How the COVID-19 grant has reached the once forgotten

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Haroon Bhorat, Tim Köhler, 25 August 2021
The COVID-19 grant is the first in South Africa to explicitly target the unemployed. By the end of 2020, the grant had brought some six million previously unreached people into a welfare net that had previously excluded them on the assumption they could find work. How have the grants impacted poverty and inequality? And what are the implications for long-term policy?

Introduction[1]

 Around the world most governments have implemented lockdowns that have imposed restrictions on social mobility and interaction in response to the COVID-19 pandemic. While such policies have afforded many countries time to produce the necessary infrastructure and delay and minimise the spread of the virus, these policies have also led to substantial losses in livelihoods, particularly among vulnerable groups. Several estimates indicate the crisis will likely result in the first increase in global extreme poverty since 1998.[2]Latest estimates suggest that between 119 and 124 million people worldwide could be pushed into extreme poverty in 2020 (effectively eradicating progress made since 2017). More than a third of the new poor are projected to be in Sub-Saharan Africa.[3] Extreme poverty is expected to increase by 2.7 percentage points for the region — equivalent to the 2011 regional poverty level.[4]

In response to the adverse effects of the pandemic on low-income households, social protection systems have expanded significantly around the world. By mid-May 2021, more than 220 countries or territories had over 3 300 planned or adapted social protection measures in place – compared with103 measures in 45 countries about a year earlier.[5] Just over half these programs take the form of non-contributory social assistance. Such an expansion of social assistance was included in the South African government’s package of relief measures on both the intensive – increasing the amount of existing grants -  and extensive – expanding the pool of new recipients - margins. From May to October 2020, every existing unconditional cash transfer (social grant) was increased and a special COVID-19 Social Relief of Distress (SRD) grant of R350 per month (about US$25 at the time of writing) was introduced, with the latter being extended to January and later to April 2021. After a hiatus of a few months, it has now been re-introduced and extended to March 2022.

The COVID-19 grant is distinct in South Africa’s social grant system. It is the first in the post-Apartheid era to target unemployed adults – a previously largely unreached group. All other existing grants predominantly target the disabled, elderly, and children – with a specific focus on household vulnerability as opposed to labour market vulnerability.[6] This is because, prior to the pandemic, the country’s social assistance system assumed prime-aged, able-bodied individuals would be able to support themselves through the labour market.[7] However, such a view neglects the widespread, structural nature of unemployment in South Africa where over 70% of unemployment is long-term. It can therefore be said that the introduction of the COVID-19 grant at least partially addressed this gap in the country’s social safety net. The addition of the grant, together with pre-existing grants, had the potential to reach 36 million individuals, or approximately 63% of the South African population.[8] Towards the end of 2020, the grant had brought over six million previously unreached individuals into the system.[9] In a few months, it exceeded the growth of all other grants in the past decade, and by March 2021 had cost the state nearly R20 billion.[10]

Using representative, longitudinal survey data collected during the national lockdown, we have examined who applied for and who received the special COVID-19 grant. We also provide some evidence of poverty and inequality effects. We find that by October 2020, the grant had brought 5.2 million previously unreached adults – mostly unemployed, young men – into the system. Such is its reach that one third of all adults co-reside with a recipient. Moreover, it was relatively well-targeted with close to 60% of recipients being non-employed, and the remainder mostly being informally employed. Notably, all else equal, the chronic non-employed were 51% more likely to receive the grant relative to other groups. Application for and receipt of the grant was relatively pro-poor, with most applicants and recipients being based in poorer households. This latter finding is in line with our fiscal incidence analysis, which suggests that, in the grant’s absence, poverty would have been over 5% higher among the poorest households, and household income inequality 1.3% - 6.3% higher depending on the measure.

How the pandemic changed the social assistance system

South Africa’s social assistance system primarily consists of tax-financed, unconditional, and means-tested (except for the Foster Care Grant) cash transfers that mostly support vulnerable children, the elderly, and the disabled. Since democratization, social assistance has expanded significantly with nearly 18 million beneficiaries (or one in every three South Africans) as of 2019/20, at a cost of 3.4% of Gross Domestic Product.[11] Social spending in South Africa is widely documented to be relatively well-targeted towards the poor, largely attributable to the use of means testing.[12]

