economic inequality in south africa essay

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Article Contents

1. introduction, 2. concepts and data sources, 3. methodology, 4. the distribution of wealth in south africa: key results and comparative perspectives, 5. robustness checks, 6. conclusion, data availability.

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Wealth Inequality in South Africa, 1993–2017

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Aroop Chatterjee, Léo Czajka, Amory Gethin, Wealth Inequality in South Africa, 1993–2017, The World Bank Economic Review , Volume 36, Issue 1, February 2022, Pages 19–36, https://doi.org/10.1093/wber/lhab012

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This article estimates the distribution of personal wealth in South Africa by combining microdata covering the universe of income tax returns, household surveys, and macroeconomic balance sheet statistics. South Africa is characterized by unparalleled levels of wealth concentration. The top 10 percent own 86 percent of aggregate wealth and the top 0.1 percent close to one-third. The top 0.01 percent of the distribution (3,500 individuals) concentrate 15 percent of household net worth, more than the bottom 90 percent as a whole. Such levels of inequality can be accounted for in all forms of assets at the top end, including housing, pension funds, and financial assets. There has been no sign of decreasing inequality since the end of apartheid.

A growing number of studies have made significant progress in measuring the distribution of household income and consumption within countries and over time, yet still little is known on the dynamics of household wealth. This knowledge gap is particularly acute in the developing world, where available data sources are scarce, often insufficiently detailed, and prone to important measurement error. Given the rise of global wealth concentration ( Alvaredo et al. 2018 ; Zucman 2019 ) and the policy challenges it poses in terms of tax evasion ( Alstadsæter, Johannesen, and Zucman 2019 ; Kleven et al. 2020 ; Londoño-Vélez and Ávila-Mahecha 2021 ) and political equilibrium ( Esteban and Ray 2006 ; Bombardini and Trebbi 2020 ; Bertrand et al. 2020 ), there is a pressing need to address this shortcoming and improve our knowledge of the wealth distribution.

This paper estimates the distribution of household wealth in South Africa from 1993 to 2017 by combining household survey data, tax microdata, and macroeconomic balance sheet statistics. A number of results emerge from our analysis.

First, South Africa displays unparalleled levels of wealth concentration. The top 10 percent of South African wealth holders own more than 85 percent of household wealth, while the top 1 percent wealth share reaches 55 percent. The top 0.01 percent (about 3,500 adults) own a higher share of wealth than the bottom 90 percent as a whole (about 32 million individuals). The average wealth of the bottom 50 percent is negative: the market value of their assets is lower than their liabilities. Such levels of wealth inequality are higher than in any other country for which comparable, high-quality estimates of the wealth distribution are available (namely France, the United Kingdom, the United States, Russia, China, and India).

Secondly, there is no evidence that wealth inequality has decreased since the end of the apartheid regime. The top 10 percent wealth share has fluctuated between 80 percent and 90 percent between 1993 and 2017, largely as the result of the rise and fall of household debt before and after the 2007–2008 crisis, with no sign of long-run trend. If anything, the available evidence suggests that the share of wealth captured by the top 1 percent and the top 0.01 percent may even have increased. This result is particularly striking considering South Africa’s recent history of positive growth (real average income and wealth per adult respectively increased by 19 percent and 33 percent from 1993 to 2017) and greater racial inclusiveness (all discriminatory laws against oppressed racial groups had been abolished by 1991).

Thirdly, these inequalities are reproduced at the level of all asset classes. The top 10 percent of wealth holders own more than 55 percent of business assets and housing wealth, and over 99 percent of bonds and stock. Financial assets constitute the bulk of the assets of the top 0.1 percent, while owner-occupied housing and pension wealth are the main holdings of the bottom 90 percent. Significant wealth accumulation is visible over the life cycle, but levels of wealth concentration within each age group are almost perfectly similar to those measured for the full population. This suggests that individuals across the wealth distribution do accumulate at relatively similar paces but start from very different initial endowments, hence pointing to the importance of inheritance.

Previous studies on post-apartheid economic inequality have focused on income, but the literature on wealth remains extremely scarce. Two studies have attempted to measure the distribution of wealth in South Africa ( Daniels and Augustine 2016 ; Mbewe and Woolard 2016 ), yet they suffer from two major limitations. 1 First, they cover only one (2015) or two years (2010, 2015) of data and therefore cannot assess any long-run trends in wealth inequality since the end of apartheid. Secondly, they rely exclusively on the National Income Dynamics Study, a wealth survey that greatly underestimates wealth concentration within the top 10 percent (this issue and its implications are discussed in more detail in Robustness Checks). This is in large part due to substantial underreporting of financial assets by survey respondents, a limitation that has now been extensively documented in the inequality measurement literature ( Korinek, Mistiaen, and Ravallion 2006 ; Alvaredo et al. 2020 ; Blanchet, Fournier, and Piketty 2017 ; Blanchet, Flores, and Morgan 2018 ), as well as by the authors of the previous studies themselves ( Daniels and Augustine 2016 ).

By contrast, following income capitalization approaches recently applied in the United States ( Saez and Zucman 2016 ) and France ( Garbinti, Goupille-Lebret, and Piketty 2021 ), our methodology combines survey and tax microdata with macrodata on household wealth totals. Unlike previous studies, it ensures that average wealth and the portfolio composition of assets across the distribution are fully consistent with the household balance sheet statistics published by the South African Reserve Bank. It allows us to obtain a much more reliable picture of wealth inequality within the top 10 percent and especially within the top 1 percent, which is key to understanding wealth dynamics in countries such as South Africa where wealth concentration is extreme. Importantly, it allows us to cover the entire 1993–2017 period, as well as to compare wealth inequality in South Africa to other countries where similar exercises have been performed.

Finally, this paper also contributes to the methodological literature on the measurement of wealth inequality in developing countries. By comparing estimates of the wealth distribution obtained with three different methodologies—direct measurement of net worth, rescaling of reported wealth components to balance sheet totals, and capitalization of income flows—we show that capitalizing reported income flows to match macroeconomic wealth totals can yield relatively good results, even in the absence of income tax microdata. Crucially, these estimates appear to be much more reliable than those solely relying on survey-based self-reported wealth, which omit the bulk of financial wealth. In other words, bridging the micro–macro gap in wealth measurement appears to be an essential step to accurately measure the wealth distribution. This opens new avenues for estimating the dynamics of wealth inequality in low- and middle-income countries, where wealth microdata are unavailable or unreliable, yet where macroeconomic balance sheet statistics can be usefully combined with surveys collecting data on household income. In that respect, we hope that this paper can serve as a useful guide for future studies aiming to measure wealth inequality in countries with limited data such as South Africa.

The rest of the paper is organized as follows. We first define the key concepts and present the main data sources used in this article. We then explain the methodology applied to combine these data sources. Finally, we present our main results on the evolution of wealth inequality in South Africa, and we contrast them with those obtained from alternative methodologies.

Following the United Nations System of National Accounts (UN SNA) guidelines ( United Nations 2009 ), we define household wealth as the total market value of the assets and liabilities held by the household sector. Using this concept is central to produce comparable estimates over time and across countries. Assets can be classified into eight broad categories: owner-occupied housing, tenant-occupied housing, unincorporated business assets, pensions, life insurance, bonds, equity, and currency (deposits, notes, and coins). Liabilities can be divided into mortgage debt and all other debts (including consumer credits, credit cards, and informal loans). 2 As with most countries in the world, there exists no unified administrative database in South Africa measuring wealth at the micro level for the full population. 3 In the absence of such information, the distribution of household wealth in South Africa has to be measured by combining several complementary data sources.

Macroeconomic Data .  In South Africa, the first comprehensive attempt to estimate the value of total household wealth in the economy goes back to Muellbauer and Aron (1999) , who collect and combine a number of data sources to provide figures on the assets and liabilities of the household sector since 1975. The South African Reserve Bank (SARB) has since then updated and revised these figures on a yearly basis. The only alternative data source that would allow us to approximate total household wealth are waves 4 (2015) and 5 (2017) of the National Income Dynamics Study (NIDS). 4 As it covers only two years, this survey offers little scope to study the evolution of wealth inequality in the long run. Moreover, it suffers from several limitations (internal inconsistencies, measurement errors, implausibly low aggregates) documented in Robustness Checks (see also supplementary online appendix S2 ). For these reasons, we prefer not to rely on this source. Throughout our series, all wealth totals thus come from macroeconomic balance sheets published by the SARB. They are then combined with diverse microdata sources to estimate how these aggregates are distributed.

Personal Income Tax Data .  We exploit Personal Income Tax (PIT) data compiled by the South African Revenue Service (SARS) to measure the distribution of wages, pension income, pension contributions, mixed income, and capital income (rents, interest, and dividends) for the top 30 percent of the population. This individual panel covers two types of tax statements over the 2010–2017 period: IRP5 forms, which are submitted to SARS by employers on behalf of their employees and cover wages and pension contributions, and ITR12 forms, which are self-assessed by all taxpayers who need to disclose information on mixed, rental, interest, and dividend incomes. 5 Due to its administrative nature, this data covers the full tax-paying population, including individual observations at the very top of the distribution, which greatly increases the granularity of measured income flows. This is an advantage over surveys, which often suffer from sample biases and higher nonresponse rates among the wealthiest.

Household Surveys .  Finally, we combine a number of household surveys to cover individuals and income or wealth concepts not captured by the tax data. We use surveys for three main purposes: to measure the distribution of key income variables for the bottom 70 percent of the population; to estimate the distribution of debts and assets that do not generate income flows and hence cannot be capitalized (owner-occupied housing, currency); and to extrapolate our 2010–2017 series back to 1993. These include two main types of surveys: 7 “income surveys” 6 covering all forms of income received by individuals (as well as certain wealth components such as housing and debts), and 54 “labor force surveys” 7 conducted on a more regular basis since 2000 and mainly covering wages and mixed income.

