While the gender gap has closed slightly over the past decade, it persists according to many metrics such as self-employment rates and business creation rates. There are also gender differences, on average, in the nature of self-employment and entrepreneurship activities. This includes sector of operation, likelihood of creating additional jobs and more. One explanation for these gaps are differences in motivations and aspirations between men and women, as well as differences in barriers faced. This chapter presents updated data and trends for European Union Member States and OECD countries.
The Missing Entrepreneurs 2021
Policies for Inclusive Entrepreneurship and Self-Employment
The Missing Entrepreneurs
2. Women’s self-employment and entrepreneurship activities
Abstract
Key messages
The data presented in this chapter are based on Eurostat Labour Force Survey data covering the self-employed and Global Entrepreneurship Monitor data on pre start-up and early-stage business activities. These data are complemented with country-specific statistics to provide additional insights.
Women are outnumbered in self-employment by two-to-one by men. In 2020, just under 10% of working women in the European Union (EU) were self-employed relative to 17% of men. Among EU Member States, the proportion of working women who are self-employed ranged from just under 5% in Denmark to more than 20% in Greece. These shares are determined by a number of factors, including social attitudes towards entrepreneurship, gender roles, economic structure, barriers to entrepreneurship and more.
Although the gender gap in self-employment has closed over the past decade, the COVID-19 pandemic has reversed some of this progress. The gender gap in self-employment in the EU was almost 9 percentage points and it closed to nearly 7 percentage points by 2019. However, estimates from 2021 suggest that this gender gap is increasing again.
Self-employed women tend to operate different types of businesses than men. Self-employed women are more likely than self-employed men to be working in personal and household services and, on average, worked three fewer hours per week.
Consequently, self-employed women were less likely than self-employed men to have created jobs for others. In the EU, about one-quarter of self-employed women had at least one employee in 2020 relative to one-third of self-employed men. This gap between men and women grew in about half of EU Member States between 2011 and 2020.
Women are less likely than men to be active in starting a business. Over the period 2016-20, less than 5% of women in the EU were involved in creating a business or managing a new business relative to about 10% of men. This gap is due to several factors, including attitudes towards entrepreneurship and barriers such as access to finance and a lack of entrepreneurship skills. For example, only 38% of women in the EU over this period reported that they have the skills to start a business relative to more than half of men.
There is also a gender gap in the nature of entrepreneurship activities. Women entrepreneurs are 60% as likely to expect that their start-up will create more than 19 jobs over the next five years. This is consistent with women entrepreneurs being less likely to operate in growth-oriented sectors and a greater level of risk aversion, on average. However, women entrepreneurs are as likely as men entrepreneurs to report introducing a new product or service over the period 2016-20.
Tailored policies and programmes to support women entrepreneurs are widely used across EU Member States and OECD countries. Common interventions include entrepreneurship training, coaching and mentoring, grants and microfinance. Relative to other inclusive entrepreneurship target groups, support for women entrepreneurs is more comprehensive and generally of higher quality. However, more tailored support is needed and governments could strengthen the policy frameworks that underpin programmes and going further to tailor schemes to local contexts.
Policy context for women’s self-employment and entrepreneurship
Looking for the “missing” women entrepreneurs
The longstanding gender gap in entrepreneurship represents a missed opportunity for innovation, social and economic value creation, and job creation. A large body of research underlines the untapped potential of women entrepreneurs (OECD, 2012[1]) and some estimates suggest that closing the gender gap in entrepreneurship could add 2% to global GDP (Blomquist, 2014[2]). Another way to approximate the size of the gender gap in entrepreneurship is to estimate the number of “missing” entrepreneurs. If women participated in early-stage entrepreneurship at the same rate as “core age” men (i.e. 30-49 years old), there would be an additional 6.8 million “missing” women entrepreneurs in the European Union (EU). This accounts for about 72% of the total number of “missing” entrepreneurs in the EU, which is about the same as the share for OECD countries (75%), representing 25.8 million “missing” women entrepreneurs.
Governments have been working to harness the potential of women’s entrepreneurship since the 1970s. Dedicated women’s entrepreneurship policies and programmes have become common across developed countries, seeking to help women overcome barriers to business creation and self-employment and to build motivations for entrepreneurship. Nonetheless, work remains to strengthen these policy frameworks by addressing the remaining gaps and by better linking schemes to policy objectives related to entrepreneurship, employment, innovation and industrial policy (OECD, 2012[1]).
About half of EU Member States have taken steps towards building a policy framework to underpin entrepreneurship programmes for women. The majority of Member States have clearly defined a ministry or department responsible for developing policy to support women entrepreneurs – 22 at the national level and 13 at the sub-national level – which is an important first step for strengthening policy in this area (Figure 2.1). Moreover, about half of the Member States (13) have a clear women’s entrepreneurship strategy, either as a standalone strategy or embedded within a broader entrepreneurship or labour market strategy. The development of a tailored strategy can be a useful tool for bringing a coherence and consistency to women’s entrepreneurship programmes, as well as raising the visibility of women’s entrepreneurship issues. It also makes the support programmes less susceptible to fluctuations in funding due to economic and political cycles. However, many of these strategies remain quite general. Only a handful of Member States have clearly outlined targets in their strategies for boosting and strengthening women’s entrepreneurship.
Figure 2.1. Policy frameworks for women’s entrepreneurship are shared across national and sub-national governments
Note: It is possible for countries to have clear policy responsibility at both the national and sub-national levels; these are not mutually exclusive.
Source: (OECD, 2020[3])
Programmes to support women entrepreneurs remain small-scale and some gaps persist
The gender gap in entrepreneurship is explained by several factors, notably gender differences in motivations and ambitions for entrepreneurship as well as differences in the number and scale of barriers faced by potential women entrepreneurs. These barriers include, for example, lower perceived levels of entrepreneurship skills, more difficulty accessing entrepreneurship training programmes and greater difficulties accessing start-up financing (OECD/EU, 2016[4]). Many of these barriers are inter-related, so the challenges faced can quickly become compounded.
Governments in EU Member States have responded with a wide range of schemes to build motivations and ambitions for entrepreneurship. They include initiatives to help women acquire entrepreneurship skills through training programmes, coaching and mentoring initiatives, business counselling and networking opportunities. They have also improved access to start-up finance with grants, microcredit and loan guarantee programmes. Governments also continue to improve the regulatory environment for new start-ups and have increased support in recent years for women entrepreneurs with care responsibilities.
Relative to tailored entrepreneurship schemes for other inclusive entrepreneurship target groups, those for women are more comprehensive and tend to be of higher quality (Figure 2.2). The OECD inclusive entrepreneurship policy assessment notes examine women’s entrepreneurship schemes in each EU Member State across four dimensions: building entrepreneurship skills; facilitating starting finance; building entrepreneurship networks and attitudes; and group-specific regulatory instruments that support entrepreneurship. Different types of schemes are assessed under these four categories according to a nine-point scale. For more information on these assessment criteria, please refer to the Reader’s Guide.
