The effect of national culture on entrepreneurship: An epidemiological approach

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The effect of national culture on

entrepreneurship: An

epidemiological approach

Student: Jesper van Eekelen

Studentnr.: s2394499 Supervisor: dr. A.A.J. van Hoorn

Address: Coehoornsingel 67a Co-assessor: dr. F. Pallas 9711 BP Groningen University of Groningen,

Phonenr.: 06 4807 8549 Groningen, the Netherlands

Email: j.van.eekelen@student.rug.nl Faculty of Economics & Business Version 4 (Final Version)

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The effect of national culture on

entrepreneurship: An

epidemiological approach

Jesper van Eekelen

Faculty of Economics and Business, University of Groningen,

Groningen, the Netherlands

Keywords Entrepreneurship, National culture, Cultural dimensions, Epidemiological approach

ABSTRACT

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Chapter 1. INTRODUCTION

The rate of entrepreneurship differs strongly across countries (van Stel, 2005). Rates of self-employment, a common proxy for entrepreneurship, vary from 3.4% in Denmark to 36.1% in Uganda1. Scholars from different disciplines have applied their disciplinary concepts to explain the differences and consequences of entrepreneurship, as there is an increasing recognition of the notion that entrepreneurship advances business development, generates new employment possibilities and supports economic growth (Thomas, & Mueller, 2000).

Differences in entrepreneurship rates between countries have been widely explained in literature by economic development (Blanchflower, 2000), demographic characteristics (van Stel, Wennekers, Thurik, Reynolds, & de Wit, 2003), and formal institutions (Wennekers, 2006). However, entrepreneurship rate differences across countries are not completely explained by economic, demographic and institutional variables (Freytag, & Thurik, 2007). Explanations must then be sought in national divergences in culture (Foreman-Peck, & Zhou, 2013). National culture is accepted by the disciplines of economics (Greif, 2001) sociology (Aldrich, 2009) and international business (Stephan & Uhlaner, 2010) as a significant regulator of entrepreneurship rates across nations. Nevertheless, cultural explanations for entrepreneurship have been largely bypassed by researchers due to the difficulties in separating the influences of culture from those of the economic and institutional environment in which decisions are taken (Fernandez, 2010). This paper applies the epidemiological approach to isolate culture from other explanatory variables, in order to observe in what way cultural dimensions explain the differences in entrepreneurship rates. The approach observes the probability of immigrants from different national backgrounds in the United States to be an entrepreneur, based on the assumption that immigrants in the same country share the same economic and institutional environment (Fernandez, 2010). Examining the differences in entrepreneurship activity between groups of migrants within the same market allows holding constant a number of alternative explanatory variables (Busch, & Lassmann, 2010). The epidemiological approach was employed by Busch and Lassmann (2010), their research neither proves nor rejects a cultural explanation. The authors conclude that “If culture matters for the choice of self-employment, then we should try to explain which cultural aspects may matter for entrepreneurship.” (2010: 27). Therefore, this study

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investigates whether the cultural dimensions uncertainty avoidance, assertiveness, and performance orientation explain the differences in entrepreneurship rates.

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Chapter 2. THEORY AND HYPOTHESES

2.1. Country determinants of entrepreneurship

The rate of entrepreneurship varies significantly across countries and time (Van Stel, 2005, Verheul, Wennekers, Audretsch, & Thurik, 2002, Wennekers, Uhlaner, & Thurik, 2002)) and among different groups or vis-à-vis native individuals (Busch, & Lassmann, 2010). The differences are widely acknowledged in cross-country research, whereas the determinants of these differences are part of an on-going debate in literature (Terjesen, Hessels, & Li, 2013). In economic and sociological models of entrepreneurship, a range of supply and demand variables are applied to explain the differences in entrepreneurship activity at macro level (Stephan, & Uhlaner, 2010). The demand side refers to the opportunities provided by the environment to be an entrepreneur, while the supply side of entrepreneurship consists of the capabilities and preferences of the people to run a business. Both the demand and supply of entrepreneurship are influenced by social demographics, technology, level of economic development, institutions, and culture (Wennekers et al., 2002). Blanchflower, Oswald, and Stutzer (2001) find for instance that entrepreneurship is more predominant among groups with the following social demographics; males, older, higher educated and married persons. Technological changes have expanded entrepreneurial opportunities, for example communication and information technologies have diminished transaction costs in many industries, which have enabled smaller businesses to compete (Wennekers et al, 2002). The level of economic development influences mostly the environmental opportunities of entrepreneurship, such as the shift from industrial structure to services creates opportunities for smaller firms, because the scale of economies differs and barriers for entry into entrepreneurship are lower (Carree, & Thurik, 2003). Other economic development explanations for different rates in entrepreneurship are competition, female labour participation, and unemployment rates (Blanchflower, 2000, Verheul et al., 2002). Institutions consist of formal and informal constraints, which define the incentive structure of societies and specifically economies (North, 1994). Institutional factors such as property rights protection influences positively firm survival and lowers average business size, which both increases the entrepreneurship rates (Desai, Gompers, & Lerner, 2003).

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is among the primary determinants of the economic and entrepreneurial development in a country (Kreiser, Marino, Dickson, & Weaver, 2010). However, the role of culture in explaining economic outcomes has been avoided, since there was no adequate approach separating the influences of culture from those of the economic and institutional environment in which decisions are taken (Fernandez, 2010). Economic results are not solely determined by culture, but culture determines the choice between numerous equilibriums (Busch, & Lassmann, 2010). Therefore, this study attempts to isolate culture from the other determinants to measure the effect of culture on entrepreneurship. The next paragraph explains how culture influence entrepreneurship, and hypothesises how different cultural dimensions affect entrepreneurship. The next chapter explains the epidemiological approach, which aims to isolate the cultural effects from other determinants of entrepreneurship.

