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CULTURE AND ENTREPRENEURSHIP
Dekuwmini Mornah
Virginia Military Institute
Tel: 540 466 0142
Email: mornahd@vmi.edu
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Raymond J. MacDermott
Virginia Military Institute
ABSTRACT
Culture affects entrepreneurship directly and indirectly through institutions. Therefore, the total
effect of culture on entrepreneurship should take into account both the direct and indirect effects.
Previous studies have ignored the possible indirect effects of culture on entrepreneurship thus
estimates are likely endogenous or incomplete. We use data from the World Bank’s Doing
Business Report alongside the nine dimensions of culture as identified by the GLOBE team to
assess the total effect of certain aspects of culture on entrepreneurial activity in a country. We
find that Future Orientation, Power Distance, Performance Orientation and Gender
Egalitarianism spur entrepreneurial activity while Uncertainty Avoidance, In-Group
Collectivism, Institutional Collectivism and Assertiveness impair it. These dimensions tend to
have significant reinforcing interaction effects with institutions on entrepreneurial activity.
JEL L26, B52, Z18
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1. EXECUTIVE SUMMARY
The effect of culture on entrepreneurship activity can be two-fold. The first can be directly
through culture itself and the second can be indirectly through institutions. Previous literature has
looked at one or the other. However, the total effect of culture on entrepreneurship is likely to be
a combination of the two effects.
We use data from the World Bank’s Doing Business Report alongside the nine dimensions of
culture as identified by the GLOBE team to assess the total effect of certain aspects of culture on
entrepreneurial activity in a country. Our methodology involved the use of series of regression
analysis to check the robustness of our results and they include: Poisson Regression Analysis,
OLS Regression Analysis and Robust Regression Analysis.
We find that Future Orientation, Power Distance, Performance Orientation and Gender
Egalitarianism spur entrepreneurial activity while Uncertainty Avoidance, In-Group
Collectivism, Institutional Collectivism and Assertiveness impair it. These dimensions tend to
have reinforcing significant interaction effects with institutions on entrepreneurial activity.
This study could have relevant policy implications especially for countries that want to boost
entrepreneurship. Knowing which aspects of culture affect entrepreneurship and how is
important in formulating social policy to make entrepreneurship work. For instance, knowing
that uncertainty avoidance impairs entrepreneurial activity, policy makers could take steps to
reduce the degree of uncertainty about entrepreneurship by providing support in the form of
education and training to entrepreneurs. Also, Collier argued, “bad culture” could be a nemesis
to development. If policy makers realize that their countries score high on certain dimensions
that impair entrepreneurship, they could actively engage in public education and sensitization to
rid the country of such negative tendencies.
2. INTRODUCTION
Collier argues that bad institutions or economic structures may be a characteristic of poor
countries and this underpins their development. He further argues, albeit controversially that
“bad culture” is not just a characteristic but rather an attribute embedded in the people of poor
countries (Collier, 2013). While we do not endorse the idea of depicting some cultures as “bad”,
we proceed under the assumption that culture, as “embedded” in a people, may have
consequences on the business orientation of a people. The present study examines how different
aspects of national culture and attributes may affect entrepreneurship or business creation.
Essentially, we ask the question: How does national culture affect entrepreneurship?
Culture may affect entrepreneurship in two ways. First, culture affects entrepreneurship directly
in the sense that a certain cultural orientation may make people of that orientation more or less
interested in business irrespective of the quality of institutions. But there is a second route
through which culture may affect entrepreneurship. Culture can influence institutions, which, in
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turn, affect entrepreneurship. In this case, culture affects entrepreneurship indirectly through its
effect on institutions. Consider Fig. 1 for instance which shows these relationships.1
Fig. 1 Direct and Indirect effects of culture on entrepreneurship
If culture affects entrepreneurship only through the direct route, then previous studies on culture
and entrepreneurship would have properly identified the total effect of culture on
entrepreneurship. If, on the other hand, culture affects entrepreneurship both directly and
indirectly through institutions, then the effect of culture on entrepreneurship would not have been
properly identified, as the total effect should be the direct plus the indirect effects.
The goal of the present study is to examine the effect of culture on institutions taking into
account the direct and indirect effects. We also examine whether culture and institutions have an
interaction effects that either tend to reinforce how they affect entrepreneurship. Instead of
cherry picking which dimensions or aspects of culture to employ in our analysis, we adopt a
holistic approach to capture culture as it relates to business in the form of the nine dimensions of
culture as determined in the GLOBE study. This approach minimizes possible problems of
omitted cultural variables. Furthermore, to the best of our knowledge, this is the first study that
employs the GLOBE cultural dimensions in this context. We settled on the GLOBE measures
because they are fairly recent, cover more industries and measure culture as it relates to business.
The rest of this paper is organized as follows. We continue with a brief literature review to close
out section 2. Section 3 presents the empirical methodology. In section 4, we present the data and
results. Robustness checks are presented in section 5 and Section 6 concludes.
Brief literature review
With respect to literature, three broad areas are relevant to this study; the interplay of culture and
institutions, the relationship between institutional quality and entrepreneurship and importantly,
the impact of culture on entrepreneurship
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1 Institutions here could be legal, economic and political institutions. We concentrate on legal and economic
institutions for two reasons. First, they have direct bearing on entrepreneurship. And second because the correlation
between legal and political institutions is incredibly high leading to econometric issues.
2a
2b
Culture
Entrepreneurship
Institutions
1. Direct
2. Indirect
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In terms of culture and institution, there is evidence that culture may affect institutional quality.
Most of the studies in this area examine this relationship either by way of historical narrative
((Fischer, 1989), (Todd, 1990), (Greif, 1994)) or through more formal empirical tests ((Guiso,
Sapienza and Zingales, 2008), (Licht et al, 2005), (Gorodnichenko and Roland, 2013), (Nguyen
et al, 2009)).2 Across these studies, several different measures are used to capture culture. These
include data from the World Values Survey, Hofstede’s Cultural Insights, and Schwartz’s
Cultural Model as well as proxies such as language and religion. While a variety of approaches
are used, the importance of culture in the foundation of institutions is undeniable.
