In 2025, nearly 11.7 percent of the world population in extreme poverty, with the poverty threshold at 2.15 U.S. dollars a day, lived in Nigeria. Moreover, the Democratic Republic of the Congo accounted for around 11.7 percent of the global population in extreme poverty. Other African nations with a large poor population were Tanzania, Mozambique, and Madagascar. Poverty levels remain high despite the forecast decline Poverty is a widespread issue across Africa. Around 429 million people on the continent were living below the extreme poverty line of 2.15 U.S. dollars a day in 2024. Since the continent had approximately 1.4 billion inhabitants, roughly a third of Africa’s population was in extreme poverty that year. Mozambique, Malawi, Central African Republic, and Niger had Africa’s highest extreme poverty rates based on the 2.15 U.S. dollars per day extreme poverty indicator (updated from 1.90 U.S. dollars in September 2022). Although the levels of poverty on the continent are forecast to decrease in the coming years, Africa will remain the poorest region compared to the rest of the world. Prevalence of poverty and malnutrition across Africa Multiple factors are linked to increased poverty. Regions with critical situations of employment, education, health, nutrition, war, and conflict usually have larger poor populations. Consequently, poverty tends to be more prevalent in least-developed and developing countries worldwide. For similar reasons, rural households also face higher poverty levels. In 2024, the extreme poverty rate in Africa stood at around 45 percent among the rural population, compared to seven percent in urban areas. Together with poverty, malnutrition is also widespread in Africa. Limited access to food leads to low health conditions, increasing the poverty risk. At the same time, poverty can determine inadequate nutrition. Almost 38.3 percent of the global undernourished population lived in Africa in 2022.

DATASET: Alpha version 2008 estimates of proportion of people per grid square living in poverty, as defined by the Multidimensional Poverty Index (http://www.ophi.org.uk/policy/multidimensional-poverty-index/), and associated uncertainty metrics. REGION: Africa SPATIAL RESOLUTION: 0.00833333 decimal degrees (approx 1km at the equator) PROJECTION: Geographic, WGS84 UNITS: Proportion of residents living in MPI-defined poverty (poverty dataset); 95% credible interval (uncertainty dataset) MAPPING APPROACH: Bayesian model-based geostatistics in combination with high resolution gridded spatial covariates applied to GPS-located household survey data on poverty from the DHS and/or LSMS programs. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Examples - ken08povmpi.tif = Kenya (ken) MPI poverty map for 2008. ken08povmpi-uncert.tif = uncertainty dataset showing 95% credible intervals. DATE OF PRODUCTION: January 2013 CITATION: Tatem AJ, Gething PW, Bhatt S, Weiss D and Pezzulo C (2013) Pilot high resolution poverty maps, University of Southampton/Oxford.

Poverty prevalence (percent) and density (number per square km) at $1.25/day and $2.00/day for select countries in Africa south of the Sahara (SSA). The value $1.25/day represents extreme poverty and $2.00/day represents moderate poverty but when mapped also includes the extremely poor. All $ values are expressed in terms of average 2005 purchasing power parity rates.

Overlaying the number of marginality dimensions with percentage of people living below 1.25$/day. This map is included in a global study on mapping marginality focusing on Sub-Saharan Africa and South Asia. The Dimensions of Marginality are based on different data sources representing different spheres of life. The poverty dataset used in this study is based on calculations by Harvest Choice. The underlying Marginality map is based on the approach on Marginality Mapping (http://www.zef.de/fileadmin/webfiles/downloads/zef_wp/wp88.pdf). The respective map can be found here: https://daten.zef.de/#/metadata/ae4ae68c-cea3-44e7-8199-1c2ae04abb88 Quality/Lineage: Poverty Data was provided and generated by Harvest Choice GIS lab. Marginality hotspots are based on the approach by Graw, V. using five dimensions of marginality. In ArcGIS thresholds were defined based on percentages and overlapping dimensions. Using raster data this data was reclassified and overlayed to build a new classification with regard to the here presented purpose. This approach is similar to the overlap over marginality and poverty mass except this map shows percentage of poverty instead of number of poor people. Purpose: This map was created in the MARGIP project to identify the marginalized and poor by highlighting those areas where the "spheres of life" have a low performance. Those areas where multiple "low performance indicators" did overlap got the highest attention for further research.

South Africa ZA: Income Share Held by Third 20% data was reported at 8.200 % in 2014. This records an increase from the previous number of 8.000 % for 2010. South Africa ZA: Income Share Held by Third 20% data is updated yearly, averaging 8.200 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 9.900 % in 2000 and a record low of 7.500 % in 2005. South Africa ZA: Income Share Held by Third 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

South Africa ZA: Income Share Held by Highest 20% data was reported at 68.200 % in 2014. This records a decrease from the previous number of 68.900 % for 2010. South Africa ZA: Income Share Held by Highest 20% data is updated yearly, averaging 68.200 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 71.000 % in 2005 and a record low of 62.700 % in 2000. South Africa ZA: Income Share Held by Highest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

South Africa ZA: Income Share Held by Lowest 10% data was reported at 0.900 % in 2014. This stayed constant from the previous number of 0.900 % for 2010. South Africa ZA: Income Share Held by Lowest 10% data is updated yearly, averaging 1.000 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 1.300 % in 2000 and a record low of 0.900 % in 2014. South Africa ZA: Income Share Held by Lowest 10% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

South Africa ZA: Income Share Held by Lowest 20% data was reported at 2.400 % in 2014. This records a decrease from the previous number of 2.500 % for 2010. South Africa ZA: Income Share Held by Lowest 20% data is updated yearly, averaging 2.600 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 3.100 % in 2000 and a record low of 2.400 % in 2014. South Africa ZA: Income Share Held by Lowest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

