A MACRO PERSPECTIVE ON FEMALE ENTREPRENEURSHIP IN
RELATION TO FINANCING BUSINESSES: DO THE LEVELS OF
EDUCATION AND HIGH-TECH INDUSTRY MATTER?
BY
Hylkje Terpstra S2729474
University of Groningen Faculty of Economics and Business
MSc Business Administration Small Business & Entrepereneurship
Supervisor: Dr. S. Murtinu Co-assessor: Dr. F. Noseleit
Abstract
This research investigates at a macro level if female entrepreneurship and the type of financing used to start and maintain firms are correlated and if this relation is moderated by the level of education and the level of high-tech industry. Female entrepreneurship is defined as “women
TABLE OF CONTENT 1. Introduction 3 2. Literature review 6 2.1. Female Entrepreneurship 7 2.2. Types of Financing 8 2.2.1. Debt Financing 9 2.2.2. Equity Financing 10
2.2.3. Alternative ways of Financing 11
2.2.4. Level of Education 12
2.2.5. Level of High-Tech Industry 14
3. Methodology 16 3.1. Sample 16 3.2. Measurement of Variables 16 3.2.1. Dependent Variables 16 3.2.2. Independent Variables 17 3.2.3. Control Variables 17 3.3. Regression Model 18 4. Results 20 4.1. Debt financing 22 4.2. Equity financing 24
4.3. Alternative ways of Financing 26
1. A macro perspective on female entrepreneurship in relation to financing businesses: do the levels of education and high-tech industry matter?
Entrepreneurial ventures are important generators for economic growth. For those ventures, financial resources are the most important necessities to establish and subsequently grow (Cassar, 2004). Due to the fact that entrepreneurs often have limited personal resources, they are forced to find external financing (Carpenter and Petersen, 2002). Examples of external financial resources that have been intensively studied in previous research are the traditional debt and equity start-up funding from family, friends, angel investors and vengure capitalists (Shane, 2009; Bruton et al., 2015). Godfred, Bokpin and Twerefou (2012) stated that new ventures have a strong preference for using personal, bootstrap and informal sources of finance. They found that the use of external traditional debt finance, such as formal bank loans, arises more frequently and is preffered more when the business is up and running. Next to that, Bruton et al. (2015) found that besides the traditional set of financing options, a set of rather new sources of financing has emerged in the entrepreneurial field. The new approaches to entrepreneurial financing found by Bruton et al. (2015) are funding through microfinance, crowdfunding, peer-to-peer lending and other financial innovations. These new and developing phenomena need to be explored given the practical importance of entrepreneurial ventures for modern economies as well as their importance for developing economies (Bellavites, Filatotchev, Kamuriwo and Vanacker, 2017).
operation (Alam, Hoque, Khalifa, Siraj, & Ghani, 2009), the difficulty to raise adequate finance is a problem for start-ups as well as mature firms.
Previous research on financing entrepreneurial firms has mainly focused on the individual perspective of the investor, the principal in the principal-agent relationship according to the agency theory (Jenson and Meckling, 1976). Taking into account that the rate of entrepreneurship differs considerably across countries, (Wennekers, Uhlaner, and Thurik, 2002) this research will take a macro perspective and look into the use of alternative financing methods compared to the traditional debt and equity funding and will investigate the influence of female entrepreneurship on these concepts.
Adding to this, there are some inconsistencies in the current literature about the effect of the level of education on being entrepreneur and the effect of educational level on the financing method of the enterprise. On the one hand, Allen, Langowitz and Minnitti (2007) found that less educated women are more likely to start a business, they also found that in developed countries female entrepreneurs have enjoyed a higher education level then their male counterparts. Gebru (2009) found that small and medium enterprise owners’ financing preference depends on the level of their education.This research will add to the debate in the current literature and will study the possible moderating effect of the educational level of the entrepreneur on the relation between female entrepreneurship and the use of new financing methods.
Combining all the aspects as mentioned above, this research is pointed at giving a macro perspective in examining the relationship between female entrepreneurship and different types of funding to start and maintain their business. It adds to previous literature not only new types of business funding, but also the moderating effects level of education and level of high-tech industry. This flows in the following research questions:
RQ1: To what extent does Female Entrepreneurship influence the type of financing choosen to start and maintain firms?
RQ2: How does the level of education influence the relation between female entrepreneurship and the type of financing for their business?
2. Literature Review
When starting a new business, acquiring resources is a critical element (Aldrich, 2002; Brush and Chaganti, 1999; Landstorm and Johannisson, 2001). It is important for the firm that the entrepreneur is able to collect and combine resources that are a necessary, to enable the firm’s existence and achieve the desired degree of growth. To accomplish growth, financial resources are crucial. This is the most essential and flexible type of resources, since it can be used to acquire other types resources (Cooper, Gimeno-Gascon and Woo, 1994). Next to financial resources, Marlow and Patton (2005) suggest that resources as previous experience, networks gained from earlier employment and education helped female entrepreneurs develop their own businesses.
who applied for a bank loan, mostly had limited education and experience in the area they wish to operate in and suggested low personal equity compared to male business owners that were seeking finance. This in combination with the fact that banks are risk averse, makes that employees at a bank are not discriminating, but that the socialisation and work-related experiences have disadvantaged women compared to men seeking finance.
