Simon C Parker a b c a Durham University, England b University of Victoria, Canada

1. Female EntrepreneurshipDraft chapter 6 of new edition of The Economics of Entrepreneurship (2009, CUP) Simon C Parker a b c a Durham University, England b University of Victoria, Canada c Max Planck Institute and IZA, Germany www.dur.ac.uk/s.c.parker

2. What is entrepreneurship? • Several possibilities: • Residual claimants (self-employed or business owners)? • Small firms (i.e. companies rather than individuals)? • Schumpeterian innovators? • Exploiters of new opportunities? • E.g. New Venture Creation • Each have their drawbacks: • A lot of self-employment is mundane; misses team starts and many nascent entrepreneurs • Small business: ditto above; categorisations are arbitrary (omits entrepreneurship in other firms); emphasis on firm not individual • Only very entrepreneurs truly innovate • Individuals do not cease to become entrepreneurs once they have founded their venture (e.g. entrepreneurial growth) Presentation to the World Bank, 24 January 2008

3. There are usually three main data sources: • Self-employment & business ownership (e.g. national household surveys, OECD) • NVC (GEM) • Small firms (surveys and industry reports) • My view/approach: • These measures are complementary • Be pragmatic: use what data you have (fly under a flag of convenience) • Use multiple dependent variables if you can, to get a more complete picture Presentation to the World Bank, 24 January 2008

4. Plan of talk • Some basic facts • Family factors 2.1 Marriage and household production 2.2 The role of children • Performance of women entrepreneurs • Women and entrepreneurial finance • Conclusion Presentation to the World Bank, 24 January 2008

5. 1. Some basic facts • Huge variation in female self-employment rates across Europe • From 20-23% in UK, Ireland & Sweden, to 40% in Portugal • In Italy, women are • Half as likely to enter entrepreneurship as men • And for different reasons: enter from inactivity or unemployment rather than career advancement or after layoff • And twice as likely to exit… • Trends are less clear; but stasis in UK and US in the 1990s • Women self-employed are disproportionately part-time (compared with women employees and men) • E.g. women comprise only 16% of full-time but fully 70% of part-time self-employees in Britain • Part-timers juggle business with home work; full-timers resemble men • Similar schooling of entrepreneurs by gender • But women have less technical, managerial and prior start-up experience than men, as well as more broken job histories Presentation to the World Bank, 24 January 2008

6. 2. Family factors 2.1 Marriage and household production • Women entrepreneurs are substantially more likely to be married in Europe… • Especially job creators: 9 out of 10 women employers in Britain married • although the same is true of male entrepreneurs • And women entrepreneurs are much more likely to have children • Women continue to do much more housework than men • even when they work too • Helps explain the prevalence of part-time women entrepreneurs? • Having a husband who is an entrepreneur increases the probability a woman becomes one too (strong evidence) • Greater effect than from husbands’ incomes Presentation to the World Bank, 24 January 2008

7. 2.2 The role of children • The “flexibility hypothesis”: women choose entrepreneurship to achieve work-life balance • Crude tests: participation in entrepreneurship likelier for those with more children? • YES on the whole, though # children is probably endogenous • Deeper tests: are work and childcare choices of entrepreneurs and non-entrepreneurs different? • E.g., women entrepreneurs more likely to work from home and provide more child care than women employees? • YES in USA; NO in EU Presentation to the World Bank, 24 January 2008

8. 3. Performance of women entrepreneurs • Relative to men, women run ventures which are smaller, have lower turnover and lower absolute profits • “Hard” Australian evidence: • Women entrepreneurs earn similar relative risk-adjusted rates of return tomen • Same risk-adjusted returns • But their smaller scale leads to lower absolute profits • Social capital: • Women have more homophilious networks and gather less information about opportunities than men • But no evidence yet that this really retards their performance • Self-declared motivations: • Women declare financial considerations less important than men (numerous studies) • So not surprising they earn lower profits? • But should we take these findings seriously? • Self-justification? Social conditioning? Reflecting household and industry variables? • Mixed evidence that women are more risk averse than men in a way that affects performance Presentation to the World Bank, 24 January 2008

9. Performance (contd.) • Decomposition analysis: women’s lower profits reflect: • More housework • Childcare, especially for young children • Industry sector (herding into services, reducing returns there) • The literature finds ambiguous effects from human capital • Women entrepreneurs also have lower survival rates • Unstable work histories affect this (but not male business survival) • Lower growth rates of Swedish women enterprises attributed to • Small scale • Service industry location • Lack of women in lucrative B2B sales Presentation to the World Bank, 24 January 2008

10. 4. Women and finance • Women use similar sources of finance as men but less of it • As much as a third less in aggregate in Britain • Could hamper future growth and survival (evidence from Norway and Sweden) • Even more pronounced for equity finance • But no greater probability of being denied finance once asked for • Discrimination? • Most studies find little or no evidence • And similar levels of satisfaction with lenders by gender nowadays • One NZ sample “does a Levitt” (identical CVs, randomised genders): find significantly higher loan rejection rates for women • But only for women with no more than high school education; and v. small sample • Alternative reasons: simply that less finance is needed: • Smaller scale • Service sector (high exit rates and no inside collateral → need more personal collateral) • Indeed, once industry, size and age of venture are controlled for there is no difference in finance outcomes • Micro-finance schemes promising • Known to have success in getting women into business in S Asia Presentation to the World Bank, 24 January 2008

11. 5. Conclusion • The descriptive groundwork has been done • We know women use less finance to start smaller and shorter-lived businesses on average, located in more competitive sectors • and they are far more likely to combine entrepreneurship with household responsibilities than men are • These factors largely explain gender performance differentials • But deep reasons why women are choosing these sectors, firm sizes, and continue to do most household work are not satisfactorily explained • Multivariate analysis largely rules out gender discrimination in credit markets in western countries • But immature financial markets means this might be a problem in ECA • If you want to promote women entrepreneurship: • Get data at the individual and household level (choices made here) • Accept that most of these firms will be small/part-time & marginal • If finance is a problem, micro-finance schemes might help • Any such policies must recognise the importance of family issues Presentation to the World Bank, 24 January 2008