2.3. National culture determinants of entrepreneurship

A country’s culture influences the rate of entrepreneurship through the cultural values of the society (Hofstede, 1980) and through the institutions that are representative for a nation’s culture (Ahlstrom, & Bruton, 2002). The underlying value systems of individuals’ national culture motivates them to behave in a specific ways (Hofstede, 1980), such as beginning their own businesses. Preferences and beliefs about entrepreneurship among national groups are shaped by their national culture, as Mueller and Thomas (2001) suggest: it is plausible that differences in culture, in which these values and beliefs are imbedded, may influence a wide range of behaviours including the decision to become self-employed. Frequently ascribed entrepreneurial behaviours are individualism, pro-activeness, competitive orientation, innovativeness, and risk-taking (Lumpkin, & Dess, 1996). The entrepreneurial conducts are mostly reflected in the cultural dimensions; uncertainty avoidance, assertiveness, and performance orientation, therefore, this paper hypothesises the effect of these cultural dimensions on entrepreneurship.

2.3.1. Uncertainty avoidance and entrepreneurship

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Innovation requires tolerance for risk and change, and the highest level of innovativeness is observed in countries with uncertainty acceptance (Shane, 1993). Innovativeness and risk-taking are factors of entrepreneurial orientations that lead to new entry, an essential act of entrepreneurship (Lumpkin, & Dess, 1996). Entrepreneurs innovate and take risks, as they are executors of creative destruction and actualisation of novelty into economic systems (Knight, 2002). In general entrepreneurs need to devote their resources and effort before the results of their entrepreneurial efforts are known. The devotion when outcomes are unknown requires entrepreneurs to innovate and take risks, which are closely related to the uncertainty avoidance aspect (Kreiser et al., 2010). Additionally, Stewart and Roth (2001) examine studies of risk-taking and concluded that risk-averse people are likely to favour regular employment, while risk-tolerant people are inclined to favour entrepreneurial careers.

Wennekers, Thurik, Van Stel, & Noorderhaven (2007) argue that nations with low uncertainty avoidance will total more individuals with entrepreneurial values who perceive a higher value to the rewards of self-employment, therefore those nations have a relatively high supply of potential entrepreneurs. Furthermore, Wennekers et al. (2007) discuss the indirect effect of uncertainty avoidance on other variables determining entrepreneurship rates. For instance, the effect of improvements in income per capita affects entrepreneurship stronger in nations with high uncertainty avoidance culture. In addition, Wennberg, Pathak and Autio (2013) find that the negative effect of fear of failure on entrepreneurial entry is more pronounced in societies with high uncertainty avoidance.

Baum et al. (1993) argue that high uncertainty avoidance is related to high self-employment as people with entrepreneurial needs are more inclined to start their own business, as they cannot satisfy their needs within existing structures. However, this study observes the respondents in the same structure, therefore eliminating the effect of formal institutions, which are partly based on the level of uncertainty avoidance. Therefore, this study hypothesises the following:

Hypothesis 1 Higher levels of uncertainty avoidance lead to lower entrepreneurial rates.

2.3.2. Assertiveness and entrepreneurship

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paid much attention to assertiveness (Maharati, Rose, Kumar, Uli, & Nazemi, 2011). Assertiveness is linked conceptually to the cultural dimension of masculinity versus femininity by Hofstede, which is a common indicator of entrepreneurship (Cullen, Johnson, Praveen, & Parboteeah, 2013).

Individuals from high assertive societies are more likely to take initiative, plus expect demanding and challenging undertakings (Den Hartog, 2004) which are aspects related to entrepreneurship (Cullen et al., 2013). Lumpkin and Dess (1996) mention proactiveness as a factor of entrepreneurial orientation, and this factor is characterised by seizing initiative and acting opportunistically to “shape the environment”. Both proactiveness characteristics match the descriptions of higher assertive societies, which tend to value taking initiative and try to have control over the environment (Den Hartog, 2004). As described in 2.3.1., those entrepreneurial orientation factors lead to new entry, a crucial act of entrepreneurship (Lumpkin & Dess, 1996).

Den Hartog (2004) indicates as well that high assertive societies incline to believe that individuals are in control. Thus, assertiveness reflects societies’ locus of control; whether people believe they have control over nature; the internal locus of control, or is controlled by nature; the external locus of control. A person is not likely to expose oneself to the risk of failure, in case the person does not believe that the outcome of a business undertaking is influenced by his or her own effort. Entrepreneurs are more likely to have an internal locus of control than an external one (Brockhaus, & Horowitz, 1986), since the perception of having the capacity to influence results is crucial for new venture formation decisions. Hence, internal locus of control increases the likelihood that potential entrepreneurs will start new business undertakings (Mueller, & Thomas, 2001). Petrakis and Kostis (2012) also predict a positive correlation between high assertiveness and entrepreneurship levels, based on the descriptions of assertive societies; those societies tend to think of others as opportunistic, and they focus on success and progress. Assertiveness relation with taking initiative, locus of control, and opportunistic observation leads this study to hypothesise the following:

Hypothesis 2 Higher levels of assertiveness lead to higher entrepreneurial rates

2.3.3. Performance orientation and entrepreneurship

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the performance orientation dimension is related to the assertiveness dimension, as many descriptions of performance orientation and assertiveness societies are identical. The description of assertive and performance orientated societies are shown in Appendix A and their descriptions are matched to show the similarities between the dimensions. Hofstede (1980) links masculinity to performance oriented society as well. Nevertheless, these dimensions are dealt with separately, as Den Hartog (2004) finds only a significant relationship between assertiveness values and performance orientation practices.

High performance oriented societies tend to value taking initiative, and expect demanding undertakings (Javidan, 2004), and those descriptions are in the “assertiveness part” mentioned as aspects related to entrepreneurship. In addition, societies that score higher on performance orientation tend to believe as well that individuals are in control, the internal locus of control is previously reasoned in this paper to positively relate to new business undertakings (Mueller, & Thomas, 2001). Wennberg et al. (2013) find a strong and highly significant effect of performance orientation on entrepreneurial entry. On the other hand, the same study finds that the positive effect of self-efficacy on entry of entrepreneurship is moderated by performance orientation.