2.1. Female Entrepreneurship
Although growing rates of new venture creation by women, entrepreneurship in general is still a male-dominated activity in the twenty-first century (Reynolds, Bygrave, Autio, Cox and Hay 2003). In the past, Cliff (1998) found that women create ventures to a lesser degree compared to men, and that the women who do succeed in creating a business accomplish less growth than male entrepreneurs. Cultural and social norms can be seen as an explanation for this gender difference, since women traditionally carry more of the domestic responsibilities such as taking care for the children and housekeeping (Foxcroft et al., 2002). More recent research from the Census Bureau Statistics in the United States declares that the number of women-owned firms has grown faster than men-owned firms in the time frame form 1997 until 2002. However, the relative importance of women-owned firms in terms of employment and sales has decreased over this time (Coleman and Robb, 2009).
(OECD, 1998; Van Praag, 1999; Lumpkin and Dess, 1996), in this research the definition of Heilman and Chen (2003) will be used when describing female entrepreneurship, in combination with the addition of Chell and Baines (1998).
It is widely known that women-owned firms continue to struggle on different aspects of entrepreneurship. Looking at performance, several studies show that women-owned firms are more likely to fail, along with having lower profit, sales and employment rates (Rosa et al., 1996; Robb, 2002; Watson, 2002). Also, Lee and Deslow (2004) found that acces to capital in the early stages of developing a firm is often mentioned as a problem for female entrepreneurs. This might be related to suggestions from Menzies, Diochon and Gasse (2004) and Sexton (1989) that among female entrepreneurs a lower popensity to grow their business is implied.
Taking the resource-based view in mind, various studies stated that female entrepreneurs have less years of experience in the industry they work in or manegerial roles they fulfill compared to male entrepreneurs (Carter, Williams, & Reynolds, 1997; Boden and Nucci, 2000; Fairlie and Robb, 2009). From this, Coleman and Robb (2009) assumed that female entrepreneurs have lower levels of human capital than male entrepreneurs. Next to this, several studies found that men tend to have more backgrounds and experience in business, whereas women are more highly educated, but their education is less related to business management (Clifford, 1996; Scott, 1986; Stevenson, 1986; Watkins and Watkins, 1984).
2.2. Types of Financing
Funding is crucial for business survival as well as business growth. The funding gap, as mentioned by Brush, Carter, Gatewood, Green and Hart (2004), obstructs growth of women-led businesses. Alsos, Isaksen and Ljunggren (2006) confirm that the difficulty for women to find financial capital restricts the early growth of their company. Orser et al. (2000) studied over 1000 firms in Canada and found that the access to capital was the biggest concern for women business owners.
sources of debt and equity for their start-up capital as well as neccesary follow-up investments. This might arise from the fact that women have a higher level of risk aversion, devotion towards smaller firms that allow for work and familky balance, and the desire to maintain control over the firm. These motives fit with smaller firms, requiring less financing that can be collected from personal sources instead of external sources. Also, the higher levels of risk aversion from female entrepreneurs lead to mostly preferred lifestile types of businesses to balance family and business demands and to avoid dependence on external sources of capital (Constantinidis et al., 2006)
Coleman and Robb (2009) found that women, compared to men, begin their businesses with less financial capital and collect lower amounts of debt and equity in the first two years. Alsos, Isaksen and Ljunggren (2006) state that the amount of money raised to start a business depends upon the wishes, perceptions and behavior of the entrepreneur, next to structural factors of the financial market. Thus, differences in raising start-up financing and funding for growth may be related to differences in these perceptions, behavior towards funding and business growth and in barriers that are structural in the financial markets. One of these barriers might be the fact that female entrepreneurs experience credibility problems when dealing with bankers (Schwartz, 1976; Hisrich and Brush, 1984; Carr, 1990; Carter and Cannon, 1992).
In this research we will focus on three methods of financing: debt financing, equity financing and alternative ways of financing.
2.2.1. Debt Financing
granting loans, but they state that women were less satisfied with their banking relationships. Walker and Joyner (1999) found compromosing evidence, in their research they found that women continuously felt that they are discriminated against in their attemts to secure funding by banks. From this, we expect a negative influence of female entrepreneurship on the use of debt financing, which concludes in our first hypothesis:
H1a: Female entrepreneurship is negatively correlated with the use of Debt Financing
2.2.2. Equity Financing
Between 1953 and 1998, less than 5 % of venture capital funding went to women-owned firms. This low level was found to be partially because of the small amount of women that are employed in the venure capital industry. Also, it is claimed that the businesses women start, are in sectors that are not attractive for external equity providers. (Brush, Carter, Gatewood, Greene and Hart, 2001). From the angel investors that were investigaged by Becker-Blease and Sohl (2007) only 9% of the proposals the investors received were from women, compared to 91% from men. However, women tend to apply more for funding to networks that include a higher proportion of women angel investors. This might be the reason of the female entrepreneurs’s unwillingness to apply for external equity (Coleman and Robb, 2009).
Three factors are found to try and explain why women face difficulties in raising equity funding. The first problem is the structural barriers women experience when applying for equity capital. Second, women strategically choose not to use this type of financing. Third, women do not posses the neccessary knowledge and capabilities to acquire equity capital (Green, Brush, Hart and Saparito, 2001). From these results of previous studies, the following hypothesis is conducted:
2.2.3. Alternative ways of Financing
Next to the traditional methods to finance a firm as mentioned above, there are alternative ways of financing. Amongst this we find micro financing, crowdfunding and peer-to-peer lending, but also all that is not debt- or equity financing. Looking at the three new methods of financing for entrepreneurial activities combined, Bruton et al. (2015) found that “previous literature has shown that the institutional environment for microfinance, crowdfunding, and peer-to-peer lending has had significant effects on the origin, diffusion and adoption of these new financial alternatives for seeding entrepreneurship in developed and developing economies.”
relationship and make this type of financing more attractive to female entrepreneurs. Chen, Li and Lai (2017).