This section presents the methodology used to estimate the distribution of household wealth in South Africa since 1993. First, a harmonized survey microfile is built by merging existing household surveys. Surveys are then combined with tax data to better capture the top end of the distribution. Finally, measures of net worth are derived by capitalizing relevant income flows and rescaling other assets and liabilities to macro totals.

Harmonization of Household Surveys .  We begin by combining household surveys to estimate the distribution of available income and wealth components, on a yearly basis, throughout the 1993–2017 period. Starting from available income surveys (1993, 1995, 2000, 2005, 2008, 2010, 2015), we first interpolate missing years from 1993 to 2017 by creating new datasets resulting from the combination and proportional reweighting of the two adjacent surveys. Yearly distributions of gross wages and mixed incomes are then corrected to make them match those reported in the Labour Force Survey series since 2000. In broad strokes, this process allows us to obtain a harmonized survey microfile covering every year from 1993 to 2017, in which the distributions of available income and wealth components are fully consistent with information reported in both income surveys (for all income concepts excluding wages and mixed income) and labor force surveys (for wages and mixed income). More details on these methodological steps are available in supplementary online appendix S2 .

Combination of Household Surveys with Tax Data .  Survey distributions are combined with PIT data to better capture the top end of the distribution in two steps. First, we derive an income concept that is comparable between the survey and tax data, which we refer to as “merging income,” 8 and we merge the two data sources based on the exact rank of merging income observed at the individual level. We then identify the quantile of the South African income distribution q above which reported merging incomes become higher in the tax data than in the survey data, and we assume that the tax data is more reliable than the survey data only above q . In practice, this implies keeping all variables from the survey data below q , and replacing all comparable variables from the tax data above q (wages, mixed income, rental income, interest, dividends, private pension income, and contributions to pension funds). Between 2010 and 2017, we find q to be consistently located between the 70th and the 75th percentiles, so that we use the tax microdata to cover the top 25–30 percent of the income distribution. 9

Income Capitalization and Rescaling .  The income capitalization method consists in using capital income flows (e.g., dividends) to approximate the distribution of households’ assets and liabilities (e.g., shares). In our case, given that the SARB balance sheet is the best available data source to capture the level and composition of total household wealth in South Africa, this implies distributing each aggregate in proportion to its income flow measured at the micro level. The core assumption is that of constant rates of return by asset class. Six types of assets can be capitalized: tenant-occupied housing from the rental income received by individual landowners; unincorporated business assets from the mixed income received by self-employed individuals; pension assets from the pension contributions and pension income of formal wage earners and pensioners; life insurance assets from factor income; bonds and interest deposits from interest income; and corporate shares and equity from dividends. 10

The capitalization method cannot be applied to liabilities nor to owner-occupied housing and currency, as these components of wealth do not generate any income flow. We therefore measure these components directly from available household surveys and rescale them proportionally to match SARB totals. To mitigate measurement issues and the risk of creating outliers with excessively negative net worth, 11 however, we do not directly rescale debts: we assume instead that mortgage debt is distributed proportionally to the value of the house of mortgagors, and that other forms of debts are distributed proportionally to the consumption of those declaring having contracted debts. These are conservative assumptions, as mortgages and other forms of debt are likely to be more unequally distributed than house values and consumption respectively. We refer to this combination of rescaling and income capitalization as a “mixed approach” (see table 1 ).

Estimating the Distribution of Personal Wealth in South Africa: A Mixed Approach

Source : Authors’ elaboration.

Note : The table shows the methodological approach used to estimate the distribution of the different assets and liabilities reported in the household balance sheets. Direct measurement corresponds to reported data on the market value of assets or liabilities in household surveys. Capitalization corresponds to assuming that the distribution of an asset follows that of one or several corresponding income flows.

Finally, to extrapolate our series backwards to 1993, we first apply our methodology to the years 2010–2017, with and without PIT data. We then compare the wealth distribution resulting from these alternative specifications to extract average correction coefficients at the quantile level, and use these coefficients to adjust the wealth distributions estimated from survey data over the 1993–2010 period (see supplementary online appendix S2.4 ).

This section presents our main results on wealth inequality in South Africa. We first provide an overview of aggregate household wealth and how it is distributed across broad wealth groups. We then present figures on the concentration of specific assets and on the dynamics of wealth accumulation over the life cycle. Finally, we discuss how wealth inequality in South Africa has evolved since 1993, and how it compares to other countries.

The Level and Composition of Aggregate Wealth in South Africa, 1993–2018

Before presenting figures on the distribution of wealth, it is useful to provide basic facts on the level and composition of household net worth in South Africa and its evolution since 1993 (see fig.  1 ). Before the early 2000s, real average wealth per adult stagnated at around 240,000 rand. It then rapidly increased by about 30 percent, before stabilizing at some 320,000 rand after the 2008 financial crisis. The net wealth to national income ratio has remained relatively stable since 1993, ranging from 2.5 (before 2003) to 2.8 (after 2008).

Evolution of Household Wealth in South Africa, 1993–2018

Source : Authors’ compilation based on data from the South African Reserve Bank. Note : This figure shows the level and composition of household wealth in South Africa between 1993 and 2018, expressed as a share of the net national income.

In 2018, financial and nonfinancial assets respectively amounted to two years and one year of national income. Pension assets represented the biggest component of financial assets (73 percent of national income), closely followed by equities and fund shares (51 percent), bonds and interest deposits (45 percent), and life insurance assets (35 percent). Meanwhile, the bulk of nonfinancial assets consisted of owner-occupied housing (75 percent of national income), followed by tenant-occupied housing (24 percent), and business assets (12 percent). The total liabilities of the household sector amounted to about 54 percent of national income, divided into mortgage debt (25 percent) and nonmortgage debt (28 percent). Household debt rose significantly between 2000 and 2008, in large part due to a boom in mortgage advances (see supplementary online appendix fig. S4.5 ).

Finally, based on the estimation made by Alstadsæter, Johannesen, and Zucman (2018) , we assume that 11.8 percent of South African GDP was held offshore in 2007, and, in the absence of data on the evolution of wealth held in offshore tax havens, that this share has remained constant throughout the period. This is a conservative assumption, given that global offshore wealth is known to have steadily risen in the past decades. Given the relative stability of wealth–income ratios, this implies that offshore wealth represented about 5 percent of net wealth throughout the period of interest (see supplementary online appendix S1 ).

The Distribution of Wealth in South Africa in 2017

Table 2 provides information on the number of adults (above 20 years old), the entry thresholds, the average wealth, and the share of wealth of various groups of the wealth distribution in 2017.

Distribution of Personal Wealth in South Africa in 2017

Source : Authors’ computations combining surveys, tax microdata, and macroeconomic balance sheet statistics.

Note : The table shows the distribution of household wealth in South Africa in 2017. The unit of observation is the individual adult aged 20 or above. Wealth thresholds are in 2018 rands. R: rands; PPP: purchasing power parity.

Average wealth varies hugely across the distribution. The bottom 50 percent of the South African population have negative net worth: the levels of the debts that they owe exceed the market value of the assets they own. The middle 40 percent of the distribution—individuals located between the median and the 90th percentile—have a net worth more than twice lower than the national average. Together, the bottom 90 percent of the South African adult population own about 14 percent of total personal wealth in the economy, while the remaining 86 percent belong to the top decile. The average wealth of the bottom 90 percent of the population is about six times lower than the national average, compared to nine times higher among the top 10 percent.

Ownership is not only polarized between top and bottom wealth groups, it is also extremely concentrated within the top 10 percent. The top 1 percent of the South African adult population (350,000 individuals) own 55 percent of aggregate personal wealth, and the top 0.1 percent alone (35,000 individuals) own almost a third of wealth. The top 0.01 percent of the distribution, amounting to some 3,500 individuals, own about 15 percent of household wealth, greater than the share of wealth owned by the bottom 90 percent as a whole (32 million individuals). Their average wealth is more than 1,500 times greater than the national average, and 9,000 times greater than the average of the bottom 90 percent.

The Composition of Personal Wealth across the Distribution

The extreme degree of wealth inequality observed in South Africa is in large part driven by the relative exclusion of poorer wealth groups from any form of wealth accumulation, and by the concentration of all forms of assets at the top end. Table 3 provides some insights into this polarization by showing the share of different types of assets held by wealth groups across the distribution. The top 10 percent own more than 55 percent of all forms of assets, including pension assets, housing wealth, unincorporated business assets, and currency, notes, and coins. They own virtually all (99.8 percent) bonds and stock in the economy. The top 1 percent alone holds more than a tenth of all forms of assets and a bit more than 95 percent of all bonds and stocks. Currency and housing wealth are the least concentrated forms of wealth, yet low wealth groups only possess a small share of them: the bottom 50 percent of the wealth distribution own about 10 percent of currency, notes, and coins, and less than 15 percent of housing assets.

Share of Total Assets Held by Wealth Group by Asset Class (Percent), 2017

Note : The table shows the shares of different types of assets held by specific wealth groups in 2017. The unit of observation is the individual adult aged 20 or above. In 2017, the top 1 percent of South Africans in terms of net worth owned 95 percent of the bonds and corporate shares in the economy. Bonds and shares represented 34.1 percent of total household assets in the economy at this date. Figures may not add up due to rounding.

Figure 2 provides another view of the link between asset types and wealth groups by representing the portfolio composition of percentiles of the wealth distribution in 2017. Currency, notes, and coins are the main form of assets held by poorest South African adults, while owner-occupied housing, pensions, and life insurance form the majority of assets for most of the distribution within the bottom 90 percent. Unincorporated business assets represent a small share of portfolios for the upper-middle class. Bonds and stocks, finally, represent a large share of wealth for the top 1 percent and the bulk of assets held within the top 0.1 percent.

Composition of Assets by Wealth Group in 2017

Source : Authors’ computations combining surveys, tax microdata, and macroeconomic balance sheet statistics. Note : The figure shows the composition of assets of various groups in the distribution of household assets in South Africa in 2017. The unit of observation is the adult aged 20 or above. The results come from the harmonized survey data file, and wealth is split equally among adult members of the household, except for the top 1 percent and above for which the individual data built from the combined survey and tax microdata are used.