People from high performance orientation cultures value more what they do rather than who they are; personal status depends on the results of effort (Cullen et al., 2013). The recognition of people that entrepreneurship offers more opportunities to excel than in regular employment, and the easier recognition of success lead individuals from high performance orientation nations favour entrepreneurship above regular employment (Autio, Pathak, & Wennberg, 2013). Hence, societies that score high performance orientation tend to observe entrepreneurship as a desired and suitable employment option. Therefore, this study hypothesises:

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Chapter 3. EPIDEMIOLOGICAL APPROACH

This paper employs the epidemiological approach to investigate in what way cultural dimensions affect entrepreneurial activity. The epidemiological approach relies on examining immigrants in one country to isolate the influence of culture from other influences, thus taking advantage of the transferability of culture relative to economic forces and institutions (Fernandez, 2007). The concept operates as follows: immigrants in a country share the same economic and institutional environment. However, they do not necessarily share the same culture as immigrants from other countries. The decision to become an entrepreneur is based on a mix of economic and institutional factors that differ across countries, but it is based as well on one’s preferences and beliefs (Busch, & Lassmann, 2010). Hence, the entrepreneurial decision depends at an aggregate level on fundamental beliefs and preferences in a country. In case the aggregate variable has explanatory power for the behaviour of immigrants, after controlling for individual characteristics, the correlation can be attributed to the cultural component since the economic and institutional environment of the country of origin are no longer relevant.

Carroll, Rhee and Rhee (1994) are the first to employ the epidemiological approach in economics. The researchers analyse the saving patterns of Canadian immigrants, in order to explore the effect of culture on different saving rates across countries. The authors find no significant evidence for their hypothesis. Carroll et al. (1994) mention the limitations of their conclusions, the data from the Canadian Survey of Family Expenditures provided restrictions. The researchers could only specify immigrants to broad regions of origin and wealth was imperfectly measured. Fernandez (2007) applies as well the epidemiological approach to study the effect of culture on female labour supply. The author analyses the labour force participation of second-generation American women, in order to test the hypothesis. Cultural proxies in the study by Fernandez are female labour force participation and attitudes in the women’s country of origin. Fernandez (2007) finds a significant effect of culture on the work participation. Busch and Lassmann (2010) study the effect of culture on entrepreneurial behaviour by observing differences in entrepreneurial rates between immigrant groups in the United States. The authors find evidence of a significantly positive relationship between self-employment rates in the immigrants’ country of origin and the self-self-employment rates of immigrants in the United States, however, the researchers do not assign any specific cultural dimensions to have effect on entrepreneurship.

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Chapter 4. DATA AND METHOD

4.1. Data

The data used for testing the hypotheses are provided by the General Social Survey (GSS), which contains demographic, behavioural, and attitudinal data from the US society. The GLOBE (Global Leadership and Organisational Behaviour Effectiveness Research) project (House, Hanges, Javidan, Dorfman, & Gupta, 2004) provides the data on cultural dimensions for each respondent.

4.1.1. Dependent variable

To operationalise the concept of entrepreneurship, the static perspective is selected (Wennekers, 1999) as this study uses self-employment as a proxy for the dependent variable; entrepreneurial activity of immigrants. Although self-employment is not synonymous with entrepreneurship, it is frequently used as a proxy for entrepreneurship (Parker, 2009). The binary variable is measured by the question; “Are you self-employed or do you work for someone else?”, with the answer possibilities “Self-employed” or “someone else”. Furthermore, the GSS allows us to separate immigrants and US natives, by selecting all the participants indicating to have another country of family origin than the United States. The study takes only the respondents into account within the age group 18-65 year, as this is considered as the work-force.

4.1.2. Key independent variables

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observed by members of that culture, which is defined in the cross-cultural psychology literature as “cultural descriptive norms” (Fischer et al., 2009, Shteynberg, Gelfand, & Kim, 2009). Autio et al. (2013) find that cultural practices exercise a more salient influence on entrepreneurial behaviour than cultural values, hence the researchers imply that cultural practices are appropriate measures of culture in studies of entrepreneurship. All GLOBE cultural practices are measured on the seven-point Likert scales (Brewer, & Venaik, 2010). The three cultural practices display acceptable agreement indices and internal uniformities, and they are validated by multilevel positive factor analyses (House et al., 2004). Those outcomes show the usefulness of applying these cultural practices for the epidemiological approach.

GSS respondents are able to select a country (or region) of family origin. The respondents from the following countries of family origin are included in the analysis; Austria, Canada(English-speaking), China, Denmark, United Kingdom, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Mexico, the Netherlands, Philippines, Poland, Russia, Spain, Sweden, and Switzerland. The family country of origin determines the levels of cultural practices assigned to each respondent. For instance, respondents with family country of origin the Netherlands are assigned the following levels; assertiveness 4.46, uncertainty avoidance 4.81, and performance orientation 4.46. The GSS respondents from England, Wales, and Scotland are combined into the United Kingdom. Furthermore, only immigrants from English speaking Canada are considered, as the GLOBE dimensions for Canada are based on the English speaking population of Canada. Additionally, the GLOBE scores for Germany are based on the average scores of former East and West Germany. The table with scores for each country can be found in Appendix B. Respondents from the United States are excluded from the analysis, and respondents from regions or countries not included in the GLOBE study are also excluded from the analysis. Respondents with missing answers are neither included in the analysis. This way a sample was made up of 25,792 individuals from 21 societies. Table 1 shows the sample descriptives for each country of origin used in the analysis. The entrepreneurship rates show evidence of difference in entrepreneurship between groups from different family-countries-of-origin, which gives reason to believe national culture influences entrepreneurship activity.

