Inequality has been a pressing subject in every arena of social science but has mostly taken up the sidelines in the age of market economies. However, the current Covid-19 pandemic that the world is dawdling with has been a wake-up call for all.
Societies all over the world have fared differently in three major parameters- income distribution within a country, public health systems relative to other countries, and the general level of development of a country, that assesses the accessibility to the prior two. The pandemic tested, figuratively, the tensile strength of societies pertaining to these three parameters. The difference became a deciding factor in the experience a country had during the pandemic (specifically the first phase). This article is an attempt to analyze their evident impact on the informal sector exploring the experience of three countries Peru, El Salvador, and India.
Graph 1: 30 countries* with the highest case-fatality ratesSource: John Hopkins University; *Syria and Taiwan were not considered due to data unavailability.
In the following table, a set of indicators were used as proxies to quantify the correlation that the parameters had with Covid fatality for the top 30 countries (graph 1), having the highest case-fatality ratio (numbers of death as a ratio to the number of cases) in 2020. The result of interest is the difference in labor force participation rate between 2019 and 2020.
Table 1: Correlation of various indicators with Covid-19 case-fatality ratio
Source: InfoSphere’s calculations
The indicator, labor force participation rate, in simple terms, means the number of people in the labor force (people having jobs or actively looking for them) as the proportion of the working-age population. By taking the difference between 2019 and 2020 allows for analysis across countries, the individuals who have lost jobs and are no longer actively looking for it. The result shows a decline in all 30 countries considered. This gives a key conclusion that there was a sense of pessimism towards job prospects during the pandemic. Given this evidence, we can assume that the volume of permanent job losses was very high for the formally employed across countries. However, the job losses could be logically deduced to have a concentration within certain categories of the services sector which required active human interaction, especially if they had no means to go into the virtual platforms.
Graph 2: Covid-19 fatality rate vs difference in labor force participation rate between 2019 and 2020
The individuals in countries where informal employment constitutes more than half of the total employment, mostly in the services sector of the urban areas, working as domestic workers, street vendors, etc; faced the actual brunt of job loss. They have little to no emergency funds available and lack the means to get proper support (credit) from the government and access to public health systems.
In the set of 30 countries tracked, the two highest declines in the labor force participation rate were observed in Peru (-12.69) and El Salvador (-6.69). Interestingly, both countries have 60% or more informal non-agricultural employment in the country, which was one of the most impacted segments during the pandemic. This makes it essential to dive into the case of Peru and El Salvador to analyze the relationship between the informal sector and the Covid-19 pandemic.
Case of Peru and El Salvador
Peru’s services sector was about 60% informal with people employed as street vendors, workers in small workshops in squatter settlements, drivers of jitney taxis, and women making tourist trinkets. Most of them had a bare minimum income to sustain themselves daily and had no backup plan. The sources of their contingency funds are also summarised in the graph below.
Graph 3: The source for “Emergency Funds” for bottom 40% income earners Source: ILO
The most concerning finding are that less than a quarter of them had savings or about one-third had family and friends that they could rely upon in case of losing their source of income. This made them highly dependent on work, especially those who had migrated from the countryside. With lockdowns, most of them lost their jobs. But for them losing jobs also meant losing the means to food and a roof. As the duration of the lockdowns lengthened, the prospects of future job opportunities eluded as well. This forced many of the people working in informal sectors to migrate back to their place of origin, in what became known as the “exodus of hunger”.
These people, mostly consisting of young families and older people, walked not due to the pandemic, but as a result of their evaluation of a set of factors like an absence of government aid, savings, household situation, little possibility of recovering employment, travel risks, travel expenses, among others. To add to this, their forced ‘reverse’ migration also made them the carriers of the virus.
Graph 4: The time frame of increase in cases during lockdown coincides with the reverse migration; the migrants became the source of the spread
As the spread increased, the pressure on Peru’s public health system also increased. As the people worst hit by the infection were the migrants, they had no avenues to receive the required healthcare. This resulted in the high Covid fatality rate (12.9%) in the country.
El Salvador also faced a similar situation under the lockdown during the pandemic, where its informal economy had faced the full brunt of the loss of life and livelihood. The informally employed workers were worse off in El Salvador than an average Latin American country (LAC), as shown in the graph below. The resources they had to sustain their lives without a daily source of income were limited and the aid by the government through social assistance programs catered to lower than 10% (CEIC database) of them.
Graph 5: Comparison of informal workers’ unavailability of financial resources to sustain their life in El Salvador to an average Latin American countrySource: EHPM 2017
However, even with these problems, the military-led lockdown saw no incidence of mass return migration as in the case of Peru. Rather, the most affected individuals were forced to two options. Firstly, to use resources employed elsewhere for consumption like diverting money from the payment stream on long-term treatments, selling assets, etc. Secondly, borrow from local loan sharks.
Peru’s and El Salvador’s two-pronged aid policy – scaling up cash assistance by advancing or increasing benefit payments to the beneficiaries and supporting all in-kind measures (food items or meals), still left most without help. The following graph gives a quantification of inadequate aid to those individuals that were in dire need in El Salvador. The state was similar for most countries having a large proportion of informally employed individuals who could not avail government aid.
Graph 6: Economic impact and government support (by pre-pandemic income level); policy implementation was inadequate in identifying who needed these benefits
Implication for India:
Much like the two Latin American countries, the informal sector in India employs around 80% of the labor force. Almost 40% of those are in the informal non-agricultural sector which was most affected by the pandemic. These were mostly employed as waste pickers, informal construction workers, informal transport workers, etc. Most of them had no savings and thus any threat to their livelihood would translate into non-availability of essential services and loss of lives. A survey of 5000 respondents across 12 states in India reports that during Covid-19 almost 80% of the households experienced a reduction in their food intake and more than 60% did not have the money for a week’s essentials.
The worst-hit out of these were the workers who had migrated to urban areas from their rural homes. It meant that these workers were dependent on their employers for accommodation as well. With the loss of accommodation, they had no choice but to move back to their villages. Like Peru, reverse migration during Covid-19 also happened in India with which cases increased in states where migration happened to.
As these workers moved back to their native states – Uttar Pradesh, Bihar, West Bengal, Rajasthan, and Odisha, (which recorded 67% of the nation’s migrants returning home) saw a spurt in the Covid-19 cases. Further, it also led to the increased spread of the virus in the rural areas, as till May 2020 (before the advent of reverse migration), 80% of the cases were concentrated just in the urban regions. Evidence for the same is that in Bihar, between May 1 and May 10, 2020, almost 70% of the cases detected were from migrant workers.
Inequality has been a cause and result of the fallouts due to the Covid-19 pandemic, while also acting as a catalyst for impact specifically on the informal workers. The condition of lack of essentials- food, means of livelihood in both the present and future, accommodation and healthcare services, and inefficient policy response left them to fend for themselves.
Both Peru and India experienced a reverse migration which became the cause of the spread of cases. Having inadequate health infrastructure and staff, the public health system collapsed under pressure. El Salvador on the other hand succeeded in saving lives by a strict lockdown but at the expense of their future. This further exasperated the inequalities in the countries
This article is co-authored by Aliva Smruti and Ashu Jain. Aliva Smruti has completed her under-graduation in Economics and Ashu Jain is a third-year student of Economics and Finance at Ashoka University.