Overall, there are a number of areas where entrepreneurship schemes in EU Member States for women entrepreneurs could be improved (OECD, 2021[5]). First, programmes and schemes could be more strongly rooted in policy frameworks to ensure that the system of schemes are cohesive and better-integrated. In many EU Member States, schemes and initiatives are designed in isolation and do not consider overarching policy objectives related to supporting women in entrepreneurship, employment and innovation. Second, governments can go further to ensure that support schemes are appropriate for the local conditions. Women’s entrepreneurship policy can be effective in any context, but the objectives, instruments and delivery mechanisms need to be selected accordingly. Finally, much greater efforts are needed overall to monitor and assess the impacts of policy interventions. Policy makers routinely face information gaps when designing support schemes for women entrepreneurs, including an understanding of the effectiveness of different approaches in different contexts, success factors, the relative impact of different interventions (e.g. training vs. coaching vs. microfinance), the effectiveness of combinations of interventions, and the role of measures in influencing institutional conditions. The lack of evaluation evidence represents a lost opportunity to learn from high impact policy interventions and may lend to the vulnerability of women’s enterprise programme funding.
Figure 2.2. Women’s entrepreneurship schemes vary in quality across EU Member States
Note: The panels in this figure present an unweighted average of policy assessment scores for EU Member States. Each policy instrument (e.g. Entrepreneurship training) is assessed a scored out of 9 as described in the Reader’s Guide. The figure shows the average score for schemes for women entrepreneurs relative to the score for all inclusive entrepreneurship groups combined (i.e. women, immigrants, youth, seniors and the unemployed). Some of the policy instruments in panel d are designed specifically for women entrepreneurs so there is no comparative policy assessment score for all inclusive entrepreneurship target groups.
Source: (OECD, 2020[3])
Building entrepreneurship skills
Most EU governments offer tailored entrepreneurship training for women who are interested in starting a business. Many of these training initiatives are dedicated programmes, which can be an effective method of attracting women into the entrepreneurship support system. However, there are several areas where entrepreneurship training programmes for women in the EU can be improved. First, as with inclusive entrepreneurship schemes in general, few are well-evaluated so it is difficult to fully understand the impact that training schemes have for women entrepreneurs. In addition, it does not appear to be a common practice to develop the training programmes in consultation with women entrepreneurs or women entrepreneurship organisations, which can help ensure that the obstacles faced are addressed. Finally, very few countries report that the scale of tailored entrepreneurship training for women entrepreneurs is sufficient.
Another important mechanism for building entrepreneurship skills is through entrepreneurship coaching and mentoring programmes. This type of scheme is now nearly as common across EU Member States and regions as entrepreneurship training programmes. Coaching and mentoring are often designed and implemented according to good practice principles, including the use of targeted outreach efforts. However, more can be done to scale up successful schemes since fewer than half of Member States have reported the scale of tailored entrepreneurship coaching and mentoring schemes for women is sufficient for demand.
The use of tailored or dedicated incubators is a less common method used to build entrepreneurship skills for women entrepreneurs. A priority for governments going forward is to improve access to business incubators and accelerators for women entrepreneurs since support and financing for growth-oriented entrepreneurs is still largely received by men entrepreneurs.
Facilitating access to start-up finance
Governments in EU Member States use a range of instruments to facilitate access to finance for women entrepreneurs. Commonly used mechanisms include microfinance schemes, loan guarantees and grants. There are a small but growing number of crowdfunding platforms that support inclusive entrepreneurship, but platforms dedicated to women’s entrepreneurship are rare.
Overall, public start-up financing schemes for women entrepreneurs appear to be designed to meet their needs. It is common to have strong links with other types of support (e.g. entrepreneurship coaching and mentoring), which can increase the chances of success for participants. However, strong monitoring and evaluation practices were only found in a small number of EU Member States so this remains an area that can be strengthened.
Expanding entrepreneurship networks
Women’s entrepreneurship is heavily promoted in most EU Member States. Common approaches used include promoting successful women entrepreneurs as role models in education (e.g. speaking to students, examples in learning materials), general promotional campaigns and awards that celebrate successful women entrepreneurs. While these types of activities are popular, it is very difficult to know whether they make an impact given that entrepreneurial decisions are influenced by many factors and are not always made in the short-term following inspiration from a role model.
It is also common for governments in EU Member States to support networking initiatives and business associations. Many of these initiatives appear to be well-linked with other entrepreneurship support initiatives for women entrepreneurs, which reinforces their value for helping women entrepreneurs access resources. However, it is also difficult to measure the impact of these schemes. It is therefore difficult to know if the scale of these activities is appropriate.
Supporting women entrepreneurs with regulatory tools
A growing number of Member States are offering support for women entrepreneurs with families, including improved access to maternity benefits and increasing childcare availability. This includes for example, increased investments in childcare in Germany and maternity supports for women entrepreneurs in Austria, i.e. Mutterschaftsbetriebshilfe (“Business continuation aide in case of motherhood”) and Wochengeld für Unternehmerinnen (“Maternity allowance for women entrepreneurs”).
Recent developments in women’s entrepreneurship policy
Policy discussions in 2020 and 2021 have been dominated by COVID-19 pandemic. The initial priority was to contain the virus outbreak with a range of measures including temporarily halting certain economic activities and limiting face-to-face interactions. Governments have now shifted their focus to economic recovery. As a result, nearly all policy developments over the past year have been in response to the COVID-19 pandemic.
Women entrepreneurs were impacted disproportionately during the COVID-19 pandemic, largely due to the concentration of women in the hardest hit sectors and increased demands from household responsibilities (see Chapter 1 for further discussion of the impacts of COVID-19 on women’s entrepreneurship). Governments rolled-out a wide range of support measures to help entrepreneurs sustain their activity through the crisis, including measures aimed to support the liquidity of entrepreneurs and structural measures aimed to help entrepreneurs adapt to the changed business environment. Liquidity measures included job retention schemes (e.g. wage subsidies), payment deferrals (e.g. income and corporate tax payments, value added tax, social security contributions) and financial supports (e.g. loan guarantees, loans, grants). Structural support measures include those to help transform business activities (e.g. digitalisation, innovation) through a range of instruments such as business development services and advice, vouchers, grants, training and networking. Now that countries are shifting their focus to economic recovery packages, these structural support measures are becoming part of wider public investment schemes and demand stimulus. For more on policy responses to support entrepreneurs and SMEs through the COVID-19 pandemic, please see (OECD, 2021[6]).
Despite the large number of schemes developed for entrepreneurs and the self-employed, few were specifically designed for women. At the national level, only a small number EU Member States implemented COVID-19 support schemes for women entrepreneurs. In Malta, the Microinvest Cash Conversion Scheme enables a conversion of up to EUR 2 000 of tax credits in Malta Enterprise’s Microinvest Tax Credit Scheme into grants; and up to EUR 2 500 – for women entrepreneurs, family-run enterprises and entrepreneurs based in Gozo (OECD, 2020[3]). In Italy, the Ministry for Equal Opportunities and the Family provided an extra allocation of EUR 5 million within the fund for SMEs for female entrepreneurship (OECD, 2020[3]).
Furthermore, only a small number of governments outside of the EU provided dedicated support to women entrepreneurs. Most of these initiatives provided increased support for those already being supported by a programme. In Canada for example, the government boosted funding for the Women Entrepreneurship Strategy (WES) Ecosystem Fund by CDN 15 million (approximately EUR 10.2 million) to support women business organisations that already receive support through the Fund. Other examples include increased cash transfers (by INR 500 or EUR 6 per month) for self-employed and women entrepreneurs in India for the 200 million women Jan Dhan account holders (OECD, 2021[6]).
