Covid-19 in Latin America: A pandemic meets extreme inequality

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In late May, the World Health Organization declared that Latin America has become the new epicenter of the Covid-19 Pandemic. It has already been noted that the region’s high levels of inequality have limited the effectiveness of various containment policies, thus contributing to this sad distinction. In this post we look at the reverse direction of causation and ask what effects the pandemic is likely to have on the region’s entrenched inequalities. 

We argue that the impact of the pandemic will itself be highly unequal in Latin America : both in terms of health and economic outcomes, and along income, spatial, gender and racial dimensions. Worse yet, this will be true both in the short-term, during the current “lockdowns”, but also in the medium and longer-term. Nonetheless, the policy responses in some countries suggest that there may be a silver lining: the crisis might provide an opportunity for rethinking the region’s structurally unequal social contract.  

In the short-term, inequalities in how individuals can cope with stay-at-home orders are particularly striking in the region. Living conditions – including access to such basic amenities as piped water and adequate sanitation facilities – are highly unequal.  The homeless and those living in cramped and precarious housing in urban slums, without access to water and sanitation, face huge difficulties in implementing social distancing and maintaining the higher levels of personal hygiene that are now required. Figure 1 shows the share of the population with no access to piped water or improved sanitation in selected LAC countries as of 2018. While things may have improved a little over the last two years, the 2018 numbers are sadly unlikely to be too far out of date…  

Figure 1: Population share with no access to piped water and to improved sanitation: selected countries in 2018

Figure 1: Population share with no access to piped water and to improved sanitation: selected countries in 2018
Source: Global Monitoring Database, World Bank 2018.

Figure 1 shows that almost one in three Bolivians has no access to piped water at home. Fully half of Brazilians have no access to improved sanitation – a sadly remarkable number. Large numbers of Hondurans and Peruvians are also deprived of access to these basic services.  These deprivations mean that those who were worst-off to begin with are also most vulnerable to the virus.  

This also implies that Covid-19 will not be color- or race-blind in Latin America. Afro-descendants are over-represented among slum dwellers in Brazil, Colombia, and many other countries. Infection and death rates will almost certainly be higher for black Latin Americans than for whites, much as in the United States. Indigenous descendants are also more vulnerable in a number of Andean countries, and in the Brazilian Amazon. 

A second pre-existing inequality that is likely to make the underprivileged more vulnerable to the pandemic is that between formal and informal workers in the region. According to the ILO’s definition, the informal sector accounts for 34% of the GDP in the region, with 53% of total employment being informal: ranging from 23% in Uruguay to above 80% in Bolivia. Perhaps most vulnerable among the informal labor force are self-employed or own-account workers, who typically account for between 20% and 40% of the labor force in Latin America, or even higher in countries such as Bolivia and Colombia (Figure 2). 

Figure 2 Share of labor force in self-employment for selected countries (Global Monitoring Database, World Bank, 2018).

Figure 2 Share of labor force in self-employment for selected countries (Global Monitoring Database, World Bank, 2018).

Self-employed workers often rely on day-to-day manual and less-skilled work that cannot be carried out from home, giving rise to a new inequality between those (typically better educated and more skilled workers) who can afford to work from home, and those who must keep moving during “lockdowns”. Because they have no labor contracts, they have no access to unemployment insurance. If they do not receive some other form of public transfer (more on which below), they are forced to keep working during the crisis to feed themselves and their families – rendering them more vulnerable to infection. While research on this is still incipient at this stage, this press article (in Portuguese) in Brazil’s Folha de São Paulo newspaper summarizes early evidence from an app-based study (by Lichand, Leal-Neto and Prokisch) in the city of Santo André, which suggests that there are, in fact: “two [infection] curves, one for the rich, which is more under control, and one for the poor, which is still rising fast.” Separately and additionally, the probability that tasks can be safely performed remotely is correlated with their skill-intensity, implying that the ability to keep working and earning during a containment period is higher for those who are initially better-paid anyway. This necessarily entails an increase in income inequality, as estimated for Argentina in this working paper by Bonavida and Gasparini. 

