An Empirical Study for European Countries: Factors Affecting Economic Growth and Self-Employment by Gender

Abstract

In economic literature, the relationship between entrepreneurship and economic growth has been widely discussed for some time now. In addition to the different theoretical approaches, a considerable amount of empirical works in recent decades have sought to verify the direct link between both variables by analyzing datasets from several distinct geographic areas. On one hand, it highlights the absence of a common indicator to measure entrepreneurship in practice relating to a country’s economic growth; on the other hand, it shows a great diversity of factors determining them. With the aim of providing new empirical evidence in the field of European entrepreneurship, this paper has analyzed data relating to 31 European countries over the last decade by introducing self-employment as an empirical proxy of entrepreneurship. In particular, this study contrasts the positive effect of public expenditure, investment, human capital, and entrepreneurship on economic growth for a wide range of countries and examines the impact of some economic and educational variables on self-employment, such as unemployment, taxes, education, and early school leaving. The estimation method used in this research had to consider the Ordinary Least Squares through a multiple regression model of constant coefficients based on annual Eurostat statistics for the period of 2010 to 2019. The results obtained verify the positive effect of public expenditure, investment, human capital, and entrepreneurship on economic growth. Moreover, the analysis of other factors affecting entrepreneurship, segregated by gender, shows how unemployment and the level of education have a positive impact on self-employment, while significant increases in the tax rate on capital and early school leaving harmed such variable. No significant differences were found between males and females.

1. Introduction

In moments of worldwide economic crises like those experienced during the so-called Great Recession of 2007–2009, a general uncertainty for businesses is created and millions of people lose their jobs. Likely, the same can apply to the current crisis generated by the COVID-19 pandemic. As demonstrated by some earlier studies focused on European countries [1,2,3], such situations often create an increase in the number of people considering going into entrepreneurship, particularly with a move toward self-employed activities. In this regard, it has been broadly accepted that entrepreneurship is one of the factors contributing the most to economic growth within a specified geographical area. This is not a novelty in this issue, as there are authors from the very beginning, such as Schumpeter, who have suggested that entrepreneurs fulfill a central function in the economy by carrying out innovations and exploring new ways to organize factors of production and, consequently, they play an important role for economic growth [4]. Additionally, a growing number of empirical studies during the last decades have also studied the improvement achieved in the well-being of the population as a result of the direct relationship between entrepreneurship and economic growth [5,6]. Unfortunately, in Europe, despite having recognized the influence of entrepreneurship on economic growth and social welfare, insufficient progress has been made so far. Indeed, the European Union institutions continue to make greater efforts in implementing measures to stimulate entrepreneurial activity in European countries.

Following up on this idea, and with the findings of previous studies, the present paper aims to add further empirical evidence in the field of European entrepreneurship. Firstly, the purpose of this work is to confirm previous findings and provides additional results with respect to the positive link between entrepreneurship and the economic growth in a wide range of European countries, analyzing statistical data available through Eurostat. Secondly, this study contributes to the increase of empirical evidence on the impact of some fundamental socioeconomic variables on entrepreneurship in the countries analyzed. The study has been carried out from a global perspective to verify the impact of entrepreneurship on economic growth and to assess how some factors are affecting European entrepreneurship over the past years. Moreover, the research has been performed by differentiating the data by gender in order to find similarities (or differences) between men and women.

Consequently, in a first step, the influence of entrepreneurship on economic growth has been addressed jointly with the impact of other economic variables that have traditionally been linked with economic growth in a positive manner [7,8,9], such as public expenditure, investment, and human capital. In a second step, once the positive effect of entrepreneurship on economic growth had been confirmed, a key part of the research focused on empirical analysis of effects, either positive or negative, of a range of variables on each domestic entrepreneurship level. Specifically, having rejected certain economic and technological variables as not being statistically significant, variables examined for the research are unemployment, taxes, formal education level, and the proportion of early school leavers. In this way, the paper aims to show and contrast the influence of these economic and educational factors on entrepreneurship across 31 European countries, since this can also affect economic growth, and therefore the wellbeing of the population.