Wealth and Age

Based on available information on age from the PIT data, we can document to what extent wealth accumulation through the life cycle contributes to reducing or exacerbating inequalities. 12 Figure 3 shows a stable relationship between age and average wealth over the 2012–2017 period. Average net worth rises significantly and linearly between ages 20 and 55: individuals aged between 20 and 25 have an average net worth lower than 25 percent of the national average, while those aged between 50 and 55 are between 50 percent and two times wealthier than the average adult. Average wealth then stabilizes between ages 50 and 65 and decreases slightly for older individuals, but still remains more than 50 percent higher than the national average for individuals older than 75. Interestingly, this pattern is almost perfectly similar to that found in the case of France (see Garbinti, Goupille-Lebret, and Piketty 2017 , fig. 5).

Average Wealth by Age Relative to Average Wealth per Adult, 2012–2017

Source : Authors’ computations combining surveys, tax microdata, and macroeconomic balance sheet statistics. Note : The figure shows the mean net worth of South African adults by age group relative to the national average. The unit of observation is the individual adult aged 20 or above.

Although average wealth does vary significantly across age groups, age differences cannot account for observed wealth disparities. Indeed, levels of wealth concentration within each age group are almost perfectly similar to those measured among the full population. The share of wealth held by the top 10 percent exceeds 85 percent, and the top 1 percent share is higher than 55 percent, whether one restricts the analysis to those aged between 20 and 39, between 40 and 59, or older than 60 (fig.  4 ). Altogether, this implies that individuals across the wealth distribution do accumulate at relatively similar paces but start from very different initial endowments. This suggests that inherited wealth could play a central role in explaining levels of wealth concentration observed in South Africa. 13

Wealth Inequality within Age Groups, 2010–2017

Source : Authors’ computations combining surveys, tax microdata, and macroeconomic balance sheet statistics. Note : The figure shows the top 10 percent wealth share and the top 1 percent wealth share estimated when splitting the South African population into three age groups (20–39 years old, 40–59 years old, and 60+ years old). The unit of observation is the individual adult aged 20 or above.

Long-Run Trends and Comparative Perspectives

We conclude this section by highlighting the most notable facts arising from the comparison of our results over time and across countries. Figure 5 plots the evolution of the share of wealth accruing to the top 10 percent in South Africa (our estimates), together with that from all other countries where a similar method could be applied: China, Russia, India, the United Kingdom, France, and the United States. In the long run, and despite a 30 percent growth in real average wealth per adult, wealth concentration has remained remarkably stable in South Africa, increasing between 2005 and 2010 before gradually stabilizing back to its pre-2000 level. Notwithstanding these short-term fluctuations and the fact that wealth concentration has increased in all other countries, South Africa has remained significantly more unequal than all these countries throughout the entire period. The South African top 10 percent wealth share has fluctuated between 80 percent and 90 percent during the 1993–2017 period, while it has remained below 75 percent in the United States, 70 percent in Russia and China, 65 percent in India, and 55 percent in France and the United Kingdom. The same result holds for the top end of the distribution: the top 1 percent wealth share was 55 percent in South Africa in 2017, compared to 43 percent in Russia, 39 percent in the United States, 31 percent in India, 30 percent in China, and less than 25 percent in France and the UK (fig.  6 ).

South African Wealth Inequality in Comparative Perspective: Top 10 Percent Wealth Share

Source : Authors’ computations combining surveys, tax microdata, and macroeconomic balance sheet statistics for South Africa; World Inequality Database ( http://wid.world ) for other countries. Note : The figure compares the top 10 percent wealth share in South Africa to that of other countries. The unit of observation is the individual adult aged 20 or above. Wealth is individualized (South Africa) or split equally among adult household members (other countries).

South African Wealth Inequality in Comparative Perspective: Top 1 Percent Wealth Share

Source : Authors’ computations combining surveys, tax microdata, and macroeconomic balance sheet statistics for South Africa; World Inequality Database ( http://wid.world ) for other countries. Note : The figure compares the top 1 percent wealth share in South Africa to that of other countries. The unit of observation is the individual adult aged 20 or above. Wealth is individualized (South Africa) or split equally among adult household members (other countries).

Having a closer look at our series, we can bring out two additional observations. First, the rapid increase in wealth concentration between 2005 and 2008 was in large part due to a strong fall in the bottom 90 percent share driven by the boom and bust in mortgage advances in the 2000s, which temporarily drove a higher share of households into negative net worth. Between 2004 and 2008, in particular, mortgage debt increased from 9 percent of net household wealth to almost 15 percent, before decreasing back to 9 percent in 2018 (see supplementary online appendix fig. S4.5 ). This temporary fall in bottom wealth shares driven by expanding debts mirrors that observed in the United States at about the same period (see supplementary online appendix fig. S4.4 ).

Secondly, it is worth noticing that while the top 10 percent share has remained broadly stable, there seems to have been an increase in wealth concentration within the top 10 percent. Between 1993 and 2017, the top 1 percent share grew from 54 percent to 57 percent and the top 0.1 percent share from 22 percent to 31 percent (see supplementary online appendix fig. S4.3 ). This is likely due to the combination of two factors: the rise in the share of nonpension financial assets, from 19 percent to 24 percent of net household wealth between 1992 and 2018, and the increase in wage inequality in South Africa during this period, which indirectly affected the distribution of pension assets.

Overall, it is particularly striking that wealth inequality has remained at extreme and stable levels in South Africa in spite of the many progressive policies that have been pursued since the early 1990s. All discriminatory laws were abolished by 1991 and a new constitution was adopted in 1994. Since then, South Africa’s successive governments endorsed several ambitious socioeconomic policy frameworks whose primary objectives consistently included reducing economic inequality inherited from colonial and apartheid regimes. 14 Yet, wealth inequality has remained remarkably stable over the past three decades. In line with our observations on the role of inheritance in explaining constant wealth disparities within age groups, our long-term series suggest that asset allocations before 1993 may still contribute to shape wealth inequality in recent years, despite the many reforms to address these lasting disparities.

In this section, we contrast our results with those obtained using alternative methodologies. We then discuss how sensitive our estimates are to different assumptions regarding the distribution of debts, the measurement of housing wealth, and equivalence scales.

Comparing Methodologies: Direct Measurement, Rescaling, and Survey-Based Mixed Approaches

In our baseline “mixed approach” to estimate wealth inequality in South Africa, we have combined surveys and exhaustive tax microdata to capitalize income flows and match wealth aggregates to macroeconomic balance sheets. To shed light on the contributions of these various data sources and methodological steps, it is useful to compare our benchmark series with three alternative specifications: one in which we estimate wealth inequality from self-reported assets and liabilities in household surveys (“direct measurement”), one in which we rescale these reported assets and liabilities to macro totals (“rescaling”), and one in which we apply our mixed approach directly to surveys, without combining them with tax data.

Direct Measurement .  In South Africa, the only publicly available data source allowing direct measurement for the entire spectrum of household wealth components is the NIDS survey. The direct measurement approach implies that figures are not consistent with macroeconomic statistics, both in terms of levels and composition of household wealth. In the case of the NIDS, this implies overstating the total value of housing assets and understating the significance of nonpension financial assets (see supplementary online appendix S2.2 ).

Rescaling .  A second way of measuring the distribution of wealth consists in assuming that the distribution of recorded wealth components and their correlation is relatively well measured by the household survey, but that it is mainly their average amounts that are understated or overstated. In this case, one can obtain an estimate of the wealth distribution by effectively scaling up individual-level assets and liabilities in the NIDS surveys to match the totals recorded in the national balance sheets. This has the advantage of ensuring consistency with macroeconomic aggregates, as in our mixed approach. The drawback is that self-reported wealth components may be more prone to measurement error than self-reported income flows, potentially creating a number of outliers and yielding implausible levels of wealth inequality.

Survey-Based Mixed Approach .  A third way of measuring wealth inequality, in the absence of tax microdata, is to directly apply our mixed methodology to household surveys, capitalizing relevant income flows and rescaling assets that do not generate income flows to macro totals. To the extent that household surveys tend to underestimate top income inequality (albeit much less than top wealth inequality), we may expect estimated wealth inequality to be lower when relying solely on surveys than when combining surveys with tax data.

Results .  Table 4 compares estimates of the share of wealth held by the bottom 50 percent, the middle 40 percent, the top 10 percent, the top 1 percent, and the top 0.1 percent derived from these different methodologies. Waves 4 and 5 of the NIDS are the only surveys collecting direct data on wealth and thus for which estimates from the three methodologies can be compared. Three main results stand out from these figures.

Shares of Household Wealth Held by Groups in South Africa (Percent): Survey-Based Results

Source : Authors’ computations from survey microdata.

Note : The table compares estimates of the share of household wealth owned by the bottom 50 percent (p0p50), the middle 40 percent (p50p90), the top 10 percent (p90p100), the top 1 percent (p99p100), and the top 0.1 percent (p99.9p100) obtained from household surveys using different methodological approaches. The unit of observation is the individual adult aged 20 or above. PSLSD: Project for Statistics on Living Standards and Development. IES: Income and Expenditure Survey. LCS: Living Conditions Survey. NIDS: National Income Dynamics Study.

First, all approaches converge in revealing an extreme degree of wealth concentration. Regardless of the methodology, the share of wealth held by the bottom 50 percent is estimated to be consistently negative, while the top 10 percent is higher than 80 percent. The fact that wealth inequality in South Africa is substantially larger than in any other country for which a similar measurement method has been applied is therefore robust to alternative methodologies.

