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The information contained in databases of summary statistics should look plausible when viewed in context. Judged by that criterion the Standardized World Income Inequality Database (SWIID) comes up short with its South African data. Figure 1 contains the series as extracted from the SWIID web site (Solt 2014b). The 95% confidence bands suggest that inequality in 1965, at the height of apartheid, was significantly lower than in the 2000s. This, however, flies in the face of much other evidence. For instance it is well-known that Black mine workers' wages were static in real terms from the early twentieth century right up to the 1970s (e.g. van der Berg 1989). The wages of white miners, by contrast, increased, so that the ratio of White to Black mine wages reached its maximum of twenty to one in 1969 (Devereux 1983, p.18). Simkins (1979) estimated the Gini coefficient in 1970 at 0.71, which seems more in line with the political and social realities. Trying to understand how the SWIID may have arrived at such a misleading estimate is instructive about the types of problems that may be lurking elsewhere in the database.There are four potential sources of error in SWIID: measurement error, model error, imputation error and sampling error . ; Martin Wittenberg - Director, DataFirst and Professor, School of Economics, University of Cape Town

Abstract
The Post-Apartheid Labour Market Series (palms) is a compilation of microdata from 69 household surveys conducted in South Africa. The dataset and the code used to create the data are publicly available from DataFirst, a data repository at the University of Cape Town (www.doi.org/10.25828/gtr1-8r20). To harmonise the data required understanding the differences across the surveys, which has generated new knowledge about the South African labour market.

South Africa has seen a dramatic decrease in household size over the last decade. In Table 1 we show that over the eight-and-a-half years from October 1995 to March 2004 the average household size has decreased by 20% or 0.74 persons (see also Pirouz 2004). Consequently for a fixed population size there would have been 20% more households in March 2004 than in October 1995. Such a rapid rate of household formation is interesting in and of itself. From the perspective of a policy maker it is particularly vital to understand this process. The new democratic government has committed itself to extending infrastructure and social services to households in deprived communities and now finds that it is trying to catch a moving target. The backlogs are increasing as the services are being rolled out. We will suggest below that there might be a connection between these two processes.

AbstractAnalysts of theSouthAfrican labour market have mainly used household surveys to analyse the labour market. It has been more difficult to explore the labour demand of firms, as a result of limited data availability. We use theQuarterlyEmploymentStatistics survey, an enterprise survey conducted byStatisticsSouthAfrica, to explore howSouthAfrican firms create and destroy jobs, thereby shedding light on many of the policy questions that are relevant in a high unemployment society likeSouthAfrica. We find that job creation and destruction rates are similar to those found inOrganisation forEconomicCo‐operation andDevelopment countries. There is little evidence that labour legislation creates rigidities that prevent firms from hiring or firing workers. We also find that larger firms are better net creators of jobs than small firms and that net job creation rates are negative in manufacturing. Our research has important policy implications – particularly for theSouthAfricanNationalPlanningCommission's 2030 plan, in which new jobs are envisaged to come mainly from small‐ and medium‐sized firms. Our research suggests that this scenario is not likely without changes to policy or legislation.

Analysts of the South African labour market have mainly used household surveys to analyse the labour market. It has been more difficult to explore the labour demand of firms, as a result of limited data availability. We use the Quarterly Employment Statistics survey, an enterprise survey conducted by Statistics South Africa, to explore how South African firms create and destroy jobs, thereby shedding light on many of the policy questions that are relevant in a high unemployment society like South Africa. We find that job creation and destruction rates are similar to those found in Organisation for Economic Co-operation and Development countries. There is little evidence that labour legislation creates rigidities that prevent firms from hiring or firing workers. We also find that larger firms are better net creators of jobs than small firms and that net job creation rates are negative in manufacturing. Our research has important policy implications – particularly for the South African National Planning Commission's 2030 plan, in which new jobs are envisaged to come mainly from small- and medium-sized firms. Our research suggests that this scenario is not likely without changes to policy or legislation.

Analysts of the South African labour market have predominantly used household surveys to analyse the labour market. It has been more di fficult to explore labour demand from the firm side, as a result of limited data from relatively small cross sectional firm surveys, mainly funded by the World Bank. We use the Quarterly Employment Survey conducted by Statistics South Africa that allows us to explore how South African enterprises create and destroy jobs, shedding light on many of the policy questions that are relevant in a high unemployment society like South Africa. We find job creation and destruction rates are similar to those found in OECD countries. There is little evidence that labour legislation creates rigidities that prevent firms from hiring or fi ring workers. We also find that larger firms are better net creators of jobs than small firms and that net job creation rates are negative in manufacturing, consistent with work using household surveys. Our research has important policy implications - particularly for the National Planning Commission's suggestion that new jobs will come mainly from small and medium sized fi rms. Our research suggests this is not likely without changes to policy or legislation. This is a joint SALDRU/DataFirst Working Paper ; We thank Naume Malepe and Mandla Masemula of Statistics South Africa for their help in explaining the QES data and sampling procedures. We are grateful for helpful comments from participants at the SALDRU seminar, University of Cape Town, the Firms and Labour Markets conference, University of Oxford and the Micro-econometric analysis of South African data conference, Durban. This research was made possible by an exploratory grant awarded by the Private Enterprise Development in Low-Income Countries (PEDL) research initiative. PEDL is a joint research initiative of the Centre for Economic Policy Research (CEPR) and the UK Department For International Development (DFID). It aims to develop a research programme focusing on private-sector development in low-income countries.