Considering the conceptual complexity of entrepreneurship and the absence of a single indicator to be adequately measured [10], self-employment has been used as an empirical proxy of entrepreneurship throughout the present paper. This indicator is in line with what has been provided from some previous studies [11], which states that the identification of an entrepreneur through a self-employed person depends on the definition of the entrepreneur itself. In this way, if the definition of an entrepreneur seeks to emphasize the ability to assume risks, then a self-employed person can be treated as an entrepreneur. This is because entrepreneurs are not hired workers that receive a risk-free wage for their work but undertake the risk of conducting economic activity and obtain a risk-bound profit [11].

Taking into account all of the above, the paper has been structured as follows: the second section sets out theoretical aspects relating to the variables analyzed in the empirical study; the third section summarizes the characteristics of the sample and the methodology used, as well as the results of the analysis carried out; finally, the fourth section contains the main conclusions.

2. Theoretical Framework

Previous studies [7] have shown that public expenditure, investment, and human capital have an impact on economic growth. In line with these works, such variables have been used in this study to contrast how they affect economic growth in European countries. Additionally, the entrepreneurship indicator has also been included for the purpose of this paper. The expected relationship between investment and human capital with economic growth is positive, as an increase in investment should be a boost to economic growth and human capital can help to develop an economy by expanding the knowledge and skillset of its people. Nevertheless, in the case of public expenditure, this relationship is not fully clear. Some authors state that fiscal policy has a negative impact on private investment, and therefore, on the gross domestic product (GDP) [12], whereas others suggest that public expenditure positively affects the GDP, among others, through increasing public investment [13].

In considering the relationship between entrepreneurship and economic growth, with the purpose of enriching the theoretical framework with different points of view, this study cites several previous works that have taken up a stance for or against the self-employment variable, especially for the approximation of entrepreneurship in a given region. One of the reasons habitually justified, when choosing a single variable to measure the entrepreneurship of an economic area, is the limitation to find related statistical information that is also reliable and comparable. In this concern, some authors [14,15] are against the consideration of self-employment as synonymous with entrepreneurship. Other authors [16] deem it is inaccurate to measure entrepreneurship through self-employment since not all entrepreneurs are self-employed and vice versa; thus, admitting that the proper variable to be frequently considered as a proxy of entrepreneurship should be self-employment. Unfortunately, despite the important efforts undertaken by the Global Entrepreneurship Monitor (GEM) over the past years [17], substitute variables typically proposed by those authors critical of using self-employment as a proxy variable have not been used in this paper.

Either way, among the reasons why this paper has used self-employment as a fundamental variable, besides a proxy of entrepreneurship, is that the definition of entrepreneur emphasizes the link between them by taking certain economic risks. For that reason, in line with some other previous studies [8,18,19] analyzing the relationship between entrepreneurship and economic growth, in addition to those focused specifically on this matter at the European level [20,21], in this paper, the variable of self-employment, considered to be the number of self-employed persons in proportion to the workforce aged between 15 and 64 years old, has been used as a proxy for entrepreneurship. Regardless, the use of self-employment as a proxy is not an arbitrary research option. In fact, some authors have also used data on self-employment as an empirical proxy for entrepreneurship in other related fields, for instance, to build and adjust a model of occupational choice that allows for entrepreneurial entry and exit, in addition to investment decisions in the presence of borrowing constraints [22]; to study the relationship of the effective corporate tax rate with, among others, entrepreneurial activity [23]; to analyze the process of selection into self-employment over the life cycle and the determinants of self-employment earnings [24]; to discuss the link between self-employment and entrepreneurship in urban and rural labor markets [25]; even to model the individual‘s movement from wage work into entrepreneurship [26]. Ultimately, the use of the data on self-employment as a proxy of entrepreneurship carried out in this paper has been consistent with a proper methodology from earlier works [27,28,29,30].