Secondly, while methodologies converge when it comes to large groups (e.g., the top 10 percent and the bottom 90 percent), they yield much more variable results when it comes to measuring wealth concentration at the top of the distribution. Direct measurement in the NIDS surveys implies a top 0.1 percent share below 10 percent, i.e., more than twice lower than most of the results obtained from rescaling or the mixed approach. This is due to the extremely poor coverage of nonpension financial assets in the NIDS: the total reported value of bonds and stock, two types of assets that are overwhelmingly concentrated at the top end of the wealth distribution, does not exceed 4 percent of macro totals in both waves of the survey (see supplementary online appendix table S4.2 ). Rescaling financial assets to balance sheet totals or capitalizing income flows corrects for this micro–macro discrepancy, moving the estimates closer to those obtained with our benchmark methodology. 15

Thirdly, the survey-based mixed approach yields relatively close results across years and data sources: the top 10 percent share lies between 85 percent and 90 percent, and the top 1 percent is estimated to be between 50 percent and 60 percent in most cases. Most importantly, these estimates are very close to those obtained when combining surveys with PIT data: despite their tendency to underestimate top income inequality, surveys can still be usefully exploited to estimate wealth concentration using the mixed approach. A careful look at the particular structure of capital income concentration can help solve this apparent paradox. The relative consistency between the two sources is mainly due to the fact that both in the surveys and the tax data, financial incomes (interest, dividends, and rental income) are extremely concentrated, so that both sources imply attributing a substantial share of wealth—and in particular of tenant-occupied housing, bonds, and shares—to the top 0.1 percent of the distribution.

In summary, our results point to the key significance of bridging the micro–macro gap. Because surveys tend to omit the bulk of financial assets, studies solely relying on self-reported household wealth are likely to very strongly underestimate top wealth inequality. By contrast, capitalizing income flows to match macro totals can prove to be a more reliable methodology, even in the absence of income tax microdata. This opens new avenues for estimating wealth inequality in other emerging countries, where tax microdata might not be available yet where surveys collecting data on income can be usefully combined with data from national accounts.

Debts, Housing Wealth, and Equivalent Scales

We conclude this paper by briefly discussing three sources of concern related to the mismeasurement of household debt, the underestimation of total housing wealth, and the distribution of wealth within households.

Mismeasurement of Household Debt .  One concern with our estimates is that debt is self-reported in household surveys. By rescaling reported debts to macro totals, we might overestimate the number of households with negative net worth, especially given that surveys tend to only capture a small fraction of private debt (see supplementary online appendix table S4.3 ). In order to evaluate the potential significance of this bias, we compare the evolution of household net worth inequality with that of household assets inequality (excluding debts) in supplementary online appendix fig. S4.14 .

Two key results emerge from this comparison. First, excluding debt systematically reduces wealth inequality, but only moderately: the top 10 percent have owned a consistent 80 percent of assets and the top 1 percent about 45 percent of assets since 1993. Secondly, debt dynamics appear to drive virtually all fluctuations in wealth inequality over time: wealth concentration has followed ups and downs, while the concentration of assets has remained remarkably stable. This points to the role of credit dynamics in accounting for short-run trends in wealth disparities. The rise and fall of wealth inequality visible in our series before and after the 2007–2008 financial crisis, in particular, coincides with the mortgage credit boom and bust (see supplementary online appendix fig. S4.5 ).

Underestimation of Housing Wealth .  A second concern relates to the aggregate value of housing wealth in South Africa. Indeed, housing appears to be the only asset class for which reported values in surveys are substantially higher than in balance sheet totals (see supplementary online appendix table S4.2 ). Whether this inconsistency arises from survey respondents overestimating the value of their home or from the SARB underestimating housing wealth remains an open question. 16 For consistency and comparability with existing studies, we choose to rely on SARB statistics. However, we report in the supplementary online appendix , series in which we assume that total housing wealth is underestimated by a factor of 2 (see figs S4.12 and S4.13). Unsurprisingly, as housing is one of the least unequally distributed assets in South Africa, increasing its average value reduces wealth inequality. Yet, because all assets are strongly concentrated at the top end, including housing (see table 3 ), it affects our main results only moderately, with the top 10 percent share still reaching about 80 percent and the top 1 percent about 40 percent.

Equivalence Scales .  Lastly, one might be concerned that the equivalence scale used in this paper—allocating wealth components directly to individuals, and therefore not accounting for wealth sharing within households—may lead to overestimating wealth inequality. It might also lead to overstating wealth inequality more in South Africa than in countries such as France, given that multigenerational households and intrafamilial sharing agreements might be more common in the former than in the latter.

We investigate this concern in supplementary online appendix figs S4.10 and S4.11 , which compare our “individual” series to that obtained when splitting wealth equally among all household members (“per capita” series), or among all adult household members (“broad equal-split” series). We find that changes in equivalence scales only moderately affect wealth inequality, which is highest in the individual series and lowest in the broad equal-split series. The top 10 percent share exceeds 80 percent, and the top 1 percent share 45 percent, in all three specifications.

This paper systematically estimated the distribution of household wealth in South Africa since 1993 by combining all relevant macro and microdata sources. Our results have revealed unparalleled levels of wealth concentration, with the top 1 percent owning a higher share of wealth than the bottom 99 percent. These extreme inequalities have remained remarkably stable since the end of the apartheid regime, despite the significant economic growth and the major social transformations that the country has undergone since then. They extend to all forms of assets, from housing to financial capital, which are consistently held by individuals located at the top end.

Methodologically, our results point to the substantial limitations of wealth surveys, which vastly underestimate financial assets and are therefore incapable of properly measuring wealth inequality within the top 10 percent. Instead, we have shown that bridging the micro–macro gap by capitalizing relevant income flows, even in the absence of tax microdata, can yield more consistent and meaningful estimates of the wealth distribution. This comes as good news for researchers aiming at tracking the dynamics of wealth concentration in countries where tax microdata might not be accessible, yet where household income surveys and macroeconomic balance sheets exist and can be combined.

We see at least two avenues for future research. First, our estimates of wealth inequality could be refined if better information on dividends and income received through unit trusts were made available to researchers (see the discussion in supplementary online appendix S3 ). Information on these forms of income are collected on a regular basis by the South African Revenue Service, but are not yet accessible. We hope that access to these data sources will enable future studies to have a more granular picture of the composition of wealth and its dynamics at the very top of the distribution.

Secondly, our findings on the stability of wealth inequality since 1993 call for further research on the dynamics and weight of inherited wealth relative to that of newly created and accumulated wealth in the post-apartheid era. This would likely require combining other complementary data sources—such as estate duty data, credit data, or panel data on income and savings—and modeling the joint dynamics of savings, inter-generational transmission, and household debt.

The derived data generated in this research are available in the article and in its online supplementary material. The household surveys used in this article are available from DataFirst, at https://www.datafirst.uct.ac.za/ . The macroeconomic data are available from the South African Reserve Bank website, at https://www.resbank.co.za/ . The tax microdata were accessed from the South African Revenue Service data lab and are not publicly available.

See Chatterjee (2019) for a broader review. Orthofer (2016) is sometimes cited as an additional study, exploiting tax microdata. However, given the method applied, the resulting estimates correspond to the distribution of financial incomes, not to the distribution of household wealth.

This classification is the most precise common decomposition that could be achieved after harmonization of all the data sources. Notice that land directly owned by the household sector is classified in housing (owner or tenant occupied), not in business assets. Liabilities include all debts contracted with both formal (e.g., commercial banks) and informal creditors.

The few countries still collecting direct information on wealth include Switzerland, Spain, France, Norway, and Colombia. These countries are the only ones still enforcing a tax on net wealth. For other countries in the world, most of what we know about wealth comes either from wealth surveys, estate duty data, or, as in this study, via the income capitalization method applied on income surveys or personal income tax data.

Other surveys collecting information on income and consumption sometimes include some information on some wealth components (mostly house value or debt), but never encompass total wealth.

The IRP5 and ITR12 data are presented in the form of source codes corresponding to specific taxable income concepts, exemptions, and deductions. See the supplementary online appendix for more details about our classification and Ebrahim and Axelson (2019) for an overview and discussion of the dataset.

The Project for Statistics on Living Standards and Development (PSLSD—1993), the Income and Expenditure Surveys (IES—1995, 2000, 2005, 2010), and the Living Conditions Surveys (LCS—2008, 2015).

The Labour Force Surveys (LFS—twice a year from 2000 to 2007) and the 40 Quarterly Labour Force Surveys (QLFS—every three months since 2008).

Defined as the sum of wages, mixed income, rental income, interest income, and pension income.

See supplementary online appendix figs S4.8 and S4.9 . Our choice of a merging point based on an income concept differs slightly from the approach of Hundenborn, Woolard, and Jellema (2019) , who rather derive a taxable-income concept from survey data, and then keep the tax data above the filing threshold of taxable income. The main reason for merging our two datasets based on a broad income concept is twofold. First, our IRP5–ITR12 panel covers a large number of individuals who are below the filing threshold, given that all employers in South Africa are now required to file an IRP5 tax form for all their employees, regardless of their level of remuneration. However, as is emphasized in the SARS’ Tax Statistics, this rule was not followed strictly by all employers, so that the tax data cannot be considered to be representative of the universe of formal wage earners. In other words, our data covers relatively well the top of the distribution up to a certain point, below which it contains a mix of low- and middle-income wage earners. It seems therefore most useful to keep as many individuals as possible from the tax data, while removing those whose location in the distribution of income cannot be identified precisely, which is what our method does in a simple way. Secondly, defining taxable income remains a complex task, and it remains unclear whether this can be done with a sufficient level of precision and consistency, in particular given that surveys tend not to properly capture the top of the distribution.

In the case of pension assets, we follow the approach proposed by Saez and Zucman (2016) and allocate them to wage earners and pensioners so as to match their distribution recorded in the NIDS. In our case, this implies distributing 75 percent of pension assets to formal wage earners proportionally to pension contributions paid, and 25 percent to pensioners proportionally to pension income received. As shown in the supplementary online appendix (fig. S4.6) , this capitalization technique applied to the NIDS data yields results which are very similar to those obtained from direct measurement. Similarly, we assume that 50 percent of life insurance assets belong to wage earners proportionally to factor income—the sum of wages, mixed income, and pension income—and that 50 percent belong to all other adults proportionally to factor income. This again reproduces well the distribution of life insurance assets reported in the NIDS (see supplementary online appendix fig. S4.7 ).