COVID-19 also had a strong impact on the delivery of long-standing women’s entrepreneurship schemes since face-to-face interactions were restricted in most EU Member States. One of the most common developments was moving programmes online, which required adjusting delivery formats and content so that support could continue on a digital platform. There are many examples across the EU of how women’s entrepreneurship support schemes are going digital, including the group coaching and peer-learning sessions in the Going for Growth schemes in Ireland being moved onto an online meeting platform. There are also examples of schemes such as Force Femmes in France that used the move online to expand their activities. This network introduced a series of virtual webinars on entrepreneurship for women over 45 years old and a virtual conference on digital entrepreneurship for older women.
For additional examples of recent policy developments, please see the country profiles in Part III of this report.
Trends in self-employment by women
Women are 40% less likely than men to be self-employed
The self-employment rate for women in the EU has been constant over the past two decades. About 10% of working women were self-employed between 2002 and 2020 (Figure 2.3). In 2020, nearly 8.5 million of the 88.6 million working women in the EU were self-employed. This proportion was about 55% lower than that of men in 2020, when 17.4 million of the 103.4 million working men were self-employed (17%).
The gender gap in self-employment in the EU has closed by about 15% since 2002, falling from 8.5 percentage points (p.p.) in 2002 to 7.5 p.p. in 2020. This slight closing of the gender gap in self-employment is due to a decrease in the share of men who are self-employed. While the share of working women who are self-employed has been constant, the rate for men declined nearly 2 p.p. over the past decade, falling from 19% in 2011 to 17% in 2020.
Figure 2.3. The gender gap in self-employment has closed slightly since 2002
Source: (Eurostat, 2021[7])
The gender gap in self-employment was closing across most EU Member States pre-COVID-19
There is a substantial amount of variation in the self-employment rate for women and the gender gap in self-employment across EU Member States. Self-employment rates for women tend to be lower in northern EU Member States such as Denmark and Sweden (approximately 5% in 2020) and are higher in southern Member States, notably in Greece (21% in 2020) and Italy (15%) (Figure 2.4). Self-employment rates for women are positively correlated with the overall self-employment rates, which are explained by several factors. In northern EU Member States such as Denmark and Sweden, unemployment rates tend to be lower and social welfare systems provide greater amounts of support so individuals are less likely to be in a situation where they need to generate income for themselves out of desperation. These Member States also often have a higher share of employment in the public sector.
Figure 2.4. The gender gap in self-employment closed in 80% of Member States over the past decade
Note: Data for Australia, Canada, Chile, Colombia, Israel, Japan, Korea, Mexico, New Zealand, Turkey, United Kingdom, United States, are for 2019 in panel a and 2011 and 2019 in panel b. Data for Korea in panel b are based on preliminary estimates.
Source: (Eurostat, 2021[7]; OECD, 2021[8])
Self-employment rates can also be influenced by a range of other country-specific factors. For example, some Member States such as Lithuania and Estonia have several possible legal forms of business activity for individuals. In Lithuania, the personal income tax law (Law No. IX-1007) defines two forms of individual activity: (i) performed on the basis of an individual activity certificate; (ii) carried out under a business license. These different forms determine the activities that are permitted and the amount of tax that is paid. Having multiple potential legal forms for small-scale business activities could reduce the amount of self-employment picked up by official statistics since some of these activities could be classified as business activities rather than self-employment. Conversely, countries such as France have mechanisms such as micro-entrepreneur (formerly auto-entrepreneur) that facilitate people moving into self-employment. Since the auto-entrepreneur status was introduced in 2009, self-employment has been markedly higher.
The gender gap in self-employment fell in most EU Member States over the past decade, notably in Ireland where the gender gap closed by about 6 p.p. This was due to an influx of self-employed women – a 24% increase – coupled with a decrease in the number of self-employed men over this period (9%). Most of this growth was concentrated in Human health and social work activities (55% increase), Other services (40% increase) and Professional, scientific and technical activities (33% increase). There was also a disproportionate increase in self-employment among women over 50 years old, which may be related to differences in availability of maternity and family supports and benefits for the self-employed relative to employees (OECD, 2020[3]).
Characteristics of self-employed women and their activities
Self-employed women are 30% less likely to be employers than self-employed men
Self-employed women in the EU are less likely to have employees than self-employed men. About one-in-four self-employed women in the EU have employees, relative to about one-in-three self-employed men (Figure 2.5). Both of these shares have declined slightly since 2002 – from about 28% to 24% in 2020 for women and 38% to 33% for men – and they are expected to decline further in the short-term due to the COVID-19 pandemic. Prior to COVID-19, the growth in solo self-employment was driven by an increase in part-time self-employment and freelance work (OECD/European Union, 2017[9]). However, some of the self-employed with employees have become solo self-employed workers over the past year since a common response to the economic crisis was to let employees go.
The gender gap in the share of the self-employed who employ others is explained by several factors, including gender differences in motivations and ambitions. Some research shows that many self-employed workers do not want to have employees of whom women are more likely to not want employees (OECD/European Union, 2019[10]). This is confirmed by country level research such as in Finland (Sutela and Pärnänen, 2019[11]). Moreover, women on average have different attitudes towards growth (page 36) and there are gender differences among the self-employed in terms of hours worked (page 18) and type of business activities, including sector (page 22), occupation (page 23), innovation rate (page 35) and scale of export activities (page 35). The legal status that women business owners use can also influence their size and growth path. For example, women create around 40% of new micro-enterprises in France, which are primarily categorised into two legal statuses. The first is auto-entrepreneurs, which is a business status that has earning restrictions that can make it difficult to hire employees and grow the business in the first few years of operations. In contrast, sole-proprietors classified as an individual enterprise (l’entreprise individuelle) are not limited by income caps and are more likely to hire employees.
Figure 2.5. Less than one-quarter of self-employed women in the EU have employees
Source: (Eurostat, 2021[7])
While the share of self-employed women (and men) who employed others declined over the past two decades, there was also a decline in the gender gap in the share of self-employed who are employers. The difference between the share of self-employed women and men who employ others declined from 9.5 p.p. in 2002 to 7.4 p.p. in 2016 but has since increased to 8.3 p.p. in 2020.
At the country level, the share of self-employed women who employ others in 2020 ranged from about 7% in Romania to more than 40% in Croatia (Figure 2.6). There is also a large variation in the difference of the share of self-employed women and men who employ others. In countries such as Ireland and Poland, there is essentially no gender difference, but there is a gap of more than 35% in Austria, Cyprus, Denmark, Estonia, Finland, France, Germany, Lithuania and the Netherlands.
The gender gap in the share of self-employed who employ others increased in about half of EU Member States over the past decade. The largest increases were observed in Malta (9.3 p.p.), Denmark (7.1 p.p.) and Slovenia (5.1. p.p.). This positive trend in Denmark is consistent with the Entrepreneurship Barometer Report (2019) which found around 30% of Danish entrepreneurs planned to hire additional staff in 2019. The majority of entrepreneurs reported the intention of hiring 1-2 workers (69%) while 8% expected to hire 10 or more new employees (Væksthus Sjælland, 2019[12]).
Figure 2.6. The gender gap in employer rates increased in about half of EU Member States since 2011
Self-employed women are slightly younger than self-employed men…
Self-employed women in the EU are, on average, slightly younger than self-employed men.
