Analytical Studies Branch Research Paper Series
Labour Market Experience, Gender Diversity and the Success of Women-owned Enterprises

Acknowledgements

This study is funded by Women and Gender Equality Canada. The author would like to thank reviewers from Women and Gender Equality Canada, and from Innovation, Science and Economic Development Canada and colleagues at Statistics Canada.

Abstract

This study investigates the relationships between ex-ante (i.e., prior to entry) socio-economic characteristics of entrants into business ownership (defined as ownership of private incorporated businesses) and two performance indicators of their enterprises (revenues and number of employees). The entrants into business ownership are defined as those who are business owners in the current year but were not in the previous year. This means that an individual can become an entrant by starting an enterprise or acquiring shares of an existing private enterprise. The study takes advantage of the Canadian Employer–Employee Dynamics Database (CEEDD), which allows the analysis of the role of personal characteristics, labour market experience, and family characteristics of the entrants over the 2001-to-2015 period. In the data, majority men-owned enterprises with entrants performed better than their majority women-owned and equally-owned counterparts. The analysis contributes to the explanation of these patterns by showing how labour market experience differs across gender and how important it is for performance. Specifically, the descriptive statistics show that men entrants were more likely than their women counterparts to be the owner of an unincorporated business in the year preceding entry, more likely to have experience in the same industry as the business owned over the five years preceding entry, and more likely to have worked in the same firms as their business partners. The regression-based analysis indicates that these factors were strongly and significantly correlated with performance across all ownership types of enterprise. Interestingly, the analysis also shows that adding gender diversity to the ownership structure of the enterprise is positively correlated with both performance indicators. The results are robust to different specifications including restricting the analysis to new enterprises only.

Keywords: business ownership, gender, gender diversity, men-owned enterprises, women-owned enterprises, equally-owned enterprises, business performance

Executive summary

Studies have found that women-owned enterprises lag men-owned enterprises in business performance such as sales, profits and employment. This lower performance has been attributed to several factors like financial constraints, industrial sector or lack of prior relevant experience. However, the studies that investigated the role of prior experience often lacked detailed quantitative evidence. This paper fills this gap by taking advantage of the Canadian Employer–Employee Dynamics Database (CEEDD) over the 2001-to-2015 period.

Business ownership in this paper is defined as ownership of private incorporated businesses captured through an administrative tax schedule (T2 Schedule 50). The entrants into business ownership are identified as the business owners who are present in the current year but not in the previous year. This means that an entrant can do so by starting an enterprise or acquiring shares of an existing private enterprise.

The paper starts by comparing the socio-economic characteristics of men and women in the years preceding entry into business ownership. The results show important differences across gender, which suggest that men entrants seem to have more pertinent labour market experience than their women counterparts. Indeed, in the year preceding entry, women entrants were proportionately less likely to be self-employed (i.e., the owner of an unincorporated enterprise throughout this paper, which could serve as training for incorporated business ownership). Over the five years preceding entry, they were less likely to have acquired experience in the industry in which their enterprise operates, and earned about a third less income than their men counterparts. Although women entrants had a higher propensity to have business partners, they were twice as likely to have their spouse as a partner, and were less likely to have worked with their business partners in the same firm.

Women entrants had more children, accumulated a third less personal income but had a higher family income over the five years preceding entry.

The regression-based analysis shows that the labour market experience of entrants was strongly positively correlated with two business performance indicators (revenues and number of employees). Specifically, it is shown that having experience as a self-employed person, sharing work experience with business partners, and having experience in the industry in which the enterprise owned operates were all strongly correlated with performance across types of enterprises (majority men-owned, majority women-owned and equally-owned) and gender of entrants. The regression results do not identify a causal relationship because, for example, previous experience as a self-employed person could be related to an unobservable factor important for success such as personal wealth.

Interestingly, the results from the regressions also show that having women entrants in majority men-owned enterprises or men entrants in majority women-owned enterprises was positively correlated with performance. In other words, adding gender diversity to the ownership structure of the enterprise is correlated with better performance.

Finally, the results show a strong tendency for the correlations between ex-ante characteristics (personal, labour market experience, family characteristic) and both performance indicators to be in the same direction. The only exceptions are the three variables pertaining to having children in different age categories (under 7 years old, between 7 and 16 years old, and in both categories). These variables had positive correlations with performance for women entrants and men entrants in women-owned enterprises but non-significant correlations with revenues and negative correlations with employment for men entering majority men-owned or equally-owned enterprises. The consistency of these results with selection processes is discussed.