The works of both William Baumol and Douglass North form the cornerstone of the body of
literature on institutions and entrepreneurship.3 Both North and Baumol emphasize the role that
the institutional environment plays in fostering and forming entrepreneurial development. The
work of both suggests that “in weak institutional environments, productive entrepreneurs will be
at low levels.”4
The literature specifically addressing culture and entrepreneurship is still young and falls into
two broad categories: micro and macro level studies. Micro-level studies look at the culture and
characteristics of the firm or individual and their implications for innovation and
entrepreneurship while macro-level studies look at culture and values at the national level and
how it affects business interactions. Given the focus of our study, we restrict our discussion to
the latter.
Within macro-level studies, Hofstede is widely cited. However many studies focus their attention
on a single dimension of culture.5 The first foray into this approach is by Shane who investigates
the link between culture and innovation using Hofstede’s 4 dimensions. By incorporating each of
the four Hofstede dimensions in a step-wise manner (but never all four in the same regression)
she finds Uncertainty Avoidance and Power Distance detract from innovation while
Individualism-Collectivism is positively related. Masculinity is insignificant. (Shane, 1993)
A follow-up by Rinne et al analyzes the effect of three Hofstede dimensions on the Global
Innovation Index. Their findings are not entirely consistent with those of (Shane, 1993). They
find Power Distance detracts from innovation and Individualism-Collectivism is positively
related. However, Uncertainty Avoidance is insignificant. (Rinne et al., 2012)
Taking a different approach, Williams and McGuire suggests national culture influences
economic creativity, which in turn, influences innovation implementation. Again, masculinity is
excluded from the analysis. Starting with Hofstede, they construct alternate measures of culture
(power proximity, uncertainty acceptance and Individualism) and establish that these do
influence economic creativity and innovation. (Williams & McGuire, 2010).
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2 See (Alesina and Guiliano, 2013) for an excellent analysis of the research on the interplay between culture and
institutions.
3 While each offers several excellent resources, see (North, 1993) and (Baumol, 2002).
4 See (Estrin, Aidis and Mickiewicz, 2007)
5 For instance, both (Pinillos and Reyes, 2011) and (Morris, Davis, and Allen, 1994) focus on the Individualism-
Collectivism dimension. Still others do the same for Power Distance and Uncertainty Avoidance.
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One of the main challenges of measuring the impact of culture on policy or socio-economic
outcomes is that the concept of culture is nebulous. It is hard to define in totality thus limiting
empirical studies on culture to just certain aspects of culture. The literature review shows that
previous studies of the effects of culture on entrepreneurship are limited in at least two ways.
First, they ignore or inadequately account for the indirect effects of culture on entrepreneurship.
Secondly, cultural values and beliefs are usually clustered. For instance, how people view risk
may depend to a degree on their future orientation. Therefore, assessing the effects of culture by
selectively picking certain dimensions while ignoring others could lead to problems of omitted
variable bias and endogeneity. The current study seeks to mitigate these problems by
simultaneously using all nine dimensions of culture as identified by GLOBE and assessing the
total effect of culture (direct plus indirect) on institutions.
3. EMPIRICAL ISSUES AND ESTIMATION METHODS
We start with a fundamental research question: To what extent does culture influence the level of
entrepreneurial activity? In other words, which aspects of culture have a direct effect on
entrepreneurial activity within a country? We adapt a model by Davis and Williamson in their
paper on Culture and Entry regulation (Davis & Williamson, 2014)
Assessing direct effect of culture on entrepreneurship (Route 1)
Consider equation (1),
!"#$!%&'( ) *+, -&'( .+, /0
1
02+
345#4$!0'& , 6&
7
&2+
8"9#:#4#:;"9&, <+&''(
(1).
Equation (1) says that entrepreneurial activity is a function of culture, the quality of institutions
and other exogenous variables X. Measures of culture include all the nine dimensions of the
GLOBE study. Measures of institutions adopted are legal and economic institutions.
The estimates on the dimensions of culture in equation (1) indicate what the direct effect of the
respective cultural dimensions is on entrepreneurial activity. For every cultural dimension for
which we find significance, it means that particular dimension has a direct effect on
entrepreneurship (route 1 is significant). If a particular dimension of culture does not have a
direct significant effect on entrepreneurship it may still affect entrepreneurial activity, albeit
indirectly through its effect on institutions (route 2). Because of the possibility of this indirect
effect of culture on entrepreneurship, it means that the co-efficient on culture in equation (1)
does not measure the total effect of culture on entrepreneurship. It only measures the direct
effect (Route 1). Therefore estimating (1) will not produce consistent estimates of the total
effect (direct plus indirect) of each cultural dimension on entrepreneurial activity. In other
words, institutional quality is endogenous to culture.6
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6 See (Tabellini, 2008) and (Licht et al., 2007)
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Assessing Indirect and Total Effect: Route 1 plus Route 2
To identify the total effect of each cultural dimension on entrepreneurship therefore, we then
estimate a model without endogenous institutions. Since institutions are affected by culture,
then the data generating process on the quality of institutions can be given as:
8"9#:#4#:;"&) *=, >&'(.=, ?0
1
02+
345#4$!0'& , <='&'(
(2)
Equation (2) says that institutional quality is a function of the dimensions of culture and other
exogenous variables, Z. If culture indeed affects entrepreneurship and institutions then by
substituting equation (2) into (1) and simplifying, we can estimate the reduced form equation,
!"#$!%&'( ) @*+, *=A7B , -&'( .+, >&'( A7.=, @/0, A7?0B
1
02+
345#4$!0, A7<='&'(
, <+&''(
(3)
By eliminating the need to control for institutional quality itself and controlling for exogenous
determinants of institutions instead, equation (3) identifies and estimates the total effect of each
cultural dimension on entrepreneurship. Given our nine cultural dimensions, the total effect of
each cultural dimension will then be given byC/0, A7?0. Whether this total effect of culture on
entrepreneurship is bigger or smaller than that estimated in (1) will depend on the sign ofCA7?0.7
Assessing interdependence of culture and institutions
But to what extent do institutions and culture interact to determine entrepreneurial activity?