As mentioned in the previous section, the present paper aims at empirically analyzing, firstly, the relationship of four variables (public expenditure, investment, human capital, and entrepreneurship) with economic growth, in line with other previous studies that associate entrepreneurship with economic growth [7,8]. Secondly, the effect of a set of performance indicators on the entrepreneurship level is discussed, such as the unemployment rate, taxes, tertiary education level, and the ratio of early leavers from formal education. Focusing on the second part of the study, of which the independent variable of the four mentioned is precisely entrepreneurship, there are various expected behaviors with regard to the influence of the variable concerned.

In the first case, the possible effect of the unemployment rate on entrepreneurship does not seem to have a single explanation, even though such a matter has been widely studied at different times and in distinct geographic areas [31]. In short, while the related literature shows two possible effects of unemployment on entrepreneurship, in the research, it has been measured through the proxy of self-employment. On one side, as regarded by some authors [32], the positive influence between both factors occurs when the rise in unemployment causes increased self-employment; in other words, this is what has been called the “refugee effect”. Nevertheless, some cases reported in scholarly journals have noted that the relationship between unemployment and self-employment can also be negative under an effect known as the “Schumpeter effect” [33], thus involving improvement of the performance for entrepreneurship, and at the same time, a reduction in unemployment [4]. That is, according to the “refugee” effect, unemployment can lead to new self-employed persons, while the “Schumpeter” effect rather conveys the fact that new self-employment reduces unemployment. Moreover, the existence of two distinct relationships between unemployment and self-employment, concerning the effects of “refugee” and “Schumpeter” (namely entrepreneurial), has also been reviewed from an empirical point of view [34]. The empirical results of this paper will show which of the two effects prevails, and therefore which one is more relevant at the European level concerning the relationship between unemployment and self-employment.

The analysis of the second variable discussed in the research relating to taxes has led to a large divergence in findings of the literature review. Some authors have even come to affirm that the current economic theory suggests that a country’s tax system may have complex and ambiguous effects on the level of entrepreneurship [30]. From a practical point of view, some empirical studies have verified a lack of unanimity on the issue, contrary to what had been raised from a theoretical perspective. In this sense, earlier works argue that the results obtained showed that, by maintaining the wage tax rate constant, a drop in the individual’s expected marginal tax rate on self-employment income reduced the probability of becoming an entrepreneur, while higher tax rates on self-employment income reduced the probability of ceasing to be an entrepreneur [35,36]. According to findings from several earlier studies (i.e., [8]), higher tax rates leads to a higher rate of entrepreneurial activity, while other studies have shown that a reduction in personal tax rates can cause entrepreneurial activity levels to drop. Nonetheless, other related studies have questioned all these results [37]. There are even those who openly admit the difficulty to achieve a clear consensus about the impact of taxes on self-employment [38], while some recent studies endorse the importance of taxes as a determinant of entrepreneurship [39]. To sum up, findings shown in the related literature on this matter are still far from uniform.

Regarding the educational indicator, most studies up to date have not been conclusive, particularly when it comes to discussing whether the educational level of each individual is determinant to becoming an entrepreneur [40]. However, the existence of a link between the average educational level of a country, which is measured through the indicator of the tertiary education level, and its entrepreneurship level has been widely shown in the literature. For that reason, the education level has been included as the third independent variable in this study. The discussion around the effect of education on economic growth has been extensively dealt with in the related literature for an extensive period [41]. Similarly, there is significant literature on the influence of education on policies for successful self-employment [42]. One of the ways by which education can influence economic growth is through entrepreneurship [8]. The relationship between education and entrepreneurship may be considered in terms of two interrelated pathways: the education of business owners and the average educational level of the local labor market. Both points of view have been analyzed by the literature, which has found significant links between markets with a higher educational level that show more educated entrepreneurs, while they have found a marked association between the education of business owners and the success of small companies [43].