All in all, we see that the alternative ways of financing might be a way to decrease the agency problem that a lot of female entrepreneurs want to go out of the way (Morris et al., 2006). Therefor, alternative ways of financing might be attractive to women-business owners. This leads us to the following hypothesis:
H1c: Female entrepreneurship is positively correlated with the use of alternative ways of financing
2.3. Level of Education
female entrepreneurs with a higher level education have more interest in growing their business, compared to lower educated female entrepreneurs, we assume that Collins (2003) indirectly suggests that insufficient education moderates the effect of entrepreneurship on the use of external financing.
Looking into the individual perspective of the level of education from the entrepreneur to be able to make a distinction between the different financing methods, Gebru (2009) found that small and medium enterprise owners’ financing preference depends on the level of their education. He states that owners who have enjoyed higher education are in a better position to understand the link between finance and firm value. As opposed to the higher educational background, Gebru (2009) states that small and medium enterprise owners with a lower eductional background are found to closely follow the descriptions of the Pecking Order Hypothesis, which excludes all internal financing source possibilities and also excluding alternative ways of financing as mentioned in this research. This leads to try funding businesses externally through the established and traditional ways of financing a firm. This leads us to the next hypothesis, were a high level of education therefor strengthengs the negative relation between female entrepreneurship and debt financing.
H2a: A higher level of education strengthens the relation between female entrepreneurship and debt financing.
Since Carter et al. (2003) found that having a graduate education in any field was a significant predictor for firms’ ability to secure equity financing, we expect that a high level of education weakens the negative relation between female entrepreneurship and equity financing. This is also stated in the next hypothesis:
Coming back to the Pecking Order Hypothesis, Gebru (2009) finds that a higher level of education enables the entrepreneur to look further that the Pecking Order Hypothesis and is therefor able to see alternative ways of financing next to the traditional debt and equity financing. This leads to the next hypothesis:
H2c: A Higher level of education strengthens the relation betweeen female entrepreneurship and alternative types of financing.
2.4. Level of High-Tech Industry
In the late 20th century and early 21st centure, the most significant explanation for growing entrepreneurial oppurtunities is a change in technology. Wennekers, Uhlaner and Thurik (2002) state that “in any era, new technologies have the potential to lead to new goods and services, creating opportunities for start-up of new firms.” Since most women-owned firms are in the service- and retail sectors (Kalleberg and Leicht, 1991; Loscocco et al., 1991; Anna et al., 1999; Du Rietz and Henrekson, 2000), previous literature of female entrepreneurship on the type of financing to start and maintain their business have mainly focussed on these industries. However, we find that female entrepreneurship also includes the fact that women are able to break out of domains they traditionally are allocated to (Chell and Baines, 1998). In the last decade, female entrepreneurs chose to set up new ventures in growth sectors such as technology and manufacturing (Morris et al., 2006).
Gompers and Lerner (2001) found that banks are incapable to finance innovative and high-tech firms appropriately. Equity financing, preferably in the form of venture capitalists, on the other hand, has shown to be a admirable option to finance high-tech start-ups. From this we derived the following hypothesis:
H3a: The level of high-tech industry strengthens the correlation between female entrepreneurship and debt financing.
Lastly many high-tech firms, especially small firms, face asymmetric information problems and a lack of collateral, and are likely to be confronted with financing constraints (Carpenter & Petersen, 2002). Since we discussed before that alternative ways of financing might help to avoid agency problems, we assume the level of high-technology industry in a country positively moderates the effect of female entrepreneurship on the use of alternative ways of financing. This is also stated in the following hypothesis:
3. Methodology 3.1. Sample
In this research, a sample is conducted by combining data from two existing databases, namely the OECD database and the EUROSTAT database. From these databases, data from 14 countries is collected over the timeframe of four years, 2010 untill 2013. The countries included in this study are Belgium, Denmark, Finland, France, Germany, Italy, Latvia, Luxembourg, The Netherlands, Poland, Slovak Republic, Spain, Sweden and the United Kingdom. This panel data set leads to a total of 56 observations taken into account in this study. Because the data is collected with regards to a macro perspective and therefor country-specific, there is no self-selection bias in the data collected for this research.
3.2. Measurements of Variables
3.2.1. Dependent Variables.
3.2.2. Independent Variables.
Female Entrepreneurship is, as in line with research of Heilman and Chen (2003), conducted by combining two variables from the OECD database (OECD, 2018), namely self-employed females with employees and self-employed females without employees in a country as a percentage of total employment of that country. Level of education (TEREDU) is operationalized by taking the share of the total population of a country in the age range of 25-64 that has received tertiary education (OECD, 2018). This is in line with the measurements used in the study from Wennekers, Stel, Thurik, and Reynolds (2005). The final independent variable is the level of high-tech industry (TECHIND). This is measured by using the variable “Employment in high- and medium-high technology manufacturing sectors and knowledge-intensive service sectors” from the EUROSTAT database. This variables measures the employment in these sectors as a percentage of total employment in a country.
3.2.3. Control Variables.
only data of the year 2013 was available trhough the OECD database. To complete the dataset, the Next Observation Carried Backward (NOCB) method is used, where the value of 2013 is used as an estimate for the values of 2010, 2011 and 2012.
3.3. Regression Model
To test the relation between Female Entrepreneurship and Type of Financing, three linear regressions are performed based on a panel data set conducted with the 14 countries mentioned before, for the period 2010-2013. Every regression performed, has a different Type of Finance as dependent variable, to be able to compare the different effects between Female Entrepreneurship and Type of Finance. In all three models, also the moderating effects will be tested individually. Due to the relatively low number of observations, the full model including both moderating effects tested at the same time will not be included in this research, since this gives unreliable results because the criteria to perform the regressions are at the minimum requirements.