The paper contributes to the explanation of the difference in performance between men-owned and women-owned enterprises by highlighting how labour market experience differs across gender and how important it is for performance. The results are robust to different specifications including restricting the analysis to new enterprises only.

The policy relevance of the paper is twofold. First, it informs policymakers by providing a better understanding of important gender differences in the socio-economic profile of entrants. Second, it highlights characteristics that matter for performance and, therefore, it potentially helps the design of programs aiming at improving the performance of businesses owned by women. This is important in the post COVID-19 recovery context. Indeed, the pandemic is likely to affect women and their enterprises more severely than their male counterparts since they are prevalent in the service sector.

1 Introduction

Although initiatives promoting women’s entrepreneurship have been adopted in Canada and in many other countries to stimulate stronger, better and fairer growth (Adema et al. 2014), majority women-owned private enterprises (WOE) still lag behind majority men-owned private enterprises (MOE) in terms of numbers, business performance such as sales, profits and employment (Fairlie and Robb 2009; Coleman and Robb 2009; Industry Canada 2015; Rosa and Sylla 2016; Grekou, Li and Liu 2018a) or survival rates (Couture and Houle forthcoming). This paper addresses three main questions: (1) What are the differences in socio-economic characteristics between women and men prior to the creation of their business? (2) What is the relationship between these characteristics, especially prior labour market experience, and the performances of their firms? (3) Are there major gender differences in the correlation of prior labour market experience and the success of their firms?

Previous studies have provided explanations for the lower performance of WOE. They have shown that, compared to their men equivalents, women entrepreneurs have less access to capital, weaker representation in key networks, less management experience, and are often more constrained with regards to business and technical education as well as access to training (Stevenson 1986; Adema et al. 2014).^Note Also, the literature shows that the industrial sectors in which women entrepreneurs operate, their personal characteristics and preferences, as well as their management strategies play a role in explaining their lower business outcomes (Rosa and Sylla 2016). Some authors, however, argue that gender differences partly disappear once key characteristics of the business owners are controlled for (Gottschalk and Niefert 2011).^Note Finally, it was found that, although the perception of opportunity to start a business was similar among Canadian men and women, their perception of necessary skills and experience differed (Gregson et al. 2017).

An important limitation of the literature, however, is the lack of quantitative evidence on the role of previous labour market experience. Although a few studies (e.g., Stevenson 1986; Fairlie and Robb 2009) discuss evidence of the adverse effect of women having less managerial experience and work experience, they do not offer an in-depth analysis of the importance of previous labour market experience. Generally, evidence of the role of prior labour market experience relies on anecdotal information (e.g., profile of women entrepreneurs like Entrepreneur.com 2008), case studies (Carter and Cannon 1992; Koehn 2001), or survey data with limits on the scope of such analysis (Fairlie and Robb 2009; Gatewood et al. 2009).

The paper investigates the relationships between ex-ante (i.e., prior to entering business ownership) characteristics of the business owners with the performance of their enterprises. It takes advantage of Statistics Canada’s Canadian Employer–Employee Dynamics Database (CEEDD), a matched database developed using administrative data sources over the period 2001 to 2015. The CEEDD allows for the identification of individuals entering business ownerships, provides information on socio-economic characteristics of the individuals (e.g., age, immigration status, previous employment status, experience in a given industry) and their family (e.g., family income, children) during the years preceding entry, as well as information about the enterprise owned.

The importance of the paper for policymaking is twofold. On one hand, it informs about the important gender differences that exist in the socio-economic profile of entrants. On the other hand, it potentially helps the design of programs aiming at improving the performance of businesses owned by women by highlighting key characteristics.

The paper is organized as follows. Section 2 presents the data and methodology. Section 3 discusses the ex-ante characteristics of entrants. Section 4 discusses the multivariate analysis, which looks at the correlations between these characteristics and business performance. Section 5 concludes the paper.

2 Data and methodology

2.1 Data

The paper relies on Statistics Canada’s CEEDD, which has been described in detail in Green et al. (2016), Grekou and Liu (2018), and Grekou, Li, and Liu (2018b).