Relevant to the purpose of this study, some authors have recently argued that a higher education level from self-employed persons should improve the growth opportunities of their firms [44]. This is because higher education improves the ability to comprehend market prospects, resulting in better exploitation of the demand on the market. The importance of education in regards to entrepreneurship is also clear when certain authors point out that the effects of education on entrepreneurship may even be more significant than the effect it has on employees. Some authors [45] empirically analyzed the returns to education by entrepreneurs and employees and concluded that they are significantly higher for the former than for the latter. That is, even though investment in education does not specifically seek to achieve results through graduates that become entrepreneurs, greater average education of the population does seem to encourage entrepreneurship.

Lastly, it was considered interesting to include a fourth variable relating to the education level of the population: early school leaving. In the European realm, there has been increasing concern for school drop-out rates among many member states of the European Union (EU). It should also be noted that the Europe 2020 agenda, a sort of common strategy for growth and employment within the EU, includes among its objectives “reducing the school drop-out rate to less than 10%” [46]. There are even various works that address the issue of lifelong learning in connection with early school leavers and entrepreneurship across European countries [47]. Nevertheless, for other geographical areas, a few decades ago, several studies also addressed the phenomenon of work transition of the early school leaver, even analyzing eventual gender differences [48]. Likewise, recent works have reviewed the issue of early school leaving and work outcomes in developing countries [49]. Despite that the current literature does not currently determine how early school leavers may affect entrepreneurship, it has been included in this study via an additional indicator. This can measure the issue of the effects of educational level on the entrepreneurial spirit of the European population. Finally, it should be noted that other socioeconomic and technological variables concerned have not been included in the research, since no significant effects were found during the preliminary test on entrepreneurial activity in the countries reviewed.

As noted in earlier work [50], various studies claim that the contribution to economic growth and well-being derived from female entrepreneurship is different from that resulting from male activity. Furthermore, the numerical or quantitative results of the activity of women entrepreneurs are often different among countries. In this regard, some previous authors [51,52,53,54] have paid attention to the existence of gender differences in entrepreneurial behavior. Based on this fact, the empirical analysis was addressed for this paper from an overall data point of view, taking into consideration data on men and women separately, since it has been considered interesting to verify whether global results remain stable between those data relating to men and women.

3. Empirical Analysis and Results

According to the information currently available, this paper includes an empirical analysis from a large sample of European countries, which is also fairly representative of the geographical, political, and socioeconomic imbalance among regions. Specifically, the research has included the following 31 European countries: Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom. For each of these countries, data have also been collected for the period of 2010–2019, thus analyzing the behavior of variables described in the preceding section from the latest available data within this period.

After having collected the data from the 31 countries concerned for the years 2010 to 2019, the model was defined to address a panel study involving 310 observations. Since the research scope has focused on European countries only, and the majority of them are EU State Members, the data retrieved at any time have been provided from various sources of information through the Eurostat Publications Office of the European Union [55,56,57]. The estimation method used to compile such data has been based on the Ordinary Least Squares through a multiple linear regression model with constant coefficients. Accordingly, it has been assumed that the coefficients calculated are the same for each of the countries included in the sample. Hence,

Table 1. Description of main variables.

Abbreviation	Variable	Description	Source
y	Economic growth	Gross domestic product	[55]
PE	Public expenditure	Total general government expenditure	[55]
I	Investment	Gross fixed capital formation	[55]
HK	Human capital	The proportion of expenditure on education (5 years before)	[55]
EI/δ	Entrepreneurial indicator	Self-employed workers concerning their labor force, 15–64 years old	[55]
UPL	Unemployment	The proportion of the unemployed, 15–64 years old	[55]
TX	Taxes	Percentage of the overall implicit tax rate on capital (2 years before)	[56,57]
EDU	Education	Number of graduates from tertiary education	[55]
ELE	Early school leaving	The ratio of early leavers from formal education, not employed persons, 18–24 years old	[55]

includes a summary description of the variables used in the analysis.

Firstly, the two following hypotheses have been formulated in order to analyze the impact of variables, which were set out in the previous subsection, on the rate of economic growth:

Hypothesis 1 (H1):

Public expenditure, investment, and human capital have positive effects on economic growth.