Having determined the direct and indirect effects of culture on entrepreneurship, we are
alsointerested in finding out the interplay between culture and institutions in determining
entrepreneurship. To assess this, we estimate equation (4), which includes interactions between
institutions and the dimension of culture.
!"#$!%&'( ) *+, -&'( .+, /0
1
02+
345#4$!0'& , A8"9#&, D0
1
02+
345#4$!0'& E8"9#&
, <+&''(
(4)
The sign of the interaction co-efficient, θk in equation (4) reflects the degree and direction of the
interdependence between the cultural dimension and institutions. When this co-efficient is
significant, it means that cultural dimension and institutions act interdependently. Conversely,
finding significant coefficients on culture and institutions but not on their interaction term would
indicate that the two are independent. A positive co-efficient means culture and institutions
interact to reinforce entrepreneurial activity. The reverse is true when we find a negative
significant interaction term.
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7 It’s also possible that the total effect can have a completely different sign and significance from the direct effect
depending on the influence of the indirect effect.
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We estimate the above models using the Poisson Quasi Maximum likelihood Estimator. 3.3
Estimation Methods. If the dependent variable is strictly nonnegative (not necessary count), then
it is advisable to model the expected regression model directly. He shows that further efficiency
gains can be obtained using a panel Poisson maximum likelihood estimator. The Poisson QMLE
is fully robust to distributional misspecifications other than those of the conditional mean and is
fully efficient. Usually, the regression coefficients are unbiased and asymptotically normal
(Wooldridge, 2010).
4. VARIABLES, DATA AND RESULTS
Variables: Main
The measure of entrepreneurship used in our analysis is the “New Business Entry Density”
reported by the World Bank’s Doing Business Report. This measures the number of newly
registered private, formal sector and limited liability companies per 1,000 working-age
population.8 While this data, drawn directly from national business registries, excludes the
informal sector and partnerships / sole proprietorships, its focus on LLCs provides a valuable
indicator of new business registration and entrepreneurship.
In terms of institutional quality, we adopt two measures of institutional quality – legal
institutions and economic institutions reported (Kuncic, 2014). The Kuncic institutional quality
dataset clusters over 30 indicators of institutions into three groups of formal institutions: legal,
political and economic. These measures are preferred because according to Kuncic, they
completely cover all aspects of the formal institutional environment of a country. We use only
the legal and economic institutional measures first because those two relate directly to business
and secondly because of the high degree of correlation between legal and political institutions.9
Culture measures come from the nine dimensions of culture reported by the Global Leadership
and Organizational Behavior Effectiveness (GLOBE) led by Robert House. This program
administered 17,000 questionnaires to managers across 62 cultures between 1994 and 1997. Nine
cultural dimensions were established: Performance Orientation, Future Orientation, Gender
Egalitarianism, Assertiveness, In-Group Collectivism, Institutional Collectivism, Power
Distance, Humane Orientation, and Uncertainty Avoidance.
For our measures of exogenous institutional quality, we follow the literature and consider
whether the country is landlocked or not (Landlocked), how far the country is from the equator
(equator distance) and the legal origin of the country (English legal Origin). We will briefly
explain how these variables are exogenous determinants of institutional quality.
Landlocked: This is a dummy variable that tells us whether the country is landlocked or not.
Institutional quality tends to improve with more exposure to international trade. Bad
institutions tend to be reformed to conform to international best practices in order to be
competitive in the international arena (Olson, 1982). Because of difficulty with access,
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8 The World Bank defines working-age population to range between 15 and 64.
9 The correlation between Legal and Political institutions in our data is the highest at 0.92. The correlations between
Legal and economic and political and economic institutions is approximately 0.74.
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landlocked countries tend not to have the same amount of exposure to international trade hence
will tend to have relatively bad institutions. Therefore, landlocked countries will tend to be
less entrepreneurial.
Equator Distance: Distance to the equator is argued to affect the quality of institutions through
western colonization and the transfer of western institutional practices to colonies. Because
western European countries were more exposed to the writings of Adams Smith, they tend to
have better institutions. These institutional practices tended to be transferred to colonies of
western European countries.
English Legal Origins: This is a dummy variable that takes the value of 1 if the country has
English legal heritage and zero otherwise. English common law countries tend to have less
government intervention and less regulation while civil law countries tend to have more
government involvement in institutions and regulation.10 With less government intervention
and regulation, there is less encumbrance on business thus could spur more entrepreneurial
activity.
These three variables capture the exogenous effect of institutions on entrepreneurship in our
models. By controlling for these exogenous determinants of institutional quality instead of
institutions itself, we technically minimize the endogeneity of institutions and can thus
estimate the total effect of culture on entrepreneurship in equation (3).
Other Variables
As check on robustness and to minimize possible omitted variable bias, some iterations of our
models include: Religion (Shares of the population that is Catholic, Protestant, Orthodox, and
Muslim) and Ethnic diversity (ethnic fractionalization) to control for possible bias of our
culture estimates in the case where culture is correlated with the degree of diversity.
Controlling for ethnicity is important because ethnic diversity may affect the quality of
economic and political decisions.11 ((Easterly & Levine, 1997), ( Alesina et al., 2003),
(Alesina, Baqir & Easterly 1999)). Table 1 provides a list of the variables, their definitions
and sources.