The CEEDD is a matched database developed by linking several administrative tax files, including individual tax files (T1, Personal Income Tax and Benefit Return); individual employment remuneration files (T4, Statement of Remuneration Paid); individual business ownership files (T1 Financial Declaration [FD] for unincorporated business owner, and T2 Schedule 50 for incorporated business owner); Immigrant Landing File; family file (T1 Family File); corporate business tax files (T2, Corporation Income Tax Return) and unincorporated business tax files (T1 Business Declaration [BD]). All files are available from 2001 to 2015, except the unincorporated business files and the unincorporated business owners’ files, which are available from 2005 to 2015.

The CEEDD therefore provides information on the individuals and the businesses they own or work for. Specifically, it contains detailed information about paid workers and business owners such as age, gender, marital status, immigrant status, earnings from paid jobs, self-employment income, and income from owned corporations. This information is augmented with information on their workplace, such as industry, number of employees, payroll, revenues and profits.

For the purpose of this paper, the universe of business owners is restricted to the T2 Schedule 50, i.e., the owners of private incorporated business with at least 10% ownership share.^{Note Note}

2.2 Defining entrants and variables of interest

The entrants into business ownership in this paper are defined as those who are business owners in the current year but were not in the year before.^Note This means that an entrant can do so by starting a business or acquiring shares of an existing private enterprise. The multivariate analysis in Section 4 below will discuss the important differences that exist between the two cases. For each year, the analysis is restricted to individuals aged 18 to 80.

One objective of the paper is to depict the profile (e.g., age, immigrant status, family income, number of children) and labour experience (e.g., employment status, experience in a given industry) of the entrants prior to entry and to determine differences that may exist across gender. The variables are constructed using information from the year preceding entry or, when applicable, by cumulating information observed over the five years preceding entry. For example, when looking at a 2010 entrant, variables are constructed using the year 2009 and cumulatively over the 2005-to-2009 period. The utilization of five years before entry implies that the analysis focuses on the 2006 to 2015 cohorts of entrants.

The correlations between these characteristics and two performance indicators of the enterprise (revenues and number of employees) are then explored through multivariate analysis in the year of entry into business ownership.^Note The detailed definition of variables can be found in Table A.1 in the Appendix.^Note

3 What are the ex-ante characteristics of the entrants?

Over the 2006-to-2015 period, the number of entrants fluctuated around 143,000 (Table 1). Men accounted for about 62% of the total number of entrants while women accounted for about 38% (Table 1). The trends for men and women were the same over this period. Hence, the number of entrants started at the peak in 2006 and declined until they reached a minimum in 2009 during the economic crisis. This result is consistent with BDC (2012), Fairlie (2014), Cao et al. (2015), and Grekou and Liu (2018) who found a decrease in entry rates due to the global financial crisis. Afterwards, the number of entrants increased, although a decline can be observed after 2012.

This section shows that men and women have statistically significant differences with respect to ex-ante characteristics, which include demographic characteristics, total income, labour market experience and networking, and family characteristics (Table 2). The aim is not to explain why these differences exist but rather to expose them before analyzing their correlations with performance by means of multivariate analysis (Section 4 below).

3.1 Demographic characteristics

Women entrants were slightly older and were relatively less likely to be immigrants than their men counterparts.

On average, women entrants were slightly older than their men counterparts (42 versus 41 for men, Table 2).

The share of immigrants among men entrants was higher than the share of immigrants among women entrants (29.95% versus 27.08% for women). It can also be noted that the share of recent immigrants—defined as those who became permanent residents 5 years or less before entry into business ownership—is lower by a factor of about 3. This is likely related to the fact that recent immigrants have less time or ability to accumulate resources to become a business owner. Among recent immigrants, men were relatively more likely to enter into business ownership.

3.2 Income, labour market experience and networking (partners)

Women earned a third less income than their men counterparts over the five years preceding entry into business ownership.

Women entrants earned less (before-tax) income than their men counterparts over the five years preceding entry (Table 2). On average over the period of study, the cumulative income for men was higher by about a third whether one looks at the mean cumulative income (higher by $114,000) or the median cumulative income (higher by $62,000). 

Women were relatively less likely to be self-employed in the year preceding entry into business ownership.

The CEEDD allows for the identification of mutually exclusive categories for entrants: employed only (paid job), owner of an unincorporated business (i.e., the “self-employed” throughout this paper) only, employed and self-employed (i.e., with both statuses), and non-employed (i.e., not in the other three categories).^{Note Note} Presumably, experience as a self-employed prepares individuals to business ownerships as they would acquire management skills and networks of suppliers and clients.