4.1.3. Control variables

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Table 1

Sample descriptives

Country of origin

N %N Entrepreneur Age %Male %Married Education Yes=1 No=0 % Austria 176 0.7 18 158 10.2 43.5 48.9 60.2 2.56 Canada 218 0.8 25 193 11.5 42.2 47.7 61.9 2.31 China 199 0.8 20 179 10.1 37.4 51.3 61.3 3.49 Denmark 263 1.0 35 228 13.3 42.3 40.3 59.7 2.71 France 774 3.0 95 679 12.3 39.9 43.9 55.7 2.53 Finland 167 0.6 17 150 10.2 43.0 53.9 64.1 2.35 Germany 6205 24.1 738 5467 11.9 40.3 49.0 60.9 2.49 Greece 171 0.7 37 134 21.6 41.2 48.5 58.5 2.67 Hungary 219 0.8 25 194 11.4 40.5 42.9 61.2 2.57 India 189 0.7 20 169 10.6 37.9 62.4 64.0 3.56 Ireland 4292 16.6 459 3833 10.7 41.2 44.2 58.5 2.51 Italy 2085 8.1 233 1852 11.2 39.6 47.4 57.1 2.47 Japan 117 0.5 13 104 11.1 39.9 46.2 51.3 3.04 Mexico 1594 6.2 109 1485 6.8 35.8 49.3 56.2 1.86 Netherlands 540 2.1 77 463 14.3 41.4 49.4 65.6 2.30 Philippines 193 0.7 13 180 6.7 38.3 40.4 61.7 3.03 Poland 1059 4.1 102 957 9.6 41.5 46.6 62.8 2.54 Portugal 129 0.5 21 108 16.3 40.0 40.3 58.1 2.50 Russia 515 2.0 78 437 15.1 41.9 46.6 61.8 3.19 Spain 407 1.6 59 348 14.5 39.5 44.0 55.0 2.39 Sweden 590 2.3 74 516 12.5 40.2 47.6 59.8 2.64 Switzerland 147 0.6 25 122 17.0 42.3 40.8 64.6 2.88 UK 5543 21.5 772 4771 13.9 43.0 50.3 63.0 2.75

Notes: N is the number of observations, N and N% computed using population weights.

%Entrepreneur represents the percentage of respondents per country who are identified as entrepreneurs. Education is the average education degree level of respondents per country. 1=degree lower than high school, 2= high school degree, 3 = junior college degree, 4= bachelor degree, and 5= graduate degree.

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Table 2

Descriptive statistics

Variables and description N Mean Standard

deviation Minimum Maximum Individual-level variables Entrepreneur 25,792 0.12 .32 0 1 Age 25,792 40.80 12.73 18 65 Marital status 25,792 0.60 .49 0 1 Gender 25,792 0.48 .50 0 1 Education

Degree Lower than high school 25,792 0.13 .13 0 1

High school degree 25,792 0.54 .50 0 1

Junior college degree 25,792 0.06 .24 0 1

Bachelor degree 25,792 0.18 .39 0 1 Graduate degree 25,792 0.09 .28 0 1 Country-level variables Assertiveness 25,792 4.27 .32 3.41 4.72 Performance orientation 25,792 4.14 .26 3.34 5.04 Uncertainty avoidance 25,792 4.56 .58 3.09 5.42

Notes: The descriptive statistics include all individuals with 21 different national backgrounds

displayed in Table 1. N, mean and standard deviation present population-weighted values. Minimum and Maximum columns present population unweighted values. Entrepreneur = 1, regular employed=0. Marital status is divided into: Married=1, Not-married=0. The cultural dimensions Assertiveness, Performance Orientation, and Uncertainty Avoidance are scaled from 1-7, 1 is low and 7 high.

Education has been associated with entrepreneurship likelihood. The analysis controlled for education, employing five educational levels based on the highest degree earned. Table 2 shows the descriptive statistics of all variables in the empirical model.

4.2. Method

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In the empirical model the individuals is i, who has a country of origin c. The individual’s entrepreneurship probability is indicated by Ent. HCC stands for Home Country Culture, thus the cultural dimensions. Gender is indicated by SEX, and marital status by MAR. EDU is the highest degree an individual has received.

Entic = β0 + β1HCCc + β2SEXic + β3 MAR + β4AGE ic + β5AGESQUAREDic + β6EDUic + εic

High multicollinearity among the independent variables can create problems for the coefficients estimations of the model, therefore the variables are checked for the presence of multicollinearity (de Vries, & Huisman, 2007). To check for multicollinearity the variance inflation factors (VIFs) of all variables are computed, with a tolerance value of less than .10, or VIF value of above 10 (Pallant, 2013). The VIF tests can be found in Appendix C. The tests show low VIF values between 1.002 and 2.017 are found for entrepreneurship, marital status, gender, and cultural practices. However, age and age squared show as expected high correlation. Additionally, a correlation matrix with all variables is created to find multicollinearity. Table 3 displays the correlation matrix and confirms that age and age squared are highly bivariate correlated. The correlation matrix shows that there are no further close relationships between the variables, and all variables can be included in the same model for analysis, because a bivariate correlation above 0.7 is considered too high (Pallant, 2013).

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Table 3

Correlation Matrix of all variables in the model

1 2 3 4 5 6 7 8 9 1 Entrepreneur 1 .102** .110** .031** .048** .097** .015* .000 .008 2 Agesquared 1 .990** -.024** .152** -.007 .028** .031** -.013* 3 Age 1 -.003 .177** -.008 .027** .032** -.013* 4 Degree 1 .001 .019** .002 .002 -.064** 5 Marital status 1 .009 .019** .013* .009 6 Gender 1 .019** -.004 .017** 7 Uncertainty avoidance 1 .614** .541** 8 Performance orientation 1 .334** 9 Assertiveness 1

* Significance at the 0.05 level ** Significance at the 0.01 level

This study adopts a two-step testing strategy to analyse the influences on entrepreneurship. First, individual and country level control variables are added in the model to estimate the proportion of predictability explained by the control variables (Model 1 and model 3 of Table 4), before adding the three cultural predictors. Moreover, the first step enables the analysis to isolate the proportions of the remaining predictability further explained by the addition of the three cultural predictors in the second step (Model 2 and 4 of Table 4), hence the model comparison indicates how much of the entrepreneurship predictability is explained exclusively by the country-level predictors.