Results
Summary statistics are reported in Table 2. Even though there are 139 countries with data for
New Firm registrations from the World Bank Doing Business Report, our analysis are
restricted to countries that have both new firm data and culture data as reported by the GLOBE
team. This leads to a total of 59 countries used in our analysis. The mean value for
entrepreneurial activity (New Firm Density) is 3.2 per 1000 population, which is about the
levels for Sierra Leone or Afghanistan. The lowest entrepreneurial activities occur in Niger,
Syria and Togo while the highest occur in Liechtenstein, Cyprus and Hong Kong. Zimbabwe,
Venezuela and Sudan are at the lowest end on quality of legal institutions while Sweden,
Finland and Denmark score the highest in terms of the quality of legal institutions. With
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10 See La Porta et al., 1999; 2008.
11 See Easterly and Levine (1997), Alesina et al. (2003), and Alesina, Baqir and Easterly (1999).
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regards to economic institutions, once again, Zimbabwe and Venezuela in addition to Iran
score the lowest while Hong Kong, Luxemburg and Denmark score the highest. There is
significant variation in all the variables at least at the country level thus allowing for
meaningful regression analysis.
Table 3 reports results of models estimating the direct effects (Model 1) and total effects (Models
2 and 3) of culture on entrepreneurship. Table 4 reports results of the interactions of culture and
institutions in determining entrepreneurial activity. Before delving into analyzing the
implications of these results on entrepreneurship, let’s make a few general observations of the
results. In Table 3, we see that Uncertainty Avoidance, Institutional Collectivism and
Assertiveness are predicted to have negative direct effects on entrepreneurship while
Performance Orientation is predicted to have a positive direct effect. The remaining cultural
variables in Model 1 do not have significant predicted direct effects on entrepreneurship.
Institutional quality vis-à-vis legal and economic institutions has positive and significant effects
on entrepreneurship as expected.
However, as indicated earlier, the direct effects of culture on entrepreneurship may not capture
the total effects of culture on entrepreneurship. Models 2 and 3 instead control for exogenous
institutional characteristics and the estimates on the cultural dimensions best capture the total
effects of culture on entrepreneurship as argued in equation (3). The difference between Model 2
and Model 3 is that Model 3 adds further explanatory variables (ethnic diversity and religion:
Protestants, Catholics and Muslim share of the population) to Model 2. Generally, the results are
statistically equivalent between Models 2 and 3. Worthy of note is that Future Orientation, Power
Distance and In-Group Collectivism that previously did not have significant direct effects on
entrepreneurship (Model 1) now have significant total effects on entrepreneurship (Models 2 &
3). This suggests that the indirect effects of these cultural dimensions on entrepreneurship
through institutions are likely significant. Humane orientation is the only cultural dimension that
is consistently insignificant across all models.
Culture and institutions may interact to reinforce or undermine the effect of one or the other on
entrepreneurship. Table 4 presents results on the interaction effect of each cultural dimension and
institutions on entrepreneurship. The difference between Model 4 and Model 5 is that Model 5
adds further independent explanatory variables to Model 4.12 With the exception of Performance
Orientation and In-Group Collectivism, the results of all the other cultural variables and their
interaction with legal and economic institutions are consistent and significant at least at the 5
percent level. Uncertainty Avoidance, Institutional Collectivism and Assertiveness have
significant negative interaction effects with both legal and economic institutions. With the
exception of Model 4a, In-Group Collectivism is negative and significant across all models.
Since the results in 4a do not gravely contradict the results in the three models for In-Group
Collectivism, we can say that In-Group Collectivism tends to have a negative interaction effect
with legal and economic institutions. On the other hand, Future Orientation, Power Distance,
Humane Orientation and Gender Egalitarianism have positive and significant interaction effects
with both legal and economic institutions. Performance Orientation tends to be leaning towards
positive (with three out of the 4 models positive and 2 significant).
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12 The “a” and “b” sub-numbering indicate whether we are referring to legal institutions – “a” or economic
institutions – “b”.
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Analyses
Uncertainty avoidance is negative and significant across all models in Table 3. In Table 4, its
interaction with the quality of legal and economic institutions is also negative and significant
across all models thus re-enforcing the results from Table 3. This means that countries that score
high on uncertainty avoidance tend to be less entrepreneurial. Uncertainty Avoidance is “the
extent to which a society, organization, or group relies on social norms, rules, and procedures to
alleviate the unpredictability of future events."13 It is “the extent to which ambiguous situations
are threatening to individuals.”14 Societies that score high on Uncertainty Avoidance do not
readily embrace change and when they take risks, they take only carefully calculated moderate
risks. The opposite holds true for low uncertainty societies. Since uncertainty, risk and change
are the hallmarks of entrepreneurship, the predicted effect is consistent with logic.
In Table 3, Future Orientation does not have a significant direct effect on entrepreneurship but its
total effect on entrepreneurship is positive and significant thus suggesting that the indirect effects
might be significant. In addition, in Table 4, Future Orientation interacts strongly and positively
with both legal and economic institutions thus reinforcing the results in Table 3. This means that
Future Oriented societies will be more entrepreneurial and will tend to build institutions that
reinforce this entrepreneurial drive. Future Orientation captures “the degree to which a
collectivity encourages and reward future-oriented behavior such as planning and delayed
gratification.”15 Future Oriented societies tend to save more for the future and see working as
precursor to long-term success. Firms in Future Oriented Societies tend to be more flexible and
adaptive to change. These attributes are likely the cornerstone of entrepreneurial success. As a
result, it is natural that entrepreneurship rises along with Future Orientation.
Power Distance does not have significant direct effect on entrepreneurship (Model 1) but it does
have a significant positive total effect on entrepreneurial activity (models 2 and 3) as reported in
Table 3. In Table 4, Power distance has a positive and significant interaction effect with
institutions on entrepreneurial activity. This is a surprising result. Power Distance is “the degree
to which members of an organization or society expect and agree that power should be shared
equally.”16 Rigid social classes, limited upward mobility, resources concentrated in the hands of
few and information asymmetry characterize high Power Distance societies. These attributes will
appear to make high Power Distance societies less entrepreneurial. One will then expect this
dimension to be negatively related to entrepreneurship. However, the results suggest otherwise.