Although men and women had very close proportions of employed only (49% for men versus  48% for women), men had higher labour market participation (Table 2). Indeed, the proportions of self-employed only (20% for men versus 17% for women), employed and self-employed (20% for men versus 18% for women) and non-employed (11% for men versus 16% for women) showed that men not only participated more but were also more likely to have acquired self-employed experience prior to entry. These results are qualitatively similar to Grekou and Liu (2018, Table A.1).

With respect to labour status over the five years that preceded entry, although a minority of men and women entrants had been business owners for at least one year, men entrants were proportionately more likely to have been so (9% versus 7%, respectively).

Women entrants had less experience in the industry in which their enterprise operates.

Prior experience in the industry of the enterprise owned can be constructed from the CEEDD in four steps. First, the two-digit North American Industry Classification System (NAICS) of the enterprise at entry is determined. Then, for each of the five years that precedes entry, the two-digit NAICS of the enterprises the entrant worked for, either as an employee or as a business owner (incorporated or unincorporated) are determined. Third, for each of these five years, a dummy indicator is created flagging whether the NAICS of the enterprises correspond to the NAICS at entry. Finally, the dummy variables are summed to generate two simple cumulative NAICS experience indicators: one indicating whether the entrant has such experience or not, and the other summing up the number of years of experience in that NAICS. ^{Note Note}

Men were more likely to have experience in the same industry (37% versus 31% for women, Table 2), and, when they have such an experience, they tended to have accumulated it for slightly more time than women (3.3 years versus 3.2 years for women). Less industry-related experience might be disadvantageous since it could negatively affect the enterprise’s performance.

Women entrants were relatively more likely to have business partners and more likely to have a spouse as a business partner.

From 2006 to 2015, women entering business ownerships had, on average, a higher propensity to have business partners than their men counterparts (66% of women entrants versus 49% of men entrants, Table 2). Furthermore, half of women had their spouse as a business partner, compared to one-quarter of men. Exploring the interactions between the entrants and their partners at entry shows that, over the five years that preceded entry, men were proportionately more likely to have worked in the same firms as their partners.

3.3 Family characteristics

Women entrants were relatively more likely than men entrants to be in couple or to have children.

Although both women and men were mainly in couples, the category “married or in common-law partnership” was proportionately more likely for women (77% versus 71% for men, Table 2). Men entrants were proportionately more likely to be single (22% versus 14%).

Women who entered business ownership were on average more than twice as likely to have at least one child under 7 years old than their men counterparts (7% versus 3%). Similar patterns apply to the number of children from 7 to 16 years old (not shown).

Like family-work balance that can affect the decision to enter business ownership (Jeon and Ostrovsky 2016), differences in family characteristics between men and women could play a role in the performance of their enterprise. 

Women entrants had higher family incomes than their men counterparts and were more likely to have spouses who owned a business.

Although women entrants’ own income tended to be lower than men entrants (Subsection 3.2 above), women’s family income was 14% higher (about $67,000) on average and 12% higher ($44,000) when calculated using the median income (Table 2). This is not entirely surprising as women were more likely than men to be married or in a common-law relationship.

The spouses of women entrants were more likely to be self-employed or business owners than the spouses of men entrants. Indeed, in all employment categories involving self-employment or business ownership, the shares of spouses of women entrants were proportionately higher than their men counterparts. This is in line with the fact that women were more likely to have their spouse as a business partner (Subsection 3.2 above). Importantly, the spouses of men entrants were more likely to be non-employed than their women counterparts.

4 What variables were correlated with the performance of the enterprises?

4.1 Estimation strategy

Variables of interest

As described in Subsection 2.2 above, two performance indicators (revenues and number of employees) are analyzed in the year of entry into business ownership. The analysis is implemented for majority men-owned private enterprises (MOE), majority women-owned private enterprises (WOE) and equally-owned private enterprises (EOE).^Note

The distribution of the performance indicators for enterprises with at least one entrant shows that MOE are more frequent in the top categories (more than $500,000 in revenues in Chart 1 and 5 employees or more in Chart 2). Furthermore, the median revenues among enterprises with at least one entrant were higher for MOE ($41,000 versus $35,000 for WOE and $38,000 for EOE). Similarly, the median number of employees was slightly higher among MOE (2 versus 1 for both WOE and EOE). The better performance of MOE are also found when analyzing the means (unconditional or focusing on enterprises with at least one employee during 6 months).