In 2020, self-employed women were about 2 p.p. more likely than men to be between 25 and 39 years old. Similarly, about 27% of self-employed women were between 40 and 49 years old relative to one-quarter of self-employed men. Thus, 53% of self-employed women were between 25 to 49 years old relative to 49% of self-employed men.
Self-employed women with employees tend to be older than those without employees. Nearly 80% of self-employed women with employees were older than 40 years old in 2020 relative to about 72% of those without employees (Figure 2.7). These shares were approximately the same for self-employed men with employees. However, self-employed women with employees are, on average, younger than self-employed men with employees. About 22% of self-employed women with employees were between 25 and 39 years old relative to 19% of self-employed men.
Figure 2.7. Self-employed women with employees tend to be older than those without
Source: (Eurostat, 2021[7])
…and are more likely to have a tertiary education
The share of self-employed with a tertiary education more than doubled since 2002, increasing from 21% in 2002 to 46% in 2020. This increase was largely offset by a decline in the share who have less than an upper secondary education, which fell from 35% to 14% (Figure 2.8). This shift was also observed among self-employed men during this period, but the increase in the share who have at least a tertiary education was smaller – from 20% in 2002 to 33% in 2020. This trend is consistent with the increasing share of women earning tertiary degrees and the slightly younger age profile of self-employed women. However, self-employed women are more likely than employees to have completed tertiary education.
Figure 2.8. The share of self-employed in the EU with a tertiary education is increasing faster than for men
Source: (Eurostat, 2021[7])
Among self-employed women, there was little difference in the educational attainment of those with employees and those without in 2020. While this may appear to cast doubt on the notion that someone with a higher educational attainment is more likely to create a business that creates jobs for others, the data do not indicate how many people are employed. Moreover, this is a relatively recent finding. Between 2002 and 2015, self-employed women with a tertiary education were more likely to have employees than those without a tertiary education.
Although tertiary education attainment rates vary across EU Member States, self-employed women were more likely to have completed tertiary education than self-employed men in nearly all Member States. In most Member States, the share of self-employed women with a tertiary education reflected general trends in education attainment. However, in Germany self-employed women were nearly twice as likely as employees to have a tertiary education (Figure 2.9). This can be explained in part by the lower share of the population in Germany that has obtained a tertiary education since there is a strong vocational education system. This is also observed in Austria for similar reasons. However, the opposite is observed in Greece, Poland, Romania and Sweden, where self-employed women are much less likely to have a tertiary education than those working as employees.
Figure 2.9. Self-employed women are more likely to have a tertiary education than self-employed men
Source: (Eurostat, 2021[7])
Self-employed women work fewer hours per week than self-employed men…
Among EU Member States, the median hours worked by full-time workers varied greatly by employment type. Overall, the self-employed with and without employees work, on average, more hours per week than employees. In addition, the self-employed with employees tend to work about 45 minutes more per day. In 2020, full-time self-employed women with employees worked, on average, 3.5 hours less per week than full-time self-employed men with employees (Figure 2.10). This gap has been fairly constant since 2015. A similar gap of about 3.3 hours per week is also found between self-employed men and women without employees.
Figure 2.10. Average weekly hours are declining for the self-employed
Note: Full-time work is not defined in most EU Member States and is defined by the survey respondent. However, full-time work is defined as more than 35 hours per week in the Netherlands and Iceland. In Sweden, full-time work is defined as more than 36 hours per week but survey respondents who work between 32 and 36 hours per week can specify if they work full-time or part-time.
Source: (Eurostat, 2021[7])
These differences in hours worked are also observed across most EU Member States, with the exception of Estonia, Latvia, Lithuania and Malta were there was little gender gap (Figure 2.11). Full-time self-employed women worked the most hours per week in Belgium (52.8 hours for self-employed women with employees and 47.3 hours for those without employees), Austria (50.3 hours and 46.2 hours) and Greece (50.1 hours and 46.6 hours), yet they worked fewer hours per week on average than self-employed men. In Belgium, for example, self-employed men worked on average 54.2 hours per week in 2020, which was about 4 hours more than self-employed women (50.1 hours per week).
Figure 2.11. Self-employed women work slightly more hours a week than those who work as employees
Note: Full-time work is not defined in most EU Member States and is defined by the survey respondent. However, full-time work is defined as more than 35 hours per week in the Netherlands and Iceland. In Sweden, full-time work is defined as more than 36 hours per week but survey respondents who work between 32 and 36 hours per week can specify if they work full-time or part-time.
Source: (Eurostat, 2021[7])
…but self-employed women are as likely to report full autonomy over their working time
About 15% of self-employed workers report that another organisation (i.e. a single client) is responsible for making decisions about working time. Self-employed men and women were about as likely to report that they fully control their working time across the EU (61% for self-employed women and 65% for self-employed men) (Figure 2.12). Furthermore, it is somewhat surprising that there is essentially no difference in the proportion of self-employed with and without employees that have full autonomy over their working time.
Figure 2.12. Self-employed women are as likely as men to have autonomy over their working time
Source: (Eurostat, 2019[14])
Self-employed women earn less than employees but the gender gap is relatively small
The median net income for full-time self-employed women and self-employed men was approximately equal over the period 2010-19. However, self-employed women had a lower median net income compared to women who worked as employees (EUR 20 620 vs EUR 17 326 in 2019) (Figure 2.13). In 2019, full-time self-employed women earned slightly more than self-employed men in 16 EU Member States (Figure 2.14). The largest difference was in Denmark where full-time self-employed women earned, on average, EUR 7 324 more per year than self-employed men. Conversely, the largest gender pay gap was in Slovenia where self-employed women made, on average, EUR 2 388 less in median net income than self-employed men.
Figure 2.13. There earnings gap between full-time self-employed men and women is negligible
Note: Full-time work is not defined in most EU Member States and is defined by the survey respondent. However, full-time work is defined as more than 35 hours per week in the Netherlands and Iceland. In Sweden, full-time work is defined as more than 36 hours per week but survey respondents who work between 32 and 36 hours per week can specify if they work full-time or part-time.
Source: (Eurostat, 2021[15])
Figure 2.14. Self-employed women earn less than those working as employees in most EU Member States
Note: Full-time work is not defined in most EU Member States and is defined by the survey respondent. However, full-time work is defined as more than 35 hours per week in the Netherlands and Iceland. In Sweden, full-time work is defined as more than 36 hours per week but survey respondents who work between 32 and 36 hours per week can specify if they work full-time or part-time.
Source: (Eurostat, 2021[15])
Women have lower self-employment rates across all sectors except other services…
Women were less likely to be self-employed than men in all sectors except for other services, where about one-third of all women were self-employed relative to 26% of men. This sector includes activities of membership organisations, repair of computers, personal and household goods and other personal service activities (e.g. Washing and (dry-) cleaning of textile and fur products, Hairdressing and other beauty treatment, Physical well-being activities). However, the sector where women were the most likely to be self-employed was Agriculture, forestry and fishing. More than 40% of women working in this sector in 2020 were self-employed, which was a lower than the share of men (53%) (Figure 2.15). These findings have been constant over the past decade.
