Master Thesis
Small Business and Entrepreneurship MSc BA
Faculty of Economics and Business,
University of Groningen
“Self-employment in the European Union: How do institutions affect the well-
being of solo- and employer entrepreneurs?”
Abstract
Key words:
Employer entrepreneurship, European Union, Institutions, Self-employment, Solo self- employed, Well-being, Life Satisfaction
This study wants to examine if employer entrepreneurs working with one or more employees benefit more from entrepreneurial- friendly institutions than solo self- employed individuals who work independently. Based on a dataset of the European Social Survey (ESS), I compare life satisfaction levels of both employer- and solo entrepreneurs of 24 EU countries between 2002 and 2016, and analyze how the quality of institutions, measured by the Global Entrepreneurship Index (GEI), affects their well-being. Even if employer entrepreneurs in the EU are overall happier than the solo self-employed, the latter group is more positively affected by the entrepreneurship- friendliness of their institutions.
Nicolas M. Döhle, s2781360
Supervised by Dr. Michael Wyrwich Co- assessed by Dr. Maria Kristalova
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Introduction
According to the European Commission (2013), “entrepreneurship is a powerful driver of economic growth and job creation”. Since “especially SMEs represent the most important source of new employment” (European Commission, 2013), it makes most sense for European policy makers to promote the formation of new companies and small businesses.
After the 2008 economic recession, the European Union decided to take steps to help the economy grow through the encouragement of entrepreneurship, and as of 2013, the promotion of entrepreneurship is an explicit strategy stated in the Entrepreneurship 2020 Action Plan of the European Union (European Commission, 2013). In particular, the 2020 Action Plan of the EU wants to work on entrepreneurial education, training, the exchange of knowledge between European countries, the simplification of regulations, and better access to finance, such as through funds (European Commission, 2013), for example the “Gründungszuschuss” (start- up grant) in Germany (Baumann & Brändle, 2012).
In general, institutions facilitating entrepreneurship distinguish themselves through economic freedom (Nyström, 2008) and legal security, such as through the rule of law (Elert et al., 2017; Bjørnskov & Foss, 2013) and the protection of property rights (Elert et al., 2017; Nyström, 2008) on the formal side, and the social legitimacy (Kibler et al., 2014) as well as the presence of an entrepreneurial culture (Freytag & Thurik, 2007; Fritsch & Wyrwich, 2017) on the informal side. There is general agreement that institutions can promote entrepreneurship, but much less is known about how institutions affect the individual well-being (Fritsch et al., 2019) of the entrepreneur. In 2018, there were around 26 million freelancers in the European Union, who account for about 14% percent of the European workforce at the age from 20- 64 (Self-employment across EU regions, 2020). The trend shows a stable share of the self-employed, with a shift from the agricultural sector towards the service and public sector (Eurofound, 2017). Although the self- employed in the EU are well and satisfied with their job (Eurofound, 2017), a recent publication of the Eurofund (2017) shows that one fifth of the self-employed was forced to become an entrepreneur because there was no other alternative (Eurofound, 2017). About 10% of the self- employed even struggle to secure their financial security (Eurofound, 2017).
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Freelancers being forced into self-employment, for example to escape unemployment, tend to have lower levels of well-being compared to people who enter self-employment voluntarily such as for profit- oriented goals (Binder & Coad, 2013).
One must recognize that self- employment does not automatically lead to well-being. The policy makers and literature, particularly the study of Binder & Coad (2013), distinguish between “necessity” and “opportunity” entrepreneurship. It is important to take into consideration that about 25% of the European entrepreneurs are considered necessity entrepreneurs (Eurofound, 2017). Although most recent literature has a good idea on how and which institutions affect the individual well-being of the self-employed (eg. Fritsch et al. 2019a, 2019b), a smaller number of studies recognized that miscellaneous groupings of the self-employed may be affected differently by institutions. As Stel et al. (2014) argue, the self-employed should be considered as a heterogeneous group.
The distinction between solo self-employed individuals, who work solely for themselves, or employer entrepreneurs who work with employees, was barely made in the literature. Existing studies which recognize the distinction between those two groups of entrepreneurs merely examine this issue from an economic perspective (e.g. Stel et al., 2014) and only a small number of studies (e.g. Schummer et al., 2019) examine the well-being of these groups in depth. I would like to contribute to literature by recognizing the heterogeneity of the self-employed in order to deepen the understanding of how institutions affect the well-being of the self-employed.
Based on the aforementioned literature, the role of institutions on the well- being between solo- or employer entrepreneurs has not been studied yet, but there are unambiguous indications that differences in well-being also exist between these groups (e.g. Schummer et al., 2019). Solo- and employer entrepreneurs differ for example by the level of engagement (Schummer et al., 2019), their economic motives (Stel et al., 2014), and their satisfaction with work (Schummer et al., 2019). The question comes up whether employer entrepreneurs, based on their higher engagement and the bigger scope of their business, benefit more from entrepreneurship- friendly institutions than the solo self-employed do. Therefore, the following research question is established
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In order to answer the research question, I use a dataset of the European Social Survey providing a large variety of data about the social structure and social changes in the European Union. In the first part of the analysis, I compare well-being levels of solo- and employer entrepreneurs of 24 countries in the European Union. In the second part of this analysis, I examine how strongly the well-being of solo self-employed and employer entrepreneurs is influenced by the entrepreneur’s institutional environment, and how this effect differs between these two groups of the self-employed. The Global Entrepreneurship Index (GEI) serves as an indicator for institutional quality in this study.
