture foundings for the year each new venture was founded
as also included to control for growth in entrerpreneurship in general.
Results
Table 1 below shows the new venture foundings by year and funding source. New
venture foundings tend to increase year over year in Jordan, but there is a noticeable decline in
the assumption of risk by banking institutions coinciding with an increase in the assumption of
entrepreneurial risk by family and government institutions; the government consistently being
the primary institution assuming the risk or uncertainty related to entrepreneurship.
[INSERT TABLE 1 HERE]

15. 15
Tables 2-4 below show the individual regressions run for Family-funded entrepreneurship
(Table 2), Government funded entrepreneurship (Table 3), and bank funded entrepreneurship.
Table 5 compares the final regression model (model 6) of each form of entrepreneurship in order
to more easily compare results across the different forms of entrepreneurship under study.
[INSERT TABLE 2 HERE]
[INSERT TABLE 3 HERE]
[INSERT TABLE 4 HERE]
[INSERT TABLE 5 HERE]
In line with H1a and H1b, periods of exogenous shock were associated with increases in
family funded entrepreneurship as well as with decreases in government funded entrepreneurship
and bank funded entrepreneurship. The coefficient for family assumption of risk was positive
and statistically significant at the <.05 level, the coefficient for government funded
entrepreneurship was negative and statistically significant at the <.001 level, and the coefficient
for bank funded entrepreneurship was negative and statistically significant at the <.01 level. In
line with our earlier argument, it seems that when exogenous shocks create uncertainty,
entrepreneurs tend to seek assumption of risk by the family institution, which is an institution
that usually garners more trust and may provide more flexibility to deal with chaotic
environments. Likewise, registered/formal new ventures were more likely to have their risk
assumed by formal banking and government institutions, and less inclined to have their risk
assumed by the informal family institution which lending confirmation to H2. The coefficient for
family assumption of risk was this hypothesis was negative and statistically significant at the
<.001 level, the coefficient for government assumption of risk was positive and statistically

16. 16
significant at the <.001 level, and the coefficient for bank assumption of risk was positive and
statistically significant at the <.05 level.
Furthermore, results indicated an initial confirmation of H3a and H3b (that increases in
internet servers to lead to decreases in assumption of risk by the family institution, and increases
in the assumption of risk by government institutions). The coefficient for family assumption of
risk was negative with a p-value that was statistically significant at the <.01 level, the coefficient
for government assumption of risk was positive and statistically significant at the <.001 level,
and the coefficient for bank assumption of risk was very mildly positive and not statistically
significant. Finally, the results pointed to a confirmation of hypotheses H4a and H4b (that
increases in the bank capital to assets ratio would not affect family funded entrepreneurship but
would lead to increases in government funded entrepreneurship). The coefficient for family
assumption of risk was negative and not statistically significant, the coefficient for government
assumption of risk was very positive and statistically significant at the <.001 level, and the
coefficient for bank funded entrepreneurship was negative and statistically significant at the <.01
level.
Discussion
Our study makes several theoretical and empirical contributions. First we contribute to
Schumpeter’s theory on economic development by delineating the conditions under which the
uncertainty/risk associated with entrepreneurial behavior is likely to be assumed by family,
government, or banking institutions. [review each of the four conditions and how it shaped which
institutions were more likely to assume entrepreneurial risk]

17. 17
Second, our study contributes to research at the nexus of institutional theory and
entrepreneurship. Specifically, we contribute to the emerging conversation surrounding the study
of entrepreneurship as an institution. In this space, [Tolbert et al. etc.]
Finally, we contributing to understanding the entrepreneurship in developing contexts..
Tables on next page….
Table 2: Family Funded Entrepreneurship
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
ExShck ***0.046 ***0.046 **0.031 *0.0257 0.021 *0.031
Formal ***-0.47 ***-0.46 ***-0.45 ***-0.45 ***-0.45 ***-0.45

18. 18
Internet 0.0002 0.0002
***-
0.0008 -0.0006 -0.0006 **-0.001
BankRatio -0.278 -0.29 -0.029 0.36 0.025 -0.67
Sex 0.009 0.011 0.011 0.011 0.011
GDP **-0.316
***-
0.0297
***-
0.028 ***-0.034
Mobile -0.0006 -0.0007 0.001
LaborPrt 0.774 0.544
Enter% ***0.0001
p-value: *= < .05 **= < .01 ***= < .001
Table 3: Government Funded Entrepreneurship
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
ExShck ***-0.114 ***-0.114 ***-0.094 ***-0.112
***-
0.066
***-0.07
Formal ***0.291 ***0.264 ***0.24 ***0.248 ***0.248 ***0.25
Internet ***0.0005 ***0.0005 ***0.009 ***0.003 ***0.002 ***0.002
BankRatio **0.836 **0.89 0.554 ***1.92 ***5.541 ***5.8
Sex ***-0.424 ***-0.046 ***-0.045
***-
0.045
**-0.045
GDP ***0.041 ***0.048 ***0.034 ***0.035
Mobile **-0.002 -0.0002 -0.001
LaborPrt
***-
8.002
**-7.9
Enter% -0.0001
p-value: *= < .05 **= < .01 ***= < .001
Table 4: Bank Funded Entrepreneurship
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
ExShck ***-.024 ***-.024 ***-0.023 ***-0.023 **-0.019 **-0.021

19. 19
Formal **.019 *.016 *.015 *.015 *.016 *0.02
Internet -7E+14 -7E+56 0.00003 0.00004 -0.00002 0.000
BankRatio ***-1.68 ***-1.68 ***-1.69 ***-1.67 ***-1.35 **-1.21
Sex -0.004 -0.004 -0.004 -0.004 -0.004
GDP 0.001 0.001 0.0002 0.001
Mobile -0.00002 0.0001 0.000
LaborPrt -0.7 -0.66
Enter% 0.000
p-value: *= < .05 **= < .01 ***= < .001
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