The sectors where self-employed women are concentrated varies across EU Member States, which is largely driven by the economic structure of different economies. For example, self-employed women in Romania are concentrated in agriculture, which accounts for 24% of total employment – the largest share in the EU. This mainly consists of self-employed and contributing family workers, with the vast majority in the latter category being women. In other countries such as Portugal, self-employed women are heavily concentrated in accommodation and food service activities, which account for a larger share of the self-employed in Portugal due to the significance of tourism in the economy.
In some countries, specific administrative requirements lead to an increase in self-employment in some sectors. In Austria, for example, there is a disproportionate number of self-employed workers in health and social work since care workers (Personenbetreuer) are mostly registered as sole-proprietors. The vast majority of these workers are women, so it is a dominant activity of self-employed women. Another example is the Slovak Republic, which has very low levels of self-employment in the agriculture sector since the previous political regime required individual farmers to merge into agricultural co-operatives.
Figure 2.15. Women are more likely to be self-employed than men in the Other service activities sector
Note: The following sectors were excluded because the self-employment rate was less than 1% or the data were could not be reported due to a low reliability of the estimate: Public administration and defence, compulsory social security; Mining and quarrying; and Electricity, gas, steam and air conditioning supply.
Source: (Eurostat, 2021[7])
…and the majority of self-employed women are professionals or service and sales workers
More than half of self-employed women worked as professionals (30%) or service and sales workers (27%) in 2020, compared to 19% and 11% of self-employed men. This concentration in professional and service and sales worker occupations is observed among employees, but the concentration is not as significant. Conversely, self-employed women were much less likely than men to be working as craft and related trades workers (4% vs. 21%) (Figure 2.16). The occupations of self-employed women are influenced by a range of factors, including level of education and sector.
Figure 2.16. More than half of self-employed women are professionals and service and sales workers
Source: (Eurostat, 2021[7])
Activities by women over the entrepreneurship life-cycle
Women are less involved in early-stage entrepreneurship than men…
Another way to examine entrepreneurship activities by women is to consider the proportion of women who are involved in starting or managing businesses. The Global Entrepreneurship Monitor (GEM) is an international study of entrepreneurship that is produced by a consortium of researchers and research institutions using a common population survey. This survey divides entrepreneurship activities into four stages: nascent entrepreneurship, new business ownership, established business ownership and business exit. For more information, please see the Reader’s Guide at the beginning of the report.
Women are less likely than men to be actively working towards starting a business. Overall, about 3% of women in the EU were involved in nascent entrepreneurship between 2016 and 2020 (Figure 2.17), i.e. actively involved in setting up a business they will own or co-own but have not yet paid salaries, wages or any other payments to the owner(s) for more than three months. This was below the proportion of men (nearly 5%) and also below the share of women in OECD countries involved in nascent entrepreneurship (6%).
This gender gap in nascent entrepreneurship was also observed across all EU Member States over this period, although the size of the gender gap varies substantially. Women were the most active in nascent entrepreneurship in Latvia (6%), Slovak Republic (7%) and Estonia (9%), but these countries had lower rates than many OECD countries: United States (9%), Colombia (14%) and Chile (17%). Moreover, the EU Member States with the highest nascent entrepreneurship rates among women were not the countries with the smallest gender gap. The gender gap in nascent entrepreneurship was the greatest in Hungary (119%) and Latvia (103%), and smallest in Finland (15%) and Spain (18%).
Women in the EU were less than half as likely as men to self-report that they were new business owners between 2016 and 2020 (Figure 2.17). Across the EU, about 2% of women and 5% of men indicated that they were the owner-manager of a new business that has paid salaries, wages or any other payments to the owners for more than three months, but not more than 42 months. The share of women identifying as new business owners was also below the OECD average of 3%.
There tends to be a strong corelation between nascent entrepreneurship rates and new business ownership rates. For example, both the nascent and new business ownership rates were high in countries such as Latvia and Estonia. However, there are a few exceptions such as the Slovak Republic which had high levels of nascent entrepreneurship among women but relatively low level of new business ownership. Early-stage entrepreneurship rates are influenced by a large range of factors, including the regulatory framework, market conditions, access to finance, creation and diffusion of knowledge, entrepreneurial capabilities and social and cultural attitudes towards entrepreneurship. Each of these factors vary greatly across Member States and these factors have different influences for men and women.
Figure 2.17. There is a gender gap in early-stage entrepreneurship across all EU Member States
Note: Nascent entrepreneurship rate is the proportion of the population that is actively involved in setting up a business they will own or co-own; this business has not paid salaries, wages or any other payments to the owners for more than three months. New business ownership is the proportion of the population that is currently an owner-manager of a new business that has paid salaries, wages or any other payments to the owners for more than three months, but not more than 42 months. All EU Member States participated in the GEM survey between 2016 and 2020 except for Belgium, Czech Republic, Denmark, Lithuania, Malta and Romania. Furthermore, the following countries did not participate in the survey in every year over this period (years of participation are indicated): Austria (2016, 2018, 2020), Bulgaria (2016-18), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Latvia (2016-17, 2019-20) and Portugal (2016, 2019). Similarly, the following OECD countries did not participate in the GEM survey between 2016 and 2020: Belgium, Czech Republic, Denmark, Iceland, Lithuania and New Zealand. The following countries did not participate in the survey in every year (years of participation are indicated): Australia (2016-17, 2019), Austria (2016, 2018, 2020), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Japan (2017-19), Latvia (2016-17, 2018-19), Mexico (2016-17, 2019), Norway (2019-20), Portugal (2016, 2019) and Turkey (2016, 2018).
…and are slightly more likely to have started their business out of “necessity”…
Individuals can be motivated to start a business for several reasons. Some people have an idea that they believe will meet a market demand and generate an income, while others seek to start a business that does something to improve society rather than focussing only on making money. Others create a business because they are unable to find employment but need to earn some income. Policy makers are interested in understanding the different types of motivations and seek to support those who create economic and social value. However, in practice these different motivations can be difficult to distinguish because it is possible for entrepreneurs to have multiple motivations and these motivations can easily change. For example, an entrepreneur who creates a business because they cannot find a job may start a sustainable business that meets a market demand and the business may end up growing. Conversely, an entrepreneur that starts a business to meet a market demand may lack the finance or skills to convert the idea into a sustainable business.
Early-stage women entrepreneurs in the EU were slightly more likely to indicate that they started a business out of “necessity” than early-stage men entrepreneurs between 2016 and 2020 (Figure 2.18). Among early-stage entrepreneurs, 21% of women indicated that they started their business because they could not find employment relative to 17% of men. These rates were similar to the OECD average for this period: 18% of early-stage women entrepreneurs and 15% of early-stage men entrepreneurs.
Figure 2.18. Women are more likely to be “necessity” entrepreneurs in countries with high unemployment and informality rates
Note: Necessity entrepreneurship rate is the proportion of early-stage entrepreneurs (i.e. nascent entrepreneurs and new business owners) who launched their business due to a lack of other opportunities in the labour market. All EU Member States participated in the GEM survey between 2016 and 2020 except for Belgium, Czech Republic, Denmark, Lithuania, Malta and Romania. Furthermore, the following countries did not participate in the survey in every year over this period (years of participation are indicated): Austria (2016, 2018, 2020), Bulgaria (2016-18), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Latvia (2016-17, 2019-20) and Portugal (2016, 2019). Similarly, the following OECD countries did not participate in the GEM survey between 2016 and 2020: Belgium, Czech Republic, Denmark, Iceland, Lithuania and New Zealand. The following countries did not participate in the survey in every year (years of participation are indicated): Australia (2016-17, 2019), Austria (2016, 2018, 2020), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Japan (2017-19), Latvia (2016-17, 2018-19), Mexico (2016-17, 2019), Norway (2019-20), Portugal (2016, 2019) and Turkey (2016, 2018).