Table 1 shows the evolution of the number of grants distributed by grant type over the last decade. The CSG constitutes the largest grant in terms of number, accounting for 71% of total grants distributed in 2019/20. By the end of June 2020, more than three in every five children (64.2%) in South Africa had a caregiver who received a CSG on their behalf.[13] The grant’s large take-up is largely attributable to gradual increases in the age eligibility threshold and a less stringent means test. The overwhelming majority of CSG recipients (and every other grant type with the exception of the War Veteran’s Grant) are women. By June 2020, of the 7.2 million CSG recipients, only 166 000 (or 2.3%) were men.[14] The Older Persons Grant (OPG, formerly the Old Age Pension) and Disability Grant (DG, the only grant intended for working-age adults – until the introduction of the COVID-19 grant) were the second and third largest grants, collectively accounting for more than one in every four recipients. More than one in every two South Africans live in a household that receives income from either the CSG or OPG.[15] Although both the OPG and DG are means-tested, the benefits are more than four times larger than the CSG.

 

Table 1: Distribution of social grants by grant type, 2009/10 versus 2019/20.

 

2009/10

2019/20

Growth in recipients

(%)

 

Monthly amount (nominal Rands)

Thousands

% of total

Monthly amount (nominal Rands)

Thousands

% of total

               

Child Support Grant

240

9 381

68.08

440

12 777

71.00

36.20

Older Persons Grant*

1 010

2 491

18.08

1 860

3 655

20.31

46.73

Disability Grant

1 010

1 299

9.43

1 860

1 058

5.88

-18.55

Foster Care Grant

680

489

3.55

1 040

350

1.94

-28.43

Care Dependency Grant

1 010

119

0.86

1 860

155

0.86

30.25

               

Total

 

13 779

100.00

 

17 996

100.00

30.60

Source: National Treasury (2011, 2020). Authors’ own calculations.

Notes: [1] * Includes War Veterans' Grant recipients whose grant amounts to R1 880 in 2019/20 and R1 030 in 2009/2010, for the 2019/20 financial year the monthly amount here refers to that for individuals between 60 and 75 years of age, and the Older Persons Grant is R1 880 for individuals over 75 years of age. [2] Recipients per grant may not sum to total recipients due to rounding. [3] Grant-in-Aid and Social Relief of Distress grant recipients are excluded here.

 Despite the relatively comprehensive reach of South Africa’s social safety net, there is still little provision for the working-aged unemployed.[16] This is rooted in the fact that, as in Latin America and elsewhere, the structure of South Africa’s social protection system relies on the assumption that only ‘dependent’ categories (such as the elderly, disabled, and children) are in need of support. Prime-aged, able-bodied individuals are presumed to be able to support themselves through the labour market and have therefore been excluded from receiving social assistance.[17] However, such a view neglects the widespread, structural unemployment that plagues South Africa. Data for the fourth quarter of 2020, for example, shows that 72% (or approximately 5.2 million individuals) of the work-seeking unemployed had been so for more than a year.[18] In this light, the introduction of the special COVID-19 grant has played an important role in addressing this gap through targeting the unemployed.

 Following the onset of the pandemic, the South African government acted swiftly to introduce a national lockdown followed shortly by a package of targeted relief measures amounting to over R500 billion (or approximately 10% of GDP), of which R50 billion was initially allocated to an expansion of social assistance.Initial economic relief measures primarily focused on tax-registered individuals and firms in the formal sector. However, there were several vocal calls for the expansion of social assistance to support low-income households.[19] These calls largely advocated supplementing the CSG on the intensive margin (i.e. increasing the amount). Analysis using pre-crisis survey data suggested that in the absence of such targeted interventions, the extreme poverty rate amongst vulnerable households may have almost tripled.[20]

The expansion of social assistance took the form of top-ups to the amounts of every existing social grant, as well as the introduction of the special COVID-19 grant for an initial period of six months. The latter grant was extended to January 2021, and later again to April 2021. Last month, President Cyril Ramaphosa announced it would be reinstated until March 2022. With the exception of the CSG, every existing grant was increased by R250 per month from May to October 2020. The CSG was increased by R300 per grant for May (a nearly 70% increase attributable to a relatively low pre-COVID-19 level of R440) but R500 per caregiver (regardless of the number of eligible children) from June onwards. Although caregivers with one child benefited more from June relative to May, those with two or more children benefited more in May relative to June onwards. In other work[21] we show that the per-child CSG top-up is more pro-poor than the per-caregiver top-up, but only marginally, and is substantially more expensive than the chosen policy. As such, this decision by government was presumably taken partly because it was accompanied by the introduction of the new COVID-19 grant as well as increases in all other grants.