Mortgage debt and other forms of debts have been recorded in surveys but the coverage is often partial and inconsistent. As a result, rescaling debts to balance sheet totals results in seriously overestimating the number of individuals with negative net worth and generating implausibly high debt values.

There are many other important categories to investigate in the context of wealth inequality in South Africa. Unfortunately, the only relevant covariate present in PIT data is age. We leave the study of other dimensions of wealth inequality (race, gender, geography, etc.) for future research.

Notice that the estimates presented here correspond to individual series, rather than to “equal-split” series where wealth would be split equally among household adult members. In practice, splitting wealth among household members would imply redistributing wealth to younger individuals, thereby making the wealth–age profile less steep. This would reinforce our argument that age is not a primary determinant of wealth inequality in South Africa.

These include the Reconstruction and Development Programme (RDP—1994); Growth, Employment and Redistribution (GEAR—1996); Accelerated and Shared Growth Initiative for South Africa (ASGISA—2005); New Growth Path (NGP—2010); and National Development Plan (NDP—2013).

Also notice that wealth inequality between the top 10 percent and the bottom 90 percent is significantly larger under the rescaling approach than when relying on the mixed approach. This is essentially due to the fact that scaling up debts to balance sheet totals creates a large number of households with strongly negative net worth (the bottom 50 percent goes down by several percentage points), especially in the NIDS where assets and liabilities suffer from important underreporting issues.

Notice that this issue is not specific to South Africa—in the United States too, survey values have been found to be higher than in balance sheets. Which source of information provides the most accurate estimate of the market value of housing wealth remains debated ( Blanchet 2016 ; Henriques and Hsu 2014 ; Dettling et al. 2015 ).

Aroop Chatterjee leads the research agenda on wealth inequality at the Southern Centre for Inequality Studies, University of Witwatersrand, Johannesburg; his email address is [email protected] . Léo Czajka is a PhD candidate at Université catholique de Louvain and a research fellow at the World Inequality Lab, Paris School of Economics; his email address is [email protected] . Amory Gethin (corresponding author) is a PhD candidate at the Paris School of Economics and a research fellow at the World Inequality Lab; his email address is [email protected] . The authors thank the SA-TIED Datalab team, as well as Facundo Alvaredo, Thomas Blanchet, Keith Breckenridge, Josh Budlender, Aalia Cassim, Lucas Chancel, Allan Davids, Andrew Kerr, Murray Leibbrandt, Thomas Piketty, Michael Sachs, Imraan Valodia, and Eddie Webster for helpful insights. The authors also thank seminar participants from the Southern Centre for Inequality Studies, WiSER, School of Economics and Finance at the University of Witwatersrand, and SALDRU at the University of Cape Town. The authors acknowledge financial support from the UNU-WIDER SA-TIED project, the Ford Foundation, the Sloan Foundation, the United Nations Development Programme, and the European Research Council (ERC Grant 340831). The study was originally commissioned under the UNU-WIDER project, Southern Africa – Towards Inclusive Economic Development (SA-TIED). The authors are responsible for all opinions and errors. A supplementary online appendix is available with this article at The World Bank Economic Review website.

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Inequality in South Africa

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South Africa has a huge gap between the rich and poor - 4 urgent reasons to tackle inequality

Pro Vice-Chancellor: Climate, Sustainability and Inequality and Director: Southern Centre for Inequality Studies., University of the Witwatersrand

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Imraan Valodia receives funding from a number of South African and international foundations that support academic and policy research.

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South Africa has exceptionally high levels of inequality . As someone who studies issues of inequality and sustainability, I have argued before that South Africa’s income inequality is the highest of all countries that have data on this. This means that the gap between the rich and the poor is wider than in any other country.

While South Africa is somewhat exceptional, income inequality within countries has been growing across the world.

The most recent data suggests that income inequality between countries has been falling , but this is largely due to the rising incomes of people in China, who make up a large part of the global population.

If we consider inequality in wealth, which gives us a fuller picture than income, the situation in South Africa is even more extreme. The top 0.1% of the population owns 25% of the wealth . Globally, according to the World Inequality Report, the top 10% of the global population owns 76% of the global wealth .

Read more: South Africa can't crack the inequality curse. Why, and what can be done

There are a number of good reasons why the South African government should focus on reducing inequality. I wish to highlight four reasons.

Not good for the economy

First, high levels of inequality are not good for the economy. This is a complex issue, because the causal relationships between economic growth and inequality are multifaceted . But these obscene levels of concentration in wealth leave too much economic power in the hands of a small group of wealthy individuals.

Not good for democracy

Second, high levels of inequality are not good for democracy. Across much of the world, especially in the developed countries, ultra-rightwing politicians such as Donald Trump have been drawing support from the electorate. Among the reasons for this is that working class people feel left behind as wealth and income gaps widen. But in fact, the effect of the economic policies that these right-wing politicians promote is to increase inequality. These political shifts undermine democratic systems, leading to a rise in ultra-nationalism and discrimination against migrants and other minority groups.

We are, unfortunately, seeing the rise of these political views in South Africa too. The rise of this type of politics also undermines multilateral efforts to address global challenges, such as climate change. For example, politicians such as Trump have promoted climate denialism and removed the United States from the Paris Agreement on climate change .

Read more: Inequality: troubling trends and why economic growth in Africa is key to reducing global disparities

Not good for social cohesion

Third, high levels of inequality are not good socially. Not only is inequality bad for social cohesion, it entrenches inter-generational inequalities.

Economist Branko Milanovic , one of the world’s academic authorities on inequality, has shown in his 2016 book that an American child, purely by the chance event of being born in America, is likely to earn 93 times the income of a child who, also by chance, is born in a poor country .

This is especially a problem in South Africa, where a child born in a low-income household is unlikely to go to a good school, and therefore less likely to attend university, and therefore less likely to find employment, and so on. This increases barriers to social mobility and gives rise to a divided society, with higher levels of tension, uncertainty and conflict.

Read more: How to ensure global debates about inequality are informed by views from developing countries

Undermines climate change efforts

Finally, with climate change, humans are now facing a challenge that threatens their very existence. The wealthy countries, and the elite in developing countries, are largely the cause of the problem , but the costs of climate change are likely to be borne disproportionately by low-income countries and communities. This inequality, which is of course linked to the historical trends of wealth accumulation, is likely to undermine efforts to deal with climate change, by creating resistance to change.

More equality, both within countries and across the world, is imperative if we are successfully to address the existential challenges of climate change.

Prof Sanjay G. Reddy will deliver the Southern Centre for Inequality Studies’ 2024 Inequality Lecture , The Political Economy of Global Inequality: A Drama in Three Parts, on 15 August. In partnership with the Southern Centre for Inequality Studies , The Conversation Africa has published several articles on inequality.

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Policy Interventions, Skilled Jobs Can Reduce Inequality in South Africa

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STORY HIGHLIGHTS

• South Africa needs skilled jobs for the poor to reduce inequality- among the highest in the world - according to a new World Bank report
• The report simulates combined policy interventions that could reduce inequality through improved education and spatial integration, and others that would ignite growth through increased competition, policy certainty and skilled migration
• According to the report, combining these reforms would reduce the number of the poor by more than half by 2030, to 4.1 million from 10.5 million today

PRETORIA, April 10, 2018 –  The number of South Africa’s poor could be reduced by more than half by 2030 through various combined policy interventions that reduce inequality by creating skilled jobs for the poor and ignite growth by increasing competition, policy certainty and promote skilled migration, according to a recently released World Bank report.

Projecting the South African economy through 2030, the 11 th edition of the South Africa Economic Update: Focus on Jobs and Inequality , assesses the potential impact of a combination of various policy interventions on jobs, poverty, and inequality. This report presents a scenario in which the number of the poor could be reduced by more half, dropping to 4.1 million by 2030 from 10.5 million in 2017. In addition, the Gini index of inequality would reduce to 56 in 2030 from 63 in 2017 and 800 thousand jobs could be created with the economy increasing at an annual rate of 2.2% as a result of these interventions.

“We see from this report that reducing South Africa’s high inequality will require improving education and spatial integration to provide the poor with skills that are required to meaningfully participate in a capital and skills intensive economy such as South Africa,” said Paul Noumba Um, World Bank Country Director. “This would need to be complemented by policy intervention that spur additional growth and provide the fiscal space to finance these reforms.”

The economic update reviews the evolution and nature of South Africa’s inequality – among the highest in the world– arguing that it has increasingly been driven by labor market developments that demand skills the country’s poor currently lack. It draws from the forthcoming World Bank’s Systematic Country Diagnostic, and the recently-released Poverty and Inequality Assessment .

Without the policy interventions modelled in the economic update, South Africa would on current trajectory not be able to attain its development targets outlined in the country’s National Development Plan of creating sufficient jobs, eradicating poverty and reduce inequality. In the baseline scenario of an average gross domestic production (GDP) growth of 1.4% annually, the number of poor would drop to 8.3 million in 2030 from 10.5 million in 2017. In addition, a modest 215,000 jobs would be created every year, mostly skilled and semi-skilled and the poverty rate would reduce to 12.7% in 2030 from 18.6% in 2017. The Gini coefficient would drop to 59.5 in 2030 from 62.8 in 2017 and the unemployment rate would move slightly from 27.2 in 2017 to reach 26.7% in 2030.

“Despite the slow growth environment that South Africa is currently facing, ongoing improvements in education among poor is slowly paying off as they gain skills and get an increasing share of skilled labor income,” said Sebastien Dessus, World Bank project leader. “As a consequence, we project income inequalities to be lower in 2030 than in 1996.”

The report argues that the gains in improving education would be boosted by increasing teachers’ capacity, accountability and financial support for poor university students. This would raise the number of poor students getting a tertiary degree to 4.6% in 2030, against 2.2% in the baseline scenario.

Furthermore, with respect to reinforcing spatial integration, investing an additional 1% of GDP every year into collective transportation systems and social housing would reduce their price, and accelerate GDP growth through higher labor supply. This would lift an additional 0.5 million people out of poverty. The Gini index of inequality would lower further by 0.7 point with vulnerable households and transient poor being the main beneficiaries.