Necessity entrepreneurship rates tend to be highest in Member States that have high levels of unemployment or have high levels of informal work. For example, Latvia and Romania are estimated to have the highest levels of undeclared work among the self-employed (Williams et al., 2019[17]). Conversely, it is low in countries where cultural attitudes dictate a preference for employment and where countries have relatively larger public sectors. This includes, for example, Finland where salaried employment is a cultural norm (European Commission, 2019[18]). In some countries, women are motivated by earnings gaps between men and women in employment. For example, in Ireland, the pay differential has been increasing, rising from 5.9% in 2017 to 7.5% in 2018 (PWC, 2020[19]).
…and less likely to start businesses in teams
Women who are working on a new business start-up are about two-thirds as likely as men to be working in teams of three or more people. Between 2016 and 2020, about 15% of women nascent entrepreneurs in the EU were working in teams of at least three people relative to 22% of men (Figure 2.19). These proportions were essentially the same as the proportions in OECD countries – 16% of women nascent entrepreneurs and 23% of men nascent entrepreneurs were working in teams of at least three people.
Figure 2.19. Fewer than one-in-six women entrepreneurs started the business in a team
Note: Nascent entrepreneurship rate is the proportion of the population that is actively involved in setting up a business they will own or co-own; this business has not paid salaries, wages or any other payments to the owners for more than three months. All EU Member States participated in the GEM survey between 2016 and 2020 except for Belgium, Czech Republic, Denmark, Lithuania, Malta and Romania. Furthermore, the following countries did not participate in the survey in every year over this period (years of participation are indicated): Austria (2016, 2018, 2020), Bulgaria (2016-18), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Latvia (2016-17, 2019-20) and Portugal (2016, 2019). Similarly, the following OECD countries did not participate in the GEM survey between 2016 and 2020: Belgium, Czech Republic, Denmark, Iceland, Lithuania and New Zealand. The following countries did not participate in the survey in every year (years of participation are indicated): Australia (2016-17, 2019), Austria (2016, 2018, 2020), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Japan (2017-19), Latvia (2016-17, 2018-19), Mexico (2016-17, 2019), Norway (2019-20), Portugal (2016, 2019) and Turkey (2016, 2018).
Consequently, women are less likely to operate established businesses than men
About 5% of women in the EU self-report that they own an established business, which is nearly half the proportion of men. These businesses are those that have paid salaries, wages or any other payments to the owners for more than 42 months. Established business ownership rates among men and women tend to be highest in countries where early-stage entrepreneurship is highest such as Portugal (6%), Estonia (7%) and Latvia (7%) (Figure 2.20). Combining the three stages of entrepreneurship as defined by GEM – nascent entrepreneurship, new business ownership and established business ownership – nearly 10% of women in the EU are actively participating in entrepreneurship. This is about half of the proportion of men (19%).
Figure 2.20. Women are half as likely as men to be established business owners
Note: Established business ownership rate is the proportion of the adult population that are currently owner-managers of an established business that has paid salaries, wages or any other payments to the owners for more than 42 months. All EU Member States participated in the GEM survey between 2016 and 2020 except for Belgium, Czech Republic, Denmark, Lithuania, Malta and Romania. Furthermore, the following countries did not participate in the survey in every year over this period (years of participation are indicated): Austria (2016, 2018, 2020), Bulgaria (2016-18), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Latvia (2016-17, 2019-20) and Portugal (2016, 2019). Similarly, the following OECD countries did not participate in the GEM survey between 2016 and 2020: Belgium, Czech Republic, Denmark, Iceland, Lithuania and New Zealand. The following countries did not participate in the survey in every year (years of participation are indicated): Australia (2016-17, 2019), Austria (2016, 2018, 2020), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Japan (2017-19), Latvia (2016-17, 2018-19), Mexico (2016-17, 2019), Norway (2019-20), Portugal (2016, 2019) and Turkey (2016, 2018).
Women entrepreneurs are most likely to stop because their business is not profitable
About one-quarter of women entrepreneurs in the EU who stopped operating their business indicated that they did so because it was not profitable (Figure 2.21). Similarly, about one-quarter of men indicated that they stopped their business because it was not profitable. This was the most commonly cited reason for stopping business activities by both men and women entrepreneurs.
Overall, there were only small gender differences in the factors for stopping a business. Women were slightly more likely to report that they stopped their business due to “personal reasons” (18% vs. 15%) but were less than half as likely to report that they had an “opportunity to sell their business” (3% vs. 8%).
Figure 2.21. Most entrepreneurs, whether women or men, exit their business because it is not profitable
Note: All EU Member States participated in the GEM survey between 2016 and 2020 except for Belgium, Czech Republic, Denmark, Lithuania, Malta and Romania. Furthermore, the following countries did not participate in the survey in every year over this period (years of participation are indicated): Austria (2016, 2018, 2020), Bulgaria (2016-18), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Latvia (2016-17, 2019-20) and Portugal (2016, 2019). Similarly, the following OECD countries did not participate in the GEM survey between 2016 and 2020: Belgium, Czech Republic, Denmark, Iceland, Lithuania and New Zealand. The following countries did not participate in the survey in every year (years of participation are indicated): Australia (2016-17, 2019), Austria (2016, 2018, 2020), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Japan (2017-19), Latvia (2016-17, 2018-19), Mexico (2016-17, 2019), Norway (2019-20), Portugal (2016, 2019) and Turkey (2016, 2018).
Barriers to business creation by women
Nearly half of women report that a fear of failure is a barrier to business creation
Nearly half of women (47%) surveyed in the EU between 2016 and 2020 reported that a “fear of failure” was a barrier to business creation relative to 40% of men. This proportion of people reporting that “fear of failure” is a barrier to entrepreneurship is slightly higher in the EU than in OECD countries, where about 43% of women reported this obstacle relative to 37% of men (Figure 2.22). This is an important barrier to entrepreneurship because it can prevent people from considering entrepreneurship as a career or part-time activity. It can also lead to people reducing their entrepreneurial ambitions.
The significance of this barrier varies across countries according to factors such as social attitudes and regulatory and tax policy. The gender gap in fear of failure was greatest in Latvia (30%), Estonia (34%) and Germany (35%) and smallest in Italy, where it was virtually non-existent over this time period. Country-specific research highlights how different factors can influence attitudes towards entrepreneurship. For example, the most significant barriers identified in Bulgaria for young women entrepreneurs are access to finance, corruption and administrative burden (Innovation Region Styria Ltd, 2019[20]). Each of these factors is an obstacle, but they also combine to influence how entrepreneurship is viewed in society. When many difficulties are perceived, people are less likely to pursue business creation.