Sets of regressions

The goal of the regressions is to understand the relationships between the characteristics of entrants and the performance of their businesses (which may have more than one entrant in a given year).

The estimation strategy relies on ordinary least squares regressions that correct for heteroscedasticity and cluster residuals at the enterprise level. The dependent variables are the natural logarithms of the performance indicators and the regressions control for a set of characteristics in the year of entry (e.g., age, immigrant status, having a spouse, number of businesses and characteristics of the enterprise owned), ex-ante characteristics (e.g., income, own labour market experience and number of children by age category) (Table 3).

Two sets of regressions are estimated. In the first set, the regressions are implemented by type of enterprises (MOE, WOE or EOE). In the second set, the regressions are implemented by type of enterprises and gender of the entrants, which allows to analyse differences across gender within types of enterprises. The regressions pool all years together but include dummy variables for the year of entry into business ownership.^{Note Note}

Because individuals entering business ownership can do so by acquiring shares of existing enterprises, regressions focusing on new enterprises only are also shown in the Appendix. However, to keep the discussion concise, these results are mentioned only when notable differences exist.

Interpretation of the coefficients

It is important to note that the coefficients from the regressions should be interpreted as correlations rather than effects. Although lagged variables are introduced, simultaneity (for example a shock correlated with current firm revenues and lagged family income) remains a potential risk. Similarly, businesses performing well may attract or limit business ownership to entrants that have specific experiences/characteristics. The opposite applies to businesses that do not perform well.

In other words, a positive coefficient, for example, of family income on revenues, suggests that entrants with higher income tended to own enterprises with higher revenues. At the same time, it can also be interpreted as meaning that enterprises with higher revenues tended to have entrant owners who had higher income. In short, such a coefficient means that higher incomes are positively associated with higher revenues.

4.2 Results by type of enterprises

Adding gender diversity to the ownership structure was positively associated with both performance indicators in MOE and WOE.

The results show that having entrants from the minority gender was positively associated with revenues and number of employees. Specifically, the results suggest that MOE with at least one woman entrant and WOE with at least one man entrant tended to have higher revenues and more employees than their respective counterparts with only men or women entrants (Tables 4 and 5).^Note The results can also be interpreted as showing that MOE and WOE with better performance foster diversity. Interestingly, the results for EOE suggest that having at least one woman entrant is negatively associated with revenues and positively associated with the number of employees.

These results align with the growing body of evidence linking gender diversity within enterprises and performance. Recent reports by consulting firms suggest that enterprises with more women had (1) higher stock prices than their peers even after controlling for size, yield, profitability and risk (Morgan Stanley), (2) higher financial returns above their respective national industry medians (McKinsey) and (3) more overall innovation (Boston Consulting Group).^Note Despite scarce quantitative evidence on the exact mechanisms under which gender-diversity fosters better performance, it seems gender-diversity relates positively with trust and employee engagement (Downey et al. 2015), which favor performance.

Being primarily a business owner, being older were positively associated with performance. Being an immigrant—especially a recent immigrant—was negatively associated with performance.

Unsurprisingly, there was a strong correlation between performance and the fact that business ownership was the main activity of the individual. Age was positively associated with both performance indicators and across all types of enterprises, however at a diminishing rate as captured by the negative coefficients on age squared.

Being an immigrant and being a recent immigrant were negatively associated with both performance indicators across all types of enterprises. The only exception was a non-significant coefficient associated with being a recent immigrant for employment in EOE (Table 4).

Having a spouse, whether a business partner or not, tended to be positively associated with revenues. Having a spouse as a business partner was negatively associated with employment.

There were significant positive associations between having a spouse who is not a business partner and both performance indicators, except with revenues in WOE.

Having a spouse as a business partner was positively associated with revenues for all types of enterprises. However, the correlations suggest that businesses owned by both spouses tended to have fewer employees than their counterparts where the entrant does not have a spouse. These results are fairly intuitive. Businesses with both spouses as worker owners will require less additional employment than their counterparts with a single worker owner.

