People with face masks seen at a South African Social Security Agency building in Cape Town. Picture: Gallo Images/Nardus Engelbrecht
People with face masks seen at a South African Social Security Agency building in Cape Town. Picture: Gallo Images/Nardus Engelbrecht

Given the extent of the Covid-19 crisis, it is crucial to ensure that the most vulnerable in SA get relief against the adverse effects of the pandemic.

Around the world, governments have expanded their social protection systems as a means of providing relief to struggling populations. As of May 22, 190 countries had planned, introduced or adapted 1,000 social-protection measures. This is more than an eightfold increase in such measures, in just two months.

In SA, a similar rollout took place. From May, the government expanded its sophisticated social grants system for six months by increasing the amounts of existing grants, while also introducing a special Covid-19 grant. This policy announcement was particularly salient, considering that the country’s poorest earners were expected to be most adversely affected by the pandemic and subsequent national lockdown.

But have these individuals actually received some relief during the lockdown?

The pandemic has resulted in data-collection complications. Researchers and the government haven’t had all the information they need to make up-to-date, evidence-informed policy. That is, until the National Income Dynamics Study: Coronavirus Rapid Mobile Survey (Nids-Cram) went into the field in May.

The Nids-Cram survey is part of a collaborative research project that aims to inform policymaking by producing rapid, reliable research on socioeconomic outcomes during the lockdown. We are among the first to use this data — but, before discussing our results, it is important to take into account some complications in design. Of particular concern here is missing household income data for a significant number of individuals, and that the estimated number of grant recipients in the data is substantially lower than in official records. Due to these and other caveats discussed in our paper, our results are not to be taken as a nationally representative picture of grant outcomes in SA.

Nearly 80% of additional child support grant spending accrued to the poorest 60% of households in May

At the same time, and despite this undercount, we are still able to draw some important conclusions from the available data. We’ve found, for example, that the distribution of grants in the beginning of lockdown has been significantly pro-poor.

The distribution of per capita household income in SA makes it clear why grants serve as an important source of relief. The average individual who lives in the poorest half of households has access to just R270 a month. Those who live in the richest 10% receive about 30 times that amount.

Grant receipt substantially increases the incomes of poor households. Prior to the Covid-related grant increases, the child support grant (CSG), the largest grant in terms of number of beneficiaries, already increased per capita household income by about 63% for those in the poorest 30% of households, and by just 3% for the richest 30%.

Concerningly, we find that the negative labour market effects of the lockdown have been disproportionately borne by individuals in lower-income households.

Though a more nationally representative result will emanate from Stats SA’s next Quarterly Labour Force Survey, our preliminary results suggest that employment loss for those in the poorest 20% of households accounted for more than a third (35%) of total employment loss between April and February — or nearly 1-million fewer people employed. This group experienced the largest relative reduction across the income distribution.

Are these losses permanent? Just 7.6% of individuals in the poorest 10% of households have a paid job to return to; those in the richest 10% of households are nearly seven times more likely to have one.

Changes in working hours and earnings reflect similar patterns.

In May, additional spending on the CSG was particularly pro-poor. In the graph, the percentage of total additional spending for the month on the CSG and the older persons grant, or OPG (formerly the old-age pension) is plotted against per capita household income quintiles, ordered from poorest to richest.

What it means:

The average individual who lives in the poorest half of households in SA has access to just R270 a month

Nearly 80% of additional CSG spending accrued to the poorest 60% of households. Additional spending on the OPG was also pro-poor, but less so. This has important implications for the ability of the grant system to benefit the informally employed, many of whom live with CSG recipients.

The disproportionate changes in outcomes observed here emphasise the importance of the grant expansion as a source of relief for vulnerable individuals. However, we emphasise that our aforementioned concerns regarding representativity be kept in mind. More research on future waves of data in the coming months will be essential to more accurately pick up such effects.

However, if the adverse changes among low-earning individuals observed in the Nids-Cram survey persist, policymakers have several things to consider.

These would include addressing the inefficiencies of the special Covid-19 grant rollout, and extending the expansion of the grant system beyond October.

*Köhler is a junior researcher and PhD candidate at the development policy research unit in the University of Cape Town’s school of economics. For more information on the Nids-Cram survey, visit http://www.cramsurvey.org 

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