COVID-19 and Inequality in the Developing World: What Do We Know?

We have lived with COVID-19 for almost two years. It has affected economies all around the world, particularly in the developing world. Yet, developing economies, while experiencing an economic contraction in 2020 have rebound relatively quickly and the IMF forecasts them to perform better than developed economies this year (although the next year’s growth rates are predicted to be somewhat lower).

But what about inequality? Has COVID-19 affected inequality in developing economies and how? Now two years after the start of the pandemic we have some evidence about this impact. While discussing this, we should have in mind that inequality has different dimensions; in addition to income inequality (which is the most often used measure of inequality), there is also wealth inequality as well as inequality in access to services. There are some structural features of developing economies, which suggest that COVID-19 should produce an increase in equality.

WHAT DOES THEORY SAY?

1. A high share of the informal sector in developing economies (80% and above, according to ILO estimates) suggests that income equality should be negatively affected due to lack of social protection by employees in the informal sector. Employees in the formal sector (government, large businesses, which account for 10% or even less of the total labor force in developing countries) have remained protected throughout the pandemic via a combination of continued salary payments as well as the access to social protection measures by both the government and their employers. At the same time, informal workers experienced loss of income due to contracted economic activities without the benefit of social protection. No developing country could afford universal cash transfers to all their citizens as was the case in most of the developed countries.
2. A low share of the high productivity (modern) sectors of economy. According to different estimates, high value adding sectors of economy make about 20% of GDP in developing countries, with agriculture, low skills services, hospitality and retail trade accounting for most of GDP. High productivity sectors have been affected little or even not affected at all by the pandemic. For example, in many developing countries banking and telecom not only recorded profit in 2020-2021 but also posted better results than in 2019. Putting aside the issue of financialization of developing economies, it is known that the low productivity sectors that are the backbone of developing economies have been hit particularly hard because they involve a lot of personal interaction between the parties, which has been made difficult or even impossible due to continued lockdown measures. Relatedly, the two sectors (modern and traditional) have different customer markets whose purchasing power has been affected very differently. Customers of the modern sector are those with higher income and better social protection, mostly shielded from the effects of COVID-19. At the same time, the traditional sector caters mostly to informal and other low-income groups whose purchasing power has been hit hard by COVID-19 as discussed above.     
3. A growing productivity gap between the modern and traditional sectors, which further compounds the situation. Developing economies, particularly in sub-Saharan Africa, have been demonstrating a widening gap in productivity between the modern and traditional sectors for some time. Productivity in telecommunication, banking, manufacturing has been growing against the backdrop of a slower growth (or even decline) in agricultural productivity (like is the case in Kenya where the value added per worker in industry grew 20% between 2005 and 2015 whereas the value added in agriculture hasn’t changed or in Uganda during the same period the value added per worker in agriculture shrank by 20%). Agriculture remains the mainstay of many developing economies as the source of employment for about three quarters of population or more. This secular trend by itself increases inequality regardless of other factors but, considering what has been discussed above about the impact of COVID-19 on the performance of the modern and traditional sectors of economy, this trend is likely to intensify.
4. Yet another long-standing difference between modern and traditional sectors, leading to growing inequalities (essentially, between formal and informal employment) is the degree of business digitization (and automation in general). One thing COVID-19 has demonstrated is the power of digital solutions. But it has also demonstrated two facts: modern sectors are structured and organized better for integration of digital solutions hence the uptake of digital solutions is higher in the formal businesses, and their customers are more likely to use digital solutions. Essentially, in question is the digital divide in developing economies, which is much wider than in developed economies.  In sub-Saharan Africa, only 7% of the continent’s inhabitants are online and despite a high mobile phone usage at 72%, only 18% of these phones are smartphones. For comparison, 88.5% of population in the United States have access to the Internet. Joseph Stiglitz argues that COVID-19 has intensified the already existing trend of automation and transition to more capital-intensive businesses as machines appear more attractive to employers, particularly in the contracting sectors that use relatively more unskilled labor. The return to capital will thus increase. And, because low-income people must spend a larger share of their income on basic goods than those at the top, any automation-driven increase in inequality will be contractionary. Although this is a general trend, the digital divide in developing countries is particularly wide and is closing slowly than in developed countries, implying more dramatic outcomes in terms of rising inequality.         
5. Prevalence of unsophisticated micro and small enterprises in the structure of the private sector, operating on the margin of profitability and their low reserves. Compared to developed economies, micro and small enterprises in developing economies are mostly involved in low value adding activities. Even small market fluctuations in price and demand make them vulnerable to closure or bankruptcy. Their unsophisticated nature has also a positive angle allowing them to quickly restart their activities after the initial shock. Indeed, we have observed micro and small businesses in developing countries springing back to business right after the lockdown restriction were removed. The downside of this unsophistication and shallow reserves is that any prolonged economic stress may force such enterprises to dispose of whatever few assets they may have simply to survive.        
6. A high share of privately provided healthcare and education services. Despite the promise of free universal education, many developing countries enthusiastically embraced the prescripts of the Washington consensus about private education and healthcare. In sub-Saharan Africa, domestic general government health expenditure account for 36% of current health expenditure. The entire health sector in Guinea Conakry is privatized. According to the Kenya National Bureau of Statistics, the number of private primary schools grew by 773% between 2003 and 2017, compared to a growth of only 33% for public primary schools. Whereas the closure of the school sector affected equally public and private schools, the outcomes have been different. Private schools have adapted and continued delivery of education services via digital solutions and individual home classes, which they and their clients (protected by the support measures discussed above) could afford. Public schools could not follow the suit, nor could their clients because of, among other things, the digital divide already explained. Moreover, public school students (generally coming from low income families) were under a higher pressure to engage in economic activities to support their households, resulting in higher dropout rates. Those rates are particularly high among female students who are pushed to start a family life earlier, get pregnant and raise children, reducing the chances of their return to school to minimum.