The strong correlations associated with having a spouse (as a business partner or not) and the fact that women were more likely to have a spouse (Table 2, Subsection 3.2 above) suggest that this variable is important for women entrants.^Note

For new enterprises, although the sign and significance of the correlations associated with spouses remain the same for most cases, a few changes can be observed (Tables A.2 and A.3 in the Appendix). Specifically, the relationships change signs (spouse not a partner and revenues in WOE turned negative; spouse a partner and employment in MOE turned positive) or lose significance in employment (spouse not a partner in EOE and spouse a partner in WOE and EOE). Hence, the role of the spouse seems more relevant once an enterprise is already established.

The number of enterprises owned and the number of business partners were positively associated with performance contrary to owning a new enterprise.

The results pertaining to the number of enterprises owned were consistent with the literature showing that enterprises operated by serial entrepreneurs (i.e., individuals who own multiple enterprises) have better performance in terms of sales, productivity and longevity (Shaw and Sorensen 2017; Lafontaine and Shaw, 2016). However, the results restricted to new enterprises only suggest that enterprises owned by serial entrepreneurs tended to generate less revenues than their counterparts with only one enterprise (Table A.2 in the Appendix).

The number of business partners tended to be positively associated with revenues and with the number of employees. Because women were more likely to have business partners (Subsection 3.2, Table 2 above), the results suggest that this variable contributed more for enterprises owned by women. However, the results restricted to new enterprises only suggest that having multiple business owners was negatively associated with revenues in EOE (Table A.2 in the Appendix).

Also, as could be expected, owning a new enterprise is negatively associated with both performance indicators.

Having experience in the same industry in which the enterprise operates and sharing work experience with business partners were strongly positively associated with performance.

Positive associations were found between both performance indicators and two variables pertaining to experience: having experience in the industry in which one’s enterprise operates and sharing work experience with business partners. Because men were more likely to have such experiences (Subsection 3.2, Table 2 above), the results suggest that the variables contributed more for enterprises owned by men.

Being self-employed only had strong positive correlations with both performance indicators. Being employed and self-employed or being employed only also had positive associations.

Across all regressions, the coefficients associated with being self-employed only had the strongest magnitude among labour status variables. Being employed and self-employed tended to have the second highest magnitude. These results highlight the importance of self-employment as a step helping individuals acquire experience and knowhow that serve them when their enterprise incorporates.^Note

Interestingly, having previous experience as a business owner tended to yield negative correlations with both performance indicators and all types of enterprises. This result is surprising since it was expected to be positively associated with better performances. However, an entrant’s previous status as a business owner might indicate that they had an earlier business which failed. It may therefore capture failure to maintain the business owner status rather than experience itself. The correlation between previous experience and performance shall be explored in a different setup than the one proposed in this paper by looking at all business owners, not just entrants, and for a period that goes beyond the year of entry.

Family cumulative income was associated with better business performance.

The correlations pertaining to family income were positive for both revenues and number of employees and across all types of enterprise. Better business performances were therefore associated with higher family income.

The fact that the levels of family income were higher for women (Subsection 3.3, Table 2 above) suggest that this variable is more important for the success women’s enterprises.^Note

Having children tended to be positively associated with revenue but there were inconsistent signs and significance of correlations with employment.

Contrary to findings showing that having young children could affect entry into business ownership (Jeong and Ostrovsky 2016), the results here show inconsistent signs of correlation between having children and performance.

Positive correlations were found across all types of enterprises and age categories. The associations with employment, however, showed inconsistency. When significant, they were negative in MOE, positive in WOE and of both signs in EOE (negative for having children aged under 7 and positive having children in both categories).

Interestingly, when focusing on new enterprises only and having children, the only notable difference was the loss of significance for all correlations with employment in WOE (Table A.3 in the Appendix). In other words, the number of employees in new WOE with entrants having children were not significantly different than their counterparts with entrants without children.

4.3 Results by type of enterprises and gender of entrants

The second set of regressions adds the gender of the entrant as a dimension for the regressions. The tables present the coefficients for men and women across types of enterprises and also present the p-values from testing whether the coefficients are different across gender (Tables 6 and 7).^Note To avoid repetition and because results are qualitatively similar to the ones depicted above, the discussion focuses on the variables with opposite signs across gender that are statistically significant.

There was a strong tendency for correlations to have the same signs across gender. However, significant differences in magnitudes were found.

For both performance indicators and across types of firms, the coefficients for men and women had the same signs and tended to follow the same patterns depicted in Subsection 4.2 above. This means that, despite the important ex-ante differences described earlier, characteristics and performance indicators tended to have the same association (positive or negative) for men and women.