The findings of this study are especially important to policy makers in order to be able to make well educated and precise decisions, to tackle the conditions of the self-employed purposefully. As Dilli et al. (2018) describes,“distinct institutional constellations facilitate the emergence of distinct forms of entrepreneurship”, and different groups of the self-employed are affected differently by policies.
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Literature Review
Self-employment and well-being
A variety of literature examining the well-being of entrepreneurs across multiple contexts confirms that self-employed individuals have a higher job satisfaction than wage employed individuals (e.g. Blanchflower, 2000, Binder & Coad, 2013), and also that findings are consistent across Europe, the USA, and Canada (Hanglberger & Merz, 2015).
At the first sight, this is surprising, as the working conditions of the self-employed are in general considered worse than the working conditions of the wage employed. Self-employed persons have longer working hours (e.g. Hyytinen & Ruuskanen, 2007) and earn overall less than their wage employed counterparts (e.g. Hamilton, 2000). Moreover, “any benefits that may accrue to the self-employed are gained at the cost of increased risk” (Bradley & Roberts, 2004). Especially in earlier phases of the venture, “being an entrepreneur is difficult work because of the high rate of failure” (Pham et al., 2018).
The well-being of entrepreneurs must therefore be determined by different contexts than success or income. Based on the study of Benz & Frey (2008), the procedural utility a person gains by being self-employed seems to be more meaningful in explaining the high levels of job satisfaction of self-employed persons than for example the financial outcomes. The term “procedural utility” can be best described as the utility gained from the work instead of the outcomes (Benz & Frey, 2008). In particular, the literature mentions key factors such as a higher level of independence (Benz & Frey, 2008), autonomy (Benz & Frey, 2008, Gelderen & Jansen, 2006), and self- determination (Benz & Frey, 2008), which make self-employment an attractive option. “Self-employed individuals obtain satisfaction from leading an independent lifestyle and ‘‘being their own bosses’’ (Binder & Coad, 2013).
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Hence, it makes sense to distinguish between the concepts of life- and job satisfaction. The relationship between self-employment and job satisfaction is relatively clear, whereas “the relationship between subjective well-being and self-employment is complicated” (Binder & Coad, 2016) and “more mixed” (Binder & Coad, 2016). “If self-employment would contribute positively to work satisfaction but decrease satisfaction with other domains of life (e.g., with the financial situation or with leisure time), it is not prima facie clear what the net effect on life satisfaction would be” (Binder & Coad, 2016).
Furthermore, one must recognize that the self-employed are a heterogeneous group, and the well- being of entrepreneurs varies with the conditions on which self-employment is based on. Binder & Coad (2013) for example distinguish between necessity entrepreneurs, being “pushed” into self-employment, for example to escape unself-employment, and opportunity entrepreneurs being “pulled” into self-employment to exploit opportunities or to follow profit- oriented goals. This distinction is important in determining the well-being of the self-employed, as entrepreneurs who become self-employed by necessity will, especially at the time or transition and the beginning of business conduct, experience a lower well-being than entrepreneurs who become self-employed by opportunity (Binder & Coad, 2013). One must therefore realize that self-employment does not automatically lead to a higher well- being, and that different groups of the self-employed have different levels in well-being.
When examining the well-being of the self-employed by dividing them into solo- and employer entrepreneurs, as done in this study, the situation is similarly complex and ambiguous. As Stel et al. (2014) describes, solo entrepreneurs as well as employer entrepreneurs are in themselves heterogeneous categories. For example, solo entrepreneurs may differ, among other factors, in their commitment to their business (Schummer et al., 2019), whereas employer entrepreneurs similarly differ, among other factors, in terms of innovativeness and their ambitions in firm growth (Stel et al., 2014).
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needs in an organization and community. Entrepreneurs in both categories can therefore draw satisfaction from their work and can also reach high satisfaction levels with their lives.
Nonetheless, there are indications that solo self-employed individuals show lower levels of well- being compared to employer entrepreneurs. Based on the available literature, solo entrepreneurs are less intrinsically motivated and less committed to their business (Schummer et al., 2019). Hence, I expect that the well-being of the solo self-employed is lower than the well-being of employer entrepreneurs and that significant differences in terms of well-being exist between these two group, which leads me to the first hypothesis
H1: Employer entrepreneurs have a higher well-being than solo self-employed individuals.
Institutions and the well-being of the self-employed
The literature confirms that the job and life satisfaction levels of the self-employed can be traced back to the institutions which surround the entrepreneur (e.g. Dilli et al., 2018, Fritsch et al., 2019b). “The more favorable institutions in a country are for entrepreneurship, the higher the job and life satisfaction of the self-employed” (Fritsch et al., 2019b).
In general, the literature distinguishes between formal and informal institutions. Formal institutions can affect entrepreneurship and overall business conduct. In particular, the availability of finance (Elert et al., 2017), less strict regulation of credit (Nyström, 2008), the protection of property rights (Elert et al., 2017; Nyström, 2008) and the rule of law (Elert et al., 2017; Bjørnskov & Foss, 2013), are among other factors key formal institutions that affect entrepreneurship and business conduct positively.
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In countries with well- developed institutions, with high levels of political rights and government control and quality, entry is easier than in less developed countries with a large unofficial market, corruption and bureaucratic delay (Djankov et al., 2002). Business entry is extremely expensive in the last three quartiles of the income distribution (Djankov et al., 2002), and therefore less expensive in well developed economies. Government control (Djankov et al., 2002), government quality (Fritsch et al., 2019a, Djankov et al., 2002), a smaller government sector (Nyström, 2008) and limited government interference (Bjørnskov & Foss, 2013) can therefore be considered as a basis for the creation of entrepreneurial- friendly regulations.