Whereas economic activities of public school students have been beneficial in the short run to help low income families to cope with the economic shock, they are likely to affect inequality in the long-run by stymieing life chances and intergenerational mobility, which is already quite low in developing countries. According to the World Bank’s Global Database on Intergenerational Mobility, sub-Saharan Africa and South Asia stand out as regions with some of the lowest levels of mobility (regression coefficient 0.53-0.84 compared to 0.11-0.32 in developed countries). The link between the years of education and life-time earnings is well established. Since the learning outcomes are likely to remain the same for students from higher income groups but worsen for students from lower income groups, inequality is likely to raise between the two groups in the longer run.

Similarly, as the disposable income of the groups at the bottom of the income distribution decreases, the share of food expenditure increases, leaving little, if anything, for health expenditures. This forced neglect of health issues is likely to result in a less healthy lowly-paid workforce and further widen the inequality gap between haves and have nots in the longer run.

WHAT DO THE ACTUAL DATA SAY?

So, the theoretical arguments for increased inequality in developing countries under the influence of COVID-19 are quire clear and convincing. But what do the actual data say after two years of the pandemic?  

Well, the data are scanty, particularly for developing economies where national statistics often lag two or three years behind the developed economies. The 2022 World Inequality Report analyzes real-time income and savings data in certain high-income countries. Studies reveal that the pandemic initially affected low-income and wealthy groups disproportionately but that government responses were able to counter this effect. In the US, for instance, employment rates fell by 37% around the trough of the COVID recession (April 15, 2020) for workers paid wage rates in the bottom quartile of the pre-COVID wage distribution, while employment fell by 14% for those in the top wage quartile. At the same time, the implementation of exceptional crisis responses in the US (including direct special payments to households, unemployment benefits, and food stamps) is found to have had a substantial impact on poverty in the US. According to the Urban Institute, poverty dropped by 45% in 2020-2021 measured against 2018 levels (20 million people escaped absolute poverty in the US over the period).

