921 research outputs found
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Reinstating the importance of categorical inequities in South Africa
No full textSouth Africa was one of the most unequal countries in the world in 1994 and inequality has featured prominently as a key socio-economic and policy challenge over the post-apartheid period. Yet, despite policy interventions with the aim of reducing inequality, these high levels of inequality remain in place. Such resilience in inequality demands from us a better understanding of the mechanisms that reproduce and create inequalities. Having consolidated the research on South Africa’s income and wealth inequality, we explore the interactions between these inequalities and different sets of categories (gender, race and class) in space to surface how the dynamics of inequality relate to mechanisms that create and reproduce inequalities in South Africa. We build this analysis further by taking stock of recent work on social mobility. In the conclusion we pull together this picture of precarious mobility and review policies to overcome inequality against this prevailing reality. These policies have not worked, making clear the urgent need for interdisciplinary research on how to break the inequality traps
Labour market effects of the great lockdown in South Africa: Earnings and employment during 2020–2022
No full textThis paper quantifies the impact of the covid-19 economic shock on aggregate earnings and employment by industry in South Africa. We construct pre-covid-19 counterfactual forecasts for the 2020 Q2 – 2022 Q4 period and compare these with reported earnings and employment levels up to 2021 Q1. We find that total compensation of employees in 2020 Q2 was 9% below forecast while employment was 14% lower than the counterfactual. Between 2020 Q2 and 2021 Q1, aggregate earnings recovered more than three times as quickly as employment, indicating a rise in inequality. We calculate possible recovery paths of earnings and employment to 2022 Q4. We outline implications for the Unemployment Insurance Fund and suggest ways in which the employment recovery might be accelerated
Employment uncertainty in the era of COVID-19: Evidence from NIDS-CRAM and the QLFS
No full textThis paper conducts an analysis of employment uncertainty and trends in South Africa during the first year of the COVID-19 pandemic, using NIDS-CRAM and five waves of Statistics SA's Quarterly Labour Force Survey (QLFS: 2020-Q1 to 2021-Q1). We find that much of the differences in estimates of labour force states including employment, unemployment and not economically active, are due to different initial conditions and different reference periods between the two surveys, as well as the way that uncertain job attachment is measured in the questionnaires. This leads to higher estimates of employment in NIDS-CRAM compared to the QLFS for both a pre-pandemic baseline and over the entire period investigated (February 2020 to March 2021). This implies the two data sources are not strictly comparable, but rather complimentary when analysing different aspects of the labour force. We discuss the implications for labour market research based on these data sources
Information Flows in the South African Post-school Education and Training sector: a focus on university and government stakeholders
No full textThe Post-school Education and Training (PSET) system in South Africa is comprised of a diverse range of education and training institutions, and institutional types. This study provides an overview of the state of data collection, analysis, reporting and dissemination in the public universities and government agencies. The aim of the study was to build an understanding of current practices and how these can be enhanced in order to strengthen the evidence base of planning in the system. Two survey instruments (one for institutions and one for government agencies) were designed and targeted the stakeholders of interest in the PSET system to gather information. The information was analysed with reference to Terenzini’s three intelligence tiers. The study revealed uneven institutional capacity across the system to operate at all three intelligence tiers with only 14 institutions demonstrating the capacity to use web-based systems to formulate targeted interventions to enhance performance. Capacity to conduct analytical research on patterns of institutional performance is also uneven. The flow of information from the DHET appears to be driven predominantly by reporting requirements. The study concludes that more attention needs to be paid to building a culture of collecting, sharing and using evidence for planning, policy and other forms of decision making.Support from the Kresge foundation for this research activity is hereby acknowledged. Opinions expressed and conclusions arrived at, are those of the authors and cannot necessarily be attributed to the Kresge Foundation
Estimating the effect of racial classification on labour market outcomes: A case study from Apartheid South Africa
No full textWhat were the effects of being officially classified as White on labour market outcomes during apartheid in South Africa? South Africa's apartheid government implemented a comprehensive system of discrimination against "non-Whites" that covered every major facet of life. Discrimination in educational opportunities, healthcare, and neighbourhood quality were designed to create productivity differentials across race groups; and these effects would not be included in most estimates of labour market discrimination. We quantify the cumulative effect of all of these forms of discrimination by estimating the causal effect of being classified as White on education, employment and income. Our identification strategy is based on a policy change that privileged ancestry over appearance in the process of racial classification for those born after the 1951 Census. We use census data from 1980, 1991, and 1996, and restrict our sample to Whites and Coloureds. The data exhibits a discontinuity as well as a trend change in racial shares for cohorts born after 1951. Combined, these imply a 6 percentage point lower likelihood of being classified as White for people born 10 years after 1951. Our preferred estimates indicate that being classified as White instead of Coloured resulted in a more than threefold increase in income for men. This corresponds to approximately 65% of the difference in mean incomes between the two population groups. Our findings for women are inconclusive.We are grateful to Keith Breckenridge, seminar participants at the University of Michigan, Middlebury College, the University of Cape Town, the African Economic History conference, University
College Dublin and Maynooth University. Special thanks go to Catherine Kannemeyer and her family for explaining how racial classification operated in practice and the personal impact it could have.