In table 1, all the variables used in the regressions are described.
TABLE 1
Description of Variables
Name variable Proxy Measurement
DEBTFIN Enterprises seeking debt financing Percentage of enterprises seeking debt financing of total business economy except financial and insurance activities
Name variable Proxy Measurement
OTHERFIN Enterprises seeking other financing options
Percentage of enterprises seeking other financing options of total
business economy except
financial and insurance activities
FEMENT Female Entrepreneurship Self-employed females with
employees + self employed females without employees as a percentage of total employment
TEREDU Tertiary education Percentage of the population of
25-64 year-old that has tertiary education as highest level of education completed
TECHIND Level of high-tech industry Percentage of employment in
high- and medium-high
technology manufacturing sectors and knowledge intensive serive sectors of total employment. SMSIZE Small- and Medium sized enterprises Percentage of small- and medium
sized manufacturing enterprises out of total manufacturing enterprises
ACTRAINING Access to training on how to start a business
The percentage out of total women in a country, who have declared that they have access to training to start or grow a business
4. Results
TABLE 2
Descriptive Statistics Variables
Variable Mean SD 1 2 3 4 5 6 7 8 9 1. DEBTFIN 31.700 8.921 - 2. EQUITYFIN 5.229 3.209 0.261 * - 3. OTHERFIN 26.279 9.277 -.097 *** 0.412 *** - 4. FEMENT 8.948 2.996 0.229 * -0.342 ** 0.012 - 5. TEREDU 30.92 7.31 -0.443 *** 0.262 * -0.320 ** -0.622 *** - 6. TECHIND 4.798 2.449 0.319 ** -0.356 *** -0.060 0.081 * -0.494 *** - 7. SMSIZE 98.912 1.027 0.279 ** -0.300 ** -0.171 0.337 ** -0.215 0.267 ** - 8. ACTRAINING 43.754 17.661 -0.205 ** 0.176 -0.412 *** -0.537 *** 0.784 *** -0.240 * -0.111 - 9. ACMONEY 26.177 10.305 -0.613 *** 0.266 * -0.517 *** -0.745 *** 0.749 *** -0.334 ** -0.571 *** 0.645 *** -
4.1 Debt Financing
In table 3, the regression results with debt financing (DEBTFIN) as dependent variable are presented. The first column only includes the effect of the control variables on debt financing, where Small- and Medium sized enterprises shows a positive correlation with debt financing, with a significance level under 5%. Access to trianing shows also a positive correlation, but is not found to be significant. Acces to money on the other hand has shown a negative correlation, with a significance level under 5%. The second column includes the independent variable female entrepreneurship and the control variables. Firstly, looking at the control variables the results of SMSIZE and ACMONEY stay the same, but slightly increase and meet a significance level of under 1%. Access to training shows now a negative correlation, but is still not significant. The results show also that Female entrepreneurship is highly significant, negatively correlated with debt financing. Column 3 provides results with female entrepreneurship and the first moderator, level of education, included. The control variables show the same results as in the first column. Female entrepreneurship now shows a more negative, still highly significant correlation with debt financing. Looking at direct effect of the level of education, we find a negative correlation between TEREDU and debt financing, with a significance level under 1%. The moderating effect of FEMENTxTEREDU shows a positive effect, with also a significance level under 1%. The last column shows the results of the regression which includes next to the control variables and female entrepreneurship, the second moderator, the level of high-tech industry. Here, the correlations of the control variables show the same directions as in the first and third column. Female entrepreneurship is less negatively correlated as with only keeping level of education as moderator in perspective, but more negatively correlated as testing only female entrepreneurship as independent variable. High-technology industry on its own does not show a significant direct correlation with debt financing, but as a moderator has a positive effect, with a significance level under 10%.
TABLE 3
Regression Results “Debt Financing”
Variable (1) (2) (3) (4) Constant -354.742** -388.150** -270.612 -414.328** SMSIZE 3.993** 4.523*** 3.690** 4.803*** ACTRAINING 0.006 -0.025 0.007 0.008 ACMONEY -0.375** -0.608*** -0.596*** -0.4005** FEMENT - -1.291*** -4.361*** -2.950** TEREDU - - -1.285*** - FEMENTxTEREDU - - 0.116*** - TECHIND - - - -2.580 FEMENTxTECHIND - - - 0.430* Adjusted R-square 0.415 0.499 0.560 0.554 F-value 13.041*** 13.687*** 11.813*** 11.547***
4.2. Equity Financing
Concluding the results from table 4 with regards to the conducted hypothesis linked to equity financing (H1b, H2b, and H3b), only H3b is significantly supported. No proof is found for H2b, and H1b is only supported when taking the moderating variable high-tech industry into account.