 By simulation, Bhorat et al[22] find that the chosen policy ultimately leads to the largest reduction in poverty over six months by bringing many previously unreached households into the system through the introduction of the COVID-19 grant. In practice however, there were delays in the processing of applications and payment of the COVID-19 grant. Despite this, payments of the grant began towards the end of May 2020 – just under three months after the first reported case of COVID-19 in South Africa.

While the top-ups to pre-existing grants benefited existing recipients, the introduction of the COVID-19 grant resulted in a significant expansion of coverage. Prior to the pandemic, approximately 18.3 million grants were distributed every month. In just a few months, the total number of grants distributed grew by 35% to 24.6 million by October 2020. Put differently, the number of grants distributed was equivalent to 41% of South Africans, as evident in Table 2.[23], [24] Given the number of all pre-existing grants remained relatively constant as shown in panel (b) in Figure 1, this expansion was directly attributable to the introduction of the COVID-19 grant, making it the second largest in terms of reach (10.3% of the population) next to the CSG (21.7% of the population).

Table 2: The Covid-19 Grant in Comparison, October 2020

Grant type

Number of grants

Share of total grants (%)

Share of population (%) (59.6 million)

 

 
   
           

COVID-19 Grant

6 112 660

24.80

10.25

   

Child Support Grant

12 936 610

52.49

21.70

   

(collected on behalf of 7.2 million caregivers)

   
   

Older Persons Grant

3 719 763

15.09

6.24

   

Disability Grant

1 074 985

4.36

1.80

   

All other grants

802 930

3.26

1.35

   
           

Total

24 646 948

100.00

41.34

   

Authors’ own compilation. Source: SASSA (2021), StatsSA (2020), NIDS-CRAM Wave 3 (2021).

Notes: [1] Grant data from SASSA (2021); Grant-in-aid excluded. [2] Total population as per the StatsSA 2020 mid-year population estimate. [3] Adults defined as those aged 18 years or older; NIDS-CRAM Wave 3 estimate for October 2020 used. [4] The shares of the total population and adults who receive the CSG calculated by using the number of grants (12.9 million) and adult caregivers (7.15 million), respectively. Total share calculated by including the latter.

 

Figure 1: The role of the COVID-19 grant in expanding social grant coverage in South Africa

Authors’ own compilation. Source: SASSA (2020a, 2021).

Notes: [1] ‘CSG’ = Child Support Grant, ‘OAP’ = Old Age Pension, ‘DG’ = Disability Grant, ‘Other’ includes the War Veterans grant, Foster Child Grant, Child Dependency Grant, and the Grant-in-Aid. [2] COVID-19 grants are those distributed for a given month but not necessarily in a given month. The latter is not shown given data limitations. [3] Number of monthly COVID-19 grants distributed for January – March 2021 equivalent to December 2020 given data limitations.

Data

For our analysis, we used representative survey data from the second and third waves of the National Income Dynamics Study: Coronavirus Rapid Mobile Survey (NIDS-CRAM), conducted via Computer Assisted Telephone Interviewing (CATI) in the preferred South African language of the respondent in July/August and November/December of  2020 respectively. The NIDS-CRAM is a broadly representative, individual-level panel survey that began with 7 000 adults and has been repeated over several months. The sample is a sub-sample of individuals aged 18 years or older who were surveyed in Wave 5 (2017) of the National Income Dynamics Study (NIDS) – a nationally representative household survey conducted approximately every two years from 2008 to 2017.

 Because it is designed as a panel, the NIDS-CRAM can provide a substantial amount of information about the dynamics of sampled individuals as the pandemic and lockdown unfolds. The data allows us to estimate personal receipt of any grant, as well as household-level[25] receipt of select grants. Importantly, from Wave 2, respondents were asked whether they had applied for and received the COVID-19 grant.

Findings

Who received the grant?

 Six months into its roll-out in October 2020, we estimate the COVID-19 grant reached over 5.2 million individuals directly, or nearly 11.3 million individuals indirectly if one includes household co-residents. Nearly two in every three recipients (63%) were male, showing that the grant has brought a large, previously unreached group into the system – unemployed men. Despite similar household-level receipt, the observed gender disparity in individual receipt is concerning considering that in the same month, women accounted for the majority (60%) of the unemployed by the broad definition. This gender gap in receipt is likely explained by the COVID-19 grant’s eligibility criterion that recipients of other grants are not eligible. Most of these – 85% in December 2020 – are women. Arguably, unemployed women who receive the CSG on behalf of a child have been unfairly excluded from receiving the COVID-19 grant as a means of support for themselves, disadvantaged by their childcare.[26] It has therefore been argued that the COVID-19 grant ought to be allowed to be held concurrently with the CSG. In his address last month, the President indeed expanded eligibility criteria of the grant to allow unemployed CSG caregivers to receive the COVID-19 grant. Rough estimates suggest this may result in 3 - 4 million additional women being reached, greatly improving the grant’s gender receipt gap.