Could it be the case that the concentration of resources in the hands of the few and the order in
high power distance societies make it possible for the few to actually implement entrepreneurial
ideas? For instance, if resources are spread evenly (but thinly), people may have ideas but may
not be able to implement them because they will not be able to amass the critical resources thus
allowing those with resources to be serial entrepreneurs. Hong Kong and New Zealand are two
high power distance societies yet they are among the top entrepreneurial societies in the world.
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13 (House, et al., 2004, p. 30)
14 (House, et al.,2004) p. 602)
15 (House, et al., 2004) p. 282)
16 (House, et al., 2004) p. 517)
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In-Group Collectivism and Institutional Collectivism both have negative total effects on
entrepreneurship (Table 3). In Table 4 both measures of collectivism have significant negative
interaction effects with institutions with the exception of In-Group Collectivism in Model 4a,
which also has negative, albeit insignificant interaction effect with institutions. These results
suggest that collectivist societies (both In-Group and Institutional) tend to be less entrepreneurial
and the negative interaction effects of collectivism on institutions reinforce this. In-Group
Collectivism captures “the degree to which individuals express pride, loyalty, and cohesiveness
in their organization.”17 Societies with high scores in this dimension tend to have a slower pace
in life, emphasize relations with socially defined duties and obligations. On the contrary,
societies with low In-Group Collectivism scores emphasize personal needs, discriminate less
between in-group members and out-group members and have a faster pace to life. The attributes
of low In-Group collectivist societies sound more complementary to entrepreneurship while
those of high In-Group collectivist societies will tend to discourage entrepreneurship and this is
consistent with the empirical results.
Institutional Collectivism depicts “the degree to which institutions encourage and reward
collective action and the collective distribution of resources.”18 In more collectivist societies,
interdependence is high, group loyalty is encouraged and prioritized over individual goals,
groups make critical decisions while rewards are based on seniority and not necessarily merit.
Given these attributes, we would anticipate individuals to be less interested in striking out on
their own as entrepreneurs. It is therefore logical that countries with high institutional
collectivism scores tend to be less entrepreneurial.
In Table 3, Humane Orientation is insignificant in determining entrepreneurial activity.
However, in Table 4, when we interact Humane Orientation with both legal and economic
institutions, we find positive and significant effects across all models. This suggests that even
though Humane Orientation does not affect entrepreneurship on its own, when combined with
institutions, it creates an environment conducive for entrepreneurial activity. "Humane
orientation" is defined as "the degree to which an organization or society encourages and rewards
individuals for being fair, altruistic, friendly, generous, caring, and kind to others."19 In high
Humane societies, the interest of others is important, as members tend to promote the wellbeing
of others. While these attributes do not particularly shout entrepreneurship, they augur well for
institutional quality, which affect entrepreneurship.
The results in Table 3 show that Performance Orientation has positive and significant direct and
total effects on entrepreneurship. Turning to the interaction effects in Table 4, performance
orientation has positive and significant interaction effects with institutions in two models and
insignificant in the other two models. Given the results in Table 3 and Table 4, we can say that
performance orientation is positive leaning in terms of its effects on entrepreneurship and this is
logical. Performance Orientation measures a society’s view on innovation and performance
improvement. High Performance Oriented Societies are competitive and materialistic, value
innovation, training and development and usually tend to have direct and explicit channels of
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17 (House, et al., 2004, p. 465)
18 (House, et al., 2004, p. 465)
19 (House, et al., 2004, p. 569)
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communication. Given this, it is straightforward to conclude that entrepreneurial activity likely
rises with Performance Orientation.
Gender Egalitarianism has strong positive and significant direct and total effects on
entrepreneurship. These results are reinforced in Table 4 where we present the interaction effects
of Gender Egalitarianism on entrepreneurship where the interaction between gender
egalitarianism and institutions is positive across board. Gender Egalitarianism reflects "the
degree to which a collective minimizes gender inequality."20 Societies that score higher on
Gender Egalitarianism rely less on biology in the determination of roles for men and women.
These societies would likely offer more opportunities to women as well as men, which will, in
turn, lead to more entrepreneurial activity. A woman with an idea can carry through with it
without discrimination in societies in which Gender Egalitarianism is high.
Assertiveness has strong significant negative direct and total effects on entrepreneurship. Its
interaction with institutions is also negative and significant across all models. This means that
countries that score high on assertiveness tend to be less entrepreneurial – a somewhat surprising
result, initially. Assertiveness "is "the degree to which individuals are assertive, confrontational,
and Assertive in their relationships with others."21 High assertive societies tend to value
competition and reward success and calculative in building trust. These attributes will tend to
lend themselves to entrepreneurship and positively influence entrepreneurship. However, the
results say otherwise. On further re-examination, high assertive societies are likely also more
confrontational, Assertive and seek dominance in their social relationships. This means less
assertive societies value cooperation and equality while more assertive societies will be relatively
less cooperative. Business and entrepreneurship require a great deal of cooperation. Without
much cooperation, entrepreneurship becomes burdensome and lonesome. This probably explains
the strong negative relationship between Assertiveness and entrepreneurship in the results.
5. ROBUSTNESS CHECKS
Our first robustness check involved adding further variables to our models to assess the
stability of the results. The results have been fairly stable. As further robustness checks, we
also estimate our model with two other estimators: pooled OLS with heteroscedasticity-robust
standard errors and also with Robust Regressions. The pooled OLS with heteroscedasticity-
robust standard errors allows for fitting the model even in the presence of moderate
heteroscedasticity. The Robust Regression analysis is most useful in estimating models in which
some observations might be outliers or influential and dragging the results one way or the other.
