# **5 Conclusion**

This paper analyzes the role of individual traits and choices on self-employment income gaps between men and women who own businesses. The analysis based on the Republic of Congo, Ghana, Rwanda, Tanzania and Uganda shows that a classification of entrepreneurs based on broad categories (such as the size of the business) provides a useful categorization. However the relevance of individual specific traits demonstrated so far in this paper shows that additionally considering the traits of individual entrepreneurs helps researchers and policy makers identify the sources of income gaps.

Looking at business profitability, the analysis shows that differences in endowments of traditional traits such as education, experience, and marriage (which can be seen as a proxy for time availability) do not do a good job in explaining income gaps. This is despite the fact that there are clear differences in relative endowments in these traits when we look at the raw data.<sup>8</sup> However, while composition effects overall do not explain the majority of the gap, they do play an imporant role in explaining aggregate income gaps (with the exception of Uganda).<sup>9</sup> In place of traditional traits such as education, experience, and marriage, we find that the composition effect acts primarily through covariates such as industry, savings, and monthly hours worked.

In Ghana, we find that the share of the gap accounted for by differences in endowments is constant across the distribution. Interestingly, while differences in monthly hours and industry choices play a role in explaining the composition effect, the most important covariate is savings. The contribution of savings to the overall gap increases across the distribution. This may indicate that women at the top of the female self-employment distribution lag behind the top earning self-employed men due to financial constraints in Ghana.

In contrast, we find that the composition effect explains a decreasing share of the income gap for the Republic of Congo, Rwanda and Tanzania. The fact that the gender income gap is increasing (or moderately decreasing in Tanzania) while the share of the gap explained by the composition effect is decreasing may indicate a “glass ceiling” for women in the Republic of Congo, Rwanda, and Tanzania which is associated with discrimination against women at the top end of the earnings distribution. Unexplained differences in returns to the same endowments could be due to discrimination; and in the Republic of Congo, Rwanda, and Tanzania, more of the gap is due to unexplained differences in returns to the same endowments at the top of the income distribution.<sup>10</sup> We view our primary policy implications as two-fold. Firstly, our results highlight

> 8See Tables C.1-C.5 in the Online Appendix.

> 9In Uganda the entire gap is due to the structural effect.

> 10 However, we stress again that while discrimination could be the root cause of the structural effect, we cannot definitively attribute the structural effect to discrimination. This is the case unless we are able to include all possible determinants of income in the set of covariates, which is not possible with our data.

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