 

Table 3: Variation in COVID-19 grant receipt by demographic group, October 2020

 

Personal receipt

Household receipt

 

Absolute

% of total

recipients

Absolute

% of total recipients

         

Total

5 240 858

100.00

11 286 416

100.00

Gender

       

Male

3 315 276

63.26

5 406 987

47.91

Female

1 925 582

36.74

5 879 429

52.09

Age

       

18-34

3 128 211

59.69

5 463 289

48.41

35-59

2 029 582

38.73

4 787 647

42.42

60+

83 065

1.58

1 035 481

9.17

Population group

       

African/Black

4 816 849

91.91

10 328 543

91.51

Coloured

274 883

5.24

678 601

6.01

Indian/Asian

106 056

2.02

163 620

1.45

White

43 070

0.82

115 652

1.02

Education

       

Up to primary

486 250

9.29

1 776 831

15.86

Up to secondary

2 504 460

47.83

4 625 425

41.3

Complete secondary

1 255 463

23.98

2 546 034

22.73

Tertiary

989 864

18.9

2 252 157

20.11

Authors’ own calculations. Source: NIDS-CRAM Wave 3.

Notes: [1] Estimates weighted using relevant sampling weight after accounting for complex survey design. [2] Household receipt refers to living in a household with at least one COVID-19 grant recipient.

 Most COVID-19 grant recipients are young (60%), African/Black (92%), and have a highest level of formal education up to matric (81%). The high levels of receipt amongst the youth is particularly notable, considering that the group accounts for more than half (55%) of the broad unemployed.

 The COVID-19 grant was intended to provide support to unemployed adults who received no other form of government assistance. How effective was this targeting? In our analysis, we found the majority (nearly 60%) of the grant’s recipients in October 2020 were non-employed.[27] Of those who were employed and received the grant, most were either informally employed or engaged in casual work or self-employment.[28]The highest share of receipt was accounted for by the chronically non-employed (42%), an important indicator of its efficacy in targeting the most needy.

 Poverty and inequality effects

To explore poverty and inequality effects of the grant, we employed fiscal incidence analysis (FIA) which is typically used to examine the distributional impacts of taxes and transfers. FIA simply consists of allocating public spending (cash transfers in this case) to individuals so that one can compare incomes excluding the transfer with incomes including it. An assumption of this approach is that, in the counterfactual scenario of zero COVID-19 grant receipt, households would exhibit their reported household incomes minus the income from the COVID-19 grant. Of course this need not be the case given that households may have received incomes from other sources.. Despite this, FIA is useful in providing evidence on poverty and inequality effects.[29]

 We estimate that the COVID-19 grant played a significant role in reducing poverty, particularly amongst the poorest individuals. Using StatsSA’s Food Poverty Line (FPL), we estimate that in the grant’s absence, poverty would have been two percentage points, or 5.3%, higher (see Table 4). When using higher poverty lines, the poverty-reducing effect remains evident but expectedly becomes smaller. This reflects the progressivity of the grant: we find that both application for and receipt of the COVID-19 grant has been relatively pro-poor. Conditional on applying, 23% of adults in the poorest 10% of households received the grant, in contrast to less than 1% of those in the richest decile. Most of the latter adults (97%) did not even apply. Regarding inequality, we find that the grant reduced household inequality by 1.3% - 6.3% relative to the counterfactual, depending on the inequality measure. Despite these observed positive effects on both poverty and inequality, it is important to note that both remain high, regardless of the inequality measure or poverty line used.

 

Table 4: Ex ante poverty and inequality effects of the COVID-19 grant, June 2020

 

Household income excl. COVID-19 grant

Household income incl. COVID-19 grant

Change in inequality

or poverty (%)

 

Inequality measures

     

Gini coefficient

0.693

0.684

-1.282

Theil index

1.036

1.010

-2.447

Atkinson index

0.634

0.591

-6.726

Poverty measures

     

StatsSA FPL (%)

38.430

36.380

-5.334

StatsSA LBPL (%)

50.040

49.250

-1.579

StatsSA UBPL (%)

62.010

61.570

-0.710

Authors’ own calculations. Source: NIDS-CRAM Wave 2.