Hypothesis 2 (H2):

Entrepreneurship has a positive effect on economic growth.

Thus, the equation used to contrast H1 and H2 is as follows:

ln (y)_it = β₀ + β₁ ln (PE)_it + β₂ ln (I)_it + β₃ ln (HK)_it + β₄ ln (EI)_it + ε_it

(1)

Equation (1) corresponds to GDP growth, where the dependent variable (y) is the gross domestic product (GDP), while the independent variables are public expenditure (PE), investment (I), human capital (HK), and entrepreneurship indicator (EI). To define the EI, the study used a reference to the data on the proportion of self-employed workers in each country concerning their labor force. Eurostat provides this data regularly [55].

H1 states that public expenditure, as well as investment and human capital, generate positive effects on economic growth. Besides being been shown in the economic literature, it has traditionally been accepted that the influence of investment [58,59], as well as human capital [60], is usually positive. In contrast, regarding the effect of public expenditure on GDP, even if only intuitively, it is expected that there is a clear positive link. Nowadays, this issue is the subject of controversy in the related literature. Some authors [7] have pointed out that expansive fiscal policies end up negatively affecting economic growth as a consequence of the crowding-out effect that leads to a drop in investment [12], while others have pointed in the opposite direction to defending the positive effects of PE on economic growth through different aspects [13].

H2 proposes that entrepreneurship has a positive effect on economic growth. In this regard, there is extensive literature analyzing the link between both variables [17,61,62,63,64,65,66,67,68]. Indeed, many previous studies have affirmed a clear positive relationship between entrepreneurship for the case of self-employment as a proxy and economic growth [69,70,71,72].

Table 2. Regression results for the GDP equation.

Variable	Coefficient	p-Value
Constant (β0)	1.210	0.000
PE	0.461	0.000
I	0.412	0.000
HK	0.108	0.000
EI	0.139	0.000
R2 (adjusted) = 0.997

Source: Own calculation based on figures provided in [55].

shows a summary of results for H1 and H2. As may be seen, the effect of the three variables compiled in the first hypothesis is positive regarding economic growth. Furthermore, they are significant. That is, public expenditure, investment, and human capital show direct effects on GDP in the group of European countries analyzed during the period of 2010–2019. On the other hand, according to the premise of H2, the fact that the EI shows a positive effect, and the fact that it is significant, supports the idea of a direct relationship between self-employment and economic growth in the countries studied.

Afterwards, a new analysis was performed by adding a pool of input data grouped by gender to validate the differences between males and females with regards to economic variables observed over the analysis period. Findings of the previous literature have highlighted either differences or similarities, depending on each aspect analyzed. Examples of this orientation can be found in some empirical studies with different conclusions, depending on whether the approach was based on economic growth [73] or entrepreneurship [74]. From the intuitive point of view, it might be expected that the relative effect on entrepreneurship is more likely to be linked to men than to women. Nevertheless, in line with similar works concerning other regions of the world [9], in the present study, the analysis of the data discriminating by gender shows that the degree of statistical significance of the results obtained is acceptable both for men and women. The EI variable is the only one where data have been discriminated against by gender in Equation (1). As seen in

Table 3. Regression results for GDP equation—Male.

Variable	Coefficient	p-Value
Constant (β0)	1.191	0.000
PE	0.470	0.000
I	0.409	0.000
HK	0.103	0.000
EI	0.129	0.000
R2 (adjusted) = 0.997

Source: Own calculations based on figures provided in [55].

and

Table 4. Regression results for GDP equation—Female.

Variable	Coefficient	p-Value
Constant (β0)	1.280	0.000
PE	0.464	0.000
I	0.416	0.000
HK	0.100	0.000
EI	0.127	0.000
R2 (adjusted) = 0.997

Source: Own calculations based on figures provided in [55].

, when assessing the influence of self-employment on economic growth, figures obtained are equally significant in all cases. It can therefore be concluded that the contribution of entrepreneurship to economic growth is positive for both genders in the 31 countries reviewed.