The report also argues that the impact of these interventions would be diminished in a slow growth environment and put a strain to public finance. Domestic factors such as policy uncertainty, low business and consumer confidence, and supply constraints are noted as having held back growth in South Africa since 2015.

The report suggests that reducing policy uncertainty could increase investment in mining by 25% and further increase GDP level by 3% in 2030. It suggests as well that increased competition could lift up GDP levels by 5% in 2030 and alone create 400 thousand jobs. Lastly, the report reveals that accelerated skilled migration would help relax the skills constraint in the short term and help create more semi-skilled and unskilled jobs. It suggests that each additional skilled migrant conservatively could create 0.5 semi-skilled or unskilled job and that 150 thousand additional skilled migrants would further increase GDP level by 2% in 2030.

• FULL REPORT: South Africa Economic Update: Focus on Jobs and Inequality
• PRESS RELEASE: South Africa: Better Education & Spatial Integration Crucial for Reduced Inequality, Job Creation
• BLOG: The South African economy is growing faster—but how fast?
• BLOG: Breaking the vicious cycle of high inequality and slow job creation
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Policy Brief Reducing inequalities in South Africa

Progress on equality thwarted by slow growth and success of top earners.

South Africa has the highest rate of measured inequality in the world. Often thought to be a legacy of the apartheid system, inequality in South Africa has stubbornly persisted. 

South Africa’s position as highest inequality country in the world has not changed

Progressive taxation and social transfers help to offset existing inequalities, but they cannot solve inequality alone 

Policies that target earnings inequalities and expand employment opportunities are a crucial part of any solution to inequality

The main earnings inequality in the South African labour market is between top incomes and everyone else

Other important inequalities are those between men and women, whites and blacks, and college-educated versus non-college educated. 

Inequalities in wealth, assets and income from capital underpin the persistence of these income inequalitie

South Africa’s Gini coefficient for household income per capita was only reduced from 0.68 to 0.66 between 1993–2014.

The key to overcoming inequality is equalizing workers’ wages and salaries

The expansion of social grants has had a strong equalizing effect in the country, but this effect has been offset by the much bigger role that earnings inequality plays. Inequality in labour income has by far the largest effect on aggregate inequality. Despite an increase in average earnings over 1993–2014, and even a major increase in the share of households earning income from labour (60.5% to 72.6%), inequality in household labour market income remained stuck at the very high Gini of 0.73. The conclusion must be that the most impactful way to redress inequality is to address inequality of earnings from labour. 

Most economic gains go to the top 5% in South Africa

Even though the aggregate rate of inequality has improved slightly, earnings inequality has deteriorated during 2003–15. Over this period, the top 5% of earners’ income increased by 5.1% per year while the average income for the other 95% mostly stagnated.

An analysis of the changes in the South African earnings distribution over the period 2001–14 found that South Africa saw the average real earnings of workers rise from R5,740 to R7,951. But because wage increases went mostly to top earners, overall inequality increased. As measured by the Gini coefficient, inequality rose from 0.55 to 0.63 an atypically large increase. 

The most important earnings divide is between workers with some form of tertiary education and other workers

The earnings divide by education has been driven by growing returns to tertiary education, while returns to work experience plateaued. The college educated are now much more likely to join South Africa’s upper class than ever before. At the same time, the earnings of the upper class are growing faster than others’. The gains for the highly educated had such a strong impact on increasing inequality in South Africa that, by themselves, they would have caused the Gini to move by eleven points.

Progress on gender and racial equality needs to continue

The increase in labour inequality was offset somewhat by major gains to equality from progressive taxation, increases in social protection, and improvements in racial and gender-based equality in the labour market.

The earnings divide between Whites and Africans 1  fell from 67% to 57% and the gap between what men and women earn also fell, by 5 percentage points. Nonetheless, these demographic divides are still so large that they continue to decrease earnings equality in South Africa, causing 3.5 percentage point (racial inequality) and 0.5 percentage point (gender inequality) net increases in earnings inequality. Continuing to improve racial and gender earnings equality is therefore crucial to improving overall levels of equality in South Africa.

The middle class needs to be bigger and more stable

The tax and transfer system in South Africa is among the most progressive of the middle-income countries, but not progressive enough to meaningfully counteract labour market inequality. The roll-out of new social grants, improvements in the progressivity of taxation policy, and new laws protecting the minimum wages of the lowest earners have all kept South African inequality from growing further, but they have not been enough to overcome the country’s rising earnings inequality. 

One of the biggest reasons that earnings inequality did not increase further has been the loss of income and employment stability to experienced workers as the economy undergoes structural changes. This phenomenon does not represent real gains to long-term equality but rather a convergence of wages in the middle of the distribution helped along by a major decrease in unionization, which narrows the gap in earnings between non-unionized and unionized workers. This phenomenon offsetts increases in the inequality measure by decreasing real wages in the middle rather than by raising wages at the bottom of the distribution. 

More research needed on wealth, generational, and intersectional inequalities

Both the labour market and the capital market have worked in ways that strongly favoured those at the top end of the earning distribution. Investment income is an unimportant part of most South African households’ overall income, measuring just 4.5% on average, but it likely has important unexplored effects for the incomes of top earners. The South African Gini for investment income was 0.98 in 2014, the most recent year calculated, meaning that investment income plays a major role in top incomes. In 2014, the bottom 77% of the distribution received no income from this source, which was still a major improvement from 2008 when only 6% of the population received investment income. 

South Africa should continue to support and expand policies that improve gender and racial inequality

Labour market policies are central here, with a need to equalize both access to employment as well as the type of work

Focus should be put on improving the long-term career trajectories of South Africa’s workers, particularly those in the bottom 95% of the distribution 

South Africa should continue to protect the system of social grants and, when possible, expand their scope

Measures should be explored to improve the efficiency of service delivery in the system of social grants in South Africa to maximize the gains from existing resources

Democratizing ownership in South Africa is an important long-term equalizer but it will require some equalization of assets and wealth in order to encourage households to save and invest

More research needs to be done on wealth inequality, age-based inequalities, intersectional inequalities, and generational inequalities to understand how the lifetime earnings and investments of different groups might impact overall levels of inequality.

Murray Leibbrandt

Timothy Shipp

WIDER Policy Brief

Volume 2/2019

© UNU-WIDER / Licensed under CC BY-NC-SA 3.0 IGO

South Africa

Sub-Saharan Africa

WHAT IS THE GINI COEFFICIENT?

It is an index that measures the extent of inequality and is often used for the analysis of income inequality prevailing in a country. It takes the value of 0 in the case of perfect equality (everybody has the same income), and 1 in the case of perfect inequality (all national income accrues to a single person). Estimates of the Gini coefficient for income nationwide range between around 0.25 (such as in some of the Nordic countries) to around 0.60 (for example, in some countries in sub-Saharan Africa).

1 | For context specificity, in South African the population groups are defined at the national level by Statistics South Africa as ‘African’, ‘White’, ‘Coloured’, and ‘Asian’. This classification is used to track post-apartheid progress on racial equality and is based on the population groups which were historically segregated under the apartheid system. The African group refers to black Africans, White to people of European descent, Coloured to people with indigenous ancestry, and Asian to people of Asian descent, the majority of whom trace their heritage to India.

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Wealth inequality in south africa—the role of government policy.

1. Introduction

2. literature review, 2.1. theoretical literature review, 2.2. empirical literature review, 2.3. contribution to literature, 3. model framework, 3.1. quality of life, cost of living, and lifetime level of accumulated wealth, 3.2. macro-economic wealth inequality model, 4. data analysis and results, 4.1. quality of life, cost of living, and lifetime level of accumulated wealth, 4.2. macro-economic wealth inequality model, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Fortuin, M.J.; Grebe, G.P.M.; Makoni, P.L. Wealth Inequality in South Africa—The Role of Government Policy. J. Risk Financial Manag. 2022 , 15 , 243. https://doi.org/10.3390/jrfm15060243

Fortuin MJ, Grebe GPM, Makoni PL. Wealth Inequality in South Africa—The Role of Government Policy. Journal of Risk and Financial Management . 2022; 15(6):243. https://doi.org/10.3390/jrfm15060243

Fortuin, Marlin Jason, Gerhard Philip Maree Grebe, and Patricia Lindelwa Makoni. 2022. "Wealth Inequality in South Africa—The Role of Government Policy" Journal of Risk and Financial Management 15, no. 6: 243. https://doi.org/10.3390/jrfm15060243

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Inequality in South Africa is a ‘ticking timebomb’

“The COVID-19 pandemic has exposed how fractured South Africa’s democracy is, and just how unequal we are as a society. The biggest ticking timebomb we have in this country is inequality,” said Busi Mavuso, the chief executive officer of Business Leadership South Africa.

Mavuso was one of several panellists to share their sentiments on rising inequality in South Africa. She spoke during a webinar organised by the University of Cape Town’s (UCT) African Centre of Excellence for Inequality Research (ACEIR) , in partnership with the Embassy of France in South Africa.

The discussion, titled ‘Historical inequalities and economic transformation in South Africa’, took place as the continent celebrates Africa Month. The virtual event formed part of a series of debates commissioned by the President of France, Emmanuel Macron, ahead of the Africa–France Summit in October. The debates have been arranged to identify the key challenges the continent faces, and to address them head-on at the summit. The summit will shift focus from heads of state and government and add the voices of civil society, entrepreneurs and the youth.

South Africa has the highest Gini coefficient (a gauge of economic inequality) in the world, making it the most unequal society – and the COVID-19 pandemic has deepened this crisis.

“If this pandemic doesn’t make us, as leaders, think carefully about how we are going to deal sustainably with our structural economic flaws, then I don’t know what will.”

“If this pandemic doesn’t make us, as leaders, think carefully about how we are going to deal sustainably with our structural economic flaws, then I don’t know what will,” Mavuso said.

