Deliberations on the nature and measurement of inequality in South Africa

Summary of the learnings from a joint workshop by the Inclusive Society Institute and the Swedish Institute of Future Studies



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Views expressed in this report do not necessarily represent the views of the Inclusive Society Institute or those of their respective Board or Council members or Members.


Authors: Percept Actuaries and Consultants

Edited: Daryl Swanepoel

Graphic Design: Nini van der Walt


AUGUST 2021


Content


1. Introduction and background


2. Some questions on poverty and inequality in South Africa


3. Measuring inequality in developing economies


Issues with the Gini coefficient


The many dimensions of inequality


A systematic approach to understanding inequality


4. Broader discussion on inequality and inequality measures


Rethinking the research questions


Abundance of inequality literature in South Africa


Wealth and inequality


Which multidimensional approach?


5. Data limitations and alternative data sources


Issues with pre-1994 data in South Africa


Useful datasets


Exploring additional data


6. Conclusion and way forward


References


List of figures


Figure 1: Bourguignon triangle (2004) – the relationship between growth, inequality, and poverty


Figure 2: Scheme of social stratification – a poverty dynamics approach to structured inequality


Figure 3: The Multi-Dimensional Inequality Framework (LSE & Oxfam, 2018)


Acronyms and abbreviations



1. Introduction and Background


South Africa has the highest income inequality in the world as measured by the Gini coefficient. Twenty-seven years after the end of apartheid, despite multiple and deliberate policy attempts to grow the economy, increase income for all, and improve the welfare of South Africans, inequality remains stubbornly high. Income inequality matters because it is intrinsically linked to economic growth and absolute poverty: Initial equality and changes in inequality during growth heavily influence the poverty reducing impact of growth. Hence, even if poverty may be regarded as a more pressing problem than inequality (Fields, 2007), distributional issues remain critical for anti-poverty strategies (Ravallion, 2001) This conundrum has implications for South African policy debates and underscores the need to understand the drivers of income inequality.


A recent review by Stats SA, the Southern Africa Labour and Development Research Unit (SALDRU) and the Agence Française de Dével­oppement (AFD) Group (Statistics South Africa, 2019) of inequality in South Africa from 1993/4 to 2018 found that South Africa con­sistently had a high Gini coefficient over the period, irrespective of the data source, with little decrease in inequality levels. However, the high Gini coefficient may obscure underlying positive redistribution dynamics. For this reason, the comprehensive review went beyond reporting the Gini coefficient and used multiple metrics and approaches to analyse the many dimensions of inequality including economic inequality, wealth and asset inequality, labour market inequality, gender inequality, inequality in the social domain and social mobility. Unfortunately, media reports of the review focused on the aggregate Gini coefficient, and this drowned out many of the positive findings in the broader analysis of inequality.


The Inclusive Society Institute (ISI) is an autonomous and independent institution that functions independently from any other entity. It is founded for the purpose of supporting and further deepening multi-party democracy. The ISI's work is motivated by its desire to achieve non-racialism, non-sexism, social justice and cohesion, economic development and equality in South Africa. This desire is pursued through a value system that embodies the social and national democratic principles associated with a developmental state.


The Swedish Institute for Future Studies (IFFS) is an independent research foundation that promotes future perspectives in research and public debate. The research program that has set the IFFS’s framework for recent research activities is called “Which future? Challenges and choices for the 21st century”. The research programme focuses on five themes, of which one is Equality. It therefore has a strong interest and experience base in measuring inequality and how best practices in inequality measurement could be applied in South Africa.