Secondly, as anticipated in the previous section and as part of the aims of this paper, once the positive effect of entrepreneurship on economic growth had been confirmed, a key part of the research focused on empirical analysis of the effects from a range of variables regarding the entrepreneurship level. Specifically, the variables examined for the research were unemployment, taxes, formal education level, and the proportion of early school leavers. In this way, the paper aims to show and contrast how these economic and educational factors influence the self-employment level, since this also affects economic growth, and thus the well-being of citizens.

To investigate the effect of unemployment, taxes, educational level, and percentage of early school leavers on national average entrepreneurship, the four following hypotheses were established as follows:

Hypothesis 3 (H3):

Unemployment has a positive effect on entrepreneurship.

Hypothesis 4 (H4):

Taxes have a negative effect on entrepreneurship.

Hypothesis 5 (H5):

Education has a positive effect on entrepreneurship.

Hypothesis 6 (H6):

The early school leaver has some effect on entrepreneurship.

The equation used to contrast these hypotheses is as follows:

ln (δ)_it = β₀ + β₁ ln (UPL)_it + β₂ ln (TX)_it + β₃ ln (EDU)_it + β₄ ln (ELE)_it + ε_it

(2)

Equation (2) is an entrepreneurship equation (δ) that is built with self-employment data. Following the main purpose of the study, variables concerning unemployment (UPL), taxes (TX), educational level (EDU), and early school leavers (ELE) have been included in the analysis.

The variable related to unemployment from the study reflects the proportion of the unemployed people ages 15 to 64 years old in the countries concerned, which raises the highest degree of statistical significance to explain the link with the dependent variable.

The variable concerning taxes, used in research to assess its influence on entrepreneurship, refers to the overall implicit tax rates on capital because the available data show that is the most decisive tax group on becoming an entrepreneur in the European countries. In any case, bearing in mind that the effects of taxes on the decision to become self-employed may not be immediate. In this paper, a time lag of two years has been included in the tax variable.

The independent variable used to measure the educational level of European countries has been the number of graduates from tertiary education in each country. Such a variable was used as a proxy of educational level in the study, as the related literature has shown that the education level has a great influence on expectations to become self-employed [42]. Additionally, the evolution of the number of educated people has shown the most significant influence on entrepreneurship. Similarly, as set out below, in order to extend the analysis to the gender perspective, both overall data and differentiated data on gender have been handled separately in the study.

Finally, the variable from Equation (2) has used key figures concerning the ratio of early leavers from formal education who are unemployed to the total population aged between 18 and 24 years old, to value the effect of early school leaving on self-employment in Europe. In other words, it attempts to measure how many individuals are interested in becoming an entrepreneur, depending on whether the number of early school leavers unemployed is increasing or dropping. Having tested the statistical analysis with different indicators, it has been proven that the selected variable offers a more acceptable level of statistical significance, at least from the perspective of both aggregate data and the male population.

Table 5. Regression results for entrepreneurship equation.

Variable	Coefficient	p-Value
Constant (β0)	1.182	0.000
UPL	0.251	0.000
TX	−0.179	0.000
EDU	0.134	0.000
ELE	−0.148	0.002
R2 (adjusted) = 0.340

Source: Own calculations based on figures provided in [55,56,57].

shows the summarized results of the study, estimated by using Equation (2). As can be seen from the approach regarding H3, unemployment has a positive effect on entrepreneurship and shows a significant direct relationship with self-employment. In line with other works [75,76,77], this shows the important positive influence of the unemployment level on entrepreneurship performance in European countries. Thus, it can be argued that one of the effects observed during the period of 2010–2019 is the increase in the number of individuals looking for a good option to become self-employed.