On the informal side, Fritsch et al., (2019b) mentions, based on the authors of Kibler et al. (2014), the social legitimacy of entrepreneurship, and based on the studies of Freytag & Thurik, (2007) and Fritsch & Wyrwich (2017), the presence of an entrepreneurial culture as key informal institutions that affect the well-being of entrepreneurs in particular. “If entrepreneurs are socially accepted and perceived as admirable role models, these informal institutions can be regarded as being entrepreneurship-facilitating” (Fritsch et al. 2019b).
Based on the study of Sobel et al. (2008), Chowdhury (2018) states that institutions can indeed influence the entrepreneur’s cognition and decisions. Nyström (2008) confirms that “institutions can obviously be expected to be influential in a person's decision to become an entrepreneur”. Institutional conditions can according to Chowdhury et al., (2018) affect the quantity of entrepreneurship, but also the quality of entrepreneurship, which is characterized by growth, innovativeness, and productivity. In other words, well developed institutions can promote the form of opportunity entrepreneurship as mentioned by Benz (2007), which leads according to Binder & Coad (2016), to higher levels of well-being among the self-employed. This leads me to the second hypothesis:
H2a: Entrepreneurship- facilitating institutions in a country positively moderate the relationship between self-employment and well-being
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nexus between economic development, entrepreneurship and institutions is important in order to understand why entrepreneurship varies between countries.
Stel et al. (2014) for example examined the relationship between solo- and employer entrepreneurs and macro- economic factors and recognized that both groups are affected differently by their economic environment. Based on the study Maslow (1970), Stel et al. (2014) claims that values such as “autonomy” are more important in well- developed economies, whereas social and material needs are more important in lower developed economies. Based on the studies of Ács et al. (2008) and North (1997), it can be confirmed that institutions and economic development are interdependent, and thus it can be assumed that the status of the value “autonomy” can also be viewed as more important in societies with well- developed institutions. As solo- entrepreneurs, compared to employer entrepreneurs, draw more satisfaction from their work if they work autonomously (Schummer et al., 2019) it is possible that the well-being of the solo self-employed is comparably higher in institutionally or economically developed societies.
However, Stel et al. (2014) state, based on the study of Congregado et al. (2014), that the high start- up rate in highly developed economies results in an intense competition, which forces entrepreneurs to grow their business in order to stay in the market. This can also be the case in well- developed institutional environments, as Chowdhury et al. (2018) confirms that business growth in these environments is stronger and thus firms become more innovative. Entrepreneurship- friendly institutions may stimulate the startup rate, and therefore the competition between businesses.
Based on this point of view, weaker solo self-employed individuals may face the threat of being pushed out of the market when the quantity of startups in the market rises, which may result in lower levels in well-being among the solo self-employed. As above all employer entrepreneurs strive for economies of scale (Stel et al., 2014) or growth, one can assume that employer entrepreneurs make more use of the benefits their institutional environment provides, which may result in higher levels of well-being. Thus, the following research question can be established.
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Methods
Data
According to the website of the European Social Survey (About the ESS ERIC, n.d.), the ESS measures “the attitudes, beliefs and behavior patterns of diverse populations” and interprets “how Europe’s social, political and moral fabric is changing”. It provides highly reliable and high- quality socio- demographic data with the focus on European countries, and therefore serves as the optimal basis for this study. Information on the individual level, such as the individual well-being and the employment status, but also basic controls such as age, gender, and education status are fully retrievable from the ESS. For the statistical analysis, I use a comprehensive data set from all rounds of the ESS from the period of 2002- 2016, which take place every two years. Thus, it is possible to provide a reliable and thorough foundation for the analysis, examining data of twelve rounds of the ESS from the period of 2002- 2016.
The Global Entrepreneurship Index (see Global Entrepreneurship Index, n.d.) serves as an indicator for the entrepreneurship- friendliness of the European countries. In the big picture, the GEI provides an indication of the health of the entrepreneurship ecosystem in a country. In particular, the GEI measures the “entrepreneurial attitudes, abilities and aspirations of the local population and then weights these against the prevailing social and economic infrastructure”. This provides insights about the institutional development of a country, and how well the ecosystem in a country promotes entrepreneurship. The methodology is endorsed by the European Commission (Institute, n.d.), and it provides “extensive, relevant, and highly illuminating data” (Global Entrepreneurship Index, n.d.) of the actual conditions of a country’s institutions. The GEI gives a simple, but clear indication for the entrepreneurship- friendliness of a country’s institutions and is therefore the optimal measurement to examine how institutions affect the well-being of the self-employed from a truly entrepreneurial perspective.
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risk capital (Ács et al., 2019). A detailed overview of the pillars is provided in the Appendix (Table A2).
Measurements
Well-being. “Subjective well-being (SWB) refers to people’s own evaluations of their lives,
evaluations that are both affective and cognitive where the affective part is better known as happiness and the cognitive as life satisfaction” (Moschidis, 2018). According to Pavot & Diener (2008), life satisfaction is “by far the most frequently used and best validated concept of measuring well-being”. “It intends to represent a broad, reflective appraisal a person makes of his or her life” (Fritsch et al., 2019b).