In Europe, studies using micro-simulations and longitudinal surveys suggest similar results, i.e. without policy responses, a strong increase in income inequality would have occurred, but government support (partial unemployment guarantee, exceptional relief, etc.) tempered this impact and sometimes reduced income inequality. E.g. panel data from the COME-HERE survey to track income inequality during COVID-19 in France, Germany, Italy, Spain and Sweden, indicate as of March 2021 a drop in both relative and absolute inequality in equivalent household disposable income among individuals.

In emerging countries, where social security systems are less developed, the effect of the pandemic on low-income groups has been more severe. The World Bank estimates that the pandemic drove about 100 million people into extreme poverty, raising the global total to 711 million in 2021, up from 655 million in 2019. Without this crisis, the number of people in extreme poverty in 2021 would have been 613 million.   

Uganda ended the year 2020 with 25% of the citizens, that is a quarter of the population, back to living below the poverty line, an increase from 21% at the beginning of the year. The four percent new returnees to poverty amounted to about 1.8 million people. The latest data from the Uganda Bureau of Statistics (as of August 2021) indicate an even bigger change in poverty of 7% during COVID-19. It’s worth noting that the Uganda national poverty line is set between US$0.88 and US$1.04, much lower that the World Bank international poverty line. The increase in poverty has been particularly pronounced in rural areas where incomes are lower than in urban areas, implying an increase in national income inequality.  

Season	Urban	Rural
Overall	11.7	23.4
before covid19	11.2	20.6
during covid 19	11.9	26.9

In Bangladesh, the study conducted by the Power and Participation Research Center (PPRC) and BRAC Institute of Governance and Development (BIGD) during the second lockdown in August 2021 found that income dropped by 18% in slums and by 15% in villages from the levels in March this year, a period when the economy had largely recovered from the first lockdown at the start of the pandemic. Overall, 19.54% of Bangladesh’s population has been pushed into poverty as a combined result of the two national lockdowns. Again, as is the case with Uganda, the low income groups have been affected disproportionately, implying an increase in income inequality.

A study published by the African Economic Research Consortium published in November 2020 estimated the welfare consequences of COVID-19 in Senegal as indeed very large. An increased share of households losing more and more income would lead to an estimated income loss of up US$ 263.3 million per month or 12.6% of monthly GDP, poverty rate reaching 72.3%, and a worsening in inequality. Nationally, the Gini coefficient was estimated to go from 0.378 (base scenario) to 0.571 (worst case scenario).

Even more developed economies have not been spared the poverty impact of COVID-19. According to the South Africa’s Quarterly Labour Force Survey (QLFS) for the 3^rd quarter of 2021, the number of employed persons in the country declined by 660,000 to 14,3 million compared to the 2^nd quarter of 2021. While South Africa remains 5he world most unequal society, the 2020 Socio-Economic Impact Assessment of COVID-19 in South Africa estimated a further increase in inequality as measured by the Gini coefficient by 0.16 in the optimistic scenario and 0.23 in the pessimistic scenario.

CONCLUSION

It is difficult to make more general conclusions about the impact of COVID-19 on inequality in developed countries based on scattered data and estimates but the negative trend appears to be visibly, particularly in light of the fact that the developing world is already characterized by a high level of income inequality as summarized in the 2022 World Inequality Report.    

An increase in in-country income inequality in developing economies appears almost certain when theory and the available data are considered together. As discussed above, many developing countries did demonstrate a remarkable resilience rebounding back to the pre-COVID-19 income levels in a matter of weeks and months after the lifting of lockdowns. However, the pandemic is not over, and more lockdowns may happen in the future. The combined effect of repeated lockdowns will erode the recovery capacity of developing economies in general and the low income groups in particular. Also, the long-term consequences of COVID-19 in terms of worse education and health outcomes for low income groups and their impact on future earnings and inequality should not be ignored.