DESK REVIEWS | 01.03.04. Poverty and inequality

DESK REVIEW | 01.03.04. Poverty and inequality

The country has experienced an increase in the number of people living in extreme poverty (from 6.6% in 2016 to 7.4% in 2017; that is from 13.5 million to 15.2 million people). There was also an increase in the proportion of people living below the poverty line (income of up to $5.50 a day). In 2017, this number stood at 26.5%, compared to 25.7% the year before. Such rates represent a change from 52.8 million to 54.8 million people. Most of people affected —over 25 million — live in the North Eastern region of the country (Brazilian Institute of Geography and Statistics, 2018c). The GINI index in Brazil was reported at 51.3 in 2015 (Trading Economics, 2019). With regards to gender equality, national figures (2016) reveal gender inequality across the country. For example, women devote about 73% more hours to domestic and/or household chores than men (18.1 hours versus 10.5 hours). The greatest inequality in the distribution of hours dedicated to these activities is in the Northeast Region, where women dedicate about 80% more hours than men, reaching 19 more hours a week. Black or mixed-race women are the ones that dedicate themselves the most to the care of people and/or household chores, with a record of 18.6 hours per week in 2016. Such figures vary little for men when considering ethnicity or region of residence (Brazilian Institute of Geography and Statistics, 2018b, 2019b).

References:

Brazilian Institute of Geography and Statistics. (2018b). Estatísticas de Gênero Indicadores sociais das mulheres no Brasil.

Brazilian Institute of Geography and Statistics. (2018c). Síntese dos Indicadores Sociais, uma análise das condições de vida da populção brasileira.

Brazilian Institute of Geography and Statistics. (2019b). Gender Statistics—Social indicators of women in Brazil. IBGE.

Trading Economics. (2019). Brazil—Gini Index. https://tradingeconomics.com/brazil/gini-index-wb-data.html

 

Since 2013, the Hong Kong Government has officially defined the poverty line as 50% of the median monthly domestic household income. The poverty lines of from 1-person to 6-person+ household in 2017 were HK$4,000, HK$9,800, HK$15,000, HK$19,900, HK$20,300, and HK$22,500 respectively (HKSAR Government, 2018). Households with monthly household income lower than the poverty line are defined as “poor households” and all members of these households are referred as “poor population”.

The poverty situation of Hong Kong can be reflected by four sets of indicators, including one set of “before-intervention” statistics and three sets of “after-intervention” statistics. The “before-intervention” poverty statistics are compiled with the assumption of no prevailing government policies and measures, which form an objective benchmark for assessing the effectiveness of intervention. It only includes household members’ employment earnings, investment income, and non-social-transfer cash income. “After-intervention” poverty statistics are compiled by further including the income provided by the government policies and measures, such as taxation, recurrent-cash benefits, non-recurrent cash benefits, and in-kind benefits. In 2017, the poverty rate before intervention was 20.1% (1,376,600 persons). After recurrent cash intervention, the poverty rate improved to 14.7% (1,008,800 persons). Among those aged 65 and over, the poverty rate after recurrent cash intervention was 30.5% (340,000 persons) (HKSAR Government, 2018).

Inequality between a society’s rich and poor is often measured by the Gini coefficient, with zero indicating equality. In 2016, the Gini coefficient of Hong Kong based on original monthly household income was 0.539 and that based on post-tax post-social transfer monthly household income was 0.473. It was the highest over the past 45 years with an increase of 0.006 points since 2006, and worse than other developed economies such as Singapore (0.356), United States (0.391), United Kingdom (0.351), Australia (0.337), and Canada (0.318) (Census and Statistics Department, 2017a; Oxfam Hong Kong, 2018).

For gender inequality in income, the median monthly income of males and females in 2016 were $16,890 and $12,000 respectively, with males’ income 40.8% higher. Also, there was a higher percentage of working women (9.1%) (excluding foreign domestic helpers) with monthly income from main employment below $6,000 than that of men (4.6%). The difference between income of working women and men can be attributed to differences between working women and men in industrial and occupational distributions, educational attainment, working experience, and nature of work. For example, proportionally more women (19.8%) than men (8.7%) worked as clerical support workers who had relatively lower monthly income from main employment in 2016. On the other hand, there was a higher proportion of men (21.2%) working as managers and administrators and professionals than women (13.1%) who had relatively higher monthly income (Census and Statistics Department, 2017a).