Notes: [1] Estimates weighted using computed bracket weights. [2] Per capita household income and poverty lines inflated to January 2021 Rands. [3] Poverty measures refer to the percentage of individuals who live in households with per capita household incomes less than the stipulated poverty line. [4] FPL = food poverty line of R598.74 per person per month, LBPL = lower bound poverty line of R859.72 per person per month, UBPL = upper bound poverty line of R1 297.77 per person per month. [5] Inequality aversion parameter of the Atkinson index = 1.

Conclusion

 Before the onset of the COVID-19 pandemic, South Africa’s social assistance system excluded prime-aged, able-bodied individuals as it assumed they could support themselves through the labour market.[30]However, such a view neglects the widespread, structural unemployment that plagues South Africa. This hole in the country’s social safety net was partially addressed through the introduction of the new COVID-19 grant – a core component of the government’s expansion of social protection in response to the pandemic. In targeting the unemployed, the COVID-19 grant is the first in South Africa to use labour market vulnerability, as opposed to household vulnerability, as a key criterion for eligibility. By the end of 2020, the grant had brought over six million previously unreached individuals into the system[31] – exceeding its growth in the last decade – at a cost of nearly R20 billion to the state by March 2021.[32]

 These were mostly non-employed, young men. The disparity in receipt by gender is likely to reduce given the recent amendment to allow unemployed caregivers to receive the grant concurrently with the CSG. The COVID-19 grant is relatively well-targeted with close to 60% of recipients being non-employed, and the remainder mostly being informally employed. In our multivariate modelling, we find that the chronic non-employed were 51% more likely to receive the grant than other groups. Application for and receipt of the grant has been relatively pro-poor. This latter finding is in line with our fiscal incidence analysis, which suggests the grant reduced poverty by 5.3% amongst the poorest households, and household income inequality by 1.3% - 6.3% depending on the measure.

Our analysis has implications for policymaking as the South African economy recovers. Any consideration for income support through social protection policy ought to consider the changing dynamics of the labour market. The partial labour market recovery observed over the course of 2020 is welcomed, but uneven. By the fourth quarter, although the number of job-seekers had returned to pre-pandemic levels, employment remained significantly lower and inactivity significantly higher, with only one third of jobs lost in the informal sector having been regained.

 Our research here suggests that the COVID-19 grant has been an important, short-term effective means of providing progressive income relief to a previously largely unreached group – the unemployed and informally employed. Any attempts to extend the grant need to constantly be mindful of the fiscal ramifications of such interventions. 

 References

Ardington, C. (2020). NIDS-CRAM Wave 1 Data Quality. NIDS-CRAM Wave 1 Technical Document. Available: https://cramsurvey.org/reports/.

 

Auditor-General. (2020). First special report on the financial management of government’s Covid-19 initiatives. Available here: https://www.sassa.gov.za/newsroom/Documents/First%20special%20report%20on%20the%20financial%20management%20of%20government%e2%80%99s%20Covid-19%20initiatives.pdf.

 

Baskaran, G., Bhorat, H. and Köhler, T. (2020). South Africa’s Special COVID-19 Grant: A Brief Assessment of Coverage and Expenditure Dynamics. Development Policy Research Unit Policy Brief 202055, DPRU, University of Cape Town, Cape Town.

 

Bassier, I., Budlender, J., Zizzamia, R., Leibbrandt, M. and Ranchhod, V. (2021). Locked down and locked out: Repurposing social assistance as emergency relief to informal workers. World Development, 139, pp.105-127.

 

Bhorat, H., Köhler, T., Oosthuizen, M., Stanwix, B., Steenkamp, F. and Thornton, A. (2020). The Economics of Covid-19 in South Africa: Early Impressions. Development Policy Research Unit Working Paper 202004, DPRU, University of Cape Town, Cape Town.

 

Bhorat, H., Oosthuizen, M. and Stanwix, B. (2021). Social Assistance Amidst the COVID‐19 Epidemic in South Africa: A Policy Assessment. South African Journal of Economics, 89(1), pp.63-81.

 

Casale, D., and Shepherd, D. (2020). The Gendered Effects of the Ongoing Lockdown and School Closures in South Africa: Evidence from NIDS-CRAM Waves 1 and 2. National Income Dynamics Study Coronavirus Rapid Mobile Survey (NIDS-CRAM) Policy Paper No. 5.