TABLE 4
Regression Results “Equity Financing”
Variable (1) (2) (3) (4) Constant 169.642** 162,550** 170.508* 104.316 SMSIZE -1.672** -1.559* -1.584* -0.830 ACTRAINING 0.031 0.024 0.012 0.027 ACMONEY -0.017 -0.067 -0.076 -0.036 FEMENT - 0.274 -0.863 -1.890*** TEREDU - - -0.177 - FEMENTxTEREDU - - 0.023 - TECHIND - - - -2.983*** FEMENTxTECHIND - - - 0.321*** Adjusted R-square 0.094 0.107 0.098 0.285 F-value 2.764* 2.528* 1.927* 4.391***
4.3. Alternative ways of Financing
Lastly, table 5 shows the results of the regressions performed with alternative ways of financing (OTHERFIN) as dependent variable. The first column includes the effects of the control variables on alternative ways of financing. Small- and Medium sized enterprises shows a negative correlation with equity financing, with a significance level under 5%. Access to trianing shows a positive correlation, but is not found to be significant. Acces to money on the other hand has shown a negative correlation, with a signficance level under 1%. The second column shows the independent variable, female entrepreneurship and the control variables. Firstly, looking at the control variables the direction of the results stay the same, only SMSIZE is found to be a bit less negatively correlated. Next to this, the results show that Female entrepreneurship has a negative correlation with alternative ways of financing, and is found the have a significant level under 1%. Column 3 provides results with the independent variable female entrepreneurship and the first moderator, level of education, included. The control variables show the same results as in the second column. Female entrepreneurship now shows more negative, but a bit less significant correlation with alternative ways of financing. Looking at direct effect of the level of education, we find a negative correlation between TEREDU and alternative ways of financing, but this relation is not found to be significant. The moderating effect of FEMENTxTEREDU shows a positive effect, but is still not significant. The last column shows the results of the regression which includes next to the control variables and female entrepreneurship, the second moderator, the level of high-tech industry in a country . Here, the correlations of the control variables show the same directions as in the previous columns. Female entrepreneurship is more negatively correlated as compared to the third column, but shows the same significance level. High-technology industry as a direct independent variable on alternative ways of financing shows a negative correlation, but is not found to be significant. The moderating effect FEMENTxTECHIND shows a positive effect, but is not found to be significant.
TABLE 5
Regression Results “Alternative ways of financing”
Variable (1) (2) (3) (4) Constant 387.866** 350.690** 380.249** 318.382** SMSIZE -3.541** -2.950** -3.145** -2.559* ACTRAINING 0.010 -0.025 -0.024 -0.015 ACMONEY -0.505*** -0.764*** -0.766*** -0.696*** FEMENT - -1.437*** -2.387** -2.584** TEREDU - - -0.365 - FEMENTxTEREDU - - 0.036 - TECHIND - - - -1.989 FEMENTxTECHIND - - - 0.255 Adjusted R-square 0.310 0.484 0.474 0.479 F-value 8.652*** 12.975*** 8.668*** 8.827***
5. Discussion 5.1. Findings
In this research, the goal was to take a macro perspective, while examining whether female entrepreneurship was in relation with the type of financing used, and if this was moderated by the level of education and high-tech industry. To answer the three main research questions, several hypothesis were conducted. It is important to keep in mind that from the regression results causations can not be established, only correlations, because of a limited number of observations.
The first hypothesis was divided into three to be able to compare the three different types of financing. H1a stated that Female Entrepreneurship is negatively correlated with the use of Debt Financing. From the given results, this hypothesis can be supported. This means than Female Entrepreneurship and the willingness to seek debt financing for funding a firm are negatively correlated. When taking a macro-perspective this implies that when a country has a high level of Female Entrepreneurs as percentage of total employment, the willingness to seek debt financing to fund firms is low. This finding is in line with the findings from previous studies (Walker and Joyner, 1999; Fabowale et al., 1995).
H1b stated that Female Entrepreneurship is negatively correlated with the use of Equity Financing. Concluding from the results this hypothesis is rejected when only looking at the regression including female entrepreneurship and equity financing. However, when taking high-technology industries into account as moderating variable, the correlation between female entrepreneurship and equity financing shows a significant effect that supports H1b, so when female entrepreneurs operate in a country where the level of high-tech industry is high, the women tend to be unwilling to seek equity financing, which is thus strengthened by the level of high-tech industry.
bear risks that are known. Another explanation might be that since alternative ways of financing are relatively new, and not researched very often, these might have restrictions or barriers faced by women that have not yet been revealed.
To answer the first research question, to what extent does female entrepreneurship influence the type of financing choosen to start and maintain their business, we combine the results of the previous mentioned hypothesis and see that all methods of financing are negatively correlated with female entrepreneurship. For debt- and equity financing, this is in line with previous literature and therefor we conclude that Female entrepreneurship is negatively correlated with the willingness to seek debt and equity financing. Alternative ways of financing, on the other hand has shown different results then expected from previous literature. Explanations for this might be unrevealed barriers that women face when seeking this kind of finance, or the perception of a greater risk when choosing this type compared to the traditional methods of financing.
Second, we looked into the moderating effect of the level of education in a country. From previous literature, several hypothesis were conducted to answer the second research question. H2a stated that a higher level of education strengthens the relation between female entrepreneurs and debt financing. The results support this hypothesis and are in line with previous literature, which means that the negative correlation between female entrepreneurship and debt financing, is strengthened by a high level of education in a country. So when female entrepreneurs live in a country with a high level of education, their willingness to seek debt financing decreases even more, compared to when the level of education was not taken into account.
H2b stated that a higher level of education weakens the relation between female entrepreneurship and equity financing. The results give no significant proof, so this hypothesis can not be supported. The small number of observations in performing these analysis might be the reason that the proof found is not significant.
support this hypothesis, also this might depend on the small number of observations for the regression, which can lead to unreliable results.
To answer the second research question, how does the level of education of the entrepreneur influence the relation between female entrepreneurship and the type of financing for their business, we look back at the hypothesis and see only for female entrepreneurship on debt financing significant proof found to support the hypothesis. Concluding on this fact, we find that the level of education has significantly proven moderating effect of the correlation between female entrepreneurship and the willingness to seek debt financing, it strengthens the negative correlation.
