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5.0 How is the performance of businesses affected?: Gender Entrepreneurship and Competitiveness in Africa, 2007

Guest post by: World Economic Forum

Article Overview: The analysis of constraints developed in the previous section indicates that, although there are cases in which women are more likely to identify certain obstacles as “major” or “very severe,” men’s and women’s perceptions tend to be in agreement more often than we might have expected.

5.0 How is the performance of businesses affected?: Gender Entrepreneurship and Competitiveness in Africa, 2007

The analysis of constraints developed in the previous
section indicates that, although there are cases in which
women are more likely to identify certain obstacles as
“major” or “very severe,” men’s and women’s perceptions
tend to be in agreement more often than we might have
expected. Even if perceptions of constraints are frequently
similar for men and women, it is important to ask
whether some constraints affect the performance of
female-owned enterprises more than they affect the
performance of male-owned enterprises.

In what follows, two indicators of performance
have been analyzed: value-added per worker and total
factor productivity (TFP).15 A priori, differences between
female- and male-owned enterprises may be expected,
due, for example, to women facing greater difficulties
than male entrepreneurs in managing their enterprises.
Or, conversely, differences may be due to women entrepreneurs
being a very selected sample, because they had
to face greater obstacles than men to start their businesses
in the first place.

The value-added per worker is very similar for men
and women, as Figure 4 illustrates.This analysis disaggregates
the results presented in Chapter 1.2 by sex of
the owner of the enterprise. Only in three countries
(Tanzania, in favor of women; Namibia and Botswana, in
favor of men) is there a statistically significant difference
between the median of the value-added per worker of
the two groups of entrepreneurs.

Women entrepreneurs are also fairly equally distributed
across quintiles of TFP—see Figure 5.16Women are
not overrepresented at the top of the distribution of
TFP, nor are they overrepresented at the bottom.
These results suggest that, once men and women
entrepreneurs are in business (and survive in business),
they face on average the same conditions, and their
enterprises display very similar levels of value-added per
worker and TFP. It may be that, if selection of women
into entrepreneurship is tougher than for men, higher
unobservable characteristics of women compensate for
higher obstacles that they may be facing as women, but
the net result is essentially one of no difference in productivity.

The positive message, therefore, is that in Africa
women’s enterprises can be just as productive as men’s.
What about the impact of business constraints on
firm productivity? Even in this case there is no evidence of the performance of female-owned enterprises being
disproportionately negatively affected.

Figure 6 shows
the relationship between median value-added per worker
(by sex of the business owner) and the severity of two
constraints that are generally identified as gender-adverse:
corruption (measured by the percentage of entrepreneurs
forced to pay bribes to obtain a service or a license,
Figure 6a) and access to finance (measured by the average
percentage of working capital financed by “formal”
sources—from local or foreign commercial banks, leasing
arrangements, investment funds, trade credit, credit
cards, Figure 6b—and by all types of external sources,
including informal networks, Figure 6c). In this case, the
chosen constraints are more “objective” than the perceptions
of entrepreneurs about the severity of an obstacle,
analyzed in the previous section.

The negative relationship between corruption and
productivity highlighted in Chapter 1.2 exists for both
men and women entrepreneurs. However, according to
the Enterprise Survey data, the productivity of femaleowned
businesses does not appear to be affected more
than the productivity of male-owned businesses.17

The
same holds for access to finance, measured as the average
percentage of working capital from formal sources.
Similarly, across countries, a larger share of working capital
derived from external sources (that is, from formal
sources as well as informal channels such as family,
friends, money lenders, but excluding internal funds and
sale of stock) is associated with higher productivity, but
the same relationship exists for men and women alike.
These findings are confirmed even after controlling
for the firm’s characteristics (size, sector, location, and
whether the firm exports or not).

Except in a few cases,
the performance of female-owned enterprises is not
disproportionately affected by the severity of the constraints.
18 In other words, once they are over the entry
threshold and are operating businesses, both men and
women entrepreneurs in this sample are by and large
affected by these constraints in the same way.

Related Articles
  1.0 Overview: Gender Entrepreneurship and Competitiveness in Africa, 2007
  2.0 Gender in African economies: Gender Entrepreneurship and Competitiveness in Africa, 2007
  7.0 Conclusions: Gender Entrepreneurship and Competitiveness in Africa 2007
  18.0 Conclusion: Entrepreneurs and entrepreneurship in Africa
  1.0 What is known and what needs to be done: Entrepreneurs and entrepreneurship in Africa

Article Tags: Africa women, business constraints, men and women, men and women, obstacles, obstacles, perceptions, perceptions, performance, women entrepreneurs, worker



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