Johannesburg was the wealthiest city in Africa as of 2021. South Africa's biggest city held *** billion U.S. dollars in private wealth, while Cape Town followed with *** billion U.S. dollars. The country led the ranking of wealthiest nations in Africa. The wealth value referred to assets such as cash, properties, and business interests held by individuals living in each country, less liabilities. Moreover, government funds were excluded.

The price per square meter in a luxury apartment in Cape Town, South Africa, reached ***** U.S. dollars in 2018. It was double of the price measured in Umhlanga, also a city in South Africa, and second in the ranking. The index tracked the square meter price in selected prime apartments, measuring from *** to *** square meters, mainly in exclusive living complexes.

This statistic shows the top 5 African cities in 2014 by number of residing billionaires. In 2014, ** billionaires were living in Lagos, Nigeria.

About this dataset

Context

This list ranks the 1 cities in the Rich County, UT by South African population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by South African Population: This column displays the rank of city in the Rich County, UT by their South African population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• South African Population: The South African population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as South African. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Rich County South African Population: This tells us how much of the entire Rich County, UT South African population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

BackgroundDespite many interventions, Togo continues to have one of the highest rates of poverty and food insecurity in the sub-Saharan African region. Currently there is no systematic analysis of the factors associated with household food-insecurity in this country. This study aimed at exploring the factors associated with food insecurity in Togo.MethodsThis was a cross-sectional study that used data from five waves (2014 to 2018) of the Gallup World Poll (GWP) for Togo. Sample size included 4754 participants, aged 15 and above. Food insecurity was measured using the Food Insecurity Experience Scale (FIES) questionnaire as per the Food and Agricultural Organization (FAO) guidelines. Our outcome variable was food insecurity, categorized as: 1) food secure (FIES score = 0–3), moderately food insecure (FIES score = 4–6), and severely food insecure (FIES score = 7–8). We did descriptive and multinomial regressions to analyze data using Stata version 16.ResultsBetween 2014 and 2018, the percentage of severe food insecurity fluctuated—42.81% in 2014, 37.79% in 2015, 38.98% in 2016, 45.41% in 2017, and 33.84% in 2018. Whereas that of moderate food insecurity increased from 23.55% to 27.33% except for 2016 and 2017 where the percentage increased to 32.33% and 27.46% respectively. In the logistic regression analysis, we found that respondents with lower than elementary education had a higher relative risk ratio of moderate (RRR = 1.45,95%CI = 1.22–1.72) and severe (RRR = 1.72, 95%CI = 1.46–2.02) food insecurity compared to those with secondary and higher education. Rural respondents had higher RRR of severe food insecurity (RRR = 1.37, 95%CI = 1.16–1.62) compared to those who lived in the urban areas. Compared with those in the richest wealth quintile, respondents in the poorest wealth quintile had 2.21 times higher RRR of moderate (RRR = 2.21, 95%CI = 1.69–2.87) and 3.58 times higher RRR of severe (RRR = 3.58, 95%CI = 2.81–4.55) food insecurity.ConclusionAbout two-thirds of participants experienced some level of food insecurity in 2018. Lower levels of education, rural residency and poorer household wealth index areas were associated with a higher risk of food insecurity. National food security programs should focus on promoting education and improving socioeconomic condition of people especially in rural areas.

Seychelles had the largest Gross Domestic Product (GDP) per capita in Africa as of 2024. The value amounted to 21,630 U.S. dollars. Mauritius followed with around 12,330 U.S. dollars, whereas Gabon registered 8,840 U.S. dollars. GDP per capita is calculated by dividing a country’s GDP by its population, meaning that some of the largest economies are not ranked within the leading ten. Impact of COVID-19 on North Africa’s GDP When looking at the GDP growth rate in Africa in 2024, Libya had the largest estimated growth in Northern Africa, a value of 7.8 percent compared to the previous year. Niger and Senegal were at the top of the list with rates of 10.4 percent and 8.3 percent, respectively. During the COVID-19 pandemic, the impact on the economy was severe. The growth of the North African real GDP was estimated at minus 1.1 percent in 2020. However, estimations for 2022 looked much brighter, as it was set that the region would see a GDP growth of six percent, compared to four percent in 2021.
Contribution of Tourism Various countries in Africa are dependent on tourism, contributing to the economy. In 2023, travel and tourism were estimated to contribute 182.6 billion U.S. dollars, a clear increase from 96.5 in 2020 following COVID-19. As of 2024, South Africa, Mauritius, and Egypt led tourism in the continent according to the Travel & Tourism Development Index.