The European Social Survey provides the data set for measuring the well-being of the European self-employed. In this study, the individually perceived level of life satisfaction is used to measure the well-being of the respondents. Life satisfaction, presented in the dataset as “life satisfaction as a whole” in the European Social Survey, is measured on a Likert scale from 0 - extremely dissatisfied to 10 - extremely satisfied (Source Questionnaire Round 9, 2018).
Employment Status. The European Social Survey also provides information about the
employment status of the respondents. This is visualized in the variable “employment relation”, which can be characterized as a numeric, nominal variable. It contains the values of 1= employee, of 2= self- employed, and of 3= working for own family business. (Source Questionnaire Round 9, 2018). This study uses only the respondents indicating a position in self-employment, the remaining respondents who indicated to be wage employed or working in a family business are deleted from the dataset.
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Institutional development. The Global Entrepreneurship Index provides an evaluation of how the
ecosystem in a country contributes to entrepreneurship (Ács, 2019), and functions in this study as the moderator between the employment status of the self-employed and their well-being. It assigns scores to each country ranging from 0 to 100. The score defines how healthy the country’s ecosystem is, and to what extent the institutional conditions in a country promote entrepreneurship. The higher the score of the GEI, the higher the degree of entrepreneurship- friendly institutions in the country. Countries in the dataset are assigned the corresponding GEI values ranging from 23 (Bulgaria), indicating a less optimal environment for the entrepreneur, to 76 (Sweden), indicating a relatively high degree of entrepreneurship- friendliness of the institutions.
Control variables. According to Fritsch et al. (2019b), the effect of the status of occupation on
well-being varies with individual characteristics. Especially age, gender, and education are highly significant indicators for the life satisfaction levels of wage employed and self-employed individuals (Fritsch et al., 2019b). Similarly, significant effects can be expected for the solo self-employed and employer entrepreneurs.
Based on Fritsch et al., (2019b), I assume that age has a minimal, negative effect on life satisfaction. The variable “age” of the ESS is given as a numeric, continuous variable. In this study, I work with a sample of respondents at the age from 18 - 65 years in order to avoid including respondents who are legally not able to enter self- employment or who are retired.
In terms of gender, the female employees, either self-employed or wage employed, show higher levels of well-being than their counterpart, and significant differences exist between male and female workers (Fritsch et al., 2019b). The variable “gender”, retrieved from the European Social Survey, is a binary variable with values 1 = male and 2= female.
13 Method of Analysis
First, I provide an overview of respondents for each country with the country’s respective GEI scores and the country’s average level of well-being. Then, I provide the descriptive statistics of all the variables used, followed by a correlation analysis between the variables “employment status” and “life satisfaction”. The main analysis is performed with an Ordinary Least Squares Regression (OLS), as this kind of method allows variables to be added stepwise into the model to examine their interaction effects.
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Analysis and Results
In this study, I work with a dataset from the European Social Survey including 12 rounds of interviews from 2002- 2016. The total sample as used in the analysis encompasses data from 241 countries of the European Union from, namely Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Germany, Denmark, Estonia, Finland, France, Greece, Hungary, Ireland, Italy, Lithuania, Luxemburg, Netherlands, Poland, Portugal, Slovenia, Slovakia, Spain and Sweden. This results in a total sample of 13.055 respondents. The GEI scores per country range from 23 (Bulgaria) at the lowest to 80 (Denmark) at the highest, whereas the average life satisfaction levels per country range from 5,28 (Bulgaria) at the lowest to 7,94 (Sweden to the highest). A more detailed overview of the sample is available in Table A1 (Appendix).
Table 1: Correlation Analysis
Table 1: Correlation analysis on life satisfaction. The number of observations of all variables is 13.055. *p< 0,1, **p< 0,05, ***p<0,01
Life Satisfaction Employment Status
Life Satisfaction 1
Employment Status 0,081** 1
Table 1 shows the Pearson correlation coefficient in the correlation analysis with the variables “life satisfaction” and “employment status”. With a coefficient of 0,081**, the results show a low degree of correlation between these variables. The reasons for this may lie in the heterogeneous nature of the self-employed. It is difficult to attribute “opportunity” entrepreneurship solely to employer entrepreneurs, as according to Stel et al (2014), employer entrepreneurs also vary in in terms of their growth motives, or for example their innovativeness. Job and life satisfaction overall also depend on the individual needs of the entrepreneur. Some solo entrepreneurs may appraise values such as autonomy more than for example social needs when working in a company with more employees (Schummer et al., 2019), and still draw a high degree of satisfaction from their work, which could explain why the results of the correlation analysis are not that ambiguous.
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Table 2: Descriptive Statistics
Table 2: Descriptive statistics of all variables. The number of observations of all variables is 13.055
Variable Mean Std. Deviation Minimum Maximum
Life Satisfaction 7,10 2,134 0 10
Employment Status 0,41 0,492 0 1
Age 46,25 11,237 18 65
Gender 1,35 0,478 1 2
Education Level 3,35 1,312 1 5
Table 2 shows a general description of the variables used in this study. The overall life satisfaction in the European Union is quite high with an average of 7,10 on a Likert Scale from 0 (extremely dissatisfied) to 10 (extremely satisfied). The variable “employment status” is a binary variable with the values 0 (zero employees) and 1 (more than zero employees). With an average of 0,41, most of the self-employed individuals in the EU does not have any employees.
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Table 3: OLS Regression on Life Satisfaction
Table 3: OLS Regression on Life Satisfaction. *p< 0,1, **p< 0,05, ***p<0,01.
