Less-educated workers among the most affected by the COVID-19 pandemic: Evidence from Sub-Saharan Africa

There is no surprise that crises disrupt economic activities. We see this in global pandemics, disruption of value chains, and conflicts. But on a granular level, how do these crises impact labor, household income, and individuals’ lives, especially those affected the most? In Sub-Saharan Africa, systematic evidence to answer this question that is so critical to policymaking has been limited.

In a recent working paper published by the World Bank’s Living Standards Measurement Study, we find that one year since the onset of the pandemic, the level of education became the main predictor of joblessness in Ethiopia, Malawi, Nigeria, and Uganda . These four countries represent 34 percent of the population of Sub-Saharan Africa.

We use nationally representative high-frequency phone survey (HFPS) data from these four countries to analyze the impacts of the COVID-19 crisis on jobs and combine it with pre-existing face-to-face panel surveys from 2010 to 2019. We also look at its impacts by gender, education, age, the pre-COVID-19 industry of work, and between the rural and urban sector. Specifically, we compare respondents’ employment status and income before and during the pandemic, which allows us to understand the effects of COVID-19 on households and individuals. Finally, we analyze the immediate impacts on work during the first few months of the pandemic (up to July 2020) and the medium-run impacts (up to February/March 2021). Here are what we find:

More than one-third of the workers were re-employed to a different industry one year into the pandemic

Among respondents that were working pre-COVID-19, on average, 34% had lost their job. Particularly in Nigeria, the rate of job loss was as strikingly high as 61%. But re-employment was also quite significant: 75% to 93% of those who had lost their job re-entered the workforce between July and October 2020. Interestingly, a large share of re-employment involved a change in the industry, especially in Ethiopia. In the four countries that we studied, 38% of respondents who lost their job were re-employed in a different industry than the one they were working in prior to the pandemic . The agriculture sector received the largest influx of workers from other industries.

Figure 1: Early-phase labor market indicators in Ethiopia, Malawi, Nigeria, and Uganda

Source: HFPS and LSMS-ISA surveys.

The less-educated were affected the most one year later

Our finding shows that women were significantly more likely to lose their job at the onset of the pandemic. Further, there was a lower probability of re-employment for women. By October 2020, women were 14 to 20 percentage points less likely than men to be re-employed after job loss. Re-employed women were also much less likely to return to a different industry than re-employed men. Women’s lower sector mobility may be one of the reasons why they were less likely to be re-employed in the period of analysis. In addition, urban respondents were 6 to 9 percentage points more likely than rural respondents to lose their jobs and significantly less likely to be re-employed.

But situations changed later. By February/March 2021, lower education turned out to be the main predictor of joblessness among those working pre-COVID-19. The impacts of the pandemic evolved differently in 2021, as governments lifted or adjusted restrictions and people, especially those with farms and businesses adapted to the situation. The least educated are 4 to 7 percentage points more likely to be jobless after one year into the pandemic, than those with primary or higher education .

Non-farm enterprises (NFE) were a less stable income source than wage employment

In the early phase of the pandemic, households relying on non-farm enterprise (NFE) income were most likely to report a decline in household income, while income from wage employment was relatively secure . Further, income loss in the early phase of COVID-19 was strongly predicted by younger, less educated household heads, urban location, and the presence of children.

We find that income sources matter a lot: households with non-farm enterprises and farming households were most likely to lose income. Additionally, households receiving domestic remittances also experienced a higher probability of income loss. On the contrary, there is a strong negative association between wage employment and income loss, suggesting that wage employment was an important factor protecting households from income loss as a relatively secure source of income during the early months of the pandemic.

In addition, while there is no significant association between the gender of the household head and the probability of total income loss, female-headed households are significantly more likely to report a loss of NFE income.

A path forward for policymaking

Our findings using the HFPS data from four countries in Sub-Saharan Africa show us that:

1. The less educated were hurt the most in terms of job loss about one year into the pandemic. What does this suggest? Policymakers should prioritize re-integrating the least educated who are inactive or unemployed into the labor force .
2. Relative vulnerability of non-farm enterprise income should not be overlooked in policy design, as a large share of households in Sub-Saharan Africa rely on this income generating activity . However, these enterprises are relatively difficult to target due to their small scale and informal nature of activities. It would be beneficial to provide easier procedures for registration to improve targeting possibilities in the future and to design safety net policies particularly targeted at non-farm enterprises during crises such as the pandemic.
3. High-Frequency Phone Surveys are a valuable tool in capturing data on outcomes, such as employment status, that are prone to changes and fluctuations. These surveys can also complement face-to-face surveys on more structural changes in the characteristics of households and individuals.