References:

Census and Statistics Department. (2017a). Hong Kong 2016 Population By-census – Thematic Report: Household Income Distribution in Hong Kong. Retrieved from https://www.censtatd.gov.hk/hkstat/sub/sp459.jsp?productCode=B1120096

HKSAR Government. (2018). Hong Kong Poverty Situation Report 2017. Hong Kong: HKSAR Government Retrieved from https://www.povertyrelief.gov.hk/eng/pdf/Hong_Kong_Poverty_Situation_Report_2017(2018.11.19).pdf.

Oxfam Hong Kong. (2018). Hong Kong Inequality Report. Retrieved from https://www.oxfam.org.hk/tc/f/news_and_publication/16372/Oxfam_inequality%20report_Eng_FINAL.pdf

According to the World Bank (2011), the GINI index for India in 2011 was 35.7. In 2017, the Inequality-Adjusted Human Development Index (IHDI) ranked India at 130 worldwide, with a score of 0.468 (United Nations Development Programme (UNDP), 2017).

References:

United Nations Department of Economic and Social Affairs, Population Division (UNDP). (2017). World Population Prospects. The 2017 Revision. Available from: https://www.un.org/development/desa/publications/world-population-prospects-the-2017-revision.html

World Bank. (2011). GINI Index (World Bank Estimate). Available from: https://data.worldbank.org/indicator/si.pov.gini

The United Nations Human Development Index (HDI) of Indonesia has increased from 0.528 in 1990 to 0.694 in 2018 (Agustina et al., 2019, p.78; United Nations Development Programme, 2018). This leads to a ranking of Indonesia in place 116 out of 189 countries (United Nations Development Programme, 2018). As with other indicators, there was considerable regional variety reported for the HDI (Sukamdi & Mujahid, 2015, p.xi).

Inequality in Indonesia has widened considerably between the years 2000 (28.5) and 2013 (39.9), but slightly diminished since 2017 (Gini index:38.1) (World Bank, 2018b).

Agustina and colleagues (2019, p.78) further report that the proportion of people in Indonesia living on ‘less than $1.90 per day in PPP’ declined substantially between 1984 (70.3%) and 2017 (5.7%); however, ‘high variability across and within provinces and districts’ remains.

Due to the absence of comprehensive social protection, older people in Indonesia are extremely vulnerable. According to Kidd and colleagues (2018, p.1), the highest rate of extreme poverty can be found among people aged 65 and over, with approximately 80 per cent of this age group living ‘households with a per capita consumption below IDR 50,000’ per day (below US$4). The proportion among those aged 80 and older is considered to be even higher. Women and those without family support are particularly vulnerable (Kidd et al., 2018, p.1).

References:

Agustina, R., Dartanto, T., Sitompul, R., Susiloretni, K. A., Suparmi, Achadi, E. L., Taher, A., Wirawan, F., Sungkar, S., Sudarmono, P., Shankar, A. H., Thabrany, H., Susiloretni, K. A., Soewondo, P., Ahmad, S. A., Kurniawan, M., Hidayat, B., Pardede, D., Mundiharno, … Khusun, H. (2019). Universal health coverage in Indonesia: concept, progress, and challenges. The Lancet, 393(10166), 75–102. https://doi.org/10.1016/S0140-6736(18)31647-7

Kidd, S., Gelders, B., & Rahayu, S. K. (2018). Implementing Social Protection for the Elderly in Indonesia. http://www.tnp2k.go.id/filemanager/files/Perlindungan Sosial Lansia/Elderly Brief – English Version.pdf

Sukamdi, & Mujahid, G. (2015). Internal Migration in Indonesia. UNFPA Indonesia Monograph Series No.3, xii, 90.