Independent and Control Variables Model 1 Model 2 Model 3
Employment Status 0,315*** (0,000) 0,285*** (0,000) 0,723*** (0,000) Age -0,002 (0,175) -0,008*** (0,000) -0,008*** (0,000) Gender 0,022 (0,566) 0,104*** (0,006) 0,105*** (0,006) Level of Education 0,186*** (0,000) 0,102*** (0,000) 0,099*** (0,000) GEI 0,040*** (0,000) 0,044*** (0,000)
GEI x Employment Status -0,008***
(0,004)
Adj. R² 0,020 0,082 0,085
F 67,145*** 241,574*** 202,843***
N 13055 13055 13055
Table 3 shows the first part of the OLS regression with the dependent variable life satisfaction, and the independent variables employment status, GEI, the multiplication between employment status and GEI, and the control variables age, gender and education. Whereas Model 1 solely regresses employment status on life satisfaction, the variables GEI and GEI*employment status are added stepwise to Model 2 and 3.
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For Hypothesis 2a, stating that entrepreneurship- facilitating institutions in a country positively moderate the relationship between self-employment and well-being, the results are similarly positive. The relationship between institutional quality (GEI) and well-being shows a comparably weak, but positive effect with ß= 0,040 in Model 2 and ß= 0,044 in Model 3, both significant at the p < 0,01 level (p = 0,000), indicating an unambiguous interrelation between entrepreneurship- friendly institutions and the well-being of the entrepreneur. Institutional development and quality do indeed positively influence self-employed individuals (Fritsch et al., 2019b), which confirms the first part of Hypothesis 2.
Multiplying the scores of the GEI with the employment status variable, there seems to be a small but significant difference between the solo self employed and employer entrepreneurs, with ß= -0,008 at p < 0,01 (0,004), indicating that employer entrepreneurs are less positively affected by their institutions than solo self-employed entrepreneurs. In contrast to Hypothesis 2b, stating that employer entrepreneurs benefit more from entrepreneurial- friendly institutions, it is the solo self-employed that, at least from a statistical standpoint, profit significantly more from high quality institutions, which concludes that Hypothesis 2b can be rejected.
Looking at the control variables, especially the relationship between education and well-being sticks out. Whereas in model 1, the beta of education shows a value of ß= 0,186 with p < 0,01 (0,000), the value gets smaller when adding the GEI score and its multiplication with employment status. The final model shows a ß= 0,099, again highly significant with p = 0,00. It seems that the role of education becomes less important when the entrepreneur finds himself in an entrepreneurial- friendly institutional environment. Along with the expectations though, people with a good educational foundation show higher levels of life satisfaction (Fritsch et al., 2019b). Whereas the negative effect of age on life satisfaction is not significant in Model 1, it becomes significant as soon as including the variable GEI into Model 2 and 3. Both models show a ß= - 0,008 with a p= 0,000, which indicates that younger entrepreneurs are overall happier than older entrepreneurs.
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Table 4: OLS Regression on Life Satisfaction (1)
Table 4: OLS Regression of the single 14 pillars of the Global Entrepreneurship Index on Life Satisfaction. *p< 0,1, **p< 0,05, ***p<0,01. Variables Model 1 (Pillar 1) Model 2 (Pillar 2) Model 3 (Pillar 3) Model 4 (Pillar 4) Model 5 (Pillar 5) Employment Status 0,474*** 0,627*** 0,763*** 0,365*** 0,512*** Age -0,008*** -0,003** -0,006*** -0,007*** -0,007*** Gender 0,081** 0,039 0,069 0,069* 0,077* Education 0,116*** 0,201*** 0,143*** 0,149*** 0,123*** Pillar 0,024*** 0,019*** 0,026*** 0,023*** 0,022*** Pillar * Employment Status -0,004*** -0,005* -0,007*** -0,001 -0,004** Adj. R² 0,089 0,039 0,066 0,073 0,073 F 214,527*** 89,082*** 153,947*** 171,429*** 171,917*** N 13.055 13.055 13.055 13.055 13.055 Variables Model 6 (Pillar 6) Model 7 (Pillar 7) Model 8 (Pillar 8) Model 9 (Pillar 9) Model 10 (Pillar 10) Employment Status 0,620*** 0,594*** 0,401*** 0,551*** 0,315*** Age -0,007*** -0,066*** -0,004** -0,007*** -0,006*** Gender 0,094** 0,093** 0,066* 0,079** 0,075** Education 0,132*** 0,128*** 0,154*** 0,100*** 0,129*** Pillar 0,027*** 0,024*** 0,016*** 0,021*** 0,023*** Pillar * Employment Status -0,005*** -0,005** -0,002 -0,004** -0,00006 Adj. R² 0,082 0,057 0,040 0,064 0,065 F 195,881*** 132,373*** 91,024*** 148,542*** 152,635*** N 13.055 13.055 13.055 13.055 13.055
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Table 4: OLS Regression on Life Satisfaction (2)
Table 4: OLS Regression of the single 14 pillars of the Global Entrepreneurship Index on Life Satisfaction. *p< 0,1, **p< 0,05, ***p<0,01 Variables Model 11 (Pillar 11) Model 12 (Pillar 12) Model 13 (Pillar 13) Model 14 (Pillar 14) Employment Status 0,422*** 0,445*** 0,153 0,035 Age -0,006*** -0,006*** -0,002 -0,003 Gender 0,066* 0,082** 0,021 0,039 Education 0,138*** 0,110*** 0,194*** 0,163*** Pillar 0,022*** 0,026*** -0,004*** 0,018*** Pillar * Employment Status -0,002 -0,003 0,002 0,005 Adj. R² 0,053 0,053 0,021 0,040 F 123,934*** 122,462*** 47,256*** 91,654*** N 13.055 13.055 13.055 13.055
Note: Pillar 11= “Process Innovation”, Pillar 12= “High Growth”, Pillar 13= “Internationalization”, Pillar 14= “Risk Capital”.