Figure 2.22. Nearly 50% of women report that fear of failure is a barrier to business creation
Note: All EU Member States participated in the GEM survey between 2016 and 2020 except for Belgium, Czech Republic, Denmark, Lithuania, Malta and Romania. Furthermore, the following countries did not participate in the survey in every year over this period (years of participation are indicated): Austria (2016, 2018, 2020), Bulgaria (2016-18), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Latvia (2016-17, 2019-20) and Portugal (2016, 2019). Similarly, the following OECD countries did not participate in the GEM survey between 2016 and 2020: Belgium, Czech Republic, Denmark, Iceland, Lithuania and New Zealand. The following countries did not participate in the survey in every year (years of participation are indicated): Australia (2016-17, 2019), Austria (2016, 2018, 2020), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Japan (2017-19), Latvia (2016-17, 2018-19), Mexico (2016-17, 2019), Norway (2019-20), Portugal (2016, 2019) and Turkey (2016, 2018).
Box 2.1. Country spotlight: Access to finance as a barrier to business creation in the Netherlands
Recent evidence from the Netherlands shows that – even after correcting for gender differences in business characteristics – female entrepreneurs who seek external finance at less likely to succeed than males (CBS, 2019[21]). The new research used data from the Financing Monitor (1 July 2017 to 1 July 2019) to examine gender gaps at different phases of seeking and acquiring external finance among employer firms (Figure 2.23). Gender differences are significant at each phase, with the exception of the outcome of the application. Of the companies that are operated by female teams, 19% identified a need for external finance and 70% indicate that their activities are oriented towards opportunities offered by lenders and investors. Both of these proportions are below the responses of male entrepreneurs. Female entrepreneurs were also less likely to make funding applications. However, there appears to be little different in the success rates of funding applications, but female entrepreneurs were more likely to report a future financing need. This suggests that women were less successful at securing the amount of funding sought, which is consistent with the broad evidence base on access to external financing by female entrepreneurs (OECD/European Union, 2019[10]).
Figure 2.23. Female entrepreneurs continue to have greater difficulties accessing finance sought
Note: Solo self-employed workers are excluded from this analysis.
Source: (CBS, 2019[21])
Women were only 75% as likely as men to report having the skills to start a business
Nearly four out of ten women in the EU (38%) reported during the period 2016-20 that they had the skills and knowledge to start a business, relative to half of men. This means that about six out of ten women entrepreneurs perceive that they do not have the skills to successfully start a business. The share of men and women who perceive that they have entrepreneurship skills is slightly higher in OECD countries. Between 2016 and 2020, 43% of women and 56% of men reported that they had the skills and knowledge to start a business (Figure 2.24). A lack of entrepreneurship skills is often considered to be one of the most significant barriers to successful business creation. This set of skills refers to business management skills (e.g. business and financial planning), personal skills and traits (e.g. a sense of initiative, risk management) and technical skills (e.g. problem solving). Although these skills will increase the chances of business survival and growth, formal education and training in these areas do not guarantee success.
Among EU Member States, women were the most likely to report that they had the skills and knowledge to start a business in Latvia (47%), Poland (48%) and Croatia (56%). Many of the countries where women are more likely to report having entrepreneurship skills have launched new schemes to help women acquire entrepreneurship skills. For example, Poland has launched several women’s entrepreneurship initiatives including the national project “Entrepreneurial Woman” which was created specifically for women who want to develop and acquire new skills from other successful business owners (OECD, 2020[3]). Moreover, some countries with high positive response rates are countries such as Latvia where informal work is more common. This may lead to a higher frequency of positive responses since the perception of entrepreneurship is likely different.
It is also important to recognise that this question about perceived capabilities to start a business also picks up other issues that influence perceptions, including culture. The case of Sweden illustrates this point. Sweden has a highly educated workforce, among the top five OECD countries with regard to its digital literacy (OECD, 2019[22]). The government has invested in building digital skills among the past five years, as well as lifelong learning initiatives and measures to improve the integration of immigrants into vocational education and training. Yet a small proportion of men and women believe that they have the skills and knowledge to start a business. This low rate is consistent with low early-stage entrepreneurship rates but also likely reflects a cultural bias towards high-tech start-ups (requiring digital skills that not everyone has) as well as “lagom” – the prevailing Swedish attitude that boasting should not be done.
Figure 2.24. About four-in-ten women report that they have the skills needed to start a business
Note: All EU Member States participated in the GEM survey between 2016 and 2020 except for Belgium, Czech Republic, Denmark, Lithuania, Malta and Romania. Furthermore, the following countries did not participate in the survey in every year over this period (years of participation are indicated): Austria (2016, 2018, 2020), Bulgaria (2016-18), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Latvia (2016-17, 2019-20) and Portugal (2016, 2019). Similarly, the following OECD countries did not participate in the GEM survey between 2016 and 2020: Belgium, Czech Republic, Denmark, Iceland, Lithuania and New Zealand. The following countries did not participate in the survey in every year (years of participation are indicated): Australia (2016-17, 2019), Austria (2016, 2018, 2020), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Japan (2017-19), Latvia (2016-17, 2018-19), Mexico (2016-17, 2019), Norway (2019-20), Portugal (2016, 2019) and Turkey (2016, 2018).
Box 2.2. Country spotlight: Developing entrepreneurial intentions through entrepreneurship education in Australia
A recent evaluation of the OzGirlsEntrepreneurship in Australia found that entrepreneurship education can increase entrepreneurial intentions among female students in secondary school (Shahin et al., 2021[23]). The OzGirlsEntrepreneurship programme is the first of three stages within the Women in STEM and Entrepreneurship Programme (WISE) and targets Year 10 female students (14-16 years old) in Victoria, Australia. In 2019, OzGirlsEntrepreneurship hosted a full-day entrepreneurship workshop for 203 students across 44 secondary schools with varying degrees of prior entrepreneurship knowledge and connection. The girls were grouped into 52 teams of 3-4 students to simulate STEM-focused entrepreneurship which is mostly team-based. The evaluation analyses data from pre- and post-programme surveys – both of which had 97% response rate with a total of 193 valid responses reviewed. It assesses the relationship between entrepreneurial attitude, entrepreneurial intention, entrepreneurial inspiration and entrepreneurial learning.
The strongest relationship was found between entrepreneurial attitudes and entrepreneurial intentions (Table 2.1). While no effect was found for entrepreneurial inspiration or learning influencing entrepreneurial intention, entrepreneurial attitude was found to play a mediating role therefore having a significant indirect effect. The findings between attitude and intent suggest a positive relationship between entrepreneurial attitude development and positive mentoring and modelling. This programme highlights the shift away from traditional skills and knowledge-based learning styles to those that foster development of attitudes, emotions and mindsets. This conclusion could be helpful in designing future entrepreneurship programming for young women.
Table 2.1. Entrepreneurial intentions among young female students are driven by entrepreneurial attitudes
Source: (Shahin et al., 2021[23])
Characteristics of women’s entrepreneurship
Women entrepreneurs are about as likely as men to introduce new products and services
Nearly one-third of entrepreneurs in the EU reported that they introduced new products and/or services between 2016 and 2020, and there was virtually no gender gap. Almost 30% of women entrepreneurs in the EU reported that they introduced new products and/or services to their clients relative to about 32% of men entrepreneurs (Figure 2.25). These proportions were about the same in OECD countries (32% of women and 35% for men). Early-stage women entrepreneurs were more likely to report introducing a new product or service than men in Estonia, Finland, Greece, Ireland, Italy and the Netherlands.