United Nations Development Programme. (2018). 2018 Statistical Update: Human Development Indices and Indicators. Human Development Reports. https://hdr.undp.org/en/content/human-development-indices-indicators-2018-statistical-update

World Bank. (2018b). GINI index (World Bank estimate) – Indonesia. World Development Indicators. https://data.worldbank.org/indicator/SI.POV.GINI?locations=ID&view=chart

As of 2017, 19.3% of the Jamaican population lived below the poverty line (see table 5) (STATIN, 2018) with a GINI coefficient of 35- placing Jamaica at a global ranking of 97 for this measure (CIA, 2019). Additionally, Jamaica’s inequality income was reported at 32% in 2018 as compared to the regional average of 34% (UNDP, 2019).

Table 5: Poverty Incidence by Region

Region 2012 2013 2014 2015 2016 2017
Kingston Metropolitan Area 19.7 17.8 15.3 14.3 11.9 17.1
Other Towns 16.6 20 16.2 14.7 16 20.1
Rural Areas 21.3 31.3 24.9 28.5 20.5 20.1
Jamaica 19.9 24.6 20.0 21.2 17.1 19.3

 

Source, Statistical Institute of Jamaica, 2018, https://statinja.gov.jm/living_conditions_poverty.aspx

References:

CIA. (2019). Central America: Jamaica — The World Factbook. https://www.cia.gov/the-world-factbook/countries/jamaica/

Statistical Institute of Jamaica (STATIN). (2019). Living Conditions and Poverty: Table Incidence of Poverty by Region: 1994-2014. Available from: https://statinja.gov.jm/living_conditions_poverty.aspx

UNDP. (2019). Human development Report 2019: Beyond Income, Beyond Averages, Beyond Today: Inequalities in Human Development in the 21st century. Available from: https://hdr.undp.org/content/human-development-report-2019

Even though Kenya is recognized as a lower-middle income country, most of its residents continue to live below the poverty line in rural areas. Poverty levels vary across different cities and towns in Kenya with a lower incidence of multidimensional poverty in Nairobi (capital city of Kenya) and satellite towns such as Ruiru (22%) and Thika (27%). This figure is higher in other cities such as Mombasa (44%) and Kisumu (46%). Additionally, location-based horizontal inequality estimates are higher in the capital city and Thika town. Although these urban centers show relatively lower overall poverty levels compared to other urban centers, they register higher inequalities in deprivation scores between their different sub-locations (Shifa & Leibbrandt, 2017).

Nevertheless, Kenya’s level of inequality is moderate in comparison to Tanzania, Uganda, and Ghana as the Gini index dropped from 0.45 in 2005/06 to 0.39 in 2015/16 while in rural areas it fell from 0.37 to 0.33, demonstrating a remarkable positive change for an indicator that seldom changes over time (International Bank for Reconstruction and Development/The World Bank, 2018). The current monetary and non-monetary poverty indicators in Kenya are better than most countries in Sub-Saharan Africa. Specifically, Kenya’s adult literacy level is among the highest in Africa and performs better in access to improved sanitation compared to countries with a similar poverty headcount (World Bank Group, 2018).

There is very low financial protection from catastrophic health expenditure under the current health insurance system in Kenya. The absence of Universal Health Coverage (UHC) and the considerable costs associated with accessing health care often drain household resources. This has predisposed an estimated 1 to 1.1 million individuals (not only from lower income groups but also those with middle and higher income) to a high risk of being pushed or trapped into poverty (Salari et al., 2019).

References:

International Bank for Reconstruction and Development/The World Bank. (2018). Fiscal Incidence Analysis for Kenya: Using the Kenya Integrated Household Budget Survey 2015/16. Washington, DC. https://openknowledge.worldbank.org/bitstream/handle/10986/30263/Kenya-Fiscal-Incidence-Analysis.pdf?sequence=1&isAllowed=y

Salari, P., Di Giorgio, L., Ilinca, S., & Chuma, J. (2019). The catastrophic and impoverishing effects of out-of-pocket healthcare payments in Kenya, 2018. BMJ Global Health, 4(6). https://doi.org/10.1136/bmjgh-2019-001809

Shifa, M., & Leibbrandt, M. (2017). Urban Poverty and Inequality in Kenya. Urban Forum, 28(4), 363–385. http://doi.org/10.1007/s12132-017-9317-0