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Chapter 5. EMPERICAL RESULTS

5.1. Baseline results

Direct logistic regression is performed to assess the impact of a number of factors on the likelihood that respondents would report that they are an entrepreneur. Table 4 shows the effect of the individual-level and country predictors on the entrepreneurship likelihood, furthermore, it reports the model fit statistics. Model 1 of Table 4 includes all individual-level controls. It reports the predictability of entrepreneurship accounted for only the individual control variables. In case a model would have guessed none of the respondents were entrepreneur, this model would have been right in 88.1% of the times. The predictability of the null model is almost identical for Model 1. The percentage of predictability shows no difference, but model 1 with control variables predicts better than the null model without explanatory variables.

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Table 4

The effects on the likelihood of being an entrepreneur (odds ratio)

Practices Values

Model 1 Model 2 Model 3 Model 4

Individual level variables

Age 4.30***(.12) 4.32***(.13) 4.27***(.13) 4.27***(.13)

Age (squared) 0.87***(.27) 0.87***(.01) 0.87***(.01) 0.87***(.01)

Gender 1.86***(.04) 1.85***(.04) 1.85***(.04) 1.86***(.04)

Marital status 1.14***(.04) 1.14**(.04) 1.14**(.04) 1.14**(.04) Education

Degree lower than high school - - - -

High school degree 0.84*(.08) 0.84*(.08) 0.87(.08) 0.87(.08) Junior college degree 0.92(.07) 0.91(.07) 0.91(.07) 0.92(.07)

Bachelor 0.90(.10) 0.90(.10) 0.91(.10) 0.92(.10)

Graduate 1.10(.07) 1.10(.21) 1.10(.08) 1.10(.08)

Country level variables

Uncertainty avoidance 1.10*(.05) 0.97(.05)

Assertiveness 1.04(.07) 0.87*(.05)

Performance orientation 0.82*(.10) 0.59***(.15)

Human orientation 1.85***(.13) 1.94***(.15)

Random part estimates

Number of observations 25,762 25,762 25,762 25,762

Number of groups (countries) 21 21 21 21

Degrees of freedom 8 11 9 12

Prob > χ2

*** *** *** ***

-2 Log likelihood 18,094.27 18,077.19 17,920.48 17,905.46

Cox & Snell R2 0.027 0.028 0.028 0.028

Nagelkerke R2 0.053 0.053 0.054 0.055

Notes: Standard errors in parentheses. The estimates represent odds ratio (OR). OR>1 represents a

positive relationship, whereas OR<1 represents a negative relationship. Age is calculated in groups of 10 years. For instance, an individual that is 10 years older, is 4.3 times more likely to be entrepreneur (in model 1). The base variable for degree is lower than high school, and the other degree odds ratios, standard errors and significance levels are based on it. For instance an individual with a high school degree is 16% (1-0.84; p<0.05) less likely to be an entrepreneur than an individual with a degree lower than high school (model 1). The cultural dimensions are scaled from 1-7, 1 is low and 7 high. * Significance at the 0.05 level

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entrepreneurship likelihood in comparison to the individual control variables; age, agesquared, gender, and marital status. The correlation matrix of Table 3 indicates a weak relationship between entrepreneurship and the independent variables, which suggested already that explaining variables are likely to be weak in explaining the variance in entrepreneurship.

The cultural practice predictors are substituted with cultural value predictors in model 4, in order to distinguish the influence of cultural practices and values on entrepreneurship likelihood. The additional country control variable human orientation value shows a positive influence, which is found to be significant in the control model 3 and model 4.Only the performance orientation value displays a similar sign and statistically significant effect on entrepreneurship probability, which confirms the unexpected opposite effect observed in model 2. The cultural value predictors in model 4 are no better predictors of entrepreneurship likelihood than the cultural practice predictors in model 2. In both models the cultural predictors have significant explanatory power; however the strength is weak in both models. The analyses of cultural influence on entrepreneurship suggest not that cultural practices exercise a more noticeable effect on entrepreneurship likelihood than cultural values do.

5.2. Robustness and extensions

5.2.1. Adding dimensions of national culture

A robustness check assesses the strength of the results of the cultural dimensions, and the robustness check extends model 2 and 4 with Hofstede’s cultural values. Hofstede has identified uncertainty avoidance as a cultural dimension in its study as well. Masculinity as a cultural dimension by Hofstede is a common predictor of entrepreneurship, and it is linked conceptually to assertiveness (Cullen et al., 2013). These two dimensions by Hofstede are added to the models.

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Table 5

Robustness check adding Hofstede dimensions

Practices Values

Model 5 Model 6

Age 4.32***(.12) 4.27***(.13)

Age (squared) 0.87***(.01) 0.87(.01)

Gender 1.85***(.04) 1.85***(.04)

Marital status 1.13**(.04) 1.14**(.04)

Education

Degree lower than high school - -

High school degree 0.85*(.08) 0.88(.08) Junior college degree 0.92(.07) 0.93(.07)

Bachelor 0.91(.10) 0.92(.10)

Graduate 1.10(.08) 1.10(.08)

Uncertainty avoidance 0.92(.06) 1.01(.07)

Assertiveness 1.53**(.13) 0.84**(.07)

Performance orientation 0.80*(.11) 0.59**(.19) Uncertainty avoidance (Hofstede) 1.00**(.00) 1.00(.00) Masculinity (Hofstede) 0.99***(.00) 1.90(.00)

Number of observations 25,762 25,762

Number of groups (countries) 21 21

Degrees of freedom 13 14

Prob > χ2 *** ***

-2 Log Likelihood 18,059.4 17,904.49

Cox & Snell R2 0.028 0.028

Nagelkerke R2 0.054 0.055

Note: See Table 4.

* Significance at the 0.05 level ** Significance at the 0.01 level *** Significance at the 0.001 level

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In Model 6 the GLOBE values assertiveness and performance orientation remain to have significant odds ratios, suggesting these two variables are robust predictors of entrepreneurship.