Figure 2.25. Nearly one-third of women entrepreneurs report introducing a new product or service
Note: All EU Member States participated in the GEM survey between 2016 and 2020 except for Belgium, Czech Republic, Denmark, Lithuania, Malta and Romania. Furthermore, the following countries did not participate in the survey in every year over this period (years of participation are indicated): Austria (2016, 2018, 2020), Bulgaria (2016-18), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Latvia (2016-17, 2019-20) and Portugal (2016, 2019). Similarly, the following OECD countries did not participate in the GEM survey between 2016 and 2020: Belgium, Czech Republic, Denmark, Iceland, Lithuania and New Zealand. The following countries did not participate in the survey in every year (years of participation are indicated): Australia (2016-17, 2019), Austria (2016, 2018, 2020), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Japan (2017-19), Latvia (2016-17, 2018-19), Mexico (2016-17, 2019), Norway (2019-20), Portugal (2016, 2019) and Turkey (2016, 2018).
Women entrepreneurs are 20% less likely to report having customers in foreign markets
Nearly half of early-stage entrepreneurs in the EU reported selling their products and services to customers in a foreign country, but women were 20% less likely than men to have foreign customers. Between 2016 and 2020, about four-in-ten early-stage women entrepreneurs in the EU self-reported having customers in another country relative to more than half of men (52%) (Figure 2.26). These proportions were slightly higher than those reported in OECD countries over this period – 39% for early-stage women entrepreneurs and 45% for early-stage men entrepreneurs – likely due to the low barriers to trade within the EU.
The gender gap in the share of early-stage entrepreneurs who self-report having foreign customers varies greatly across EU Member States. Women were slightly more likely to report that they exported their products and services in Finland and Bulgaria, and the gender gap was less than 3 p.p. in Poland, Portugal and Spain. However, early-stage women entrepreneurs in Hungary were only 60% as likely as early-stage men entrepreneurs to have foreign customers.
Figure 2.26. About four-in-ten women entrepreneurs report having customers in other countries
Note: All EU Member States participated in the GEM survey between 2016 and 2020 except for Belgium, Czech Republic, Denmark, Lithuania, Malta and Romania. Furthermore, the following countries did not participate in the survey in every year over this period (years of participation are indicated): Austria (2016, 2018, 2020), Bulgaria (2016-18), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Latvia (2016-17, 2019-20) and Portugal (2016, 2019). Similarly, the following OECD countries did not participate in the GEM survey between 2016 and 2020: Belgium, Czech Republic, Denmark, Iceland, Lithuania and New Zealand. The following countries did not participate in the survey in every year (years of participation are indicated): Australia (2016-17, 2019), Austria (2016, 2018, 2020), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Japan (2017-19), Latvia (2016-17, 2018-19), Mexico (2016-17, 2019), Norway (2019-20), Portugal (2016, 2019) and Turkey (2016, 2018).
Women entrepreneurs are less likely to expect their new businesses to achieve high employment growth
Only small percentage of entrepreneurs are successful at turning their start-up into a high growth firm and women are half as likely as men to expect to achieve this. Between 2016 and 2020, fewer than 5% of early-stage women entrepreneurs in the EU expected that their new start-up would create at least 19 jobs in the next five years relative to 13% of early-stage men entrepreneurs (Figure 2.27). These proportions were substantially below the proportions of early-stage entrepreneurs who expected this level of growth in OECD countries: 11% of early-stage women entrepreneurs and more than 17% of early-stage men entrepreneurs.
More than 10% of early-stage women entrepreneurs in Hungary and Ireland reported that they expected to create at least 19 jobs over the next five years. Early-stage women entrepreneurs in Ireland were among the most likely to report introducing new products and services and selling to customers in foreign markets, which can fuel business growth. In Hungary, these positive attitudes are somewhat inconsistent with other responses to the GEM survey. While early-stage women entrepreneurs were more likely than the EU to report that they had clients in other countries, they were among the least likely to report that they introduced new products and services.
However, virtually no women entrepreneurs in Italy and Greece (less than 1% in each), Spain (2%) and Luxembourg (3%) expect high growth in the next five years. These low rates can be explained by various factors including difficult domestic market conditions or small local markets, lower export rates and lower growth ambitions. In Finland, where growth expectations are below the EU average, research confirms low levels of entrepreneurial aspirations among women but notes that those aspirations among women vary according to business size and sector (Autio, 2017[24]). Those who already have at least one employee are nearly twice as likely to have a willingness to grow (24% vs. 13% for solo self-employed), while those working in agriculture and forestry have very low growth ambitions (Sutela and Pärnänen, 2019[11]).
Figure 2.27. Few women entrepreneurs in the EU expect high growth
Note: All EU Member States participated in the GEM survey between 2016 and 2020 except for Belgium, Czech Republic, Denmark, Lithuania, Malta and Romania. Furthermore, the following countries did not participate in the survey in every year over this period (years of participation are indicated): Austria (2016, 2018, 2020), Bulgaria (2016-18), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Latvia (2016-17, 2019-20) and Portugal (2016, 2019). Similarly, the following OECD countries did not participate in the GEM survey between 2016 and 2020: Belgium, Czech Republic, Denmark, Iceland, Lithuania and New Zealand. The following countries did not participate in the survey in every year (years of participation are indicated): Australia (2016-17, 2019), Austria (2016, 2018, 2020), Estonia (2016-17), Finland (2016), France (2016-18), Hungary (2016), Ireland (2016-19), Japan (2017-19), Latvia (2016-17, 2018-19), Mexico (2016-17, 2019), Norway (2019-20), Portugal (2016, 2019) and Turkey (2016, 2018).
Conclusions
There continues to be a gender gap in self-employment and entrepreneurship, both in terms of activity rates and also in the types of activities undertaken. The reasons for this gap are not so clear-cut. Some of the gender differences can be explained by the institutional barriers that constrain women in entrepreneurship, including family and tax policies that discourage labour market participation and entrepreneurship, and negative social attitudes towards women’s entrepreneurship. In addition, there are market failures that make it more difficult for women to be successful in business creation and self-employment. This includes, for example, bias in financial markets and public policy initiatives that are not effective at reaching potential women entrepreneurs.
Governments have responded to these market and institutional failures with a range of policy interventions, including training, coaching and mentoring, microfinance and support for women’s entrepreneurship networks and support organisations. Progress can be seen as the gender gaps have been closing, albeit slowly. While policy has a role, many other factors have also influenced the closing of the gap. This includes, for example, increasing education rates and labour market participation rates. Much work remains and COVID-19 has renewed the urgency of policy action because the pandemic and policy response appear to have increased the gender gap in entrepreneurship.
Countries can reap many benefits if governments continue to pursue this agenda. Estimates show that GDP increases when the gender gap in entrepreneurship closes and there is untapped potential in terms of innovation and job creation among potential women entrepreneurs. Government priorities will depend on context but overall, policy priorities includes:
Greater use of tailored support for women entrepreneurs;
Strengthen policy frameworks that underpin programmes so that support systems become more cohesive and efficient; and
Increase efforts to measure women’s entrepreneurship activities and the impacts of policy, which can improve the quality of programmes, strengthen knowledge sharing and increase the number of successful policy transfers.
For further policy discussion on women’s entrepreneurship and related policy actions, please refer to (OECD/EU, 2016[4]). Examples of recent policy actions to support women’s entrepreneurs are highlighted in Chapters 7 and 8, as well as several country profiles in Part III of this report.
References
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