The results for the direct and total effects are presented in Table 5. By and large, the results are
consistent with our earlier estimates. The only differences are with regards to Future Orientation,
which has a negative significant direct effect on entrepreneurship for the OLS analysis and
Humane Orientation, which was earlier found to be insignificant, has picked up significance in
two of the models. The results on the interaction effects are presented in Table 6. Similarly, these
results are statistically equivalent to those from earlier analysis using the Poisson estimator.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
20 (House, et al., 2004, p. 30)
21 (House, et al., 2004, p. 30)
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6. CONCLUSION
We set out to find out to what extent different dimensions of culture might affect entrepreneurial
activity in a country. In particular, we sought to estimate the total effect of culture on
entrepreneurship given that institutions might be endogenous in determining the effect of culture
on entrepreneurship. We find that indeed some aspects of culture do have significant effects on
entrepreneurship with some dimensions having further effects on entrepreneurship through their
interaction with institutions. Future Orientation, Power Distance, Performance Orientation and
Gender Egalitarianism have robust positive total effects on entrepreneurship. Their interactions
with institutions reinforce this positive effect. On the other hand, Uncertainty Avoidance, In-
Group Collectivism, Institutional Collectivism and Assertiveness tend to impair entrepreneurial
activities and this effect is reinforced by their interactions with institutions. The effect of Human
orientation is largely positive but not robust.
So What?
This study could have relevant policy implications especially for countries that want to boost
entrepreneurship. Knowing which aspects of culture affect entrepreneurship and how is
important in formulating social policy to make entrepreneurship work. For instance, knowing
that uncertainty avoidance impairs entrepreneurial activity, policy makers could take steps to
reduce the degree of uncertainty about entrepreneurship by providing support in the form of
education and training to entrepreneurs. Also, Collier argued, “bad culture” could be a nemesis
to development. If policy makers realize that their countries score high on certain dimensions
that impair entrepreneurship, they could actively engage in public education and sensitization to
rid the country of such negative tendencies.
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Variable Description Source
New Business
Density
This measures the number of newly registered private,
formal sector and limited liability companies per 1000
working-age population.
World Bank Doing Business
Report 2013
Uncertainty
Avoidance
“the extent to which a society, organization, or group
relies on social norms, rules, and procedures to alleviate
the unpredictability of future events".
House et al, 2004, p. 30
Future Orientation
"the degree to which a collectivity encourages and
rewards future-oriented behaviors such as planning and
delaying gratification"
House et al, 2004, p. 282
Power Distance
“the degree to which members of an organization or
society expect and agree that power should be shared
equally.
House et al, 2004, p. 517
In-Group
Collectivism
"the degree to which individuals express pride, loyalty,
and cohesiveness in their organizations or families"
House et al, 2004, p. 30
Institutional
Collectivism
"the degree to which organizational and societal
institutional practices encourage and reward collective
distribution of resources and collective action"
House et al, 2004, p. 30
Humane
Orientation
"the degree to which an organization or society
encourages and rewards individuals for being fair,
altruistic, friendly, generous, caring, and kind to others".
House et al, 2004, p. 569
Performance
Orientation
“the extent to which a community encourages and
rewards innovation, high standards, excellence, and
performance improvement
House et al, 2004, p. 30
Gender
Egalitarianism
“the degree to which a collective minimizes gender
ine qua lity "
House et al, 2004p. 30.
Assertiveness
"the degree to which individuals are assertive,
confrontational, and aggressive in their relationships with
others"
House et al, 2004p. 30.
Legal Institutions
Composite measure of the quality of formal legal
institutions of the country
Kuncic (2014)
Economic
Institutions
Composite measure of the quality of formal economic
institutions of the country
Kuncic (2014)
Distance to
Equator
Measured as the absolute value of the latitude of the
country, scaled to values between 0 and 1 (0 is the
equator).
CIA World Fact Book
Landlocked Dummy variable for whether a country is landlocked. CIA World Fact Book
English Legal
Origin
Dummy variable for whether the legal origins or
