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Microcredit: an answer to the gender problem in funding?

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Microfinance institutions (MFIs) target people excluded from the traditional banking system. By providing start-up capital to these under-financed individuals, they enable a greater number of women to start their own business, particularly in sectors where initial capital requirements are high. Our study follows a portfolio of 3,640 microcredit applicants in France over the 2000–2006 time period, identifying MFI client profiles and bringing to light gender differences in borrowers compared to a wider sample of entrepreneurs. This study shows that the male–female gap found amongst company creators is also maintained amongst the clienteles of MFIs. Empirical results also suggest that gender is a decisive factor regarding the amount of credit provided to borrowers when comparing with other factors in the borrower and firm profile. Thus to a certain extent, MFIs are found to reinforce gender inequalities in France.

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  1. In France, 31% of microcredit borrowers are unemployed people.

  2. Data for European countries can be found in European Commission (2008).

  3. For a review of gender inequalities and the risks of poverty and social exclusion in 30 European countries, see European Commission (2006).

  4. To our knowledge, the only study is that of Underwood (2006) for the European Microfinance Network.

  5. For more details, see Brana and Jegourel (2011).

  6. In France, the durability rate for 3-year-old firms is 70.4% for firms created by men, and 67.7% for firms created by women.

  7. See for example Boden and Nucci (2000).

  8. However, these studies rely on the same database for the United States (SSBFs).

  9. see Carter and Shaw (2006) for the survey.

  10. See Croson and Gneezy (2009) for a survey of gender differences in preferences.

  11. We excluded data from the few businesses created on a family basis.

  12. For Allen et al. (2007), entrepreneurship through necessity refers to people who start their own business because other employment options are either nil or unsatisfactory. They find that necessity entrepreneurship is much more prevalent amongst women than amongst men.

  13. This result confirms the idea that women generally constitute a lower credit risk in microfinance than men (D’Espallier et al. 2010).

  14. For methodology, see for example Cole and Mehran (2009), Muravyev et al. (2009), or Bellucci et al. (2010).

  15. The correlation between explanatory variables is very low and the variance inflation factors (VIFs) are low (=1.2).

  16. Even if access to subsidies does not vary statistically depending on gender (cf. Table 2).

  17. Of borrowers with non-zero personal assets.

  18. The gap is smaller between men and women for borrowers without own funds. Within this group, women have projects that are lower than men’s by 10.9% and their microcredit amount is lower by 13%.

  19. See also Eurochambres (2006).


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Correspondence to S. Brana.



1.1 Descriptive statistics for dependant and independent variables

See Tables 6 and 7.

Table 6 Dummy variables
Table 7 Quantitative variables

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Brana, S. Microcredit: an answer to the gender problem in funding?. Small Bus Econ 40, 87–100 (2013).

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