To promote knowledge sharing and mutual learning on inequality measurement and the inequality context in South Africa, ISI and IFFS hosted a workshop on 1 July 2021 to discuss best practices and alternative approaches in inequality and poverty measurement. The workshop was attended by representatives of the Inclusive Society Institute, representatives of IFFS and independent academics from South Africa, Sweden, and Germany. Percept Actuaries and Consultants and 71Point4 presented initial ideas and research ques­tions for an agenda on inequality research in South Africa which is being supported by the Frederich Ebert Stiftung. This report sets out the focus of ISI’s research on inequality and the themes and issues which were discussed at the workshop


2. Some questions on poverty and inequality in South Africa


Before defining a research agenda on inequality, it is important to understand the contentious and sometimes controversial inter­relationship between inequality, poverty, and economic growth. While it is undisputed that economic growth leads to a decrease in absolute poverty, the extent of this decrease and how it is distributed depends on the level of inequality and changes in it. The interrelationships between growth, inequality and poverty are best captured in the Bourguignon triangle (Figure 1). The causal chain from income and wealth inequality to growth (also known as the ‘inequality–growth’ link) are underpinned by two conflicting schools of thought: the traditional (classical) perspective and the ‘new’ political economy of development theories (modern).


Figure 1: Bourguignon triangle (2004) – the relationship between growth, inequality, and poverty


The classical perspective highlights the growth-enhancing effects of income and wealth inequality through the saving-enhancing effects (the rich save proportionately more than the poor), as well as the existence of investment indivisibilities and incentive effects (Aghion & Bolton, 1997; Kaldor, 1955). In contrast, the modern perspective links greater inequality to reduced growth through condi­tions such as resultant political and social instability leading to greater uncertainty and lower investment, high transaction costs, unproductive rent-seeking activities, and increased insecurity of property rights (Thorbecke et al., 2002).


The Kuznets hypothesis of the inverted U-shaped relationship between growth and inequality describes the opposite causal direction (i.e., the ‘growth–inequality’ link). The modern approach, however, suggests that growth patterns resulting in more inequality would lead to lower future growth paths, which negatively impact growth-induced poverty reduction. Ultimately, the poverty-reduction effects of growth depend on how the growth pattern affects income distribution, since inequality acts as the ‘filter’ between growth and poverty reduction (Thorbecke, 2013). Effective poverty reduction would therefore require some combination of higher growth and a more pro-poor distribution of the gains from growth.


There are signs of movement towards a more equal South African society, with a small but growing black middle-class population. However, the COVID-19 pandemic has entrenched unemployment in South Africa, particularly among this group (Futshane, 2021). Although the decline in employment observed was similar for all age groups (and age and education subgroups), it was marked by substantial churning that far exceeded churning estimates during pre-COVID years.


The aim of future ISI inequality reports is not to redo the StatsSA (2019) inequality report and its underlying analyses, but to add more nuance using the same and alternative data sources to explore different research questions and identify positive micro channels out of inequality and poverty, into prosperity. This is being done to obtain a deeper understanding of the impact of transformation initia­tives in post-apartheid South Africa which is not reflected in high-level metrics of income inequality. Our chosen approach will provide a more accurate description of the poverty alleviating strides that have been made, which would otherwise not be recognised.


Metrics and approaches for measuring poverty and inequality: Are there other metrics that should be considered when designing policy interventions?



To understand what lies beneath the average poverty and inequality measures, it is useful to build a poverty and inequality profile. This profile is derived by decomposing poverty and inequality metrics by socio-economic or demographic characteristics. To capture the dynamic aspects of poverty and structural inequality, Schotte et al. (2018) suggests a social stratification scheme that identifies the relationship between individual and household characteristics and patterns of economic mobility. This scheme has advantages over both purely money-metric and multidimensional approaches: it remains anchored in a money-metric threshold (the cost-of-basic-needs poverty line) to broadly determine who can and cannot afford to meet their basic needs (first column in Figure 2), but further distinction between the poor and non-poor is then determined based on propensities for poverty transitions (second column of Figure 2). These propensities are derived from a set of individual and household characteristics that allows inference of multidimensional determinants of economic empowerment.


Figure 2: Scheme of social stratification – a poverty dynamics approach to structured inequality

Source: Schotte, et al., 2018.

Note: Solid lines denote absolute expenditure thresholds. Dashed lines denote probability thresholds.