Painting a picture

In his keynote address, Professor Vimal Ranchhod, deputy director of the Southern Africa Labour and Development Research Unit (SALDRU) at UCT said that inequality in South Africa can be directly attributed to the high levels of unemployment. This, he said, leads to income inequality, and black and women South Africans are adversely affected.

He explained that inequality manifests in different ways, including gender inequalities, urban and rural dweller inequalities, education inequalities, and racial inequalities.

Having analysed data from the past 25 years – since the advent of democracy – Professor Ranchhod said it’s clear that South Africa has long been a “highly unequal society”. Yet, he continued, policies indicate that inequality was recognised as an important challenge for redress “long ago”. Several policies aimed at addressing inequality were introduced. But despite this mixture of policy rhetoric, and the fact that some policies were implemented eventually, inequality still remains “extremely persistent” today.

“Short of massively disruptive social change, in the form of revolutions, what we need is a policy system which thinks systematically and substantially.”

Ranchhod also discussed and explained the inequality trap in education and provided the audience with a hypothetical example demonstrating how it operates, highlighting the wide gap between rich and poor. In this context, he said, unequal access to schools means that some children won’t have the opportunity to acquire the same skills or education levels as others. As a result, only a fraction of young adults will enter the labour force with the same high levels of secondary and tertiary education.

“This is how the inequality trap manifests,” he said.

“Short of massively disruptive social change, in the form of revolutions, what we need is a policy system which thinks systematically and substantially. It can’t be small, marginal changes … [in order to] reduce inequality.”

Nothing to lose

Mavuso said that South Africa finds itself in an environment where too many people are living in abject poverty; and sadly, they have nothing to lose. But the country and its people need the opposite in order to thrive.

“We are sitting in an environment of two economies and one nation, and it’s unsustainable.”

“If people have something to lose then they think before they act, and they somehow become motivated. We are sitting in an environment of two economies and one nation, and it’s unsustainable,” she said.

According to Mavuso, countries that will bounce back quickly following the COVID-19 pandemic are countries with “diamond structures”. This she explained refers to countries with an 80% middle-class population. But South Africa’s pyramid structure is poles apart from that. Only 10% of South Africans live in “opulence”, while 35% are ranked as middle class, and more than 50% live in abject poverty. Mavuso stressed that no nation in the world can achieve inclusive economic growth if it excludes the majority of its citizens and only includes the minority.

“We cannot go to war with only 10% of our soldiers. If we agree that our focus as a country right now is on economic recovery, then I’m afraid that our economic recovery efforts [are] elusive,” she said.

Does corporate South Africa have a role to play in the process? Absolutely.

“If you agree that businesses [are] the only social partner with disproportionate resources, we have an obligation to do more to address … socio-economic transformation in this country,” she said.

She said government policies such as Broad-Based Black Economic Empowerment (BBBEE), introduced to try and intervene in the inequality crisis, are unrealistic without proper monitoring and evaluation processes and strategies.

“BBBEE has now been made a blunt instrument because of the lack of monitoring and evaluation. By monitoring BBBEE, government has to drag corporate South Africa, kicking and screaming, to ensure that they implement effective BBBEE interventions and policies. [Without] them we have seen how we have regressed as an economy,” she said.

Address segregation

Professor Michael Sachs, a professor in economics at the Southern Centre for Inequality Studies at the University of the Witwatersrand, said that it’s time to stop thinking about inequality as a problem of the poor, and to start thinking about it as a problem for the affluent.

“We need to think more about what the sacrifice is that the affluent need to make in order to overcome this problem,” he said.

Segregation too remains a fundamental problem in South Africa. He said that segregation in the education system, which exposes the large disparities between private and public schools, must be addressed. If we do not do so, it will be difficult to overcome the problem of inequality.

“Inequality is reproduced by the segregation that exists in social systems.”

Without actively working to change the structures of society; without transforming institutions, progress will be stunted, Sachs said.

“We may not actually solve the problem,” he pointed out. “We may entrench the current situation.”

Other speakers to add their voices at this event included Shaeera Kalla, a researcher at the University of Johannesburg, and Tashmia Ismail-Saville, CEO of the Youth Employment Service.

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South Africa most unequal country in the world: Report

Race plays key factor in a society where 10 percent of population owns more than 80 percent of wealth, World Bank says.

South Africa is the most unequal country in the world, with race playing a determining factor in a society where 10 percent of the population owns more than 80 percent of the wealth, a World Bank report has said.

“South Africa… is the most unequal country in the world, ranking first among 164 countries,” the Washington-based institution said Wednesday in a report, Inequality in Southern Africa.

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Almost three decades after the end of apartheid, “race remains a key driver of high inequality in South Africa, due to its impact on education and the labor market,” it said.

When race is considered as a factor in income disparities, the report added, “its contribution to income inequality amounts to 41 percent, while contribution of education is reduced to 30 percent.

“The legacy of colonialism and apartheid, rooted in racial and spatial segregation, continues to reinforce inequality.”

The country’s neighbours that make up the rest of the Southern African Customs Union – Botswana, Eswatini, Lesotho and Namibia – established in 1910, all finish higher on the list of the most unequal countries in the world.

In the region, women earn on average 30 percent less than men with the same level of education with the pay gap as wide as 38 percent in Namibia and South Africa.

The uneven distribution of agricultural land is also a factor driving inequality, especially in rural areas.

In Namibia, 70 percent of the 39.7 million hectares (98.1 million acres) of commercial agricultural land “still belong to Namibians of European descent”, the World Bank said.

The report was produced before the COVID-19 pandemic and its authors used the Gini coefficient – an indicator of income inequality – to rank countries.

• InFocus Pages
• South Africa
• Southern Africa

How South Africa Could Tackle 'Huge Gap' Between Rich And Poor

The gap between the rich and poor in South Africa is wider than any other country in the world, writes Imraan Valodia , Pro Vice-Chancellor of Climate, Sustainability and Inequality at the University of the Witwatersrand .

Writing in the The Conversation Africa,  he explains that while recent data suggest income inequality between countries globally has been falling, which he attributes to the rising incomes of people in China, "If we consider inequality in wealth, which gives us a fuller picture than income, the situation in South Africa is even more extreme", he wrote of the country where 0.1% of the population own 25% of the wealth.

Valodia urges the South African government to focus on reducing inequality, because not only is it "not good for the economy", it also has negative consequences for democracy and social cohestion: "This is especially a problem in South Africa, where a child born in a low-income household is unlikely to go to a good school, and therefore less likely to attend university, and therefore less likely to find employment, and so on." he wrote.

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Poverty, Inequality and Unemployment in South Africa: Context, Issues and the Way Forward

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The This paper outlines the recent labour market reforms in South Africa and discusses their likely impact on poverty and the working poor. Gauteng, South Africa&#39;s economic powerhouse, has long been dependent on immigration to supply its labour requirements, a phenomenon deeply rooted in the provinces early economic history and the development of mining and heavy industry. As far as possible, the analysis compared in-migrants to non-migrants and intra-Gauteng migrants in order to provide insight into special benefits or challenges that in-migrant households may present. The Labour Force Survey module on migrant labour allowed the profiling of migrant labourers and the approximation of economic links between Gauteng and other provinces as represented by remittances.

Professor Vaola Sambo (Ph.D.)

The article explores the policies that have been promulgated in South Africa post-democracy to address the issue of income inequality. These policies include the National Norms and Standards for School Funding Policy (NNSSF), and the Employment Equity Act 47 of 2013 as amended. South Africa has been found to be one of the most unequal countries in the world because of the cohabitation of the first and third economies. On the one hand, the NNSSF policy aims to address income inequality by correcting the legacy of apartheid in the schooling system. On the other hand, the Employment Equity Act intends to amongst other things correct disparities in income. The article relies on a qualitative methodology. The findings reveal that despite the various policies that have been promulgated, the results do not reflect what the policies intended to achieve. As a result, inequalities are still rampant and the majority of the citizens are languishing in abject poverty. The article concludes with a framework that highlights the key prerequisites that need to be in place in order to address income inequalities.

muzi maziya

Kate Philip

University of Cape Town: Southern Africa Labour and Development Research Unit

Hayley McEwen , Murray Leibbrandt

Creating jobs and reducing unemployment are key economic and social challenges in South Africa. This is explicitly recognized by the South African government, which, under their policy framework known as the “Accelerated and Shared Growth Initiative for South Africa”(ASGISA), aims to halve unemployment by 2014 by removing a number of constraints on faster output and employment growth. This report explores some of the linkages between growth, poverty, inequality and the labour market in post-apartheid South Africa. The ...

Journal of Poverty

Benjamin J Roberts

Social work and society

Ina Conradie

South Africa is currently emerging from a political and socio-economic crisis. A political faction largely based on patrimonialism threatened to destroy the economy and thus social service delivery. With the recent election of Cyril Ramaphosa as State President a new start has been made to build a successful economy which can act as a base for pro-poor policies. This process will however not be easy. Although South Africa is known as the welfare leader in Africa, with 45.5% of its population receiving welfare grants, these social grants are not large enough to alleviate poverty, and almost 54% of the population remains under the poverty line. The National Planning Commission of South Africa is attempting to institute a comprehensive social security floor to cover all possible needs of the poor and excluded, but with the numbers cited above this remains a difficult undertaking. I will argue that a range of interventions is necessary to address this complex situation. The comprehensiv...

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South Africa has a huge gap between the rich and poor - 4 urgent reasons to tackle inequality

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While South Africa is somewhat exceptional, income inequality within countries has been growing across the world.

The most recent data suggests that income inequality between countries has been falling , but this is largely due to the rising incomes of people in China, who make up a large part of the global population.

If we consider inequality in wealth, which gives us a fuller picture than income, the situation in South Africa is even more extreme. The top 0.1% of the population owns 25% of the wealth . Globally, according to the World Inequality Report, the top 10% of the global population owns 76% of the global wealth .

There are a number of good reasons why the South African government should focus on reducing inequality. I wish to highlight four reasons.