Table 4 highlights the effect of the single 14 pillars of the Global Entrepreneurship Index on the life satisfaction levels of the respondents. A more detailed description of all 14 pillars is attached in Table A2 (Appendix).
All 14 pillars of the Global Entrepreneurship Index show a highly significant relationship with life satisfaction levels at p < 0,01. All pillars, except the pillar “Internationalization” (ß= - 0,004), positively affect the well-being of the self-employed. These are “opportunity perception (ß= 0,024), startup skills (ß = 0,019), risk acceptance (ß= 0,026), networking opportunities (ß= 0,023), cultural support (ß= 0,022), opportunity startups (ß= 0,027), technology absorption (ß= 0,024), human capital (ß= 0,016), competition (ß= 0,021), product innovation (ß= 0,023), process innovation (ß= 0,022), high growth (ß= 0,026) and risk capital (ß= 0,018).
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this, it is visible that the effects of the single pillars are not equally strong for both groups of the self-employed.
Overall, it can be said that solo entrepreneurs benefit slightly, but significantly more from the development of their institutional environment than employer entrepreneurs. Only the pillars “Internationalization”(ß= 0,0029) and “Risk Capital” ß= 0,005) show the opposite effect and seem more beneficial for employer entrepreneurs, but the relationships between these pillars and the dependent variable “life satisfaction” is not significant.
Also the pillars “networking opportunity” (ß= -0,001), “human capital” (ß= -0,002), “process innovation” (ß= -0,002), “high growth” (ß= -0,003), “product innovation” (ß= -0,0006), which indicate a stronger effect for the solo self-employed are not significant.
Significantly stronger effects for the solo entrepreneurs are visible in the pillars “opportunity perception (ß= -0,004, p< 0,01) start-up skills (ß= -0,005, p< 0,1), risk acceptance (ß= -0,007, p< 0,01), cultural support (ß= -0,004, p< 0,05), opportunity start-ups (ß= -0,005, p< 0,01), technology absorption ( ß= -0,005, p< 0,05) and competition (ß= -0,004, p< 0,05)”. The Betas range from ß= -0,004 (“opportunity perception, cultural support, competition”) to ß = - 0,007 (“risk acceptance”).
Discussion and Conclusion
The statistical analysis of this study shows that employer entrepreneurs are happier than the solo self-employed counterpart, confirming Hypothesis 1. There is a strong difference between these groups. In fact, the results demonstrate a strong and highly significant gap in well-being between employer entrepreneurs and solo entrepreneurs.
One of the reasons for this may lie in higher levels of intrinsic motivation and higher levels of commitment to their business which is according to Schummer et al. (2019), attributed to employer entrepreneurs. A higher motivation leads to higher organizational commitment and an increase in psychological well-being (Schummer et al., 2019).
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Necessity entrepreneurs, being pushed into self-employment, may focus more on the material outcomes of their business in order to secure sustainability, whereas “opportunity entrepreneurs” draw more satisfaction from the procedures in their work. The latter group shows higher levels of well-being (Binder & Coad, 2016).
It is therefore possible that especially employer entrepreneurs may pull out more utility from their work and may in conclusion experience a higher satisfaction from their needs (Schummer et al., 2019). Based on the literature (see Schummer et al.,2019; Stel et al., 2014), it is less likely that employer entrepreneurs with growth motivations are entrepreneurs by necessity, which makes necessity entrepreneurship, rather, attributable to solo entrepreneurs, which could explain why employer entrepreneurs are overall happier.
In any case, well- developed institutions affect the well-being of the self-employed positively, which confirms the first part of Hypothesis 2. In other words, the higher the degree of the entrepreneurship- friendliness of the institutions in a country, the higher the life satisfaction of the entrepreneur.
A likely reason for this relationship is that entrepreneurial- friendly institutions decrease the costs of doing business and starting a business. Based on Djankov et al. (2002), business entrance is distinctly easier in well- developed institutional environments. Entrepreneurship- friendly institutions may bring down regulatory burdens for conducting business. As mentioned in previous parts of the report, there is a direct link between lower administrative burdens in business conduct and the higher well-being of the self-employed (Fritsch et al., 2019a).
Moreover, institutions can reduce uncertainty by the reduction of transaction costs (Williamson, 1985; Bjørnskov & Foss, 2013), which leads to the development of smaller businesses, as entrepreneurs are able to use the market instead of vertical integration (Williamson, 1985). Based on Congregado et al. (2014), Stel et al. (2014) perceives secular developments in technology and culture as further drivers for downsizing enterprises. Politically motivated entrepreneurial support, for example through financial access, funds and economic regulations (European Commission, 2013) further contribute to small business entrepreneurship and make self- employment an attractive opportunity.
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an entrepreneur decreases, and even entrepreneurs with lower qualifications and opportunities have a chance to be a successful entrepreneur.