The research reports to be published by the ISI will not experiment with alternative inequality measures but will rather explore differ­ent lenses of analysis (e.g., gender, youth, employment) to existing measures to shed light on the main drivers of inequality and likely policy options to address them. Future phases of the research will consider a more multi-dimensional approach to inequality, pov­erty, and well-being because it provides a more comprehensive view of the changes in inequality that have occurred across multiple dimensions over time. It also allows for further interrogation of the persistent issues that prevent equality from being achieved, thus informing more progressive policy development.

Structural unemployment and inequality: Is aggregate unemployment the biggest driver of inequality?


Approximately two-thirds of overall inequality in South Africa is driven by inequality in earnings, and about half of this is due to the ex­tremely high levels of unemployment (Statistics South Africa, 2019). A key question for those who are employed and earning income, is how much of a difference does variation in income between individuals contribute to inequality? Second, what then, e.g., access to education and variation in quality of education, explains this variation?


What are the gender dimensions to inequality?


This overarching question will be explored through the gender dimensions of unemployment, income availability, gender and grants, and gender and post-school education. Gender intersects with many disadvantages and inequities, including income inequality. Even though women represent over half of the South African population, their share of household income and expenditure is significantly lower than that of men (Statistics South Africa, 2019). By exploring the gender dimensions of household formation, unemployment, income availability (including grants), and post-school education, we may gain a deeper understanding of how inequalities accentuate vulnerabilities, and which levers may contribute to achieving income equality for women.


Household composition dynamics: To what extent is inequality in South Africa driven by generational wealth dynamics?


It may also be useful to consider generational wealth dynamics and to what extent it drives inequality in South Africa. In higher-in­come groups, income and opportunities to access income (e.g., education) may be derived from existing wealth. There is robust evi­dence that wealth is more unequally distributed than income in South Africa (Orthofer, 2016). Lower rates of population growth among high-income groups, compared to low-income groups, further drive inequality through the concentration of inherited wealth (Peterson, 2017). Questions for research here include the specific nature of the inequality dynamics of certain age groups and cohorts. Working with 71point4, wealth dynamics can also be explored using alternative (non-survey) data on housing and credit markets.


The contribution of global inequality dynamics: What components of South African inequality are not necessarily South Afri­can-specific but related to the way economies function globally?


There is a growing consensus amongst scholars that a major contributor to increasing income inequality globally are the top 1% of individuals on the earnings distribution and this elite subgroup is where more attention should be paid (Alvaredo et al., 2013). Income generated from the wealth of the top 1%, in addition to their earned income, are important to consider when exploring income inequal­ity and how best to target interventions. This approach may be of relevance in the South African context where wealth has accumu­lated along racial lines for decades. If, for example, we exclude the top 1% of earners from inequality calculations, would it change the inequality measure and if so, how? There is, however, a strong social justice component to understanding the disparities in income between the top 1% and the rest of the population and this dimension should not be ignored.


For the first workstream of ISI’s work on inequality, the more nuanced questions that need further appraisal and analysis using the Stats SA (2019) report but also other available inequality, wealth, and poverty analyses will be identified. We propose to primarily focus on literature that analyses the more recent household surveys and panel studies like GHS, QLFS, and NIDS as more recent data will provide a clear direction for change and required policy actions. We also propose looking at alternative sources of data relating to wealth, access to financial services, property ownership and other relevant dimensions. This piece of work is necessary to add depth and nuance to the current discourse.


3. Measuring inequality in developing economies


The discussion in this part of the workshop was informed by short presentations and insights shared by researchers of the IFFS, as well as research-related questions of clarity posed by both the IFFS and the ISI’s participants. The discussion mostly focused on broad themes around the measurement and nature of inequality in South Africa.


Issues with the Gini coefficient


The Gini coefficient is often used as an inequality index due to its invariance properties and its ability to satisfy the transfer principle. However, it was considered useful only in cases where it is decomposed, which is often done in the current literature. Despite this, the Gini has several limitations that make it a poor indicator of progress and distribution. In the South Africa context, the Gini was further highlighted as a poor metric to target because it excludes income generated from the informal sector that may not always be accurately captured by surveys (this may speak to the shortcomings of survey data, rather than the Gini itself).


