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Methods for credible evaluation of programme stimulus effects in South Africa
No full textIn response to the effects of the COVID-19 pandemic, in 2020-21 the South African government instituted various economic relief and stimulus programmes. These included substantial increases to social grant disbursements and a large new targeted jobs programme. Potential “spillover” or “multiplier” effects of these programmes are an important part of prospective policy evaluation and are of particular interest during a period of fiscal constraints. This review considers approaches for quantitatively evaluating stimulus effects of government programmes, with particular reference to the South African pandemic response. After discussing the general approach of random and quasi-random programme evaluation methods, we review the existing international literature evaluating stimulus effects of jobs programmes and cash transfers. We highlight key lessons in terms of methods, data requirements, and the necessity of rigorous local evaluations. We also describe the South African programmes and discuss local data sources. We suggest that the social grant top-ups and jobs programme present an exciting opportunity to credibly measure programme stimulus effects in South Africa.We are grateful for comments on this paper from Murray Leibbrandt and Kate Philip, and for inputs which informed this work from Karthik Muralidharan, Daniel Riera-Crichton, participants of the first and second workshops on measuring stimulus effects, and the BankservAfrica team. We thank the Project Management Office (PMO) in the South African Presidency, Sharmi Surianarain of the Harambee Youth Employment Accelerator, and Agence Française de Développement (AFD) for assistance in organising and facilitating the workshops on stimulus effects. This review is an input into a joint project of the PMO, AFD and SALDRU concerned with evaluating the stimulus effects of income transfer programmes such as the Presidential Employment Stimulus and 2020-21 social grant top-ups in South Africa
The deepening of inequalities in Latin America during and after the pandemic
No full textLatin America continues in social, economic, and political turmoil in 2021. The vulnerabilities set by pre-existing conditions such as persistent inequality, high informality and exclusionary social protection systems have been exacerbated by recent health and humanitarian crises unprecedented experienced in the region’s modern history. These crises have significantly impacted on socioeconomic indicators, as accounted in the increased levels of vulnerability and poverty next to stagnant economic growth. Public sector responses have been relevant but insufficient to cushion the effect of these multiple crises and, in many cases, unveiled the degree to which unrequested orthodoxy limited the role of the state in providing adequate support to its citizens. The chapter explores efforts to tackle the impacts of compounded deprivations of spatial segregation, pervasive informality, gendered and racialised vulnerabilities, and the education crisis, and explores the options governments face in terms of reversing the adverse effects of the pandemic while sustaining the economic rebound. In a context of polarised political participation, discontent will inevitably lead to contention and, in some cases, instability and violence, should the governments choose to be aloof about the need for a socially just recovery
Employment and earnings by industry before Covid-19
No full textEmployment levels and the distribution of earnings by industry in 2010 and 2019/20 are examined in this paper, illustrating trends over this decade before the impact of Covid-19 and the accompanying economic downturn. Drawing on both the Quarterly Labour Force Survey (QLFS) and the Quarterly Employment Statistics (QES) aggregates, we provide estimates of the distribution of earnings consistent with the System of National Accounts (SNA) income and production aggregates.
We draw attention to similarities and differences between the QLFS, QES and SNA data sources, and note differences in the implicit trends over the 2010-2020 decade. We provide distributions of gross earnings within eleven employment and industry sectors, consistent with the national accounts compensation of employees’ aggregates adjusted to include earned income attributable to employers and the self-employed in unincorporated enterprises.
We find evidence that the national accounts have under-estimated growth in earnings since 2010, and that the levels of both nominal and real GDP in recent years are understated. Nonetheless, we find that QLFS estimates of earnings have to be raised by about 50 per cent in order to generate earnings levels consistent with the national production accounts. The adjustments required vary considerably by industry. We compile uprated earnings distributions by industry in two ways: aligned with industry-specific SNA aggregate earnings, and uniformly uprated to align with aggregate SNA earnings.