5.2.2. Robustness check of cultural effect on entrepreneurship

Entrepreneurship rates in the countries of origin can be used as a cultural proxy to verify the effect of national culture on entrepreneurship rates. Fogli and Fernandez (2006) used female labour participation and total fertility rates from the country of origin as proxies for national culture to explain female immigrants’ behaviour in the United States such as their individual work and fertility outcomes. Yuengert (1995) found a positive correlation between aggregate self-employment shares of immigrants and home-country self-employment rates. Therefore, national entrepreneurship rates are assigned to all individuals to verify the robustness of culture as a predictor of entrepreneurship. The data on national entrepreneurship rates are from Global Entrepreneurship Monitor, and can be found in Appendix E. There is no multicollinearity with the other variables of the original empirical model. Model 7 of Table 6 shows a positive partial effect of entrepreneurship rates of the immigrant’s country of origin on the individual’s average likelihood to be an entrepreneur. The outcomes show validity of the epidemiological approach, as it confirms that national culture influences entrepreneurship rates. On the contrary, the variance in entrepreneurship has not been explained by all aspects of culture in the original model 2, because the proxy for national culture explains as well partly the variance in entrepreneurship in addition to the original cultural predictors.

5.2.3. Extension of control variables

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Table 6

Robustness check adding extra cultural proxy and parent-entrepreneurship

Model 7 Model 8

Age 4.28***(.12) 4.39***(.13)

Age (squared) 0.87***(.01) 0.87***(.01)

Gender 1.85***(.04) 1.86***(.04)

Marital status 1.13**(.04) 1.11**(.04)

Education

Degree lower than high school -

High school degree 0.86(.08) 0.85(.08) Junior college degree 0.92(.07) 0.94(.07)

Bachelor 0.91(.10) 0.93(.10)

Graduate 1.11(.08) 1.10(.08)

Parent entrepreneur - 1.86***(.04)

Uncertainty avoidance 1.13**(.05) 1.10*(.05)

Assertiveness 1.12(.07) 1.00(.07)

Performance orientation 0.71***(.11) 0.84(.10) Entrepreneurship rate country of origin 1.05***(.01) -

Prob > χ2

*** ***

-2 Log Likelihood 18,066.02 17,859.80

Cox & Snell R2 0.028 0.036

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entrepreneurship rates better than the original model 2. On the other hand, including this control variable to the model changes the odds ratios and significance levels of the cultural predictors, indicating as well that the cultural practices are not robust predictors of entrepreneurship probability.

5.2.4. Excluding outliers in dataset

There is a potential concern that results might be driven by influential outliers in the dataset. Table 1 shows the sample descriptives, including the distribution of number of observations per country of origin. The United Kingdom, Ireland and Germany emerge to be outliers, as these countries combined represent 62.2% of all observations (16,040 out of 25,792 observations). Excluding these countries changes not the sign or significance of the cultural practice predictors, although the model as whole is better in predicting the variance in entrepreneurship probability (Cox & Snell R2 3.2%, and Nagelkerke R2 6.3%). Not including Ireland and the United Kingdom individually in the analyses makes the predictors statistically insignificant, whereas removing only respondent with Germany as country of origin results in all predictors to be significant; uncertainty avoidance 1.20 (p<0.01), performance orientation 0.78 (p<0.05), and assertiveness 1.25 (p<0.05).

The dataset is also verified for outliers in the dependent variable, which resulted in removing observations with family country of origin Greece in the analysis, as it has a large percentage of entrepreneurs. Excluding Greece from the analysis affects negatively the odds ratios and significance levels of the cultural predictors; performance orientation and assertiveness.

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Chapter 6. DISCUSSION AND CONCLUSION

This paper tests in what way national culture affects entrepreneurship activity, as rates of entrepreneurship vary largely between countries. The differences are partly explained by economic, institutional, and social demographic determinants, nonetheless, a large part of variation remains unexplained. Literature has acknowledged the influence of culture on entrepreneurship activity, only researchers have been hesitant to clarify economic outcomes with reference to national culture in quantitative empirical work. Culture is intertwined in institutions, therefore, it is complicated to use culture in cross-country studies on entrepreneurship. By employing an epidemiological approach, this research intends to isolate the cultural effects from other institutional effects on entrepreneurship in a quantitative study.

The significant and quantitatively differences in entrepreneurship rates across immigrant groups in the United States have generally been interpreted as an indication of the importance of cultural differences (Busch, & Lassmann, 2010). Immigrants in the United States are analysed in the empirical model, as they share the same economic and institutional environment, and are assumed to have different national cultures. Their likelihood of being an entrepreneur is predicted with the cultural dimensions uncertainty avoidance, performance orientation, and assertiveness, while controlling for individual characteristics. The proxy for entrepreneurship in this paper is self-employment, while the cultural practices from the GLOBE study operationalises the cultural dimensions.

The results in this paper show that cultural dimensions are not accurate predictors of immigrants becoming self-employed, and all hypotheses are rejected. On the other hand, culture explains some of the variation in self-employment rates. The influence of culture on entrepreneurship is confirmed by the robustness check using entrepreneurship rates in the countries of origin as a proxy for culture. Nevertheless, national culture remains a weak predictor in comparison to the control variables in the empirical model.

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significant opposite effects on entrepreneurship are observed, but uncertainty avoidance and assertiveness chance signs when switching from Model 2 to Model 4.