Based on the theory of Malchow-Møller et al. (2008), stating that self-employment especially occurs when the individual qualification is either too high or too low, it can be assumed that especially individuals in the lower end of the ability distribution may enter self-employment more frequently out of opportunity reasons, which according to Benz & Frey (2008) and Larsson & Thulin (2018) leads to higher levels of well-being among the self- employed.
In contrast to the expectations of Hypothesis 2b, stating that employer entrepreneurs profit more from entrepreneurship- friendly institutions, the results of this study shows that it is the solo self- employed that benefit, statistically, significantly more from the development of their institutional environment.
In order to gain deeper insights about the relationship between entrepreneurship- friendly institutions and the well-being of the self-employed, I regressed all 14 pillars of the Global Entrepreneurship Index on the life satisfaction of the self-employed (Table 2), and came to the results that only the pillars belonging to the group of “entrepreneurial attitudes” (opportunity perception, start-up skills, risk acceptance and cultural support) and the pillars belonging to the group of “entrepreneurial abilities” (opportunity start- up, technology absorption and competition) show significant differences between solo and employer entrepreneurs.
None of the pillars from the group of “entrepreneurial aspirations” (with the pillars product innovation, process innovation, high growth, internationalization and risk capital) did show significant benefits in well-being for the solo self-employed. A possible explanation for this issue is that “entrepreneurial aspirations”, especially the pillar “risk capital” in the sense of the Global Entrepreneurship Index (see Appendix, Table A2) could be a sign that employer entrepreneurs use more often the availability of risk capital towards their business, which could also be further indication that growth aspirations are higher in the case of employer entrepreneurs.
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stronger employer entrepreneurs stay in the market if the competition is intensifying during economic growth, which is based on Ács et al. (2008), usually accompanied with institutional development.
The results of the remaining pillar groups “entrepreneurial attitudes” and “entrepreneurial abilities, the results are quite surprising, as based on the literature, “entrepreneurial attitudes”, such as the seek for opportunities and the taking of risks are more frequently attributed to employer entrepreneurs who are highly motivated and are striving for growth (Schummer et al., 2019). The same counts for “entrepreneurial abilities” which enable quality and opportunity entrepreneurship. Still, it seems that solo entrepreneurs benefit more from the development of their institutional environment.
In general, “entrepreneurial attitudes”, in the sense of the Global Entrepreneurship Index, measure to what extent the entrepreneurs in a country perceives opportunities, to what extent they think they are capable of starting a business, to what extent they are willing to take a risk, and to what extent society and culture supports entrepreneurship (Ács, 2019). For example, in countries scoring high in this part of the GEI, the confidence of the individual to possess the necessary skills and opportunities to start a business is higher, as well as the readiness to take risks.
In terms of solo entrepreneurship, it is possible that the entrepreneurial attitudes in a country may lessen the inhibition to become self-employed, even if the individual does not have motivations to grow a larger business through hiring employees. As Douglas & Shepherd (2000) describe, there is a general propensity to become self-employed if the same resources can be gained as in the previous position, such as in wage employment. From this perspective, it is possible that individuals tend to decide for (solo) self-employment even if entrepreneurship does not provide significantly more resources than their previous employment status.
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Besides “entrepreneurial attitudes”, the “entrepreneurial abilities” with the pillars “opportunity start- up, technology absorption and competition” showed again a stronger, positive effect on the well-being of solo entrepreneurs. According to Douglas & Shepherd (2000), the abilities of the entrepreneur affect to a large extent the intention of the individual to become self-employed. If the individual possesses entrepreneurial abilities to a high degree, it will have a stronger intention to become self-employed (Douglas & Shepherd, 2000).
The “entrepreneurial abilities” pillars by the Global Entrepreneurship Index on the other hand, also give insights into the market conditions of the entrepreneur as well. In synopsis, “entrepreneurial abilities” measure to what extent opportunity entrepreneurship is limited by the costs of doing business, to what extent technology is diffused and absorbed by the firms, and to what extent the competition is regulated in a country (Ács, 2019). Low levels of competition, for example through a stronger regulation of competition, decrease the incentive for companies to innovate (Stel et al., 2014), which can help weaker solo entrepreneurs to sustain in the market as the competition is less aggressive. Furthermore, technological development in general leads to smaller businesses (Congregado et al., 2014). As Congregado et al. (2014) explain: “Globalization in concert with the spread of ICT (information and communication technologies) enables solo entrepreneurs and small firms to reap the fruits of scale economies through loosely organized networks”. That is why solo entrepreneurs can conduct a successful business without the need for employees.
As North (1981) describes: “The opportunities that entrepreneurs spot and act on depend upon the institutional framework within which the entrepreneur works”. Some institutional environments provide opportunities for productivity or growing a business, whereas other environments provide possibilities to rent- seek (Baumol, 1990). Tax advantages for example may especially attract solo entrepreneurs who are less productive (Herrmann, 2018). Furthermore, policies promoting entrepreneurship and less entry regulations promote solo entrepreneurship (Vries et al., 2019). From that perspective, lower competition, a spread of communication technologies and lower costs of doing business may therefore increase the abilities of necessity entrepreneurs, which are more likely attributed to solo entrepreneurs (Vries et al., 2019).
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less satisfied with their lives (Larsson & Thulin, 2018), it is possible that the negative effect of necessity entrepreneurship on entrepreneurial satisfaction diminishes if the entrepreneur gains a satisfying income through self-employment (Kautonen & Palmroos, 2009).
It is possible that the incomes of such entrepreneurs are higher in institutional environments, as these offer more profit opportunity a high degree of “entrepreneurial abilities”. According to Larsson & Thulin (2018), income is directly related to life satisfaction.