What has been raised so far is also satisfied in H4. The proportion of overall implicit tax rates on capital in the European countries concerned has a significantly negative effect on entrepreneurship. This result is, in general terms, consistent with the findings of earlier studies in both the European and Latin American cases [8,9]. To sum up, as expected from a point of view of economic logic, it reflects the fact that the greater level of taxation is, the less likely it is that the number of entrepreneurs will be increased due to the existence of weaker incentives for entrepreneurship. Therefore, it could be claimed that the increase in taxes discourages individuals from becoming self-employed. In any case, this broad conclusion must be taken cautiously. This part of the analysis, which uses fiscal variables, makes it necessary to limit the scope of the results within the research framework of the general approach from this study, particularly those relating to a rather heterogeneous set of European countries.

The main issue raised in H5 concerning the positive relationship between education and entrepreneurship also applies to the European countries concerned. As in the variables reviewed so far, the relationship appears to be significantly correlated, and in this case, directly linked as well. Thus, in line with the review of empirical literature [78], the results obtained in the present study show that a higher level of education often has a positive effect on entrepreneurship in a country.

The concern about high levels of school drop-out has been present in EU common policies [46,79,80]. However, that variable has habitually been addressed in studies relating to developing countries [49], while at the European level, the research topic has traditionally been focused on social inequalities of university graduates accessing the labor market [81]. As proposed in H6 from the present paper, this variable has been included in the study to discuss the relationship of the level of early school leaving within the youth population in Europe to entrepreneurship. Statistically speaking, as seen in Table 5, this relationship is negative and significant. Consequently, the larger percentage of the European population aged between 18 and 24 years old who are leaving school prematurely and are not employed, the less likely the propensity for entrepreneurship, measured in terms of self-employment levels in the European countries concerned. This negative relationship could therefore be considered consistent, despite the impact of the high level of early school leaving on the European economy, in addition to the harmful effect on entrepreneurship.

The analysis of Equation (2) concludes with the evaluation of results from gender-disaggregated data, thereby showing the results concerning men and women, respectively, in

Table 6. Regression results for entrepreneurship equation—Male.

Variable	Coefficient	p-Value
Constant (β0)	1.541	0.000
UPL	0.246	0.000
TX	−0.127	0.002
EDU	0.128	0.000
ELE	−0.195	0.000
R2 (adjusted) = 0.311

Source: Own calculations based on figures provided in [55,56,57].

and

Table 7. Regression results for entrepreneurship equation—Female.

Variable	Coefficient	p-Value
Constant (β0)	0.892	0.000
UPL	0.280	0.000
TX	−0.242	0.000
EDU	0.136	0.000
ELE	−0.099	0.020
R2 (adjusted) = 0.353

Source: Own calculations based on figures provided in [55,56,57].

. Besides the dependent variable, there also are independent variables whose data have been obtained against by genders from Equation (2). When reviewing the coefficients relating to the variables of unemployment, education, and early school leavers, in addition to their influence on entrepreneurship, it can be concluded that the above assumptions are met according to the working hypothesis generally accepted. Moreover, the degree of significance is almost always valid in absolute terms for such cases.

In summary, in comparison with the results of analysis based on gender differentiation, it could be argued that the impact of the factors concerned, such as unemployment and level of education, on entrepreneurship level is more intense in females than in males. However, in the case of the variable relating to early school leavers, the effect is greater on the male population. This latter finding is also in line with other studies showing that certain aspects concerning entrepreneurship are sometimes, so to speak, less adequate for women than for men [74].

4. Conclusions

The main purpose of the research was to provide new empirical evidence regarding the impact of some socioeconomic factors on entrepreneurship and verify the positive effect of self-employment on economic growth in a wide range of European countries during the last decade. To achieve this objective, several scenarios have been tested by analyzing the available annual data provided by Eurostat, and then disaggregated by gender. Since certain previous works have found some gender inequalities in the field of entrepreneurship, this study aimed to verify whether the behavior of the chosen variables was different between men and women.