By focusing on the Gini, a grim picture of inequality is painted in South Africa. This ignores the political reforms and improvements in access that have taken place. In order to present a more accurate depiction of inequality in South Africa, a broader approach, which focuses on overall welfare and progressive reform is necessary. A multidimensional approach, that still places economic indicators at its core, provides the granularity required to view inequality in a more holistic way and highlight the roots of the problem.


The many dimensions of inequality


Although income and wealth dimensions remain at the forefront of measuring inequality, the inclusion of dimensions such as education (Hoxby & Avery, 2013), health (Ataguba et al., 2011), crime (Sampson et al., 2005), and spatial inequality (Reardon & Bischoff, 2015) have been investigated to provide a more comprehensive view of the development progress that has taken place in South Africa.


The post-apartheid development policy largely focused on addressing existing economic, social, and spatial inequalities along racial lines. This has led to several reforms that have improved the overall quality of life and living conditions of disadvantaged groups in South Africa. This progress is often under-reported in the media.


Basic living conditions are at the forefront of progressive reforms. Housing, with the addition of water, sanitation, electricity, and telephone access, saw a 152% increase in the budget allocation following apartheid (Brook, 2017). To date, approximately 2-3 million government-subsidised homes have been built (Centre for Affordable Housing Finance Africa, 2021). The benefits of housing have been enhanced by the expansion of water and sanitation to 95% of the population 20 years after apartheid (Jacobs et al., 2014).


Access to education and opportunities for employment have also improved over the last three decades. The once racially segregated schooling system has been dismantled to expand access to integrated schooling. Reforms have attempted to decolonise the school­ing system, particularly by allowing students to be taught in their mother tongue language. Approximately 20% of the overall budget has been allocated to education to ensure equitable access to free schooling for all South Africans (Brook, 2017).


To ensure long-term economic shifts, affirmative action policies have been introduced to tackle the employment disparities among racial and gender groups. Twenty years after the end of the apartheid era, the racial gap in employment has been reduced, however, this gap still remains large, with a more than 50% difference in employment between the Caucasian and Black population (Fredericks & Yu, 2017). The gender gap has also remained, making African women highly vulnerable to unemployment (Fredericks & Yu, 2017).


Healthcare access and supply was recognised as critical in the post-apartheid era. In an attempt to address health inequalities, approximately 3% of the budget was allocated to healthcare sector reforms (Brook, 2017). This has led to the expansion of primary healthcare clinics nationwide and free access to primary healthcare services for all, along with free access to higher levels of care for impoverished individuals. Similar to the education sector where access has increased, policy discussions in the health sector are now moving towards addressing the quality of the services provided so that real changes can be seen in outcomes.


Multidimensional approaches to measuring inequality, such as the Level of Living approach (Kaldaru et al., 2009), have the advantage of tracking progress over time at an individual (including children) and household level. This approach seeks to determine whether indi­viduals have the resources needed to govern their own lives. Overall progress can be evaluated by reviewing the average level of each dimension and the proportion of individuals without important resources. Inequality can be evaluated by reviewing dispersion of the population and differences between groups. This creates a shift in thinking from wealth creation to establishing overall welfare.


The multidimensional approach was considered more comprehensive and indicative of how inequality manifests in the lived experi­ences of South Africans when compared to the aggregate Gini coefficient. The StatsSA 2019 report provides a more comprehensive approach to capturing the gradual reforms made in post-apartheid South Africa (Statistics South Africa, 2019). It was hypothesised that combining economic indicators with other dimensions such as life expectancy may denote the state of inequality more clearly.


A systematic approach to understanding inequality


Another proposed framework was a systemic approach to understanding inequality. This approach provides a holistic multidimension­al view of inequality and the power relations of influence. It includes seven domains, four of which are linked to financial security, with several indicators under each domain Figure 3.