World Bank Group. (2018). 17th Edition of the Kenya Economic Update: Policy Options to Advance the Big 4 – Unleashing Kenya’s Private Sector to Drive Inclusive Growth and Accelerate Poverty Reduction. Nairobi, Kenya. https://openknowledge.worldbank.org/handle/10986/29676

Mexico has a much higher level of income inequality than other OECD countries, with its Gini coefficient (0.45) exceeding by far the OECD average (0.37), but closer to the Latin American average (Lambert & Park, 2019). According to the International Monetary Fund, IMF, the main reasons why poverty rates remain high are the country’s meagre per capita growth rates and deficiencies in the planning and targeting of social policies. It has also been noted that, while conditional cash transfer programs have been very effective at reducing inequality, other social programs have disproportionately benefited individuals at the top rather than at the bottom of the income distribution (Lambert & Park, 2019).

Regardless of continuing poverty alleviation strategies and other social programmes, income is highly concentrated, and the latest report of the National Council for the Evaluation of Social Policy, CONEVAL 2016, estimated that 7.6% of the Mexican population live in extreme poverty and 36% live in moderate poverty[1] (CONEVAL, 2018). Since 2009, the Mexican government has measured poverty using a multidimensional index of social deprivation (CONEVAL, 2018). The index has shown differential rates according to its subcomponents, such as access to education, social security, and access to health services, among others.

Regarding gender equality, there has been important progress since the year 2001 when President Vicente Fox created the National Institute for Women as an independent body within the federal government to coordinate compliance with national policy regarding equality and the eradication of violence against women. The institute is in charge of guaranteeing equal development and rights between men and women, through the development of public policies and other mechanisms such as media campaigns and publications. This institute also works with the legislative branch and the executive at federal and state level to follow up on the implementation and supervision of gender equality law. In addition, fundamental steps have been taken through the passing of legislation focused on eliminating discrimination and inequalities[2].

However, important challenges remain. A study in 2016 showed that, among those in paid work, women’s wages were, on average, between 17% and 47% lower than men’s. There were differences according to the state where they lived in and a wider difference by type of occupation. While the wage divide decreases as educational attainment increases, the wage divide between men and women prevails. Among those with no formal education, women’s wages are almost half of men’s, with a total difference of -50% and -33% for those with a college or university degree. In addition, among the population aged 15 years and older, 28% of women report having no own income, that is, they depend on others to subsist. Among men in this same age group, only 6% find themselves in this position, showing another facet of income inequality by gender in the country (INMUJERES, 2016).

Regarding general health inequalities, inequality in financial protection related to socioeconomic status has decreased significantly in parallel with the general decrease in the lack of financial protection. On the other hand, large inequality persists in indicators of access to health services and health indicators, both by socioeconomic status and by other social indicators (Gutierrez et al., 2014).

[1] The National Council for the Evaluation of Social Policy generates a Social Deprivation Index taking into account the following factors: educational lagging, access to health services, access to social security, space and quality of the household, basic services and access to food. Extreme poverty includes individuals that presents deprivation or lacks three or more of these factors, while moderate poverty includes those lacking two factors.

[2] Specifically, the General Law for Equality among Women and Men (Ley General para la Igualdad entre Mujeres y Hombres), a National Norm for Labour Equality and No Discrimination (Norma Mexicana NMX-R-025-SCFI-2015 en Igualdad Laboral y No Discriminación) generated as a collaboration between INMUJERES, the Labour and Social Prevision Secretariat (STPS), and the National Center for the Prevention of all Discrimination (CONAPRED), and a General Law for a Life Free of Violence for Women (Ley General de Acceso de las Mujeres a una Vida Libre de Violencia). Within the federal administration, mainstreaming of gender issues and gender equality has been the focus of many efforts in the last presidential terms.