The first conclusion of the present work, according to empirical evidence obtained from the data analysis of 31 European countries over the past decade, is that public investment still has a positive effect on economic growth in the geographical area examined. By studying the influence of public expenditure, investment, and human capital on economic growth from 2010 to 2019, a clear and significant effect has been noted among them. Similarly, considering self-employment a related indicator, a positive impact of entrepreneurship on economic growth has been observed from this research. Hence, results obtained in this empirical work add to the large findings of the previous studies, either theoretical or practical, which further demonstrate the relevance of public policies on development and its economic growth of a given area.

In the second place, focusing on the analysis of the factors affecting entrepreneurship, similar results have also been found in the related literature, particularly in the case of the variables analyzed in this study: unemployment, taxes, education, and early school leaving. As stated in the previous section, the multiple regression model used in the study has confirmed that the influence of these variables on self-employment as a proxy of entrepreneurship is statistically significant.

Considering the variables separately, it can be concluded that the behavior of unemployment in Europe over the last decade, besides its link with entrepreneurial development, could be categorized within what some authors have called the “refugee effect” [25]. This is because the highest proportion of the unemployed seems to be an incentive for entrepreneurship in many European countries. Thus, the impact of high unemployment rates of the population aged between 15 and 64 years old has an increasing effect on self-employment in the case of both aggregate data and those differentiated by gender. Following the push-pull theory, it can be said that unemployment is shown as a “push” factor for European entrepreneurship. Nonetheless, the differentiation of variables, whether or not they are considered as pull or push factors, has not been the subject of this paper due to the certain ambiguity of such terms [82]. Moreover, that would have forced us to distinguish between opportunity and necessity entrepreneurship, while a single indicator has been used to measure it throughout the study, regardless of the motivation of those who choose self-employment.

Furthermore, the results of this research suggest that the relationship between taxes and entrepreneurship is inverted, which inevitably provides additional empirical evidence to the controversy, either theoretical or empirical, in the discussion about that variable. Indeed, the impact of the overall implicit tax rate on capital is significant and positive, when addressing the issue both from a general approach and from gender differentiation.

Finally, a positive link between education and entrepreneurship has been observed in the study, which largely coincides with the results obtained in other theoretical and empirical articles in this research field [66]. Statistically speaking, high national standards for education reflect a positive and clear influence on entrepreneurship levels, thereby reinforcing the importance of implementing active educational policies to strengthen the economy of any geographical area. In the same vein, the relationship between the early school leavers and entrepreneurial activity figures is statistically significant. This also seems to be in line with the harmful effect that early school leaving has on the European economy, which fully justifies the concern of the European institutions to reduce the number of school leavers, especially those outside the labor market and aged between 18 and 24 years old. The variable related to early school leaving is the only one in which certain differences between men and women have been detected, and whose impact is even greater if the range of individuals examined belongs to the segment of the male population.

In summary, findings on the results of this study enforce the conclusions from related studies in this research field, besides underlining the key role of the public sector in promoting entrepreneurship at the European level. If variables with a positive effect are used as catalysts for entrepreneurship and the impact of variables with negative influence is reduced, it will be positive not only for entrepreneurial activity but also for economic growth. Indeed, from the European institutions, as well as from the private sector, many efforts have been made to boost the citizens’ entrepreneurial spirit, for instance, by boosting entrepreneurship training, by conveniently channeling more access for funding to entrepreneurs, or even by fighting against existing bureaucratic obstacles for start-ups.

Nevertheless, in such a time as now, when most countries are being ravaged by the COVID-19 pandemic, it appears to be the right moment to take advantage of the negative evolution of some economic variables, such as the rise of the number of jobless workers. This would help to deal with unemployment toward new business fields, particularly those based on sustaining innovation and disruptive technologies, along with the importance of public policies to promote the training and educational improvement of European citizens. However, it should not be forgotten that a great disparity remains among the European countries. For that reason, it would be pretty interesting to focus future research on similarities and differences among various countries in the field of entrepreneurship by analyzing which factors have experimented with the most profound changes since the Great Recession. In fact, this could serve to better cope with the next worldwide crisis derived from the effect of the coronavirus on the enterprise activity in the global economy.