Third, the moderating effect of the level of high-tech industry was examined. To do this, hypotheses were conducted from previous literature, as can be seen in the literature review of this paper. H3a stated that a high level of high-tech industry strengthens the correlation between female entrepreneruship and debt financing. The results support this hypothesis, that the level of high-tech industry strengthens the negative correlation between female entrepreneurship and the willingness to seek debt financing.
H3b stated that a high level of high-tech industry weakens the correlation between female entrepreneurship and equity financing. The results show opposite significant effects compared to what was expected, so H3b is also rejected. The results suggest that operating in a high-tech industry not only strengthens the negative correlation between female entrepreneurship and their willingness to seek equity financing, but can be seen as a requirement for the correlation, because without the high-tech industry variable included, the correlation between female entrepreneurship and the willingness to seek equity finance is not found to be significantly verified.
observations that restricts the reliability of this research, since the results found are positive (in the expected direction) only not found to be significant.
To answer the last research question, how does the level of high-tech industry in a country influence the relation between female entrepreneurship and the type of financing for their business, again only one hypothesis is confirmed, namely the strengthening effect of high-tech industry on the negative correlation between female entrepreneurship and the willingness to seek debt finance. Concluding from this, we find, except for the moderating effect of high-tech industry on the correlation between female entrepreneurship and debt financing, no evidence that suggests that high-tech industry influences the relation between female entrepreneurship and the type of financing for their business.
To conclude the findings of this research, which adds to existing literature by taking a macro-perspective instead of researching the individual unit of analysis and in this perspective take the motives of the entrepreneurs in different countries that drive them to the specific decision of which financing type to use, we find that female entrepreneurship is negatively correlated with all types of financing mentioned in this research. The negative correlation between female entrepreneurship and the willingness to seek debt financing is strengthened by the level of education and the level of high-tech industries as moderating variables.
5.2 Theoretical Implications
Next to this, it is important to mention the operationalization of the dependent variables, since these are measured by firms that seek a particular source of finance instead of having actually acquired this type of finance. This is of importance when interpreting the results, they are pointed to the willingness to search a certain type of finance. Finally, it is important to keep in mind that entrepreneurs often gather funding from multiple sources (Hanssens, Deloof, and Vanacker, 2015). This is not included in this research.
5.3. Limitations
First of all, the dataset used for this research can be seen as a limitation, since the gathered database only includes data from 14 specific countries from 2010 until 2013, this leaves out a lot of other insights and might not be a reliable comparison for the reality of averages for the variables used. Also, the low number of observations leads to several limitations. First, controlling for country and year was not possible, since the amount of dummy-variables as regressors were not covered by enough observations to meet the regression criteria. In general, the number of obstervations meets the criteria of performing an analysis through regressions by a very small margin. Because of this, the results from this study might be a misleading representation of the reality, and when interpreting the relations found this should be taken into account.
5.4. Policy Recommendations
interesting for existing firms to attract. This improves their socio-economic positions (Audretsch and Thurik, 2000), and eventually will increases welfare in a country.
5.5. Further Research
6. References
Alam, G. M., Hoque, K. E., Khalifa, M. T. B., Siraj, S. B., & Ghani, M. F. B. A. (2009). The role of agriculture education and training on agriculture economics and national development of Bangladesh. African Journal of Agriculture Research, 4(12), 1334-1350.
Aldrich, H. E. (2002). Organizations Evolving. London: SAGE Publications.
Allen, E., Langowitz, N., & Minniti, M. (2007). The 2006 Global Entreprenership Monitor Special Topic Report: Women in Entrepreneurship. Center for Women Leadership, Babson College. Babson Park, MA.
Alsos, G. A., Isaksen, E. J., & Ljunggren, E. (2006). New Venture Financing and Subsequent Business Growth in Men- and Women-Led Businesses. Entrepreneurship Theory
and Practice, 30(5), 667–686.
Anna, A. L., Chandler, G. N., Jansen, E., & Mero, N. P. (1999). Women Business owners in traditional and non-traditional industries. Journal of Business Venturing, 15(3), 279-303.
Audretsch, D. B., & Thurik, A. R. (2000). Capital and democracy in the 21st century: from the managed to the entrepreneurial economy. Jounral of Evolutionary Economics, 10(1),
17-34.
Audretsch, D. B., Thurik, A. R., Verheul, I., & Wennekers, A. R. M. (eds). (2002). Entrepreneurship: Determinants and Policies in the New Economy, Boston/Dordrecht: Kluwer Academic Publishers.
Bellavites, C., Filatotchev, I., Kamuriwo, D. S., & Vanacker, T. (2017). Entrepreneurial finance: new frontiers of research and practice. Venture Capital, 19(1-2),1-16
Boden, R. J., & Nucci, A. R. (2000). On the survival prospects of men’s and women’s new business ventures. Journal of Business Venturing, 15(4), 347-362.
Brush, C. G. (1992). Research of women business owners: past trends, a new perspective, future directions. Entrepreneurship Theory and Practice, 16, 5-30.
Brush, C. G., & Chaganti, R. (1999). Businesses without glamour? An analysis of resources on performance by size and age in small service and retail firms. Journal of Business Venturing, 14(3), 233-257.
Bruton, G., Khavul, S., Siegel, D., and Wright, M. (2015). New Financial Alternatives in Seeding Entrepreneurship: Microfinance, Crowdfunding, and Peer-to-Peer Innovations.
Entrepreneurship Theory and Practice. 39: 9-26
Carpenter, R. E., & Petersen, B. C. (2002). Capital Market Imperfections, High-Tech Investment, and New Equity Financing. The Economic Journal, 112(477), 54-72.
Carr, M. (1990). Women in small-scale industries - some lessons from Africa. Small
Enteprise Development, 1(1), 47-51.