Figure 3: The Multi-Dimensional Inequality Framework (LSE & Oxfam, 2018)


By taking this broader perspective, multiple domains can be evaluated. In addition to inputs, processes can also be reviewed, and the various types of inequality can be more accurately identified (Bucelli & Mcknight, 2021) This framework attempts to empower communities (International Civil Society Centre, n.d.). It emphasises the need for agenda setting, policy reform and indicators to be driven by the input of marginalised communities. Despite the benefits that may be derived from community participation, these approaches can be challenging to apply as they often require additional tax and property data.


4. Broader discussion on inequality and inequality measures


In this part of the workshop, the discussion shifted towards how the initial research questions presented earlier could be reframed and how best to think about the measurement of inequality in South Africa.


Rethinking the research questions


A theme that emerged during the discussion was the need to consider the research question(s) more carefully. The suggested research question of excluding the top 1% of the income distribution from inequality measurements was viewed as bypassing a fun­damental cause of inequality. It was also viewed as signaling the wrong political measure if a structure of privilege is excluded from measurement. Instead, it was suggested that it would be more helpful to focus on the top 1% of the income distribution to better understand how fiscal instruments could be best used for income redistribution, most notably of the wealth tax base.


At a broader level, it was suggested that researchers take a step back and ask the following questions:

Which types of inequality matters the most?

  • Which type of inequality do we want to understand more and why?

  • Is this study only useful for policymakers, or for community participants too?

  • How should the lived experience be incorporated into the measurement of inequality?



The discussion also emphasised the need to veer away from measuring the level of inequality, to why inequality continues to remain high and what can be done to address this. This is of particular importance when reviewing the high levels of income inequality that persist despite improvements in absolute poverty and access to social and essential services. There was some speculation that is may be due to current policies being unable to identify and address the root causes of inequality. The abundant literature on poverty and inequality in post-apartheid South Africa make the root causes clear, which suggests that the issues may lie in policy design and implementation. The limitations of quantitative data in capturing the full picture of inequality were acknowledged, and there was agreement that gaps in qualitative data need to be filled.


Abundance of inequality literature in South Africa


The literature on income inequality in South Africa is vast and the quantitative measurements of inequality presented in this literature show little variation over time. This literature is useful to establish best practices for policy design in South Africa (Leibbrandt et al., 2021).


Most of the academic literature on income inequality is often misinterpreted or misrepresented by the media. Media attention needs to shift away from a sole focus on income inequality towards a multidimensional approach of reporting on inequality that pre­sents the state of the country in a more nuanced way. To delve further into the structural and demographic factors associated with inequality, disaggregation of indicators with a focus on gender and the young may lead to more meaningful results. The capacity to investigate these measures are apparent in the Stats SA 2019 report which includes multiple dimensions of inequality (Statistics South Africa, 2019).


Wealth and inequality


Wealth inequality has largely been excluded when investigating indicators of inequality, with more emphasis being placed on pover­ty and marginalisation related to income inequality. The multidimensional approach goes beyond income inequality and has the advantage of allowing wealth disparities to be included as an additional factor rather than an alternative one. By adding wealth inequality to the debate, power inequality, mentioned in the systemic approach, becomes increasingly relevant. The inclusion of mul­tiple economic indicators, including wealth, presents a more comprehensive picture and allows us to answer questions related to the lack of distributional progress following the end of the Apartheid era.


Which multidimensional approach?


The inclusion of several dimensions of wealth and well-being provides a more accurate representation of the current economic state of South Africa with respect to equality. Various metrics have been studied to date, and are already available as a means of evaluating South Africa in a multidimensional way. However, the outcomes of these are often similar regardless of the metric used.


Although the need to interpret inequality through a multidimensional lens is evident, the ideal method of doing this has not been made clear. Various weightings can be used to determine the final measure of inequality, and the relevance of each contributing domain needs to be explored. The inclusion and weighting of indicators needs to be carefully considered and critiqued in the South Afri­can context.


5. Data limitations and alternative data sources


In the last part of the workshop, participants focused on the nature and shortcomings of the datasets typically used for inequality analyses.