Not good for the economy

First, high levels of inequality are not good for the economy. This is a complex issue, because the causal relationships between economic growth and inequality are multifaceted . But these obscene levels of concentration in wealth leave too much economic power in the hands of a small group of wealthy individuals.

Not good for democracy

Second, high levels of inequality are not good for democracy. Across much of the world, especially in the developed countries, ultra-rightwing politicians such as Donald Trump have been drawing support from the electorate. Among the reasons for this is that working class people feel left behind as wealth and income gaps widen. But in fact, the effect of the economic policies that these right-wing politicians promote is to increase inequality. These political shifts undermine democratic systems, leading to a rise in ultra-nationalism and discrimination against migrants and other minority groups.

We are, unfortunately, seeing the rise of these political views in South Africa too. The rise of this type of politics also undermines multilateral efforts to address global challenges, such as climate change. For example, politicians such as Trump have promoted climate denialism and removed the United States from the Paris Agreement on climate change .

Not good for social cohesion

Third, high levels of inequality are not good socially. Not only is inequality bad for social cohesion, it entrenches inter-generational inequalities.

Economist Branko Milanovic , one of the world’s academic authorities on inequality, has shown in his 2016 book that an American child, purely by the chance event of being born in America, is likely to earn 93 times the income of a child who, also by chance, is born in a poor country .

This is especially a problem in South Africa, where a child born in a low-income household is unlikely to go to a good school, and therefore less likely to attend university, and therefore less likely to find employment, and so on. This increases barriers to social mobility and gives rise to a divided society, with higher levels of tension, uncertainty and conflict.

Undermines climate change efforts

Finally, with climate change, humans are now facing a challenge that threatens their very existence. The wealthy countries, and the elite in developing countries, are largely the cause of the problem , but the costs of climate change are likely to be borne disproportionately by low-income countries and communities. This inequality, which is of course linked to the historical trends of wealth accumulation, is likely to undermine efforts to deal with climate change, by creating resistance to change.

More equality, both within countries and across the world, is imperative if we are successfully to address the existential challenges of climate change.

Prof Sanjay G. Reddy will deliver the Southern Centre for Inequality Studies’ 2024 Inequality Lecture , The Political Economy of Global Inequality: A Drama in Three Parts, on 15 August. In partnership with the Southern Centre for Inequality Studies , The Conversation Africa has published several articles on inequality.

Written by Imraan Valodia , Pro Vice-Chancellor: Climate, Sustainability and Inequality and Director: Southern Centre for Inequality Studies., University of the Witwatersrand

This article is republished from The Conversation under a Creative Commons license. Read the original article .

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Prof M. Von Vintel

South Africa has one of the highest levels of income inequality in the world with an estimated Gini coefficient in the region of 0.67. Write an essay in which you address at least one of the following points:

• Consider the traditional ways in which inequality is measured. Is income necessarily the best way to measure inequality or should we look at a broader set of measures?

Suggested keywords:

• "income inequality" AND measurement
• (income OR lifetime OR wealth OR opportunity OR consumption) AND inequality AND measurement
• "income inequality" AND measurement AND "South Africa"
• (income OR lifetime OR wealth OR opportunity OR consumption) AND inequality AND measurement AND "South Africa"
• Consider the relationship between poverty and inequality. If income is redistributed so that it is more equal, will this necessarily mean a decline in poverty rates? Conversely, will a decline in poverty rates necessarily lead to a more equal distribution of income?
• inequality AND poverty
• income AND inequality AND poverty
• income AND inequality AND poverty AND reduction
• income AND inequality AND poverty AND reduction AND "South Africa"
• Discuss the contributing factors to income inequality in South Africa. These could be historical or contemporary.
• “income inequality” AND (factors OR causes)
• "income inequality" AND “South Africa” AND (factors OR causes)
• income AND inequality AND (factors OR causes)
• income AND inequality AND “South Africa” AND (factors OR causes)
• "income inequality" AND Brazil
• "income inequality" AND Brazil AND “South Africa”
• "income inequality" AND (developing OR emerging OR middle income) AND countries

“Depression and anxiety disorders are together responsible for 8% of years lived with disability globally. Contrary to widely held preconceptions, these are not diseases of affluence. Within a given location, those with the lowest incomes are typically 1.5 to 3 times more likely than the rich to experience depression or anxiety.

Recent research has established a bidirectional causal relationship between poverty and mental illness. Researchers have begun to isolate the underlying mechanisms, which can guide effective policies to protect the mental health of those living in poverty.”

The above extract comes from Ridley et al.2020. Poverty, depression, and anxiety: Causal evidence and mechanisms. Science370,eaay0214(2020).DOI:10.1126/science.aay0214 Download the PDF of the article at the following link: https://www.science.org/doi/10.1126/science.aay0214 Then write an essay in which you choose ONE of the mechanisms listed in the article showing the causal pathway of mental ill-health on poverty OR the causal pathway of poverty on mental ill-health. Using this mechanism as the focus of your essay, discuss:

• The existing evidence for the existence of this mechanism in the South African context; and
• The possible policy interventions which have been shown to be successful in breaking this mechanism of the poverty-mental ill-health cycle.
• poverty AND “mental illness” AND “South Africa”
• poverty AND “mental health” AND “South Africa”
• “economic condition” AND “mental illness" AND “South Africa”
• “economic condition” AND “mental health” AND “South Africa”

Suggested databases to search:

• Google Scholar
• Sabinet African Journals 
• EBSCO Host (Academic Source Premier, Africa Wide Information, Business Source Premier and EconLit)

Topic 1: The macroeconomic effects of decarbonisation: The case of South Africa

Study the ongoing decarbonisation policies in South Africa, such as government investment  and/or carbon taxes, and their effects on the local economy, focusing on output growth, private consumption, employment, inflation, and other macroeconomic indicators, etc.

• (Decarbonisation OR “low carbon” OR green OR sustainable) AND economy AND (impact OR effect)
• (Decarbonisation OR “low carbon” OR green OR sustainable) AND economy AND (employment OR inflation OR gdp)
• (Decarbonisation OR “low carbon” OR green OR sustainable) AND economy AND (employment OR inflation OR gdp AND “South Africa”

Topic 2: Price stability and debt sustainability: The coordination of fiscal and macroprudential policy

Study the coordination fiscal and macroprudential policy and its impact on price stability and debt sustainability. Students can do a general study or a case study on South Africa.

• (fiscal OR macroprudential) AND policies AND “price stability”
• (fiscal OR macroprudential) AND policies AND “debt sustainability”
• (fiscal OR macroprudential) AND policies AND “price stability” AND "South Africa"
•  (fiscal OR macroprudential) AND policies AND “debt sustainability” AND "South Africa"
• EBSCO Host  (Academic Source Premier, Africa Wide Information, Business Source Premier and EconLit)

Prof R Jafta

Topic 1: AGOA: PROGRESS AND PROSPECTS FOR SOUTH AFRICA UNDER RENEWAL

Start here for context and key issues: https://www.tralac.org/publications/article/16476-the-agoa-renewal-and-improvement-act-of-2024-key-features-proposed-changes-and-implications.html

• AGOA AND renewal
• (AGOA OR African Growth and Opportunity Act) AND renewal

Topic 2: Green trade policy: a developing country perspective

Start here for context and key issues: https://www.imf.org/-/media/Files/Publications/Fandd/Article/2023/June/Bataille.ashx

• "climate change" AND policies AND (international OR global) AND trade
• "climate change" AND policies AND (international OR global) AND trade AND (emerging OR developing) countries
• EBSCO Host  (Academic Source Premier, Africa Wide Information, Business Source Premier and EconLit)
• New Palgrave Dictionary of Economics

Dr M Nchake

Economic and social consequences of exposure to conflict: a case of Russia- Ukraine on SA economy. Focus more on key economic and social indicators. You may also refer to other countries like SA.

• political AND conflict AND exposure AND economic AND social AND (impact OR consequences)
• political AND conflict AND exposure AND economic AND social AND (impact OR consequences) AND Ukraine
• political AND conflict AND exposure AND economic AND social AND (impact OR consequences) AND "South Africa"

Gendered effects of electricity shortages in South Africa? Make sure to focus on both the production and consumption side of the economy.

• (gender OR women) AND electricity AND shortages (effect OR impact) AND "South Africa"
• (gender OR women) AND (electricity shortages OR loadshedding) AND (effect OR impact) AND "South Africa"
• ABI/Inform Collection

Prof S Du Plessis

Topic 1: Stricter regulations and penalties should be implemented to reduce distracted driving.

Discuss the potential effectiveness of such measures and their impact on road safety by addressing the costs and benefits associated with implementing stricter regulations and penalties. You may also touch on how such measures might affect public spending on emergency services, healthcare, and law enforcement.

• distracted driving AND (regulations OR penalties) AND (effect OR impact)
• distracted driving AND (regulations OR penalties) AND economy AND (cost OR benefit)
• distracted driving AND (regulations OR penalties) AND public services AND (cost OR benefit)
• distracted driving AND (regulations OR penalties) AND (government OR public) AND (service OR finance OR spending)

Topic 2: Cities should implement congestion pricing to reduce traffic and pollution.

Do you agree with the statement? Discuss the potential economic benefits and drawbacks of congestion pricing, providing examples from cities that have adopted this policy.

• (pollution OR traffic congestion) AND pricing
• (pollution OR traffic congestion) AND pricing AND (city OR cities)

According to a recent UNU-WIDER report, South Africa is on the wrong side of the Laffer curve. Write an essay to explain this phenomenon, why National Treasury has not decreased tax rates in the recent past and what you would expect to see in the next Budget given these findings.

• "tax rate" AND "south africa"
• "tax rate" AND revenue AND "south africa"

Topic 2: Budget competition essay:

Current exchange rate policy in South Africa: Will it be conducive to economic growth post Covid-19? (Given the economic challenges post Covid-19, argue for or against continuing with the status quo regarding exchange rate determination in South Africa.)

• "exchange rate" AND policy AND covid-19 AND "South Africa"
• "exchange rate policy" AND covid-19 AND "South Africa"
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