References:

CONEVAL. (2018). Diez años de medición de pobreza multidimensional en México: avances y desafíos en política social. https://www.coneval.org.mx/Medicion/MP/Paginas/Pobreza-2018.aspx

Gutiérrez, J. P., García-Saisó, S., Dolci, G. F., & Ávila, M. H. (2014). Effective access to health care in Mexico. BMC Health Services Research, 14(1). https://doi.org/10.1186/1472-6963-14-186

INMUJERES. (2016). Brecha salarial de género en México. http://www.imf-formacion.com/blog/corporativo/igualdad-2/brecha-salarial-de-genero/

Lambert F, & Park H. (2019). Income Inequality and Government Transfers in Mexico.

Gini Coefficient

The Gini Coefficient is a measure of income inequality, with a score of 100 indicating complete inequality (one household has all the income) and a score of 0 indicating complete equality (all households have the same income). New Zealand has a Gini index of 33, sitting in the top third of most unequal countries and higher than the OECD median of 31 (Statistics NZ, n.d.). The index increased significantly in the 1990s but has plateaued since then in the low 30s (Statistics NZ, n.d.).

Gender inequality

The average gender pay gap in 2019 was 9.3% and, whilst lower than the 16.2% reported in 1998, has plateaued at this level since 2017 (Statistics NZ, 2019). However, this gap varies by occupation, from 7.1% for clerical/administrative workers to 16.7% for professionals.

These differences are further magnified when looking at Māori and Pacific populations, who earn between 15-26% less than Europeans (Table 14) as a population or when compared by gender (The Treasury, 2018). Whilst variables such as age, occupation, and highest qualification explain some of these differences they only account for ~40% of the variance, indicating at least some of the remaining variance may be due to discrimination (The Treasury, 2018).

 Table 14: Average wage by ethnicity and gender and their ratio to the European wage (The Treasury, 2018)

Total $ Male $ Female $ Total wage as a percentage of European wage Male wage as a percentage of European male wage Female wage as a percentage of European female wage
European 30.09 32.61 27.55
Maori 24.72 26.02 23.53 82.2 79.8 85.0
Pacific 22.96 24.13 21.71 76.3 74.0 78.8

 

Regional disparities 

Table 15 details the OECD wellbeing indicators for the regions in NZ. Regional disparities in health outcomes in New Zealand are the second largest among OECD countries, with Auckland ranking in the top 20% of OECD regions and Gisborne in the bottom 20%. The low performing regions in New Zealand fare better than the OECD median region in six out of the 13 well-being indicators but fall below the OECD median in life expectancy, mortality rate, unemployment rate, homicide rate, disposable income per capita, broadband access and share of labour force with at least a secondary degree (OECD, 2019; n.d.).

Table 15: OECD wellbeing indicators for NZ regions 2018.

Region Education Jobs Income Safety Health Environment Civic engagement Accessiblity to services Housing Community Life satisfaction
Score [0-10] Score [0-10] Score [0-10] Score [0-10] Score [0-10] Score [0-10] Score [0-10] Score [0-10] Score [0-10] Score [0-10] Score [0-10]
Northland 1.9 5.9 2.7 9.0 5.9 10.0 6.7 3.9 7.8 8.4 8.9
Auckland 5.3 7.7 4.5 8.9 8.8 9.0 6.9 7.1 6.1 8.7 7.8
Waikato 3.3 8.2 3.5 9.4 7.5 9.7 7.4 5.7 7.8 9.8 7.8
Bay of Plenty 2.7 8.4 3.4 9.6 7.5 10.0 8.1 5.3 7.8 9.3 8.1
Gisborne 2.5 7.7 3.1 7.9 2.0 10.0 8.2 5.2 7.2 9.8 8.5
Hawke’s Bay 2.5 7.7 3.1 10.0 6.8 9.3 8.2 5.2 7.8 8.5 8.5
Taranaki 2.2 8.5 3.8 9.4 6.5 9.9 8.0 5.3 8.3 10.0 8.1
Manawatu-Wanganui 2.9 8.0 3.1 10.0 5.4 10.0 8.2 4.8 8.3 9.2 7.4
Wellington 5.6 8.8 4.9 9.8 7.8 9.6 8.6 7.1 7.2 8.6 7.4
Tasman-Nelson-Marl. 3.3 8.9 3.3 10.0 7.0 10.0 8.6 6.3 7.8 9.3 8.5
West Coast 3.3 8.9 3.3 10.0 3.3 10.0 8.4 6.3 6.7 8.7 9.3
Canterbury 3.8 9.6 3.9 9.4 8.0 8.5 8.2 6.3 7.8 9.8 7.8
Otago 4.0 8.8 3.3 8.8 7.5 9.6 8.4 6.0 6.7 9.4 9.6
Southland 1.6 9.3 3.2 10.0 5.6 9.5 7.9 6.5 7.8 9.9 8.5