Issues with pre-1994 data in South Africa


The benefits of reviewing longitudinal data were expressed in the workshop, particularly when following multidimensional progress over time. The comprehensive collection of data, related to several important dimensions of inequality, is currently reported in the Stats SA report. However, progress over longer periods of time is challenging to see due to the limitations of pre-1994 data. Histor­ical datasets do not provide information on all population groups. Census data collected during the Apartheid era often excluded black South Africans who were severely impoverished and often unemployed. This has heavily affected the ability to review all dimensions of inequality over time as data cannot accurately be collected retrospectively. The Stats SA reports and various household surveys therefore provide a starting point for the collection of multidimensional data (Statistics South Africa, 2019).


Useful datasets


Several relevant and useful datasets were identified for studying multidimensional inequality. NiDS and GHS were highlighted as key sources of data on various indicators of the multidimensional poverty index between 2008 and 2017. The lack of wealth data in household surveys can be overcome through the use of property market, pension, credit and anonymised tax data. The inclusion of these data sources often results in variations in the findings obtained by income inequality data, highlighting the need to include wealth indicators. Additionally, HEMIS may be useful for tracking individuals through higher education and the tax system.


Despite the availability of a wide array of data sources, collecting longitudinal data in multiple dimensions, including wealth, may be difficult to access due to tedious application processes and restricted access. The new implementation of the POPI act has also created difficulty in accessing data due to the uncertainty surrounding how data is distributed and the fear of prosecution if the act is breached. Due to these limitations, it is important for existing literature to be considered and used to improve efficiency.


Exploring additional data


The discussion highlighted the need to explore inequality in various population sub-groups. This may improve the quality of data and supplement the already available literature. Focus groups were proposed as a source of qualitative data which can be used to em­power communities and emphasize the indicators that are considered valuable to the population. The inclusion of vulnerable groups, such as youth and children, during national surveys can also be considered a goal for South Africa. This has the ability to improve the quality of data that is currently available and provide a longitudinal view of progress made in the country. It is important to note that progress may appear to be slower when including youth.


6. Conclusion and way forward


After a robust debate on inequality and inequality measures, there was consensus that aggregate measures of inequality are not as useful as measures that lend itself to more nuance and granularity, especially in the South African context.


Based on the current inequality literature, it is evident that strides have been made in South Africa post-1994 (Statistics South Africa 2019). However, structural issues remain a binding constraint for further growth and development. All participants agreed that more could be done to rectify this position. An important outcome regarding the way forward was the need for a second workshop that focuses on policy options for reducing inequality.


References


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Alvaredo, F., Atkinson, A. B., Piketty, T., & Saez, E. (2013). The Top 1 Percent in International and Historical Perspective. Journal of Economic Perspectives, 27(3), 3–20. https://doi.org/10.1257/JEP.27.3.3


Ataguba, J. E., Akazili, J., & McIntyre, D. (2011). Socioeconomic-related health inequality in South Africa: evidence from General Household Surveys. International Journal for Equity in Health 2011 10:1, 10(1), 1–10. https://doi.org/10.1186/1475-9276-10-48


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This report has been published by the Inclusive Society Institute

The Inclusive Society Institute (ISI) is an autonomous and independent institution that functions independently from any other entity. It is founded for the purpose of supporting and further deepening multi-party democracy. The ISI’s work is motivated by its desire to achieve non-racialism, non-sexism, social justice and cohesion, economic development and equality in South Africa, through a value system that embodies the social and national democratic principles associated with a developmental state. It recognises that a well-functioning democracy requires well-functioning political formations that are suitably equipped and capacitated. It further acknowledges that South Africa is inextricably linked to the ever transforming and interdependent global world, which necessitates international and multilateral cooperation. As such, the ISI also seeks to achieve its ideals at a global level through cooperation with like-minded parties and organs of civil society who share its basic values. In South Africa, ISI’s ideological positioning is aligned with that of the current ruling party and others in broader society with similar ideals.


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