Both employment and earnings were severely disrupted by the 2020 Covid-19 economic shock. At the time of writing (early 2021) the economic recovery path is far from clear. This paper provides sectoral benchmark data from official sources against which the recovery might be assessed but also indicates that there are substantial discrepancies between the available measures of earnings by industry
South Africa’s Unemployment Insurance Fund Benefit Function: A Mathematical Critique
No full textThis paper highlights the unnecessary complexity of South Africa’s Unemployment Insurance Fund (UIF) benefit function, known as the Income Replacement Rate (IRR), and the disadvantageous manner in which the IRR is low for most earners. Possible alternative formulae are described, along with the implications for total expenditure on the UIF. The paper recommends simpler (and more optimal) formulae
Reweighting the OHS and GHS to improve data quality: representativeness, household counts, and small households
No full textThe October Household Surveys (OHS) (1994-9) and the General Household Surveys (GHS) (2002-present) collected by StatsSA comprise South Africa's only nationally-representative time series with information on both people and households for (almost) every year of the post-apartheid period. However, the quality of these data has been compromised in three ways by how the survey weights have been calibrated. We document these problems and their implications in detail; and then use cross-entropy estimation to recalibrate the survey weights for a stacked version of these surveys between 1995 and 2011 to address these weaknesses. The first of these is that the weight calibration procedure breaks with sampling practise by calibrating person and household weights separately. This creates conceptual problems because the data is not properly representative of the population. It also creates statistical problems, including that a series of total population and household counts cannot be reliably extracted from the series, which is typically a first-order output for such a time series. Secondly, issues with the benchmarks StatsSA use mean the series of household counts extracted from the GHS is probably too low. Thirdly, no compensation is made by the survey weights for the chronic undersampling of small households over the entire period. Our new weights make headway in resolving these issues. Our weights yield consistent counts of people and households benchmarked on both person and household auxiliary information for the first time; and, benchmarked counts of one-, two-, and three-person households. Work is ongoing to improve the weights.Amy Thornton acknowledges financial support from the NRF Chair in Poverty and Inequality
Research and from the African Centre for Inequality Research
The role of employment history and age during COVID-19: Understanding 2020 South African employment dynamics in historical context
No full textIn this paper we seek to understand how the employment of different age groups in 2020 was affected by the COVID-19 pandemic in South Africa, along with the correlation between individuals’ outcomes and their employment history. First, cross-sectional employment outcomes by age (and education) are presented for four 2020 months (February, April, June and October, as measured in NIDS-CRAM). Thereafter, employment dynamics over the year are described and contrasted with employment dynamics from five pre-COVID years (2010-2014, as measured in panels based on the QLFS). We find that several aspects of the churning observed in 2020 far exceed transitions from these benchmark years, with a greater proportion of those without employment at the beginning of the year finding work by the end of the year and much higher job attainment among youth. Finally, we analyse employment outcomes during 2020 according to individuals’ employment history between 2012 and 2017 (as captured in NIDS waves 3 to 5). We find that employment history correlated strongly with 2020 employment outcomes: individuals with stronger employment histories were more likely to remain stably employed, or, among the non-employed, to find work. This shows the importance of historical context in understanding the employment effects of COVID-19
Creating household weights for NIDS-CRAM
No full textNIDS-CRAM is widely used to investigate the impact of the COVID pandemic on individuals and households. However, because NIDS-CRAM is a survey of individuals it is difficult to make accurate statements about households. Nevertheless many issues of interest, such as the hunger questions in NIDS-CRAM, are about the household and not just the respondent.
The problem with using the existing NIDS-CRAM weights for these analyses is that there is double-counting: there are potentially many individuals from the same household in the NIDS-CRAM survey. We show that overlapping membership affects between 40% to 50% of the observations.
In this paper we lay out the theory for dealing with this problem and generate a set of "household weights" to reduce the double-counting. We use these weights to produce some initial estimates of how prevalent hunger might have been during the lockdown.
Paradoxically estimates of the fraction of households a ected by hunger are not changed much by using the household weights rather than the person weights released with NIDS-CRAM. The reason for this is that hunger is only very weakly associated with household size, so the double-counting implicit in using the person weights does not skew the estimates much.
However if one wants to generate estimates of the number of households or people affected by hunger the household weights make a much bigger difference. Indeed, we generate a first set of numbers that quantify the problem.
For instance somewhere between 1.5 million and 3.1 million children were a ected by hunger at the time of the field work for NIDS-CRAM wave 5. These estimates have to be treated with some caution, because our weights do not properly deal with changes in the distribution of households since 2017, in particular new household formation
Pareto efficient intrahousehold allocations and land rights: evidence from South Africa
No full textWe study whether South African farm households participating in a land reform program make Pareto efficient intrahousehold consumption decisions. Using evaluation survey data of beneficiary households participating in South Africa’s Land Redistribution for Agricultural Development (LRAD) program, we estimate and test the unitary and collective models of intrahousehold resource allocation. By estimating the households’ demand function’s responses to the size of land grant transfers going to resident men and women, we find evidence contradicting the income pooling hypothesis of the unitary model. On the other hand, we cannot reject the hypothesis allocations are Pareto efficient. A test based on a linearisation of the demand system also favours Pareto efficiency.We thank Michael Carter and seminar participants at the University of Pretoria for useful comments. Fieldwork for the study was funded by the World Bank
CVACS Survey 1 Preliminary Results
No full textThe COVID-19 Vaccine Survey (CVACS) aims to collect high quality, timely information to inform the development of campaigns and programmes to improve COVID-19 vaccination uptake in South Africa. Preliminary findings from the CVACS Round 1 survey were released in a webinar on 14 December 2021. Though data collection for the first round of interviews was still underway, results based off the approximately 2000 interviews first conducted were presented at this webinar. These preliminary results were made public as the CVACS team felt that they would still provide important insights for South African vaccine demand creators and policy makers in the development of campaigns and programmes for improved COVID-19 vaccination rates, especially in light of the approaching festive season and the circulating Omicron variant driving high infection rates. The full webinar is available to view on YouTube: https://www.youtube.com/watch?v=PCb8pEbZQS
Household Survival Strategies during COVID-19: Evidence from Panel Data in South Africa
No full textAfter an income shock, households reduce spending and asset holding, diversify income sources, and change household composition or location. Migration is common in South Africa, often resulting in food insecurity. During the COVID-19 pandemic, the unemployment rate surpassed thirty percent, accompanied by extreme poverty levels. The social relief of distress grant, the old age pension, and employment income all significantly reduced food insecurity. SRD receipt reduced household hunger levels by ten percent, and severe hunger in children by more than twenty percent in vulnerable households. In contrast, mobility strategies did not effectively prevent food insecurity in households during the pandemic.The author would like to gratefully acknowledge funding from the National Research Foundation South African Research Chair in Poverty and Inequality Research