Carter, S., & Cannon, T. (1992). Women as Entrepreneurs. (London: Academic Press).
Carter, N. M., Brush, C. G., Greene, P. G., Gatewood, E., & Hart, M. M. (2003). Women entrepreneurs who break through to equity financing: The influence of human, social, and financial capital. Venture Capital, 5(1), 1-28.
Cassar, G. (2004). The Financing of Business Start-ups. Journal of Business Venturing, 19(2), 261-282
Chell, E., & Baines, S. (1998). Does gender affect business ‘performance’? A study of Micro businesses in business service in the UK. Entrepreneurship and Regional Development,
10, 117-135.
Chen, J., A. Chang, and G. Bruton. (2017). “Microfinance: Where Are We Today and Where Should the Research Go in the Future?” International Small Business Journal, 35 (7): 793–802.
Chen, D., Li, X., and Lai, F. (2017) Gender discrimitation in online peer-to-peer credit lending: evidence from a lending platform in China. Electronic Commerce Research, 17(4), 553-583
Cliff, J. (1998). Does one size fit all? Exploring relationship between attitudes towards growth, gender, and business size. Journal of Business Venturing, 13(6), 523-542.
Clifford, V. (1996). A Case Study of a Feminist Small Business: Theory into Practice.
International Review of Women and Leadership, 2(2), 98-111
Collins, D., J. Morduch, S. Rutherford, and O. Ruthven. (2009). Portfolios of the Poor: How the World’s Poor Live on $2 a Day. Princeton, NJ: Princeton University Press.
Collins, J. (2003). Cultural diversity and entrepreneurship: policy responses to immigrant entrepreneurs in Australia. Entrepreneurship and Regional Development: An International
Journal, 15(2), 137-149.
Constantinidis, C., Cornet, A., & Asandei, S. (2006). Financing of women-owned ventures: The impact of gender and other owner- and firm-related variables. Venture Capital,
8(2), 133-157.
Cooper, A. C., Gimeno-Gascon, F. J., & Woo, C. Y. (1994). Initial human and financial capital as predictors of new venture performance. Journal of Business Venturing, 9(5), 371-395.
Delmar, F., & Davidsson, P. 2000. Where Do They Come From? Prevalencde and Characteristics of Nascent Entrepreneurs. Entrepreneurship and Regional Development, 12, 1-23.
Du Rietz, A., & Henrekson, M. (2000). Testing the female underperformance hypothesis.
Small Business Economics, 14(1), 1-10.
EUROSTAT. (2018). Your key to European statistics. Retrieved December 28, 2018, from https://ec.europa.eu/eurostat/data/database
Fabowale, L., Orser, B., & Riding, A. (1995). Gender, structureal factors and credit terms between Canadian small businesses and financial institutions. Entrepreneurship Theory
Fairlie, R. W., & Robb, A. M. (2009). Gender differences in business performance: evidence from the characteristics of business owners survey. Small Business Economics, 33, 375.
Fay, M., & Williams, L. (1993). Sex of applicant and the availability of business ‘start-up’ finance. Australian Journal of Management, 16(1), 65-72.
Galuszka, P., Brzozowska, B. (2016) Crowdfunding and the democratization of the music market. Media, culture & Society, 39(6), 833-849
Gebru, G. H. (2009). Financing preferences of micro and small enterprise owners in Tigray: does POH hold? Journal of Small Business and Enterprise Development, 16(2), 322-334.
Godfred, E., Bokpin, A., & Twerefou, D. K. (2012). Microenterprise financing preference. Journal of Economic Studies, 39(1), 84-105.
Gompers, P., and Lerner, J. (2001). The Venture Capital Revolution. Journal of Economic Perspectives, 15, 145-168.
Green, P. G., Brush, C. G., Hart, M. M., & Saparito, P. (2001). Patterns of venture capital funding: Is gender a factor? Venture Capital, 3(1), 63-83.
Greiner, M. E., & Wang, H. (2010). Building consumer-to-consumer trust in e-finance marketplaces: An empirical analysis. International Journal of Electronic Commerce, 15(2),
Hanssens, J., Deloof, M., & Vanacker, T. (2015). Underexplored issues in entrepreneurial finance. In Audretsch, D. B., Hayter, C. S., & Link, A. N. (Eds), Concise guide to
entrepreneurship, technology and innovation (219-223). Cheltenham (UK), Northamption (MA,
USA): Edward Elgar Publishing.
Heilman, M., & Chen, J. (2003). Entrepreneurship as a solution: The allure of self-employment for women and minorities. Human Resource Management Review, 13, 347-364.
Hisrich, R., & Brush, C. G. (1984). The women entrepreneur: management skills and business problems. Journal of Small Business Management, 22(1), 30-37.
Jensen, R. S. (2005). Women towards ownership in business and agriculture. National Report. Oslo: Innovation Norway.
Jenson, M. C., & Meckling, W. H. (1976). Theory of the Firm: Managerial Behaviour, Agency Costs and Ownership Structure. Journal of Financial Economics, 3(4), 305-360.
Kalleberg, A. L., & Leicht, K. T. (1991) Gender and organizational performance: Determinants of small business survival and success. Academy of Management Journal, 34(1),
136-161.
Khavul, S., H. Chavez, and G. Bruton. (2013). “When Institutional Change Outruns the Change Agent: The Contested Terrain of Entrepreneurial Microfinance for those in Poverty.”
Journal of Business Venturing, 28: 30–50.
Koper, G. (1993). Women entrepreneurs and the granting of business credit, in Allen, S. and Truman, C. (eds), Women in business: Perspectives on Women Entrepreneurs (Londen:
Landstrom, H., & Johannisson, B. (2001). Theoretical foundations of Swedish entrepreneurship and small-business research. Scandinavian Journal of Management, 17(3),
225-248.
