women select into paid employment in Ghana (Owoo et al. 2022), and the education and literacy of family members are strong predicators of women selecting into paid employment in Pakistan (Hussain, Rabbi, and Ali 2012). These findings are consistent with the results here and likely explain why there are not large gender gaps in the job quality of wage employment.

Figure 5. JQM among the Wage Employed, by Education, Location, and Age-Group <!-- Start of picture text --> 4.00 100%<br>3.50<br>80%<br>3.00<br>2.50 60%<br>2.00<br>1.50 40%<br>1.00<br>20%<br>0.50<br>0.00 0%<br>Male Female Primary Secondary Tertiary Rural Urban 16 - 24 25+<br>Sex Education Location Age group<br>Income Benefits Stability Working Conditions Share of Wage Employees<br>JQM<br>Share of Wage Employees<br><!-- End of picture text --> _Source:_ Estimates based on multiple labor force and household surveys (see annex table A1). _Note:_ The sample includes 37 countries with information for all dimensions. This figure shows the JQM by sex for the wage employed only and the share of the wage employed among all workers by sex. The sample for the education portion excludes two countries without information on education, and the sample for the location portion excludes nine countries without information on location.

The analysis of quality of the jobs among other disadvantaged groups of the population offers additional insights into disparities in labor markets across developing countries. Common disadvantaged groups are those less well educated, living in rural areas, and youth. In some countries, young people usually have unpaid jobs, and, even if young people are paid, they are less likely to have benefits and social security (World Bank 2012). Figure 5 shows the JQMs for the wage employed by educational attainment, location, and two age-groups, the young (ages 16–24) and workers (ages 25 or more). As expected, the largest difference is among the results disaggregated by education. The average JQM is 30 percent higher among people with secondary educational attainment than among people with primary education, and the average JQM is 26 percent and 63 percent higher among those with tertiary education than among those with secondary education and primary education, respectively. The scores of each dimension are higher among high-skill workers, but the difference is especially pronounced in the benefits dimension, where the scores of those with tertiary or secondary educational attainment are almost three times higher and two times higher, respectively, than the scores of those with primary education. The difference between individuals living in urban and rural areas and younger and older individuals are similar. The JQMs of urban and older (and more experienced) workers is, on average, 22 percent higher than the JQMs of rural and younger individuals, respectively. The greatest difference is found in the benefits dimension in both cases.

Worker allocation across sectors greatly depends on educational attainment. For example, on average, almost half the wage employed with primary education work in agriculture, compared with less than a fourth of the wage employed with secondary education and only 5 percent of those with tertiary education. In public administration, the shares are somewhat turned around. To explore the extent to 19