All errors and omissions remain the full responsibility of the authors. We recognize that the use of the term "non-White" is problematic. We apologize for this, but it has proven to be impossible to write this paper without using Apartheid era terminology and racial groups
NIDS-CRAM Wave 1 Data Quality
No full textThis technical report assesses the overall quality of data collected in the first wave of NIDS-CRAM. Several quality dimensions are investigated including the importance of item non-response, measurement error and the degree to which the data on key variables adequately represent the national situation. The focus on these data-quality dimensions is motivated by several considerations. Most obvious is the usefulness of the data in informing policy. To that end this paper with its focus on item level data quality, complements an earlier technical paper that considered the issue of representivity at the level of the sample frame and unit non-response. Surveys around individual and household wellbeing are typically conducted face-to-face. The lockdown in response to Covid-19 forced researchers into new modes of data collection and a consideration of NIDS-CRAM data quality is informative in assessing the feasibility of telephone surveys for policy relevant social science research
Unpacking the potential implications of Covid-19 for gender inequality in the SA labour market
No full textPrevious economic downturns such as the recent 2008-2009 global financial crisis have tended to disproportionately affect male employment due to greater contractions in industries typically filled by men (e.g. manufacturing). However, the expected recession triggered by the current COVID-19 pandemic could lead to worse labour market outcomes for women, exacerbating gender inequality in the labour market. Through an occupational sorting lens, this study highlights how the COVID-19 pandemic might derail the progress made by women in the South African labour market. We utilize occupational context data from the O*NET Survey (US Department of Labour) to characterize COVID-19 risk in two key ways: work that is physically proximate enough to make infection likely, and work that requires regular exposure to infectious disease. These two measures of occupational work context are then merged with the Post-Apartheid Labour Market series (PALMS) to describe the distribution of risk in South Africa shortly before the pandemic. We find that although similar proportions of men and women work in proximate occupations, women are 16 percentage points more likely to be exposed to infectious diseases in their jobs due to their clustering in occupations like domestic work, personal care, nursing, and clerking. Our results suggest that the high interpersonal nature of women’s work coupled by the fact that they still carry out a larger share of child care puts them at a higher disadvantage relative to men in terms of income or job loss as a result of COVID-19. Finally, that men often do dangerous work (e.g. mining) is an often-invoked justification for the gender wage gap. However, the frontline response to COVID-19 has further shone a light on how the labour market undervalues the type of risky work often carried out by women given women are over-represented in health professional, retail shop clerk and personal care work occupations.Branson and Mosomi acknowledge support from the Kresge foundation. Opinions expressed and conclusions arrived at, are those of the authors and cannot necessarily be attributed to the Kresge Foundation
Enterprising women in Southern Africa: When does land ownership matter?
No full textLimited access to finance is one of the major barriers for women entrepreneurs in Africa. This paper presents a model of start-ups in which firms’ sales and profits depend on their productivity and access to credit. However, due to the lack of collateral assets such as land, female entrepreneurs have more constrained access to credit than do men. Testing the model on data from the World Bank Enterprise Surveys in Eswatini, Lesotho, and Zimbabwe, we find land ownership to be important for female entrepreneurial performance in terms of sales levels. This finding suggests that the small Southern African economies would benefit from removing obstacles to women’s land tenure and enabling financial institutions to lend against movable collateral. While land ownership is linked with higher sales levels, it seems less critical for sales growth and innovation where access to short term loans for working capital seems to be key.The authors thank Mina Baliamoune, Mthuli Ncube, and Léonce Ndikumana for stimulating discussions on earlier drafts. Helpful insights were also provided by graduate students in the Applied Econometrics course at the Technical University of Ostrava. Earlier versions were presented at the Conference on Pathways to Gender Equality (American University, Washington DC), the 1st Private Sector Development Research Network Conference (Graduate Institute, Geneva) and the economics seminar series at the University of Gra.The views expressed are those of the authors and not necessarily those of the African Development Bank.Zuzana Brixiová acknowledges funding from the Czech Science Foundation under Grant No. GA19 – 25280S. Fiona Tregenna acknowledges funding under the South African Research Chairs Initiative of the Department of Science and Technology and National Research Foundation of South Africa (Grant No. 98627)
The ‘great regression’ and the protests to come in Latin America
No full textLatin America was in turmoil in 2019. Protests raged across different countries and against governments across the political spectrum. Widespread mobilisation from social organisations denounced corruption and voiced various demands, including greater political freedoms, better and affordable public services, and the urgent need to tackle corruption and inequality in Mexico, Guatemala, Nicaragua, Honduras, Venezuela, Colombia, Ecuador, Peru, Bolivia, Chile and Brazil. The region ended the year with unfulfilled promises of a new social pact, and the promise of intensified mobilisations
Sample design and weighting in the NIDS-CRAM survey
No full textThe sample frame for NIDS-CRAM is NIDS wave 5, which was conducted in 2017. Continuing sample members (CSMs) and temporary sample members (TSMs) who were 18 years or older at the time of the NIDS-CRAM wave 1 fieldwork in April 2020 were reinterviewed. The NIDS-CRAM sample is drawn using a stratified sampling design but with “batch sampling”.
This batch sampling method was designed to allow flexibility to adjust the sampling rate in each stratum as information about stratum response rates became available as the “fieldwork” progressed. The motivation is that there was substantial uncertainty about both the level and drivers of non-response to a telephone survey and about the sample size that was possible given the response rates and budget and time constraints.This paper was funded by the CRAM study and is available on their website. We thank Martin Wittenberg, Nicola Branson, Tim Brophy, Reza Daniels and Kim Ingle for very helpful inputs on the sample design and usage of the NIDS wave 5 data as the sample frame. All errors and omissions remain the responsibility of the authors