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Asset indices are widely used, particularly in the analysis of Demographic and Health Surveys, where they have been routinely constructed as "wealth indices." Such indices have been externally validated in a number of contexts. Nevertheless, we show that they often fail an internal validity test, that is, ranking individuals with "rural" assets below individuals with no assets at all. We consider from first principles what sort of indexes might make sense, given the predominantly dummy variable nature of asset schedules. We show that there is, in fact, a way to construct an asset index which does not violate some basic principles and which also has the virtue that it can be used to construct "asset inequality" measures. However, there is a need to pay careful attention to the components of the index. We show this with South African data.JEL Codes: D63, I32

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. JEL Classification: J23, L51

We analyse the long‐term trends in wage inequality in South Africa, using household survey data. We show that the trends in household income inequality are largely driven by changes in wage inequality. Given the detailed nature of our series we show that measurement issues and breaks in the series need to be dealt with in order to draw robust conclusions from the data. Most standard inequality measures show that wage inequality has increased over the period. Nevertheless the choice of measure matters, because there are different trends in different parts of the distribution. It appears that the distribution below the median has become more compressed, while the top of the wage distribution has moved away from the median. The inequality in the labour market translates into even higher inequality in society given that high earners tend to live together with other high earners while low wage individuals often end up sharing their incomes with the unemployed. Furthermore there are many South Africans with access to no wage income. Given the trends analysed here it is not surprising that overall inequality in South Africa has not come down or has even increased since the end of apartheid.

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