distribution by economic sector and occupations. Finally, we compare the characteristics of vulnerable (bottom 40 percent) and non-vulnerable (top 60 percent) workers within each employment type to better understand the profile of poorer workers. Due to sample size, we can only use the GMD to parametrically explore characteristics of unpaid, informal wage, and low-educated self-employed, with a much lighter touch on high-educated self-employed. We complement these findings with an analysis of the IES that allows us to understand more about the characteristics of low- and high-educated self-employed and informal employers.

# **5.1 Distribution of Demographic Characteristics by Employment Type**

Women’s informal sector participation is higher than their share of the workforce in urban SSA, and they dominate the non-wage informal sectors. Women are 47 percent of the entire workforce while they represent 51.5 percent of the informal sector (using the lower-bound definition) (Figure 7). Within the informal sector, women are disproportionally represented in two types of jobs: they are 58.1 percent of unpaid workers and 59.9 percent of LE-SE. By contrast, women are less than 40 percent of informal (35.2 percent) and formal (38.2 percent) wage employees. These aggregate trends are reflected across countries.<sup>48</sup> Married women especially cluster in unpaid and LE-SE. The conditional estimates confirm that women and dependent spouses are more likely to be unpaid or LE-SE than are men and household heads.<sup>49</sup> As most spouses in the sample are female, it is not surprising that female spouses follow this same pattern (Table 2).

The urban informal sector mainly employs prime-age workers. Those aged 25-55 years are 73.3 percent of the workforce and 66.9 percent of informal sector workers (Figure 7). LE-SE and informal wage employees – the two largest employment types – are mainly prime-aged adults. This age pattern appears in most countries. However, a closer look reveals more nuanced patterns.

Youth crowd into unpaid jobs. Youth (age 15-24) are 16.5 percent of the urban labor force, being particularly over-represented among unpaid workers (61.8 percent) (Figure 7). This result emerges from the conditional analysis, as well, where prime-aged and older workers are 20 percent less likely than youth to hold an unpaid wage job (Table 2). Youth are notably absent from informal self-employment.

Older workers have a propensity for informal self-employment. Older workers make up 10.2 percent of the workforce, but 16 percent of the low-educated self-employed (Figure

> 48 For example, a smaller share of women than men hold informal wage employment in 25 of the 26 countries in the sample.

> 49 The estimates for specifications that includes gender but not marital status, marital status but not gender, and an interactive gender and marital status variables are available from the authors. The lack of statistical significance on the female dummy in the unpaid employee regression is due to the spouse variable. When marital status is not included, the coefficient estimate for females is positive and statistically significant at the 1% level. The coefficient estimates for the female variable are higher in both the unpaid employee and selfemployment regressions when marital status is not included.

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