For women, economic opportunities are not just about jobs, they are about good jobs

While jobs are an essential pathway out of poverty, not all jobs are good jobs. Although overall employment in Latin America and the Caribbean (LAC) is indeed slowly recovering, the quality of employment in the region has deteriorated since the beginning of the pandemic in 2020. Unfortunately, women have been particularly affected by this phenomenon . This is a concerning dynamic that could lead to widening gender gaps in different dimensions. 

The gender disparity in job quality has been highlighted in the latest World Bank’s LAC Poverty Update “From Infection to Inflation” and it is a finding that deserves more attention. Hence, a key question to ask is: How does the quality of employment vary between men and women in the LAC region? Overall, the gender disparity is more pronounced in earnings and job security, and it is observed across all sectors of employment. 

Quality of employment for men and women in Latin America and the Caribbean 

The Job Quality Index (JQI) becomes a handy tool to answer this question. This index combines four dimensions that characterize a “good” job: 

1. Earnings above a certain threshold, in this case, the $6.85 a day purchasing power parity poverty line.
2. Benefits, which, in this case means health and/or retirement.
3. Security, in other words, the job is permanent and/or stable.
4. Satisfaction, proxied by the worker not having a second job.

The values for the JQI range from 0 to 1, indicating low to high job quality. Earnings above the poverty line is a necessary condition for the JQI to be greater than zero.

According to the JQI, both men and women in the region perform jobs of low-quality level. Within countries, however, employed women perform jobs of even lower quality than those of men  (except for Honduras and Panama where there is not significant difference). There is also substantial variation in the size of the gender gap in job quality across countries, with Peru, Bolivia and Colombia ranking with the highest disparity. Furthermore, the observed regional disparity in job quality (against women) holds across all sectors of employment: agriculture, industry, and services. The biggest gender gap is found in agriculture (0.14) and the smallest in industry (0.02), although this sector concentrates only 11 percent of female workers in the region.

 

 Job Quality Index in LAC (latest year available). Value and gender gap

 

 

Source: World Bank staff calculations based on SEDLAC (CEDLAS and the World Bank). Note: LAC12 corresponds to Argentina, Bolivia, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, Panama, Paraguay, Peru, Salvador and Uruguay. Together, these countries represent 67 percent of the total population of LAC. Argentina has urban coverage only. *p < 0.1 **p < 0.05 ***p < 0.01

 

As mentioned above, the gender difference in job quality then becomes clear when comparing data across these dimensions. Looking at regional figures, 66 percent employed women have a job that satisfies the income criteria meaning they earn above the poverty threshold of $6.85 a day (2017 PPP) whereas the share among employed men is higher, 80 percent. The dimension where both fare worst is benefits, with only 45 percent of women and 47 percent of men receiving them. An important gender gap is observed in job security with 59 percent of women performing secure jobs compared to a higher 66 percent of men. 

Job satisfaction, proxied by not having a second job, is where they fare better (80 and 85 percent) but this finding should be interpreted carefully. Data limitations prevent to fully capture ‘job satisfaction,’ and there are many other reasons why men and/or women do not take a second job (other than feeling satisfied with their main job). 

It is well documented that women in the region (and across the world) lost jobs at a much higher rate than men during the pandemic. But there is more to it. Data shows that the gender gap in job losses during the pandemic widened more in countries where women were disproportionately concentrated in low-quality jobs.  

 

Gender gap in job losses vs. job quality

Sources: World Bank staff calculations based on SEDLAC (CEDLAS and the World Bank). Note: Gender gap in job losses is defined as the difference between the share of women and the share of men who lost their job. Gender gap in JQI is defined as the difference in the index between women and men (hence the negative values). In the case of El Salvador and Panama, for which no data is available for 2020, job losses were simulated using the LAC average. In the case of Mexico, job losses were calculated by comparing 2020 with respect to 2018. Argentina has urban coverage only. Fitted line equation: y = -0.4315x + 0.0071

 

Lower benefits and job security with respect to pre-pandemic statistics have driven the overall deterioration in the JQI, but the magnitude of the change is not the same across gender. Ecuador, Peru, Bolivia, and Colombia show the largest decline in the JQI of employed women, and this is due to a larger decline in the average benefits and job security dimensions than the observed among employed men. Satisfaction has a smaller contribution to the drop in quality although important declines are observed for women in Bolivia and Ecuador. Declines in income have been particularly large for women in Peru and Ecuador, and for men in Panama. 

Change (%) in dimensions of Job Quality Index among Employed Women. 2021 vs. 2019

 

Sources: World Bank staff calculations based on SEDLAC (CEDLAS and the World Bank). Note: Argentina has urban coverage only.

 

The strongest predictors of job quality are education, sector of employment and urban location. Yet, these variables do not operate for men and women alike. For women in LAC this is not fully a skills problem: they have on average higher educational attainment than men, and yet they participate less in the labor market. When they do, they have jobs of lower quality. The explanation lies in the additional constraints that women face to access economic opportunities such as the heavier burden of household and care work and their lower participation in Science, Technology, Engineering and Math (STEM) fields of education. More action to raise the quality —not just the level— of female employment is needed.

 

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