Lee, S., & Denslow, D. (2004). A study on the major problems of U.S. women-owned small businesses. Journal of Small Business Stratgy, 15(2), 77-89.
Lin, M. F., Prabhala, N. R., & Viswanathan, S. (2013). Judging borrowers by the company they keep: Friendship networks and information asymmetry in online peer-to-peer lending. Management Science, 59(1), 17–35.
Loscocco, K. A., Robinson, J., Hall, R. H., & Allen, J. K. (1991). Gender and small business success: An inquiry into women’s relative disadvantage. Social Forces, 70(1), 65-85.
Lumpkin, G. T., and Dess, G. G. 1996. Clarifying the entrepreneurial orientation construct and linking it to performance. Academy of Management Review, 21(1), 1-37.
Marlow, S., & Patton, D. (2005). All Credit to Men? Entrepreneurship, Finance, and Gender. Entrepreneurship Theory and Practice, 29(6), 717-735.
Martinez-Climent, C., Zorio-Grima, A., and Ribeiro-Soriano, D. (2018). Financial return crowdfunding: literature review and bibliometric analysis. International Entrepreneurship and
Management Journal. 3.
Morris, M. H., Miyasaki, N. N., Watters, C. E., & Coombes, S. M. (2006). The dilemma of growth: Understanding venture size choices of women entrepreneurs. Journal of Small Business Management. 44(2), 221-244.
OECD, 1998. Fostering Entrepreneurship, the OECD Jobs Strategy, Paris: OECD
OECD (2018). doi: 10.1787/5d5d0d63-en (Accessed on 30 December 2018)
Olm, K., Carsrud, A. L., & Alvey, L. (1998). The role of networkds in new venture funding of female entrepreneurs: a continuing analysis. Frontiers of Entrepreneurship Research.
(Wellesley, MA: Babson College), 658-659.
Orser, B. J., Hogarth-Scott, S., & Riding, A. (2000). Performance, firm size, and management problem solving. Journal of Small Business Management, 38(4), 42-48.
Orser, B., & Hogarth-Scott, S. (2002) Opting for growth: Gender dimensions of choosing enterprise development. Canadian Journal of Administrative Sciences, 19(3), 284-300.
Orser, B. J., Riding, A. L., & Manley, K. (2006). Women entrepreneurs and financial capital. Entrepreneurship Theory and Practice, 30(5), 643-665.
Parker, S. C., & Belghitar, Y. (2006). What happens to nascent entrepreneurs? An econometric analysis of the PSED. Small Business Economics, 27, 81-101.
Reynolds, P. D., Bygrave, W. D., Autio, E., Cox, L., & Hay, M. (2003) . Global
Entrepreneurship Monitor 2003 Executive Report. London: London Business School
Robb, A. M. (2002). Entrepreneurial performance by women and minorities: The case of new firms. Journal of Development Entrepreneurship, 7(4), 383-397.
Robinson, P. B., & Sexton, E. A. 1994. The Effect of Education and Experience on Self-employment Success. Journal of Business Venturing, 9(2), 141-156.
Rosa, P., Carter, S., & Hamilton, D. (1996). Gender as a determinant of small business performance: insights from a British study. Small Business Economics, 8, 463-478.
Rutashobya, L. K., & Nchimbi, M. I. (1999). The African female entrepreneur: knowledge gaps and priority areas for future reserach. In Rutashobya, L. K., & Olomi, D. R. (eds), African Entrepreneurship and Small Business Development. Dar es Salaam: Dar es Salaam University Press (DUP)
Schwartz, E. B. (1976). Entrepreneurship: a new female frontier. Journal of
Contemporary Business, 5, 47-76.
Shane, S. (2009). Fool’s gold: the truth behind angel investing in America. New York: Oxford University Press.
Sexton, D. (1989). Growth Decisions and Growth Pattern of Women-Owned Businesses, in Hagen, O., Rivchun, C., and Sexton, D. (eds), Women-Owned Businesses (135-150). New York: Prager
Scott, C. E. (1986). Why More Women Are Becoming Entrepreneurs. Journal of Small Business Management, 24(4), 37-44.
Uhlaner, L. M., Thurik, R., & Hutjes, J. (2002). Post-Materialism as a Cultural Factor Influencing Entrepreneurial Activity Across Nations. ERIM Report ERS-2002-62, Erasmus University: Rotterdam.
Van Praag, C. M. 1999. Some classic views on entrepreneurship. The Economist, 147, 311-335.
Verheul, I., & Thurik, R. (2001). Start-up capital: “Does gender matter?”. Small Business
Economics, 16(4), 329-345.
Walker, D., & Joyner, B. E. (1999) Female entrepreneurship and the market process: Gender-based public policy considerations. Journal of Developmental Entrepreneurship, 4(2),
95-116.
Watkins, J., & Watkins, D. (1984). The Female Entrepreneur: Background and Determinants of Business Choice - Some British Data. International Small Business Journal,
2(4), 21-31.
Watson, J. (2002). Comparing the performance of male- and female-controlled businesses: Relation outputs to inputs. Entrepreneurship Theory and Practice, 26(3), 91-100.
Whittam, S. P. G., and Wyper, J. (2007). The pecking order hypothesis: does it apply to start-up firms? Journal of Small Business and Enterprise Development, 14(1), 8-21.
Wennekers, S., Stel, A., Thurik, A. R., & Reynolds, P. (2005). Nascent Entrepreneurship and the Level of Economic Development. Small Business Economics, 24, 293-309.