Concluding Remarks and Implications
In this study, I wanted to answer the question if employer entrepreneurs benefit more from entrepreneurship- friendly institutions than the solo self-employed. Contrary to the expectations based on the literature, it is the solo self-employed who benefit slightly, but significantly more from entrepreneurship- friendly institutions than employer entrepreneurs.
Based on the results of the analysis, it seems that entrepreneurial- friendly institutions, at least in the European Union, form the conditions in the market in way that especially entrepreneurs with smaller companies have a chance to earn a living and to be happy entrepreneurs.
All in all, entrepreneurship- friendly institutions affect the self-employed positively as a whole. Similarly, entrepreneurship- facilitating institutions do not only affect the self-employed, but also the paid employed positively (Fritsch et al., 2019a, 2019b).
From there, policy makers should be aware that the policies and strategies created to encourage entrepreneurship contribute not only to a specific type of entrepreneurs but affects a variety of aspects in society. This makes it difficult for policy makers to target specific groups of entrepreneurs, and unproductive entrepreneurship, such as rent- seekers (Baumol, 1990) or entrepreneurs who exploit tax advantages (Herrmann, 2018), is also attracted.
The strategies, such as in the Entrepreneurship Action Plan 2020 of the European Union, may therefore benefit the quantity of startups, but not per se the quality. Policy makers should be more conscious about their strategies in order to make precise and differentiated decisions which are beneficial for the whole society.
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policy makers should reduce general subsidies towards entrepreneurship and “reallocate resources to programs that support high growth companies” (Shane, 2009).
From there, EU strategies supporting all kinds of entrepreneurship, should be adjusted in order to promote the type of “opportunity” entrepreneurs who contribute to the creation of jobs and wealth. At this moment, as the results of this study show, especially the solo self-employed benefit, who conduct business on a lower scale and who provide less employment opportunities.
Limitations and Suggestions for Future Research
This study examined the well-being of different groups of the self-employed, and how this well- being is moderated by the institutional framework of the entrepreneur. The framework of this study relies on a sample of 24 countries of the European Union. As already mentioned before in this study, there are parallels between the entrepreneurial well-being of European countries, and North American countries such as the USA and Canada (Hanglberger & Merz, 2015).
Nevertheless, Western markets have distinct characteristics that do not count for example in Asian or South American markets. In Asian markets such as China, the regulations related to self-employment are less entrepreneurial- friendly and opportunities differ based on urban or non- urban areas (Pham et al., 2018). Furthermore, even inside the European Union, the institutional conditions for entrepreneurs vary unambiguously between countries. The study of Fritsch et al. (2019b) showed that the well-being of entrepreneurs varies between different institutional regimes. The job and life satisfaction of entrepreneurs in “liberal” market regimes (e.g. UK and Ireland) is significantly higher than in “coordinated” market regimes, for example Germany. (Fritsch et al., 2019b). It is to expect that the single elements (e.g. the pillars of the GEI) of a society’s institutional framework have different effects on the well-being of the self- employed in different institutional regimes. Future research may therefore expand focus and examine the well-being of entrepreneurs in markets with different institutional conditions.
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31 Appendix
Table A1 - Division of respondents per country
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Table A2: The Pillars of the Global Entrepreneurship Index
Entrepreneurial Attitudes Pillars
Pillar 1
(Opportunity Perception)
Opportunity perception describes to what extent opportunities are recognized by individuals or entrepreneurs in a county, and to what extent the exploitation of these opportunities is limited in a market, for example through regulations.
Pillar 2 (Startup Skills)
Startup skills describes to what extent the population in a country perceives to have the necessary skills to start a business, and to what extent there is actually quality education and human resources.
Pillar 3
(Risk Acceptance)
Risk acceptance describes the percentage of the population who is willing to take risks to start a business, and to what extent there are general risks related to the country.
Pillar 4 (Networking)
Networking describes to what extent there are possibilities to build networks, and to what extent it is possible to connect and communicate with networks globally
Pillar 5
(Cultural Support)
Cultural support describes to what extent entrepreneurship is supported in a society, and to what extent corruption in a country affects this view.
Entrepreneurial Abilities Pillars
Pillar 6
(Opportunity Startup)
Opportunity Startup describes to what extent entrepreneurs are entrepreneurs by “opportunity” and to what extent this is limited by regulations in a country.
Pillar 7
(Technology Absorption)
Technology Absorption describes to what extent technology is diffused in a country and to what extent it can be absorbed by the businesses.
Pillar 8
(Human Capital)
Human Capital describes to what extent entrepreneurs are educated and to what extent the labor market in a country provides highly educated employees and their development.
Pillar 9 (Competition)
Competition evaluates the product and market uniqueness of startups against the market power of their competitors.
Entrepreneurial Aspirations Pillars
Pillar 10
(Product Innovation)
Product Innovation describes to what extent companies in country are able to create new products and to what extent technologies enable product innovation
Pillar 11
(Process Innovation)
(Process Innovation) Process Innovation describes to what extent businesses in a country are able create new technologies and to what extent institutions support the development of new technologies
Pillar 12 (High Growth)
High growth describes to what extent companies are growing quickly and to what extent business strategies are sophisticated.
Pillar 13
(Internationalization)
Internationalization measures to what extent the businesses in a country are able to export their products and to what extent a country is able to make complex products, for example through international collaboration
Pillar 14 (Risk Capital)