traditions of the country is English
La Porta et al. (2008)
Ethnic Linguistic
Fractionalization
This measures the probability that two randomly
selected individuals from a country belong to different
ethnic groups.
Alesina et al. (2003)
Religion
Percent of population that is Catholic, Protestant,
Muslim.
McCleary and Barro (2006)
Table 1: Variable descriptions and sources
Other Variables
Culture Variables
Institutiona l Quality Variab les
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Table 2: Summary Statistics of variables
Variable N Mean Std. Dev. Min Max
NewDensity 977 3.234 4.836 0.002 44.13
Culture Variables
Uncertainty Avoidance 1904 4.117 0.595 2.883 5.371
Future Orientation 1904 3.800 0.453 2.877 5.068
Power Distance 1904 5.165 0.443 3.589 5.802
In-Group Collectivism 1904 5.148 0.760 3.179 6.362
Institutional collectivism 1904 4.231 0.432 3.246 5.224
Humane Orientation 1904 4.100 0.463 3.181 5.229
Performance Orientation 1904 4.070 0.407 3.204 4.935
Gender Egalitarianism 1904 3.376 0.377 2.497 4.076
Aggressiveness 1904 4.124 0.363 3.376 4.889
Institutional Variables
Legal Institutional Quality 2396 0.001 0.952 -2.148 1.933
Economic Institutional Quality 2214 0.013 0.944 -2.927 1.958
Exogenous Inst. Variables
Landlocked 5170 0.290 0.454 0.000 1.000
Distance from Equator 4931 0.270 0.168 0.000 0.640
English Legal Origins 6154 0.348 0.476 0.000 1.000
Other Control Variables
Ethno-ling Fractionalization 6222 0.439 0.258 0.000 0.930
Protestant Population (%) 5134 0.488 2.108 0.000 26.000
Catholic Population (%) 4760 0.741 4.774 0.000 56.900
Muslim Population (%) 7038 0.237 0.362 0.000 0.999
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Table 3: Direct and Total Effects of Culture on Entrepreneurship: Poisson Regressions
Independent Variable Direct Effect Total Effect
Model 1 Model 2 Model 3
Uncertainty Avoidance -1.1174*** -1.4205*** -1.0672***
(0.1443) (0.139) (0.1844)
Future Orientation -0.0739 1.0620*** 1.1225***
(0.1422) (0.2006) (0.2345)
Power Distance 0.1582 0.3699* 0.4423*
(0.1319) (0.1952) (0.2361)
In-Group Collectivism 0.0055 -0.6912*** -0.5518***
(0.0968) (0.1046) (0.1334)
Institutional collectivism -0.4211*** -0.5720*** -0.6073***
(0.1209) (0.1458) (0.1872)
Humane Orientation -0.0628 -0.0051 0.214
(0.0984) (0.1463) (0.1853)
Performance Orientation 1. 5601*** 1.8168*** 1.1928***
(0.1435) (0.1973) (0.3014)
Gender Egalitarianism 1.0281*** 1.3771*** 1. 2191***
(0.1375) (0.1648) (0.2089)
Assertiveness -1.0069*** -1.0230*** -0.8941***
(0.1571) (0.1639) (0.2329)
Legal Institutions 0.5469***
(0.1265)
Economic Institutions 0.6501***
(0.1184)
Landlocked -0.3588*** 0. 1611
(0.1184) (0.1473)
Equator Distance 0.7851** 1.4102***
(0.3199) (0.4551)
English Legal Origins 0.2398* 0.1098
(0.1237) (0.1562)
Ethno-Ling Fractionalization -2.5162***
(0.3086)
Protestants 0.0136
(0.2387)
Catholics 0.1957
(0.2706)
Muslims 0.303
(0.3951)
Constant 0.7326 -1.3036 -0.9425
(1.4701) (2.1802) (2.9646)
N308 305 253
Standard errors in parentheses * p < 0.10, ** p < 0.05, *** p < 0.01
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Table 4: Interactions of Culture variables and institutions: Poisson Regression Models
Interaction Model 4a Model 5a Model 4b Model 5b
Uncertainty Avoidance*_ -0.6573*** -1.1515*** -0.5306*** -1.1500***
(0.1474) (0.228) (0.1888) (0.2684)
Future Orientation*_ 1.9667*** 0.9959*** 2.0806*** 1.2516***
(0.2373) (0.2877) (0.2856) (0.3599)
Power Distance*_ 0.5470*** 0. 5769*** 0.8855*** 0. 9309***
(0.1053) (0.1397) (0.1314) (0.1800)
In-Group Collectivism*_ -0.0413 -0.2879** -0.3207*** -0.4250***
(0.0935) (0.1147) (0.1078) (0.1466)
Institutional collectivism*_ -1.9708*** -0.7124** -1.9719*** -0.7965*
(0.2315) (0.3334) (0.2775) (0.4108)
Humane Orientation*_ 1.0599*** 0.7250*** 1.2546*** 0.6826***
(0.1239) (0.1878) (0.1435) (0.2263)
Performance Orientation*_ -0.1159 0. 5407* 0.6945** 0.2293
(0.2185) (0.2799) (0.2760) (0.3545)
Gender Egalitarianism*_ 0.8230*** 0.9683*** 0.6266*** 0.6195***
(0.1292) (0.1620) (0.1447) (0.1925)
Assertiveness*_ -1.1634*** -1.1172*** -0.9005*** -0.8943***
(0.1702) (0.2448) (0.2032) (0.3012)
Landlocked -0.2526 0.4823*** -0.4003*** -0.1212
(0.1540) (0.1790) (0.1443) (0.1847)
Equator Distance -2.0440*** -3.7466*** -4.0360*** -5.4657***
(0.3543) (0.4566) (0.3949) (0.5040)
English Legal Origins -0.5056*** -0.9498*** -0.7121*** -1.2398***
(0.1084) (0.1700) (0.1316) (0.1975)
Ethno-Ling Fractionalization -0.1561 -0.9397**
(0.5052) (0.4576)
Protestants -0.5925 1.3613**
(0.4833) (0.6639)
Catholics -0.0086 0.6902
(0.5256) (0.6203)
Muslims 0.2366 0.8391
(0.5582) (0.6432)
Constant 1.4975*** 1.9412*** 2.2927*** 2.2544***
(0.126) (0.4124) (0.1353) (0.4756)
N233 191 233 191
Standard errors in parentheses * p < 0.10, ** p < 0.05, *** p < 0.01
Legal
Economic
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Table 5: Direct and Total Effects of Culture on Entrepreneurship: Pooled OLS and Robust Regressions