 

Ferguson, J. (2015). Give a man a fish: Reflections on the new politics of distribution. Duke University Press.

 

Gentilini, U., Almenfi, M., Orton, I. and Dale, P. (2021). Social Protection and Jobs Responses to COVID-19: A Real-Time Review of Country Measures. Version 15. World Bank, Washington, DC. World Bank.

 

Köhler, T. and H. Bhorat. (2020). Social assistance during South Africa’s national lockdown: Examining the COVID-19 grant, changes to the Child Support Grant, and post-October policy options. National Income Dynamics Study Coronavirus Rapid Mobile Survey (NIDS-CRAM) Wave 2 Policy Paper No. 9.

 

Mahler, D.G., Lakner, C., Aguilar, R.A.C. and Wu, H. (2020). Updated estimates of the impact of COVID-19 on global poverty. Data Blog. World Bank Blogs.

 

Marinescu, I. (2018). No strings attached: The behavioral effects of US unconditional cash transfer programs. National Bureau of Economic Research working paper no. 24 337.

 

Moore, E. and Seekings, J. (2019). Consequences of social protection on intergenerational relationships in South Africa: Introduction. Critical Social Policy, 39(4), pp.513-524.

 

National Income Dynamics Study-Coronavirus Rapid Mobile Survey (NIDS-CRAM) 2020, Waves 2 and 3 [datasets]. Version 2.0.0. Cape Town: Allan Gray Orbis Foundation [funding agency]. Cape Town: Southern Africa Labour and Development Research Unit [implementer], 2020. Cape Town: DataFirst [distributor], 2020 and 2021.

 

South Africa Social Security Agency (SASSA) (2020a). Twelfth statistical report: Payment system: Period March 2020. Available at:

https://www.sassa.gov.za/statistical-reports/Documents/March%202020%20Social%20grant%20payment%20report%2011%20March%202020.pdf.

 

South Africa Social Security Agency (SASSA) (2021). Twelfth statistical report: Payment system: Period March 2021. Available at:

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[1] This article is based on a DPRU Working Paper by the authors: Can cash transfers aid labour market recovery?

Evidence from South Africa’s special COVID-19 grant (DPRU, 202108)

 

[2] Defined as the number of individuals living on less than $1.90 per day.

[3] Mahler et al, 2020

[4] Valensisi, 2020

[5] Gentilini et al, 2021

[6] UIF – unemployment insurance – is not a social grant. It provides limited support to the unemployed but only on a short-term basis and only to those previously employed in the formal sector.

[7] Ferguson, 2015

[8] Bhorat et al, 2021

[9] Baskaran et al, 2020

[10] SASSA, 2021

[11] SASSA, 2020 (a)

[12] Van der Berg, 2014

[13] Based on data from SASSA (2020a) of nearly 13 million CSGs distributed, and StatsSA’s 2020 mid-year population estimate of just under 20 million children under the age of 18 years.

[14] SASSA, 2020 (a)

[15] Bassier et al, 2021

[16] Moore and Seekings, 2019

[17] Ferguson, 2017

[18] Own calculations using Statistics South Africa’s 2020 Quarter 4 Quarterly Labour Force Survey microdata.

[19] Bhorat et al, 2020

[20] https://theconversation.com/south-africa-can-and-should-top-up-child-support-grants-to-avoid-a-humanitarian-crisis-135222.

[21] Köhler and Bhorat, 2020

[22] Bhorat et al, 2021

[23] Assuming a population of 60.14 million as per StatsSA’s 2021 mid-year population estimates.

[24] It is not appropriate to state that 41% of the South African population received social grants given that many recipients receive more than one grant.

[25] For household-level receipt, given that the NIDS-CRAM is not a household-based survey, we cannot directly observe whether sampled individuals co-reside with other sampled individuals who report being grant recipients. Rather, the questionnaire includes a question on how many people in the respondent’s household received a particular grant in the reference month.

[26] Casale and Shepherd, 2020

[27] We utilise non-employment as a broad category here as opposed to unemployment by either the narrow or broad definition to include the searching job-seekers, the discouraged, as well as the economically inactive.

[28] Due to data limitations, we are unable to identify the informally employed in any alternative way.

[29] The caveats are discussed in more detail in our paper.

[30] Ferguson, 2015

[31] Baskaran et al, 2020

[32] SASSA, 2021

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