On top of the inequality between formal and informal workers, the sizable informal sector in LAC exacerbates important gender inequalities. Women represent 55% of informal workers in the region, going from 48.3% in South America to 61.8% in Central America. If we consider that women are also more likely to bear the burden of unpaid work, to be the on the frontline as caregivers and health workers, being excluded from social insurance benefits adds a worrisome level of vulnerability for girls and women in the region.

Finally, there is good reason to suspect that the pandemic will have durable, long-term effects on inequality in the region, arising primarily from its severe negative impact on investment in the human capital of the poor. Beyond the direct effect of the virus on the health of those infected, the current crisis will almost certainly negatively affect both in utero and early childhood nutrition in a region where stunting and wasting for children under 5 are still of great concern (Figure 4).

Figure 4 Stunting children as a proportion of children below 5 years of age.

Figure 4 Stunting children as a proportion of children below 5 years of age.
Source: Global database on child growth and malnutrition WHO, UNICEF, WB 2014-2018.

Figure 4 documents that the prevalence of under-5 stunting is greater than 20% in Ecuador, Haiti and Honduras. It is over 45% in Guatemala.  The negative income shocks arising from this crisis are already leading to greater and deeper poverty and can be expected to lead to worsening nutrition for at-risk children, with inevitable long-term consequences for their cognitive abilities.  A second channel through which the pandemic is harming human capital accumulation is through school closures. This blog post suggests that in late April there were already 171 million Latin American students out of school.  Even back then, they had missed over a month of school. Inequalities in school quality and connectivity meant that remote teaching was either absent or of very poor quality for poorer children, but better for richer children attending private schools. Being out of school for a prolonged period might lead to higher drop-out rates and reduce educational attainment. Once again, these losses are likely to be greater for children from poorer families. 

The above discussion suggests that Covid-19 is likely to exacerbate inequalities in health, income, nutrition and schooling in a region already highly unequal, and to do so in ways likely to deepen entrenched racial, gender and spatial inequalities.  The one silver lining is that the social policy response has been relatively rapid – and perhaps even generous – in many countries, even some where the health policy response has left much to be desired. Peru has had one of the swiftest policy responses: introducing a lockdown almost three months ago and delivering a US$ 107 cash transfer to 9 million vulnerable people (Gentilini et al. 2020), followed by four more cash transfer programs. Brazil introduced a new cash transfer program for adults without a formal job (partly responding to the unequal access to social insurance discussed above), but also extended the coverage of the long-standing Bolsa Familia program to reach an additional one million families (Gentilini et al. 2020). Colombia similarly increased the resources to beneficiaries of both the Familias en Accion and Jovenes en Accion programs. 

Behind the ability of these countries – hardly paragons of the welfare state – to respond fairly quickly and effectively was the pre-existing data infrastructure from existing conditional cash transfer and other programs developed over the last two decades. Those programs had generated registries with basic information on the identity and location of poor households, which could be immediately leveraged to inform the crisis response.

Yet, these registries – like the social protection programs they serve – are incomplete. The pandemic has shone a harsh light on those uncovered by the existing transfer programs – often informal sector workers who do not qualify for family-based programs like school-oriented conditional cash transfers. More broadly, the crisis has highlighted the extent to which disadvantaged Latin Americans are more vulnerable to all of its negative consequences – in health, education, jobs and incomes. It comes after a year of social protests driven by deep dissatisfaction with the existing social contract, even in countries where some progress had been made. There is a chance here for societies and governments to realize that they are stronger when opportunities and protections are more fairly distributed, and to renegotiate the structurally unequal social contract that has prevailed for centuries. 

But let’s make no mistake: when inequality is as entrenched as it is in LAC, this is easier said than done.

Authors

Francisco Ferreira

Acting Director for Development Policy in the World Bank’s Development Research Group

Marta Schoch

Consultant at The World Bank

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