Confirmation of the hypotheses could possibly be achieved if limitations on the data are overcome. Firstly, self-employment was used as a proxy for entrepreneurship, which includes micro-entrepreneurs as well. Many self-employed individuals in for instance the service sectors, transport services and retail services are pushed into self-employment, as they have not the choice of not being self-employed (Busch, & Lassmann, 2010). As entrepreneurs are perceived as individuals building firms, and growing it through investments and generating employment, then one should take only incorporated self-employed immigrants into account. Secondly, currently all individuals indicating to have a country of family origin outside the United States are included in the analyses. The individuals can be first or even fourth generation immigration. First generation immigrants may deviate from their traditional behaviour due to initial shock from for instance a different language or institutions (Fernandez, 2007). Later generations may suffer from “loss of national culture”, as the influence of original culture may weaken over time, due to the new observed culture (Fernandez, 2007). Therefore, including only second generation immigrants in the analyses is optimal, as they have inherited their parents’ culture to some extent (Hofstede, 1980, Sapienza, Zingales, & Guiso, 2006). In addition, second generation immigrants do not suffer from the previously mentioned initial shock such as first generation migrants might do. Thirdly, the data shows signs of outliers, as 62% of the observations are from three countries of origin. The results would be more reliable if the individuals were equally distributed based on their countries of origin.

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INFO ABOUT THE AUTHOR

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APPENDIX A

Description of what performance orientation and assertiveness societies tend to do

The description of societies with high or low performance orientation and assertiveness are matched in two tables. The original tables can be found in the book: Culture, Leadership, and Organisations The GLOBE study of 62 societies (House et al., 2004), for performance orientation on page 245 and assertiveness on page 415. The first items in both tables have words underscored as they refer to each other’s society’s description. The items which are either identical or describe the same phenomena are in italics..

Table A1

Societies that score higher on performance orientation and assertiveness, tend to

Societies that score higher on performance orientation, tend to:

Societies that score higher on assertiveness, tend to:

- value assertiveness, competitiveness, and materialism

- stress equity, competition, and performance

- emphasise results more than people - emphasise results over relationships

- reward performance - reward performance

- value taking initiative - value taking initiative

- expect demanding targets - expect demanding and challenging targets - believe that individuals are in control - believe that individuals are in control - have a "can-do" attitude - have a "can-do" attitude

- believe that anyone can succeed if he or she tries hard enough

- believe that anyone can succeed if he or she tries hard enough

- value what you do more than who you are

- value what you do more than who you are

- value being direct, explicit, and to the point in communications

- value being explicit and to the point in communications

- value training and development - value assertive, dominant, and tough behaviour for everyone in society

- value and reward individual achievement

- have sympathy for the strong

- have performance appraisal systems that emphasise achieving results

- value competition

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improvement calculation

- value bonuses and financial rewards - values success and progress

- have a sense of urgency - value direct and unambiguous

communications - believe that schooling and education

are critical for success

- act and think of others as opportunistic

- have a monochronich approach to time - values expressiveness and revealing thoughts and feelings

- attach little importance to age in promotional decisions

- have relatively positive connotations for the term aggression (e.g. aggressions helps to win - have a just-world belief

- try to have control over the environment

Table A2

Societies that score lower on performance orientation and assertiveness, tend to

Societies that score lower on performance orientation, tend to

Societies that score lower on assertiveness, tend to

- view assertiveness as socially unacceptable

- view assertiveness as socially unacceptable and value modesty and tenderness

- value societal and family relationships - value people and warm relationships

- view merit pay as potentially destructive to harmony

- view "merit pay" as potentially destructive to harmony

- have high respect for quality of life - stress equality, solidarity, and quality of life

- emphasise seniority and experience - emphasise tradition, seniority, and experience

- emphasise tradition

- value harmony with the environment rather than control

- value harmony with the environment rather than control

- have performance appraisal systems that emphasise integrity, loyalty, and

cooperative spirit

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- emphasise integrity, loyalty, and cooperative spirit

- have high value for sympathy - have sympathy for the weak

- associate competition with defeat and punishment

- value who you are more than what you do

- value who you are more than what you do

- value ambiguity and subtlety in language and communications

- value ambiguity and subtlety in language and communications

- have a polychronic approach to time - speak indirectly and emphasise "face-saving"

- have a low sense of urgency - value detached and self-possessed conduct

- emphasise loyalty and belongingness - have far more negative connotations with the term aggressions (e.g. aggressions leads only to negative outcomes)

- view feedback and appraisal as judgment and discomforting

- Have an unjust-world belief

- value "attending the right school" as an important success criterion

- build trust on the basis of predictability

- regard being motivated by money as inappropriate

- think of others as inherently worthy of trust

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APPENDIX B

The cultural practise scores for each country considered in the analysis

Table B1

Assertiveness, performance orientation, and uncertainty avoidance practice scores per country.

UNSDCODE Countries Assertiveness Performance

orientation Uncertainty avoidance 40 Austria 4.59 4.47 5.1 124 Canada 4.09 4.46 4.54 156 China 3.77 4.37 4.81 208 Denmark 4.04 4.4 5.32 826 United Kingdom 4.23 4.16 4.7 250 France 4.44 4.43 4.66 276 Germany 4.715 4.29 5.27

280 Germany (former West) 4.66 4.42 5.35

278 Germany (former East) 4.77 4.16 5.19

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APPENDIX C

VIF scores of all variables in the model.

Table C1

VIF scores off all variables

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APPENDIX D

The outcomes of the models with all GLOBE practices and values included, and the correlation matrices.

Table D1

The effects on the likelihood of being an entrepreneur with all GLOBE dimensions (odds ratio)

Practices Values

Age 4.32***(.12) 4.23***(.13)

Age (squared) .87***(.01) .87***(.01)

Gender 1.85***(.04) 1.85***(.04)

Marital status 1.13**(.04) 1.14**(.04)

Education

Degree lower than high school

High school degree .88(.08) .89(.08)

Junior college degree .92(.07) .93(.07)

Bachelor .91(.10) .92(.10)

Graduate 1.10(.08) 1.10(.08)

Uncertainty avoidance .75**(.10) 1.36**(.10) Assertiveness 1.21(.21) .87*(.06) Performance orientation .95(.17) .59**(.19) Human orientation .96(.10) 2.02***(.17) Power distance 1.24(.11) .73(.19) Future orientation 1.08(.15) .79(.13) Institutional collectivism 1.20(.17) 1.07(.09) In-group collectivism .75**(.09) .73(.16) Gender egalitarianism .89(.14) 1.68***(.12) Random part estimates

