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This paper provides an introduction to this Special Issue of Development Southern Africa that evaluates the impact of COVID-19 in South Africa, one year into the pandemic. All of the papers use evidence from the National Income Dynamics Study – Coronavirus Rapid Mobile Survey (NIDS-CRAM), a five-wave longitudinal survey conducted from April 2020 to July 2021. As we write this article in June 2022, South Africa has just returned to the same level of GDP that it had at the end of 2019. This two-year period marks one of the most tumultuous in the country's economic history. We showcase results pertaining to employment, income support, hunger, schooling, early childhood development, mental health, and vaccine hesitancy. We also reflect on the policy learnings that can be gleaned in each of these domains and draw on some of the international lessons learnt to point to the way forward. [ABSTRACT FROM AUTHOR]

This paper conducts an analysis of employment uncertainty 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 complementary when analysing different aspects of the labour force. We discuss the implications for labour market research based on these data sources. [ABSTRACT FROM AUTHOR]

This paper examines the quality of data on household assets, liabilities and net worth in the South African National Income Dynamics Study (NIDS) Wave 2. The NIDS is the first nationally representative survey on household wealth in South Africa. The cross-sectionally weighted data are found to be fit for use in terms of the univariate distributions of net worth, assets and liabilities, but population totals are probably underestimated due to the presence of missing wealth data in Phase 2 of Wave 2 that is not taken into account in the weights. When compared with national accounts estimates of household net worth, there is an apparent inversion of the estimated totals of financial assets versus non-financial assets. Further research is required into why this is so. We find that the NIDS wealth module is a suitable instrument for the analysis of household wealth. [ABSTRACT FROM PUBLISHER]

This paper evaluates a topic in the globalization and poverty debate that is often difficult to measure, namely the transmission of price changes associated with tariff liberalization to households. Furthermore, it raises the question of whether there are discernible differences between male- and female-headed households that affect this consumption-trade link. It is a partial analysis as a consequence, but one that demonstrates the importance of such a focus for continued research and policy development surrounding the impacts of globalization. Specifically, the paper evaluates how tariff changes impacted male- and female-headed households in South Africa over the discrete periods 1995, 2000, and 2004. The analysis of consumption trends by sex of household head shows statistically significant differences which confirm that resources are managed differently between the sexes, and these are transmitted through to the tariff incidence analysis. On the whole, it was found that: (1) male-headed households almost always bear a greater share of the tariff incidence compared to female-headed; (2) both male- and female-headed households — across all expenditure quantiles other than the most wealthy — bear a greater share of the tariff burden compared to their share of total expenditure; and (3) changes to the incidence over 1995, 2000, and 2004 between the sexes mimicked the trends for the population as a whole, but showed crucial differences at the bottom end of the expenditure distribution. This suggests that the sex of the household head matters, and must be considered in addition to other household identifying factors (e.g. socio-economic status) when evaluating the impacts of tariff liberalization. [ABSTRACT FROM AUTHOR]