South Africa ZA: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 55.500 % in 2014. This records an increase from the previous number of 53.200 % for 2010. South Africa ZA: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 58.800 % from Dec 2005 (Median) to 2014, with 4 observations. The data reached an all-time high of 66.600 % in 2005 and a record low of 53.200 % in 2010. South Africa ZA: Poverty Headcount Ratio at National Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Poverty. National poverty headcount ratio is the percentage of the population living below the national poverty lines. National estimates are based on population-weighted subgroup estimates from household surveys.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

This study employs a balanced panel dataset comprising 46 Sub-Saharan African countries over the period 2000 to 2023 to examine the role of institutional quality in addressing energy poverty and promoting inclusive development. The dataset includes both constructed and directly sourced variables. The dependent variable, Inclusive Development Index (IDI), is a composite indicator developed using min-max normalization from measures of income, health, and education, sourced primarily from the UNDP and World Bank. Key explanatory variables include energy poverty (ENPO), measured as the percentage of the population without access to electricity, and institutional quality (INSTQ), computed as the average of six World Governance Indicators (voice and accountability, political stability, government effectiveness, regulatory quality, rule of law, and control of corruption). The dataset also includes interaction terms such as INSTQENPO to assess moderating effects. Control variables include foreign direct investment (FDI) and gross fixed capital formation (GFCF), both measured as a percentage of GDP, as well as population growth (POPG) and urban population share (URBP), sourced from the World Development Indicators. The dataset was cleaned, normalized, and structured for panel econometric analysis using Eviews 10 and is suitable for replication and further policy-oriented research on energy-institution-development dynamics in the region.

Distribution of County Governments’ equitable revenue share allocation for FY 2018/19 is based on the current formula, which uses six parameters with specific weights: population (45 percent); basic equal share (26 percent); poverty (18 percent); land area (8 percent); fiscal responsibility (2 percent) and development factor (1 percent).

South Africa ZA: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 23.500 % in 2014. This stayed constant from the previous number of 23.500 % for 2010. South Africa ZA: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 23.500 % from Dec 1993 (Median) to 2014, with 6 observations. The data reached an all-time high of 25.500 % in 2000 and a record low of 20.300 % in 2005. South Africa ZA: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

South Africa ZA: Income Share Held by Highest 10% data was reported at 50.500 % in 2014. This records a decrease from the previous number of 51.300 % for 2010. South Africa ZA: Income Share Held by Highest 10% data is updated yearly, averaging 50.500 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 54.200 % in 2005 and a record low of 44.900 % in 2000. South Africa ZA: Income Share Held by Highest 10% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Elasticity of poverty concerning foreign aid and remittances (random effect).

South Africa ZA: Income Share Held by Second 20% data was reported at 4.800 % in 2014. This records an increase from the previous number of 4.700 % for 2010. South Africa ZA: Income Share Held by Second 20% data is updated yearly, averaging 4.900 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 5.600 % in 2000 and a record low of 4.700 % in 2010. South Africa ZA: Income Share Held by Second 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

The focus of this study is the implications of structural transformation for gender equality, specifically equal pay, in Sub-Saharan Africa. While structural transformation affects key development outcomes, including growth, poverty, and access to decent work, its effect on the gender pay gap is not clear ex-ante. Evidence on the gender pay gap in sub-Saharan Africa is limited, and often excludes rural areas and informal (self-)employment. This paper provides evidence on the extent and drivers of the gender pay gap in non-farm wage- and self-employment activities across three countries at different stages of structural transformation (Malawi, Tanzania and Nigeria). The analysis leverages nationally-representative survey data and decomposition methods, and is conducted separately among individuals residing in rural versus urban areas in each country. The results show that women earn 40 to 46 percent less than men in urban areas, which is substantially less than in high-income countries. The gender pay gap in rural areas ranges from (a statistically insignificant) 12 percent in Tanzania to 77 percent in Nigeria. In all rural areas, a major share of the gender pay gap (81 percent in Malawi, 83 percent in Tanzania and 70 percent in Nigeria) is explained by differences in workers’ characteristics, including education, occupation and sector. This suggests that if rural men and women had similar characteristics, most of the gender pay gap would disappear. Country-differences are larger across urban areas, where differences in characteristics account for only 32 percent of the pay gap in Tanzania, 50 percent in Malawi and 81 percent in Nigeria. Our detailed decomposition results suggest that structural transformation does not consistently help bridge the gender pay gap. Gender-sensitive policies are required to ensure equal pay for men and women.

South Africa ZA: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 37.600 % in 2014. This records an increase from the previous number of 35.800 % for 2010. South Africa ZA: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 47.800 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 53.900 % in 1996 and a record low of 35.800 % in 2010. South Africa ZA: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Poverty. Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Dynamic panel estimates using a system-GMM approach.

South Africa ZA: Income Share Held by Fourth 20% data was reported at 16.500 % in 2014. This records an increase from the previous number of 15.900 % for 2010. South Africa ZA: Income Share Held by Fourth 20% data is updated yearly, averaging 16.500 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 18.800 % in 2000 and a record low of 14.200 % in 2005. South Africa ZA: Income Share Held by Fourth 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Central African Republic CF: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 43.000 % in 2021. This records a decrease from the previous number of 56.200 % for 2008. Central African Republic CF: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 56.200 % from Dec 1992 (Median) to 2021, with 3 observations. The data reached an all-time high of 61.300 % in 1992 and a record low of 43.000 % in 2021. Central African Republic CF: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Central African Republic – Table CF.World Bank.WDI: Social: Poverty and Inequality. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).