Exclusive growth? Rapidly increasing top incomes amid low national growth in South Africa

Abstract

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The creation of an individual panel using administrative tax microdata in South Africa

“…Figure 3 shows taxable incomes at the 90th, 50th, and 10th percentiles. Further research, following on from Wittenberg (2017) and Bassier and Woolard (2018), could be undertaken to assess how the income distribution from the panel, especially at the top end, compares to surveys in South Africa such as the Income and Expenditure Survey, the QLFS, and the National Income Dynamics Survey. Previous research to compare these data sources has either used the aggregated Tax Statistics published by SARS and National Treasury, or a sample of micro data from one or two years, both of which have relied on the ITR12 returns alone.…”

Taking stock of South African income inequality

“…This paper is complemented by recent work by Bassier and Woolard (2018), who drill down into the SARS data and household survey data to make two critical points. The first is that in the years between 2003 and 2015, nearly 60 per cent of the population earned zero taxable income.…”

“…The use of this database has also helped identify more top earners than previously thought. For instance, Credit Suisse in 2016 estimated that there were about 45,000 dollar millionaires in the country, but Bassier and Woolard (2018) put the number at about 182,000. Hundenborn et al (2018b) calculate that the number of people who earned over R10 million per year had more than doubled from 482 in 2011 to 1,048 in 2014.…”

Assessing the quality of the income data used in SAMOD, a South African tax-benefit microsimulation model

“…A number of recent studies have explored in detail the quality of income data using South African survey or Census data. These include detailed fiscal analysis using the Income and Expenditure Survey (IES) 2010/11 (Inchauste et al, 2015); spatial analysis of small area level income data using the 2011 Census of Population (Noble et al, 2013); analysis of data on wealth using the National Income Dynamics Study (NIDS) (Orthofer, 2016); in-depth analysis of the income distribution also using NIDS (Hundenborn et al, 2017) and the Post-Apartheid Labour Market Series (PALMS) dataset (Bassier and Woolard, 2018;Wittenberg, 2017). The latter four studies drew from administrative data on income tax to validate the income data in NIDS (Hundenborn et al, 2017;Orthofer, 2016) and PALMS (Bassier and Woolard, 2018;Wittenberg, 2017) respectively.…”

“…These include detailed fiscal analysis using the Income and Expenditure Survey (IES) 2010/11 (Inchauste et al, 2015); spatial analysis of small area level income data using the 2011 Census of Population (Noble et al, 2013); analysis of data on wealth using the National Income Dynamics Study (NIDS) (Orthofer, 2016); in-depth analysis of the income distribution also using NIDS (Hundenborn et al, 2017) and the Post-Apartheid Labour Market Series (PALMS) dataset (Bassier and Woolard, 2018;Wittenberg, 2017). The latter four studies drew from administrative data on income tax to validate the income data in NIDS (Hundenborn et al, 2017;Orthofer, 2016) and PALMS (Bassier and Woolard, 2018;Wittenberg, 2017) respectively. There is a growing recognition of the importance of administrative data as a data resource on income, especially with reference to individuals working in the formal sector, and recently the National Treasury (NT) and the South African Revenue Service (SARS) have made anonymized personal income tax data available for research purposes (Arndt, 2018).…”