Abstract

South African policymakers are endeavouring to ensure that the poor have better access to financial services. However, a lack of understanding of the financial needs of poor households impedes a broad strategy to attend to this need. The Financial Diaries study addresses this knowledge gap by examining financial management in rural and urban households. The study is a year-long household survey based on fortnightly interviews in Diepsloot (Gauteng), Langa (Western Cape) and Lugangeni (Eastern Cape). In total, 160 households were involved in this pioneering study which promises to offer important insights into how poor people manage their money as well as the context in which poor people make financial decisions. The study paints a rich picture of the texture of financial markets in townships, highlighting the prevalence of informal financial products, the role of survivalist business and the contribution made by social grants. The Financial Diaries dataset includes highly detailed, daily cash flow data on income, expenditure and financial flows on both a household and individual basis.

Geographic coverage

Langa in Cape Town, Diepsloot in Johannesburg and Lugangeni, a rural village in the Eastern Cape.

Analysis unit

Households and individuals

Universe

The survey covered households in the three geographic areas.

Kind of data

Sample survey data

Sampling procedure

To create the sampling frame for the Financial Diaries, the researchers echoed the method used in the Rutherford (2002) and Ruthven (2002), a participatory wealth ranking (PWR). Within South Africa, the participatory wealth ranking method is used by the Small Enterprise Foundation (SEF), a prominent NGO microlender based in the rural Limpopo Province. Simanowitz (1999) compared the PWR method to the Visual Indicator of Poverty (VIP) and found that the VIP test was seen to be at best 70% consistent with the PWR tests. At times one third of the list of households that were defined as the poorest by the VIP test was actually some of the richest according to the PWR. The PWR method was also implicitly assessed in van der Ruit, May and Roberts (2001) by comparing it to the Principle Components Analysis (PCA) used by CGAP as a means to assess client poverty. They found that three quarters of those defined as poor by the PCA were also defined as poor by the PWR. We closely followed the SEF manual to conduct our wealth rankings, and consulted with SEF on adapting the method to urban areas.

The first step is to consult with community leaders and ask how they would divide their community. Within each type of areas, representative neighbourhoods of about 100 households each were randomly chosen. Townships in South Africa are organised by street - with each street or zone having its own street committee. The street committees are meant to know everyone on their street and to serve as stewards of all activity within the street. Each street committee in each area was invited to a central meeting and asked to map their area and give a roster of household names. Following the mapping, each area was visited and the maps and rosters were checked by going door to door with the street committee.

Two references groups were then selected from the street committee and senior members of the community with between four and eight people in each reference group. Each reference group was first asked to indicate how they define a poor household versus those that are well off. This discussion had a dual purpose. First, it relayed information about what each community believes is rich or poor. Second, it started the reference group thinking about which households belong under which heading.

Following this discussion, each reference group then ranked each household in the neighbourhood according to their perceived wealth. The SEF methodology of wealth ranking is de-normalised in that reference groups are invited to put households into as many different wealth piles as they feel in appropriate. Only households that are known by both reference groups were kept in the sample.

The SEF guidelines were used to assign a score to each household in a particular pile. The scores were created by dividing 100 by the number of piles multiplied by the level of the pile. This means that if the poorest pile was number 1, then every household in the pile was assigned a score of 100, representing 100% poverty. If the wealthiest pile was pile number 6, then every household in that pile received a score of 16.7 and every household in pile 5 received a score of 33.3. An average score for both reference groups was taken for the distribution.

One way of assessing how good the results are is to analyse how consistent the rankings were between the two reference groups. According to the SEF methodology, a result is consistent if the scores between the two reference groups have no more than a 25 points difference. A result is inconsistent if the difference between the scores is between 26 and 50 points while a result is unreliable is the difference between the scores is above 50 points. SEF uses both consistent and inconsistent rankings, as long as they use the average across two reference groups - this would mean that 91% of the sample could be used. However, because only used two reference groups were used, only the consistent household for the final sample selection was considered.

To test this further,the number of times that the reference groups put a household in the exact same category was counted. The extent of agreement at either end of the wealth spectrum between the two reference groups was also assessed. This result would be unbiased by how many categories the reference groups put households into.

Following the example used in India and Bangladesh, the sample was divided into three different wealth categories depending on the household's overall score. Making a distinction between three different categories of wealth allowed the following of a similar ranking of wealth to Bangladesh and India, but also it kept the sample from being over-stratified. A sample of 60 households each was then drawn randomly from each area. To draw the sample based on a proportion representation of each wealth ranking within the population would likely leave the sample lacking in wealthier households of some rankings to draw conclusions. Therefore the researchers drew equally from each ranking.