 

Regional inequality is also highlighted by the NZ index of deprivation (NZDep). NZDep is a scale of deprivation derived from variables in the census including income, employment, living conditions and qualifications. It is a scale from 1 (least deprived) to 10 (most deprived) for defined geographical areas of NZ (Atkinson et al., 2019). This means areas with a NZDep score of 10 are in the most deprived 10% areas of NZ. For example, Northland and the East Cape are highlighted as areas with high deprivation.

Māori and Pacific people are overrepresented in deciles with higher deprivation when compared those of NZ European and Asian ethnicities as highlighted when comparing Māori to non-Māori across deciles or NZDep2013 and the population distribution across deprivation scores by ethnicity.

Table 16 describes child poverty statistics in New Zealand in 2019 using 3 different measures (Statistics NZ, 2020). Regardless of which measure is used, Māori, and Pacific people are more affected when compared to Europeans. While 13.4% of children in NZ live in households experiencing material hardship, this differentially affects Māori (23.3%) and Pacific (28.6%) children when compared to Europeans (9.8%).

Table 16: Child poverty statistics for the year ended June 2019 (Statistics NZ, 2020)

Percentage of children living in households with less than 50 percent of the median equivalised disposable household income before housing costs are deducted Percentage of children living in households with less than 50 percent of the median equivalised disposable household income after housing costs are deducted (for the 2017/18 base financial year) Percentage of children living in households that experienced material hardship
European 11.0
(80,300 children)
17.0
(124,300 children)
9.8
(72,700 children)
Māori 19.6
(55,000 children)
24.7
(69,100 children)
23.3
(64,200 children)
Pacific Peoples 21.2
(30,200 children)
24.7
(35,000 children)
28.6
(40,600 children)
Total population 14.9
(168,500 children)
20.8
(235,400 children)
13.4
(151,700 children)

 

References:

Atkinson, J., Salmond, C., Crampton, P. (2019). NZDep2018 Index of Deprivation. Interim Research Report, December 2019. University of Otago, Wellington. Available from: https://www.otago.ac.nz/wellington/otago730394.pdf.

Ministry of Health. (2018). Ngā awe o te hauora: Socioeconomic determinants of health. Available from: https://www.health.govt.nz/our-work/populations/maori-health/tatau-kahukura-maori-health-statistics/nga-awe-o-te-hauora-socioeconomic-determinants-health/neighbourhood-deprivation.

OECD. (2019). Regions and Cities at a Glance 2018 – NEW ZEALAND. Available from: https://www.oecd.org/regional/NEW%20ZEALAND-Regions-and-Cities-2018.pdf.

OECD. (n.d.). OECD Regional Wellbeing: Auckland. Available from: https://www.oecdregionalwellbeing.org/NZ12.html.

Statistics NZ. (2019). Gender pay gap unchanged since 2017. New Zealand Government Website. Available from: https://www.stats.govt.nz/news/gender-pay-gap-unchanged-since-2017.

Statistics NZ. (2020). Child poverty statistics: Year ended June 2019. New Zealand Government Website. Available from: https://www.stats.govt.nz/information-releases/child-poverty-statistics-year-ended-june-2019.

Statistics NZ. (n.d.). Income inequality. New Zealand Government Website.

The Treasury. (2018). Statistical Analysis of Ethnic Wage Gaps in New Zealand (AP 18/03). Available from: https://treasury.govt.nz/publications/ap/ap-18-03-html#section-5.