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Prob > χ2 *** ***

-2 Log likelihood 18050.3 17881.41

Cox & Snell R2 0.029 0.029

Nagelkerke R2 0.055 0.057

Table D2

Correlation matrix with all GLOBE practices

Cultural practices 1 2 3 4 5 6 7 8 9 1 Uncertainty avoidance 1 .155** .614** -.350** -.261** .827** -.774** -.121** .541** 2 Power distance 1 -.119** -.564** -.273** -.212** .036** -.681** .520** 3 Performance orientation 1 .184** -.334** .665** -.331** .139** .334** 4 Human orientation 1 -.156** -.055** .325** .695** -.735** 5 Gender egalitarianism 1 -.107** -.153** .340** -.217** 6 Future orientation 1 -.805** .166** .288** 7 In-group collectivism 1 -.076** -.285** 8 Institutional collectivism 1 -.770** 9 Assertiveness 1

Note: See Table 3.

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Table D3

Correlation matrix with all GLOBE values

Cultural values 1 2 3 4 5 6 7 8 9 1 Uncertainty avoidance 1 .212** -.414** -.467** -.714** .557** .410** -.050** .371** 2 Power distance 1 -.023** -.153** -.145** -.426** -.082** -.393** .078** 3 Performance orientation 1 .324** .262** -.003 -.333** .521** -.454** 4 Human orientation 1 .332** -.198** -.031** .225** -.354** 5 Gender egalitarianism 1 -.411** -.025** -.080** -.250** 6 Future orientation 1 .277** .465** .068** 7 In-group collectivism 1 -.344** .263** 8 Institutional collectivism 1 -.307** 9 Assertiveness 1

Note: See Table 3.

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APPENDIX E

Country entrepreneur rates 20132 Table E1

Entrepreneurship rates per country in 2013

Country Self-employment rate (%)

Austria* 7.6 Canada 8.4 China 11 Denmark* 3.4 Finland 6.6 France 4.1 Germany 5.1 Greece 12.6 Hungary 7.2 India 10.7 Italy 3.7 Japan 5.7 Mexico 4.2 Netherlands 8.7 Philippines 6.6 Poland 6.5 Portugal 7.7 Russia 3.4 Spain 8.4 Sweden 6 Switzerland 10 United Kingdom 6.6

*The entrepreneurship rates for Austria and Denmark are from 2012

2

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APPENDIX F

Robustness check: excluding outliers. Table F1

Robustness check, excluding outliers: Excluding Ireland, United Kingdom Germany

No Ireland/UK Germany No Ireland No United Kingdom No Germany

Age 5.74***(.21) 4.46***(.14) 4.53***(.14) 4.57***(.14)

Age (squared) 0.85***(.02) 0.87***(.02) 0.87***(.02) 0.86***(.02)

Gender 1.93***(.07) 1.88***(.04) 1.88***(.05) 1.82***(.05)

Marital status 1.11(.07) 1.12*(.05) 1.16**(.05) 1.12*(.05)

Education - - - -

Degree lower than high school - - -

High school degree 0.71**(.13) 0.82*(.09) 0.86(.10) 0.80*(.09) Junior college degree 0.86*(.11) 0.90(.07) 0.98(.08) 0.85*(.07)

Bachelor 0.87(.17) 0.85(.11) 0.93(.12) 0.93(.11)

Graduate 1.00(.12) 1.09(.08) 1.07(.09) 1.10(.08)

Country level variables - - - -

Uncertainty avoidance 1.17*(.07) 1.08(.05) 1.08(.05) 1.20***(.06)

Assertiveness 1.26(.13) 1.01(.08) 1.07(.07) 1.25*(.10)

Performance orientation 0.75*(.14) 0.88(.12) 0.83(.10) 0.77**(.10)

Number of observations 9,741 21,476 20,224 19,565

Number of groups (countries) 18 20 20 20

Degrees of freedom 11 11 11 11

Prob > χ2

*** *** *** ***

-2 Log likelihood 6,538.62 15,209.01 13,747.60 13,724.99

Cox & Snell R2 0.032 0.030 0.027 0.028

Nagelkerke R

2

0.063

0.058

0.053

Note: See Table 4.

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Table F2

Robustness check, excluding outlier: Excluding Greece

No Greece Individual level variables

Age 4.26***(.13)

Age (squared) .87***(.01)

Gender 1.85***(.04)

Marital status 1.14**(.04)

Education

Degree lower than high school -

High school degree .84*(.08) Junior college degree .92(.07)

Bachelor .91(.10)

Graduate 1.11(.08)

Uncertainty avoidance 1.15(.08)

Assertiveness .98(.11)

Performance orientation .77(.13)

Number of observations 25,172

Number of groups (countries) 20

Degrees of freedom 11

Prob > χ2

***

-2 Log likelihood 17,641.33

Cox & Snell R2 .028

Nagelkerke R2 .054

Note: See Table 4.

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Table F3

Robustness check, excluding outliers: Excluding Russia & Hungary, and Sweden

No Russia & Hungary No Sweden Individual level variables

Age 4.10***(.13) 4.25***(.13)

Age (squared) 0.88***(.01) 0.87***(.01)

Gender 1.83***(.04) 1.84***(.04)

Marital status 1.15**(.04) 1.14**(.04)

Education

Degree lower than high school - -

High school degree 0.89(.08) 0.84*(.08)

Junior college degree 0.95(.07) 0.92(.07)

Bachelor 0.93(.10) 0.91(.10)

Graduate 1.13(.08) 1.11(.08)

Uncertainty avoidance 1.13*(.05) 1.15(.08)

Assertiveness 1.03(.07) 0.98(.11)

Performance orientation 0.86(.10) 0.77(.13)

Prob > χ2

*** ***

-2 Log likelihood 17527.35 17,641.33

Cox & Snell R2 .026 0.028

Nagelkerke R2 .051 0.054

Note: See Table 4.