Mode of data collection

Face-to-face [f2f]

As of April 2025, South Africa's GDP was estimated at over 410 billion U.S. dollars, the highest in Africa. Egypt followed, with a GDP worth around 347 billion U.S. dollars, and ranked as the second-highest on the continent. Algeria ranked third, with nearly 269 billion U.S. dollars. These African economies are among some of the fastest-growing economies worldwide. Dependency on oil For some African countries, the oil industry represents an enormous source of income. In Nigeria, oil generates over five percent of the country’s GDP in the third quarter of 2023. However, economies such as the Libyan, Algerian, or Angolan are even much more dependent on the oil sector. In Libya, for instance, oil rents account for over 40 percent of the GDP. Indeed, Libya is one of the economies most dependent on oil worldwide. Similarly, oil represents for some of Africa’s largest economies a substantial source of export value. The giants do not make the ranking Most of Africa’s largest economies do not appear in the leading ten African countries for GDP per capita. The GDP per capita is calculated by dividing a country’s GDP by its population. Therefore, a populated country with a low total GDP will have a low GDP per capita, while a small rich nation has a high GDP per capita. For instance, South Africa has Africa’s highest GDP, but also counts the sixth-largest population, so wealth has to be divided into its big population. The GDP per capita also indicates how a country’s wealth reaches each of its citizens. In Africa, Seychelles has the greatest GDP per capita.

Sample distribution and comprehensive knowledge of HIV by background characteristics of the study population, India, NFHS-5, 2019−21.

As of June 2022, Nassef Sawiris, with a net worth of 7.3 billion U.S. dollars, is the richest man in Egypt, fourth richest in the African continent, and ranked 292 in the world. His sibling Naguib Sawiris ranked second, with a net worth of 3.4 billion U.S. dollars. Their father, Onsi Sawiris, who passed away in June 2021, founded Orascom Construction PLC, which he then passed on to his son Nassef. Four other Egyptian billionaires followed, with three of them belonging to the same family; Mansour. They have a combined net worth of 5.1 billion U.S. dollars. Furthermore, their family business, Mansour group, works in several industries, mainly the automotive industry. It is a General Motors dealer and owns several other franchises.

Orascom in the market since 1950

Born in a Coptic family in the South of Egypt (Upper Egypt), Onsi Sawiris started his construction career in 1950. Soon after, the president of Egypt, Gamal Abdel Nasser assumed power nationalizing the company 10 years later and preventing him from leaving the country for a few years. He was later allowed to leave for Libya returning in President Anwar Sadat’s time in office, establishing Orascom Onsi Sawiris & Co. In 1995, the company was transferred to his son Nassef. As of the fiscal year ending 2020, the total revenue of Orascom construction reached 3.37 billion U.S. dollars with an increment of 5.87 percent year-on-year.

Concentrated wealth in the continent

Among the 20 wealthiest individuals in the African continent, 14 were from Nigeria, Egypt, and South Africa. The wealthiest individual in Africa was the Nigerian Aliko Dangote of the Dangote Group. He was followed by Nicky Oppenheimer and his family and Johann Rupert and his family who were from South Africa. Nassef Sawiris, from Egypt, ranked fourth. This followed the same ranking in terms of the countries with the largest Gross Domestic Product (GDP) in the continent. Furthermore, by reviewing the overall private wealth in Africa, Johannesburg, Cape Town, Cairo, and Lagos rank among the cities with the highest private wealth.

19 of the 20 countries with the lowest estimated GDP per capita in the world in 2024 are located in Sub-Saharan Africa. South Sudan is believed to have a GDP per capita of just 351.02 U.S. dollars - for reference, Luxembourg has the highest GDP per capita in the world, at almost 130,000 U.S. dollars, which is around 400 times larger than that of Burundi (U.S. GDP per capita is over 250 times higher than Burundi's). Poverty in Sub-Saharan Africa Many parts of Sub-Saharan Africa have been among the most impoverished in the world for over a century, due to lacking nutritional and sanitation infrastructures, persistent conflict, and political instability. These issues are also being exacerbated by climate change, where African nations are some of the most vulnerable in the world, as well as the population boom that will place over the 21st century. Of course, the entire population of Sub-Saharan Africa does not live in poverty, and countries in the southern part of the continent, as well as oil-producing states around the Gulf of Guinea, do have some pockets of significant wealth (especially in urban areas). However, while GDP per capita may be higher in these countries, wealth distribution is often very skewed, and GDP per capita figures are not representative of average living standards across the population. Outside of Africa Yemen is the only country outside of Africa to feature on the list, due to decades of civil war and instability. Yemen lags very far behind some of its neighboring Arab states, some of whom rank among the richest in the world due to their much larger energy sectors. Additionally, the IMF does not make estimates for Afghanistan, which would also likely feature on this list.

In 2024, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the overall poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States The poverty threshold for a single person in the United States was measured at an annual income of ****** U.S. dollars in 2023. Among families of four, the poverty line increases to ****** U.S. dollars a year. Women and children are more likely to suffer from poverty. This is due to the fact that women are more likely than men to stay at home, to care for children. Furthermore, the gender-based wage gap impacts women's earning potential. Poverty data Despite being one of the wealthiest nations in the world, the United States has some of the highest poverty rates among OECD countries. While, the United States poverty rate has fluctuated since 1990, it has trended downwards since 2014. Similarly, the average median household income in the U.S. has mostly increased over the past decade, except for the covid-19 pandemic period. Among U.S. states, Louisiana had the highest poverty rate, which stood at some ** percent in 2024.