South Africa faces a ‘triple challenge’ of high poverty, inequality, and unemployment and it has been identified as one of the world’s most unequal countries in the world (The World Bank, 2018a). The Living Conditions Survey (2014/15) found that the country’s Gini coefficient increased at the end of Apartheid (i.e., 0.61 in 1996) to 0.63 in 2015 as one of the highest in the world[1] (The World Bank, 2018a).

South Africa sees a polarisation of its employment market and is divided into two extreme job types: on the one end of the spectrum there is a small number of people with high earning jobs which once obtained, they are unlikely to give up and the other extreme where the majority of the population work at low earning jobs – the latter being more fluid and witnessing exits from employment (The World Bank, 2018a). The National Minimum Wage (NMW) was set at ZAR3500 per month across all sectors from May 2018 (with domestic and agriculture minimums set at 75 and 90% respectively (The World Bank, 2018a). Race and gender statistical trends remain biased where African and female workers on average earn significantly less than male and white workers (The World Bank, 2018a). Despite a notable decline in the observed gender inequality after 2011 (The World Bank, 2018a), the average gender pay gap in South Africa is reported at 28.6% in the Global Wage Report for the year 2018/19 (i.e., where women earn an average of 28.6% less than men for the same job). Women are generally earning less in South Africa leading to female-headed households being 10% more likely to become impoverished (and 2% less likely to escape it) than households headed by their male-counterparts (The World Bank, 2018a). Women still comprise less than 50% of positions of influence, for example 32% of Supreme Court of Appeal judges, 31% of advocates, 30% of ambassadors and 24% of Heads of State-owned enterprises (StatsSA, 2018c). Less than a third (32%) of managers in South Africa are women, and tend to dominate the domestic worker, clerical and technician occupations (men dominating the rest) (StatsSA, 2018c). By 2017, senior level management (decision-making level) are over-represented by men who dominate in both the public (60.7%) and private (68.5%) sectors (SAHRC, 2017a). Top level management in both public and private sectors also continue to be overrepresented by men, where women comprise 32.6% of top positions in government and 21.6% in the private sector (Department of Labour, 2017).

The majority of South Africans live in poverty (76%), of which nearly half are considered chronically poor and living at the upper-bound national poverty line of ZAR 992 per person per month (The World Bank, 2018a). Middle class earners constitute 20% of the working population between 2008 and 2015 and are a comparably smaller proportion than in other countries (The World Bank, 2018a). South Africa has also seen an increase in its poverty rate from 36 to 40% between 2011 and 2015 (The World Bank, 2018a). Poverty has also ‘deepened’ during this period as well and shows a 2.4 point increase (i.e., 16.4 to 18.8%) when calculated at the US$1.9 a day poverty line. Female-headed households, black South Africans, the less educated, the unemployed and bigger families experience higher levels of poverty (The World Bank, 2018a).

Rural areas in South Africa have the highest concentration of poverty (60.3% in 2006 and 59.7% in 2015), for which the Eastern Cape, KwaZulu-Natal, and Limpopo are the three poorest provinces in the country (2006-2015) (The World Bank, 2018a).

[1] Gini coefficient: Numbers range from 0 to 1; the higher the number/closer to 1, the greater the degree of income inequality

References:

Department of Labour. (2017). Commission for Employment Equity Annual Report 2017-2018. Availabe from: https://www.abp.org.za/wp-content/uploads/2018/07/Commission-for-Employment-Equity-18th-Annual-Report.pdf

SAHRC. (2017a). RESEARCH BRIEF ON GENDER AND EQUALITY IN SOUTH AFRICA 2013 to 2017. Available from: https://www.sahrc.org.za/home/21/files/RESEARCH%20BRIEF%20ON%20GENDER%20AND%20EQUALITY%20IN%20SOUTH%20AFRICA%202013%20to%202017.pdf

StatsSA. (2018c). How do women fare in the South African labour market? Statistics South Africa. http://www.statssa.gov.za/?p=11375

The World Bank. (2018a). Overcoming Poverty and Inequality in South Africa:An Assessment of Drivers, Constraints and Opportunities. Available from: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/530481521735906534/overcoming-poverty-and-inequality-in-south-africa-an-assessment-of-drivers-constraints-and-opportunities