OLS Robust Reg OLS Robust Reg
Uncertainty Avoidance -2.8939*** -1.0757*** -2.3514*** -3.8433***
(0.5797) (0.3039) (0.4428) (0.3293)
Future Orientation -2.2046** 0.7669** 2.2911*** 5.8614***
(0.8988) (0.3302) (0.6960) (0.4571)
Power Distance 1.9296** 0.6581** -0.1733 1.6922***
(0.7666) (0.3074) (0.7094) (0.4332)
In-Group Collectivism -1.2193* -0.3284 -1.5068*** -0.9819***
(0.6434) (0.2407) (0.4445) (0.2450)
Institutional collectivism -0.7313 0.4561* -1.3832** -3.2459***
(0.7184) (0.2680) (0.5380) (0.3352)
Humane Orientation 1.2453** 0.1207 0.619 0.8292**
(0.5176) (0.2467) (0.6192) (0.3347)
Performance Orientation 6.6721*** 0.3798 1.5163*** 2.7528***
(0.9825) (0.3404) (0.5788) (0.5034)
Gender Egalitarianism 2.6487*** 1. 5861*** 2.0289*** 2.7495***
(0.4808) (0.2767) (0.5921) (0.3524)
Assertiveness -1.5262** -0.2859 -1.0472* -3.2367***
(0.6554) (0.2967) (0.5846) (0.3834)
Legal Institutions 0.7862 -0.0376
(0.4920) (0.2394)
Economic Institutions 2.5966*** 1.5588***
(0.4788) (0.2356)
Landlocked 0.2612 1.0343***
(0.3483) (0.2498)
Equator Distance -6.7387*** -4.4584***
(2.3184) (0.9807)
English Legal Origins 1. 049 2.2172***
(0.6452) (0.3407)
Ethno-Ling Fractionalization -7.4703*** -10.2891***
(1.2753) (0.6274)
Protestants 0.2577 4.6601***
(0.7727) (0.4456)
Catholics 0.6042 1.5441***
(0.7018) (0.4954)
Muslims 1.3262 4.5708***
(0.8670) (0.5837)
Constant -12.8505* -6.6189** 11.2401 -2.3113
(6.5938) (2.8521) (8.1429) (5.0983)
N308 308 253 253
r2 0.5337 0.5464 0.4973 0.8193
r2_a 0.5164 0.5296 0.4632 0.8071
F20.2373 32.4181 20.1281 66.8866
Standard errors in parentheses * p < 0.10, ** p < 0.05, *** p < 0.01
Model 1
Model 3
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Model 4a Model 5a Model 4a Model 5a Model 4a Model 5a Model 4a Model 5a
Uncertainty Avoidance*_ -2.1164*** -2.1716*** -3.8782*** -2.3813*** -1.9139*** -2.6787*** -2.5351*** -1.8365***
(0.5050) (0.4113) (0.3143) (0.2757) (0.4849) (0.4468) (0.3975) (0.2765)
Future Orie ntation*_ 5. 3851*** 2.9495*** 4.4823*** 3.0924*** 4.9914*** 3. 1716*** 2.3696*** 3.1610***
(0.8072) (0.5617) (0.4857) (0.3797) (0.7738) (0.7415) (0.5609) (0.3834)
Power Distance*_ 1. 5700*** 1.6500*** 2.7534*** 1. 9060*** 2.2296*** 2.2280*** 1.8176*** 2.1921***
(0.4626) (0.2984) (0.2450) (0.1860) (0.4593) (0.4080) (0.3172) (0.2163)
In-Group Collectivism*_ -0.548 -0.7907** -1.6033*** -2.0686*** -1.5123*** -1.4702*** -1.5855*** -2.1508***
(0.3454) (0.3182) (0.2156) (0.1705) (0.3535) (0.2888) (0.2645) (0.1850)
Institutional collectivism*_ -5.5304*** -4.2203*** -3.6987*** -2.5372*** -4.4697*** -2.9273*** -0.8439 -2.8165***
(0.8678) (0.8128) (0.4409) (0.4234) (0.7757) (1.0183) (0.5257) (0.4606)
Humane Orientation*_ 3.6477*** 3.1860*** 2.3079*** 2. 1509*** 3.1976*** 2.4641*** 0.8750*** 2.1350***
(0.5632) (0.4489) (0.2832) (0.2467) (0.5023) (0.4790) (0.3050) (0.2205)
Performance Orientation*_ 0.4525 2.1789*** 4.1368*** 1.1057*** -0.8824 1.2304* 0. 9632* 1.0852***
(0.6364) (0.5245) (0.4073) (0.3335) (0.6199) (0.6381) (0.5221) (0.3615)
Gender Egalitarianism*_ 2.0308*** 2.8789*** 2.2055*** 2.8563*** 1.5359*** 1.7872*** 1.7473*** 2.0649***
(0.3830) (0.3360) (0.2642) (0.2109) (0.3040) (0.4029) (0.3072) (0.2177)
Assertiveness*_ -3.5698*** -4. 3093*** -5.2460*** -2.6852*** -1.9794*** -2.6584*** -1.7545*** -2.7181***
(0.6487) (0.6233) (0.3763) (0.3248) (0.4169) (0.6375) (0.3904) (0.3166)
Landlocked -0.1321 1.9597*** 1.7036*** 1.2095*** -1.1234*** 0.4112 -0.1176 0. 3196
(0.3909) (0.3844) (0.2615) (0.2122) (0.3985) (0.4497) (0.2782) (0.1988)
Equator Distance -7.8855*** -14.8038*** -9.5613*** -16.4057*** -10.9208*** -18.5728*** -5.1221*** -14.8356***
(2.1217) (1.8186) (0.8743) (0.7447) (2.5452) (2.2725) (0.9856) (0.6943)
English Legal Origins -1.5534** -2.3853*** -2.6328*** -0.26 -0.9218* -2.0358*** 0. 1869 0.2176
(0.6350) (0.5199) (0.2619) (0.2544) (0.5405) (0.5676) (0.2756) (0.2321)
Ethno-Ling Fract -5.0651*** -6.2567*** -6.4765*** -7.2007***
(1.2778) (0.5990) (1.4855) (0.5054)
Protestants -1.5621*** -1. 9916*** 2.9553*** 0.3244
(0.5921) (0.4282) (0.7546) (0.4045)
Catholics -0.6579 1.4435*** 1.3595 0.8143*
(0.8526) (0.5487) (1.0782) (0.4903)
Muslims -0.6326 0.1802 1.6433* -0.0351
(0.8460) (0.6045) (0.9725) (0.5260)
Constant 5.5135*** 10.0562*** 5.1761*** 8. 5796*** 6.7081*** 10.0099*** 3.4095*** 8.4565***
(0.9170) (1.1829) (0.3416) (0.5279) (1.1279) (1.5434) (0.3928) (0.4986)
N233 191 233 191 233 191 233 191
r2 0.5107 0.7588 0.82 0.9185 0.5354 0.7228 0.7207 0.9183
r2_a 0.484 0.7367 0. 8101 0.911 0. 51 0.6973 0. 7054 0.9108
F23.29 38.2548 83.4915 122.5028 39.0297 64.3974 47.297 122.2017
Standard errors in parentheses * p < 0.10, ** p < 0.05, *** p < 0.01
Pooled OLS
RREG
Pooled OLS
RREG
Table 6: Interactions of Culture variables and institutions: Pooled OLS and Robust Regression Mode ls
Legal Institutions
Economic Institutions
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