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This paper conducts an analysis of labour market dynamics in South Africa during the initial period of lockdown, from the end of March to the end of April 2020, using the first wave of the NIDS‐CRAM (2020) survey. Within our sample of over 6,000 adults aged 18 to 59, we found that there was a very large decrease in employment. The fraction of the sample that was conventionally classified as employed decreased from 57% in February to 48% in April. If we further exclude temporarily absent workers, which we term “furloughed” employees, this fraction decreases further to 38%. Thus, about one out of every three employed people in our sample either lost their job or did not work and received no wages during April. This has extremely large implications for poverty and welfare. We further analyse the labour market by comparing across demographic groups as defined by race, by gender, by age groups, by geographic areas and by education levels. The over‐arching finding from this analysis is that the job losses were not uniformly distributed amongst the different groups. In particular, groups who have always been more vulnerable – such as women, African/Blacks, youth and less educated groups – have been disproportionately negatively affected.

This paper conducts a review of the literature on skills shortages in South Africa. It is demonstrated that different Government departments have different views concerning the definition of skills shortages. This is largely due to the omission in any official government literature of tying the concept of "skills shortages" to productivity. There is also a complex and frequently overlapping institutional architecture that undermines the effective administration of skills development. An important example of this is that the link between providing skills training and accrediting individuals with a qualification that acknowledges this training is very poorly administered, highlighting poor co-ordination between the Department of Labour and Department of Education. Among Sectoral Education andTraining Authorities (SETAs), there is also under-performance on their mandate to provide skills training for the unemployed -an activity that is flagged in this review simply because of the strong public good nature to this activity and the fact that only SETAs are institutionally empowered to effect this change. A variety of policy recommendations are made with respect to both closed-and open-economy solutions to skills shortages. A key point is that immigration legislation must be relaxed in order to help solve the pervasive skills constraints in South Africa.

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We investigate the question whether problem gambling (PG) in a recent South African sample, as measured by the Problem Gambling Severity Index (PGSI), is dimensional or categorical. We use two taxometric procedures, Mean Above Minus Below A Cut (MAMBAC) and Maxim Covariance (MAXCOV), to investigate the taxonic structure of PG as constructed by the PGSI. Data are from the 2010 South African National Urban Prevalence Study of Gambling Behavior. A representative sample of the urban adult population in South Africa (N = 3,000). Responses are to the 9 item PGSI. MAMBAC provided positive but modest evidence that PG as measured by the PGSI was taxonic. MAXCOV pointed more strongly to the same conclusion. These analyses also provide evidence that a PGSI cutoff score of 10 rather than the standard 8 may be called for. PG as constructed by the PGSI may best be thought of as categorical, but further studies with more theory based measurements are needed to determine whether this holds in a wider range of samples and for other screens. A higher cutoff score may be called for on the PGSI when it is used for research purposes to avoid false positives.