Nevertheless, differences in the magnitudes of the correlations existed and were often statistically significant as illustrated by the number of cases with p-values lower than 0.1.

The age categories of children had positive associations with both indicators for women entrants and men entering WOE. However, they had non-significant associations with revenues and negative associations with employment for men entering MOE or EOE.

For women entrants, having children had positive associations with all performance indicators (Tables 6 and 7, Models 2, 4, and 6). For men, the correlations associated with having children tended to be non-significant with revenues (except positive associations in WOE, Table 6, Models 1, 3 and 5), negative with employment in MOE and EOE (Table 7, Models 1 and 5) and positive with employment in WOE (Table 7, Model 3).

These results mean that, overall, the enterprises with women entrants with children tended to outperform the enterprises with women entrants without children. Men entering WOE exhibited similar patterns. However, the relation for men entering MOE and EOE was non-significant with respect to revenues and reverse with respect to employment.

Although more evidence is necessary to fully explain the results, they are consistent with selection processes. For example, women with children who are able (and willing) to become business partners are likely to have unobserved characteristics (e.g., specific management skills, capacity/willingness to negotiate flexible work arrangements or benefits) that distinguish them from their counterparts with no children. Also, enterprises that perform well are more likely to offer packages that may be more attractive to women entrants with children than to their counterparts without children. These unobserved characteristics of entrants and firms would foster positive assortative matching and contribute to explain the results.

The results focusing on new enterprises only reinforce the hypothesis that selection processes play a role (Tables A.4 and A.5 in the Appendix). Indeed, the differences observed between men and women are still present but become blurred as the positive correlations observed for women having children turn into negative or non-significant correlations.

5 Conclusion

The paper has shown important differences in the socio-economic characteristics of men and women prior to entering business ownership but also important similarities in the correlations between these characteristics and two business performance indicators (revenues and number of employees).

The descriptive statistics suggest that men entrants seem to have more pertinent labour market experience than their women counterparts. Indeed, in the year preceding entry, women entrants were proportionately less likely to be self-employed. Over the five years preceding entry, they were proportionately less likely to have acquired experience in the industry in which their enterprise operates, and earned about a third less income than their men counterparts. Although women entrants had a higher propensity to have business partners, they were twice as likely to have their spouse as a partner, and were less likely to have worked with their business partners in the same firm.

Women entrants had more children, accumulated a third less personal income than their male counterparts but had a higher family income over the five years preceding entry.

The multivariate analysis shows that the labour market experience of the entrants (defined as having experience as a self-employed; having experience in the industry in which the enterprise operates; sharing work experience with business partners of the entrants) was positively associated with both revenues and the number of employees. Adding gender diversity to the business ownership structure was also positively associated with performance. Being older, being Canadian-born, the number of business partners (for existing enterprises), the number of enterprises owned (for existing enterprises), cumulative family income over the five years preceding entry, and having a spouse were positively associated with performance.

Running regressions by types of enterprises and gender of the entrants revealed similarities across gender. However, differences in the signs of the correlations exist with respect to children. The age categories of children had positive associations with both indicators for women entrants and men entering WOE but non-significant associations with revenues and negative associations with employment for other men entrants. These results seem consistent with selection processes fostering positive assortative matching between business performance and specific unobserved characteristics possessed by individuals who have children.

The results of the paper inform policymakers on the important gender differences in the socio-economic profile of entrants and potentially helps the design of programs aiming at improving the performance of businesses owned by women.

It is interesting to note that the profile of women entering business ownership is different from the working women in the top 1% income distribution as described in Richards (2019), especially with respect to family characteristics. For example, working women in the top 1% had fewer children than their men counterparts to the contrary of women entering business ownership. This underlines the importance of studying multiple facets of working women for a better understanding of their profile.

The paper also stresses the importance of taking into account experience and family characteristics of entrants for the performance of firms. Future research shall investigate the role of these characteristics in determining entry into business ownership and understanding performance over periods beyond the entry year. This will help address the important question of whether women entrants are more opportunity-based or necessity-based. Also, the relationship between ex-ante characteristics and the ownership structure of the business (e.g., men majority or women majority) in terms of formation, performance and evolution deserves attention.

6 Appendix 1

6.1 Variable description

6.2 Results restricting the population to new enterprises only

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